M/EEG+FMRI BIB

The successful use of functional magnetic resonance imaging (fMRI) as a way of visualizing cortical function depends largely on the important relationships between the signal observed and the underlying neuronal activity that it is believed to represent. Currently, a relatively direct correlation seems to be favoured between fMRI signals and population synaptic activity (including inhibitory and excitatory activity), with a secondary and potentially more variable correlation with cellular action potentials.

Keywords: Action Potentials/physiology ; Animals ; Cerebral Cortex/*physiology ; Cerebrovascular Circulation/*physiology ; Excitatory Postsynaptic Potentials/physiology ; Human ; *Magnetic Resonance Imaging ; Neural Inhibition/physiology ; Neurons/*physiology ; Support, Non-U.S. Gov't ; Synaptic Transmission/*physiology

The interpretation of task-induced functional imaging of the brain is critically dependent on understanding the relationship between observed haemodynamic responses and the underlying neural changes. However, the precise nature of this neurovascular coupling relationship remains unknown. In particular, it is unclear which measure of functional magnetic resonance imaging blood oxygen level dependent (fMRI BOLD) activity is the best correlate of neural activity. We measured the somatosensory evoked potential (SEP) amplitude at the scalp, and fMRI BOLD signal to increases in intensity of contralateral median nerve electrical stimulation in healthy non-anaesthetised subjects. We compared correlation analyses between SEP amplitude and both peak voxel fMRI BOLD percentage signal change and mean voxel fMRI BOLD percentage signal change across a somatosensory cluster, and we also performed a voxel-by-voxel correlation between fMRI BOLD activity and SEP amplitude. We found that fMRI BOLD changes in primary somatosensory cortex correlate significantly with SEP amplitudes, suggesting a linear neurovascular coupling relationship under the conditions investigated. We also found that mean changes across a cluster correlate less well with SEP amplitude than peak voxel levels. This suggests that the area of haemodynamic activity correlating with SEP amplitude is smaller than the entire cluster observed.

Keywords: Adult ; Brain Mapping ; Comparative Study ; Electric Stimulation ; Electrophysiology/*methods ; Evoked Potentials, Somatosensory/*physiology ; Female ; Hemodynamic Processes/physiology ; Human ; *Magnetic Resonance Imaging ; Male ; Nerve Net/physiology ; Oxygen/metabolism ; Somatosensory Cortex/*physiology ; Support, Non-U.S. Gov't

OBJECTIVE: To introduce a new technique for co-registration of Magnetoencephalography (MEG) with magnetic resonance imaging (MRI). We compare the accuracy of a new bite-bar with fixed fiducials to a previous technique whereby fiducial coils were attached proximal to landmarks on the skull. METHODS: A bite-bar with fixed fiducial coils is used to determine the position of the head in the MEG co-ordinate system. Co-registration is performed by a surface-matching technique. The advantage of fixing the coils is that the co-ordinate system is not based upon arbitrary and operator dependent fiducial points that are attached to landmarks (e.g. nasion and the preauricular points), but rather on those that are permanently fixed in relation to the skull. RESULTS: As a consequence of minimizing coil movement during digitization, errors in localization of the coils are significantly reduced, as shown by a randomization test. Displacement of the bite-bar caused by removal and repositioning between MEG recordings is minimal ( approximately 0.5 mm), and dipole localization accuracy of a somatosensory mapping paradigm shows a repeatability of approximately 5 mm. The overall accuracy of the new procedure is greatly improved compared to the previous technique. CONCLUSIONS: The test-retest reliability and accuracy of target localization with the new design is superior to techniques that incorporate anatomical-based fiducial points or coils placed on the circumference of the head.

Keywords: Brain/anatomy & histology ; Comparative Study ; Data Collection ; Equipment Design ; Head ; Human ; *Image Processing, Computer-Assisted ; *Magnetic Resonance Imaging ; *Magnetoencephalography ; Monte Carlo Method ; Posture ; Reproducibility of Results ; Stereotaxic Techniques/*instrumentation/standards

Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data is commonly carried out under the assumption that each source may be represented as a spatially fixed pattern of activation, which leads to the instantaneous mixing model. To allow modeling patterns of spatio-temporal dynamics, in particular, the flow of oxygenated blood, we have developed a convolutive ICA approach: spatial complex ICA applied to frequency-domain fMRI data. In several frequency-bands, we identify components pertaining to activity in primary visual cortex (V1) and blood supply vessels. One such component, obtained in the 0.10 Hz band, is analyzed in detail and found to likely reflect flow of oxygenated blood in V1.

The haemodynamic responses to neural activity that underlie the blood-oxygen-level-dependent (BOLD) signal used in functional magnetic resonance imaging (fMRI) of the brain are often assumed to be driven by energy use, particularly in presynaptic terminals or glia. However, recent work has suggested that most brain energy is used to power postsynaptic currents and action potentials rather than presynaptic or glial activity and, furthermore, that haemodynamic responses are driven by neurotransmitter-related signalling and not directly by the local energy needs of the brain. A firm understanding of the BOLD response will require investigation to be focussed on the neural signalling mechanisms controlling blood flow rather than on the locus of energy use.

Keywords: Action Potentials/physiology ; Astrocytes/physiology ; Brain/*blood supply/physiology ; Brain Mapping ; Cerebrovascular Circulation/*physiology ; Energy Metabolism/*physiology ; Human ; Magnetic Resonance Imaging ; Neural Inhibition/physiology ; Presynaptic Terminals/physiology ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.

Blood oxygenation dependent contrast (BOLD) fMRI is used increasingly to probe connectivity based on temporal correlations between signals from different brain regions. This approach assumes that there is constant local coupling of neuronal activity to the associated BOLD response. Here we test the alternative hypothesis that there is not a fixed relationship between these by determining whether attention modulates apparent neurovascular coupling. Electrical stimulation of the median nerve was applied with and without a concurrent distractor task (serial subtraction). Increasing stimulation intensity increased discomfort ratings ( p<0.001) and was associated with a significant increase in both somatosensory evoked potential (SEP) N20-P25 amplitude and BOLD fMRI response in the contralateral primary (SI) and bilaterally in the secondary somatosensory cortices. Attention to stimulation was reduced during distractor task performance and resulted in an overall trend for reduction in discomfort ( p=0.056), which was significant at the highest stimulation level ( p<0.05). A volume of interest analysis confined to SI confirmed a reduction in BOLD response with distraction ( p<0.001). However, distraction did not measurably affect SEP magnitude. The quantitative relationship between the BOLD fMRI response and the local field potential measured by the early SEP response therefore varies with attentional context. This may be a consequence of differences in either local spatial or temporal signal summation for the two methods. Either interpretation suggests caution in assuming a simple, fixed relationship between local BOLD changes and related electrophysiological activity.

Combined EEG/fMRI recording has been used to localize the generators of EEG events and to identify subject state in cognitive studies and is of increasing interest. However, the large EEG artifacts induced during fMRI have precluded simultaneous EEG and fMRI recording, restricting study design. Removing this artifact is difficult, as it normally exceeds EEG significantly and contains components in the EEG frequency range. We have developed a recording system and an artifact reduction method that reduce this artifact effectively. The recording system has large dynamic range to capture both low-amplitude EEG and large imaging artifact without distortion (resolution 2 microV, range 33.3 mV), 5-kHz sampling, and low-pass filtering prior to the main gain stage. Imaging artifact is reduced by subtracting an averaged artifact waveform, followed by adaptive noise cancellation to reduce any residual artifact. This method was validated in recordings from five subjects using periodic and continuous fMRI sequences. Spectral analysis revealed differences of only 10 to 18% between EEG recorded in the scanner without fMRI and the corrected EEG. Ninety-nine percent of spike waves (median 74 microV) added to the recordings were identified in the corrected EEG compared to 12% in the uncorrected EEG. The median noise after artifact reduction was 8 microV. All these measures indicate that most of the artifact was removed, with minimal EEG distortion. Using this recording system and artifact reduction method, we have demonstrated that simultaneous EEG/fMRI studies are for the first time possible, extending the scope of EEG/fMRI studies considerably.

Keywords: Adult ; Algorithms ; *Artifacts ; Electroencephalography/*methods/statistics & numerical data ; Female ; Human ; Image Processing, Computer-Assisted/*methods/statistics & numerical data ; Magnetic Resonance Imaging/*methods/statistics & numerical data ; Male ; Reproducibility of Results ; Signal Processing, Computer-Assisted

Ballistocardiogram and imaging artifacts cause major interference with simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) recording. In particular, the large amplitude of the imaging artifact precludes easy retrieval of EEG signals during fMRI scanning. Recording with 20,000-Hz digitization rate combined with 3000-Hz low-pass filter revealed the real waveform of the imaging artifact, in which it was elucidated that each artifact peak precisely corresponded to each gradient component and actually had differential waveforms of the original gradient pulses. Based on this finding, to retrieve EEG signal during fMRI acquisition, a blip-type echo planar sequence was modified so that EEG sampling might be performed at every 1000 micros (digitization rate 1000 Hz) exclusively in the period in which the artifact resided around the baseline level. This method, called stepping stone sampling, substantially attenuated the amplitude of the imaging artifact. The remnant of the artifact was subtracted from the averaged artifact waveform. In human studies, alpha activity was successfully retrieved by inspection, and its attenuation/augmentation was observed during eyes open/closed periods. Fast Fourier transform analysis further revealed that even from DC up to 120 Hz, retrieved EEG data during scanning had very similar power distributions to the data retrieved during no scanning, implying the availability of the high-frequency band of the retrieved EEG signals, including even the gamma band.

Keywords: Adult ; Alpha Rhythm ; *Artifacts ; Ballistocardiography/methods ; Brain Mapping/methods ; Cerebral Cortex/*physiology ; Echo-Planar Imaging/methods ; Electroencephalography/*methods ; Female ; Fourier Analysis ; Human ; Image Interpretation, Computer-Assisted/*methods ; Magnetic Resonance Imaging/*methods ; Male ; Phantoms, Imaging ; Reference Values ; Support, Non-U.S. Gov't

The purpose of this study was to investigate the changes in specific absorption rate (SAR) in human-head tissues while using nonmagnetic metallic electroencephalography (EEG) electrodes and leads during magnetic resonance imaging (MRI). A realistic, high resolution (1 mm(3)) head model from individual MRI data was adopted to describe accurately thin tissues, such as bone marrow and skin. The RF power dissipated in the human head was evaluated using the FDTD algorithm. Both surface and bird cage coils were used. The following numbers of EEG electrodes/leads were considered: 16, 31, 62, and 124. Simulations were performed at 128 and 300 MHz. The difference in SAR between the electrodes/leads and no-electrodes conditions was greater with the bird cage coil than with the surface coil. The peak 1 g averaged SAR values were highest at 124 electrodes, increasing to as much as two orders of magnitude (x172.3) at 300 MHz compared to the original value. At 300 MHz, there was a fourfold (x3.6) increase of SAR averaged over the bone marrow, and a sevenfold (x7.4) increase in the skin. At 128 MHz, there was a fivefold (x5.6) increase of whole head SAR. Head models were obtained from two different subjects, with an inter-subject whole head SAR variability of 3%. .

Keywords: Adult ; *Electrodes ; Electroencephalography/*instrumentation ; Human ; Magnetic Resonance Imaging/*instrumentation ; Male ; Support, Non-U.S. Gov't

Magneto- and electroencephalography (MEG/EEG) and functional magnetic resonance imaging (fMRI) provide complementary information about the functional organization of the human brain. An important advantage of MEG/EEG is the millisecond time resolution in detecting electrical activity in the cerebral cortex. The interpretation of MEG/EEG signals, however, is limited by the difficulty of determining the spatial distribution of the neural activity. Functional MRI can help in the MEG/EEG source analysis by suggesting likely locations of activity. We present a geometric interpretation of fMRI-guided inverse solutions in which the MEG/EEG source estimate minimizes a distance to a subspace defined by the fMRI data. In this subspace regularization (SSR) approach, the fMRI bias does not assume preferred amplitudes for MEG/EEG sources, only locations. Characteristic dependence of the source estimates on the regularization parameters is illustrated with simulations. When the fMRI locations match the true MEG/EEG source locations, they serve to bias the underdetermined MEG/EEG inverse solution toward the fMRI loci. Importantly, when the fMRI loci do not match the true MEG/EEG loci, the solution is insensitive to those fMRI loci.

A sudden change in the direction of motion is a particularly salient and relevant feature of visual information. Extensive research has identified cortical areas responsive to visual motion and characterized their sensitivity to different features of motion, such as directional specificity. However, relatively little is known about responses to sudden changes in direction. Electrophysiological data from animals and functional imaging data from humans suggest a number of brain areas responsive to motion, presumably working as a network. Temporal patterns of activity allow the same network to process information in different ways. The present study in humans sought to determine which motion-sensitive areas are involved in processing changes in the direction of motion and to characterize the temporal patterns of processing within this network of brain regions. To accomplish this, we used both magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI). The fMRI data were used as supplementary information in the localization of MEG sources. The change in the direction of visual motion was found to activate a number of areas, each displaying a different temporal behavior. The fMRI revealed motion-related activity in areas MT+ (the human homologue of monkey middle temporal area and possibly also other motion sensitive areas next to MT), a region near the posterior end of the superior temporal sulcus (pSTS), V3A, and V1/V2. The MEG data suggested additional frontal sources. An equivalent dipole model for the generators of MEG signals indicated activity in MT+, starting at 130 ms and peaking at 170 ms after the reversal of the direction of motion, and then again at approximately 260 ms. Frontal activity began 0-20 ms later than in MT+, and peaked approximately 180 ms. Both pSTS and FEF+ showed long-duration activity continuing over the latency range of 200-400 ms. MEG responses in the region of V3A and V1/V2 were relatively small, and peaked at longer latencies than the initial peak in MT+. These data revealed characteristic patterns of activity in this cortical network for processing sudden changes in the direction of visual motion.

Keywords: Adult ; *Brain Mapping ; Cerebral Cortex/*physiology ; *Evoked Potentials, Visual ; Human ; Magnetic Resonance Imaging/*methods ; Magnetoencephalography/*methods ; Male ; Middle Aged ; Motion Perception/*physiology ; Nerve Net/physiology ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.

Cerebral hemodynamic responses to brief periods of neural activity are delayed and dispersed in time. The specific shape of these responses is of some importance to the design and analysis of blood oxygenation level-dependent (BOLD), functional magnetic resonance imaging (fMRI) experiments. Using fMRI scanning, we examine here the characteristics and variability of hemodynamic responses from the central sulcus in human subjects during an event-related, simple reaction time task. Specifically, we determine the contribution of subject, day, and scanning session (within a day) to variability in the shape of evoked hemodynamic response. We find that while there is significant and substantial variability in the shape of responses collected across subjects, responses collected during multiple scans within a single subject are less variable. The results are discussed in terms of the impact of response variability upon sensitivity and specificity of analyses of event-related fMRI designs.

Keywords: Adult ; Brain/anatomy & histology ; Cerebrovascular Circulation/*physiology ; Female ; Hemodynamic Processes/*physiology ; Human ; Image Processing, Computer-Assisted/*methods ; Magnetic Resonance Imaging ; Male ; Models, Neurological ; Oxygen/*blood ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.

Combined EEG-fMRI has recently been used to explore the BOLD responses to interictal epileptiform discharges. This study examines whether misspecification of the form of the haemodynamic response function (HRF) results in significant fMRI responses being missed in the statistical analysis. EEG-fMRI data from 31 patients with focal epilepsy were analysed with four HRFs peaking from 3 to 9 sec after each interictal event, in addition to a standard HRF that peaked after 5.4 sec. In four patients, fMRI responses were correlated with gadolinium-enhanced MR angiograms and with EEG data from intracranial electrodes. In an attempt to understand the absence of BOLD responses in a significant group of patients, the degree of signal loss occurring as a result of magnetic field inhomogeneities was compared with the detected fMRI responses in ten patients with temporal lobe spikes. Using multiple HRFs resulted in an increased percentage of data sets with significant fMRI activations, from 45% when using the standard HRF alone, to 62.5%. The standard HRF was good at detecting positive BOLD responses, but less appropriate for negative BOLD responses, the majority of which were more accurately modelled by an HRF that peaked later than the standard. Co-registration of statistical maps with gadolinium-enhanced MRIs suggested that the detected fMRI responses were not in general related to large veins. Signal loss in the temporal lobes seemed to be an important factor in 7 of 12 patients who did not show fMRI activations with any of the HRFs.

We describe two new methods for the inverse problem of electrocardiography. Both employ regularization with multiple constraints, rather than the standard single-constraint regularization. In one method, multiple constraints on the spatial behavior of the solution are used simultaneously. In the other, spatial constraints are used simultaneously with constraints on the temporal behavior of the solution. The specific cases of two spatial constraints and one spatial and one temporal constraint are considered in detail. A new method, the L-Surface, is presented to guide the choice of the required pairs of regularization parameters. In the case when both spatial and temporal regularization are used simultaneously, there is an increased computational burden, and two methods are presented to compute solutions efficiently. The methods are verified by simulations using both dipole sources and measured canine epicardial data.

Keywords: Animals ; Dogs ; Electrocardiography/*methods ; Mathematics ; *Models, Cardiovascular ; *Signal Processing, Computer-Assisted ; Support, U.S. Gov't, Non-P.H.S.

A novel method based on selective detection of rapidly changing DeltaB(0) magnetic fields and suppression of slowly changing DeltaB(0) fields is presented. The ultimate goal of this work is to present a method that may allow detection of transient and subtle changes in B(0) in cortical tissue associated with electrical currents produced by neuronal activity. The method involves the detection of NMR phase changes that occur during a single-shot spin-echo (SE) echo-planar sequence (EPI) echo time. SE EPI effectively rephases all changes in B(0) that occur on a time scale longer than the echo time (TE) and amplifies all DeltaB(0) changes that occur during TE/2. The method was tested on a phantom that contains wires in which current can be modulated. The sensitivity and flexibility of the technique was demonstrated by modulation of the temporal position and duration of the stimuli-evoked transient magnetic field relative to the 180 RF pulse in the imaging sequence-requiring precise stimulus timing. Currently, with this method magnetic field changes as small as 2 x 10(-10) T (200 pT) and lasting for 40 msec can be detected. Implications for direct mapping of brain neuronal activity with MRI are discussed.

Keywords: Brain Mapping/*instrumentation/methods ; Electromagnetic Fields ; Human ; Image Processing, Computer-Assisted ; Magnetic Resonance Imaging/*methods ; Neurons/*physiology ; *Phantoms, Imaging

OBJECTIVES: In this paper, we employed advanced methods for the modeling of human cortical activity related to voluntary right one-digit movements from combined high-resolution electroencepholography (EEG) and functional magnetic resonance imaging (fMRI). METHODS: Multimodal integration between EEG and fMRI data was performed by using realistic head models, a large number of scalp electrodes (128) and the estimation of current density strengths by linear inverse estimation. RESULTS: Increasing of spatial details of the estimated cortical density distributions has been detected by using the proposed integration method with respect to the estimation using EEG data alone. CONCLUSION: The proposed method of multimodal EEG-fMRI data is useful to increase spatial resolution of movement-related potentials and can also be applied to other kinds of event-related potentials.

Keywords: Brain Mapping/methods ; Cerebral Cortex/*physiology ; Cortical Synchronization ; Electrodes ; Electroencephalography/*methods ; Human ; Magnetoencephalography/*methods ; Motor Activity/*physiology ; Nerve Net ; Signal Processing, Computer-Assisted ; *Systems Integration

Previous simulation studies have stressed the importance of the use of fMRI priors in the estimation of cortical current density. However, no systematic variations of signal-to-noise ratio (SNR) and number of electrodes were explicitly taken into account in the estimation process. In this simulation study we considered the utility of including information as estimated from fMRI. This was done by using as the dependent variable both the correlation coefficient and the relative error between the imposed and the estimated waveforms at the level of cortical region of interests (ROI). A realistic head and cortical surface model was used. Factors used in the simulations were the different values of SNR of the scalp-generated data, the different inverse operators used to estimated the cortical source activity, the strengths of the fMRI priors in the fMRI-based inverse operators, and the number of scalp electrodes used in the analysis. Analysis of variance results suggested that all the considered factors significantly afflict the correlation and the relative error between the estimated and the simulated cortical activity. For the ROIs analyzed with simulated fMRI hot spots, it was observed that the best estimation of cortical source currents was performed with the inverse operators that used fMRI information. When the ROIs analyzed do not present fMRI hot spots, both standard (i.e., minimum norm) and fMRI-based inverse operators returned statistically equivalent correlation and relative error values.

Keywords: Analysis of Variance ; Brain Mapping ; Cerebral Cortex/*physiology ; *Computer Simulation ; *Electroencephalography ; Electrophysiology ; Human ; *Magnetic Resonance Imaging ; *Models, Neurological

The widely used technique of functional magnetic resonance imaging (fMRI) based on the blood oxygenation level-dependent (BOLD) effect is a tool for the investigation of changes in local brain activity upon stimulation. The principle of measurement is based on the assumption that there is a strong coupling between changes in neural activity, metabolism, vascular response and oxygen extraction in the area under investigation. As fMRI is on the way to become a routine tool in clinical examinations, we wanted to investigate whether, generally and under a variety of conditions, there is a strong link between the BOLD signal and neural activity. For clinical and experimental application of the method, it is crucial, whether the absence of changes in BOLD signal intensity upon stimulation can always be interpreted as an absence of changes in brain activity. We approached this question by inhibiting the nitric oxide mediated 'neurovascular coupling' via application of 7 nitroindazole. Before and after inhibition of this neurovascular coupling, we acquired evoked potentials and performed fMRI during somatosensory stimulation in rats. Cerebral blood flow response as well as BOLD signal intensity changes following electrical stimulation were abolished within 10 min after application of 7 nitroindazole, whereas somatosensory-evoked potentials were only slightly affected but still clearly detectable. Even 1 h after injection of 7 nitroindazole, there was still remaining electrical activity. Thus, we observed an uncoupling between electrical, i.e., neural activity and the BOLD signal. According to our results, the absence of BOLD signal changes did not permit the conclusion that there was no neural activity in the area under investigation. Our findings are especially relevant for the clinical application of fMRI in patients suffering from cerebrovascular and other brain diseases.

Keywords: Animals ; Blood Gas Analysis ; Cerebrovascular Circulation/*physiology ; Evoked Potentials, Somatosensory/physiology ; Heart Rate ; Magnetic Resonance Imaging ; Male ; Neurons/*physiology ; Oxygen/*blood ; Rats ; Rats, Sprague-Dawley ; Somatosensory Cortex/blood supply/physiology

Nowadays, several types of brain imaging device are available to provide images of the functional activity of the cerebral cortex based on hemodynamic, metabolic, or electromagnetic measurements. However, static images of brain regions activated during particular tasks do not convey the information of how these regions communicate with each other. In this study, advanced methods for the estimation of cortical connectivity from combined high-resolution electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data are presented. These methods include a subject's multicompartment head model (scalp, skull, dura mater, cortex) constructed from individual magnetic resonance images, multidipole source model, and regularized linear inverse source estimates of cortical current density. Determination of the priors in the resolution of the linear inverse problem was performed with the use of information from the hemodynamic responses of the cortical areas as revealed by block-designed (strength of activated voxels) fMRI. We estimate functional cortical connectivity by computing the directed transfer function (DTF) on the estimated cortical current density waveforms in regions of interest (ROIs) on the modeled cortical mantle. The proposed method was able to unveil the direction of the information flow between the cortical regions of interest, as it is directional in nature. Furthermore, this method allows to detect changes in the time course of information flow between cortical regions in different frequency bands. The reliability of these techniques was further demonstrated by elaboration of high-resolution EEG and fMRI signals collected during visually triggered finger movements in four healthy subjects. Connectivity patterns estimated for this task reveal an involvement of right parietal and bilateral premotor and prefrontal cortical areas. This cortical region involvement resembles that revealed in previous studies where visually triggered finger movements were analyzed with the use of separate EEG or fMRI measurements.

Event-related fMRI (efMRI) has been repeatedly used to seek the neural sources of endogenous event-related potentials (ERP). However, significant discrepancies exist between the efMRI data and the results of previously published intracranial ERP studies of oddball task. To evaluate the capacity of efMRI to define the sources of the P3 component of ERP within the human brain, both efMRI and intracerebral ERP recordings were performed in eight patients with intractable epilepsy (five males and three females) during their preoperative invasive video-EEG monitoring. An identical auditory oddball task with frequent and target stimuli was completed in two sessions. A total of 606 intracerebral sites were electrophysiologically investigated by means of depth electrodes. In accordance with the finding of multiple intracerebral generators of P3 potential, the target stimuli evoked MRI signal increase in multiple brain regions. However, regions with evident hemodynamic and electrophysiological responses overlapped only partially. P3 generators were always found within hemodynamic-active sites, if these sites were investigated by means of depth electrodes. On the other hand, unequivocal local sources of P3 potential were apparently also located outside the regions with a significant hemodynamic response (typically in mesiotemporal regions). Both methods should thus be viewed as mutually complementary in investigations of the spatial distribution of cortical and subcortical activation during oddball task.

Keywords: Adult ; Auditory Cortex/physiology ; Auditory Perception/*physiology ; Brain/*physiology ; Cerebrovascular Circulation/physiology ; Electrodes, Implanted ; Electroencephalography ; Electrophysiology ; Epilepsy/physiopathology ; Evoked Potentials, Auditory/physiology ; Female ; Humans ; Magnetic Resonance Imaging ; Male ; Oxygen/blood ; Research Support, Non-U.S. Gov't

The linear transform model of functional magnetic resonance imaging (fMRI) hypothesizes that fMRI responses are proportional to local average neural activity averaged over a period of time. This work reports results from three empirical tests that support this hypothesis. First, fMRI responses in human primary visual cortex (V1) depend separably on stimulus timing and stimulus contrast. Second, responses to long-duration stimuli can be predicted from responses to shorter duration stimuli. Third, the noise in the fMRI data is independent of stimulus contrast and temporal period. Although these tests can not prove the correctness of the linear transform model, they might have been used to reject the model. Because the linear transform model is consistent with our data, we proceeded to estimate the temporal fMRI impulse-response function and the underlying (presumably neural) contrast-response function of human V1.

Keywords: Artifacts ; Human ; *Magnetic Resonance Imaging ; Models, Neurological ; Noise ; Photic Stimulation ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S. ; Time Factors ; Visual Cortex/*physiology

Keywords: ICP

The validity of functional magnetic resonance imaging (FMRI) brain maps with respect to the sites of neuronal activation is still unknown. One source of localization error may be pixels with large signal amplitudes, since such pixels may be expected to overlie large vessels, running remote from the centre of neuronal activation. In this study, magnetoencephalography was used to determine the centre of neuronal activation in a simple finger tapping task. The localization accuracy of conventional FMRI depending on FMRI signal enhancement was investigated relative to the magnetoencephalography reference. The results show a deterioration of FMRI localization with increasing signal amplitude related to increased contributions from large vessels. We conclude that FMRI data analysis should exclude large signal amplitudes and that magnetoencephalography may help to improve FMRI brain mapping results in a multimethod approach.

Keywords: Adult ; Brain/*physiology ; *Brain Mapping ; Human ; Magnetic Resonance Imaging/*methods ; *Magnetoencephalography ; Support, Non-U.S. Gov't

A general mathematical model for the delivery of O2 to the brain is presented, based on the assumptions that all of the brain capillaries are perfused at rest and that all of the oxygen extracted from the capillaries is metabolized. The model predicts that disproportionately large changes in blood flow are required in order to support small changes in the O2 metabolic rate. Interpreted in terms of this model, previous positron emission tomography (PET) studies of the human brain during neural stimulation demonstrating that cerebral blood flow (CBF) increases much more than the oxygen metabolic rate are consistent with tight coupling of flow and oxidative metabolism. The model provides a basis for the quantitative interpretation of functional magnetic resonance imaging (fMRI) studies in terms of changes in local CBF.

Keywords: Brain/physiology ; *Cerebrovascular Circulation ; Human ; *Models, Neurological ; *Oxygen Consumption ; *Regional Blood Flow ; Tomography, Emission-Computed

Recently, we introduced a new 'GLM-beamformer' technique for MEG analysis that enables accurate localisation of both phase-locked and non-phase-locked neuromagnetic effects, and their representation as statistical parametric maps (SPMs). This provides a useful framework for comparison of the full range of MEG responses with fMRI BOLD results. This paper reports a 'proof of principle' study using a simple visual paradigm (static checkerboard). The five subjects each underwent both MEG and fMRI paradigms. We demonstrate, for the first time, the presence of a sustained (DC) field in the visual cortex, and its co-localisation with the visual BOLD response. The GLM-beamformer analysis method is also used to investigate the main non-phase-locked oscillatory effects: an event-related desynchronisation (ERD) in the alpha band (8-13 Hz) and an event-related synchronisation (ERS) in the gamma band (55-70 Hz). We show, using SPMs and virtual electrode traces, the spatio-temporal covariance of these effects with the visual BOLD response. Comparisons between MEG and fMRI data sets generally focus on the relationship between the BOLD response and the transient evoked response. Here, we show that the stationary field and changes in oscillatory power are also important contributors to the BOLD response, and should be included in future studies on the relationship between neuronal activation and the haemodynamic response.

Keywords: Adult ; *Alpha Rhythm ; Brain Mapping ; Cerebrovascular Circulation ; Cortical Synchronization ; Female ; Humans ; Linear Models ; Magnetic Resonance Imaging/*methods ; Magnetoencephalography ; Male ; Oxygen/*blood ; Research Support, Non-U.S. Gov't ; Visual Cortex/*physiology

EEG-fMRI and EEG dipole source localisation are two non-invasive imaging methods that can be applied to the study of the haemodynamic and electrical consequences of epileptic discharges. Using them in combination has the potential to allow imaging with the spatial resolution of fMRI and the temporal resolution of EEG. However, although considerable data are available concerning their concordance in studies involving event-related potentials (ERPs), less is known about how well they agree in epilepsy. To this end, 17 patients were selected from a database of 57 who had undergone an EEG-fMRI scanning session followed by a separate EEG session outside of the scanner. Spatiotemporal dipole modelling was compared with the peak and closest EEG-fMRI activations and deactivations. On average, the dipoles were 58.5 mm from the voxel with the highest positive t value and 32.5 mm from the nearest activated voxel. For deactivations, the corresponding values were 60.8 and 34.0 mm. These values are considerably higher than is generally observed with ERPs, probably as a result of the relatively widespread field, which can lead to artificially deep dipoles, and the occurrence of EEG-fMRI responses remote from the presumed focus of the epileptic activity. The results suggest that EEG and MEG inverse solutions for equivalent current dipole approaches should not be strongly constrained by EEG-fMRI results in epilepsy, and that the use of distributed source modelling will be a more appropriate way of combining EEG-fMRI results with source localisation techniques.

Knowledge of regional cerebral hemodynamics has widespread application for both physiological research and clinical assessment because of the well-established interrelation between physiological function, energy metabolism, and localized blood supply. A magnetic resonance technique was developed for quantitative imaging of cerebral hemodynamics, allowing for measurement of regional cerebral blood volume during resting and activated cognitive states. This technique was used to generate the first functional magnetic resonance maps of human task activation, by using a visual stimulus paradigm. During photic stimulation, localized increases in blood volume (32 +/- 10 percent, n = 7 subjects) were detected in the primary visual cortex. Center-of-mass coordinates and linear extents of brain activation within the plane of the calcarine fissure are reported.

Keywords: Blood Volume ; *Brain Mapping ; Humans ; Magnetic Resonance Imaging/methods ; Magnetic Resonance Spectroscopy/methods ; Regional Blood Flow ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S. ; Visual Cortex/anatomy & histology/blood supply/*physiology

Although functional magnetic resonance imaging (fMRI) is a widely used and powerful tool for studying brain function, the quantitative interpretation of fMRI measurements for basic neuroscience and clinical studies can be complicated by inter-subject and inter-session variability arising from modulation of the baseline vascular state by disease, aging, diet, and pharmacological agents. In particular, recent studies have shown that the temporal dynamics of the cerebral blood flow (CBF) and the blood oxygenation level dependent (BOLD) responses to stimulus are modulated by changes in baseline CBF induced by various vasoactive agents and by decreases in vascular compliance associated with aging. These effects are not readily explained using current models of the CBF and BOLD responses. We present here a second-order nonlinear feedback model of the evoked CBF response in which neural activity modulates the compliance of arteriolar smooth muscle. Within this model framework, the baseline vascular state affects the dynamic response by changing the relative contributions of an active smooth muscle component and a passive connective tissue component to the overall vessel compliance. Baseline dependencies of the BOLD signal are studied by coupling the arteriolar compliance model with a previously described balloon model of the venous compartment. Numerical simulations show that the proposed model describes to first order the observed dependence of CBF and BOLD responses on the baseline vascular state.

Keywords: Aging/physiology ; Algorithms ; Arterioles/anatomy & histology/physiology ; Brain Chemistry/physiology ; Carbon Dioxide/physiology ; Cerebrovascular Circulation/*physiology ; Compliance ; Elasticity ; Hemoglobins/metabolism ; Humans ; Magnetic Resonance Imaging ; Models, Neurological ; Models, Statistical ; Muscle Contraction/physiology ; Muscle, Smooth, Vascular/anatomy & histology/*physiology ; Nonlinear Dynamics ; Oxygen/blood ; Research Support, Non-U.S. Gov't ; Viscosity

The acquisition of ERPs concurrently with fMRI in cognitive paradigms is appealing, but technically challenging. Little is known about the effects of the fMRI environment on the time-course and topography of previously documented ERP effects. We examined the replicability of ERP differences in the scanner at the level of individual subjects, using two cognitive paradigms and two statistical procedures. ERP P3 differences found outside the scanner in both paradigms were also robustly detected in the ERPs acquired during fMRI scanning. These P3 effects had equivalent time-courses and scalp topographies inside and outside the scanner. This replication at the level of individual data-sets has implications for the clinical applicability of ERP-fMRI and, more generally, for the quality of scanner recorded ERPs.

Alterations in gyral contour made it difficult to identify the motor cortex thought to be near an arteriovenous malformation (AVM) in a 24-year-old man considered for stereotactic radiosurgery. Functional imaging in three modalities was performed preoperatively to compare the reliability of localization using functional magnetic resonance imaging (fMRI) on a conventional scanner with positron emission tomography (PET) and magnetoencephalography (MEG). Similar tasks were used for each imaging modality in an attempt to activate and identify the sensory and motor cortex. Data from all three modalities converged for the sensory task, and fMRI and PET data converged for the motor task. The right hemisphere motor strip was localized adjacent and anterior to the AVM. These data were used in planning the radiosurgery isodose configuration to the AVM in order to reduce the irradiation of motor cortex parenchyma. A postoperative fMRI study was also performed using newer techniques to reduce head motion artifact and to improve signal-to-noise ratio. The data confirmed the conclusions derived from the preoperative evaluations. This study demonstrates how conventional MRI scanners can be used for functional studies of use in surgical planning.

Keywords: Adult ; Comparative Study ; Human ; Intracranial Arteriovenous Malformations/*pathology/radionuclide imaging/surgery ; *Magnetic Resonance Imaging ; *Magnetoencephalography ; Male ; Motor Cortex/*pathology/radionuclide imaging ; Radiosurgery ; Somatosensory Cortex/pathology/radionuclide imaging ; Stereotaxic Techniques ; *Tomography, Emission-Computed

An integrated model for magnetoencephalography (MEG) and functional Magnetic Resonance Imaging (fMRI) is proposed. In the model, the neural activity is related to the Post Synaptic Potentials (PSPs) which is common link between MEG and fMRI. Each PSP is modeled by the direction and strength of its current flow which are treated as random variables. The overall neural activity in each voxel is used for equivalent current dipole in MEG and as input of extended Balloon model in fMRI. The proposed model shows the possibility of detecting activation by fMRI in a voxel while the voxel is silent for MEG and vice versa. Parameters of the model can illustrate situations like closed field due to non-pyramidal cells, canceling effect of inhibitory PSP on excitatory PSP, and effect of synchronicity. In addition, the model shows that the crosstalk from neural activities of the adjacent voxels in fMRI may result in the detection of activations in these voxels that contain no neural activities. The proposed model is instrumental in evaluating and comparing different analysis methods of MEG and fMRI. It is also useful in characterizing the upcoming combined methods for simultaneous analysis of MEG and fMRI.

Keywords: Algorithms ; Excitatory Postsynaptic Potentials/physiology ; Humans ; Image Processing, Computer-Assisted/*statistics & numerical data ; Linear Models ; Magnetic Resonance Imaging/*statistics & numerical data ; Magnetoencephalography/*statistics & numerical data ; Models, Statistical ; Oxygen/blood

Artifacts generated by motion (e.g., ballistocardiac) of the head inside a high magnetic field corrupt recordings of EEG and EPs. This paper introduces a method for motion artifact cancellation. This method is based on adaptive filtering and takes advantage of piezoelectric motion sensor information to estimate the motion artifact noise. This filter estimates the mapping between motion sensor and EEG space, subtracting the motion-related noise from the raw EEG signal. Due to possible subject motion and changes in electrode impedance, a time-varying mapping of the motion versus EEG is required. We show that this filter is capable of removing both ballistocardiogram and gross motion artifacts, restoring EEG alpha waves (8-13 Hz), and visual evoked potentials (VEPs). This adaptive filter outperforms the simple band-pass filter for alpha detection because it is also capable of reducing noise within the frequency band of interest. In addition, this filter also removes the transient responses normally visible in the EEG window after echo planar image acquisition, observed during interleaved EEG/fMRI recordings. Our adaptive filter approach can be implemented in real-time to allow for continuous monitoring of EEG and fMRI during clinical and cognitive studies.

Keywords: Adult ; Alpha Rhythm ; *Artifacts ; Ballistocardiography ; Brain/*physiology ; *Electroencephalography ; *Evoked Potentials, Visual ; Female ; Human ; *Magnetic Resonance Imaging ; Male ; Motion ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.

A component based method (CompCor) for the reduction of noise in both blood oxygenation level-dependent (BOLD) and perfusion-based functional magnetic resonance imaging (fMRI) data is presented. In the proposed method, significant principal components are derived from noise regions-of-interest (ROI) in which the time series data are unlikely to be modulated by neural activity. These components are then included as nuisance parameters within general linear models for BOLD and perfusion-based fMRI time series data. Two approaches for the determination of the noise ROI are considered. The first method uses high-resolution anatomical data to define a region of interest composed primarily of white matter and cerebrospinal fluid, while the second method defines a region based upon the temporal standard deviation of the time series data. With the application of CompCor, the temporal standard deviation of resting-state perfusion and BOLD data in gray matter regions was significantly reduced as compared to either no correction or the application of a previously described retrospective image based correction scheme (RETROICOR). For both functional perfusion and BOLD data, the application of CompCor significantly increased the number of activated voxels as compared to no correction. In addition, for functional BOLD data, there were significantly more activated voxels detected with CompCor as compared to RETROICOR. In comparison to RETROICOR, CompCor has the advantage of not requiring external monitoring of physiological fluctuations.

We used a real-skull phantom head to investigate the performances of representative methods for EEG source localization when considering various head models. We describe several experiments using a montage with current sources located at multiple positions and orientations inside a human skull filled with a conductive medium. The robustness of selected methods based on distributed source models is evaluated as various solutions to the forward problem (from the sphere to the finite element method) are considered. Experimental results indicate that inverse methods using appropriate cortex-based source models are almost always able to locate the active source with excellent precision, with little or no spurious activity in close or distant regions, even when two sources are simultaneously active. Superior regularization schemes for solving the inverse problem can dramatically help the estimation of sparse and focal active zones, despite significant approximation of the head geometry and the conductivity properties of the head tissues. Realistic head models are necessary, though, to fit the data with a reasonable level of residual variance.

Keywords: Electroencephalography/*methods ; Head/*radiation effects ; Human ; Models, Theoretical ; Phantoms, Imaging ; Reproducibility of Results ; Skull/*radiation effects ; Time Factors

We introduce a bottom-up model for integrating electroencephalography (EEG) or magnetoencephalography (MEG) with functional magnetic resonance imaging (fMRI). An extended neural mass model is proposed based on the physiological principles of cortical minicolumns and their connections. The fMRI signal is extracted from the proposed neural mass model by introducing a relationship between the stimulus and the neural activity and using the resultant neural activity as input of the extended Balloon model. The proposed model, validated using simulations, is instrumental in evaluating the upcoming combined methods for simultaneous analysis of MEG/EEG and fMRI.

Keywords: Algorithms ; Brain/*physiology ; Brain Mapping/*methods ; Computer Simulation ; Diagnosis, Computer-Assisted/*methods ; Electroencephalography/*methods ; Evoked Potentials/physiology ; Humans ; Magnetic Resonance Imaging/*methods ; Magnetoencephalography/*methods ; *Models, Neurological ; Nerve Net/physiology ; Systems Integration

Combined analysis of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) has the potential to provide higher spatiotemporal resolution than either method alone. In some situations, in which the activity of interest cannot be reliably reproduced (e.g., epilepsy, learning, sleep states), accurate combined analysis requires simultaneous acquisition of EEG and fMRI. Simultaneous measurements ensure that the EEG and fMRI recordings reflect the exact same brain activity state. We took advantage of the spatial filtering properties of the bipolar montage to allow recording of very short (125-250 ms) visual-evoked potentials (VEPs) during fMRI. These EEG and fMRI measurements are of sufficient quality to allow source localization of the cortical generators. In addition, our source localization approach provides a combined EEG/fMRI analysis that does not require any manual selection of fMRI activations or placement of source dipoles. The source of the VEP was found to be located in the occipital cortex. Separate analysis of EEG and fMRI data demonstrated good spatial overlap of the observed activated sites. As expected, the combined EEG/fMRI analysis provided better spatiotemporal resolution than either approach alone. The resulting spatiotemporal movie allows for the millisecond-to-millisecond display of changes in cortical activity caused by visual stimulation. These data reveal two peaks in activity corresponding to the N75 and the P100 components. This type of simultaneous acquisition and analysis allows for the accurate characterization of the location and timing of neurophysiological activity in the human brain.

Keywords: Adult ; *Brain Mapping ; Computer Graphics ; Data Display ; Dominance, Cerebral/physiology ; *Electroencephalography ; Evoked Potentials, Visual/*physiology ; Female ; Human ; *Image Enhancement ; *Image Processing, Computer-Assisted ; Imaging, Three-Dimensional ; *Magnetic Resonance Imaging ; Male ; Occipital Lobe/*physiology ; Photic Stimulation ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.

An issue in blood oxygenation level dependent contrast-based functional MRI is the accurate interpretation of the activation-induced signal changes. Hemodynamic factors other than activation-induced changes in blood oxygenation are known to contribute to the signal change magnitudes and dynamics, and therefore need to be accounted for or removed. In this paper, a general method for removal of effects other than activation-induced blood oxygenation changes from fMRI brain activation maps by the use of hypercapnic stress normalization is introduced. First, the effects of resting blood volume distribution across voxels on activation-induced BOLD-based fMRI signal changes are shown to be significant. Second, the effects of hypercapnia and hypoxia on resting and activation-induced signal changes are demonstrated. These results suggest that global hemodynamic stresses may be useful for non-invasive mapping of blood volume. Third, the normalization technique is demonstrated.

Keywords: Brain/*anatomy & histology/blood supply/*physiology ; Brain Mapping/*methods ; Carbon Dioxide/*blood ; Humans ; Image Processing, Computer-Assisted/methods ; Magnetic Resonance Imaging/*methods ; Oxygen/blood

Integrating electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data may help to optimize anatomical and temporal resolution in the investigation of cortical function. Successful removal of fMRI scanning artifacts from continuous EEG in simultaneous recordings has been reported. We assessed the feasibility of recording reliable visual evoked potentials (VEPs) during fMRI scanning using available artifact removing procedures. EEG during administration of visual stimuli was recorded using MRI-compatible 32-channel equipment in nine normal subjects (mean age, 23.9 +/- 2.5 years), with and without fMRI acquisition. fMRI scanning and cardioballistographic artifacts were removed after subtraction of averaged artifact waveforms. Consistency between VEPs waveforms and of P1 and N1 peak latencies and amplitudes in the two conditions was assessed. Good correlation was found between VEP waveforms (Pearson's correlation coefficient: r(P) between 0.76-0.94 across subjects; P < 0.0001) and between latency or amplitude of P1 and N1 peaks (latencies: r = 0.7, P < 0.035; amplitudes: r > 0.65, P < 0.05; Spearman rank correlation coefficient) in the two recording conditions. No significant differences were found between P1 and N1 parameters in the two conditions (Wilcoxon signed rank test). Consistent VEP waveforms, latencies, and amplitudes with and without fMRI scanning indicate that reliable VEPs may be obtained simultaneously with fMRI recording. This possibility might be helpful by shortening recording times and reducing variability from learning, habituation, and fatigue phenomena from separate recordings for the integration of event-related EEG and fMRI data.

Keywords: Adult ; *Artifacts ; Brain/*physiology ; *Brain Mapping ; Electroencephalography ; Evoked Potentials, Visual/*physiology ; Female ; Humans ; *Magnetic Resonance Imaging ; Male ; Photic Stimulation ; Research Support, Non-U.S. Gov't

The coupling between neurotransmitter-induced changes in neuronal activity and the resultant hemodynamic response is central to the interpretation of neuroimaging techniques. In the present study, MRI experiments showed that dopamine transporter blockers such as cocaine and dopamine releasers such as amphetamine and D1 receptor agonists induced large positive increases in relative cerebral blood volume (rCBV) that were not sensitive to nitric oxide synthase inhibition. However, D1/D5 receptor antagonism with SCH-23390 prevented or blocked the hemodynamic response without any concomitant effect on dopamine release. Dopamine D2/D3 receptor agonists, in contrast, induced negative changes in rCBV in brain regions corresponding largely to those endowed with these receptors. D1 and D5 receptor mRNAs were expressed in microvessels of responsive brain areas, while D2 and D3 receptors were not consistently associated with the microvascular bed. D3 receptors had an astroglial localization. Together, these experiments show that direct effects of dopamine upon the vasculature cannot be ignored in measuring the hemodynamic coupling associated with dopaminergic drugs. These results further suggest that this coupling is partially mediated through D1/D5 receptors on the microvasculature leading to increased rCBV and through astroglial D3 receptors leading to decreased rCBV. These data provide additional support for the role of local post-synaptic events in neurovascular coupling and emphasize that the interpretation of fMRI signals exclusively in terms of neuronal activity may be incomplete.

Functional neuroimaging in humans is used widely to study brain function in relation to human disease and cognition. The neural basis of neuroimaging signals is probably synaptic activity, but the effect of context, defined as the interaction between synaptic inhibition, excitation, and the electroresponsive properties of the targeted neurons, is not well understood. We examined here the effect of interaction of synaptic excitation and net inhibition on the relationship between electrical activity and vascular signals in the cerebellar cortex. We show that stimulation of the net inhibitory parallel fibers simultaneously with stimulation of the excitatory climbing fibers leads to a further rise in total local field potentials (LFP) and cerebral blood flow (CBF) amplitudes, not a decrease, as predicted from theoretical studies. However, the combined stimulation of the parallel and climbing fiber systems produced changes in CBF and LFP that were smaller than their algebraic sum evoked by separate stimulation of either system. This finding was independent of the starting condition, i.e., whether inhibition was superimposed on a state of excitation or vice versa. The attenuation of the increases in LFP and CBF amplitudes was similar, suggesting that synaptic activity and CBF were coupled under these conditions. The result might be explained by a relative neuronal refractoriness that relates to the intrinsic membrane properties of Purkinje cells, which determine the recovery time of these cells. Our work implies that neuronal and vascular signals are context-sensitive and that their amplitudes are modulated by the electroresponsive properties of the targeted neurons.

Keywords: Animals ; Blood Flow Velocity/*physiology ; Brain/blood supply/*physiology ; Cerebrovascular Circulation/*physiology ; Electric Stimulation ; Humans ; Laser-Doppler Flowmetry ; Male ; Membrane Potentials/physiology ; Microelectrodes ; Olivary Nucleus/blood supply/physiology ; Purkinje Cells/physiology ; Rats ; Rats, Wistar ; Research Support, Non-U.S. Gov't ; Synapses/physiology

This paper deals with the estimation of the blood oxygen level-dependent response to a stimulus, as measured in functional magnetic resonance imaging (fMRI) data. A precise estimation is essential for a better understanding of cerebral activations. The most recent works have used a nonparametric framework for this estimation, considering each brain region as a system characterized by its impulse response, the so-called hemodynamic response function (HRF). However, the use of these techniques has remained limited since they are not well-adapted to real fMRI data. Here, we develop a threefold extension to previous works. We consider asynchronous event-related paradigms, account for different trial types and integrate several fMRI sessions into the estimation. These generalizations are simultaneously addressed through a badly conditioned observation model. Bayesian formalism is used to model temporal prior information of the underlying physiological process of the brain hemodynamic response. By this way, the HRF estimate results from a tradeoff between information brought by the data and by our prior knowledge. This tradeoff is modeled with hyperparameters that are set to the maximum-likelihood estimate using an expectation conditional maximization algorithm. The proposed unsupervised approach is validated on both synthetic and real fMRI data, the latter originating from a speech perception experiment.

Keywords: *Algorithms ; Brain/*blood supply/*physiology ; Brain Mapping/*methods ; Cerebrovascular Circulation/physiology ; Comparative Study ; Computer Simulation ; Hemodynamic Processes/physiology ; Human ; Image Interpretation, Computer-Assisted/*methods ; Imaging, Three-Dimensional/*methods ; Likelihood Functions ; Magnetic Resonance Imaging/*methods ; *Models, Cardiovascular ; Models, Statistical ; Reproducibility of Results ; Sensitivity and Specificity ; Speech Perception/physiology ; Support, Non-U.S. Gov't

All perfusion-based imaging modalities depend on the relationship between neuronal and vascular activity. However, the relationship between stimulus and response was never fully characterized. With the use of optical imaging (intrinsic signals and intravascular fluorescent dyes) during repetitive stimulation paradigms, we observed reduced responses with temporally close stimuli. Cortical evoked potentials, however, did not produce the same reduced responsiveness. We therefore termed these intervals of reduced responsiveness refractory periods. During these refractory periods an ability to respond was retained, but at a near 60% reduction in the initial magnitude. Although increasing the initial stimulus duration lengthened the observed refractory periods, significantly novel or temporally spaced stimuli overcame them. We observed this phenomenon in both rodent and human subjects in somatosensory and auditory cortices. These results have significant implications for understanding the capacities, mechanisms, and distributions of neurovascular coupling and thereby possess relevance to all perfusion-dependent functional imaging techniques.

Keywords: Acoustic Stimulation ; Animals ; Evoked Potentials, Somatosensory/physiology ; Fluorescent Dyes ; Humans ; Image Processing, Computer-Assisted ; Male ; Optics ; Proprioception/physiology ; Rats ; Rats, Sprague-Dawley ; Refractory Period, Neurologic/*physiology ; Research Support, U.S. Gov't, P.H.S. ; Somatosensory Cortex/*physiology ; Temporal Lobe/physiology

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) measurements were performed in six healthy subjects to determine the representation of stimulation of the right thumb in somatosensory cortex. In all subjects EEG-based dipole locations could be determined in primary (S1) and secondary (S2) somatosensory cortex. The stimulus-induced blood oxygenation level dependent response of the fMRI showed deviations of 23.5 mm (standard deviation, SD = 6.9) for S1 and 15.7 mm (SD = 3.5) for S2 cortex. fMRI constrained dipole searches lead to higher residual variances. The data show that simultaneous EEG and fMRI measurements of somatosensory activity are feasible and yield reliable and valid results.

Keywords: Adult ; Analysis of Variance ; Electric Stimulation/methods ; Electroencephalography/*methods/statistics & numerical data ; Female ; Humans ; Linear Models ; Magnetic Resonance Imaging/*methods/statistics & numerical data ; Male ; Research Support, Non-U.S. Gov't ; Somatosensory Cortex/*physiology

The blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal response to neural stimulation is influenced by many factors that are unrelated to the stimulus. These factors are physiological, such as the resting venous cerebral blood volume (CBV(v)) and vessel size, as well as experimental, such as pulse sequence and static magnetic field strength (B(0)). Thus, it is difficult to compare task-induced fMRI signals across subjects, field strengths, and pulse sequences. This problem can be overcome by normalizing the neural activity-induced BOLD fMRI response by a global hypercapnia-induced BOLD signal. To demonstrate the effectiveness of the BOLD normalization approach, gradient-echo BOLD fMRI at 1.5, 4, and 7 T and spin-echo BOLD fMRI at 4 T were performed in human subjects. For neural stimulation, subjects performed sequential finger movements at 2 Hz, while for global stimulation, subjects breathed a 5 CO(2) gas mixture. Under all conditions, voxels containing primarily large veins and those containing primarily active tissue (i.e., capillaries and small veins) showed distinguishable behavior after hypercapnic normalization. This allowed functional activity to be more accurately localized and quantified based on changes in venous blood oxygenation alone. The normalized BOLD signal induced by the motor task was consistent across different magnetic fields and pulse sequences, and corresponded well with cerebral blood flow measurements. Our data suggest that the hypercapnic normalization approach can improve the spatial specificity and interpretation of BOLD signals, allowing comparison of BOLD signals across subjects, field strengths, and pulse sequences. A theoretical framework for this method is provided.

Keywords: Adult ; Algorithms ; Brain Mapping ; Cerebrovascular Circulation ; Comparative Study ; Echo-Planar Imaging ; Female ; Humans ; Hypercapnia/*blood ; Image Interpretation, Computer-Assisted ; Magnetic Resonance Imaging/*methods ; Male ; Oxygen/*blood ; Psychomotor Performance/physiology ; Reference Values ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S.

We mapped ocular dominance columns (ODCs) in normal human subjects using high-field (4 T) functional magnetic resonance imaging (fMRI) with a segmented echo planar imaging technique and an in-plane resolution of 0.47 x 0.47 mm(2). The differential responses to left or right eye stimulation could be reliably resolved in anatomically well-defined sections of V1. The orientation and width ( approximately 1 mm) of mapped ODC stripes conformed to those previously revealed in postmortem brains stained with cytochrome oxidase. In addition, we showed that mapped ODC patterns could be largely reproduced in different experiments conducted within the same experimental session or over different sessions. Our results demonstrate that high-field fMRI can be used for studying the functions of human brains at columnar spatial resolution.

Keywords: Adult ; *Brain Mapping ; Dominance, Cerebral/*physiology ; Humans ; *Magnetic Resonance Imaging ; Male ; *Ocular Physiology ; Photic Stimulation ; Research Support, Non-U.S. Gov't ; Visual Cortex/physiology

Using a model of the functional MRI (fMRI) impulse response based on published data, we have demonstrated that the form of the fMRI response to stimuli of freely varied timing can be modeled well by convolution of the impulse response with the behavioral stimulus. The amplitudes of the responses as a function of parametrically varied behavioral conditions are fitted well using a piecewise linear approximation. Use of the combined model, in conjunction with correlation analysis, results in an increase in sensitivity for the MRI study. This approach, based on the well-established methods of linear systems analysis, also allows a quantitative comparison of the response amplitudes across subjects to a broad range of behavioral conditions. Fit parameters, derived from the amplitude data, are relatively insensitive to a variety of MRI-related artifacts and yield results that are compared readily across subjects.

Keywords: Adult ; Brain/anatomy & histology/*physiology ; Brain Mapping ; Cerebrovascular Circulation/physiology ; Human ; Linear Models ; Magnetic Resonance Imaging/*statistics & numerical data ; Photic Stimulation ; Psychomotor Performance/physiology

Recent advances in brain imaging techniques, including functional magnetic resonance imaging (fMRI), offer great promise for noninvasive mapping of brain function. However, the indirect nature of the imaging signals to the underlying neural activity limits the interpretation of the resulting maps. The present report represents the first systematic study with sufficient statistical power to quantitatively characterize the relationship between changes in blood oxygen content and the neural spiking and synaptic activity. Using two-dimensional optical measurements of hemodynamic signals, simultaneous recordings of neural activity, and an event-related stimulus paradigm, we demonstrate that (1) there is a strongly nonlinear relationship between electrophysiological measures of neuronal activity and the hemodynamic response, (2) the hemodynamic response continues to grow beyond the saturation of electrical activity, and (3) the initial increase in deoxyhemoglobin that precedes an increase in blood volume is counterbalanced by an equal initial decrease in oxyhemoglobin.

Keywords: Animals ; Brain Mapping ; Comparative Study ; Computer Simulation ; Demography ; Electric Stimulation ; Electrophysiology/methods ; Evoked Potentials, Somatosensory/physiology ; Hemodynamic Processes/physiology ; Hemoglobins/*metabolism ; Magnetic Resonance Imaging/methods ; Neurons/*physiology ; Nonlinear Dynamics ; Oxygen/*metabolism ; Rats ; Somatosensory Cortex/blood supply/cytology/*metabolism ; Spectrum Analysis/methods ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S. ; Time Factors

To assess the degree of fine-scale somatotopy within the hand area of the human primary motor cortex (M1), functional mapping of individual movements of all fingers was performed in healthy young subjects (n = 7) using MRI at 0.8 x 0.8 mm2 resolution and 4 mm section thickness. The experimental design comprised both a direct paradigm contrasting single digit movements vs. motor rest and multiple differential paradigms contrasting single digit movements vs. the movement of another digit. Direct mapping resulted in largely overlapping activations. A somatotopic arrangement was only recognizable when considering the mean center-of-mass coordinates of individual digit representations averaged across subjects. In contrast, differential paradigms revealed more segregated and somatotopically ordered activations in single subjects. The use of center-of-mass coordinates yielded inter-digit distances ranging from 2.0 to 16.8 mm, which reached statistical significance for pairs of more distant digits. For the middle fingers, the functional somatotopy obtained by differential mapping was dependent on the choice of the digit used for control. These results confirm previous concepts that finger somatotopy in the human M1 hand area emerges as a functional predominance of individual digit representations sharing common areas in a distributed though ordered network.

Keywords: Adult ; Analysis of Variance ; Brain Mapping/*methods ; Female ; Fingers/*physiology ; Human ; Least-Squares Analysis ; Male ; Motor Cortex/*physiology

There is an increasing interest in using physiologically plausible models in fMRI analysis. These models do raise new mathematical problems in terms of parameter estimation and interpretation of the measured data. In this paper, we show how to use physiological models to map and analyze brain activity from fMRI data. We describe a maximum likelihood parameter estimation algorithm and a statistical test that allow the following two actions: selecting the most statistically significant hemodynamic model for the measured data and deriving activation maps based on such model. Furthermore, as parameter estimation may leave much incertitude on the exact values of parameters, model identifiability characterization is a particular focus of our work. We applied these methods to different variations of the Balloon Model (Buxton, R.B., Wang, E.C., and Frank, L.R. 1998. Dynamics of blood flow and oxygenation changes during brain activation: the balloon model. Magn. Reson. Med. 39: 855-864; Buxton, R.B., Uludag, K., Dubowitz, D.J., and Liu, T.T. 2004. Modelling the hemodynamic response to brain activation. NeuroImage 23: 220-233; Friston, K. J., Mechelli, A., Turner, R., and Price, C. J. 2000. Nonlinear responses in fMRI: the balloon model, volterra kernels, and other hemodynamics. NeuroImage 12: 466-477) in a visual perception checkerboard experiment. Our model selection proved that hemodynamic models better explain the BOLD response than linear convolution, in particular because they are able to capture some features like poststimulus undershoot or nonlinear effects. On the other hand, nonlinear and linear models are comparable when signals get noisier, which explains that activation maps obtained in both frameworks are comparable. The tools we have developed prove that statistical inference methods used in the framework of the General Linear Model might be generalized to nonlinear models.

Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical properties in humans, it is necessary to obtain an accurate and explicit representation of the cortical surface in individual subjects. Here we describe a set of automated procedures for obtaining accurate reconstructions of the cortical surface, which have been applied to data from more than 100 subjects, requiring little or no manual intervention. Automated routines for unfolding and flattening the cortical surface are described in a companion paper. These procedures allow for the routine use of cortical surface-based analysis and visualization methods in functional brain imaging.

Keywords: Brain Mapping/instrumentation ; Cerebral Cortex/*anatomy & histology ; Human ; Image Processing, Computer-Assisted/*instrumentation ; Magnetic Resonance Imaging/*instrumentation ; Reference Values ; Software

We studied MEG and fMRI responses to electric median and tibial nerve stimulation in five healthy volunteers. The aim was to compare the results with those of a previous study using only fMRI on the primary and secondary somatosensory cortices in which the somatotopic organization of SII was observed with fMRI. In the present work we focus on the comparison between fMRI activation and MEG equivalent current dipole (ECD) localizations in the SII area. The somatotopic organization of SII was confirmed by MEG, with the upper limb areas located more anteriorly and more inferiorly than the lower limb areas. In addition a substantial consistency of the ECD locations with the areas of fMRI activation was observed, with an average mismatch of about 1 cm. MEG ECDs and fMRI activation areas showed comparable differences in SI.

Keywords: Adult ; Brain Mapping/*methods ; Dominance, Cerebral/physiology ; Electric Stimulation ; Evoked Potentials, Somatosensory/physiology ; Female ; Humans ; *Image Processing, Computer-Assisted ; *Magnetic Resonance Imaging ; *Magnetoencephalography ; Male ; Median Nerve/physiology ; Reference Values ; Research Support, Non-U.S. Gov't ; Somatosensory Cortex/*physiology ; Tibial Nerve/physiology

Functional magnetic resonance imaging (fMRI) and positron emission tomography measure local changes in brain hemodynamics induced by cognitive or perceptual tasks. These measures have a uniformly high spatial resolution of millimeters or less, but poor temporal resolution (about 1s). Conversely, electroencephalography (EEG) and magnetoencephalography (MEG) measure instantaneously the current flows induced by synaptic activity, but the accurate localization of these current flows based on EEG and MEG data alone remains an unsolved problem. Recently, techniques have been developed that, in the context of brain anatomy visualized with structural MRI, use both hemodynamic and electromagnetic measures to arrive at estimates of brain activation with high spatial and temporal resolution. These methods range from simple juxtaposition to simultaneous integrated techniques. Their application has already led to advances in our understanding of the neural bases of perception, attention, memory and language. Further advances in multi-modality integration will require an improved understanding of the coupling between the physiological phenomena underlying the different signal modalities.

Keywords: Animals ; Brain Mapping/*methods ; Electroencephalography/methods ; Human ; Magnetic Resonance Imaging/methods ; Magnetoencephalography/methods ; Perception/physiology ; Spectroscopy, Near-Infrared/methods ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S. ; *Systems Integration ; Tomography, Emission-Computed/methods

We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.

Keywords: *Computer Simulation/trends ; Electroencephalography/*methods ; Evoked Potentials/*physiology ; *Software/trends ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.

Functional MRI (fMRI) can be applied to study the functional connectivity of the human brain. It has been suggested that fluctuations in the blood oxygenation level-dependent (BOLD) signal during rest reflect the neuronal baseline activity of the brain, representing the state of the human brain in the absence of goal-directed neuronal action and external input, and that these slow fluctuations correspond to functionally relevant resting-state networks. Several studies on resting fMRI have been conducted, reporting an apparent similarity between the identified patterns. The spatial consistency of these resting patterns, however, has not yet been evaluated and quantified. In this study, we apply a data analysis approach called tensor probabilistic independent component analysis to resting-state fMRI data to find coherencies that are consistent across subjects and sessions. We characterize and quantify the consistency of these effects by using a bootstrapping approach, and we estimate the BOLD amplitude modulation as well as the voxel-wise cross-subject variation. The analysis found 10 patterns with potential functional relevance, consisting of regions known to be involved in motor function, visual processing, executive functioning, auditory processing, memory, and the so-called default-mode network, each with BOLD signal changes up to 3 BOLD signal are consistent and show the least variation around the mean. These findings show that the baseline activity of the brain is consistent across subjects exhibiting significant temporal dynamics, with percentage BOLD signal change comparable with the signal changes found in task-related experiments.

Keywords: Brain/*physiology ; *Brain Mapping ; Health ; Humans ; Magnetic Resonance Imaging ; Research Support, Non-U.S. Gov't ; Rest/*physiology

We report on the simultaneous and continuous acquisition of EEG and functional MRI data in a patient with a left hemiparesis and focal epilepsy secondary to malformation of cortical development in the right hemisphere. EEG-triggered fMRI localization was previously demonstrated in this patient. In the experiments reported here, 322 spikes maximum at electrode C4 and 126 focal slow waves were identified offline. A hierarchy of models was explored in order to assess the relative contributions of each type of EEG event. Modeling the BOLD response to C4 spikes alone showed an area of activation within the large malformation, adjacent to the area of infolding cortex. However, also modeling slow-waves gave rise to a broader and stronger activation, suggesting that the generators overlap. Motor mapping of the right hand showed activation in the left sensorimotor cortex; left-hand tapping led to a more diffuse area of activation, displaced superiorly into the superior frontal gyrus, and a small area of activation within the lesion. In conclusion, continuous EEG-fMRI is useful to compare the functional mapping of epileptiform activity and eloquent cortices in individual patients.

Keywords: Adult ; Brain/pathology/*physiopathology ; Cerebral Cortex/*abnormalities ; *Electroencephalography ; Epilepsies, Partial/*physiopathology ; Humans ; *Magnetic Resonance Imaging ; Male ; Motor Activity/physiology ; Paresis/physiopathology ; Research Support, Non-U.S. Gov't

How well does the functional MRI (fMRI) signal reflect underlying electrophysiology? Despite the ubiquity of the technique, this question has yet to be adequately answered. Therefore, we have compared cortical maps generated based on the indirect blood oxygenation level-dependent signal of fMRI with maps from microelectrode recording techniques, which directly measure neural activity. Identical somatosensory stimuli were used in both sets of experiments in the same anesthetized macaque monkeys. Our results demonstrate that fMRI can be used to determine the topographic organization of cortical fields with 55% concordance to electrophysiological maps. The variance in the location of fMRI activation was greatest in the plane perpendicular to local vessels. An appreciation of the limitations of fMRI improves our ability to use it effectively to study cortical organization.

Keywords: Animals ; Brain Mapping/*methods ; Cerebrovascular Circulation ; Comparative Study ; Dose-Response Relationship, Drug ; *Electrophysiology ; Face/physiology ; Hand/physiology ; Humans ; Macaca mulatta/*physiology ; Magnetic Resonance Imaging ; Microelectrodes ; Oxygen/*blood ; Reproducibility of Results ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S. ; Somatosensory Cortex/*blood supply/*physiology

EEG signals recorded simultaneously with fMRI are massively compromised by severe artefacts, among them the cardiac cycle-related ballistocardiogram (BCG) artefact. Different methods have been proposed to remove the BCG artefact focusing on channel-wise template subtraction procedures or spatial filtering approaches such as independent component analysis (ICA). Here we systematically compared the performance of the optimal basis set (OBS), a channel-wise correction approach, with ICA and a recently proposed combination of both (OBS-ICA). The three different procedures were applied to 60-channel EEG data from 12 subjects recorded during fMRI acquisition in a 3-T scanner. In addition to examination of the residual BCG artefact, the signal-to-noise ratio (SNR) and the topography of the resulting auditory evoked potential component N1 were compared. Whereas all three approaches led to a significant artefact reduction, the ICA procedure resulted in a significantly reduced N1 SNR and amplitude when compared to BCG-uncorrected data, indicating a rather poor performance. In contrast to ICA, OBS and OBS-ICA corrected data substantially improved the SNR of the N1. The quality of the auditory evoked potential N1 topography was investigated by means of equivalent current dipole modelling. On a descriptive level, all three correction procedures led to a reduced localization error when compared to BCG-uncorrected data. This improvement was significant for OBS-ICA. We conclude that OBS and OBS-ICA can efficiently remove BCG artefacts and substantially improve the quality of EEG signals recorded inside the scanner, a prerequisite for the successful integration of simultaneously recorded EEG and fMRI.

Goal-directed behavior requires the continuous monitoring and dynamic adjustment of ongoing actions. Here, we report a direct coupling between the event-related electroencephalogram (EEG), functional magnetic resonance imaging (fMRI), and behavioral measures of performance monitoring in humans. By applying independent component analysis to EEG signals recorded simultaneously with fMRI, we found the single-trial error-related negativity of the EEG to be systematically related to behavior in the subsequent trial, thereby reflecting immediate behavioral adjustments of a cognitive performance monitoring system. Moreover, this trial-by-trial EEG measure of performance monitoring predicted the fMRI activity in the rostral cingulate zone, a brain region thought to play a key role in processing of response errors. We conclude that investigations of the dynamic coupling between EEG and fMRI provide a powerful approach for the study of higher order brain functions.

Keywords: Adult ; Comparative Study ; Electroencephalography/*methods ; Evoked Potentials/*physiology ; Female ; Humans ; Magnetic Resonance Imaging/*methods ; Male ; Photic Stimulation/methods ; Psychomotor Performance/*physiology ; Research Support, Non-U.S. Gov't

Two major non-invasive techniques in cognitive neuroscience, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. Recent hardware and software developments have made it feasible to acquire EEG and fMRI data simultaneously. We emphasize the potential of simultaneous EEG and fMRI recordings to pursue new strategies in cognitive neuroimaging. Specifically, we propose that, by exploiting the combined spatiotemporal resolution of the methods, the integration of EEG and fMRI recordings on a single-trial level enables the rich temporal dynamics of information processing to be characterized within spatially well-defined neural networks.

Many studies have investigated the temporal properties of BOLD signal responses to task performance in regions of interest, often noting significant departures from the conventionally modelled response shape, and significant variation between regions. However, these investigations are rarely extended across the whole brain nor incorporated into the routine analysis of fMRI studies. As a result, little is known about the range of response shapes generated in the brain by common paradigms. The present study finds such temporal dynamics can be complex. We made a detailed investigation of BOLD signal responses across the whole brain during a two minute motor-sequence task, and tracked changes due to learning. The multi-component OSORU (Onset, Sustained, Offset, Ramp, Undershoot) linear model, developed by Harms and Melcher (J.Neurophysiology, 2003), was extended to characterise responses. In many regions, signal transients persisted for over thirty seconds, with large signal spikes at onset often followed by a dip in signal below the final sustained level of activation. Training altered certain features of the response shape, suggesting that different features of the response may reflect different aspects of neuro-vascular dynamics. Unmodelled, this may give rise to inconsistent results across paradigms of varying task durations. Few of the observed effects have been thoroughly addressed in physiological models of the BOLD response. The complex, extended dynamics generated by this simple, often employed task, suggests characterisation and modelling of temporal aspects of BOLD responses needs to be carried out routinely, informing experimental design and analysis, and physiological modelling.

Concurrent event-related EEG-fMRI recordings pick up volume-conducted and hemodynamically convoluted signals from latent neural sources that are spatially and temporally mixed across the brain, i.e. the observed data in both modalities represent multiple, simultaneously active, regionally overlapping neuronal mass responses. This mixing process decreases the sensitivity of voxel-by-voxel prediction of hemodynamic activation by the EEG when multiple sources contribute to either the predictor and/or the response variables. In order to address this problem, we used independent component analysis (ICA) to recover maps from the fMRI and timecourses from the EEG, and matched these components across the modalities by correlating their trial-to-trial modulation. The analysis was implemented as a group-level ICA that extracts a single set of components from the data and directly allows for population inferences about consistently expressed function-relevant spatiotemporal responses. We illustrate the utility of this method by extracting a previously undetected but relevant EEG-fMRI component from a concurrent auditory target detection experiment.

The brain acts as an integrated information processing system, which methods in cognitive neuroscience have so far depicted in a fragmented fashion. Here, we propose a simple and robust way to integrate functional MRI (fMRI) with single trial event-related potentials (ERP) to provide a more complete spatiotemporal characterization of evoked responses in the human brain. The idea behind the approach is to find brain regions whose fMRI responses can be predicted by paradigm-induced amplitude modulations of simultaneously acquired single trial ERPs. The method was used to study a variant of a two-stimulus auditory target detection (odd-ball) paradigm that manipulated predictability through alternations of stimulus sequences with random or regular target-to-target intervals. In addition to electrophysiologic and hemodynamic evoked responses to auditory targets per se, single-trial modulations were expressed during the latencies of the P2 (170-ms), N2 (200-ms), and P3 (320-ms) components and predicted spatially separated fMRI activation patterns. These spatiotemporal matches, i.e., the prediction of hemodynamic activation by time-variant information from single trial ERPs, permit inferences about regional responses using fMRI with the temporal resolution provided by electrophysiology.

Keywords: Adult ; Brain/*cytology/*physiology ; Electroencephalography ; Evoked Potentials/*physiology ; Female ; Humans ; Magnetic Resonance Imaging ; Male ; Neurons/*physiology ; Research Support, Non-U.S. Gov't ; Time Factors

Probability theory is applied to the analysis of fMRI data. The posterior distribution of the parameters is shown to incorporate all the information available from the data, the hypotheses, and the prior information. Under appropriate simplifying conditions, the theory reduces to the standard statistical test, including the general linear model. The theory is particularly suited to handle the spatial variations in the noise present in fMRI, allowing the comparison of activated voxels that have different, and unknown, noise. The theory also explicitly includes prior information, which is shown to be critical in the attainment of reliable activation maps.

Keywords: Human ; Image Enhancement ; Likelihood Functions ; Magnetic Resonance Imaging/*methods ; Models, Statistical ; *Probability Theory ; Sensitivity and Specificity ; Signal Processing, Computer-Assisted ; Statistics

We present an approach to characterizing the differences among event-related hemodynamic responses in functional magnetic resonance imaging that are evoked by different sorts of stimuli. This approach is predicated on a linear convolution model and standard inferential statistics as employed by statistical parametric mapping. In particular we model evoked responses, and their differences, in terms of basis functions of the peri-stimulus time. This facilitates a characterization of the temporal response profiles that has a high effective temporal resolution relative to the repetition time. To demonstrate the technique we examined differential responses to visually presented words that had been seen prior to scanning or that were novel. The form of these differences involved both the magnitude and the latency of the response components. In this paper we focus on bilateral ventrolateral prefrontal responses that show deactivations for previously seen words and activations for novel words.

Keywords: Evoked Potentials/*physiology ; Frontal Lobe/*physiology ; Hemodynamic Processes/*physiology ; Human ; Linear Models ; *Magnetic Resonance Imaging ; Memory/*physiology ; Models, Theoretical ; Reaction Time ; Reference Values ; Support, Non-U.S. Gov't

Functional magnetic resonance imaging (fMRI) is used widely to determine the spatial layout of brain activation associated with specific cognitive tasks at a spatial scale of millimeters. Recent methodological improvements have made it possible to determine the latency and temporal structure of the activation at a temporal scale of few hundreds of milliseconds. Despite the sluggishness of the hemodynamic response, fMRI can detect a cascade of neural activations - the signature of a sequence of cognitive processes. Decomposing the processing into stages is greatly aided by measuring intermediate responses. By combining event-related fMRI and behavioral measurement in experiment and analysis, trial-by-trial temporal links can be established between cognition and its neural substrate.

Keywords: Brain/*physiology ; *Brain Mapping ; Cognition/*physiology ; Human ; *Magnetic Resonance Imaging/methods

The line-bisection task has proven an especially useful clinical tool for assessment of spatial neglect syndrome in neurological patients. Here, we investigated the neural processes involved in performing this task by recording high-density event-related potentials from 128 scalp electrodes in normal observers. We characterized a robust net negative potential from 170-400 ms poststimulus presentation that correlates with line-bisection judgments. Topographic mapping shows three distinct phases to this negativity. The first phase (approximately 170-190 ms) has a scalp distribution exclusively over the right parieto-occipital and lateral occipital scalp, consistent with generators in the region of the right temporo-parietal junction and right lateral occipital cortices. The second phase (approximately 190-240 ms) sees the emergence of a second negative focus over the right central parietal scalp, consistent with subsequent involvement of right superior parietal cortices. In the third phase (approximately 240-400 ms), the topography becomes dominated by this right central parietal negativity. Inverse source modeling confirmed that right hemisphere lateral occipital, inferior parietal, and superior parietal regions were the likeliest generators of the bulk of the activity associated with this effect. The line stimuli were also presented at three contrast levels (3, 25, and 100%) in order to manipulate both the latency of stimulus processing and the relative contributions from magnocellular and parvocellular inputs. Through this manipulation, we show that the line-bisection effect systematically tracks/follows the latency of the N1 component, which is considered a temporal marker for object processing in the ventral visual stream. This pattern of effects suggests that this task invokes an allocentric (object-based) form of visuospatial attention. Further, at 3% contrast, the line-bisection effect was equivalent to the effects seen at higher contrast levels, suggesting that parvocellular inputs are not necessary for successful performance of this task.

Keywords: Adult ; Algorithms ; Attention/*physiology ; *Brain Mapping ; Cerebral Cortex/*physiology ; Electroencephalography ; Evoked Potentials, Visual/physiology ; Female ; Human ; Image Processing, Computer-Assisted ; Laterality/*physiology ; Male ; Middle Aged ; Photic Stimulation ; Psychometrics ; Space Perception/*physiology ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.

There is a growing appreciation of the importance of nonlinearities in evoked responses in fMRI, particularly with the advent of event-related fMRI. These nonlinearities are commonly expressed as interactions among stimuli that can lead to the suppression and increased latency of responses to a stimulus that are incurred by a preceding stimulus. We have presented previously a model-free characterization of these effects using generic techniques from nonlinear system identification, namely a Volterra series formulation. At the same time Buxton et al. (1998) described a plausible and compelling dynamical model of hemodynamic signal transduction in fMRI. Subsequent work by Mandeville et al. (1999) provided important theoretical and empirical constraints on the form of the dynamic relationship between blood flow and volume that underpins the evolution of the fMRI signal. In this paper we combine these system identification and model-based approaches and ask whether the Balloon model is sufficient to account for the nonlinear behaviors observed in real time series. We conclude that it can, and furthermore the model parameters that ensue are biologically plausible. This conclusion is based on the observation that the Balloon model can produce Volterra kernels that emulate empirical kernels. To enable this evaluation we had to embed the Balloon model in a hemodynamic input-state-output model that included the dynamics of perfusion changes that are contingent on underlying synaptic activation. This paper presents (i) the full hemodynamic model (ii), how its associated Volterra kernels can be derived, and (iii) addresses the model's validity in relation to empirical nonlinear characterizations of evoked responses in fMRI and other neurophysiological constraints.

Keywords: Brain/*physiology ; Cerebrovascular Circulation/*physiology ; Hemodynamic Processes/physiology ; *Magnetic Resonance Imaging ; *Models, Cardiovascular ; *Models, Neurological ; *Nonlinear Dynamics ; Support, Non-U.S. Gov't

In this fMRI study, we looked for the regions supporting interaction between cortical arousal and attention during three conditions: detection, observation, and rest. Arousal measurements were obtained from the EEG low-frequency (LF) power (5-9.5 Hz) recorded continuously together with fMRI. Whatever the condition, arousal was positively correlated with the fMRI signal of the right dorsal-lateral prefrontal and superior parietal cortices, closely overlapping regions involved in the maintenance of attention. Although the inferior temporal areas also presented a correlation with arousal during detection, path analysis suggests that this influence may be indirect, through the top-down influence of the previously mentioned network. However, those visual-processing areas could account for the correlation between arousal and performances. Lastly, the medial frontal cortex, frontal opercula, and thalamus were inversely correlated with arousal but only during detection and observation so that they could account for the control of arousal.

Keywords: Adult ; Arousal/*physiology ; Attention/*physiology ; Brain Mapping/methods ; Comparative Study ; Electroencephalography/*methods ; Female ; Humans ; Magnetic Resonance Imaging/methods ; Male ; Photic Stimulation ; Reaction Time/physiology ; Reference Values ; Research Support, Non-U.S. Gov't ; Visual Perception/physiology

Minimum norm algorithms for EEG source reconstruction are studied in view of their spatial resolution, regularization, and lead-field normalization properties, and their computational efforts. Two classes of minimum norm solutions are examined: linear least squares methods and nonlinear L1-norm approaches. Two special cases of linear algorithms, the well known Minimum Norm Least Squares and an implementation with Laplacian smoothness constraints, are compared to two nonlinear algorithms comprising sparse and standard L1-norm methods. In a signal-to-noise-ratio framework, two of the methods allow automatic determination of the optimum regularization parameter. Compensation methods for the different depth dependencies of all approaches by lead-field normalization are discussed. Simulations with tangentially and radially oriented test dipoles at two different noise levels are performed to reveal and compare the properties of all approaches. Finally, cortically constrained versions of the algorithms are applied to two epileptic spike data sets and compared to results of single equivalent dipole fits and spatiotemporal source models.

Keywords: Algorithms ; Electroencephalography/*methods ; Epilepsy/*diagnosis/pathology/physiopathology ; Female ; Human ; Image Interpretation, Computer-Assisted ; Linear Models ; Magnetic Resonance Imaging/*methods ; Male ; Nonlinear Dynamics ; Signal Processing, Computer-Assisted

OBJECTIVES: A framework for combining bioelectric and biomagnetic data is presented. The data are transformed to signal-to-noise ratios and reconstruction algorithms utilizing a new regularization approach are introduced. METHODS: Extensive simulations are carried out for 19 different EEG and MEG montages with radial and tangential test dipoles at different eccentricities and noise levels. The methods are verified by real SEP/SEF measurements. A common realistic volume conductor is used and the less well known in vivo conductivities are matched by calibration to the magnetic data. Single equivalent dipole fits as well as spatio-temporal source models are presented for single and combined modality evaluations and overlaid to anatomic MR images. RESULTS: Normalized sensitivity and dipole resolution profiles of the different EEG/MEG acquisition systems are derived from the simulated data. The methods and simulations are verified by simultaneously measured somatosensory data. CONCLUSIONS: Superior spatial resolution of the combined data studies is revealed, which is due to the complementary nature of both modalities and the increased number of sensors. A better understanding of the underlying neuronal processes can be achieved, since an improved differentiation between quasi-tangential and quasi-radial sources is possible.

Keywords: *Brain Mapping ; *Computer Simulation ; Electroencephalography/*methods/standards ; Evoked Potentials, Somatosensory/physiology ; Head ; Human ; Image Processing, Computer-Assisted ; Magnetoencephalography/*methods/standards ; Software

This paper presents a method for estimating the conditional or posterior distribution of the parameters of deterministic dynamical systems. The procedure conforms to an EM implementation of a Gauss-Newton search for the maximum of the conditional or posterior density. The inclusion of priors in the estimation procedure ensures robust and rapid convergence and the resulting conditional densities enable Bayesian inference about the model parameters. The method is demonstrated using an input-state-output model of the hemodynamic coupling between experimentally designed causes or factors in fMRI studies and the ensuing BOLD response. This example represents a generalization of current fMRI analysis models that accommodates nonlinearities and in which the parameters have an explicit physical interpretation. Second, the approach extends classical inference, based on the likelihood of the data given a null hypothesis about the parameters, to more plausible inferences about the parameters of the model given the data. This inference provides for confidence intervals based on the conditional density.

Keywords: *Bayes Theorem ; Brain/*physiology ; Cerebrovascular Circulation ; Hemodynamic Processes ; Humans ; Likelihood Functions ; *Magnetic Resonance Imaging ; Models, Cardiovascular ; Models, Neurological ; Nonlinear Dynamics ; Oxygen/blood ; Probability ; Research Support, Non-U.S. Gov't ; Statistics/methods

Keywords: Animals ; Cats ; Cattle ; Dogs ; Electric Conductivity ; *Electrodiagnosis ; *Electrophysiology ; Guinea Pigs ; Human ; Rabbits

The purpose of this study was the development of a real-time filtering procedure of MRI artifacts in order to monitor the EEG activity during continuous EEG/fMRI acquisition. The development of a combined EEG and fMRI technique has increased in the past few years. Preliminary spike-triggered applications have been possible because in this method, EEG knowledge was only necessary to identify a trigger signal to start a delayed fMRI acquisition. In this way, the two methods were used together but in an interleaved manner. In real simultaneous applications, like event-related fMRI study, artifacts induced by MRI events on EEG traces represent a substantial obstacle for a right analysis. Up until now, the methods proposed to solve this problem are mainly based on procedures to remove post-processing artifacts without the possibility to control electrophysiological behavior of the patient during fMRI scan. Moreover, these methods are not characterized by a strong prior knowledge of the artifact, which is an imperative condition to avoid any loss of information on the physiological signals recovered after filtering. In this work, we present a new method to perform simultaneous EEG/fMRI study with real-time artifacts filtering characterized by a procedure based on a preliminary analytical study of EPI sequence parameters-related EEG-artifact shapes. Standard EEG equipment was modified in order to work properly during ultra-fast MRI acquisitions. Changes included: high-performance acquisition device; electrodes/cap/wires/cables materials and geometric design; shielding box for EEG signal receiver; optical fiber link; and software. The effects of the RF pulse and time-varying magnetic fields were minimized by using a correct head cap wires-locked environment montage and then removed during EEG/fMRI acquisition with a subtraction algorithm that takes in account the most significant EPI sequence parameters. The on-line method also allows a further post-processing utilization.

Keywords: Algorithms ; *Artifacts ; Echo-Planar Imaging/methods ; *Electroencephalography/methods ; Human ; *Magnetic Resonance Imaging/methods ; *Signal Processing, Computer-Assisted ; Support, Non-U.S. Gov't

Modeling the haemodynamic response in functional magnetic resonance (fMRI) experiments is an important aspect of the analysis of functional neuroimages. This has been done in the past using parametric response function, from a limited family. In this contribution, we adopt a semi-parametric approach based on finite impulse response (FIR) filters. In order to cope with the increase in the number of degrees of freedom, we introduce a Gaussian process prior on the filter parameters. We show how to carry on the analysis by incorporating prior knowledge on the filters, optimizing hyper-parameters using the evidence framework, or sampling using a Markov Chain Monte Carlo (MCMC) approach. We present a comparison of our model with standard haemodynamic response kernels on simulated data, and perform a full analysis of data acquired during an experiment involving visual stimulation.

Keywords: Hemodynamic Processes/*physiology ; Humans ; *Magnetic Resonance Imaging ; Markov Chains ; Monte Carlo Method ; Normal Distribution ; Photic Stimulation

To avoid neurological impairment during surgery near language-related eloquent brain areas, we performed presurgical functional brain mapping with functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) in 172 patients using language tasks. For MEG localizations, we used either a moving equivalent-current dipole fit or a current-density reconstruction using a minimum variance beamformer with a spatial filter algorithm. We localized the Wernicke and Broca language areas for every patient. We integrated the results into a frameless stereotaxy system. To visualize the results in the navigation microscope during surgery, we superimposed the fMRI and MEG findings on the brain surface. MEG and fMRI results differed in 4 and in 19 other. In the vicinity of large gliomas, the BOLD (blood oxygenation level-dependent) effect was suppressed in 53 who had surgery, only 7 patients (5.6 transient language deterioration, which resolved in all cases. We used MEG and fMRI to show different aspects of brain activity and to establish validation between MEG and fMRI. We conclude that measurement by both MEG and fMRI increases the degree of reliability of language area localization and that the combination of fMRI and MEG is useful for presurgical localization of language-related eloquent cortex.

The analysis of functional magnetic resonance imaging (fMRI) time-series data can provide information not only about task-related activity, but also about the connectivity (functional or effective) among regions and the influences of behavioral or physiologic states on that connectivity. Similar analyses have been performed in other imaging modalities, such as positron emission tomography. However, fMRI is unique because the information about the underlying neuronal activity is filtered or convolved with a hemodynamic response function. Previous studies of regional connectivity in fMRI have overlooked this convolution and have assumed that the observed hemodynamic response approximates the neuronal response. In this article, this assumption is revisited using estimates of underlying neuronal activity. These estimates use a parametric empirical Bayes formulation for hemodynamic deconvolution.

Keywords: Bayes Theorem ; *Brain Mapping ; Hemodynamic Processes ; Human ; *Magnetic Resonance Imaging ; *Models, Neurological ; Neurons/physiology ; *Psychophysiology ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.

OBJECTIVE: Co-registration of EEG (electroencephalogram) and fMRI (functional magnetic resonance imaging) remains a challenge due to the large artifacts induced on the EEG by the MR (magnetic resonance) sequence magnetic fields. Thus, we present an algorithm, based on the average-subtraction method, which is able to correct EEG data for gradient and pulse artifacts. METHODS: MR sequence timing parameters are estimated from the EEG data and both slice and volume artifact templates are subtracted from the data. A clustering algorithm is proposed to account for the variability of the pulse artifact. RESULTS: The algorithm is able to keep the spontaneous EEG as well as visual evoked potentials (VEPs), while removing gradient and pulse artifacts with only a subtraction of selectively averaged data. In the frequency domain, the artifact frequencies are strongly attenuated. Estimated MR sequence time parameters showed that the correction is extremely sensitive to the slice time value. Pulse artifact clustering showed that most of the variability is due to the time jitter of the pulse artifact markers. CONCLUSIONS: Selective subtraction of averages in combination with proper time alignment is enough to remove most of the MR-induced artifacts. SIGNIFICANCE: Clean EEG can be obtained from raw signals that are corrupted by MR-induced artifacts during simultaneous EEG-fMRI scanning without using dedicated hardware to synchronize EEG and fMRI clocks.

OBJECTIVE: Electroencephalography (EEG) is a challenge to record simultaneously with functional MRI (fMRI), for it is prone to large artifacts induced by both the static and the time-variant fields of the MR scanner. However, truly concurrent EEG/fMRI recording has great potential for clinical and scientific neurological applications. We have devised a method for acquiring EEG simultaneously with fMRI that minimizes contamination of the EEG signals. METHODS: We recorded EEG differentially during fMRI using special twisted dual-lead electrodes in a bipolar montage, and a combination of analog pre-processing and digital post-processing of the EEG data. We implemented a functional scan protocol that typically yields artifact-free EEG over 87% of the MR scanning period. RESULTS: Our approach greatly reduced gradient, radio frequency, motion and ballistocardiographic artifact in the EEG, and allowed continuous monitoring of the EEG during functional scanning. To illustrate the quality of the EEG following post-processing, we demonstrated that EEG recorded during fMRI retains useful spectral information. CONCLUSIONS: Quality EEG may be recorded simultaneously with fMRI. With this union, activation maps could be made of any relevant changes in the EEG, such as inter-ictal spikes or spectral variations, or of evoked response potentials (ERPs).

Keywords: Brain/*anatomy & histology/*physiology ; Brain Mapping/*methods ; Electroencephalography ; Human ; Magnetic Resonance Imaging ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.

The alpha rhythm in the EEG is 8-12 Hz activity present when a subject is awake with eyes closed. In this study, we used simultaneous EEG and fMRI to make maps of regions whose MRI signal changed reliably with modulation in posterior alpha activity. We scanned 11 subjects as they rested with eyes closed. We found that increased alpha power was correlated with decreased MRI signal in multiple regions of occipital, superior temporal, inferior frontal, and cingulate cortex, and with increased signal in the thalamus and insula. These results are consistent with animal experiments and point to the alpha rhythm as an index of cortical inactivity that may be generated in part by the thalamus. These results also may have important implications for interpretation of resting baseline in fMRI studies.

Keywords: Adult ; *Alpha Rhythm ; Female ; Human ; *Magnetic Resonance Imaging ; Male ; Occipital Lobe/*physiology ; Parietal Lobe/*physiology ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S. ; Thalamus/physiology

In vivo measurements of equivalent resistivities of skull (rho(skull)) and brain (rho(brain)) are performed for six subjects using an electric impedance tomography (EIT)-based method and realistic models for the head. The classical boundary element method (BEM) formulation for EIT is very time consuming. However, the application of the Sherman-Morrison formula reduces the computation time by a factor of 5. Using an optimal point distribution in the BEM model to optimize its accuracy, decreasing systematic errors of numerical origin, is important because cost functions are shallow. Results demonstrate that rho(skull)/rho(brain) is more likely to be within 20 and 50 rather than equal to the commonly accepted value of 80. The variation in rho(brain)(average = 301 omega x cm, SD = 13%) and rho(skull)(average = 12230 omega x cm, SD = 18%) is decreased by half, when compared with the results using the sphere model, showing that the correction for geometry errors is essential to obtain realistic estimations. However, a factor of 2.4 may still exist between values of rho(skull)/rho(brain) corresponding to different subjects. Earlier results show the necessity of calibrating rho(brain) and rho(skull) by measuring them in vivo for each subject, in order to decrease errors associated with the electroencephalogram inverse problem. We show that the proposed method is suited to this goal.

Keywords: Adult ; Brain/*physiology ; Brain Mapping/methods ; Comparative Study ; Computer Simulation ; Electric Impedance/*diagnostic use ; Electroencephalography/methods ; Female ; Head/*physiology ; Human ; Male ; *Models, Biological ; Reproducibility of Results ; Sensitivity and Specificity ; Skull/*physiology ; Support, Non-U.S. Gov't ; Tomography/methods

Simultaneous recording of electroencephalogram/functional magnetic resonance images (EEG/fMRI) was applied to identify blood oxygenation level-dependent (BOLD) changes associated with spontaneous variations of the alpha rhythm, which is considered the hallmark of the brain resting state. The analysis was focused on inter-subject variability associated with the resting state. Data from 7 normal subjects are presented. Confirming earlier findings, three subjects showed a negative correlation between the BOLD signal and the average power time series within the alpha band (8-12 Hz) in extensive areas of the occipital, parietal and frontal lobes. In small thalamic areas, the BOLD signal was positively correlated with the alpha power. For subjects 3 and 4, who displayed two different states during the data acquisition time, it was shown that the corresponding correlation patterns were different, thus demonstrating the state dependency of the results. In subject 5, the changes in BOLD were observed mainly in the frontal and temporal lobes. Subject 6 only showed positive correlations, thus contradicting the negative BOLD alpha power cortical correlations that were found in most subjects. Results suggest that the resting state varies over subjects and, sometimes, even within one subject. As the resting state plays an important role in many fMRI experiments, the inter-subject variability of this state should be addressed when comparing fMRI results from different subjects.

This paper proposes and implements biophysical constraints to select a unique solution to the bioelectromagnetic inverse problem. It first shows that the brain's electric fields and potentials are predominantly due to ohmic currents. This serves to reformulate the inverse problem in terms of a restricted source model permitting noninvasive estimations of Local Field Potentials (LFPs) in depth from scalp-recorded data. Uniqueness in the solution is achieved by a physically derived regularization strategy that imposes a spatial structure on the solution based upon the physical laws that describe electromagnetic fields in biological media. The regularization strategy and the source model emulate the properties of brain activity's actual generators. This added information is independent of both the recorded data and head model and suffices for obtaining a unique solution compatible with and aimed at analyzing experimental data. The inverse solution's features are evaluated with event-related potentials (ERPs) from a healthy subject performing a visuo-motor task. Two aspects are addressed: the concordance between available neurophysiological evidence and inverse solution results, and the functional localization provided by fMRI data from the same subject under identical experimental conditions. The localization results are spatially and temporally concordant with experimental evidence, and the areas detected as functionally activated in both imaging modalities are similar, providing indices of localization accuracy. We conclude that biophysically driven inverse solutions offer a novel and reliable possibility for studying brain function with the temporal resolution required to advance our understanding of the brain's functional networks.

Keywords: Biophysics/*methods ; Brain Mapping/*methods ; Cerebral Cortex/*physiology ; Dominance, Cerebral/physiology ; Electroencephalography/*methods ; Evoked Potentials/physiology ; Human ; Image Processing, Computer-Assisted/*methods ; Imaging, Three-Dimensional/*methods ; Linear Models ; *Mathematical Computing ; *Models, Neurological ; Motor Cortex/physiology ; Nerve Net/physiology ; Psychomotor Performance/*physiology ; Reaction Time/physiology ; Support, Non-U.S. Gov't

The temporal characteristics of the BOLD response in sensorimotor and auditory cortices were measured in subjects performing finger tapping while listening to metronome pacing tones. A repeated trial paradigm was used with stimulus durations of 167 ms to 16 s and intertrial times of 30 s. Both cortical systems were found to be nonlinear in that the response to a long stimulus could not be predicted by convolving the 1-s response with a rectangular function. In the short-time regime, the amplitude of the response varied only slowly with stimulus duration. It was found that this character was predicted with a modification to Buxton's balloon model. Wiener deconvolution was used to deblur the response to concatenated short episodes of finger tapping at different temporal separations and at rates from 1 to 4 Hz. While the measured response curves were distorted by overlap between the individual episodes, the deconvolved response at each rate was found to agree well with separate scans at each of the individual rates. Thus, although the impulse response cannot predict the response to fully overlapping stimuli, linear deconvolution is effective when the stimuli are separated by at least 4 s. The deconvolution filter must be measured for each subject using a short-stimulus paradigm. It is concluded that deconvolution may be effective in diminishing the hemodynamically imposed temporal blurring and may have potential applications in quantitating responses in eventrelated fMRI.

Keywords: Acoustic Stimulation ; Auditory Cortex/*physiology ; Data Interpretation, Statistical ; Evoked Potentials, Auditory/*physiology ; Human ; Image Processing, Computer-Assisted ; Magnetic Resonance Imaging/*methods ; Nonlinear Dynamics ; Oxygen/*blood ; Somatosensory Cortex/*physiology ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.

A probabilistic multiple source solution for the bioelectromagnetic inverse problem is described. The model-dependent solution assumes a finite number of discrete primary sources at fixed locations within a bounded conductor. Covariance statistics derived from a set of detectors outside the conducting region are used to determine a metric on the space of possible sources. This metric function is used to construct a weighted pseudo-inverse matrix, which, in turn, may be used to estimate the spatio-temporal distribution of source activity. The results are embodied in the form of the PROMS (probabilistic reconstruction of (multiple sources) algorithm. Computer simulations using the algorithm are described. These methods are compared with other algorithms, including minimum norm estimation, and the MUSIC and spatial filtering algorithms.

Synthetic Aperture Magnetometry (SAM) is a beamformer approach for the localisation of neuronal activity from EEG/MEG data. SAM estimates the optimum orientation of each source in a predefined source space by a nonlinear search for the orientation that maximises the beamformer output. However, MEG is most sensitive to cortical sources and these sources are generally oriented perpendicular to the surface. The reconstructed neuronal activity can therefore reasonably be constrained to the cortical surface, orientated perpendicular to it, therefore removing the search for the optimum orientation for the computation of the beamformer weights. This paper sets out to compare the performance of a constrained and unconstrained beamformer (SAM), with respect to the localisation accuracy of the source reconstructions and the spatial resolution. Fifty sources were randomly placed on a cortical surface estimated from an MRI, and we simulated data over a range of different signal-to-noise ratios (SNRs) for each source. These datasets were analysed using both an unconstrained beamformer (SAM) and a constrained beamformer (with the sources orientated perpendicular to the cortical surface). The influence of errors in the estimation of the surface location and surface normals on the performance of the constrained beamformer, representing MEG/MRI coregistration and segmentation errors, were also examined. The spatial resolution of the beamformer improves, typically by a factor of four by applying anatomical constraints, and the localisation accuracy improves marginally. However, the advantage in spatial resolution disappears when errors are introduced into the orientation and location constraints, and, moreover, the localisation accuracy of the inaccurately constrained beamformer degrades rapidly. We conclude that the use of anatomical constraints is only advantageous if the MEG/MRI coregistration error is smaller than 2 mm and the error in the estimation of the cortical surface orientation is smaller than 10 degrees.

Keywords: Algorithms ; Brain/*anatomy & histology ; Computer Simulation ; Human ; Image Interpretation, Computer-Assisted ; Magnetic Resonance Imaging ; Magnetoencephalography/*instrumentation ; Nonlinear Dynamics ; Support, Non-U.S. Gov't

The purpose of this study was to develop a method for obtaining simultaneous electrophysiological and functional magnetic resonance imaging data. Using phantom experiments and tests on several of the investigators, a method for obtaining simultaneous electrophysiological and fMRI data was developed and then tested in three volunteers including two task activation experiments. It was then applied in a sleep experiment (n = 12). Current limiting resistance and low-pass filtering were added to the electrophysiological circuit. Potential high frequency current loops were avoided in the electrical layout near the subject. MRI was performed at 1.5 T using conventional and echo planar imaging sequences. There was no evidence of subject injury. Expected correlations were observed between the electrophysiological and fMRI data in the task activation experiments. The fMRI data were not significantly degraded by the electrophysiological apparatus. Alpha waves were detected from within the magnet in seven of the 15 experimental sessions. There was degradation of the electrophysiological data due to ballistocardiographic artifacts (pulsatile whole body motion time-locked to cardiac activity) which varied between subjects from being minimal to becoming large enough to make detection of alpha waves difficult. We conduded that simultaneous fMRI and electrophysiological recording is possible with minor modifications of standard electrophysiological equipment. Our initial results suggest this can be done safely and without compromise of the fMRI data. The usefulness of this technique for studies of such things as sleep and epilepsy is promising. Applications requiring higher precision electrophysiological data, such as evoked response measurements, may require modifications based on ballistocardiographic effects.

Keywords: Artifacts ; Brain/*physiology ; Echo-Planar Imaging ; Electroencephalography/*methods ; Human ; Magnetic Resonance Imaging ; Movement/*physiology

Electromagnetic fields as measured with electroencephalogram (EEG) are a direct consequence of neuronal activity and feature the same timescale as the underlying cognitive processes, while hemodynamic signals as measured with functional magnetic resonance imaging (fMRI) are related to the energy consumption of neuronal populations. It is obvious that a combination of both techniques is a very attractive aim in neuroscience, in order to achieve both high temporal and spatial resolution for the non-invasive study of cognitive brain function. During the last decade a number of research groups have taken up this challenge. Here, we review the development of the combined EEG-fMRI approach. We summarize the main data integration approaches developed to achieve such a combination, discuss the current state-of-the-art in this field and outline challenges for the future success of this promising approach.

This article gives an overview of the different functional brain imaging methods, the kinds of questions these methods try to address and some of the questions associated with functional neuroimaging data for which neural modeling must be employed to provide reasonable answers.

Keywords: Brain/metabolism/*physiology ; *Brain Mapping/methods ; Cerebrovascular Circulation ; Cognition/*physiology ; Hemodynamic Processes ; Human ; Magnetic Resonance Imaging ; Nerve Net ; Neurons/physiology ; Tomography, Emission-Computed ; Tomography, Emission-Computed, Single-Photon

In this study, we have preformed simultaneous near-infrared spectroscopy (NIRS) along with BOLD (blood oxygen level dependent) and ASL (arterial spin labeling)-based fMRI during an event-related motor activity in human subjects in order to compare the temporal dynamics of the hemodynamic responses recorded in each method. These measurements have allowed us to examine the validity of the biophysical models underlying each modality and, as a result, gain greater insight into the hemodynamic responses to neuronal activation. Although prior studies have examined the relationships between these two methodologies through similar experiments, they have produced conflicting results in the literature for a variety of reasons. Here, by employing a short-duration, event-related motor task, we have been able to emphasize the subtle temporal differences between the hemodynamic parameters with a high contrast-to-noise ratio. As a result of this improved experimental design, we are able to report that the fMRI measured BOLD response is more correlated with the NIRS measure of deoxy-hemoglobin (R = 0.98; P < 10(-20)) than with oxy-hemoglobin (R = 0.71), or total hemoglobin (R = 0.53). This result was predicted from the theoretical grounds of the BOLD response and is in agreement with several previous works [Toronov, V.A.W., Choi, J.H., Wolf, M., Michalos, A., Gratton, E., Hueber, D., 2001. Investigation of human brain hemodynamics by simultaneous near-infrared spectroscopy and functional magnetic resonance imaging. Med. Phys. 28 (4) 521-527.; MacIntosh, B.J., Klassen, L.M., Menon, R.S., 2003. Transient hemodynamics during a breath hold challenge in a two part functional imaging study with simultaneous near-infrared spectroscopy in adult humans. NeuroImage 20 1246-1252.; Toronov, V.A.W., Walker, S., Gupta, R., Choi, J.H., Gratton, E., Hueber, D., Webb, A., 2003. The roles of changes in deoxyhemoglobin concentration and regional cerebral blood volume in the fMRI BOLD signal Neuroimage 19 (4) 1521-1531]. These data have also allowed us to examine more detailed measurement models of the fMRI signal and comment on the roles of the oxygen saturation and blood volume contributions to the BOLD response. In addition, we found high correlation between the NIRS measured total hemoglobin and ASL measured cerebral blood flow (R = 0.91; P < 10(-10)) and oxy-hemoglobin with flow (R = 0.83; P < 10(-05)) as predicted by the biophysical models. Finally, we note a significant amount of cross-modality, correlated, inter-subject variability in amplitude change and time-to-peak of the hemodynamic response. The observed co-variance in these parameters between subjects is in agreement with hemodynamic models and provides further support that fMRI and NIRS have similar vascular sensitivity.

Keywords: Adult ; Biological Markers ; Brain Chemistry/physiology ; Cerebral Arteries/anatomy & histology/*physiology ; Cerebrovascular Circulation/*physiology ; Comparative Study ; *Electron Spin Resonance Spectroscopy ; Female ; Fingers/physiology ; Humans ; *Magnetic Resonance Imaging ; Male ; Middle Aged ; Movement/*physiology ; Oxygen/*blood ; Reproducibility of Results ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; *Spectroscopy, Near-Infrared ; Vitamin E/metabolism ; Vitamins/metabolism

This chapter provides a comprehensive survey of the motivations, assumptions and pitfalls associated with combining signals such as fMRI with EEG or MEG. Our initial focus in the chapter concerns mathematical approaches for solving the localization problem in EEG and MEG. Next we document the most recent and promising ways in which these signals can be combined with fMRI. Specifically, we look at correlative analysis, decomposition techniques, equivalent dipole fitting, distributed sources modeling, beamforming, and Bayesian methods. Due to difficulties in assessing ground truth of a combined signal in any realistic experiment-a difficulty further confounded by lack of accurate biophysical models of BOLD signal-we are cautious to be optimistic about multimodal integration. Nonetheless, as we highlight and explore the technical and methodological difficulties of fusing heterogeneous signals, it seems likely that correct fusion of multimodal data will allow previously inaccessible spatiotemporal structures to be visualized and formalized and thus eventually become a useful tool in brain imaging research.

Keywords: EEG, MEG, fMRI, MRI, multimodal analysis, fusion

In magnetoencepholography(MEG) inverse research, according to the point source model and distributed source model, the neuromagnetic source reconstruction methods are classified as parametric current dipole localization and nonparametric source imaging (or current density reconstruction). MEG source imaging technique can be formulated as an inherent ill-posed and highly underdetermined linear inverse problem. In order to yield a robust and plausible neural current distribution image, various approaches have been proposed. Among those, the weighted minimum-norm estimation with Tikhonov regularization is a popular technique. The authors present a relatively overall theoretical framework Followed by a discussion of the development, several regularized minimum-norm algorithms have been described in detail, including the depth normalization, low resolution electromagnetic tomography(LORETA), focal underdetermined system solver(FOCUSS), selective minimum-norm(SMN). In addition, some other imaging methods, e.g., maximum entropy method(MEM), the method incorporating other brain functional information such as fMRI data and maximum a posteriori(MAP) method using Markov random field model, are explained as well. From the generalized point of view based on minimum-norm estimation with Tikhonov regularization, all these algorithms are aiming to resolve the tradeoff between fidelity to the measured data and the constraints assumptions about the neural source configuration such as anatomical and physiological information. In conclusion, almost all the source imaging approaches can be consistent with the regularized minimum-norm estimation to some extent.

Keywords: *Algorithms ; Bayes Theorem ; English Abstract ; Image Processing, Computer-Assisted/*methods ; *Magnetoencephalography ; Models, Statistical ; Nonlinear Dynamics ; Support, Non-U.S. Gov't

We investigated the characteristics of the hemodynamic response (HDR) to paired presentations of visual face stimuli using functional magnetic resonance imaging (fMRI). Photographs of faces were presented singly or in pairs with either a 1-s or 6-s intrapair interval (IPI). Each trial (single face or face pairs) was followed by an intertrial interval of 16-20 s. Faces were presented at fixation and passively viewed by the 10 subjects. Images were acquired at 1.5 Tesla using a gradient-echo echo-planar imaging sequence sensitive to blood-oxygenation-level-dependent (BOLD) contrast. To examine the refractory properties of the HDR, we subtracted the single-stimulus hemodynamic response from the composite response evoked by face pairs for all voxels significantly active on single face trials. The residual represents the contribution of the second stimulus to the fMRI signal. Event-related presentation of faces evoked activity in medial calcarine cortex and the fusiform gyrus bilaterally. In both calcarine and fusiform regions, the hemodynamic response to the second face in a pair was of lower amplitude and of increased latency at 1 s IPI, with significant recovery of both amplitude and latency toward single-stimulus values at 6 s IPI. At 1 s IPI, significantly greater recovery was found in posterior fusiform regions (50-60%) than in midfusiform regions (10-40%). These regional differences were not apparent at 6 s IPI. No differences were found across slices in calcarine cortex. There was a significant difference in mean latency to HDR peak between calcarine and fusiform cortex, with the HDR peaking about 400 ms earlier in calcarine cortex. We conclude that characteristics of the HDR, notably its amplitude, latency, and refractory properties, differ across visual cortical areas.

Keywords: Adult ; Arousal/*physiology ; Attention/*physiology ; Brain Mapping ; Echo-Planar Imaging ; Evoked Potentials, Visual/physiology ; Face ; Female ; Hemodynamic Processes/*physiology ; Human ; Image Enhancement ; *Magnetic Resonance Imaging ; Male ; Oxygen Consumption/physiology ; Pattern Recognition, Visual/*physiology ; Reaction Time ; Refractory Period, Neurologic/*physiology ; Regional Blood Flow/physiology ; Support, U.S. Gov't, Non-P.H.S. ; Support, U.S. Gov't, P.H.S. ; Visual Cortex/*blood supply

The temporal dynamics of fMRI responses can span a broad range, indicating a rich underlying physiology, but also posing a significant challenge for detection. For instance, in human auditory cortex, prolonged sound stimuli ( approximately 30 sec) can evoke responses ranging from sustained to highly phasic (i.e., characterized by prominent peaks just after sound onset and offset). In the present study, we developed a method capable of detecting a wide variety of responses, while simultaneously extracting information about individual response components, which may have different neurophysiological underpinnings. Specifically, we implemented the general linear model using a novel set of basis functions chosen to reflect temporal features of cortical fMRI responses. This physiologically-motivated basis set (the OSORU basis set) was tested against (1) the commonly employed sustained-only basis set (i.e., a single smoothed boxcar function), and (2) a sinusoidal basis set, which is capable of detecting a broad range of responses, but lacks a direct relationship to individual response components. On data that included many different temporal responses, the OSORU basis set performed far better overall than the sustained-only set, and as well or better than the sinusoidal basis set. The OSORU basis set also proved effective in exploring brain physiology. As an example, we demonstrate that the OSORU basis functions can be used to spatially map the relative amount of transient vs. sustained activity within auditory cortex. The OSORU basis set provides a powerful means for response detection and quantification that should be broadly applicable to any brain system and to both human and non-human species.

Keywords: Acoustic Stimulation ; Auditory Cortex/*physiology ; Brain Mapping ; Cerebral Cortex/physiology ; Evoked Potentials, Auditory ; Humans ; Linear Models ; Magnetic Resonance Imaging/*methods ; Research Support, Non-U.S. Gov't ; Time Factors

We introduce model averaging in neuroimaging. We show that model summary images can be directly compared and averaged after histogram equalization. We demonstrate that averaging enhances the ROC curve in a simulation study. The averaging procedure is applied to a fMRI study of motor cortex.

Keywords: Brain Mapping ; Echo-Planar Imaging ; Fingers/innervation ; Humans ; *Image Enhancement ; *Image Processing, Computer-Assisted ; *Magnetic Resonance Imaging ; Models, Statistical ; Motor Activity/physiology ; Motor Cortex/*physiology ; Nerve Net/physiology ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S.

OBJECTIVES: We developed a method to register EEG and MRI data used for the source reconstruction of electric brain activity. METHODS: The method is based on matching of the head surfaces as obtained by 3D scanning after the EEG recording, and by segmentation of MRI data. The registration accuracy was estimated by calculating the residual error of the surface matching and its intra-individual and inter-individual variability. In addition, the test-retest reliability concerning the transformation of electrode positions was studied, to estimate how inaccuracies resulting from the 3D scanning of the head surface translate into registration uncertainty. RESULTS: For 61 measurements, performed on 20 subjects, the average root mean square of the Euclidean distances between the 3D-scanned and the MRI-derived head surfaces amounted to 3.4 mm. An inter-individual standard deviation of 0.24 mm, and an intraindividual standard deviation of 0.003-0.31 mm proved a high inter- and intra-subject stability of the surface matching technique. The variation of transformation results when studying the test-retest reliability amounted to 1.6 mm on average. The maximum error of transformation was smaller than the diameter of the electrodes. CONCLUSIONS: The findings suggest that the surface matching technique is a precise method for determination of the transformation of electrode positions and MRI data into a single co-ordinate system and can successfully be used in a routine laboratory setting.

Keywords: Brain/anatomy & histology/physiology ; *Electroencephalography ; Head/anatomy & histology ; Human ; Image Processing, Computer-Assisted/*methods ; *Magnetic Resonance Imaging ; Reproducibility of Results

Keywords: Algorithms ; Brain Mapping/*methods ; *Electroencephalography/standards ; Human ; Image Enhancement ; Image Processing, Computer-Assisted/methods ; *Magnetic Resonance Imaging/standards ; *Magnetoencephalography/standards ; Neural Networks (Computer) ; *Tomography, Emission-Computed/standards

Face perception is typically associated with activation in the inferior occipital, superior temporal (STG), and fusiform gyri (FG) and with an occipitotemporal electrophysiological component peaking around 170 ms on the scalp, the N170. However, the relationship between the N170 and the multiple face-sensitive activations observed in neuroimaging is unclear. It has been recently shown that the amplitude of the N170 component monotonically decreases as gaussian noise is added to a picture of a face [Jemel et al., 2003]. To help clarify the sources of the N170 without a priori assumptions regarding their number and locations, ERPs and fMRI were recorded in five subjects in the same experiment, in separate sessions. We used a parametric paradigm in which the amplitude of the N170 was modulated by varying the level of noise in a picture, and identified regions where the percent signal change in fMRI correlated with the ERP data. N170 signals were observed for pictures of both cars and faces but were stronger for faces. A monotonic decrease with added noise was observed for the N170 at right hemisphere sites but was less clear on the left and occipital central sites. Correlations between fMRI signal and N170 amplitudes for faces were highly significant (P < 0.001) in bilateral fusiform gyrus and superior temporal gyrus. For cars, the strongest correlations were observed in the parahippocampal region and in the STG (P < 0.005). Besides contributing to clarify the spatiotemporal course of face processing, this study illustrates how ERP information may be used synergistically in fMRI analyses. Parametric designs may be developed further to provide some timing information on fMRI activity and help identify the generators of ERP signals.

In this paper, the computational and practical aspects of a realistically-shaped multilayer model for the conductivity geometry of the human head are discussed. A novel way to handle the numerical difficulties caused by the presence of the poorly conducting skull is presented. Using our method, both the potential on the surface of the head and the magnetic field outside the head can be computed accurately. The procedure was tested with the multilayer sphere model, for which analytical expressions are available. The method is then applied to a realistically-shaped head model, and it is numerically shown that for the computation of B, produced by cerebral current sources, it is sufficient to consider a brain-shaped homogeneous conductor only since the secondary currents on the outer interfaces give only a negligible contribution to the magnetic field outside the head. Comparisons with the sphere model are also included to pinpoint areas where the homogeneous conductor model provides essential improvements in the calculation of the magnetic field outside the head.

Keywords: Brain/physiology ; Electric Conductivity ; *Electromagnetic Fields ; *Electromagnetics ; Head/*anatomy & histology ; Human ; Models, Anatomic ; Models, Biological ; Support, Non-U.S. Gov't

A parametric method is proposed to examine the relationship between neuronal activity, measured with event related potentials (ERPs), and the hemodynamic response, observed with functional magnetic resonance imaging (fMRI), during an auditory oddball paradigm. After verifying that the amplitude of the evoked response P300 increases as the probability of oddball target presentation decreases, we explored the corresponding effect of target frequency on the fMRI signal. We predicted and confirmed that some regions that showed activation changes following each oddball are affected by the rate of presentation of the oddballs, or the probability of an oddball target. We postulated that those regions that increased activation with decreasing probability might be responsible for the corresponding changes in the P300 amplitude. fMRI regions that correlated with the amplitude of the P300 wave were supramarginal gyri, thalamus, insula and right medial frontal gyrus, and are presumably sources of the P300 wave. Other regions, such as anterior and posterior cingulate cortex, were activated during the oddball paradigm but their fMRI signal changes were not correlated with the P300 amplitudes. This study thus shows how combining fMRI and ERP in a parametric design identifies task-relevant sources of activity and allows separation of regions that have different response properties.

Keywords: Acoustic Stimulation ; Adult ; Brain/anatomy & histology/*physiology ; *Event-Related Potentials, P300/physiology ; Female ; Human ; Magnetic Resonance Imaging/*methods ; Male

Temporal clustering analysis (TCA) is an exploratory data-driven technique that has been proposed for the analysis of resting fMRI to localise epileptiform activity without need for simultaneous EEG. Conventionally, fMRI of epileptic activity has been limited to those patients with subtle clinical events or frequent interictal epileptiform EEG discharges, requiring simultaneous EEG recording, from which a linear model is derived to make valid statistical inferences from the fMRI data. We sought to evaluate TCA by comparing the results with those of EEG correlated fMRI in eight selected cases. Cases were selected with clear epileptogenic localisation or lateralisation on the basis of concordant EEG and structural MRI findings, in addition to concordant activations seen on EEG-derived fMRI analyses. In three, areas of activation were seen with TCA but none corresponding to the electro-clinical localisation or activations obtained with EEG driven analysis. Temporal clusters were closely coincident with times of maximal head motion. We feel this is a serious confound to this approach and recommend that interpretation of TCA that does not address motion and physiological noise be treated with caution. New techniques to localise epileptogenic activity with fMRI alone require validation with an appropriate independent measure. In the investigation of interictal epileptiform activity, this is best done with simultaneous EEG recording.

Keywords: Cluster Analysis ; Comparative Study ; Electrocardiography ; *Electroencephalography ; Epilepsies, Partial/*pathology/*physiopathology ; Humans ; Image Processing, Computer-Assisted ; Magnetic Resonance Imaging ; Research Support, Non-U.S. Gov't

A number of beamformers have been introduced to localize neuronal activity using magnetoencephalography (MEG) and electroencephalography (EEG). However, currently available information about the major aspects of existing beamformers is incomplete. In the present study, detailed analyses are performed to study the commonalities and differences among vectorized versions of existing beamformers in both theory and practice. In addition, a novel beamformer based on higher-order covariance analysis is introduced. Theoretical formulas are provided on all major aspects of each beamformer; to examine their performance, computer simulations with different levels of correlation and signal-to-noise ratio are studied. Then, an empirical data set of human MEG median-nerve responses with a large number of neuronal generators is analyzed using the different beamformers. The results show substantial differences among existing MEG/EEG beamformers in their ways of describing the spatial map of neuronal activity. Differences in performance are observed among existing beamformers in terms of their spatial resolution, false-positive background activity, and robustness to highly correlated signals. Superior performance is obtained using our novel beamformer with higher-order covariance analysis in simulated data. Excellent agreement is also found between the results of our beamformer and the known neurophysiology of the median-nerve MEG response.

Keywords: Brain/cytology/*radiation effects ; Brain Mapping ; Comparative Study ; *Electroencephalography ; Electromagnetics/methods ; Evoked Potentials/radiation effects ; Human ; Image Interpretation, Computer-Assisted ; Least-Squares Analysis ; *Magnetoencephalography ; Median Nerve/physiology/radiation effects ; *Models, Neurological ; Neurons/physiology/radiation effects ; Signal Processing, Computer-Assisted ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, Non-P.H.S. ; Support, U.S. Gov't, P.H.S. ; Time Factors

We investigated the neural basis of auditory object processing in the cerebral cortex by combining neural modeling and functional neuroimaging. We developed a large-scale, neurobiologically realistic network model of auditory pattern recognition that relates the neuronal dynamics of cortical auditory processing of frequency modulated (FM) sweeps to functional neuroimaging data of the type obtained using PET and fMRI. Areas included in the model extend from primary auditory to prefrontal cortex. The electrical activities of the neuronal units of the model were constrained to agree with data from the neurophysiological literature regarding the perception of FM sweeps. We also conducted an fMRI experiment using stimuli and tasks similar to those used in our simulations. The integrated synaptic activity of the neuronal units in each region of the model, convolved with a hemodynamic response function, was used as a correlate of the simulated fMRI activity, and generally agreed with the experimentally observed fMRI data in the brain areas corresponding to the regions of the model. Our results demonstrate that the model is capable of exhibiting the salient features of both electrophysiological neuronal activities and fMRI values that are in agreement with empirically observed data. These findings provide support for our hypotheses concerning how auditory objects are processed by primate neocortex.

Keywords: Adult ; Auditory Cortex/physiology ; Auditory Pathways/physiology ; Auditory Perception/*physiology ; Brain Mapping ; Cerebral Cortex/*physiology ; Dominance, Cerebral/physiology ; Female ; Human ; *Image Enhancement ; *Image Processing, Computer-Assisted ; *Imaging, Three-Dimensional ; *Magnetic Resonance Imaging ; Male ; Memory, Short-Term/physiology ; *Neural Networks (Computer) ; Neurons/physiology ; Oxygen/*blood ; Pitch Perception/physiology ; Prefrontal Cortex/physiology ; Psychoacoustics ; Reference Values ; Retention (Psychology)/physiology ; Sound Localization/physiology ; Sound Spectrography ; Speech Perception/physiology ; Support, U.S. Gov't, P.H.S. ; Tomography, Emission-Computed

The influence of gray and white matter tissue anisotropy on the human electroencephalogram (EEG) and magnetoencephalogram (MEG) was examined with a high resolution finite element model of the head of an adult male subject. The conductivity tensor data for gray and white matter were estimated from magnetic resonance diffusion tensor imaging. Simulations were carried out with single dipoles or small extended sources in the cortical gray matter. The inclusion of anisotropic volume conduction in the brain was found to have a minor influence on the topology of EEG and MEG (and hence source localization). We found a major influence on the amplitude of EEG and MEG (and hence source strength estimation) due to the change in conductivity and the inclusion of anisotropy. We expect that inclusion of tissue anisotropy information will improve source estimation procedures.

Keywords: Adult ; Anisotropy ; Brain/*physiology ; Brain Mapping ; *Electroencephalography ; *Finite Element Analysis ; Human ; *Magnetoencephalography ; Male ; Reference Values ; Signal Processing, Computer-Assisted ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, Non-P.H.S.

Self-regulation of slow cortical potentials (SCPs) has been successfully used to prevent epileptic seizures as well as to communicate with completely paralyzed patients. The thought translation device (TTD) is a brain-computer interface (BCI) that was developed for training and application of SCP self-regulation. To investigate the neurophysiological mechanisms of SCP regulation the TTD was combined with functional magnetic resonance imaging (fMRI). The technical aspects and pitfalls of combined fMRI data acquisition and EEG neurofeedback are discussed. First data of SCP feedback during fMRI are presented.

Keywords: Biofeedback (Psychology)/*methods/physiology ; Cerebral Cortex/*physiology ; Electroencephalography/*methods ; Evoked Potentials/*physiology ; Feasibility Studies ; Feedback/physiology ; Hippocampus/physiology ; Humans ; Image Interpretation, Computer-Assisted/*methods ; Magnetic Resonance Imaging/*methods ; Motor Cortex/physiology ; Online Systems ; Pilot Projects ; Reproducibility of Results ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S. ; Sensitivity and Specificity ; *User-Computer Interface

The present study aims at finding the optimal inverse solution for the bioelectromagnetic inverse problem in the absence of reliable a priori information about the generating sources. Three approaches to tackle this problem are compared theoretically: the maximum-likelihood approach, the minimum norm approach, and the resolution optimization approach. It is shown that in all three of these frameworks, it is possible to make use of the same kind of a priori information if available, and the same solutions are obtained if the same a priori information is implemented. In particular, they all yield the minimum norm pseudoinverse (MNP) in the complete absence of such information. This indicates that the properties of the MNP, and in particular, its limitations like the inability to localize sources in depth, are not specific to this method but are fundamental limitations of the recording modalities. The minimum norm solution provides the amount of information that is actually present in the data themselves, and is therefore optimally suited to investigate the general resolution and accuracy limits of EEG and MEG measurement configurations. Furthermore, this strongly suggests that the classical minimum norm solution is a valuable method whenever no reliable a priori information about source generators is available, that is, when complex cognitive tasks are employed or when very noisy data (e.g., single-trial data) are analyzed. For that purpose, an efficient and practical implementation of this method will be suggested and illustrated with simulations using a realistic head geometry.

Keywords: Action Potentials/physiology ; Brain Mapping ; Cerebral Cortex/*physiology ; Computer Graphics ; Computer Simulation ; Electroencephalography/*statistics & numerical data ; Human ; *Image Processing, Computer-Assisted ; *Imaging, Three-Dimensional ; Likelihood Functions ; Magnetoencephalography/*statistics & numerical data ; Reference Values ; *Signal Processing, Computer-Assisted

Feasibility of continuously and simultaneously recording visual evoked potentials (VEPs) with fMRI was assessed by quantitatively comparing cortical source images by means of receiver operating characteristic (ROC) curve analysis. The averaged EEG source images coincided well with simultaneously acquired fMRI activations. Strong correlation was found between the cortical source images of VEPs recorded inside and outside the scanner. Application of fMRI prior information strengthened correlation between estimated source images as well as resulted in source estimates with higher spatial resolution. The present results demonstrate that reliable cortical source images can be acquired during simultaneous fMRI scanning and they may be used for multimodal functional source imaging studies.

The recording of an EEG while the patient is undergoing magnetic resonance imaging (MRI) data acquisition, as far as we are aware, has not been previously accomplished. By careful selection and arrangement of analog multiplexed cable-telemetry equipment to eliminate both ferrous and RF sources, a stable, readable EEG can be obtained without interfering with the diagnostic quality of the MRI. This arrangement does not cause localized heating or burning at the electrode sites. This technical capability permits more accurate neurophysiological control during the acquisition of echo planar functional MRI studies as well as providing indications of anatomical localization of electrical sources.

Keywords: *Echo-Planar Imaging ; Electroencephalography/*methods ; Human ; Monitoring, Physiologic

We present a novel approach to MEG source estimation based on a regularized first-order multipole solution. The Gaussian regularizing prior is obtained by calculation of the sample mean and covariance matrix for the equivalent moments of realistic simulated cortical activity. We compare the regularized multipole localization framework to the classical dipole and general multipole source estimation methods by evaluating the ability of all three solutions to localize the centroids of physiologically plausible patches of activity simulated on the surface of a human cerebral cortex. The results, obtained with a realistic sensor configuration, a spherical head model, and given in terms of field and localization error, depict the performance of the dipolar and multipolar models as a function of variable source surface area (50-500 mm(2)), noise conditions (20, 10, and 5 dB SNR), source orientation (0-90 degrees ), and source depth (3-11 cm). We show that as the sources increase in size, they become less accurately modeled as current dipoles. The regularized multipole systematically outperforms the single dipole model, increasingly so as the spatial extent of the sources increases. In addition, our simulations demonstrate that as the orientation of the sources becomes more radial, dipole localization accuracy decreases substantially, while the performance of the regularized multipole model is far less sensitive to orientation and even succeeds in localizing quasi-radial source configurations. Furthermore, our results show that the multipole model is able to localize superficial sources with higher accuracy than the current dipole. These results indicate that the regularized multipole solution may be an attractive alternative to current-dipole-based source estimation methods in MEG.

Keywords: Biomedical Engineering ; Brain/*anatomy & histology/physiology ; Evaluation Studies ; Human ; Image Processing, Computer-Assisted/methods ; *Magnetics ; Models, Theoretical ; Neurons/physiology ; Support, Non-U.S. Gov't

Electroencephalographic (EEG) monitoring during functional magnetic resonance imaging (fMRI) experiments is increasingly applied for studying physiological and pathological brain function. However, the quality of the fMRI data can be significantly compromised by the EEG recording due to the magnetic susceptibility of the EEG electrode assemblies and electromagnetic noise emitted by the EEG recording equipment. We therefore investigated the effect of individual components of the EEG recording equipment on the quality of echo planar images. The artifact associated with each component was measured and compared to the minimum scalp-cortex distance measured in normal controls. The image noise originating from the EEG recording equipment was identified as coherent noise and could be eliminated by appropriate shielding of the EEG equipment. It was concluded that concurrent EEG and fMRI could be performed without compromising the image quality significantly if suitable equipment is used. The methods described and the results of this study should be useful to other researchers as a framework for testing of their own equipment and for the selection of appropriate equipment for EEG recording inside a MR scanner.

Keywords: Adolescent ; Adult ; Artifacts ; Cerebral Cortex/anatomy & histology/physiology ; *Electroencephalography ; Female ; Human ; Image Enhancement ; *Magnetic Resonance Imaging ; Male ; Middle Aged ; Scalp/anatomy & histology/physiology ; Support, Non-U.S. Gov't

Grey matter heterotopia are commonly associated with refractory epilepsy. Depth electrodes recordings have shown that epileptiform activity can be generated within these lesions, and also at a distance in the neocortex. Heterotopia seem to be part of a more complex circuitry involving also the surrounding and distant cerebral cortex. Blood oxygenation level-dependent (BOLD) changes to interictal spikes using continuous EEG and functional MRI (EEG-fMRI) can help to understand non-invasively the mechanisms of epileptogenicity in these patients. We studied 14 patients with epilepsy and heterotopia using simultaneous recording of EEG-fMRI. EEG was continuously acquired from inside the scanner during 2 h sessions. Epileptic spikes were visually identified in the filtered EEG and each type of spike determined one EEG-fMRI study. We looked at positive (activation) and negative (deactivation) changes in the BOLD signal. Eleven patients had nodular heterotopia and three band heterotopia. Four patients had more than one type of spikes, with a total of 26 EEG-fMRI studies. We excluded three with less than three spikes, and therefore a total of 23 studies (12 with nodular and 11 with band heterotopia) were analysed. Nodular heterotopia: Activation was present in nine studies, with involvement of the heterotopia or surrounding cortex in six, three of which had concomitant distant activation. Deactivation was also observed in nine studies, with involvement of the heterotopia and surrounding cortex in four, three of which had concomitant distant deactivation. Band heterotopia: Activation was present in all 11 studies, and always involved the heterotopia and surrounding cortex, 9 of which had concomitant distant activation. Deactivation was also observed in all 11 studies, with involvement of both the heterotopia and surrounding cortex, in addition to distant deactivation in 5 studies. EEG-fMRI studies reveal, non-invasively, metabolic responses in the heterotopia despite the fact that spikes are generated in the neocortex. The responses, activation or deactivation, had different correlation with the lesion and surrounding or distant cortex, activation reflecting intense neuronal activity, or excitation, and deactivation a possible distant (extra-lesional) inhibition. EEG-fMRI may become a useful tool to understand the epileptogenicity of such malformations.

Keywords: Brain/*pathology ; Choristoma/*pathology ; *Electroencephalography ; Epilepsy/*pathology ; Female ; Humans ; *Magnetic Resonance Imaging ; Male ; Research Support, Non-U.S. Gov't

OBJECTIVEs: We developed a new technique of fully automatic alignment of brain data acquired with scalp sensors (e.g. electroencephalography/evoked potential (EP) electrodes, magnetoencephalography sensors) with a magnetic resonance imaging (MRI) volume of the head. METHODS: The method uses geometrical features (two sets of head points: digitized from the subject and extracted from MRI) to guide the alignment. It combines matching on 3 dimensional (3D) geometrical moments that perform the initial alignment, and 3D distance-based alignment that provides the final tuning. To reduce errors of the initial guessed computation resulting from digitization of the head surface points we introduced weights to compute geometrical moments, and a procedure to remove outliers to eliminate incorrectly digitized points. RESULTS: The method was tested on simulated (Monte Carlo trials) and on real data sets. The simulations demonstrated that for the number of test points within the range of 0.1-1% of the total number of head surface points and for the digitization error in the range of -2-2 mm the average map error was between 0.7 and 2.1 mm. The average distance error was less than 1 mm. Tests on real data gave the average distance error between 2.1 and 2.5 mm. CONCLUSIONS: The developed technique is fast, robust and comfortable for the patient and for medical personnel. It registers scalp sensor positions with MRI head volume with accuracy that is satisfactory for localization of biological processes examined with a commonly used number of scalp sensors (32, 64, or 128).

Keywords: Automatic Data Processing/*methods ; *Electroencephalography ; Equipment Design ; Evoked Potentials, Somatosensory/*physiology ; Head ; Human ; *Magnetic Resonance Imaging ; Magnetics ; *Models, Theoretical ; Sensitivity and Specificity

In this paper, we describe a temporal model for event-related potentials (ERP) in the context of statistical parametric mapping (SPM). In brief, we project channel data onto a two-dimensional scalp surface or into three-dimensional brain space using some appropriate inverse solution. We then treat the spatiotemporal data in a mass-univariate fashion. This implicitly factorises the model into spatial and temporal components. The key contribution of this paper is the use of observation models that afford an explicit distinction between observation error and variation in the expression of ERPs. This distinction is created by employing a two-level hierarchical model, in which the first level models the ERP effects within-subject and trial type, while the second models differences in ERP expression among trial types and subjects. By bringing the analysis of ERP data into a classical hierarchical (i.e., mixed effects) framework, many apparently disparate approaches (e.g., conventional P300 analyses and time-frequency analyses of stimulus-locked oscillations) can be reconciled within the same estimation and inference procedure. Inference proceeds in the normal way using t or F statistics to test for effects that are localised in peristimulus time or in some time-frequency window. The use of F statistics is an important generalisation of classical approaches, because it allows one to test for effects that lie in a multidimensional subspace (i.e., of unknown but constrained form). We describe the analysis procedures, the underlying theory and compare its performance to established techniques.

Keywords: Analysis of Variance ; Brain Mapping/methods ; Comparative Study ; Computer Simulation ; Event-Related Potentials, P300/physiology ; Evoked Potentials/*physiology ; Humans ; *Models, Neurological ; Models, Statistical ; Reproducibility of Results ; Research Support, Non-U.S. Gov't ; Time Factors

In this paper, we frame the strategy and motivations behind developments in statistical parametric mapping (SPM) for the analysis of electroencephalogram (EEG) data. This work deals specifically with SPM procedures for the analysis of event-related potentials (ERP). We place these developments in the larger context of integrating electrophysiological and hemodynamic measurements of evoked brain responses through the fusion of EEG and fMRI data. In this paper, we consider some fundamental issues when selecting an appropriate statistical model that enables diverse questions to be asked of the data and at the same time retains maximum sensitivity. The three key issues addressed in this paper are as follows: (i) should multivariate or mass univariate analyses be adopted, (ii) should time be treated as an experimental factor or as a dimension of the measured response variable, and (iii) how to form appropriate explanatory variables in a hierarchical observation model. We review the relative merits of the different options and explain the rationale for our choices. In brief, we motivate a mass univariate approach in terms of sensitivity to region-specific responses. This involves modeling responses at each voxel or space bin separately. In contradistinction, we treat time as an experimental factor to enable inferences about temporally distributed responses that encompass multiple time bins. In a companion paper, we develop statistical models of ERPs in the time domain that follow from the heuristics established here and illustrate the approach using simulated and real data.

Keywords: Analysis of Variance ; Brain/anatomy & histology/*physiology ; Brain Mapping ; Electroencephalography ; Evoked Potentials/*physiology ; Humans ; Magnetic Resonance Imaging ; *Models, Neurological ; Models, Statistical ; Multivariate Analysis ; Research Support, Non-U.S. Gov't ; Sensitivity and Specificity

This paper introduces the general framework, concepts, and procedures of anatomically informed basis functions (AIBF), a new method for the analysis of functional magnetic resonance imaging (fMRI) data. In contradistinction to existing voxel-based univariate or multivariate methods the approach described here can incorporate various forms of prior anatomical knowledge to specify sophisticated spatiotemporal models for fMRI time-series. In particular, we focus on anatomical prior knowledge, based on reconstructed gray matter surfaces and assumptions about the location and spatial smoothness of the blood oxygenation level dependent (BOLD) effect. After reconstruction of the grey matter surface from an individual's high-resolution T1-weighted MRI, we specify a set of anatomically informed basis functions, fit the model parameters for a single time point, using a regularized solution, and finally make inferences about the estimated parameters over time. Significant effects, induced by the experimental paradigm, can then be visualized in the native voxel-space or on the reconstructed folded, inflated, or flattened cortical surface. As an example, we apply the approach to a fMRI study (finger opposition task) and compare the results to those of a voxel-based analysis as implemented in the Statistical Parametric Mapping package (SPM99). Additionally, we show, using simulated data, that the approach offers several desirable features particularly in terms of superresolution and localization.

Keywords: Brain/*anatomy & histology/*physiology ; Cerebrovascular Circulation ; Computer Simulation ; Fingers/physiology ; Human ; Image Processing, Computer-Assisted ; Magnetic Resonance Imaging/*methods ; *Models, Anatomic ; *Models, Neurological ; Movement/physiology ; Oxygen/blood ; Support, Non-U.S. Gov't

We combined information from functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) to assess which cortical areas and in which temporal order show macroscopic activation after right median nerve stimulation. Five healthy subjects were studied with the two imaging modalities, which both revealed significant activation in the contra- and ipsilateral primary somatosensory cortex (SI), the contra- and ipsilateral opercular areas, the walls of the contralateral postcentral sulcus (PoCS), and the contralateral supplementary motor area (SMA). In fMRI, two separate foci of activation in the opercular cortex were discerned, one posteriorly in the parietal operculum (PO), and one anteriorly near the insula or frontal operculum (anterior operculum, AO). The activation sites from fMRI were used to constrain the solution of the inverse problem of MEG, which allowed us to construct a model of the temporal sequence of activation of the different sites. According to this model, the mean onset latency for significant activation at the contralateral SI was 20 msec (range, 17-22 msec), followed by activation of PoCS at 23 msec (range, 21-25 msec). The contralateral PO was activated at 26 msec (range, 19-32 msec) and AO at 33 msec (range, 22-51 msec). The contralateral SMA became active at 36 msec (range, 24-48 msec). The ipsilateral SI, PO, and AO became activated at 54-67 msec. We conclude that fMRI provides a useful means to constrain the inverse problem of MEG, allowing the construction of spatiotemporal models of cortical activation, which may have significant implications for the understanding of cortical network functioning.

Keywords: Adult ; Brain Mapping/*methods ; Cerebral Cortex/*physiology ; Human ; Magnetic Resonance Imaging ; Magnetoencephalography ; Male ; Median Nerve/*physiology ; Reaction Time ; Somatosensory Cortex/*physiology ; Support, Non-U.S. Gov't

The feasibility of recording event-related potentials (ERP) during functional MRI (fMRI) scanning using higher level cognitive stimuli was studied. Using responses to illusory figures in a visual oddball task, evoked potentials were obtained with their expected configurations and latencies. A rapid stimulation scheme using randomly varied trial lengths was employed, and class-wise characteristics of the hemodynamic response were obtained by a nonlinear analysis of the fMRI time series. Implications and limitations of conducting combined ERP-fMRI experiments using higher level cognitive stimuli are discussed. EEG/fMRI results revealed a sequential activation of striate and extrastriate occipital cortex along the ventral path of object processing for Kanizsa figures. Interestingly, Kanizsa figures activated the human motion area MT. Targets resulted in activations of frontal and parietal cortex which were not activated for standard stimuli.

Keywords: Adult ; Arousal/physiology ; Brain Mapping ; *Electroencephalography ; Evoked Potentials, Visual/physiology ; Female ; Frontal Lobe/blood supply/physiology ; Human ; *Magnetic Resonance Imaging ; Male ; Occipital Lobe/blood supply/*physiology ; Optical Illusions/*physiology ; Orientation/physiology ; Parietal Lobe/blood supply/physiology ; Pattern Recognition, Visual/*physiology ; Reference Values ; Regional Blood Flow/physiology ; Visual Cortex/blood supply/*physiology ; Visual Pathways/blood supply/physiology

EEG-triggered, blood oxygen level-dependent functional MRI (BOLD-fMRI) was used in 24 patients with localization-related epilepsy and frequent interictal epileptiform discharges (spikes) to identify those brain areas involved in generating the spikes, and to study the evolution of the BOLD signal change over time. The location of the fMRI activation was compared with the scalp EEG spike focus and the structural MR abnormality. Twelve patients (50%) had an fMRI activation concordant with the EEG focus and structural brain abnormalities where present (n = 7). In 2 other patients, the fMRI activation was non-concordant with electroclinical findings. The remaining 10 patients (41.7%) showed no significant fMRI activation. These patients had significantly lower mean spike amplitudes compared to those with positive fMRI results (p = 0.03). The time course of the BOLD response was studied in 3 patients and this revealed a maximum signal change 1.5 to 7.5 sec after the spike. In conclusion, EEG-triggered fMRI can directly identify the generators of interictal epileptiform activity, with high spatial resolution, in selected patients with frequent spikes. The superior spatial resolution obtainable through EEG-triggered fMRI may provide an additional non-invasive tool in the presurgical evaluation of patients with intractable focal seizures.

Keywords: Action Potentials/physiology ; Adolescent ; Adult ; *Electroencephalography ; Epilepsies, Partial/*pathology/*physiopathology ; Female ; Hemodynamic Processes/physiology ; Human ; *Magnetic Resonance Imaging ; Male ; Middle Aged ; Support, Non-U.S. Gov't ; Temporal Lobe/*pathology/*physiopathology

In this note we describe a heuristic, starting with a dimensional analysis, which relates hemodynamic changes to the spectral profile of ongoing EEG activity. In brief, this analysis suggests that 'activation', as indexed by increases in hemodynamic signals, should be associated with a loss of power in lower EEG frequencies, relative to higher frequencies. The fact that activation is expressed in terms of frequency (i.e., per second) is consistent with a dimensional analysis in the sense that activations reflect the rate of energy dissipation (per second). In this heuristic, activation causes an acceleration of temporal dynamics leading to (i) increased energy dissipation; (ii) decreased effective membrane time constants; (iii) increased effective coupling among neuronal ensembles; and (iv) a shift in the EEG spectral profile to higher frequencies. These predictions are consistent with empirical observations of how changes in the EEG spectrum are expressed hemodynamically. Furthermore, the heuristic provides a simple measure of neuronal activation based on spectral analyses of EEG.

In this study we investigated the spatial heterotopy of MEG and fMRI localizations after sensory and motor stimulation tasks. Both methods are frequently used to study the topology of the primary and secondary motor cortex, as well as a tool for presurgical brain mapping. fMRI was performed with a 1.5T MR system, using echo-planar imaging with a motor and a sensory task. Somatosensory and motor evoked fields were recorded with a biomagnetometer. fMRI activation was determined with a cross-correlation analysis. MEG source localization was performed with a single equivalent current dipole model and a current density localization approach. Distances between MEG and fMRI activation sites were measured within the same anatomical 3-D-MR image set. The central region could be identified by MEG and fMRI in 33 of 34 cases. However, MEG and fMRI localization results showed significantly different activation sites for the motor and sensory task with a distance of 10 and 15 mm, respectively. This reflects the different neurophysiological mechanisms: direct neuronal current flow (MEG) and secondary changes in cerebral blood flow and oxygenation level of activated versus non activated brain structures (fMRI). The result of our study has clinical implications when MEG and fMRI localizations are used for pre- and intraoperative brain mapping. Although both modalities are useful for the estimation of the motor cortex, a single modality may err in the exact topographical labeling of the motor cortex. In some unclear cases a combination of both methods should be used in order to avoid neurological deficits.

Keywords: Adolescent ; Adult ; Aged ; Aged, 80 and over ; Brain Neoplasms/physiopathology/*surgery ; Female ; Human ; *Imaging, Three-Dimensional ; *Magnetic Resonance Imaging ; *Magnetoencephalography ; Male ; Middle Aged ; Motor Cortex/physiopathology/*surgery ; Somatosensory Cortex/physiopathology/*surgery ; *Stereotaxic Techniques ; Support, Non-U.S. Gov't ; *Surgery, Computer-Assisted

We investigated a co-registration algorithm using a contour-fitting procedure to integrate functional data from magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) for frameless stereotaxy. In fMRI the shape of the head was reconstructed from anatomical images, in MEG it was scanned using an electromagnetic sensor position indicator. Functional information was transferred to the 3D-MR image set used for frameless stereotaxy by fitting the digitized (MEG) and reconstructed head shape (fMRI) to the 3D-MR images. The mean residual error of the contour fit was 2.3 mm for the MEG and 1.3 mm for the fMRI registration. According to computer simulations, the achievable transformation error is 0.75 and 0.5 mm, respectively. This method enables independent recording of functional and anatomical measurements with a co-registration accuracy better than 2 mm.

Keywords: Brain/anatomy & histology/*surgery ; Human ; Imaging, Three-Dimensional ; Magnetic Resonance Imaging/*methods ; *Magnetoencephalography ; Models, Biological ; Neuronavigation/*methods ; Surgery, Computer-Assisted/methods

Despite the ubiquitous use of functional magnetic resonance imaging (fMRI), the extent to which the magnitude and spatial scale of the fMRI signal correlates with neuronal activity is poorly understood. In this study, we directly compared single and multiunit neuronal activity with blood oxygenation level-dependent (BOLD) fMRI responses across a large area of the cat area 18. Our data suggest that at the scale of several millimeters, the BOLD contrast correlates linearly with the underlying neuronal activity. At the level of individual electrode recording sites, however, the correlation between the two signals varied substantially. We conclude from our study that T(2)*-based positive BOLD signals are a robust predictor for neuronal activity only at supra-millimeter spatial scales.

Keywords: Animals ; Brain/cytology/*physiology ; Cats ; Cerebral Cortex/cytology/physiology ; Cerebrovascular Circulation/physiology ; Electrodes, Implanted ; Magnetic Resonance Imaging ; Neurons/*physiology ; Oxygen/*blood ; Photic Stimulation ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S. ; Visual Cortex/cytology/physiology

The feasibility of recording event-related potentials (ERP) during functional MRI (fMRI) scanning was studied. Using an alternating checkerboard stimulus in a blocked presentation, visually evoked potentials were obtained with their expected configuration and latencies. A clustered echoplanar imaging protocol was applied to observe the hemodynamic response due to the visual stimulus interleaved with measuring ERPs. Influences of the electrode/amplifier set up on MRI scanning and the scanning process on the recording of electrophysiological signals are reported and discussed. Artifacts overlaid on the electrophysiological recordings were corrected by post hoc filtering methods presented here. Implications and limitations of conducting combined ERP/fMRI experiments using higher-level cognitive stimuli are discussed. Magn Reson Med 44:277-282, 2000.

Keywords: Adult ; Echo-Planar Imaging ; Electrodes ; *Electroencephalography ; Evoked Potentials, Visual/*physiology ; Feasibility Studies ; Female ; Human ; Image Processing, Computer-Assisted ; Magnetic Resonance Imaging/*methods ; Male ; Signal Processing, Computer-Assisted

EEG-triggered functional MRI (fMRI) offers the potential to localize the generators of scalp EEG events, such as interictal epileptiform discharges, using a biological measurement as opposed to relying solely on modelling techniques. Although recent studies have demonstrated these possibilities in a small number of patients, wider application has been limited by concerns about patient safety, severe problems due to pulse-related artefact obscuring the EEG trace, and lack of reproducibility data. We have systematically studied and resolved the issues of patient safety and pulse artefact and now report the application of the technique in 24 experiments in 10 consecutive patients with localization-related epilepsy and frequent interictal epileptiform discharges (spikes or spike wave). At least two experiments were performed for each patient. In each experiment, 10- or 20-slice snapshot gradient-echo planar images were acquired approximately 3.5 s after a single typical epileptiform discharge (activation image) and in the absence of discharges (control image). Between 21 and 50 epileptiform discharges were sampled in each experiment. The significance of functional activation was tested using the t test at 95% confidence on a pixel-by-pixel basis. Six of the 10 patients showed reproducible focal changes of the blood oxygen level-dependent (BOLD) signal, which occurred in close spatial relationship to the maximum of the epileptiform discharges in the concurrent EEG. No reproducible focal BOLD signal changes were observed in the remaining four patients. In conclusion, EEG-triggered fMRI is now a sufficiently developed technique to be more widely used in clinical studies, demonstrating that it can reproducibly localize the brain areas involved in the generation of spikes and spike wave in epilepsy patients with frequent interictal discharges.

Keywords: Adult ; Brain/pathology/*physiopathology ; Brain Mapping ; Electroencephalography/*methods ; Epilepsies, Partial/*diagnosis/*physiopathology ; Female ; Human ; Magnetic Resonance Imaging/*methods ; Male ; Middle Aged ; Support, Non-U.S. Gov't

PURPOSE: To demonstrate the integration of complementary functional and structural data acquired with magnetic resonance imaging (MRI) in a patient with localization-related epilepsy. METHODS: We studied a patient with partial and secondarily generalized seizures and a hemiparesis due to a malformation of cortical development (MCD) in the right hemisphere by using EEG-triggered functional MRI (fMRI), diffusion tensor imaging (DTI), and chemical shift imaging (CSI). RESULTS: fMRI revealed significant changes in regional blood oxygenation associated with interictal epileptiform discharges within the MCD. DTI showed a heterogeneous microstructure of the MCD with reduced fractional anisotropy, a high mean diffusivity, and displacement of myelinated tracts. CSI demonstrated low N-acetyl aspartate (NAA) concentrations in parts of the MCD. CONCLUSIONS: The applied MR methods described functional, microstructural, and biochemical characteristics of the epileptogenic tissue that cannot be obtained with other noninvasive means and thus improve the understanding of the pathophysiology of epilepsy.

Keywords: Adult ; Anisotropy ; Aspartic Acid/analogs & derivatives/analysis ; Cerebral Cortex/abnormalities/chemistry/physiopathology ; Electroencephalography/statistics & numerical data ; Epilepsies, Partial/blood/*diagnosis/physiopathology ; Human ; Magnetic Resonance Imaging/methods/*statistics & numerical data ; Male ; Nervous System Malformations/diagnosis ; Oxygen/blood

The simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance image (fMRI) is a promising tool that is capable of providing high spatiotemporal brain mapping, with each modality supplying complementary information. One of the major barriers to obtain high-quality simultaneous EEG/fMRI data is that pulsatile activity due to the heartbeat induces significant artifacts in the EEG. The purpose of this study was to develop a novel algorithm for removing heartbeat artifact, thus overcoming problems associated with previous methods. Our method consists of a mean artifact wave form subtraction, the selective removal of wavelet coefficients, and a recursive least-square adaptive filtering. The recursive least-square adaptive filtering operates without dedicated sensor for the reference signal, and only when the mean subtraction and wavelet-based noise removal is not satisfactory. The performance of our system has been assessed using simulated data based on experimental data of various spectral characteristics, and actual experimental data of alpha-wave-dominant normal EEG and epileptic EEG.

Keywords: Adult ; *Algorithms ; *Artifacts ; Ballistocardiography/methods ; Brain/*physiology ; Brain Mapping ; Comparative Study ; Electroencephalography/*methods ; Epilepsy/physiopathology ; Female ; Heart Rate/*physiology ; Humans ; Image Processing, Computer-Assisted ; Magnetic Resonance Imaging/*methods ; Male ; Middle Aged ; Research Support, Non-U.S. Gov't ; Signal Processing, Computer-Assisted ; Subtraction Technique ; Time Factors

Keywords: Brain/blood supply/*physiology ; Humans ; Magnetic Resonance Imaging/*methods/*trends ; Oxygen/blood ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't

The acquisition of electroencephalograms (EEG) during functional magnetic resonance imaging (fMRI) experiments raises important practical issues of patient safety. The presence of electrical wires connected to the patient in rapidly changing magnetic fields results in currents flowing through the patient due to induced electromotive forces (EMF), by three possible mechanisms: fixed loop in rapidly changing gradient fields; fixed loop in a RF electromagnetic field; moving loop in the static magnetic field. RF-induced EMFs were identified as the most important potential hazard. We calculated the minimum value of current-limiting resistance to be fitted in each EEG electrode lead for a representative worst case loop, and measured RF magnetic field intensity and heating in a specific type of current-limiting resistors. The results show that electrode resistance should be > or = 13 k(omega) for our setup. The methodology presented is general and can be useful for other centers.

Keywords: *Electroencephalography ; Electromagnetic Fields/adverse effects ; Human ; *Magnetic Resonance Imaging ; Models, Theoretical ; Safety ; Support, Non-U.S. Gov't ; Temperature

The goal of our research is to develop an experimental and analytical framework for spatiotemporal imaging of human brain function. Preliminary studies suggest that noninvasive spatiotemporal maps of cerebral activity can be produced by combining the high spatial resolution (millimeters) of functional MRI (fMRI) with the high temporal resolution (milliseconds) of electroencephalography (EEG) and magnetoencephalography (MEG). Although MEG and EEG are sensitive to millisecond changes in mental activity, the ability to resolve source localization and timing is limited by the ill-posed inverse problem. We conducted Monte Carlo simulations to evaluate the use of MRI constraints in a linear estimation inverse procedure, where fMRI weighting, cortical location and orientation, and sensor noise statistics were realistically incorporated. An error metric was computed to quantify the effects of fMRI invisible (missing) sources, extra fMRI sources, and cortical orientation errors. Our simulation results demonstrate that prior anatomical and functional information from MRI can be used to regularize the EEG/MEG inverse problem, giving an improved solution with high spatial and temporal resolution. An fMRI weighting of approximately 90% was determined to provide the best compromise between separation of activity from correctly localized sources and minimization of error caused by missing sources. The accuracy of the estimate was relatively independent of the number and extent of the sources, allowing for incorporation of physiologically realistic multiple distributed sources. This linear estimation method provides an operator-independent approach for combining information from fMRI, MEG, and EEG and represents a significant advance over traditional dipole modeling.

Keywords: Brain/*physiopathology/radiography ; Human ; Magnetic Resonance Imaging ; Magnetoencephalography ; Monte Carlo Method ; Support, Non-U.S. Gov't

Most existing analytical techniques for EEG-fMRI data need specific assumptions about the hemodynamic response function (HRF). These assumptions may not be appropriate when the HRF varies from subject to subject or from region to region. In this article, we introduce a deconvolution method for EEG-fMRI activation detection, which can be implemented with voxel-specific HRFs. A comparison of performance is made between three fixed HRFs and the deconvolution method under the framework of the general linear model. The main results are as follows: (1) the volume of detected regions from the deconvolved HRFs is larger. (2) In some subjects, the deconvolution technique can find areas of activation that have not been detected with the three fixed HRFs at our threshold of significance. (3) Deconvolution obtained higher adjusted coefficients of multiple determination compared to those obtained with the three fixed HRFs. The results suggest that the fixed HRF methods may not be the most appropriate for the analysis of epileptic activity with EEG-fMRI, and the deconvolution method may be a better choice.

Keywords: Brain/*anatomy & histology/pathology/*physiology ; *Brain Mapping ; Cerebrovascular Circulation/*physiology ; Comparative Study ; *Electroencephalography ; Epilepsies, Partial/pathology/*physiopathology ; Epilepsy/classification/pathology/physiopathology ; Hemodynamic Processes/*physiology ; Humans ; *Magnetic Resonance Imaging ; Reference Values ; Research Support, Non-U.S. Gov't

Functional magnetic resonance imaging (fMRI) triggered by scalp electroencephalography (EEG) recordings has become a promising new tool for noninvasive epileptic focus localization. Studies to date have shown that it can be used safely and that highly localized information can be obtained. So far, no reports using comprehensive clinical information and/or long-term follow-up after epilepsy surgery in a larger patient group have been given that would allow a valuable judgment of the utility of this technique. Here, the results of 11 patients with EEG-triggered fMRI exams who also underwent presurgical evaluation of their epilepsy are given. In most patients we were able to record good quality EEG inside the magnet, allowing us to trigger fMRI acquisition by interictal discharges. The fMRI consisted of echoplanar multislice acquisition permitting a large anatomical coverage of the patient's brain. In 8 of the 11 patients the exam confirmed clinical diagnosis, either by the presence (n = 7) or absence (n = 1) of focal signal enhancement. In six patients, intracranial recordings were carried out, and in five of them, the epileptogenic zone as determined by fMRI was confirmed. Limitations were encountered a) when the focus was too close to air cavities; b) if an active epileptogenic focus was absent; and c) if only reduced cooperation with respect to body movements was provided by the patient. We conclude that EEG-triggered fMRI is a safe and powerful noninvasive tool that improves the diagnostic value of MRI by localizing the epileptic focus precisely.

Keywords: Adolescent ; Adult ; Anticonvulsants/therapeutic use ; Brain Mapping/methods ; Drug Resistance ; Electroencephalography/*methods ; Epilepsy/*diagnosis/drug therapy/surgery ; Female ; Human ; Magnetic Resonance Imaging/*methods ; Male ; Preoperative Care ; Sensitivity and Specificity ; Support, Non-U.S. Gov't

Both electroencephalography (EEG) and magnetoencephalography (MEG) are currently used to localize brain activity. The accuracy of source localization depends on numerous factors, including the specific inverse approach and source model, fundamental differences in EEG and MEG data, and the accuracy of the volume conductor model of the head (i.e., the forward model). Using Monte Carlo simulations, this study removes the effect of forward model errors and theoretically compares the use of EEG alone, MEG alone, and combined EEG/MEG data sets for source localization. Here, we use a linear estimation inverse approach with a distributed source model and a realistic forward head model. We evaluated its accuracy using the crosstalk and point spread metrics. The crosstalk metric for a specified location on the cortex describes the amount of activity incorrectly localized onto that location from other locations. The point spread metric provides the complementary measure: for that same location, the point spread describes the mis-localization of activity from that specified location to other locations in the brain. We also propose and examine the utility of a noise sensitivity normalized inverse operator. Given our particular forward and inverse models, our results show that 1) surprisingly, EEG localization is more accurate than MEG localization for the same number of sensors averaged over many source locations and orientations; 2) as expected, combining EEG with MEG produces the best accuracy for the same total number of sensors; 3) the noise sensitivity normalized inverse operator improves the spatial resolution relative to the standard linear estimation operator; and 4) use of an a priori fMRI constraint universally reduces both crosstalk and point spread.

Keywords: *Algorithms ; *Artifacts ; Bayes Theorem ; Brain/anatomy & histology/physiology ; Brain Mapping/*methods ; Electrodes/standards ; Electroencephalography/*methods ; Human ; Image Processing, Computer-Assisted/*methods ; Magnetoencephalography/*methods ; Models, Neurological ; *Monte Carlo Method ; Reproducibility of Results ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.

Simultaneous acquisition of EEG and fMRI data enables the investigation of the hemodynamic correlates of interictal epileptiform discharges (IEDs) during the resting state in patients with epilepsy. This paper addresses two issues: (1) the semi-automation of IED classification in statistical modelling for fMRI analysis and (2) the improvement of IED detection to increase experimental fMRI efficiency. For patients with multiple IED generators, sensitivity to IED-correlated BOLD signal changes can be improved when the fMRI analysis model distinguishes between IEDs of differing morphology and field. In an attempt to reduce the subjectivity of visual IED classification, we implemented a semi-automated system, based on the spatio-temporal clustering of EEG events. We illustrate the technique's usefulness using EEG-fMRI data from a subject with focal epilepsy in whom 202 IEDs were visually identified and then clustered semi-automatically into four clusters. Each cluster of IEDs was modelled separately for the purpose of fMRI analysis. This revealed IED-correlated BOLD activations in distinct regions corresponding to three different IED categories. In a second step, Signal Space Projection (SSP) was used to project the scalp EEG onto the dipoles corresponding to each IED cluster. This resulted in 123 previously unrecognised IEDs, the inclusion of which, in the General Linear Model (GLM), increased the experimental efficiency as reflected by significant BOLD activations. We have also shown that the detection of extra IEDs is robust in the face of fluctuations in the set of visually detected IEDs. We conclude that automated IED classification can result in more objective fMRI models of IEDs and significantly increased sensitivity.

Infrequent occurrences of a deviant sound within a sequence of repetitive standard sounds elicit the automatic mismatch negativity (MMN) event-related potential (ERP). The main MMN generators are located in the superior temporal cortex, but their number, precise location, and temporal sequence of activation remain unclear. In this study, ERP and functional magnetic resonance imaging (fMRI) data were obtained simultaneously during a passive frequency oddball paradigm. There were three conditions, a STANDARD, a SMALL deviant, and a LARGE deviant. A clustered image acquisition technique was applied to prevent contamination of the fMRI data by the acoustic noise of the scanner and to limit contamination of the electroencephalogram (EEG) by the gradient-switching artifact. The ERP data were used to identify areas in which the blood oxygenation (BOLD) signal varied with the magnitude of the negativity in each condition. A significant ERP MMN was obtained, with larger peaks to LARGE deviants and with frontocentral scalp distribution, consistent with the MMN reported outside the magnetic field. This result validates the experimental procedures for simultaneous ERP/fMRI of the auditory cortex. Main foci of increased BOLD signal were observed in the right superior temporal gyrus [STG; Brodmann area (BA) 22] and right superior temporal plane (STP; BA 41 and 42). The imaging results provide new information supporting the idea that generators in the right lateral aspect of the STG are implicated in processes of frequency deviant detection, in addition to generators in the right and left STP.

Keywords: Adult ; Arousal/physiology ; Attention/*physiology ; Auditory Cortex/*physiology ; Brain Mapping ; Contingent Negative Variation/*physiology ; *Electroencephalography ; Evoked Potentials, Auditory/*physiology ; Female ; Human ; *Image Processing, Computer-Assisted ; *Magnetic Resonance Imaging ; Male ; Middle Aged ; Nerve Net/physiology ; Oxygen Consumption/physiology ; Pitch Discrimination/*physiology ; Support, U.S. Gov't, P.H.S. ; Temporal Lobe/physiology

Research groups who study epileptic spikes with simultaneous EEG-fMRI have used mostly the general linear model (GLM). A shortcoming of the GLM is that the specification of a simple hemodynamic response function (HRF) may lead to biased results. Other methods, which predict the hemodynamic response from the measured data, have been termed recognition models. The merit of recognition models lies in the power of estimating the region-specific or voxel-specific HRF. We propose an approach that merges these two models in a general framework: estimate the HRF on the training data sets, and applying the estimated HRF on the other part of the data sets. The merit of this framework is that it can utilize the advantages of both models. A comparison of performance is made between the GLM with three fixed HRFs and the new model with voxel-specific HRFs. The main results are as follows: (1) in 18 of the 21 patients, the new model has a higher adjusted coefficient of multiple determination than the GLM with fixed HRF; (2) in some subjects, with the new model, we found areas of activation that had not been detected with the three fixed HRFs at our threshold of significance. The results suggest that the new model can do better than the fixed HRF GLM for the analysis of epileptic activity with EEG-fMRI.

Keywords: *Electroencephalography ; Epilepsy/*physiopathology ; Humans ; *Magnetic Resonance Imaging ; Models, Statistical ; Sensitivity and Specificity

Electroencephalography-correlated functional magnetic resonance imaging (EEG/fMRI) can be used to identify blood oxygen level-dependent (BOLD) signal changes associated with both physiological and pathological EEG events. Here, we implemented continuous and simultaneous EEG/fMRI to identify BOLD signal changes related to spontaneous power fluctuations in the alpha rhythm (8-12 Hz), the dominant EEG pattern during relaxed wakefulness. Thirty-two channels of EEG were recorded in 10 subjects during eyes-closed rest inside a 1.5-T magnet resonance (MR) scanner using an MR-compatible EEG recording system. Functional scanning by echoplanar imaging covered almost the entire cerebrum every 4 s. Off-line MRI artifact subtraction software was applied to obtain continuous EEG data during fMRI acquisition. The average alpha power over 1-s epochs was derived at several electrode positions using a Fast Fourier Transform. The power time course was then convolved with a canonical hemodynamic response function, down-sampled, and used for statistical parametric mapping of associated signal changes in the image time series. At all electrode positions studied, a strong negative correlation of parietal and frontal cortical activity with alpha power was found. Conversely, only sparse and nonsystematic positive correlation was detected. The relevance of these findings is discussed in view of the current theories on the generation and significance of the alpha rhythm and the related functional neuroimaging findings.

Keywords: Adult ; *Alpha Rhythm ; Brain Mapping/*methods ; Cerebral Cortex/*physiology ; Electroencephalography/*methods ; Female ; Fourier Analysis ; Frontal Lobe/physiology ; Human ; *Image Processing, Computer-Assisted ; Imaging, Three-Dimensional/*methods ; Magnetic Resonance Imaging/*methods ; Male ; Mathematical Computing ; Oxygen Consumption/physiology ; Parietal Lobe/physiology ; Reference Values ; *Signal Processing, Computer-Assisted ; Support, Non-U.S. Gov't

We studied six patients with localization-related epilepsy, frequent interictal epileptiform discharges, and positive spike-triggered blood oxygen level-dependent functional MRI (BOLD-fMRI) findings. EEG source analysis solutions based on 64-channel EEG recorded in a separate session outside the scanner were obtained using dipole models and compared to the BOLD localization. The BOLD and structural images were coregistered, allowing the measurement of distances between the generator models and BOLD activation(s) and structural lesion when present. In all cases dipole models could be found that explained a sufficient amount of the data and that were anatomically concordant with the BOLD localization. In the five cases with structural abnormality visible on T1 scans, the BOLD activation overlapped or was in close proximity to the abnormality. The overall mean distance between the main moving dipole and the center of the nearest BOLD activation was 3.5 and 2.2 cm for the negative and positive peaks, respectively, including one case of a deep BOLD activation, in which the distance was 5 cm. In conclusion, the degree of agreement between the BOLD and EEG source localization indicates that the combination of these two noninvasive techniques offers the possibility of advancing the study of the generators of epileptiform electrical activity.

Keywords: Adult ; Brain Mapping ; Cerebral Cortex/*physiopathology ; Dominance, Cerebral/physiology ; *Electroencephalography ; Epilepsy, Frontal Lobe/*diagnosis/etiology/physiopathology ; Epilepsy, Temporal Lobe/*diagnosis/etiology/physiopathology ; Evoked Potentials ; Female ; Human ; *Imaging, Three-Dimensional ; *Magnetic Resonance Imaging ; Male ; Middle Aged ; Oxygen/*blood ; Sensitivity and Specificity ; Support, Non-U.S. Gov't ; Temporal Lobe/physiopathology

We assessed the relation between hemodynamic and electrical indices of brain function by performing simultaneous functional MRI (fMRI) and electroencephalography (EEG) in awake subjects at rest with eyes closed. Spontaneous power fluctuations of electrical rhythms were determined for multiple discrete frequency bands, and associated fMRI signal modulations were mapped on a voxel-by-voxel basis. There was little positive correlation of localized brain activity with alpha power (8-12 Hz), but strong and widespread negative correlation in lateral frontal and parietal cortices that are known to support attentional processes. Power in a 17-23 Hz range of beta activity was positively correlated with activity in retrosplenial, temporo-parietal, and dorsomedial prefrontal cortices. This set of areas has previously been characterized by high but coupled metabolism and blood flow at rest that decrease whenever subjects engage in explicit perception or action. The distributed patterns of fMRI activity that were correlated with power in different EEG bands overlapped strongly with those of functional connectivity, i.e., intrinsic covariations of regional activity at rest. This result indicates that, during resting wakefulness, and hence the absence of a task, these areas constitute separable and dynamic functional networks, and that activity in these networks is associated with distinct EEG signatures. Taken together with studies that have explicitly characterized the response properties of these distributed cortical systems, our findings may suggest that alpha oscillations signal a neural baseline with inattention whereas beta rhythms index spontaneous cognitive operations during conscious rest.

Keywords: *Attention ; Brain/*physiology ; *Cognition ; Electroencephalography ; Human ; Magnetic Resonance Imaging ; Support, Non-U.S. Gov't

Since its development about 15 years ago, functional magnetic resonance imaging (fMRI) has become the leading research tool for mapping brain activity. The technique works by detecting the levels of oxygen in the blood, point by point, throughout the brain. In other words, it relies on a surrogate signal, resulting from changes in oxygenation, blood volume and flow, and does not directly measure neural activity. Although a relationship between changes in brain activity and blood flow has long been speculated, indirectly examined and suggested and surely anticipated and expected, the neural basis of the fMRI signal was only recently demonstrated directly in experiments using combined imaging and intracortical recordings. In the present paper, we discuss the results obtained from such combined experiments. We also discuss our current knowledge of the extracellularly measured signals of the neural processes that they represent and of the structural and functional neurovascular coupling, which links such processes with the hemodynamic changes that offer the surrogate signal that we use to map brain activity. We conclude by considering applications of invasive MRI, including injections of paramagnetic tracers for the study of connectivity in the living animal and simultaneous imaging and electrical microstimulation.

Functional magnetic resonance imaging (fMRI) is widely used to study the operational organization of the human brain, but the exact relationship between the measured fMRI signal and the underlying neural activity is unclear. Here we present simultaneous intracortical recordings of neural signals and fMRI responses. We compared local field potentials (LFPs), single- and multi-unit spiking activity with highly spatio-temporally resolved blood-oxygen-level-dependent (BOLD) fMRI responses from the visual cortex of monkeys. The largest magnitude changes were observed in LFPs, which at recording sites characterized by transient responses were the only signal that significantly correlated with the haemodynamic response. Linear systems analysis on a trial-by-trial basis showed that the impulse response of the neurovascular system is both animal- and site-specific, and that LFPs yield a better estimate of BOLD responses than the multi-unit responses. These findings suggest that the BOLD contrast mechanism reflects the input and intracortical processing of a given area rather than its spiking output.

Keywords: Action Potentials ; Animals ; Contrast Sensitivity ; Electrodes ; Electrophysiology ; Hemodynamic Processes ; Macaca mulatta ; *Magnetic Resonance Imaging ; Neurons/*physiology ; Oxygen/blood ; Photic Stimulation ; Signal Processing, Computer-Assisted ; Support, Non-U.S. Gov't ; Synaptic Transmission ; Visual Cortex/*physiology

We determined locations of 33 scalp electrodes used for electroencephalographic (EEG) recording by placing markers in the positions determined by the 10-20 system and performing magnetic resonance image (MRI) scanning on volunteer subjects. Small Vaseline-filled capsules glued on the scalp with collodion produced easily delineated regions of increased signal on standard MRI head images. Measurements of each capsule's coordinates in 3 dimensions were made from MRI scans. A spherical surface was fitted through the marker positions, giving an average radius and an origin (center of sphere). The coordinate axes were rotated to ensure that electrode Cz was on the z-axis and that the y-axis was oriented in the posterior-anterior direction. Two spherical (angular) coordinates were determined for each electrode. Spherical electrode coordinates for different subjects differed by less than 20 degrees in all cases. An average and standard deviation of the spherical coordinates were calculated for each electrode. Standard deviations of several degrees were obtained. The average spherical coordinates obtained were close to those expected on the basis of applying the 10-20 system of placement to an ideal sphere. These measurements provide data necessary for various analyses of EEG performed to help localize epileptic foci.

Keywords: Brain/anatomy & histology/*physiology ; Brain Mapping ; Electrodes ; Electroencephalography/*instrumentation ; Female ; Human ; *Magnetic Resonance Imaging ; Male

Functional mapping of the human brain has made tremendous progress in the past years thanks to new technical developments. Imaging methods are now available; they allow to study brain functions with high spatial and temporal resolution. Single photon emission computer tomography (SPECT), positron emission tomography (PET), functional magnetic resonance imaging (fMRI) and high resolution electro- and magnetoencephalography (EEG and MEG) are currently intensively applied techniques to functional studies, each one having specific properties concerning spatial and temporal resolution. The success of these methods in basic neuroscience research has led to the demand for applying them to clinical questions. Diseases of the central nervous system that lead to brain dysfunction can be ideally explored using these techniques. Of particular importance are those diseases in which a focal neuronal dysfunction is the primary cause and where surgical resection of this focus might be the cure. This is often the case for epilepsy, where a discrete primary focus might exist from which pathological rhythms evolve and propagate throughout the brain, leading to seizures that severely handicap the patient. Surgical resection of the primary focus is only possible if the focus can be exactly localized and adequately separated from functionally important areas. This is where these new functional imaging tools become important. The use of SPECT and PET for focus localization has been most extensively studied and their specificity and sensitivity are intensively discussed. In the last few years functional MRI has evolved as a new interesting tool in epileptic focus localization. The most important limitation of these techniques, however, is the temporal resolution. Since epileptic activity can propagate very fast, several hyper- or hypoactive regions are seen in the images and primary areas cannot be distinguished from regions of propagation. The only methods that have sufficient temporal resolution to follow neuronal activity in real time are the electrophysiological measures, i.e. the EEG and the MEG. Localization of the sources in the brain that produced a given surface electromagnetic field has become possible through algorithms that solve the so-called inverse problem. Several different algorithms exist and many groups begun to apply them to epileptic data with the aim to localize the focus of the pathological electrical discharges. This review article discusses the use of distributed EEG source localization procedures in the presurgical evaluation of patients with intractable focal epilepsy. In contrast to equivalent dipole models, distributed localization methods do not localize one active point in the brain but rather assume extended active areas, which is generally the case in epileptic activity. The methods shown here are based on linear numerical methods and are therefore less prone to errors when working with scattered solution spaces such as the one defined by anatomical constraints. Solutions constraint to the gray matter determined in the individual MRI are shown here. We illustrate three methods to increase the spatial resolution of the source localization procedures: One is to increase the number of recording channels to more than 100, the second to use linear methods of high precision to detect focal sources (EPIFOCUS), and the third to combine EEG source localization with EEG-triggered functional magnetic resonance imaging. The importance of EEG source localization for the interpretation of fMRI data will be particularly discussed in view of the important difference of the temporal resolution by the two methods. The localization methods can be applied to interictal as well as to ictal activity. In case of analysis of ictal EEG we propose to use full scalp frequency analysis to determine the time period of seizure onset and to localize the sources of the initial dominant frequency.

The development of functional magnetic resonance imaging (fMRI) has brought together a broad community of scientists interested in measuring the neural basis of the human mind. Because fMRI signals are an indirect measure of neural activity, interpreting these signals to make deductions about the nervous system requires some understanding of the signaling mechanisms. We describe our current understanding of the causal relationships between neural activity and the blood-oxygen-level-dependent (BOLD) signal, and we review how these analyses have challenged some basic assumptions that have guided neuroscience. We conclude with a discussion of how to use the BOLD signal to make inferences about the neural signal.

Keywords: Animals ; Brain/*physiology ; Brain Mapping ; *Cerebrovascular Circulation ; Electrophysiology ; Human ; *Magnetic Resonance Imaging ; Models, Neurological ; Oxygen/*blood ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.

Cerebral currents responsible for the extra-cranially recorded magnetoencephalography (MEG) data can be estimated by applying a suitable source model. A popular choice is the distributed minimum-norm estimate (MNE) which minimizes the l2-norm of the estimated current. Under the l2-norm constraint, the current estimate is related to the measurements by a linear inverse operator. However, the MNE has a bias towards superficial sources, which can be reduced by applying depth weighting. We studied the effect of depth weighting in MNE using a shift metric. We assessed the localization performance of the depth-weighted MNE as well as depth-weighted noise-normalized MNE solutions under different cortical orientation constraints, source space densities, and signal-to-noise ratios (SNRs) in multiple subjects. We found that MNE with depth weighting parameter between 0.6 and 0.8 showed improved localization accuracy, reducing the mean displacement error from 12 mm to 7 mm. The noise-normalized MNE was insensitive to depth weighting. A similar investigation of EEG data indicated that depth weighting parameter between 2.0 and 5.0 resulted in an improved localization accuracy. The application of depth weighting to auditory and somatosensory experimental data illustrated the beneficial effect of depth weighting on the accuracy of spatiotemporal mapping of neuronal sources.

Accurate co-registration of MRI and EEG data is indispensable for the correct interpretation of EEG maps or source localizations in relation to brain anatomy derived from MRI. In this study, a method for the co-registration of EEG and MRI data is presented. The method consists of an iterative matching of EEG-electrode based reconstructions of the scalp surface to scalp-segmented MRIs. EEG-electrode based surface reconstruction is achieved via spline interpolation of individually digitized 3D-electrode coordinates. In contrast to other approaches, neither fiducial determination nor any additional provisions (such as bite bars, other co-registration devices or head shape digitization) are required, and co-registration errors associated with inaccurate fiducial determination are avoided. The accuracy of the method was estimated by calculating the root-mean-square (RMS) deviation of spline interpolated and MRI-segmented surface reconstructions in 20 subjects. In addition, the distance between co-registered and genuine electrode coordinates was assessed via a simulation study, in which surface reconstruction was based on virtual electrodes determined on the scalp surface of a high-resolution MRI data set. The mean RMS deviation of surface reconstructions was 2.43 mm, and the maximal distance between any two matched surface points was 5.06 mm. The simulated co-registration revealed a mean deviation of genuine and co-registered electrode coordinates of 0.61 mm. It is concluded that surface matching using spline interpolated reconstructions of scalp surfaces is a precise and highly practicable method to co-register EEG and MRI data.

Keywords: Adult ; Brain/*anatomy & histology/*physiology ; Brain Mapping/*methods ; *Electroencephalography ; Human ; *Image Processing, Computer-Assisted ; Imaging, Three-Dimensional ; *Magnetic Resonance Imaging ; Scalp/*anatomy & histology/*physiology ; Skull/anatomy & histology ; Support, Non-U.S. Gov't

The possibility of combining the high spatial resolution of functional magnetic resonance imaging (fMRI) with the high temporal resolution of electroencephalography (EEG) may provide a new tool in cognitive neurophysiology, as well as in clinical applications such as epilepsy. However, the simultaneous recording of EEG and fMRI raises important practical problems: 1) the patients' safety, in particular the risk of skin burns due to electrodes heating; 2) the impairment of the EEG recording by the static magnetic field, as well as by RF and magnetic field gradients used during MRI; and 3) the quality of MR images, which may be affected by the presence of conductors and electronic devices in the MRI bore. Here we present our experiences on 19 normal volunteers who underwent combined fMRI and 16-channel EEG examination. Consistent with previous reports, safety could be assured when performing EEG recordings during fMRI acquisition. Electrophysiological signals recorded with surface EEG were similar inside and outside the 1.5 T magnet. Furthermore, fMRI using motor or visual tasks revealed similar areas of activation when performed with and without 16-channel EEG recording. J. Magn. Reson. Imaging 2001;13:943-948.

Keywords: Attention/physiology ; Brain Mapping/instrumentation ; Cerebral Cortex/*physiology ; Echo-Planar Imaging/*instrumentation ; Electrodes ; Electroencephalography/*instrumentation ; Equipment Safety ; Heat/adverse effects ; Human ; *Image Enhancement ; *Image Processing, Computer-Assisted ; Magnetic Resonance Imaging/*instrumentation ; Motion Perception/physiology ; Motor Activity/physiology ; Pattern Recognition, Visual/physiology ; Reference Values ; Support, Non-U.S. Gov't

Keywords: Animals ; Brain/blood supply/physiology ; Carbon Dioxide/blood ; Cerebrovascular Circulation/physiology ; Echo-Planar Imaging/methods ; Human ; Magnetic Resonance Imaging/*methods ; Magnetic Resonance Spectroscopy/methods ; Oxygen/*blood ; Support, Non-U.S. Gov't

In BOLD fMRI data analysis, robust and accurate estimation of the Hemodynamic Response Function (HRF) is still under investigation. Parametric methods assume the shape of the HRF to be known and constant throughout the brain, whereas non-parametric methods mostly rely on artificially increasing the signal-to-noise ratio. We extend and develop a previously proposed method that makes use of basic yet relevant temporal information about the underlying physiological process of the brain BOLD response in order to infer the HRF in a Bayesian framework. A general hypothesis test is also proposed, allowing to take advantage of the knowledge gained regarding the HRF to perform activation detection. The performances of the method are then evaluated by simulation. Great improvement is shown compared to the Maximum-Likelihood estimate in terms of estimation error, variance, and bias. Robustness of the estimators with regard to the actual noise structure or level, as well as the stimulus sequence, is also proven. Lastly, fMRI data with an event-related paradigm are analyzed. As suspected, the regions selected from highly discriminating activation maps resulting from the method exhibit a certain inter-regional homogeneity in term of HRF shape, as well as noticeable inter-regional differences.

Keywords: Adult ; Bayes Theorem ; Hemodynamic Processes/*physiology ; Human ; Magnetic Resonance Imaging/*methods/statistics & numerical data ; *Models, Biological ; Psychomotor Performance/*physiology ; Statistics ; Support, Non-U.S. Gov't

The signal intensity during the dynamic approach to the equilibrium state of longitudinal magnetization is a function of sequence parameters, such as repetition time and flip angle, and depends on tissue characteristics, including longitudinal relaxation time of stationary tissue and the rate of blood inflow. A method is presented to extract information from data acquired during the transient state prior to T(1) equilibrium using echo-planar acquisitions in T(2)*-weighted functional magnetic resonance imaging (fMRI) experiments. A voxel in a single slice acquisition is assumed to contain either stationary tissue or large vessels with flowing blood. Models are presented to characterize longitudinal magnetization relaxation of heterogeneous stationary tissue and blood inflow. The data were fitted to theoretical models for longitudinal relaxation of stationary tissue and inflowing blood assuming no residual signal prior to each RF excitation. Parameters were estimated at 3 T for each model using least squares estimation. A goodness-of-fit criterion was applied to exclude voxels that have transient data that does not fit the selected (best fit) model. Voxels that best fit the inflow model, measured at various TR and flip angles, were assumed to contain large draining veins and were excluded from functional maps. Histogram analysis of T(1) distributions for activated voxels in a visual paradigm demonstrated the distributions are centered at T(1) values of gray matter with tails at both sides of the center due to partial voluming of gray matter with white matter and CSF respectively. The mean gray matter volume fraction in activated voxels was about 0.9. The results indicate that transient data sets can provide additional information that is useful for both localization and characterization of the functionally relevant BOLD response.

Keywords: Artifacts ; Brain/*physiology ; *Electroencephalography ; Epilepsy/diagnosis ; Evoked Potentials ; Humans ; *Magnetic Resonance Imaging ; Models, Neurological

Target detection is the process of bringing a salient stimulus into conscious awareness. Target detection evokes a prominent event-related potential (ERP) component (P3) in the electroencephalogram (EEG). We combined the high spatial resolution of functional magnetic resonance imaging (fMRI) with the high temporal resolution of EEG to investigate the neural generators of the P3. Event-related brain activation (ERBA) and ERPs were computed by time-locked averaging of fMRI and EEG, respectively, recorded using the same paradigm in the same subjects. Target detection elicited significantly greater ERBAs bilaterally in the temporal-parietal cortex, thalamus and anterior cingulate. Spatio-temporal modelling of ERPs based on dipole locations derived from the ERBAs indicated that bilateral sources in the temporal-parietal cortex are the main generators of the P3. The findings provide convergent fMRI and EEG evidence for significant activation of the temporal-parietal cortex 285-610 ms after stimulus onset during target detection. The methods developed here provide a novel multimodal neuroimaging technique to investigate the spatio-temporal aspects of processes underlying brain function.

Keywords: Adult ; Brain Mapping/*methods ; *Electroencephalography ; Evoked Potentials/physiology ; Female ; Human ; Magnetic Resonance Imaging/*methods ; Male ; Parietal Lobe/*physiology ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, Non-P.H.S. ; Support, U.S. Gov't, P.H.S. ; Temporal Lobe/*physiology

This article reviews the application of finite element methods to models of bioelectric phenomena. The models represent the electrical fields created in the body as a result of membrane current sources or external current applied for diagnostic or therapeutic purposes. We formulate the governing equations for these models and then derive the finite element equations for the generalized bioelectric problem. The 32 papers reviewed here, all those appearing in the literature to date, cover the areas of electrocardiology, therapeutic and functional electrical stimulation in the cerebellum, cochlea, spinal cord, and peripheral nerves, cardiac defibrillation, electrical impedance tomography, bidomain cardiac models, electroporation, and therapeutic electrical stimulation of bone. For each, we summarize the purpose of the study, the model details and assumptions, the major results, and the applicability of the study. The models are then considered as a group to critique the appropriateness of the finite element method, the means of implementation, and the factors affecting accuracy, thus providing an overview of the state of finite element modeling of bioelectric phenomena.

Keywords: Central Nervous System Diseases/therapy ; Cochlear Implants ; Electric Countershock ; Electric Stimulation Therapy ; *Electrophysiology ; Human ; *Models, Biological ; Tomography, X-Ray/methods ; Ventricular Fibrillation/therapy

Investigating human brain function non-invasively by simultaneous EEG and fMRI measurements is gaining in popularity as more and better solutions to the inherent technical challenges emerge. We demonstrate the use of a commercially available frequency divider and phase-locking device for the purpose of synchronizing an MRI acquisition with a simultaneous recording of the EEG. Synchronization hugely improves the effectiveness of MRI artefact removal from the EEG signal by the common mean template subtraction method. It complements or substitutes post-processing techniques like filtering, thereby increasing the usable bandwidth of the EEG signal to about 150 Hz. This is important for covering the full range of human Gamma band activity. Similarly, synchronization eliminates the necessity for over-sampling of the EEG signal.

fMRI and EEG are complimentary methods for the analysis of brain activity since each method has its strength where the other one has limits: The spatial resolution is thus in the range of millimeters with fMRI and the time resolution is in the range of milliseconds with EEG. For a comprehensive understanding of brain activity in target detection, nine healthy subjects (age 24.2 +/- 2.9) were investigated with simultaneous EEG (27 electrodes) and fMRI using an auditory oddball paradigm. As a first step, event-related potentials, measured inside the scanner, have been compared with the potentials recorded in a directly preceding session in front of the scanner. Attenuated amplitudes were found inside the scanner for the earlier N1/P2 component but not for the late P300 component. Second, an independent analysis of the localizations of the fMRI activations and the current source density as revealed by low resolution electromagnetic tomography (LORETA) has been done. Concordant activations were found in most regions, including the temporoparietal junction (TPJ), the supplementary motor area (SMA)/anterior cingulate cortex (ACC), the insula, and the middle frontal gyrus, with a mean Euclidean distance of 16.0 +/- 6.6 mm between the BOLD centers of gravity and the LORETA-maxima. Finally, a time-course analysis based on the current source density maxima was done. It revealed different time-course patterns in the left and right hemisphere with earlier activations in frontal and parietal regions in the right hemisphere. The results suggest that the combination of EEG and fMRI permits an improved understanding of the spatiotemporal dynamics of brain activity.

Human cortical information processing is thought to be dominated by distributed activity in vector state space (Churchland, P.S., Sejnowski, T.J., 1992. The Computational Brain. MIT Press, Cambridge.). In principle, it should be possible to quantify distributed brain activation with independent component analysis (ICA) through vector-based decomposition, i.e., through a separation of a mixture of sources. Using event-related functional magnetic resonance imaging (fMRI) during a selective attention-requiring task (visual oddball), we explored how the number of independent components within activated cortical areas is related to reaction time. Prior to ICA, the activated cortical areas were determined on the basis of a General linear model (GLM) voxel-by-voxel analysis of the target stimuli (checkerboard reversal). Two activated cortical areas (temporoparietal cortex, medial prefrontal cortex) were further investigated as these cortical regions are known to be the sites of simultaneously active electromagnetic generators which give rise to the compound event-related potential P300 during oddball task conditions. We found that the number of independent components more strongly predicted reaction time than the overall level of activation (GLM BOLD-response) in the left temporoparietal area whereas in the medial prefrontal cortex both ICA and GLM predicted reaction time equally well. Comparable correlations were not seen when principle components were used instead of independent components. These results indicate that the number of independently activated components, i.e., a high level of cortical activation complexity in cortical vector state space, may index particularly efficient information processing during selective attention-requiring tasks. To our best knowledge, this is the first report describing a potential relationship between neuronal generators of cognitive processes, the associated electrophysiological evidence for the existence of distributed networks and BOLD fMRI signals using information from model order selection techniques.

Keywords: Adult ; Attention/*physiology ; Brain Mapping ; Cerebral Cortex/*physiology ; Dominance, Cerebral/physiology ; Event-Related Potentials, P300/physiology ; Female ; Humans ; *Image Enhancement ; *Image Processing, Computer-Assisted ; *Imaging, Three-Dimensional ; Linear Models ; *Magnetic Resonance Imaging ; Male ; Nerve Net/physiology ; Neurons/physiology ; Oxygen/*blood ; Pattern Recognition, Visual/*physiology ; Principal Component Analysis ; Reaction Time/*physiology

Objective: Electroencephalography (EEG) is an important tool for studying the temporal dynamics of the human brain's large-scale neuronal circuits. However, most EEG applications fail to capitalize on all of the data's available information, particularly that concerning the location of active sources in the brain. Localizing the sources of a given scalp measurement is only achieved by solving the so-called inverse problem. By introducing reasonable a priori constraints, the inverse problem can be solved and the most probable sources in the brain at every moment in time can be accurately localized. Methods and Results: Here, we review the different EEG source localization procedures applied during the last two decades. Additionally, we detail the importance of those procedures preceding and following source estimation that are intimately linked to a successful, reliable result. We discuss (1) the number and positioning of electrodes, (2) the varieties of inverse solution models and algorithms, (3) the integration of EEG source estimations with MRI data, (4) the integration of time and frequency in source imaging, and (5) the statistical analysis of inverse solution results. Conclusions and Significance: We show that modern EEG source imaging simultaneously details the temporal and spatial dimensions of brain activity, making it an important and affordable tool to study the properties of cerebral, neural networks in cognitive and clinical neurosciences.

A realistically shaped three-dimensional single-neuron model was constructed for each of four principal cell types in the neocortex in order to infer their contributions to magnetoencephalography (MEG) and electroencephalography (EEG) signals. For each cell, the soma was stimulated and the resulting intracellular current was used to compute the current dipole Q for the whole cell or separately for the apical and basal dendrites. The magnitude of Q is proportional to the magnetic field and electrical potential far from the neuron. A train of spikes and depolarization shift in an intracellular burst discharge were seen as spikes and an envelope in Q for the layer V and layer II/III pyramidal cells. The stellate cells lacked the envelope. As expected, the pyramidal cells produced a stronger Q than the stellate cells. The spikes produced by the layer V pyramidal cells (n = 4) varied between -0.78 and 2.97 pA m with the majority of the cells showing a current toward the pia (defined as positive). The basal dendrites, however, produced considerable spike currents. The magnitude and direction of dipole moment are in agreement with the distribution of the dendrites. The spikes in Q for the layer V pyramidal cells were produced by the transient sodium conductance and potassium conductance of delayed rectifier type; the conductances distributed along the dendrites were capable of generating spike propagation, which was seen in Q as the tail of a triphasic wave lasting several milliseconds. The envelope was similar in magnitude (-0.41 to -0.90 pA m) across the four layer V pyramidal cells. The spike and envelope for the layer II/III pyramidal cell were 0.47 and -0.29 pA m, respectively; these values agreed well with empirical and theoretical estimates for guinea pig CA3 pyramidal cells. Spikes were stronger for the layer IV spiny stellate (0.27 pA m) than the layer III aspiny stellate cell (0.06 pA m) along their best orientations. The spikes may thus be stronger than has been previously thought. The Q for a population of stellate cells may be weaker than a linear sum of their individual Q values due to their variable dendritic geometry. The burst discharge by pyramidal cells may be detectable with MEG and EEG when 10 000-50 000 cells are synchronously active.

The aim of this work was to investigate the dependence of BOLD responses on different patterns of stimulus input/neuronal changes. In an earlier report, we described an input-state-output model that combined (i) the Balloon/Windkessel model of nonlinear coupling between rCBF and BOLD signals, and (ii) a linear model of how regional flow changes with synaptic activity. In the present investigation, the input-state-output model was used to explore the dependence of simulated PET (rCBF) and fMRI (BOLD) signals on various parameters pertaining to experimental design. Biophysical simulations were used to estimate rCBF and BOLD responses as functions of (a) a prior stimulus, (b) epoch length (for a fixed SOA), (c) SOA (for a fixed number of events), and (d) stimulus amplitude. We also addressed the notion that a single neuronal response may differ, in terms of the relative contributions of early and late neural components, and investigated the effect of (e) the relative size of the late or endogenous neural component. We were interested in the estimated average rCBF and BOLD responses per stimulus or event, not in the statistical efficiency with which these responses are detected. The BOLD response was underestimated relative to rCBF with a preceding stimulus, increasing epoch length, and increasing SOA. Furthermore, the BOLD response showed some highly nonlinear behaviour when varying stimulus amplitude, suggesting some form of hemodynamic rectification. Finally, the BOLD response was underestimated in the context of large late neuronal components. The difference between rCBF and BOLD is attributed to the nonlinear transduction of rCBF to BOLD signal. Our simulations support the idea that varying parameters that specify the experimental design may have differential effects in PET and fMRI. Moreover, they show that fMRI can be asymmetric in its ability to detect deactivations relative to activations when an absolute baseline is stipulated. Finally, our simulations suggest that relative insensitivity to BOLD signal in specific regions, such as the temporal lobe, may be partly explained by higher cognitive functions eliciting a relatively large late endogenous neuronal component.

Keywords: Arousal/*physiology ; Brain/*blood supply ; Comparative Study ; Hemodynamic Processes/*physiology ; Human ; *Image Enhancement ; Image Processing, Computer-Assisted ; *Magnetic Resonance Imaging ; Models, Neurological ; Neurons/physiology ; *Nonlinear Dynamics ; Oxygen/*blood/physiology ; Regional Blood Flow/physiology ; Sensitivity and Specificity ; Support, Non-U.S. Gov't ; Tomography, Emission-Computed

To use Electroencephalography (EEG) and Magnetoencephalography (MEG) as functional brain 3D imaging techniques, identifiable distributed source models are required. The reconstruction of EEG/MEG sources rests on inverting these models and is ill-posed because the solution does not depend continuously on the data and there is no unique solution in the absence of prior information or constraints. We have described a general framework that can account for several priors in a common inverse solution. An empirical Bayesian framework based on hierarchical linear models was proposed for the analysis of functional neuroimaging data [Friston, K., Penny, W., Phillips, C., Kiebel, S., Hinton, G., Ashburner, J., 2002. Classical and Bayesian inference in neuroimaging: theory. NeuroImage 16, 465-483] and was evaluated recently in the context of EEG [Phillips, C., Mattout, J., Rugg, M.D., Maquet, P., Friston, K., 2005. An empirical Bayesian solution to the source reconstruction problem in EEG. NeuroImage 24, 997-1011]. The approach consists of estimating the expected source distribution and its conditional variance that is constrained by an empirically determined mixture of prior variance components. Estimation uses Expectation-Maximization (EM) to give the Restricted Maximum Likelihood (ReML) estimate of the variance components (in terms of hyperparameters) and the Maximum A Posteriori (MAP) estimate of the source parameters. In this paper, we extend the framework to compare different combinations of priors, using a second level of inference based on Bayesian model selection. Using Monte-Carlo simulations, ReML is first compared to a classic Weighted Minimum Norm (WMN) solution under a single constraint. Then, the ReML estimates are evaluated using various combinations of priors. Both standard criterion and ROC-based measures were used to assess localization and detection performance. The empirical Bayes approach proved useful as: (1) ReML was significantly better than WMN for single priors; (2) valid location priors improved ReML source localization; (3) invalid location priors did not significantly impair performance. Finally, we show how model selection, using the log-evidence, can be used to select the best combination of priors. This enables a global strategy for multiple prior-based regularization of the MEG/EEG source reconstruction.

We used simultaneous electroencephalogram-functional magnetic resonance imaging (EEG-fMRI) and EEG-near infrared spectroscopy (NIRS) to investigate whether changes of the posterior EEG alpha rhythm are correlated with changes in local cerebral blood oxygenation. Cross-correlation analysis of slowly fluctuating, spontaneous rhythms in the EEG and the fMRI signal revealed an inverse relationship between alpha activity and the fMRI-blood oxygen level dependent signal in the occipital cortex. The NIRS-EEG measurements demonstrated a positive cross-correlation in occipital cortex between alpha activity and concentration changes of deoxygenated hemoglobin, which peaked at a relative shift of about 8 s. Our data suggest that alpha activity in the occipital cortex is associated with metabolic deactivation. Mapping of spontaneously synchronizing distributed neuronal networks is thus shown to be feasible.

Keywords: Adult ; *Alpha Rhythm ; Brain Chemistry/*physiology ; Electroencephalography ; Energy Metabolism/physiology ; Female ; Hemoglobins/metabolism ; Human ; *Magnetic Resonance Imaging ; Male ; Oxygen/*blood ; Photic Stimulation ; *Spectroscopy, Near-Infrared ; Support, Non-U.S. Gov't

Differences in the blood oxygen level dependent (BOLD) signal changes were studied during voluntary hyperventilation (HV) between young healthy volunteer groups, (1) with intermittent rhythmic delta activity (IRDA) (N = 4) and (2) controls (N = 4) with only diffuse arrhythmic slowing in EEG (normal response). Subjects hyperventilated (3 min) during an 8-min functional MRI in a 1.5-T scanner, with simultaneous recording of EEG (successful with N = 3 in both groups) and physiological parameters. IRDA power and average BOLD signal intensities (of selected brain regions) were calculated. Hypocapnia showed a tendency to be slightly lighter in the controls than in the IRDA group. IRDA power increased during the last minute of HV and ended 10-15 s after HV. The BOLD signal decreased in white and gray matter after the onset of HV and returned to the baseline within 2 min after HV. The BOLD signal in gray matter decreased approximately 30% more in subjects with IRDA than in controls, during the first 2 min of HV. This difference disappeared (in three subjects out of four) during IRDA in EEG. BOLD signal changes seem to depict changes, which precede IRDA. IRDA due to HV in healthy volunteers represent a model with a clearly defined EEG pattern and an observable BOLD signal change.

The resistivity values of the different tissues of the head affect the lead fields of electroencephalography (EEG). When the head is modeled with a concentric spherical model, the different resistivity values have no effect on the lead fields of the magnetoencephalography (MEG). Recent publications indicate that the resistivity of the skull is much lower than what was estimated by Rush and Driscoll. At the moment, this information on skull resistivity is, however, slightly controversial. We have compared the spatial resolution of EEG and MEG for cortical sources by calculating the half-sensitivity volumes (HSVs) of EEG and MEG as a function of electrode and magnetometer distance, respectively, with the relative skull resistivity as a parameter. Because the spatial resolution is related to the HSV, these data give an overview of the effect of these parameters on the spatial resolution of both techniques. Our calculations show that, with the new information on the resistivity of the skull, in the spherical model for cortical sources the spatial resolution of the EEG is better than that of the MEG.

Keywords: Brain/*physiology ; Comparative Study ; Computer Simulation ; Electric Impedance ; Electrodes ; Electroencephalography/*methods ; Head/physiology ; Human ; Magnetoencephalography/*methods ; *Models, Neurological ; Reproducibility of Results ; Sensitivity and Specificity ; Skull/*physiology ; Support, Non-U.S. Gov't

As the limits of stimuli presentation rates are explored in event-related fMRI design, there is a greater need to assess the implications of averaging raw fMRI data. Selective averaging assumes that the fMRI signal consists of task-dependent signal, random noise, and non-task dependent brain signal that can be modeled as random noise so that it tends to zero when averaged over a practical number of trials. We recorded a total of four fMRI data series from two normal subjects (subject 1, axially acquired; subject 2, coronally acquired) performing a simple visual event-related task and a water phantom with the same fMRI scanner imaging parameters. To determine which fraction of the fMRI data was deterministic as opposed to random, we created different data subsets by taking the odd or even time points of the full data sets. All data sets were first dimension-reduced with principal component analysis (PCA) and separated into 100 spatially independent components with independent component analysis (ICA). The mutual information between best-matching pairs of components selected from full data set-subset comparisons was plotted for each data set. Visual inspection suggested that 45-85 components were reproducible, and hence deterministic, accounting for 79-97% of the variance, respectively, in the raw data. The reproducible components exhibited much less trial-to-trial variability than the raw data from even the most activated voxel. Many (22-47) of reproducible components were significantly affected by stimulus presentation (P < 0.001). The most significantly-stimulus-correlated component was strongly time-locked to stimulus presentation and was directly stimulus correlated, corresponding to occipital brain regions. However, other spatially distinct task-related components demonstrated variable temporal relationships with the most significantly-stimulus-correlated component. Our results suggest that the majority of the variance in fMRI data is in fact deterministic, and support the notion that the data consist of differing components with differing temporal relationships to visual stimulation. They further suggest roles for restricting interpretations of the spatial extent of activation from event-related designs to a specific region of interest (ROI) and/or first separating the data into spatially independent components. Averaging the time courses of spatially independent components time-locked to stimulus presentation may prevent possible biases in the estimates of the spatial and temporal extent of stimulus-correlated activation and of trial-to-trial variability.

Keywords: Analysis of Variance ; Brain/physiology ; Data Interpretation, Statistical ; *Evoked Potentials ; Human ; Magnetic Resonance Imaging/*statistics & numerical data ; Phantoms, Imaging ; Principal Component Analysis

Data may now be recorded concurrently from EEG and functional MRI, using the Simultaneous Imaging for Tomographic Electrophysiology (SITE) method. As yet, there is no established means to integrate the analysis of the combined data set. Recognizing that the hemodynamically convolved time-varying EEG spectrum, S, is intrinsically multidimensional in space, frequency, and time motivated us to use multiway Partial Least-Squares (N-PLS) analysis to decompose EEG (independent variable) and fMRI (dependent variable) data uniquely as a sum of atoms. Each EEG atom is the outer product of spatial, spectral, and temporal signatures and each fMRI atom the product of spatial and temporal signatures. The decomposition was constrained to maximize the covariance between corresponding temporal signatures of the EEG and fMRI. On all data sets, three components whose spectral peaks were in the theta, alpha, and gamma bands appeared; only the alpha atom had a significant temporal correlation with the fMRI signal. The spatial distribution of the alpha-band atom included parieto-occipital cortex, thalamus, and insula, and corresponded closely to that reported by Goldman et al. [NeuroReport 13(18) (2002) 2487] using a more conventional analysis. The source reconstruction from EEG spatial signature showed only the parieto-occipital sources. We interpret these results to indicate that some electrical sources may be intrinsically invisible to scalp EEG, yet may be revealed through conjoint analysis of EEG and fMRI data. These results may also expose brain regions that participate in the control of brain rhythms but may not themselves be generators. As of yet, no single neuroimaging method offers the optimal combination of spatial and temporal resolution; fusing fMRI and EEG meaningfully extends the spatio-temporal resolution and sensitivity of each method.

Epileptic disorders manifest with seizures and interictal epileptic discharges (IEDs). The hemodynamic changes that accompany IEDs are poorly understood and may be critical for understanding epileptogenesis. Despite a known linear coupling of the neurovascular elements in normal brain tissues, previous simultaneous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) studies have shown variable correlations between epileptic discharges and blood oxygenation level-dependent (BOLD) response, partly because most previous studies assumed particular hemodynamic properties in normal brain tissue. The occurrence of IEDs in human subjects is unpredictable. Therefore, an animal model with reproducible stereotyped IEDs was developed by the focal injection of penicillin into the right occipital cortex of rats anesthetized with isoflurane. Simultaneous EEG-fMRI was used to study the hemodynamic changes during IEDs. A hybrid of temporal independent component analysis (ICA) of EEG and spatial ICA of fMRI data was used to correlate BOLD fMRI signals with IEDs. A linear autoregression with exogenous input (ARX) model was used to estimate the hemodynamic impulse response function (HIRF) based on the data from simultaneous EEG-fMRI measurement. Changes in the measured BOLD signal from the right primary visual cortex and bilateral visual association cortices were consistently coupled to IEDs. The linear ARX model was applied here to confirm that a linear transform can be used to study the correlation between BOLD signal and its corresponding neural activity in this animal model of occipital epilepsy.

Objective: Recording low amplitude electroencephalography (EEG) signals in the face of large gradient artifacts generated by changing functional magnetic resonance imaging (fMRI) magnetic fields continues to be a challenge. We present a new method of removing gradient artifacts with time-varying waveforms, and evaluate it in continuous (non-interleaved) simultaneous EEG-fMRI experiments. Methods: The current method consists of an analog filter, an EEG-fMRI timing error correction algorithm, and a temporal principal component analysis based gradient noise removal algorithm. We conducted a phantom experiment and a visual oddball experiment to evaluate the method. Results: The results from the phantom experiment showed that the current method reduced the number of averaged samples required to obtain high correlation between injected and recovered signals, compared to a conventional average waveform subtraction method with adaptive noise canceling. For the oddball experiment, the results obtained from the two methods were very similar, except that the current method resulted in a higher P300 amplitude when the number of averaged trials was small. Conclusions: The current method enabled us to obtain high quality EEGs in continuous simultaneous EEG-fMRI experiments. Significance: Continuous simultaneous EEG-fMRI acquisition enables efficient use of data acquisition time and better monitoring of rare EEG events.

The combination of functional magnetic resonance imaging (FMRI) and electroencephalography (EEG) has received much recent attention, since it potentially offers a new tool for neuroscientists that makes simultaneous use of the strengths of the two modalities. However, EEG data collected in such experiments suffer from two kinds of artifact. First, gradient artifacts are caused by the switching of magnetic gradients during FMRI. Second, ballistocardiographic (BCG) artifacts related to cardiac activities further contaminate the EEG data. Here we present new methods to remove both kinds of artifact. The methods are based primarily on the idea that temporal variations in the artifacts can be captured by performing temporal principal component analysis (PCA), which leads to the identification of a set of basis functions which describe the temporal variations in the artifacts. These basis functions are then fitted to, and subtracted from, EEG data to produce artifact-free results. In addition, we also describe a robust algorithm for the accurate detection of heart beat peaks from poor quality electrocardiographic (ECG) data that are collected for the purpose of BCG artifact removal. The methods are tested and are shown to give superior results to existing methods. The methods also demonstrate the feasibility of simultaneous EEG/FMRI experiments using the relatively low EEG sampling frequency of 2048 Hz.

Keywords: Algorithms ; *Artifacts ; Electrocardiography ; Electroencephalography/*statistics & numerical data ; Evoked Potentials/physiology ; Heart Rate/physiology ; Humans ; Image Processing, Computer-Assisted/*methods ; Lasers ; Magnetic Resonance Imaging/*statistics & numerical data ; Principal Component Analysis ; Reproducibility of Results ; Research Support, Non-U.S. Gov't

The contingent negative variation (CNV) is a long-latency electroencephalography (EEG) surface negative potential with cognitive and motor components, observed during response anticipation. CNV is an index of cortical arousal during orienting and attention, yet its functional neuroanatomical basis is poorly understood. We used functional magnetic resonance imaging (fMRI) with simultaneous EEG and recording of galvanic skin response (GSR) to investigate CNV-related central neural activity and its relationship to peripheral autonomic arousal. In a group analysis, blood oxygenation level dependent (BOLD) activity during the period of CNV generation was enhanced in thalamus, somatomotor cortex, bilateral midcingulate, supplementary motor, and insular cortices. Enhancement of CNV-related activity in anterior and midcingulate, SMA, and insular cortices was associated with decreases in peripheral sympathetic arousal. In a subset of subjects in whom we acquired simultaneous EEG and fMRI data, we observed activity in bilateral thalamus, anterior cingulate, and supplementary motor cortex that was modulated by trial-by-trial amplitude of CNV. These findings provide a likely functional neuroanatomical substrate for the CNV and demonstrate modulation of components of this neural circuitry by peripheral autonomic arousal. Moreover, these data suggest a mechanistic model whereby thalamocortical interactions regulate CNV amplitude.

Keywords: Adult ; Arousal/*physiology ; Brain/*physiology ; Brain Mapping ; Cerebral Cortex/*physiology ; Contingent Negative Variation/*physiology ; Dominance, Cerebral/physiology ; *Electroencephalography ; Female ; Galvanic Skin Response/physiology ; Gyrus Cinguli/physiology ; Humans ; *Image Enhancement ; *Image Processing, Computer-Assisted ; *Magnetic Resonance Imaging ; Male ; Neural Pathways/physiology ; Oxygen/*blood ; Peripheral Nervous System/physiology ; Psychomotor Performance/physiology ; Reaction Time/physiology ; Research Support, Non-U.S. Gov't ; Sympathetic Nervous System/physiology ; Thalamus/physiology

Simultaneous electroencephalograph-functional magnetic resonance imaging (EEG-fMRI) recording has become an important tool for investigating spatiotemporal properties of brain events, such as epilepsy, evoked brain responses, and changes in brain rhythms. Reduction of noise in EEG signals during fMRI recording is crucial for acquiring high-quality EEG-fMRI data. The main source of the noise includes the gradient artifact, the radio frequency (RF) pulse artifact, and the cardiac pulse artifact. Since the RF pulse artifact is relatively small in amplitude, little attention has been paid to this artifact, and its origin is not well understood. However, the amplitude of the RF pulse artifact fluctuates randomly even if a very high EEG sampling rate is used, making it more salient than the gradient artifact after postprocessing for noise removal. In this paper, we investigate the cause of the RF pulse artifact in EEG systems that use carbon wires.

A two-scale theoretical description outlines relationships between brain current sources and the resulting extracranial electric field, recorded as EEG. Finding unknown sources of EEG, the so-called inverse problem, is discussed in general terms, with emphasis on the fundamental non-uniqueness of inverse solutions. Hemodynamic signatures, measured with fMRI, are expressed as voxel integrals to facilitate comparisons with EEG. Two generally distinct cell groups (1 and 2), generating EEG and fMRI signals respectively, are embedded within the much broader class of synaptic action fields. Cell groups 1 and 2 may or may not overlap in specific experiments. Implications of this incomplete overlap for co-registration studies are considered. Each experimental measure of brain function is generally sensitive to a different kind of source activity and to different spatial and temporal scales. Failure to appreciate such distinctions can exacerbate conflicting views of brain function that emphasize either global integration or functional localization.

Keywords: Brain/*physiology/radionuclide imaging ; *Electroencephalography ; Human ; *Magnetic Resonance Imaging ; Magnetoencephalography ; Models, Neurological ; Synapses/*physiology ; Tomography, Emission-Computed

The last decade has seen an unprecedented increase in the use of functional magnetic resonance imaging (fMRI) to understand the neural basis of cognition and behavior. Being non-invasive and relatively easy to use, most studies relied on changes in the blood oxygenation level dependent (BOLD) contrast as an indirect marker of variations in brain activity. However, the fact that BOLD fMRI is dependent on the blood flow response that follows neural activity and does not measure neural activity per se is seen as an inherent cause for concern while interpreting data from these studies. In order to characterize the BOLD signal correctly, it is imperative that we have a better understanding of neural events that lead to the BOLD response. A review of recent studies that addressed several aspects of BOLD fMRI including events at the level of the synapse, the nature of the neurovascular coupling, and some parameters of the BOLD signal is provided. This is intended to serve as background information for the interpretation of fMRI data in normal subjects and in patients with compromised neurovascular coupling. One of the aims is also to encourage researchers to interpret the results of functional imaging studies in light of the dynamic interactions between different brain regions, something that often is neglected.

There are three physiological alpha rhythms in mature healthy humans: (a) the classical posterior alpha; (b) the Rolandic mu rhythm and (c) the midtemporal 'third rhythm'. The classical posterior alpha rhythm develops out of a 4/s rhythm appearing at age 4 months and gradually reaches the alpha frequency band around age 3 years. The mature frequency around 10/s is subject to subtle physiological changes and grossly decelerates in the face of pathology. No posterior alpha rhythm may be detectable in a minority of healthy adults with an inherited low voltage fast EEG. One is tempted to speculate that these individuals may have a hidden alpha rhythm in neuronal level and defective mechanisms of synchronization. Alpha blocking with visual stimuli (eye opening) is a classical response; responses to mental stimuli (mental arithmetic) are inconsistent, presumably due to the involvement of higher cognitive functions. The Rolandic my rhythm is found with scalp EEG in a minority of subjects but there is good reason to presume that all healthy adults have this rhythm. A particularly powerful mu rhythm reaches the scalp but this could be also an indicator of a mild CNS dysfunction. There is even a relationship between mu rhythm and the central spike activity in children with benign Rolandic epilepsy. The midtemporal third rhythm is not detectable in the scalp EEG unless there are local bone defects. Its functional significance is debatable; its blocking responses encompass various higher cognitive tasks and are inconsistent; responses to auditory stimuli do occur but appear to be of secondary significance. This rhythm arises from midtemporal structures which by far exceed the borders of the auditory cortex. Abnormal rhythmical alpha activity-above all the alpha coma in life-threatening cerebral anoxia -is discussed in order to deepen our understanding of the physiological alpha rhythms. Severe cortical de-afferentation may give rise to cortical autorhythmicity-either in alpha frequency or in other frequency bands. Physiological alpha rhythms are likely to have closer relationships to 'events' than one might have thought earlier. The demonstration of event-related desynchronization and synchronization (in Pfurtscheller's work) clearly underscores this view.

Keywords: *Alpha Rhythm ; Animals ; Brain/*physiology ; *Electroencephalography ; Human

In functional cerebral studies, it has been established that co-registered electroencephalography (EEG) measurements and functional magnetic resonance imaging (fMRI) were complementary. However, EEG data recorded inside an MRI scanner are heavily distorted, mainly by the most prominent artifact, the cardiac pulse artifact (PA). We describe an original algorithm which yields a high-quality PA filter and demonstrates how this tool can be used to improve the quality of P300 ERP measurements during event-related fMRI (e-fMRI) experiments. EEG data were acquired in interleaved mode during e-fMRI while six healthy volunteers performed a visual odd-ball task, involving Distractors, Target and Novel stimuli, to elicit P300 components. The PA was corrected with the original algorithm. The temporal variations in the PA were evidenced using a principal component analysis (PCA), on each EEG channel. The procedure yielded several PA templates, which were regressed from the EEG data. The PA removal procedure was optimised, and then implemented to improve the measured P300 components. Regressing the most adequate PA template resulted in a high-quality reduction in spectral power at frequencies associated with the cardiac PA. More reliable P300 component measurements were obtained, evidencing higher amplitudes for Novels (9.76-11.20 microV) than for to Targets (6.3-9.09 microV) in centro-parietal and prefrontal areas. The improvement of the processing of EEG data acquired simultaneously with fMRI data provides a new tool and casts perspectives to study the functional organisation of the brain.

Keywords: Adult ; *Artifacts ; Brain Mapping ; Cerebral Cortex/blood supply/physiology ; *Diagnostic Techniques, Neurological ; *Electroencephalography ; Event-Related Potentials, P300/*physiology ; Female ; Humans ; Image Processing, Computer-Assisted ; *Magnetic Resonance Imaging ; Male ; *Subtraction Technique

Paramagnetic deoxyhemoglobin in venous blood is a naturally occurring contrast agent for magnetic resonance imaging (MRI). By accentuating the effects of this agent through the use of gradient-echo techniques in high fields, we demonstrate in vivo images of brain microvasculature with image contrast reflecting the blood oxygen level. This blood oxygenation level-dependent (BOLD) contrast follows blood oxygen changes induced by anesthetics, by insulin-induced hypoglycemia, and by inhaled gas mixtures that alter metabolic demand or blood flow. The results suggest that BOLD contrast can be used to provide in vivo real-time maps of blood oxygenation in the brain under normal physiological conditions. BOLD contrast adds an additional feature to magnetic resonance imaging and complements other techniques that are attempting to provide positron emission tomography-like measurements related to regional neural activity.

Keywords: Animals ; *Blood Flow Velocity ; Brain/*anatomy & histology/physiology/physiopathology ; Carbon Dioxide/blood ; *Cerebrovascular Circulation ; Female ; Hemoglobins/*metabolism ; Hypoglycemia/physiopathology ; Kinetics ; Magnetic Resonance Imaging/methods ; Models, Neurological ; Oxygen/*blood ; Rats ; Rats, Inbred Strains

The blood-oxygen-level-dependent (BOLD) signal measured in the brain with functional magnetic resonance imaging (fMRI) during an activation experiment often exhibits pronounced transients at the beginning and end of the stimulus. Such transients could be a reflection of transients in the underlying neural activity, or they could result from transients in cerebral blood flow (CBF), cerebral metabolic rate of oxygen (CMRO2), or cerebral blood volume (CBV). These transients were investigated using an arterial spin labeling (ASL) method that allows simultaneous measurements of BOLD and CBF responses. Responses to a finger-tapping task (40-s stimulus, 80-s rest) were measured in primary motor area (M1) and supplementary motor area (SMA) in five healthy volunteers. In SMA, the average BOLD response was pronounced near the beginning and end of the stimulus, while in M1, the BOLD response was nearly flat. However, CBF responses in the two regions were rather similar, and did not exhibit the same transient features as the BOLD response in SMA. Because this suggests a hemodynamic rather than a neural origin for the transients of the BOLD response in SMA, we used a generalization of the balloon model to test the degree of hemodynamic transients required to produce the measured curves. Both data sets could be approximated with modest differences in the shapes of the CMRO2 and CBV responses. This study illustrates the utility and the limitations of using theoretical models combined with ASL techniques to understand the dynamics of the BOLD response.

Keywords: Adult ; Blood Volume/physiology ; Brain Mapping ; Energy Metabolism/physiology ; Hemoglobins/metabolism ; Humans ; Image Enhancement/*methods ; *Image Processing, Computer-Assisted ; Magnetic Resonance Imaging/*methods ; *Models, Neurological ; Models, Theoretical ; Motor Activity/*physiology ; Motor Cortex/*blood supply/physiology ; Oxygen/*blood ; Oxygen Consumption/physiology ; Reference Values ; Regional Blood Flow/physiology ; Reproducibility of Results ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S. ; Spin Labels

At high magnetic fields (7 and 8.4 T), water proton magnetic resonance images of brains of live mice and rats under pentobarbital anesthetization have been measured by a gradient echo pulse sequence with a spatial resolution of 65 x 65-microns pixel size and 700-microns slice thickness. The contrast in these images depicts anatomical details of the brain by numerous dark lines of various sizes. These lines are absent in the image taken by the usual spin echo sequence. They represent the blood vessels in the image slice and appear when the deoxyhemoglobin content in the red cells increases. This contrast is most pronounced in an anoxy brain but not present in a brain with diamagnetic oxy or carbon monoxide hemoglobin. The local field induced by the magnetic susceptibility change in the blood due to the paramagnetic deoxyhemoglobin causes the intra voxel dephasing of the water signals of the blood and the surrounding tissue. This oxygenation-dependent contrast is appreciable in high field images with high spatial resolution.

Keywords: Animals ; Brain/anatomy & histology/blood supply/*metabolism ; Magnetic Resonance Imaging ; *Magnetic Resonance Spectroscopy/methods ; Mice ; *Oxygen Consumption ; Protons ; Rats ; Rats, Inbred Strains

The relationships between brain electrical and metabolic activity are being uncovered currently in animal models using invasive methods; however, in the human brain this relationship remains not well understood. In particular, the relationship between noninvasive measurements of electrical activity and metabolism remains largely undefined. To understand better these relations, cerebral activity was measured simultaneously with electroencephalography (EEG) and positron emission tomography using [(18)f]-fluoro-2-deoxy-D-glucose (PET-FDG) in 12 normal human subjects during rest. Intracerebral distributions of current density were estimated, yielding tomographic maps for seven standard EEG frequency bands. The PET and EEG data were registered to the same space and voxel dimensions, and correlational maps were created on a voxel-by-voxel basis across all subjects. For each band, significant positive and negative correlations were found that are generally consistent with extant understanding of EEG band power function. With increasing EEG frequency, there was an increase in the number of positively correlated voxels, whereas the lower alpha band (8.5-10.0 Hz) was associated with the highest number of negative correlations. This work presents a method for comparing EEG signals with other more traditionally tomographic functional imaging data on a 3-D basis. This method will be useful in the future when it is applied to functional imaging methods with faster time resolution, such as short half-life PET blood flow tracers and functional magnetic resonance imaging.

Keywords: Adult ; Brain/*metabolism/radionuclide imaging ; Brain Mapping/*methods ; Electroencephalography/*methods ; Energy Metabolism/physiology ; Female ; Fludeoxyglucose F 18/diagnostic use ; Glucose/metabolism ; Human ; Male ; Middle Aged ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S. ; *Tomography, Emission-Computed

In view of the complexity of the conductivity and the geometry of the human head, a numerical method would appear to be necessary for the adequate calculation of the electric potential and the magnetic induction generated by electric sources within the brain. Four numerical methods that could be used for solving this problem are the finite-difference method, the finite-element method, the boundary-element method, and the finite-volume method. These methods could be used to calculate the electric potential and the magnetic induction directly. Alternatively, they could be applied to the electric potential or the electric field and the magnetic induction could then be determined by numerical integration of the Biot-Savart law. In this paper the four numerical methods are briefly reviewed. Thereafter the relative merits of the methods and the various options for using them to solve the EEG and MEG problem are evaluated.

Keywords: Brain Mapping/*methods ; Comparative Study ; *Electroencephalography ; Human ; *Magnetoencephalography ; Mathematics

The locations of the origin of wave M100 of the auditory evoked magnetic field in response to tone bursts of different carrier frequencies, obtained through dipole localization methods (DLM), were related to cerebral structures, displayed by coronal MRI (magnetic resonance imaging) tomograms of the respective subjects. This was done by displaying the landmarks which served as reference for the neuromagnetic measurements in MRI tomogram (reference plane). All calculated source locations project exactly onto the transverse temporal gyri (Heschl) in which the primary auditory cortex, the supposed origin of wave M100, is located. The results highlight the exceptional capabilities of a combination of these 2 non-invasive, high-resolution techniques for functional diagnosis.

Keywords: Auditory Cortex/anatomy & histology/*physiology ; Brain Mapping ; *Electromagnetic Fields ; *Electromagnetics/*methods ; Evoked Potentials ; Human ; *Magnetic Resonance Imaging ; Support, Non-U.S. Gov't

Magnetoencephalography (MEG) is a relatively novel noninvasive technique, with a much shorter history than EEG, that conveys neurophysiological information complementary to that provided by EEG, with high temporal and spatial resolution. Despite its a priori, highly competitive profile, the role of MEG in the clinical setting is still controversial. We briefly review the major obstacles MEG faces in becoming a routine clinical test and the different strategies needed to bypass them. The high cost and complexity associated with MEG equipment are powerful hindrances to wide acceptance of this relatively new technique in clinical practice. The most straightforward advantage is based on the relative facility of MEG recordings in the process of source localization, which also carries some degree of uncertainty, thus partly explaining why the development of clinical applications of MEG has been so slow. Obviously, a decrease in the cost and the elaboration of semiautomatic protocols that could reduce the complexity of the studies and favor the development of consensual strategies, as well as a major effort on the part of clinicians to identify clinical issues where MEG could be decisive, would be most welcome.

Keywords: *Behavior ; Brain/*pathology/physiopathology ; Brain Mapping ; Electroencephalography/methods ; Electromagnetic Fields ; Epilepsy/*diagnosis/physiopathology ; Evoked Potentials/physiology ; Humans ; Magnetoencephalography/economics/*methods

Distributed linear solutions of the EEG source localisation problem are used routinely. In contrast to discrete dipole equivalent models, distributed linear solutions do not assume a fixed number of active sources and rest on a discretised fully 3D representation of the electrical activity of the brain. The ensuing inverse problem is underdetermined and constraints or priors are required to ensure the uniqueness of the solution. In a Bayesian framework, the conditional expectation of the source distribution, given the data, is attained by carefully balancing the minimisation of the residuals induced by noise and the improbability of the estimates as determined by their priors. This balance is specified by hyperparameters that control the relative importance of fitting and conforming to various constraints. Here we formulate the conventional Weighted Minimum Norm (WMN) solution in terms of hierarchical linear models. An Expectation-Maximisation (EM) algorithm is used to obtain a Restricted Maximum Likelihood (ReML) estimate of the hyperparameters, before estimating the Maximum a Posteriori solution itself. This procedure can be considered a generalisation of previous work that encompasses multiple constraints. Our approach was compared with the classic WMN and Maximum Smoothness solutions, using a simplified 2D source model with synthetic noisy data. The ReML solution was assessed with four types of source location priors: no priors, accurate priors, inaccurate priors, and both accurate and inaccurate priors. The ReML approach proved useful as: (1) The regularisation (or influence of the a priori source covariance) increased as the noise level increased. (2) The localisation error (LE) was negligible when accurate location priors were used. (3) When accurate and inaccurate location priors were used simultaneously, the solution was not influenced by the inaccurate priors. The ReML solution was then applied to real somatosensory-evoked responses to illustrate the application in an empirical setting.

Keywords: Algorithms ; Artifacts ; *Bayes Theorem ; Electroencephalography/*statistics & numerical data ; Evoked Potentials, Somatosensory/physiology ; Humans ; Image Processing, Computer-Assisted/*statistics & numerical data ; Likelihood Functions ; Magnetic Resonance Imaging

Distributed linear solutions have frequently been used to solve the source localization problem in EEG. Here we introduce an approach based on the weighted minimum norm (WMN) method that imposes constraints using anatomical and physiological information derived from other imaging modalities. The anatomical constraints are used to reduce the solution space a priori by modeling the spatial source distribution with a set of basis functions. These spatial basis functions are chosen in a principled way using information theory. The reduced problem is then solved with a classical WMN method. Further (functional) constraints can be introduced in the weighting of the solution using fMRI brain responses to augment spatial priors. We used simulated data to explore the behavior of the approach over a range of the model's hyperparameters. To assess the construct validity of our method we compared it with two established approaches to the source localization problem, a simple weighted minimum norm and a maximum smoothness (Loreta-like) solution. This involved simulations, using single and multiple sources that were analyzed under different levels of confidence in the priors.

Keywords: Brain/*anatomy & histology/*physiology ; Brain Mapping/methods ; *Electroencephalography/methods ; Human ; Magnetic Resonance Imaging/methods ; Models, Neurological ; Reproducibility of Results

Distributed linear solutions of the EEG source localization problem are used routinely. Here we describe an approach based on the weighted minimum norm method that imposes constraints using anatomical and physiological information derived from other imaging modalities to regularize the solution. In this approach the hyperparameters controlling the degree of regularization are estimated using restricted maximum likelihood (ReML). EEG data are always contaminated by noise, e.g., exogenous noise and background brain activity. The conditional expectation of the source distribution, given the data, is attained by carefully balancing the minimization of the residuals induced by noise and the improbability of the estimates as determined by their priors. This balance is specified by hyperparameters that control the relative importance of fitting and conforming to prior constraints. Here we introduce a systematic approach to this regularization problem, in the context of a linear observation model we have described previously. In this model, basis functions are extracted to reduce the solution space a priori in the spatial and temporal domains. The basis sets are motivated by knowledge of the evoked EEG response and information theory. In this paper we focus on an iterative expectation-maximization procedure to jointly estimate the conditional expectation of the source distribution and the ReML hyperparameters on which this solution rests. We used simulated data mixed with real EEG noise to explore the behavior of the approach with various source locations, priors, and noise levels. The results enabled us to conclude: (i) Solutions in the space of informed basis functions have a high face and construct validity, in relation to conventional analyses. (ii) The hyperparameters controlling the degree of regularization vary largely with source geometry and noise. The second conclusion speaks to the usefulness of using adaptative ReML hyperparameter estimates.

Keywords: *Algorithms ; Bayes Theorem ; Brain/anatomy & histology/physiology ; Electroencephalography/*statistics & numerical data ; Electromagnetic Fields ; Head/anatomy & histology ; Linear Models ; Models, Anatomic

Keywords: Segmentation

The elucidation of the complex machinery used by the human brain to segregate and integrate information while performing high cognitive functions is a subject of imminent future consequences. The most significant contributions to date in this field, known as cognitive neuroscience, have been achieved by using innovative neuroimaging techniques, such as electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI), which measure variations in both the time and the space of some interpretable physical magnitudes. Extraordinary maps of cerebral activation involving function-restricted brain areas, as well as graphs of the functional connectivity between them, have been obtained from EEG and fMRI data by solving some spatio-temporal inverse problems, which constitutes a top-down approach. However, in many cases, a natural bridge between these maps/graphs and the causal physiological processes is lacking, leading to some misunderstandings in their interpretation. Recent advances in the comprehension of the underlying physiological mechanisms associated with different cerebral scales have provided researchers with an excellent scenario to develop sophisticated biophysical models that permit an integration of these neuroimage modalities, which must share a common aetiology. This paper proposes a bottom-up approach, involving physiological parameters in a specific mesoscopic dynamic equations system. Further observation equations encapsulating the relationship between the mesostates and the EEG/fMRI data are obtained on the basis of the physical foundations of these techniques. A methodology for the estimation of parameters from fused EEG/fMRI data is also presented. In this context, the concepts of activation and effective connectivity are carefully revised. This new approach permits us to examine and discuss some future prospects for the integration of multimodal neuroimages.

Keywords: Brain/anatomy & histology/*physiology ; Brain Mapping/*methods ; *Data Interpretation, Statistical ; Electroencephalography/*methods ; Humans ; Magnetic Resonance Imaging/*methods ; *Models, Neurological ; Psychomotor Performance/physiology ; Regression Analysis ; Time Factors

Magnetic resonance (MR) can offer a unique window on the structure/function relationships in the brain, by utilizing the established link between tissue function, metabolism, and hemodynamics. This report focuses on recent applications of MR-based cerebral blood volume (CBV) imaging in humans. Our methodology uses high-speed single-shot or echo planar imaging techniques, which provide the necessary temporal resolution for mapping the rapid cerebral transit of contrast agents. These MR CBV mapping techniques have been used to study normal human brain task activation and in the clinical study of patients with brain tumors. In the latter, positron emission tomography imaging was used for functional metabolic and CBV correlation. Susceptibility contrast CBV imaging should allow us to improve our understanding of the relationship between the detailed physiology and morphology of the microvascular bed and functional attributes of the brain. These techniques can be applied to understanding fundamental questions of cognitive neuroscience and can aid in improving diagnostic sensitivity and specificity in various neuropathologies.

Keywords: Brain/*anatomy & histology ; Brain Neoplasms/*diagnosis ; Cerebrovascular Circulation/*physiology ; *Contrast Media ; Gadolinium/*diagnostic use ; Gadolinium DTPA ; Humans ; *Magnetic Resonance Imaging ; Organometallic Compounds/*diagnostic use ; Pentetic Acid/*diagnostic use ; Tomography, Emission-Computed ; Visual Cortex/anatomy & histology

The past two decades have seen an enormous growth in the field of human brain mapping. Investigators have extensively exploited techniques such as positron emission tomography and MRI to map patterns of brain activity based on changes in cerebral hemodynamics. However, until recently, most studies have investigated equilibrium changes in blood flow measured over time periods upward of 1 min. The advent of high-speed MRI methods, capable of imaging the entire brain with a temporal resolution of a few seconds, allows for brain mapping based on more transient aspects of the hemodynamic response. Today it is now possible to map changes in cerebrovascular parameters essentially in real time, conferring the ability to observe changes in brain state that occur over time periods of seconds. Furthermore, because robust hemodynamic alterations are detectable after neuronal stimuli lasting only a few tens of milliseconds, a new class of task paradigms designed to measure regional responses to single sensory or cognitive events can now be studied. Such event related functional MRI should provide for fundamentally new ways to interrogate brain function, and allow for the direct comparison and ultimately integration of data acquired by using more traditional behavioral and electrophysiological methods.

Keywords: Brain/*anatomy & histology/*physiology ; Brain Mapping ; Cerebrovascular Circulation/physiology ; Computer Systems ; Human ; *Magnetic Resonance Imaging/instrumentation/methods ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) has become a widely used application in spite of EEG perturbations due to electromagnetic interference in the MR environment. The most prominent and disturbing artifacts in the EEG are caused by the alternating magnetic fields (gradients) of the MR scanner. Different methods for gradient artifact correction have been developed. Here we propose an approach for the systematic evaluation and comparison of these gradient artifact correction methods. Exemplarily, we evaluate different algorithms all based on artifact template subtraction-the currently most established means of gradient artifact removal. We introduce indices for the degree of gradient artifact reduction and physiological signal preservation. The combination of both indices was used as a measure for the overall performance of gradient artifact removal and was shown to be useful in identifying problems during artifact removal. We demonstrate that the evaluation as proposed here allows to reveal frequency-band specific performance differences among the algorithms. This emphasizes the importance of carefully selecting the artifact correction method appropriate for the respective case.

The most significant progresses in the understanding of human brain functions have been possible due to the use of functional magnetic resonance imaging (fMRI), which when used in combination with other standard neuroimaging techniques (i.e., EEG) provides researchers with a potential tool to elucidate many biophysical principles, established previously by animal comparative studies. However, to date, most of the methods proposed in the literature seeking fMRI signs have been limited to the use of a top-down data analysis approach, thus ignoring a pool of physiological facts. In spite of the important contributions achieved by applying these methods to actual data, there is a disproportionate gap between theoretical models and data-analysis strategies while trying to focus on several new prospects, like for example fMRI/EEG data fusion, causality/connectivity patterns, and nonlinear BOLD signal dynamics. In this paper, we propose a new approach which will allow many of the abovementioned hot topics to be addressed in the near future with an underlying interpretability based on bottom-up modeling. In particular, the theta-MAP presented in the paper to test brain activation corresponds very well with the standardized t test of the SPM99 toolbox. Additionally, a new Impulse Response Function (IRF) has been formulated, directly related to the well-established concept of the hemodynamics response function (HRF). The model uses not only the information contained in the signal but also that in the structure of the background noise to simultaneously estimate the IRF and the autocorrelation function (ACF) by using an autoregressive (AR) model with a filtered Poisson process driving the dynamics. The short-range contributions of voxels within the near-neighborhood are also included, and the potential drift was characterized by a polynomial series. Since our model originated from an immediate extension of the hemodynamics approach [Friston, K.J., Mechelli, A., Turner, R., Price C.J. (2000a). Nonlinear responses in fMRI: the balloon model, volterra kernels, and other hemodynamics. NeuroImage 12, 466-477.], a natural interpretability of the results is feasible.

Keywords: Algorithms ; Brain Mapping/*methods ; Cerebrovascular Circulation/physiology ; Cluster Analysis ; Computer Simulation ; Electroencephalography ; Humans ; Linear Models ; Magnetic Resonance Imaging/*methods ; Models, Neurological ; Movement/physiology ; Oxygen/blood ; Photic Stimulation ; Reproducibility of Results

The general linear model (GLM) has been used to analyze simultaneous EEG-fMRI to reveal BOLD changes linked to interictal epileptic discharges (IED) identified on scalp EEG. This approach is ineffective when IED are not evident in the EEG. Data-driven fMRI analysis techniques that do not require an EEG derived model may offer a solution in these circumstances. We compared the findings of independent components analysis (ICA) and EEG-based GLM analyses of fMRI data from eight patients with focal epilepsy. Spatial ICA was used to extract independent components (IC) which were automatically classified as either BOLD-related, motion artefacts, EPI-susceptibility artefacts, large blood vessels, noise at high spatial or temporal frequency. The classifier reduced the number of candidate IC by 78 IC. Concordance between the ICA and GLM-derived results was assessed based on spatio-temporal criteria. In each patient, one of the IC satisfied the criteria to correspond to IED-based GLM result. The remaining IC were consistent with BOLD patterns of spontaneous brain activity and may include epileptic activity that was not evident on the scalp EEG. In conclusion, ICA of fMRI is capable of revealing areas of epileptic activity in patients with focal epilepsy and may be useful for the analysis of EEG-fMRI data in which abnormalities are not apparent on scalp EEG.

A quantitative theory is developed for the relationship between stimulus and the resulting blood oxygen level-dependent (BOLD) functional MRI signal. The relationship of stimuli to neuronal activity during evoked responses is inferred from recent physiology-based quantitative modeling of evoked response potentials (ERPs). A hemodynamic model is then used to calculate the BOLD response to neuronal activity having the form of an impulse, a sinusoid, or an ERP-like damped sinusoid. Using the resulting equations, the BOLD response is analyzed for different forms, frequencies, and amplitudes of stimuli, in contrast with previous research, which has mostly concentrated on sustained stimuli. The BOLD frequency response is found to be closely linear in the parameter ranges of interest, with the form of a low-pass filter with a weak resonance at approximately 0.07 Hz. An improved BOLD impulse response is systematically obtained which includes initial dip and post-stimulus undershoot for some parameter ranges. It is found that the BOLD response depends strongly on the precise temporal course of the evoked neuronal activity, not just its peak value or typical amplitude. Indeed, for short stimuli, the linear BOLD response is closely proportional to the time-integrated activity change evoked by the stimulus, regardless of amplitude. It is concluded that there can be widely differing proportionalities between BOLD and peak activity, that this is the likely reason for the low level of correspondence seen experimentally between ERP sources and BOLD measurements and that non-BOLD measurements, such as ERPs, can be used to correct for this effect to obtain improved activity estimates. Finally, stimulus sequences that optimize the signal-to-noise ratio in event-related BOLD fMRI (efMRI) experiments are derived using the hemodynamic transfer function.

Keywords: Brain/*anatomy & histology/*physiology/radionuclide imaging ; *Cerebrovascular Circulation ; Evoked Potentials ; Hemodynamic Processes ; Humans ; Models, Neurological ; Oxygen/*blood ; Positron-Emission Tomography

In the companion article a local electrovascular coupling (LEVC) model was proposed to explain the continuous dynamics of electrical and vascular states within a cortical unit. These states produce certain mesoscopic reflections whose discrete time series can be reconstructed from electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). In this article we develop a recursive optimization algorithm based on the local linearization (LL) filter and an innovation method to make statistical inferences about the LEVC model from both EEG and fMRI data, i.e., to estimate the unobserved states and the unknown parameters of the model. For a better understanding, the LL filter is described from a Bayesian point of view, providing the particulars for the case of hybrid data (e.g., EEG and fMRI), which could be sampled at different rates. The dynamics of the exogenous synaptic inputs going into the cortical unit are also estimated by introducing a set of Gaussian radial basis functions. In order to study the dynamics of the electrical and vascular states in the striate cortex of humans as well as their local interrelationships, we applied this algorithm to EEG and fMRI recordings obtained concurrently from two subjects while passively observing a radial checkerboard with a white/black pattern reversal. The EEG and fMRI data from the first subject was used to estimate the electrical/vascular states and parameters of the LEVC model in V1 for a 4.0 Hz reversion frequency. We used the EEG data from the second subject to investigate the changes in the dynamics of the electrical states when the frequency of reversion is varied from 0.5-4.0 Hz. Then we made use of the estimated electrical states to predict the effects on the vasculature that such variations produce. Hum Brain Mapp, 2006. (c) 2006 Wiley-Liss, Inc.

The purpose of this study was to establish the relationship between regional CBF and CBV at normal, resting cerebral metabolic rates. Eleven healthy volunteers were investigated with PET during baseline conditions, and during hyper- and hypocapnia. Values for rCBF and rCBV were obtained using (15)O-labelled water and carbon monoxide, respectively. The mean value of rCBF using PET was 62 +/- 18 ml.100 g(-1) min(-1) during baseline conditions, with an average increase of 46% during hypercapnia, and a decrease of 29% during hypocapnia; baseline rCBV was 7.7 ml/100 g, with 27% increase during hypercapnia and no significant decrease during hypocapnia. A regionally uniform exponential relationship was confirmed between P(a)CO(2) and rCBF as well as rCBV. It is shown that the theoretical implication of this is that the rCBV vs. rCBF relationship should be modelled by a power function; however, due to pronounced intersubject variability, the goodness of fit for linear and nonlinear models were not significantly different. The results of the study are applied to a numerical estimation of regional brain deoxy-haemoglobin content. Independently of the choice of model for the rCBV vs. rCBF relationship, a nonlinear deoxy-haemoglobin vs. rCBF relationship was predicted, and the implications for the BOLD response are discussed.

The standard Gaussian function is proposed for the hemodynamic modulation function (HDMF) of functional magnetic resonance imaging (fMRI) time-series. Unlike previously proposed parametric models, the Gaussian model accounts independently for the delay and dispersion of the hemodynamic responses and provides a more flexible and mathematically convenient model. A suboptimal noniterative scheme to estimate the hemodynamic parameters is presented. The ability of the Gaussian function to represent the HDMF of brain activation is compared with Poisson and Gamma models. The proposed model seems valid because the lag and dispersion values of hemodynamic responses rendered by the Gaussian model are in the ranges of their previously reported values in recent optical and fMR imaging studies. An extension of multiple regression analysis to incorporate the HDMF is presented. The detected activity patterns exhibit improvements with hemodynamic correction. The proposed model and efficient parameter estimation scheme facilitated the investigation of variability of hemodynamic parameters of human brain activation. The hemodynamic parameters estimated over different brain regions and across different stimuli showed significant differences. Measurement of hemodynamic parameters over the brain during sensory or cognitive stimulation may reveal vital information on physiological events accompanying neuronal activation and functional variability of the human brain, and should lead to the investigation of more accurate and complex models.

Keywords: Brain/blood supply/*physiology ; *Brain Mapping ; Cerebrovascular Circulation/*physiology ; Discrimination (Psychology) ; Human ; Language ; Magnetic Resonance Imaging/methods ; Mental Processes/*physiology ; *Models, Cardiovascular ; *Models, Neurological ; Models, Statistical ; Normal Distribution ; Photic Stimulation ; Poisson Distribution ; Reaction Time ; Speech Perception/physiology ; Temporal Lobe/physiology ; Visual Perception/physiology

A baseline or control state is fundamental to the understanding of most complex systems. Defining a baseline state in the human brain, arguably our most complex system, poses a particular challenge. Many suspect that left unconstrained, its activity will vary unpredictably. Despite this prediction we identify a baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF. The OEF is defined as the ratio of oxygen used by the brain to oxygen delivered by flowing blood and is remarkably uniform in the awake but resting state (e.g., lying quietly with eyes closed). Local deviations in the OEF represent the physiological basis of signals of changes in neuronal activity obtained with functional MRI during a wide variety of human behaviors. We used quantitative metabolic and circulatory measurements from positron-emission tomography to obtain the OEF regionally throughout the brain. Areas of activation were conspicuous by their absence. All significant deviations from the mean hemisphere OEF were increases, signifying deactivations, and resided almost exclusively in the visual system. Defining the baseline state of an area in this manner attaches meaning to a group of areas that consistently exhibit decreases from this baseline, during a wide variety of goal-directed behaviors monitored with positron-emission tomography and functional MRI. These decreases suggest the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors.

Keywords: Adult ; Aged ; Aged, 80 and over ; Attention/physiology ; Brain/*physiology/radionuclide imaging ; Brain Chemistry ; *Brain Mapping ; Cerebrovascular Circulation ; Female ; Humans ; *Magnetic Resonance Imaging ; Male ; Middle Aged ; *Models, Neurological ; Oxygen/blood ; Oxygen Consumption ; Oxyhemoglobins/analysis ; Parietal Lobe/physiology ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S. ; Rest/*physiology ; Supine Position ; Tomography, Emission-Computed ; Wakefulness/physiology

Acquisition of electroencephalogram (EEG) during functional magnetic resonance imaging (fMRI) provides an additional monitoring tool for the analysis of brain state fluctuations. The exploration of brain responses following inputs or in the context of state changes is crucial for a better understanding of the basic principles governing large-scale neuronal dynamics. State-of-the-art techniques allow EEG activity-from DC (direct current) up to high frequencies in the gamma range-to be acquired simultaneously with fMRI data. In the interleaved mode, spiking activities can also be assessed during concurrent fMRI. The utilization of fMRI evidence to better constrain solutions of the inverse problem of source localization of EEG activity is an exciting possibility. Nonetheless, this approach should be applied cautiously since the degree of overlap between underlying neuronal activity sources is variable and, for the most part, unknown. The ultimate goal is to make joint inferences about the activity, dynamics, and functions by exploiting complementary information from multimodal data sets.

Keywords: Animals ; Brain/*blood supply/*physiology ; *Brain Mapping ; Electroencephalography/*methods ; Humans ; Image Processing, Computer-Assisted/methods ; *Magnetic Resonance Imaging ; Oxygen/blood

Here we present a detailed biophysical model of how brain electrical and vascular dynamics are generated within a basic cortical unit. The model was obtained from coupling a canonical neuronal mass and an expandable vasculature. In this proposal, we address several aspects related to electroencephalographic and functional magnetic resonance imaging data fusion: (1) the impact of the cerebral architecture (at different physical levels) on the observations; (2) the physiology involved in electrovascular coupling; and (3) energetic considerations to gain a better understanding of how the glucose budget is used during neuronal activity. The model has three components. The first is the canonical neural mass model of three subpopulations of neurons that respond to incoming excitatory synaptic inputs. The generation of the membrane potentials in the somas of these neurons and the electric currents flowing in the neuropil are modeled by this component. The second and third components model the electrovascular coupling and the dynamics of vascular states in an extended balloon approach, respectively. In the first part we describe, in some detail, the biophysical model and establish its face validity using simulations of visually evoked responses under different flickering frequencies and luminous contrasts. In a second part, a recursive optimization algorithm is developed and used to make statistical inferences about this forward/generative model from actual data. Hum. Brain Mapping 2006. (c) 2006 Wiley-Liss, Inc.

Recent work has demonstrated the feasibility of simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Virtually no systematic comparisons between EEG recorded inside and outside the MR scanner have been conducted, and it is unknown if different kinds of frequency mix, topography, and domain-specific processing are uniformly recordable within the scanner environment. The aim of the study was to investigate several typical EEG waveforms in the same subjects inside the magnet during fMRI and outside the MR examination room. We examined whether uniform artifact subtraction allows the extraction of these different EEG waveforms inside the scanner during EPI scanning to the same extent as outside the scanner. Three well-established experiments were conducted, eliciting steady state visual evoked potentials (SSVEP), lateralized readiness potentials (LRP), and frontal theta enhancement induced by mental addition. All waveforms could be extracted from the EEG recorded during fMRI. Substantially no differences in these waveforms of interest were found between gradient-switching and intermediate epochs during fMRI (only the SSVEP-experiment was designed for a comparison of gradient-with intermediate epochs), or between waveforms recorded inside the scanner during EPI scanning and outside the MR examination room (all experiments). However, non-specific amplitude differences were found between inside and outside recorded EEG at lateral electrodes, which were not in any interaction with the effects of interest. The source of these differences requires further exploration. The high concordance of activation patterns with published results demonstrates that EPI-images could be acquired during EEG recording without significant distortion.

Using group functional Magnetic Resonance Imaging (fMRI) and group Magnetoencephalography (MEG) we studied two cognitive paradigms: A language task involving covert letter fluency and a visual task involving biological motion direction discrimination. The MEG data were analyzed using an adaptive beam-former technique known as Synthetic Aperture Magnetometry (SAM), which provides continuous 3-D images of cortical power changes. These images were spatially normalized and averaged across subjects to provide a group SAM image in the same template space as the group fMRI data. The results show that frequency-specific, task-related changes in cortical synchronization, detected using MEG, match those areas of the brain showing an evoked cortical hemodynamic response with fMRI. The majority of these changes were event-related desynchronizations (ERDs) in the 5-10 Hz and 15-25 Hz frequency ranges. Our study demonstrates how SAM, spatial normalization, and intersubject averaging enable group MEG studies to be performed. SAM analysis also allows the MEG experiment to have exactly the same task design as the corresponding fMRI experiment. This new analysis framework represents an important advance in the use of MEG as a cognitive neuroimaging technique and also allows mutual cross-validation with fMRI.

Keywords: Adult ; Cerebral Cortex/anatomy & histology/physiology ; Cerebrovascular Circulation/*physiology ; *Cortical Synchronization ; Discrimination (Psychology)/physiology ; Female ; Human ; Magnetic Resonance Imaging ; Magnetoencephalography ; Male ; Motion Perception/physiology ; Nerve Net/anatomy & histology/physiology ; Psychomotor Performance/physiology ; Support, Non-U.S. Gov't

The ability to trigger functional magnetic resonance imaging (fMRI) acquisitions related to the occurrence of EEG-based physiologic transients has changed the field of fMRI into a more dynamically based technique. By knowing the temporal relationship between focal increases in neuronal firing rates and the provoked focal increase in blood flow, investigators are able to maximize the fMR-linked images that show where the activity originates. Our mastery of recording EEG inside the bore of a MR scanner has also allowed us to develop cognitive paradigms that record not only the fMR BOLD images, but also the evoked potentials (EPs). The EPs can subsequently be subjected to localization paradigms that can be compared to the localization seen on the BOLD images. These two techniques will most probably be complimentary. BOLD responses are dependent on a focal increase in metabolic demand while the EPs may or may not be related to energy demand increases. Additionally, recording EPs require that the source or sources of that potential come from an area that is able to generate far-field potentials. These potentials are related to the laminar organization of the neuronal population generating that potential. As best we know the BOLD response does not depend on any inherent laminar neuronal organization. Therefore, by merging these two recording methods, it is likely that we will gain a more detailed understanding of not only the areas involved in certain physiologic events, e.g. focal epilepsy or cognitive processing, but also on the sequencing of the activation of the various participating regions.

Keywords: Artifacts ; Brain Diseases/complications/*diagnosis/physiopathology ; Electrodes ; Electroencephalography/instrumentation/*methods ; Epilepsy/*etiology/physiopathology ; Equipment Design ; Evoked Potentials/physiology ; Human ; Image Enhancement/methods ; Magnetic Resonance Imaging/*methods ; Signal Processing, Computer-Assisted

We develop a novel approach of cross-modal correspondence analysis (CMCA) to address whether brain activities observed in magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) represent a common neuronal subpopulation, and if so, which frequency band obtained by MEG best fits the common brain areas. Fourteen adults were investigated by whole-head MEG using a single equivalent current dipole (ECD) and synthetic aperture magnetometry (SAM) approaches and by fMRI at 1.5 T using linear time-invariant modeling to generate statistical maps. The same somatosensory stimulus sequences consisting of tactile impulses to the right sided: digit 1, digit 4 and lower lip were used in both neuroimaging modalities. To evaluate the reproducibility of MEG and fMRI results, one subject was measured repeatedly. Despite different MEG dipole locations and locations of maximum activation in SAM and fMRI, CMCA revealed a common subpopulation of the primary somatosensory cortex, which displays a clear homuncular organization. MEG activity in the frequency range between 30 and 60 Hz, followed by the ranges of 20-30 and 60-100 Hz, explained best the defined subrepresentation given by both MEG and fMRI. These findings have important implications for improving and understanding of the biophysics underlying both neuroimaging techniques, and for determining the best strategy to combine MEG and fMRI data to study the spatiotemporal nature of brain activity.

Keywords: forward problems inverse problems forward simulation inverse solutions, finite elements, forward simulation, anisotropy, thalamus

Electroencephalogram (EEG) data acquired in the MRI scanner contains significant artifacts, one of the most prominent of which is ballistocardiogram (BCG) artifact. BCG artifacts are generated by movement of EEG electrodes inside the magnetic field due to pulsatile changes in blood flow tied to the cardiac cycle. Independent Component Analysis (ICA) is a statistical algorithm that is useful for removing artifacts that are linearly and independently mixed with signals of interest. Here, we demonstrate and validate the usefulness of ICA in removing BCG artifacts from EEG data acquired in the MRI scanner. In accordance with our hypothesis that BCG artifacts are physiologically independent from EEG, it was found that ICA consistently resulted in five to six independent components representing the BCG artifact. Following removal of these components, a significant reduction in spectral power at frequencies associated with the BCG artifact was observed. We also show that our ICA-based procedures perform significantly better than noise-cancellation methods that rely on estimation and subtraction of averaged artifact waveforms from the recorded EEG. Additionally, the proposed ICA-based method has the advantage that it is useful in situations where ECG reference signals are corrupted or not available.

Near-infrared spectroscopy (NIRS) has been used to noninvasively monitor adult human brain function in a wide variety of tasks. While rough spatial correspondences with maps generated from functional magnetic resonance imaging (fMRI) have been found in such experiments, the amplitude correspondences between the two recording modalities have not been fully characterized. To do so, we simultaneously acquired NIRS and blood-oxygenation level-dependent (BOLD) fMRI data and compared Delta(1/BOLD) (approximately R(2)(*)) to changes in oxyhemoglobin, deoxyhemoglobin, and total hemoglobin concentrations derived from the NIRS data from subjects performing a simple motor task. We expected the correlation with deoxyhemoglobin to be strongest, due to the causal relation between changes in deoxyhemoglobin concentrations and BOLD signal. Instead we found highly variable correlations, suggesting the need to account for individual subject differences in our NIRS calculations. We argue that the variability resulted from systematic errors associated with each of the signals, including: (1) partial volume errors due to focal concentration changes, (2) wavelength dependence of this partial volume effect, (3) tissue model errors, and (4) possible spatial incongruence between oxy- and deoxyhemoglobin concentration changes. After such effects were accounted for, strong correlations were found between fMRI changes and all optical measures, with oxyhemoglobin providing the strongest correlation. Importantly, this finding held even when including scalp, skull, and inactive brain tissue in the average BOLD signal. This may reflect, at least in part, the superior contrast-to-noise ratio for oxyhemoglobin relative to deoxyhemoglobin (from optical measurements), rather than physiology related to BOLD signal interpretation.

Keywords: Adult ; Brain/*physiology ; Brain Chemistry/*physiology ; Comparative Study ; Data Interpretation, Statistical ; Diffusion ; Hemoglobins/metabolism ; Human ; Magnetic Resonance Imaging/*methods ; Oxygen/*blood ; Spectroscopy, Near-Infrared/*methods ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, Non-P.H.S. ; Support, U.S. Gov't, P.H.S.

Using continuous EEG-correlated fMRI, we investigated the Blood Oxygen Level Dependent (BOLD) signal correlates of interictal epileptic discharges (IEDs) in 63 consecutively recruited patients with focal epilepsy. Semi-automated spike detection and advanced modeling strategies are introduced to account for different EEG event types, and to minimize false activations from uncontrolled motion. We show that: (1) significant hemodynamic correlates were detectable in over 68 and were highly, but not entirely, concordant with site(s) of presumed seizure generation where known; (2) deactivations were less concordant and may non-specifically reflect the consequential or downstream effects of IEDs on brain activity; (3) a striking pattern of retrosplenial deactivation was observed in 7 cases mainly with focal discharges; (4) the basic hemodynamic response to IEDs is physiological; (5) incorporating information about different types of IEDs, their durations and saturation effects resulted in more powerful models for the detection of fMRI correlates; (6) focal activations were more likely when there was good electroclinical localization, frequent stereotyped spikes, less head motion and less background EEG abnormality, but were also seen in patients in whom the electroclinical focus localization was uncertain. These findings provide important new information on the optimal use and interpretation of EEG-fMRI in focal epilepsy and suggest a possible role for EEG-fMRI in providing new targets for invasive EEG monitoring.

The multifaceted technological challenge of acquiring simultaneous EEG-correlated fMRI data has now been met and the potential exists for mapping electrophysiological activity with unprecedented spatio-temporal resolution. Work has already begun on studying a host of spontaneous EEG phenomena ranging from alpha rhythm and sleep patterns to epileptiform discharges and seizures, with far reaching clinical implications. However, the transformation of EEG data into linear models suitable for voxel-based statistical hypothesis testing is central to the endeavour. This in turn is predicated upon a number of assumptions regarding the manner in which the generators of EEG phenomena may engender changes in the blood oxygen level dependent (BOLD) signal. Furthermore, important limitations are posed by a set of considerations quite unique to 'paradigmless fMRI'. Here, these issues are assembled and explored to provide an overview of progress made and unresolved questions, with an emphasis on applications in epilepsy.

We present a Monte Carlo analysis method for evaluating MRI-MEG/EEG co-registration techniques. The method estimates the error in co-registration as a function of position within the brain. Using this analysis technique, we demonstrate the limitations of conventional head-based fiducial point methods, and propose a new strategy utilising a dental bite-bar incorporating accurately machined fiducial markers. Results presented demonstrate the improved accuracy of MEG/EEG to MRI co-registration using the bite-bar.

Keywords: Brain/*physiology ; *Electroencephalography ; Human ; *Magnetic Resonance Imaging ; *Magnetoencephalography ; *Monte Carlo Method ; Reference Standards

Functional magnetic resonance imaging (fMRI) is used to investigate where the neural implementation of specific cognitive processes occurs. The standard approach uses linear convolution models that relate experimentally designed inputs, through a haemodynamic response function, to observed blood oxygen level dependent (BOLD) signals. Such models are, however, blind to the causal mechanisms that underlie observed BOLD responses. Recent developments have focused on how BOLD responses are generated and include biophysical input-state-output models with neural and haemodynamic state equations and models of functional integration that explain local dynamics through interactions with remote areas. Forward models with parameters at the neural level, such as dynamic causal modelling, combine both approaches, modelling the whole causal chain from external stimuli, via induced neural dynamics, to observed BOLD responses.

The correlation between signals acquired using electroencephalography (EEG) and fMRI was investigated in humans during visual stimulation. Evoked potential EEG and BOLD fMRI data were acquired independently under similar conditions from eight subjects during stimulation by a checkerboard flashed at frequencies ranging from 2-12 Hz. The results indicate highly correlated changes in the strength of the EEG signal averaged over two occipital electrodes and the BOLD signal within the occipital lobe as a function of flash frequency for 7/8 subjects (average linear correlation coefficient of 0.76). Both signals peaked at approximately 8 Hz. For one subject the correlation coefficient was 0.20; the EEG signal peaked at 6 Hz and the BOLD signal peaked at 10 Hz. Overall, the EEG and BOLD signals, each averaged over 40-sec stimulation periods, appear to be coupled linearly during visual stimulation by a flashing checkerboard.

Keywords: *Brain Mapping ; *Cerebrovascular Circulation ; Comparative Study ; *Electroencephalography ; Evoked Potentials, Visual ; Human ; *Magnetic Resonance Imaging ; Oxygen/*blood ; *Photic Stimulation ; Support, U.S. Gov't, P.H.S.

We studied the effect of use of contextual information on the reproducibility of the results in analysis of fMRI data. We used data from a repeated simple motor fMRI experiment. In the first approach, statistical parametric maps were computed from a spatially unsmoothed data and thresholded using a Bonferroni corrected threshold. In the second approach, the maps were computed from a spatially unsmoothed data but were segmented into nonactive and active regions using a spatial contextual clustering method. In the third approach, the statistical parametric maps were computed from spatially smoothed data and thresholded, using, optionally, a spatial extent threshold. The variation in the classification was largest in the Bonferroni thresholded statistical parametric maps. There were no significant differences in variation between statistical parametric maps generated with all the other methods. In addition to reproducibility, the detection rates of weak simulated activations in the presence of measured scanner and physiological noise were investigated. Contextual clustering method was the most sensitive method, while the least sensitive method was the Bonferroni corrected thresholding. Using simulated data, we demonstrated that the contextual clustering method preserves the shapes of activation regions better than the method using spatial smoothing of the data.

Keywords: Adult ; Attention/*physiology ; *Brain Mapping ; Cerebral Cortex/*physiology ; Cluster Analysis ; Comparative Study ; Echo-Planar Imaging ; Human ; *Image Processing, Computer-Assisted ; *Magnetic Resonance Imaging ; Motor Activity/*physiology ; Pattern Recognition, Visual ; Phantoms, Imaging ; Sensitivity and Specificity ; Support, Non-U.S. Gov't

In this paper dynamic inverse problems are studied, where the investigated object is allowed to change during the measurement procedure. In order to achieve reasonable results, temporal a priori information will be considered. Here, &lquot;temporal smoothness&rquot; is used as a quite general, but for many applications sufficient, a priori information. This is justified in the case of slight movements during an x-ray scan in computerized tomography, or in the field of current density reconstruction, where one wants to conclude from electrical measurements on the surface of the head, the locations of brain activity. First, the notion of a dynamic inverse problem is introduced, then we describe how temporal smoothness can be incorporated in the regularization of the problem, and finally an efficient solver and some regularization properties of this solver are presented. This theory will be exploited in three practically relevant applications in a following paper.

We present a new approach for non-invasive localization of focal epileptogenic discharges in patients considered for surgical treatment. EEG-triggered functional MR imaging (fMRI) and 3D EEG source localization were combined to map the primary electrical source with high spatial resolution. The method is illustrated by the case of a patient with medically intractable frontal lobe epilepsy. EEG obtained in the MRI system allowed triggering of the fMRI acquisition by the patient's habitual epileptogenic discharges. fMRI revealed multiple areas of signal enhancement. Three-dimensional EEG source localization identified the same active areas and provided evidence of onset in the left frontal lobe. Subsequent electrocorticography from subdural electrodes confirmed spike and seizure onset over this region. This approach, i.e. the combination of EEG-triggered fMRI and 3D EEG source analysis, represents a promising additional tool for presurgical epilepsy evaluation allowing precise non-invasive identification of the epileptic foci.

Keywords: Adolescent ; Electroencephalography/*methods ; Epilepsies, Partial/*physiopathology ; Epilepsy, Frontal Lobe/*physiopathology ; Female ; Human ; Image Processing, Computer-Assisted ; Magnetic Resonance Imaging/*methods ; Magnetoencephalography/*methods ; Support, Non-U.S. Gov't ; Tomography

The primary goal of the study was to compare estimates of motor cortex localization from functional magnetic resonance imaging (FMRI) and magnetoencephalography (MEG). Thirteen normal volunteers were studied using both methods. FMRI was performed on a clinical 1.5 T system using gradient-echo acquisitions and basic t-test processing. MEG primary motor field was characterized by a single dipole model. Comparisons between the location of the best-fitting MEG dipole and the FMRI activation results were made using both fixed regions-of-interest weighted averaging and clustering analysis to reduce the observed FMRI activations to a single representative location.Both FMRI and MEG identified expected anatomic regions of primary motor activity and there was overall agreement to within 10 mm between these two functional imaging modalities. Given the observed agreement between these two techniques, it does not appear that the proposed artifactual mechanisms of local bulk motions or large-vessel sensitivity will seriously preclude the clinical utility of FMRI for preoperative localization of sensorimotor cortex. © 1996 Wiley-Liss, Inc.

In the first part of this paper the notion of dynamic inverse problems was introduced and two procedures, namely STR and STR-C, for the efficient spatio-temporal regularization of such problems were developed. In this part the application of the new methods to three practically important problems, namely dynamic computerized tomography, dynamic electrical impedance tomography and spatio-temporal current density reconstructions will be presented. Dynamic reconstructions will be carried out in simulated objects which show the quality of the methods and the efficiency of the solution process. A comparison to a Kalman smoother approach will be given for dynEIT.

Humans are capable of recognizing objects, often despite highly adverse viewing conditions (e.g., occlusion). The term perceptual closure has been used to refer to the neural processes responsible for filling-in missing information in the visual image under such conditions. Closure phenomena have been linked to a group of object recognition areas, the so-called lateral-occipital complex (LOC). Here, we investigated the spatiotemporal dynamics of perceptual closure processes by coregistering data from high-density electrical recordings (ERPs) and functional magnetic resonance imaging (fMRI) while subjects participated in a perceptual closure task. Subjects were presented with highly fragmented images and control scrambled images. Fragmented images were calibrated to be 'just' recognizable as objects (that is, perceptual closure was necessary), whereas the scrambled images were unrecognizable. Comparison of responses to these two stimulus classes revealed the neural processes underlying perceptual closure. fMRI revealed an object recognition system that mediates these closure processes, the core of which consists of the LOC regions. ERP recordings resulted in the well-characterized N(CL) component (for negativity associated with closure), a robust relative negativity over bilateral occipito-temporal scalp that occurs in the 230-400 ms timeframe. Our investigations further revealed an extended network of dorsal and frontal regions, also involved in perceptual closure processes. Inverse source analysis showed that the major generators of N(CL) localized to the identical regions within LOC revealed by the fMRI recordings and detailed the temporal dynamics across these LOC regions including interactions between LOC and these other nodes of the object recognition circuit.

The ballistocardiogram (BCG) represents one of the most prominent sources of artifacts that contaminate the electroencephalogram (EEG) during functional MRI. The BCG artifacts may affect the detection of interictal epileptiform discharges (IED) in patients with epilepsy, reducing the sensitivity of the combined EEG-fMRI method. In this study we improved the BCG artifact correction using a multiple source correction (MSC) approach. On the one hand, a source analysis of the IEDs was applied to the EEG data obtained outside the MRI scanner to prevent the distortion of EEG signals of interest during the correction of BCG artifacts. On the other hand, the topographies of the BCG artifacts were defined based on the EEG recorded inside the scanner. The topographies of the BCG artifacts were then added to the surrogate model of IED sources and a combined source model was applied to the data obtained inside the scanner. The artifact signal was then subtracted without considerable distortion of the IED topography. The MSC approach was compared with the traditional averaged artifact subtraction (AAS) method. Both methods reduced the spectral power of BCG-related harmonics and enabled better detection of IEDs. Compared with the conventional AAS method, the MSC approach increased the sensitivity of IED detection because the IED signal was less attenuated when subtracting the BCG artifacts. The proposed MSC method is particularly useful in situations in which the BCG artifact is spatially correlated and time-locked with the EEG signal produced by the focal brain activity of interest.

The ability to continuously acquire simultaneous EEG and fMRI data during seizures presents a formidable challenge both clinically and technically. Published ictal fMRI reports have so far been unable to benefit from simultaneous electrographic recordings and remain largely assumptive. Unique findings from a Continuous EEG-correlated fMRI experiment are presented in which a focal subclinical seizure was captured in its entirety. For the first time dynamic and biphasic Blood Oxygen Level Dependent (BOLD) signal changes are shown using statistical parametric mapping time-locked to the ictal EEG activity localizing seizure generation and propagation sites, with millimeter resolution, to electroclinically concordant gray matter structures. Though presently of limited clinical applicability, a new avenue is opened for further research.

Keywords: Brain Mapping ; *Electroencephalography ; Epilepsy/*pathology/*physiopathology ; Epilepsy, Tonic-Clonic/pathology/physiopathology ; Fourier Analysis ; Human ; Image Processing, Computer-Assisted ; *Magnetic Resonance Imaging ; Male ; Middle Aged ; Oxygen/blood ; Support, Non-U.S. Gov't ; Telemetry

During a Magnetic Resonance sequence, simultaneously acquired ElectroEncephaloGraphy (EEG) data are compromised by severe pollution due to artifacts originating from the switching of the magnetic field gradients. In this work, it is shown how these artifacts can be strongly reduced or even removed through application of an adaptive artifact restoration scheme. The method has proved to be fully automatic and to retain high frequency EEG information, which is indispensable for many EEG applications.

Keywords: Animals ; *Artifacts ; Electroencephalography/instrumentation/*methods ; Image Processing, Computer-Assisted/methods ; Magnetic Resonance Imaging/instrumentation/*methods ; Rats ; Rats, Wistar ; Support, Non-U.S. Gov't

The study investigates the possibility of combined recording event-related potentials (ERPs) and functional MRI (fMRI). Visual evoked potentials (VEPs) were elicited by an alternating black and white checkerboard, which was presented blockwise outside the static 1.5 T magnetic field and during an echo planar imaging (EPI). An fMRI sequence with a time window for interleaved EEG-measurement and a measurement protocol which reduces pulse artifacts and vibrations was used. Thus, during an EPI sequence, it was possible to detect VEPs which had the same structure and latencies as VEPs outside the magnetic field and which corresponded well with the observed activated areas of the visual cortex.

Keywords: Adult ; Brain/*physiology ; *Echo-Planar Imaging ; *Electroencephalography ; *Evoked Potentials, Visual ; Female ; Human ; Male ; Reaction Time

Due to its low computational complexity, finite difference modeling offers a viable tool for studying bioelectric problems, allowing the field behavior to be observed easily as different system parameters are varied. Previous finite difference formulations, however, have been limited mainly to systems in which the conductivity is orthotropic, i.e., a strictly diagonal conductivity tensor. This in turn has limited the effectiveness of the finite difference, technique in modeling complex anatomies with arbitrarily anisotropic conductivities, e.g., detailed fiber structures of muscles where the fiber can lie in any arbitrary direction. In this paper, we present both two-dimensional and three-dimensional finite difference formulations that are valid for structures with an inhomogeneous and nondiagonal conductivity tensor. A data parallel computer, the connection machine CM-5, is used in the finite difference implementation to provide the computational power and memory for solving large problems. The finite difference grid is mapped effectively to the CM-5 by associating a group of nodes with one processor. Details on the new approach and its data parallel implementation are presented together with validation and computational performance results. In addition, an application of the new formulation in providing the potential distribution inside a canine torso during electrical defibrillation is demonstrated.

Keywords: Algorithms ; Animals ; Anisotropy ; *Computer Simulation ; Dogs ; Electric Conductivity ; *Electric Countershock ; *Models, Cardiovascular ; Radiography, Thoracic ; Support, U.S. Gov't, P.H.S. ; Tomography, X-Ray Computed

Simultaneous electroencephalography (EEG)/functional magnetic resonance imaging (fMRI) acquisition can identify the brain networks involved in generating specific EEG patterns. Yet, the combination of these methodologies is hampered by strong artifacts that arise due to electromagnetic interference during magnetic resonance (MR) image acquisition. Here, we report corrections of the gradient-induced artifact in phantom measurements and in experiments with an awake behaving macaque monkey during fMRI acquisition at a magnetic field strength of 4.7 T. Ninety-one percent of the amplitude of a 10 microV, 10 Hz phantom signal could successfully be recovered without phase distortions. Using this method, we were able to extract the monkey EEG from scalp recordings obtained during MR image acquisition. Visual evoked potentials could also be reliably identified. In conclusion, simultaneous EEG/fMRI acquisition is feasible in the macaque monkey preparation at 4.7 T and holds promise for investigating the neural processes that give rise to particular EEG patterns.

Hemodynamic responses to auditory and visual stimuli and motor tasks were assessed for the nonlinearity of response in each of the respective primary cortices. Five stimulus or task durations were used (1, 2, 4, 8, and 16 s), and five male subjects (aged 19 +/- 1.9 years) were imaged. Two tests of linearity were conducted. The first test consisted of using BOLD responses to short stimuli to predict responses to longer stimuli. The second test consisted of fitting ideal impulse response functions to the observed responses for each event duration. Both methods show that the extent of the nonlinearity varies across cortices. Results for the second method indicate that the hemodynamic response is nonlinear for stimuli less than 10 s in the primary auditory cortex, nonlinear for tasks less than 7 s in the primary motor cortex, and nonlinear for stimuli less than 3 s in the primary visual cortex. In addition, neural adaptation functions were characterized that could model the observed nonlinearities.

Keywords: Acoustic Stimulation ; Adaptation, Physiological ; Adult ; Algorithms ; Cerebral Cortex/*blood supply/physiology ; *Cerebrovascular Circulation ; Comparative Study ; Hemodynamic Processes ; Human ; Linear Models ; Male ; *Models, Cardiovascular ; Motor Activity/physiology ; *Nonlinear Dynamics ; Photic Stimulation ; Physical Stimulation ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, P.H.S.

Blood oxygenation level-dependent functional magnetic resonance imaging (BOLD-fMRI) is widely used as a tool for functional brain mapping. During brain activation, increases in the regional blood flow lead to an increase in blood oxygenation and a decrease in paramagnetic deoxygenated hemoglobin (deoxy-Hb), causing an increase in the MR signal intensity at the site of brain activation. However, not a few studies using fMRI have failed to detect activation of areas that ought to have been activated. We assigned BOLD-positive (an increase in the signal intensity), BOLD-negative (a decrease in the signal intensity), and BOLD-silent (no change) brain activation to respective circulatory conditions through a description of fMRI signals as a function of the concentration of oxygenated Hb (oxy-Hb) and deoxy-Hb obtained with near-infrared optical imaging (NIOI). Using this model, we explain the sensory motor paradox in terms of BOLD-positive, BOLD-negative, and BOLD-silent brain activation.

Keywords: Adult ; Afferent Pathways/physiology ; Arousal/*physiology ; Brain/*blood supply ; Brain Mapping ; Electric Stimulation ; *Electroencephalography ; Evoked Potentials/physiology ; Female ; Hemoglobins/metabolism ; Human ; *Image Enhancement ; *Image Processing, Computer-Assisted ; *Imaging, Three-Dimensional ; Laser-Doppler Flowmetry ; *Magnetic Resonance Imaging ; Male ; Median Nerve/physiology ; Middle Aged ; Motor Cortex/physiology ; Oxygen/*blood ; Oxygen Consumption/physiology ; Oxyhemoglobins/metabolism ; Pattern Recognition, Visual/physiology ; Photic Stimulation ; Reference Values ; Somatosensory Cortex/physiology ; Support, Non-U.S. Gov't ; *Tomography, Optical ; Visual Cortex/physiology

The electrical activity of the brain can be monitored using ElectroEncephaloGraphy (EEG). From the positions of the EEG electrodes, it is possible to localize focal brain activity. Thereby, the accuracy of the localization strongly depends on the accuracy with which the positions of the electrodes can be determined. In this work, we present an automatic, simple, and accurate scheme that detects EEG electrode markers from 3D MR data of the human head.

Keywords: *Electrodes ; *Electroencephalography/instrumentation/methods ; Human ; *Image Processing, Computer-Assisted ; *Magnetic Resonance Imaging ; Support, Non-U.S. Gov't

The classical model of blood oxygen level-dependent (BOLD) responses by Buxton et al. [Buxton, R.B., Wong, E.C., Frank, L.R., 1998. Dynamics of blood flow and oxygenation changes during brain activation: the Balloon model. Magn. Reson. Med. 39, 855-864] has been very important in providing a biophysically plausible framework for explaining different aspects of hemodynamic responses. It also plays an important role in the hemodynamic forward model for dynamic causal modeling (DCM) of fMRI data. A recent study by Obata et al. [Obata, T., Liu, T.T., Miller, K.L., Luh, W.M., Wong, E.C., Frank, L.R., Buxton, R.B., 2004. Discrepancies between BOLD and flow dynamics in primary and supplementary motor areas: application of the Balloon model to the interpretation of BOLD transients. NeuroImage 21, 144-153] linearized the BOLD signal equation and suggested a revised form for the model coefficients. In this paper, we show that the classical and revised models are special cases of a generalized model. The BOLD signal equation of this generalized model can be reduced to that of the classical Buxton model by simplifying the coefficients or can be linearized to give the Obata model. Given the importance of hemodynamic models for investigating BOLD responses and analyses of effective connectivity with DCM, the question arises which formulation is the best model for empirically measured BOLD responses. In this article, we address this question by embedding different variants of the BOLD signal equation in a well-established DCM of functional interactions among visual areas. This allows us to compare the ensuing models using Bayesian model selection. Our model comparison approach had a factorial structure, comparing eight different hemodynamic models based on (i) classical vs. revised forms for the coefficients, (ii) linear vs. non-linear output equations, and (iii) fixed vs. free parameters, epsilon, for region-specific ratios of intra- and extravascular signals. Using fMRI data from a group of twelve subjects, we demonstrate that the best model is a non-linear model with a revised form for the coefficients, in which epsilon is treated as a free parameter.

Functional magnetic resonance imaging (fMRI) was used to investigate the changes in blood oxygenation level dependent (BOLD) signal, cerebral blood flow (CBF) and cerebral metabolic rate of oxygen consumption (CMR(O(2))) accompanying neuronal inhibition. Eight healthy volunteers performed a periodic right-hand pinch grip every second using 5% of their maximum voluntary contraction (MVC), a paradigm previously shown to produce robust ipsilateral neuronal inhibition. To simultaneously quantify CBF and BOLD signals, an interleaved multislice pulsed arterial spin labeling (PASL) and T(2)*-weighted gradient echo sequence was employed. The CMR(O(2)) was calculated using the deoxyhemoglobin dilution model, calibrated by data measured during graded hypercapnia. In all subjects, BOLD, CBF and CMR(O(2)) signals increased in the contralateral and decreased in the ipsilateral primary motor (M1) cortex. The relative changes in CMR(O(2)) and CBF were linearly related, with a slope of approximately 0.4. The coupling ratio thus established for both positive and negative CMR(O(2)) and CBF changes is in close agreement with the ones observed by earlier studies investigating M1 perfusion and oxygen consumption increases. These findings characterize the hemodynamic and metabolic downregulation accompanying neuronal inhibition and thereby establish the sustained negative BOLD response as a marker of neuronal deactivation.

In this paper basic mathematical and physical concepts of the biomagnetic inverse problem are reviewed with some new approaches. The forward problem is discussed for both homogeneous and inhomogeneous media. Geselowitz' formulae and a surface integral equation are presented to handle a piecewise homogeneous conductor. The special cases of a spherically symmetric conductor and a horizontally layered medium are discussed in detail. The non-uniqueness of the solution of the magnetic inverse problem is discussed and the difficulty caused by the contribution of the electric potential to the magnetic field outside the conductor is studied. As practical methods of solving the inverse problem, a weighted least-squares search with confidence limits and the method of minimum norm estimate are discussed.

Keywords: Animals ; Electric Conductivity ; Human ; *Magnetics ; Mathematics ; *Models, Biological ; Support, Non-U.S. Gov't

There is increasing evidence that neuronal networks can operate with a temporal resolution in the millisecond range. In principle, this provides the option to encode information not only in the amplitude of neuronal responses but also in the precise temporal relations between the discharges of distributed neurons.

Keywords: Acoustic Stimulation ; Animals ; Excitatory Postsynaptic Potentials ; Humans ; Nerve Net/*physiology ; Neurons/*physiology ; Psychophysics ; Signal Transduction/physiology ; Synaptic Transmission/*physiology ; Time Factors

In this paper, the Bayesian Theory is used to formulate the Inverse Problem (IP) of the EEG/MEG. This formulation offers a comparison framework for the wide range of inverse methods available and allows us to address the problem of model uncertainty that arises when dealing with different solutions for a single data. In this case, each model is defined by the set of assumptions of the inverse method used, as well as by the functional dependence between the data and the Primary Current Density (PCD) inside the brain. The key point is that the Bayesian Theory not only provides for posterior estimates of the parameters of interest (the PCD) for a given model, but also gives the possibility of finding posterior expected utilities unconditional on the models assumed. In the present work, this is achieved by considering a third level of inference that has been systematically omitted by previous Bayesian formulations of the IP. This level is known as Bayesian model averaging (BMA). The new approach is illustrated in the case of considering different anatomical constraints for solving the IP of the EEG in the frequency domain. This methodology allows us to address two of the main problems that affect linear inverse solutions (LIS): (a) the existence of ghost sources and (b) the tendency to underestimate deep activity. Both simulated and real experimental data are used to demonstrate the capabilities of the BMA approach, and some of the results are compared with the solutions obtained using the popular low-resolution electromagnetic tomography (LORETA) and its anatomically constraint version (cLORETA).

Keywords: Artifacts ; *Bayes Theorem ; Brain/*physiology ; Brain Mapping ; Data Collection/statistics & numerical data ; Dominance, Cerebral/physiology ; Electroencephalography/*statistics & numerical data ; Evoked Potentials, Auditory/physiology ; Human ; Image Processing, Computer-Assisted/*statistics & numerical data ; Imaging, Three-Dimensional/*statistics & numerical data ; Linear Models ; Magnetic Resonance Imaging ; Magnetoencephalography/*statistics & numerical data ; Mathematical Computing ; Models, Neurological ; Nerve Net/physiology ; Occipital Lobe/physiology ; Reproducibility of Results ; *Signal Processing, Computer-Assisted ; Thalamus/physiology

The location of the international 10-20 system electrode positions and 14 fiducial landmarks are described in cartesian coordinates (+/- 1.4 mm average accuracy). Six replications were obtained on 3 separate days from 4 normal subjects, who were compared to each other with a best-fit sphere algorithm. Test-retest reliability depended on the electrode position: the parasagittal electrodes were associated with greater measurement errors (maximum 7 mm) than midline locations. Location variability due to head shape was greatest in the temporal region, averaging 5 mm from the mean. For each subject's electrode locations a best-fitting sphere was determined (79-87 mm radius, 6% average error). A surface-fitting algorithm was used to transfer the electrode locations and best-fitting sphere to MR images of the brain and scalp. The center of the best-fitting sphere coincided with the floor of the third ventricle 5 mm anterior to the posterior commissure. The melding of EEG electrode location information with brain anatomy provides an empirical basis for associating hypothetical equivalent dipole locations with their anatomical substrates.

Keywords: Adult ; Brain/*anatomy & histology/physiology ; Brain Mapping ; Electrodes ; Electroencephalography/*instrumentation ; Evoked Potentials, Visual/physiology ; Female ; Human ; Magnetic Resonance Imaging ; Male ; Photic Stimulation

In this study, the feasibility of dipole source localization (DSL) and coregistration with functional magnetic resonance imaging (fMRI) activation patterns on the basis of simultaneously acquired data is demonstrated. Brain activity was mapped during the performance of a somatosensory single reaction and a choice reaction task at high spatiotemporal resolution in six healthy subjects. The choice reaction task required a categorization of two different stimulus intensities, whereas for the single reaction task merely the perception of a tactile stimulus had to be confirmed by the subjects. An offline artifact correction algorithm was applied to 32-channel EEG data that were acquired between subsequent MRI scans. Using a multiple dipole approach, five distinct dipole sources were identified within areas of the somatosensory system. Coregistration of fMRI and DSL showed consistent spatial activation patterns with a mean distance of 9.2 +/- 6.8 mm between dipole sources and fMRI activation maxima. However, since the number of fMRI activation sites exceeded the number of cerebral dipole sources, it was not possible to assign a dipole source to each fMRI activation site. Dipole moment time courses were consistent with previously reported results of similar experiments. A comparison of brain activation patterns during the two tasks with both fMRI and DSL indicated an involvement of the contralateral secondary somatosensory cortex in somatosensory categorization.

Keywords: Adult ; Artifacts ; Attention/*physiology ; Brain Mapping/methods ; Choice Behavior/*physiology ; Dominance, Cerebral/physiology ; Electroencephalography/*methods ; Evoked Potentials, Somatosensory/physiology ; Female ; Human ; Image Processing, Computer-Assisted/*methods ; Imaging, Three-Dimensional/*methods ; Magnetic Resonance Imaging/*methods ; Male ; Median Nerve/physiology ; Motor Neurons/physiology ; Oxygen Consumption/physiology ; Parietal Lobe/*physiology ; Reaction Time/*physiology ; Sensory Thresholds ; Somatosensory Cortex/*physiology ; Support, Non-U.S. Gov't ; Touch/*physiology

The proportionality of blood oxygen level-dependent (BOLD) response during a cognitive task and that from a hypercapnic challenge was investigated in cortical structures involved in working memory (WM). Breath holding (BH) following inspiration was used to induce a BOLD response characteristic of regional vasomotor reactivity but devoid of metabolic changes. BOLD effects measured during BH were used to normalize individual subject activations during WM, which effectively reduced the confounding influence of individual- and region-specific differences in hemodynamic responsivity common to both tasks. In a study of seven subjects, the BH calibration reduced intersubject variability in WM effect amplitude by 24.8 resulted in a 23.7 voxel extent significant at P < 0.001, with further increases at more stringent thresholds. Because the BH task does not require CO(2) inhalation or other invasive manipulations and is broadly applicable across cortical regions, the proposed approach is simple to implement and may be beneficial for use not only in quantitative group fMRI analyses, but also for multicenter and longitudinal studies. Hum Brain Mapp, 2006. (c) 2006 Wiley-Liss, Inc.

Previous evidence from functional magnetic resonance imaging (fMRI) has shown that a painful galvanic stimulation mainly activates a posterior sub-region in the secondary somatosensory cortex (SII), whereas a non-painful sensory stimulation mainly activates an anterior sub-region of SII [Ferretti, A., Babiloni, C., Del Gratta, C., Caulo, M., Tartaro, A., Bonomo, L., Rossini, P.M., Romani, G.L., 2003. Functional topography of the secondary somatosensory cortex for non-painful and painful stimuli: an fMRI study. Neuroimage 20 (3), 1625-1638.]. The present study, combining fMRI with magnetoencephalographic (MEG) findings, assessed the working hypothesis that the activity of such a posterior SII sub-region is characterized by an amplitude and temporal evolution in line with the bilateral functional organization of nociceptive systems. Somatosensory evoked magnetic fields (SEFs) recordings after alvanic median nerve stimulation were obtained from the same sample of subjects previously examined with fMRI [Ferretti, A., Babiloni, C., Del Gratta, C., Caulo, M., Tartaro, A., Bonomo, L., Rossini, P.M., Romani, G.L., 2003. Functional topography of the secondary somatosensory cortex for non-painful and painful stimuli: an fMRI study. Neuroimage 20 (3), 1625-1638.]. Constraints for dipole source localizations obtained from MEG recordings were applied according to fMRI activations, namely, at the posterior and the anterior SII sub-regions. It was shown that, after painful stimulation, the two posterior SII sub-regions of the contralateral and ipsilateral hemispheres were characterized by dipole sources with similar amplitudes and latencies. In contrast, the activity of anterior SII sub-regions showed statistically significant differences in amplitude and latency during both non-painful and painful stimulation conditions. In the contralateral hemisphere, the source activity was greater in amplitude and shorter in latency with respect to the ipsilateral. Finally, painful stimuli evoked a response from the posterior sub-regions peaking significantly earlier than from the anterior sub-regions. These results suggested that both ipsi and contra posterior SII sub-regions process painful stimuli in parallel, while the anterior SII sub-regions might play an integrative role in the processing of somatosensory stimuli.

Keywords: Adult ; Electric Stimulation ; Evoked Potentials, Somatosensory/physiology ; Female ; Humans ; Laterality/physiology ; Magnetic Resonance Imaging ; Magnetoencephalography ; Male ; Models, Neurological ; Nociceptors/*physiology ; Oxygen/blood ; Pain Threshold/physiology ; Research Support, Non-U.S. Gov't ; Somatosensory Cortex/*physiology

Characteristics of the blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal poststimulus undershoot in the visual cortex were studied at varying levels of arterial blood oxygen saturation (Y(sat)). Undershoot with an amplitude of -0.6+/-0.2 after positive BOLD response (+1.7+/-0.5 control conditions. Cerebral blood volume (CBV), as determined with vascular-space-occupancy-dependent fMRI, increased by 26-43 peak, but the CBV proceeded at baseline level during the BOLD poststimulus undershoot. Mild hypoxic hypoxia (Y(sat) ranging from 0.82 to 0.89) had no effect on the amplitude or duration of poststimulus undershoot in activated BOLD pixels. Hypoxia did not influence CBV during the BOLD poststimulus undershoot. In contrast, the positive BOLD signal at the level of all activated pixels was smaller in hypoxia than in normoxia. The present results show that the BOLD poststimulus undershoot is not influenced by curtailed oxygen availability and that, during the undershoot, CBV is not different from resting state.

Knowledge of the electrical conductivity properties of excitable tissues is essential for relating the electromagnetic fields generated by the tissue to the underlying electrophysiological currents. Efforts to characterize these endogenous currents from measurements of the associated electromagnetic fields would significantly benefit from the ability to measure the electrical conductivity properties of the tissue noninvasively. Here, using an effective medium approach, we show how the electrical conductivity tensor of tissue can be quantitatively inferred from the water self-diffusion tensor as measured by diffusion tensor magnetic resonance imaging. The effective medium model indicates a strong linear relationship between the conductivity and diffusion tensor eigenvalues (respectively, final sigma and d) in agreement with theoretical bounds and experimental measurements presented here (final sigma/d approximately 0.844 +/- 0.0545 S small middle dots/mm(3), r(2) = 0.945). The extension to other biological transport phenomena is also discussed.

Keywords: Brain/*anatomy & histology/physiology ; *Brain Mapping/instrumentation/methods ; Diffusion ; Electroencephalography ; Human ; *Magnetic Resonance Imaging ; Magnetoencephalography ; Models, Neurological ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, Non-P.H.S. ; Support, U.S. Gov't, P.H.S.

The draining vein problem is recognized as one of the most severe constraints on the spatial resolution of BOLD contrast fMRI, used widely in imaging neuroscience. Changes in blood oxygenation arising from local brain activity-related changes in blood flow propagate downstream in veins and can give rise to spurious activation at sites remote from neuronal activity. The geometry of the venous vasculature is quite regular in structure and is well depicted in photomicrographs. Quantitative analysis of this geometry, together with hydrodynamic considerations, permit upper bounds dependent on the area of cortical neuronal activity to be derived for the spatial extent of draining vein contamination. It is estimated that an activated cortical area of 100 mm(2) will generate an oxygenation change in venous blood that extends without dilution along the vein no more than 4.2 mm beyond the edge of the activated area. At greater distances along the draining vein this oxygenation change will be diluted. The model leads to a quantitative prediction of the functional form of this dilution.

Keywords: Cerebral Cortex/*blood supply/*physiology ; Cerebral Veins/*physiology ; Humans ; *Models, Cardiovascular ; Oxygen/*blood ; Research Support, Non-U.S. Gov't

The locations of active brain areas can be estimated from the magnetic field produced by the neural current sources. In many cases, the actual current distribution can be modeled with a set of stationary current dipoles with time-varying amplitudes. This work studies global optimization methods that find the minimum of the least-squares error function of the current dipole estimation problem. Three different global optimization methods were investigated: clustering method, simulated annealing, and genetic algorithms. In simulation studies, the genetic algorithm was the most effective method. The methods were also applied to analysis of actual measurement data.

Keywords: Algorithms ; Comparative Study ; Evoked Potentials, Auditory ; Human ; Language Tests ; Least-Squares Analysis ; Linear Models ; *Magnetoencephalography ; *Models, Neurological ; Reference Values ; Reproducibility of Results ; *Signal Processing, Computer-Assisted ; Support, Non-U.S. Gov't ; Visual Cortex/*physiology

Combining event-related potentials (ERP) and functional magnetic resonance imaging (fMRI) may provide sufficient temporal and spatial resolution to clarify the functional connectivity of neural processes, provided both methods represent the same neural networks. The current study investigates the statistical correspondence of ERP tomography and fMRI within the common activity volume and time range in a complex visual language task. The results demonstrate that both methods represent similar neural networks within the bilateral occipital gyrus, lingual gyrus, precuneus and middle frontal gyrus, and the left inferior and superior parietal lobe, middle and superior temporal gyrus, cingulate gyrus, superior frontal gyrus and precentral gyrus. The mean correspondence of both methods over subjects was significant. On an individual basis, only half of the subjects showed significantly corresponding activity patterns, suggesting that a one-to-one correspondence between individual fMRI activation patterns and ERP source tomographies integrated over microstates cannot be assumed in all cases.

Keywords: Adult ; Brain/anatomy & histology/physiology ; *Brain Mapping ; Cognition ; *Electroencephalography ; Evoked Potentials/*physiology ; Female ; Human ; Image Processing, Computer-Assisted/methods ; *Language ; *Magnetic Resonance Imaging ; Male ; Nerve Net/anatomy & histology/physiology ; Photic Stimulation ; Reaction Time ; Reading ; Reference Values ; Support, Non-U.S. Gov't ; Word Association Tests

Truly simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) were registered in curarized rats injected with convulsive doses of pentylenetetrazol (PTZ, 65 mg/kg, sc). Rigorous control of physiological parameters like body temperature and ventilation with control of blood gasses helped to avoid potential interference between systemic parameters, and central PTZ-induced blood oxygenation level-dependent (BOLD) changes. Simultaneous EEG/fMRI recordings demonstrated progressive epileptiform EEG discharges with concomitant BOLD changes, the latter gradually affecting most of the fore- and midbrain. Approximately 15 min after PTZ injection, the first BOLD contrast changes mainly occurred in neocortex, and coincided with the first minor EEG alterations. Most regions that displayed BOLD changes were regions with reportedly high GABA(A) receptor densities. Full-blown epileptiform discharges occurred on the EEG tracing, approximately 30 min after PTZ injection, and coincided with bilateral positive and/or negative BOLD contrast changes in cortical and subcortical regions. Behavioral observations demonstrated the first of several generalized clonic or clonic-tonic seizure episodes to occur also around this time. Approximately 90 min after injection, the electrographic paroxysms gradually decreased in amplitude and duration, whereas the BOLD signal changes still extended with alternating positive and negative traces, and spread to subcortical regions like caudate-putamen and globus pallidus.

Keywords: Adult ; Brain Mapping ; Female ; Frontal Lobe/*physiology ; Human ; Image Processing, Computer-Assisted ; *Language ; Magnetic Resonance Imaging ; Male ; Motion Perception/*physiology ; Motor Cortex/physiology ; Parietal Lobe/anatomy & histology/physiology ; Support, Non-U.S. Gov't

Changes in the cerebral blood flow (CBF) baseline produce significant changes to the hemodynamic response. This work shows that increases in the baseline blood flow level produce blood oxygenation-level dependent (BOLD) and blood flow responses that are slower and lower in amplitude, while decreases in the baseline blood flow level produce faster and higher amplitude hemodynamic responses. This effect was characterized using a vascular model of the hemodynamic response that separated arterial blood flow response from the venous blood volume response and linked the input stimulus to the vascular response. The model predicted the baseline blood flow level effects to be dominated by changes in the arterial vasculature. Specifically, it predicted changes in the arterial blood flow time constant and venous blood volume time constant parameters of +294 for a 27 vascular model performance was compared to an empirical model of the hemodynamic response. The vascular and empirical hemodynamic models captured most of the baseline blood flow level effects observed and can be used to correct for these effects in fMRI data. While the empirical hemodynamic model is easy to implement, it did not incorporate any explicit physiological information.

While it is generally believed that interactions across long distances in the visual field occur only in the higher-order cortical areas, other results suggest that such interactions are processed very early. In the preceding paper, we identified the latencies within a subset of cortical areas in the human visual system. In the present study, we test in which areas and at which latencies the responses to two visual patterns start interacting. We used functional magnetic resonance imaging directly combined with visual-evoked potential source analysis. Interactions appeared first anterolaterally to the retinotopic areas, at 80 ms for two stimuli presented in the left lower visual quadrant and at 100 ms for symmetrical stimulation of both lower quadrants. In the lateral occipital-V5 region (LOV5), two patterns presented simultaneously in one quadrant elicited a response with shorter latency and infra-linear addition of the amplitudes compared with the patterns presented separately. For bilateral stimulation, the timing of the LOV5 response coincided with the response to contralateral stimulation alone. Other visual areas showed interactions appearing later than within LOV5: starting at 150 ms in V1, at 120 ms in V3-V3a for the left visual hemifield stimulation and at 160 ms for both visual hemifields stimulation. Our data show that distinct patterns in the visual field interact first in LOV5, suggesting that this region must be the first to pool spatial information across the whole visual field.

Keywords: Adult ; Brain Mapping ; Evoked Potentials, Visual/physiology ; Female ; Human ; Individuality ; Laterality/physiology ; Magnetic Resonance Imaging ; Male ; Middle Aged ; Models, Neurological ; Motion Perception/physiology ; Photic Stimulation ; Retina/physiology ; Support, Non-U.S. Gov't ; Visual Cortex/*physiology ; Visual Fields/*physiology ; Visual Perception/physiology

The authors describe and illustrate an integrated trio of software programs for carrying out surface-based analyses of cerebral cortex. The first component of this trio, SureFit (Surface Reconstruction by Filtering and Intensity Transformations), is used primarily for cortical segmentation, volume visualization, surface generation, and the mapping of functional neuroimaging data onto surfaces. The second component, Caret (Computerized Anatomical Reconstruction and Editing Tool Kit), provides a wide range of surface visualization and analysis options as well as capabilities for surface flattening, surface-based deformation, and other surface manipulations. The third component, SuMS (Surface Management System), is a database and associated user interface for surface-related data. It provides for efficient insertion, searching, and extraction of surface and volume data from the database.

Keywords: Anatomy, Artistic ; Anatomy, Cross-Sectional ; Brain/*anatomy & histology ; Cerebral Cortex/*anatomy & histology ; Databases, Factual ; Human ; *Image Processing, Computer-Assisted ; Magnetic Resonance Imaging ; Medical Illustration ; Neuroanatomy/methods ; *Software ; Support, Non-U.S. Gov't ; Support, U.S. Gov't, Non-P.H.S. ; Support, U.S. Gov't, P.H.S. ; Systems Integration

In this paper we report three neuroimaging studies of language that investigate potential sources of inconsistency in measured hemodynamic responses: (1) between sessions for fMRI, including differences in hormonal status, (2) between sessions for PET, and (3) between scanning modalities (PET and fMRI). Differences in evoked responses between sessions of the same modality were small. In particular we did not find any effect of hormone levels when testing during the first and third weeks of the menstrual cycle (although we cannot exclude the possibility that activation in the temporoparietal regions is sensitive to hormonal status). Comparing the two modalities showed that prefrontal regions were more activated in fMRI than in PET. This may relate to task switching between blocks in fMRI that is not induced by PET paradigms or increased error variance in these regions for PET. In contrast, temporal activations were found in PET more than in fMRI. We attribute the lack of temporal activations, in fMRI, to a combination of factors, including susceptibility artifacts, anticipatory activity during the control condition, discontinuous sampling of peristimulus time, and differences in the source, acquisition, and analysis of the measured signals. It is concluded that although there is sufficient reproducibility of results for these paradigms within each modality, the regionally specific differences in sensitivity found between modalities warrant further investigation. These regionally specific differences are important for a properly qualified interpretation of activation profiles in fMRI.

Keywords: Adult ; Brain/*anatomy & histology/physiology/*radionuclide imaging ; Brain Mapping ; Cerebrovascular Circulation ; Comparative Study ; Female ; Hemodynamic Processes/physiology ; Human ; *Magnetic Resonance Imaging ; Male ; Menstrual Cycle/physiology ; Prefrontal Cortex/anatomy & histology/physiology/radionuclide imaging ; Reading ; Sensitivity and Specificity ; Speech/physiology ; Support, Non-U.S. Gov't ; Temporal Lobe/anatomy & histology/physiology/radionuclide imaging ; *Tomography, Emission-Computed

The subject of this article is detection of brain magnetic fields, or magnetoencephalography (MEG). The brain fields are many orders of magnitude smaller than the environmental magnetic noise and their measurement represent a significant metrological challenge. The only detectors capable of resolving such small fields and at the same time handling the large dynamic range of the environmental noise are superconducting quantum interference devices (or SQUIDs). The SQUIDs are coupled to the brain magnetic fields using combinations of superconducting coils called flux transformers (primary sensors). The environmental noise is attenuated by a combination of shielding, primary sensor geometry, and synthetic methods. One of the most successful synthetic methods for noise elimination is synthetic higher-order gradiometers. How the gradiometers can be synthesized is shown and examples of their noise cancellation effectiveness are given. The MEG signals measured on the scalp surface must be interpreted and converted into information about the distribution of currents within the brain. This task is complicated by the fact that such inversion is nonunique. Additional mathematical simplifications, constraints, or assumptions must be employed to obtain useful source images. Methods for the interpretation of the MEG signals include the popular point current dipole, minimum norm methods, spatial filtering, beamformers, MUSIC, and Bayesian techniques. The use of synthetic aperture magnetometry (a class of beamformers) is illustrated in examples of interictal epileptic spiking and voluntary hand-motor activity.

Keywords: Brain/pathology ; Electromagnetic Fields ; Human ; Image Processing, Computer-Assisted ; Magnetoencephalography/instrumentation/*methods ; Models, Theoretical ; Software

OBJECTIVE: To study whether hemodynamic changes in human brain generate scalp-EEG responses. METHODS: Direct current EEG (DC-EEG) was recorded from 12 subjects during 5 non-invasive manipulations that affect intracranial hemodynamics by different mechanisms: bilateral jugular vein compression (JVC), head-up tilt (HUT), head-down tilt (HDT), Valsalva maneuver (VM), and Mueller maneuver (MM). DC shifts were compared to changes in cerebral blood volume (CBV) measured by near-infrared spectroscopy (NIRS). RESULTS: DC shifts were observed during all manipulations with highest amplitudes (up to 250 microV) at the midline electrodes, and the most pronounced changes (up to 15 microV/cm) in the DC voltage gradient around vertex. In spite of inter-individual variation in both amplitude and polarity, the DC shifts were consistent and reproducible for each subject and they showed a clear temporal correlation with changes in CBV. CONCLUSIONS: Our results indicate that hemodynamic changes in human brain are associated with marked DC shifts that cannot be accounted for by intracortical neuronal or glial currents. Instead, the data are consistent with a non-neuronal generator mechanism that is associated with the blood-brain barrier. SIGNIFICANCE: These findings have direct implications for mechanistic interpretation of slow EEG responses in various experimental paradigms.

Keywords: Adult ; Brain/*physiology ; Brain Mapping ; Cerebrovascular Circulation/*physiology ; Comparative Study ; Electrodes ; *Electroencephalography ; Female ; Head/physiology ; Hemodynamic Processes/*physiology ; Human ; Jugular Veins/physiology ; Laterality ; Male ; Posture/physiology ; Scalp ; Spectroscopy, Near-Infrared/instrumentation/methods ; Support, Non-U.S. Gov't

A spatial filtering method for localizing sources of brain electrical activity from surface recordings is described and analyzed. The spatial filters are implemented as a weighted sum of the data recorded at different sites. The weights are chosen to minimize the filter output power subject to a linear constraint. The linear constraint forces the filter to pass brain electrical activity from a specified location, while the power minimization attenuates activity originating at other locations. The estimated output power as a function of location is normalized by the estimated noise power as a function of location to obtain a neural activity index map. Locations of source activity correspond to maxima in the neural activity index map. The method does not require any prior assumptions about the number of active sources of their geometry because it exploits the spatial covariance of the source electrical activity. This paper presents a development and analysis of the method and explores its sensitivity to deviations between actual and assumed data models. The effect on the algorithm of covariance matrix estimation, correlation between sources, and choice of reference is discussed. Simulated and measured data is used to illustrate the efficacy of the approach.

Keywords: Algorithms ; Craniotomy ; Electrodes, Implanted ; *Electroencephalography ; Human ; Intraoperative Period ; Linear Models ; Models, Neurological ; Sensitivity and Specificity ; *Signal Processing, Computer-Assisted

We measured the timing of activity in distinct functional areas of the human visual cortex after onset of a visual pattern. This is not possible with visual evoked potentials (VEPs) or magnetic fields alone, and direct combination of functional magnetic resonance imaging (fMRI) with electromagnetic data has turned out to be difficult. We tested a relatively new approach, where both position and orientation of the active cortex was given to the VEP source model. Subjects saw the same visual patterns flashed ON and OFF, both when recording VEPs and fMRI responses. We identified the positions and orientations of the activated cortex in four retinotopic areas in each individual, and the corresponding dipoles were seeded to model the individual evoked potential data. Unexplained variance, comprising signals from other areas, was inversely modeled. Despite the partially a priori fixed model and optimized signal-to-noise ratio of VEP data, full separation of retinotopic areas was only seldom possible due to crosstalk between the adjacent sources, but separation was usually possible between areas V1 and V3/V3a. Whereas the latencies generally followed the hierarchical organization of cortical areas (V1-V2-V3), with around 25 ms between the strongest responses, an early activation emerged 10-20 ms after V1, close to the temporo-occipital junction (LO/V5) and with an additional 20-ms latency in the corresponding region of the opposite hemisphere. Our approach shows that it is feasible to directly seed information from fMRI to electromagnetic source models and to identify the components and dynamics of VEPs in different retinotopic areas of a human individual.

Keywords: Adult ; Brain Mapping ; Electroencephalography ; Evoked Potentials, Visual/*physiology ; Female ; Human ; Individuality ; Magnetic Resonance Imaging ; Male ; Middle Aged ; Models, Neurological ; Occipital Lobe/physiology ; Photic Stimulation ; Retina/physiology ; Support, Non-U.S. Gov't ; Visual Cortex/*physiology ; Visual Fields/physiology ; Visual Pathways/physiology

To achieve a deeper understanding of the brain, scientists, and clinicians use electroencephalography (EEG) and magnetoencephalography (MEG) inverse methods to reconstruct sources in the cortical sheet of the human brain. The influence of structural and electrical anisotropy in both the skull and the white matter on the EEG and MEG source reconstruction is not well understood. In this paper, we report on a study of the sensitivity to tissue anisotropy of the EEG/MEG forward problem for deep and superficial neocortical sources with differing orientation components in an anatomically accurate model of the human head. The goal of the study was to gain insight into the effect of anisotropy of skull and white matter conductivity through the visualization of field distributions, isopotential surfaces, and return current flow and through statistical error measures. One implicit premise of the study is that factors that affect the accuracy of the forward solution will have at least as strong an influence over solutions to the associated inverse problem. Major findings of the study include (1) anisotropic white matter conductivity causes return currents to flow in directions parallel to the white matter fiber tracts; (2) skull anisotropy has a smearing effect on the forward potential computation; and (3) the deeper a source lies and the more it is surrounded by anisotropic tissue, the larger the influence of this anisotropy on the resulting electric and magnetic fields. Therefore, for the EEG, the presence of tissue anisotropy both for the skull and white matter compartment substantially compromises the forward potential computation and as a consequence, the inverse source reconstruction. In contrast, for the MEG, only the anisotropy of the white matter compartment has a significant effect. Finally, return currents with high amplitudes were found in the highly conducting cerebrospinal fluid compartment, underscoring the need for accurate modeling of this space.

Keywords: Animals ; Comparative Study ; Electroencephalography/*trends ; Forecasting ; Human ; Magnetic Resonance Imaging ; Magnetoencephalography/*trends ; Sensitivity and Specificity ; Support, U.S. Gov't, Non-P.H.S. ; Tomography, Emission-Computed ; Tomography, Emission-Computed, Single-Photon

We investigated whether: (1) EEG recordings could be successfully performed in an MRI imager, (2) subclinical epileptic discharges could be used to trigger ultrafast functional MRI images, (3) artifact-free functional MRI images could be obtained while the patient was having the EEG monitored, and (4) the functional MRI images so obtained would show focal signal increases in relation to epileptic discharges. We report our results in two patients who showed focally higher signal intensity, reflective of increased local blood flow, in ultrafast functional MRI timed to epileptic discharges recorded while the patients were in the imager and compared with images not associated with discharges. One patient showed a focal increase despite a clinical and EEG history of generalized discharges. This approach may have the potential to identify brain regions activated during brief focal epileptic discharges.

Keywords: Adult ; *Echo-Planar Imaging ; Electroencephalography/*methods ; Epilepsy/*physiopathology ; Female ; Human ; Magnetic Resonance Imaging

Keywords: Brain/*pathology/*physiology ; Electroencephalography ; Human ; Magnetic Resonance Imaging ; Magnetoencephalography

It has been well recognized that the nonlinear hemodynamic responses of the blood oxygenation level-dependent (BOLD) functional MRI (fMRI) are important and ubiquitous in a series of experimental paradigms, especially for the event-related fMRI. Although this phenomenon has been intensively studied and it has been found that the post-capillary venous expansion is an intrinsically nonlinear mechanical process, the existence of an additional neural basis for the nonlinearity has not been clearly shown. In this paper, we assessed the correlation between the electric and vascular indices by performing simultaneous electroencephalography (EEG) and fMRI recordings in humans during a series of visual stimulation (i.e., radial checkerboard). With changes of the visual stimulation frequencies (from 0.5 to 16 Hz) and contrasts (from 1 related potentials (ERPs) and hemodynamic responses show nonlinear behaviors. In particular, the mean power of the brain electric sources and the neuronal efficacies (as originally defined in the hemodynamics model [Friston et al. Neuroimage, 12, 466-477, 2000], here represent the vascular inputs) in primary visual cortex consistently show a linear correlation for all subjects. This indicates that the hemodynamic response nonlinearity found in this paper primarily reflects the nonlinearity of underlying neural activity. Most importantly, this finding underpins a nonlinear neurovascular coupling. Specifically, it is shown that the transferring function of the neurovascular coupling is likely a power transducer, which integrates the fast dynamics of neural activity into the vascular input of slow hemodynamics.

Simultaneously acquired functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) data hold great promise for localizing the spatial source of epileptiform events detected in the EEG trace. Despite a number of studies applying this method, there has been no independent and systematic validation of the approach. The present study uses a nonparametric method to show that interictal discharges lead to a blood oxygen level dependent (BOLD) response that is significantly different to that obtained by examining random 'events'. We also use this approach to examine the optimization of analysis strategy for detecting these BOLD responses. Two patients with frequent epileptiform events and a healthy control were studied. The fMRI data for each patient were analyzed using a model derived from the timings of the epileptiform events detected on EEG during fMRI scanning. Twenty sets of random pseudoevents were used to generate a null distribution representing the level of chance correlation between the EEG events and fMRI data. The same pseudoevents were applied to control data. We demonstrate that it is possible to detect blood oxygen level-dependent (BOLD) changes related to interictal discharges with specific and independent knowledge about the reliability of this activation. Biologically generated events complicate the fMRI-EEG experiment. Our proposed validation examines whether identified events have an associated BOLD response beyond chance and allows optimization of analysis strategies. This is an important step beyond standard analysis. It informs clinical interpretation because it permits assessment of the reliability of the connection between interictal EEG events and the BOLD response to those events.

The integration of electroencephalogram (EEG) recordings and functional magnetic resonance imaging (fMRI) can provide considerable insight into brain functionality. However, the direct relationship between neural and hemodynamic activity is still poorly understood. Of particular interest is the spatial correspondence between event-related potential (ERP) and fMRI sources. In the current study we localized sources generated by a checkerboard stimulus presented to eight subjects using both EEG and fMRI. The location of the sources of the visual evoked potential (VEP) were estimated at each timepoint and compared to the location of peak fMRI activity. In the majority of participants we found that the N75 dipole location coincides with a region of positive blood oxygenation level-dependent (BOLD) activation and the P100 dipole location coincides with a region of negative BOLD activation. These findings demonstrate the importance of including the negative BOLD response in combined EEG/fMRI studies. Hum Brain Mapp, 2006. (c) 2006 Wiley-Liss, Inc.

Magnetic resonance imaging (MRI) of brain functional activity relies principally on changes in cerebral hemodynamics, which are more spatially and temporally distributed than the underlying neuronal activity changes. We present a novel MRI technique for mapping brain functional activity by directly detecting magnetic fields induced by neuronal firing. Using a well-established visuomotor paradigm, the locations and latencies of activations in visual, motor, and premotor cortices were imaged at a temporal resolution of 100 msec and a spatial resolution of 3 mm, and were found to be in consistent with the electrophysiological and functional MRI (fMRI) literature. Signal strength was comparable to traditional event-related fMRI methods: about 1% of the baseline signal. The magnetic-source MRI technique greatly increases the temporal accuracy in detecting neuronal activity, providing a powerful new tool for mapping brain functional organization in human and animals.

Keywords: *Action Potentials ; Brain/*physiology ; Brain Mapping/*methods ; Female ; Human ; *Magnetic Resonance Imaging ; Male ; Neurons/*physiology ; Support, U.S. Gov't, Non-P.H.S. ; Support, U.S. Gov't, P.H.S.

We describe a mathematical model linking changes in cerebral blood flow, blood volume and the blood oxygenation state in response to stimulation. The model has three compartments to take into account the fact that the cerebral blood flow and volume as measured concurrently using laser Doppler flowmetry and optical imaging spectroscopy have contributions from the arterial, capillary as well as the venous compartments of the vasculature. It is an extension to previous one-compartment hemodynamic models which assume that the measured blood volume changes are from the venous compartment only. An important assumption of the model is that the tissue oxygen concentration is a time varying state variable of the system and is driven by the changes in metabolic demand resulting from changes in neural activity. The model takes into account the pre-capillary oxygen diffusion by flexibly allowing the saturation of the arterial compartment to be less than unity. Simulations are used to explore the sensitivity of the model and to optimise the parameters for experimental data. We conclude that the three-compartment model was better than the one-compartment model at capturing the hemodynamics of the response to changes in neural activation following stimulation.

Keywords: Inverse

In this paper we presented two methods for the modeling of human cortical activity by using combined high-resolution electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data. These methods were based on linear inverse estimation and used subjects multi-compartment head model (scalp, skull, dura mater, cortex) constructed from magnetic resonance images and a multi-dipole source model. Hemodynamic responses of the investigated cortical areas as derived from block-design and event-related functional Magnetic Resonance Imaging (fMRI) were used as priors in the resolution of the linear inverse problem. High resolution EEG (128 electrodes) and fMRI data were recorded in separate sessions, while normal subjects executed voluntary right one-digit movements. Results showed that linear inverse solutions obtained with fMRI priors present more localized spots of activation with respect to those obtained without fMRI priors. Remarkably, the spots of activation were localized in the hand regions of the primary somatosensory (post-central) and motor (pre-central) areas contralateral to the movement. This may suggest that both methods increased the spatial resolution of linear inverse solutions computed from EEG data.

Keywords: Fusion

In this paper, we present a new approach to the recovering of dipole magnitudes in a distributed source model for magnetoencephalographic (MEG) and electroencephalographic (EEG) imaging. This method consists in introducing spatial and temporal a priori information as a cure to this ill-posed inverse problem. A nonlinear spatial regularization scheme allows the preservation of dipole moment discontinuities between some a priori noncorrelated sources, for instance, when considering dipoles located on both sides of a sulcus. Moreover, we introduce temporal smoothness constraints on dipole magnitude evolution at time scales smaller than those of cognitive processes. These priors are easily integrated into a Bayesian formalism, yielding a maximum a posteriori (MAP) estimator of brain electrical activity. Results from EEG simulations of our method are presented and compared with those of classical quadratic regularization and a now popular generalized minimum-norm technique called low-resolution electromagnetic tomography (LORETA).

We describe a new magnetic resonance (MR) image analysis tool that produces cortical surface representations with spherical topology from MR images of the human brain. The tool provides a sequence of low-level operations in a single package that can produce accurate brain segmentations in clinical time. The tools include skull and scalp removal, image nonuniformity compensation, voxel-based tissue classification, topological correction, rendering, and editing functions. The collection of tools is designed to require minimal user interaction to produce cortical representations. In this paper we describe the theory of each stage of the cortical surface identification process. We then present classification validation results using real and phantom data. We also present a study of interoperator variability.

Keywords: Algorithms ; Automation ; Brain/anatomy & histology ; Cerebral Cortex/*anatomy & histology ; Computer Simulation ; Humans ; *Image Processing, Computer-Assisted ; Magnetic Resonance Imaging/*methods ; Models, Anatomic ; *Models, Neurological ; Research Support, U.S. Gov't, P.H.S. ; Sensitivity and Specificity ; *Software ; Surface Properties

This paper is devoted to blind deconvolution and blind separation problems. Blind deconvolution is the identification of a point spread function and an input signal from an observation of their convolution. Blind source separation is the recovery of a vector of input signals from a vector of observed signals, which are mixed by a linear (unknown) operator. We show that both problems are paradigms of nonlinear ill-posed problems. Consequently, regularization techniques have to be used for stable numerical reconstructions. In this paper we develop a rigorous convergence analysis for regularization techniques for the solution of blind deconvolution and blind separation problems. We prove convergence of the alternating minimization algorithm for the numerical solution of regularized blind deconvolution problems and present some numerical examples. Moreover, we show that many neural network approaches for blind inversion can be considered in the framework of regularization theory.

Keywords: fMRI, ICA, review

This thesis explores the relationship between the shape of the surface of the human brain and the function of the underlying tissue. In this work, structural information is provided by magnetic resonance imaging. Functional information is gathered using functional magnetic resonance imaging and by electrophysiological monitoring with sub-durally implanted metal electrodes lying directly on the brain surface, which are localised using X-ray computed tomography images. The thesis examines techniques for comparing the information provided by the functional modalities with the shape of the underlying brain surface structures. The feasibility of comparing localisation of functional regions provided by functional magnetic resonance imaging with that provided by direct electrophysiological mapping is explored. The possibility of relating the shape of the cortical surface to the function of the brain is examined. Suitable geometrical measures for quantifying the shape of the brain surface are proposed. The measures discussed include measures of convexity in both two and three dimensions, measures based on surface area and volume measurements, and a set of measures based on integrals of intrinsic and extrinsic curvatures. Published work comparing surface shape and function is reviewed. Practical methods for applying the set of measures considered to discrete surfaces extracted from MR volumes are proposed. A discrete triangulated surface model has been devised to allow the calculation of these shape measures, and is described in detail. The smoothing of this surface model, and of measures extracted from it, is discussed in relation to noise in the surface fitted to the discrete dataset obtained from the anatomical images. The techniques are then applied to three-dimensional magnetic resonance images of a number of human brains. Initially the set of measures is applied to a series of normal ex-vivo foetal brains with gestational ages ranging from 19 weeks to 40 weeks. The shape measures are shown to reliably characterise the development of folding during normal development, with differences between gestational ages being significantly greater than the variability in the measures when applied to several brains of the same gestational age. The measures are then applied to a series of abnormally developed foetal brains, to a set of normal adult brains, and to a set of schizophrenic adult brains, in order to characterise the ability of the measures to distinguish between normal and abnormal brain surface shapes.

Short introductory to MEG. Covers difference between EEG and MEG. Has a photo of 1st SQUID MEG at MIT

Keywords: MEG, overview

EEG was recorded during fMRI scanning of 16 normal controls in resting condition with eyes closed. Time variations of the occipital alpha band amplitudes were correlated to the fMRI signal variations to obtain insight into the hemodynamic correlates of the EEG alpha activity. Contrary to earlier studies, no a priori assumptions were made on the expected shape of the alpha band response function (ARF). The ARF of different brain regions and subjects were explored and compared. It was found that: (1) the ARF of the thalamus is mainly positive. (2) The ARFs at the occipital and left and right parietal points are similar in amplitude and timing. (3) The peak time of the thalamus is a few seconds earlier than that of occipital and parietal cortex. (4) No systematic BOLD activity was found preceding the alpha band activity, although in the two subjects with the strongest alpha band power such correlation was present. (5) There is a strong and immediate positive correlation at the eyeball, and a strong negative correlation at the back of the eye. Furthermore, it was found that in one subject the cortical ARF was positive, contrary to the other subjects. Finally, a cluster analysis of the observed ARF, in combination with a Modulated Sine Model (MSM) fit to the estimated ARF, revealed that within the cortex the ARF peak time shows a spatial pattern that may be interpreted as a traveling wave. The spatial pattern of alpha band response function represents the combined effect of local differences in electrical alpha band activity and local differences in the hemodynamic response function (HRF) onto these electrical activities. To disentangle the contributions of both factors, more advanced integration of EEG inverse modeling and hemodynamic response modeling is required in future studies.

Keywords: Adult ; Alpha Rhythm/*methods ; Blood Flow Velocity/physiology ; Brain/*blood supply/*physiology ; Brain Mapping/*methods ; Cerebrovascular Circulation/*physiology ; Female ; Humans ; Magnetic Resonance Imaging/*methods ; Male ; Reproducibility of Results ; Sensitivity and Specificity

Functional magnetic resonance imaging (fMRI) can provide maps of brain activation with millimeter spatial resolution but is limited in its temporal resolution to the order of seconds. Here, we describe a technique that combines structural and functional MRI with magnetoencephalography (MEG) to obtain spatiotemporal maps of human brain activity with millisecond temporal resolution. This new technique was used to obtain dynamic statistical parametric maps of cortical activity during semantic processing of visually presented words. An initial wave of activity was found to spread rapidly from occipital visual cortex to temporal, parietal, and frontal areas within 185 ms, with a high degree of temporal overlap between different areas. Repetition effects were observed in many of the same areas following this initial wave of activation, providing evidence for the involvement of feedback mechanisms in repetition priming.

We describe a comprehensive linear approach to the problem of imaging brain activity with high temporal as well as spatial resolution based on combining EEG and MEG data with anatomical constraints derived from MRI images. The inverse problem of estimating the distribution of dipole strengths over the cortical surface is highly underdetermined, even given closely spaced EEG and MEG recordings. We have obtained much better solutions to this problem by explicitly incorporating both local cortical orientation as well as spatial covariance of sources and sensors into our formulation. An explicit polygonal model of the cortical manifold is first constructed as follows: (1) slice data in three orthogonal planes of section (needle-shaped voxels) are combined with a linear deblurring technique to make a single high-resolution 3-D image (cubic voxels), (2) the image is recursively flood-filled to determine the topology of the gray-white matter border, and (3) the resulting continuous surface is refined by relaxing it against the original 3-D gray-scale image using a deformable template method, which is also used to computationally flatten the cortex for easier viewing. The explicit solution to an error minimization formulation of an optimal inverse linear operator (for a particular cortical manifold, sensor placement, noise and prior source covariance) gives rise to a compact expression that is practically computable for hundreds of sensors and thousands of sources. The inverse solution can then be weighted for a particular (averaged) event using the sensor covariance for that event. Model studies suggest that we may be able to localize multiple cortical sources with spatial resolution as good as PET with this technique, while retaining a much more fine grained picture of activity over time.

Sustained negative BOLD responses, in the human visual system, have not been reported at the usual field strengths. Such negative responses are likely due to a decrease of cerebral perfusion in non-stimulated areas adjacent to the activated ones, as a result of reallocation of the cortical blood resources. This reallocation may even affect activated areas, thus inducing signal extinction or negative BOLD signal in areas where positive BOLD responses would be anticipated. In combining partial visual field stimulation experiments and retinotopic mapping experiments at 1.5 T, we show that such negative responses may be detected, following reduced visual field stimulation.

Keywords: HRF

Using precomputed BEM form fit the best approximating sphere for each sensor and then use 3d interpolation to approximate forward field

Based on an improved understanding of the underlying physiologic mechanisms and a growing number of applications to selected brain systems, the main purpose of this contribution is to present a discussion of the general potential and the specific challenges of this continuously expanding field. Rather than providing a comprehensive survey, emphasis will be placed on both characteristic advantages that render MRI particularly attractive for functional neuroimaging and potential problems that may hamper the interpretation of the experimental results. Apart from discussing crucial aspects ranging from cerebral hemodynamics to data acquisition and parametric mapping, specific points addressed are the neural basis of the functional MRI signal as well as the achievable spatial and temporal resolution. Technical complications will be discussed as well as limitations resulting from pharmacological and pathological modulations of the neurovascular coupling. A final section covers the increasingly difficult translation of a neuroscientific question into a proper MRI-compatible paradigm.

We present a method for detecting significant and regionally specific correlatio ns between sensory input and the braiifs physiological response, as measured with functional MRI. The method involves testing for correlations, between sensory input and the hemodynamic response, after convolving the sensory input with an estimate of the hemodynamic response function. This estimate is obtained without reference to any assumed input. To lend the approach statistical validity, it is brought into the framework of s tatistical parametric mapping by using a measure of cross-correlations, between sensory input and hemo dynamic response, that is valid in the presence of intrinsic autocorrelations. These autocorrelations are necessarily present, due to the hemodynamic response function or temporal point spread function.

In the present work, a modification of the EEG/MEG inverse solution method presented by Trujillo et. al. 2004 (known as Bayesian Model Averaging (BMA)), is introduced in order to include prior information provided by fMRI. This BMA approach basically finds a model-free Primary Current Density (PCD) inside the brain by dealing with the uncertainty of selecting a specific model to carry out inference upon it. The models differ in the anatomical constraint used to find the solution, which are defined by different combinations of brain areas taken from a segmentation of the brain into 69 compartments

Poster #WE 245

Integrated analyses of human anatomical and functional measurements offer a powerful paradigm for human brain mapping, Magnetoencephalography (MEG) and EEG provide excellent temporal resolution of neural population dynamics as well as capabilities for source localization. Anatomical magnetic resonance imaging (MRI) provides excellent spatial resolution of head and brain anatomy, whereas functional MRI (fMRI) techniques provide an alternative measure of neural activation based on associated hemodynamic changes. These methodologies constrain and complement each other and can thereby improve our interpretation of functional neural organization. We have developed a number of computational tools and techniques for the visualization, comparison, and integrated analysis of multiple neuroimaging techniques. Construction of geometric anatomical models from volumetric MRI data allows improved models of the head volume conductor and can provide powerful constraints for neural electromagnetic source modeling. These approaches, coupled to enhanced algorithmic strategies for the inverse problem, can significantly enhance the accuracy of source-localization procedures. We have begun to apply these techniques for studies of the functional organization of the human visual system. Such studies have demonstrated multiple, functionally distinct visual areas that can be resolved on the basis of their locations, temporal dynamics, and differential sensitivity to stimulus parameters. Our studies have also produced evidence of internal retinotopic organization in both striate and extrastriate visual areas but have disclosed organizational departures from classical models. Comparative studies of MEG and fMRI suggest a reasonable but imperfect correlation between electrophysiological and hemodynamic responses. We have demonstrated a method for the integrated analysis of fMRI and MEG, and we outline strategies for improvement of these methods. By combining multiple measurement techniques, we can exploit the complementary strengths and transcend the limitations of the individual neuroimaging methods. 'on file. good vision review. and technical review.'

Keywords: Fusion, Fusion Review

This paper starts discussing some alternatives to integrate functional information as constraints for the inverse solution. Concrete examples of situations where functional images substantially diverge from electrophysiological methods are presented to promote the discussion about the most reasonable alternatives to combine these image modalities. The results of an anatomically constrained inverse solution that employs a sound physical model are compared with the EEG triggered fMRI in an epileptic patient. This example serves to show that the spatial resolution attainable with inverse solutions is comparable in some situations with that of functional images. Finally, some concrete strategies to ameliorate the quality and reliability of linear inverse solutions maps in more general situations are briefly described. The main conclusion of this paper is that integration of functional modalities into the solution of the NIP should be cautiously considered until a more tight coupling between BOLD effects and electrophysiological measurements could be established

Keywords: Fusion

In recent years, cognitive neuroscientists have taken great advantage of functional magnetic resonance imaging (fMRI) as a non-invasive method of measuring neuronal activity in the human brain. But what exactly does fMRI tell us? We know that its signals arise from changes in local haemodynamics that, in turn, result from alterations in neuronal activity, but exactly how neuronal activity, haemodynamics and fMRI signals are related is unclear. It has been assumed that the fMRI signal is proportional to the local average neuronal activity, but many factors can influence the relationship between the two. A clearer understanding of how neuronal activity influences the fMRI signal is needed if we are correctly to interpret functional imaging data.

Poster #WE 217

Original Gamma HRF model paper

Keywords: electronic data processing, least squares

In this study, we propose a new multimodal approach for solving the EEG/MEG inverse problem. This method involves a distributed source model and accounts for anatomo-functional constraints derived from functional magnetic resonance imaging (fMRI) data. In the following, we briefly describe the source model, the regularization procedure and the way functional priors are introduced. In order to assess the value of the proposed approach, we then present results obtained using simulated data.

The linearity of the cerebral perfusion response relative to stimulus duration is an important consideration in the characterization of the relationship between regional cerebral blood flow (CBF), cerebral metabolism, and the blood oxygenation level dependent (BOLD) signal. It is also a critical component in the design and analysis of functional neuroimaging studies. To study the linearity of the CBF response to different duration stimuli, the perfusion response in primary motor and visual cortices was measured during stimulation using an arterial spin labeling technique with magnetic resonance imaging (MRI) that allows simultaneous measurement of CBF and BOLD changes. In each study, the perfusion response was measured for stimuli lasting 2, 6, and 18 sec. The CBF response was found in general to be nonlinearly related to stimulus duration, although the strength of nonlinearity varied between the motor and visual cortices. In contrast, the BOLD response was found to be strongly nonlinear in both regions studied, in agreement with previous findings. The observed nonlinearities are consistent with a model with a nonlinear step from stimulus to neural activity, a linear step from neural activity to CBF change, and a nonlinear step from CBF change to BOLD signal change. Hum. Brain Mapping 13:1-12, 2001. ? 2001 Wiley-Liss, Inc.

The authors present general descriptive models for spatiotemporal MEG (magnetoencephalogram) data and show the separability of the linear moment parameters and nonlinear location parameters in the MEG problem. A forward model with current dipoles in a spherically symmetric conductor is used as an example: however, other more advanced MEG models, as well as many EEG (electroencephalogram) models, can also be formulated in a similar linear algebra framework. A subspace methodology and computational approach to solving the conventional least-squares problem is presented. A new scanning approach, equivalent to the statistical MUSIC method, is also developed. This subspace method scans three-dimensional space with a one-dipole model, making it computationally feasible to scan the complete head volume

The explicit form of the lead field is dependent on the head modeling assumptions and sensor configuration. The lead field can be partitioned into the product of a vector dependent on sensor characteristics and a matrix kernel dependent only on head modeling assumptions. Here we review analytic solutions for the spherical head model and boundary element methods (BEMs) for arbitrary head geometries. These results are presented in a unified form in terms of their matrix kernels. Using this formulation and a recently developed approximation formula for EEG, based on the Berg parameters, we present novel reformulations of the basic EEG and MEG kernels that dispel the myth that EEG is inherently more complicated to calculate than MEG. We also present novel investigations of different BEM methods and present evidence that improvements over currently published E/MEG BEM methods can be realized using alternative error weighting methods.

We present a unified treatment of analytical and numerical solutions of the forward problem in a form suitable for use in inverse methods. This formulation is achieved through factorization of the lead field into the product of the moment of the elemental current dipole source with a kernel matrix that depends on the head geometry and source and sensor locations, and a sensor matrix that models sensor orientation and gradiometer effects in MEG and differential measurements in EEG.

The infinite series analytic solution to the multilayer isotropic model is presented in Cartesian coordinates and the dipole moment clearly separated.

An L1 norm minimization scheme is applied to the determination of the impulse response vector h of flaws detected in practical examples of ultrasonic nondestructive evaluation in CANDU nuclear reactors. For each problem, parametric programming is applied to find the optimum value of the damping parameter that will yield the best estimate of h according to a quantified performance factor. This performance factor is based on a quantified analysis of the transitions in estimates of h as the damping parameter is varied over a wide range of possible values. It is shown that for the examined cases in which the true impulse response is a sparsely filled spike strain, the L1 norm provides significantly better results than the more commonly used L2 norm minimization schemes. These results are shown to be consistent with theoretical predictions

'sensory motor paradox'

In the context of realizing the functional requirements of a task, brain dynamics organize brain activities that cause biophysical and physiological signals, which the instruments of various neuroimaging modalities can measure. An ultimate goal is to make joint inferences about the underlying activity, dynamics, and functions by exploiting complementary information from multimodal datasets, acquired from the same subject who performed the same task. An intermediate problem is to design cross-modal analyses that improve the spatial and temporal resolution of one modality by incorporating complementary information from another modality. Given that M/EEG and fMRI BOLD signals are complementary in time and space with respect to a common subspace of brain activity, is there an fMRI-related M/EEG analysis that spatially and temporally enhances the M/EEG signal? Likewise, is there an M/EEG-related fMRI analysis that temporally and spatially enhances the BOLD signal? A theoretical principle is to design cross-modal analyses that maximize the dynamic coupling between jointly observed signals within the framework of nonlinear system identification. In particular, we define a linear spatial estimator that maximizes the empirical coupling of the estimated M/EEG source activity as driven by local BOLD signal, and a nonlinear dynamic transform that maximizes the coupling of BOLD signal as driven by the estimated M/EEG signal. The latter transformation can be the basis for fMRI statistical parametric maps that couple more tightly with neuronal activity compared with task-derived maps. For M/EEG and fMRI datasets obtained from different sessions, we describe a method of temporal alignment that uses separately identified nonlinear system models to simulate virtual simultaneous datasets. The critical criterion for empirical evaluation of these methods is between-session reliability.

Keywords: Fusion

We present a new approach to the electromagnetic inverse problem that explicitly addresses the ambiguity associated with its ill-posed character. Rather than calculating a single “best” solution according to some criterion, our approach produces a large number of likely solutions that both fit the data and any prior information that is used. Whereas the range of the different likely results is representative of the ambiguity in the inverse problem even with prior information present, features that are common across a large number of the different solutions can be identified and are associated with a high degree of probability. This approach is implemented and quantified within the formalism of Bayesian inference, which combines prior information with that of measurement in a common framework using a single measure. To demonstrate this approach, a general neural activation model is constructed that includes a variable number of extended regions of activation and can incorporate a great deal of prior information on neural current such as information on location, orientation, strength, and spatial smoothness. Taken together, this activation model and the Bayesian inferential approach yield estimates of the probability distributions for the number, location, and extent of active regions. Both simulated MEG data and data from a visual evoked response experiment are used to demonstrate the capabilities of this approach.

Mapping neuro-physiological functions to high resolution MRI is an effective means to evaluate localization reconstructions and to exhibit the spatio-temporal aspects of dynamic functional processes. The registration step needed between MEG/EEG and MRI is a source of error which, for the worse cases may be greater than errors related to the localization algorithms. Several registration methods can be used: those based on fiducial markers and those based on surface matching. The aim of this paper is to propose a fully automatic surface matching method and to discuss its extended theoretical and experimental evaluation. The registration procedure matches the skin surface, segmented from MRI, and a digitized description of the head performed with a 3D tracker during the MEG/EEG examination. The registration uncertainties at the edges of the MRI volume were estimated to be between 2 and 3 mm. In comparison with commonly used manual methods the improvement in accuracy is significant. Registration uncertainties are smaller than the localization uncertainties usually observed. By minimizing manual intervention, the reliability of the registration process is increased and the accuracy is stabilized. With this automatic registration method the fusion of MEG/EEG localizations with MRI anatomical data gives highly significant information. Finally the accuracy obtained allows the use of complex anatomical constraints in the localization process without introducing large modelling errors.

Numerical simulation studies were performed using a multiple dipole source model and a spherical approximation of the head to examine how the resolution of simultaneously active neuromagnetic sources depends upon: 1) source modeling assumptions (i.e., number of assumed dipoles); 2) actual source parameters (e.g., location, orientation, and moment); and 3) measurement errors. Forward calculations were conducted for a series of source configurations in which the number of dipoles, specific dipole parameters, and noise levels were systematically varied. Simulated noisy field distributions were fit by multiple dipole models of increasing model order (1, 2,..., 6 and alternative statistical approaches (i.e., percent of variance, reduced chi-square, and F-ratio) were compared for their effectiveness in determining adequate model order. Limits of spatial resolution were established for a variety of multi-source configurations and noise conditions. Implications for the analysis of empirical data are discussed.

A new method for EEG/MEG and fMRI data fusion (EEG/MEG fMRI) is presented. A linear model for both kinds of measurements is used, and the main assumption is that the variability of the estimated activation in both cases (variance and covariance matrix) is essentially the same, except for a scaling factor. Bayesian Theory is used as a natural framework for including the prior information associated with both kinds of imaging techniques. Additionally it allows the automatic estimation of all the tuning parameters in the model. The Point Spread Function (PSF) for the new model is computed, and the results are compared with methods that use only electric measurements. This work shows that the new methodology has a superior performance according to many of the quality measures used to characterize electrophysiological tomographic techniques. It is also demonstrated that previous procedures, based on thresh holding the fMRI by means of Statistical Parametric Mapping (SPM), and using the resultant active regions as constraints for solving the EEG/MEG inverse problem (fMRI->EEG/MEG), is biased by the fMRI estimation. The use of the new method is illustrated in the analysis of a Somatosensory MEG-fMRI experiment.

Depending on the available information, different co-registration methods for merging structural Magnetic Resonance Imaging (sMRI) and fMRI coordinate systems may be useful. The usage of scanner coordinates as well as landmark-, surface-, and volume-based registration is discussed. Dipole fits can benefit from fMRI constraints: Meaningful seed points for source locations are obtained. A reconstructed dipole in the vicinity of each fMRI hotspot yields the corresponding source time course. Spatially unconstrained dipoles are then necessary to account for remaining activity. Current density reconstructions react upon fMRI constraints in two ways: Activity in the vicinity of fMRI hotspots is bundled. Remaining activity can be localized correctly, if its field distribution cannot be generated from sources within the hotspots, and if the fMRI constraint is imposed softly.

Keywords: Fusion

The minimum norm least-squares approach based on lead field theory provides a unique inverse solution for a magnetic source image that is the best estimate in the least-squares sense. This has been applied to determine the source current distribution when the primary current is confined to a surface or set of surfaces. In model simulations of cortical activity of the human brain, the magnetic field pattern across the scalp is interpreted with prior knowledge of anatomy to yield a unique magnetic source image across a portion of cerebral cortex, without resort to an explicit source model.

Accuracy and time play an important role in medical and neuropsychological diagnosis and research. The inverse problem in the field of Electro- and MagnetoEncephaloGraphy requires the repeated simulation of the field distribution for a given dipolar source in the human brain using a volume-conduction model of the head. High resolution finite element head modeling allows the inclusion of tissue conductivity inhomogeneities and anisotropies. We will present new approaches for individually determining the direction-dependent conductivities of skull and brain white matter, based on non-invasive multimodal magnetic resonance imaging data, and for generating a high resolution realistic anisotropic finite element model of the human head. Error estimations will indicate the necessity of the chosen complex forward model. The finite element approach within the inverse problem leads to a sparse, large scale, linear equation system with many different right hand sides to be solved. The presented solution process is based on a parallel algebraic multigrid method. It is shown that very short computation times can be achieved through the combination of the multigrid technique and the parallelization on distributed memory computers. The iterative solver approach is shown to be stable towards modeling of tissue anisotropy. A solver time comparison to a classical parallel Jacobi preconditioned conjugate gradient method is given.

Keywords: Fusion