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

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

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.

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

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

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.

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

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.

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

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

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

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.

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

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

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: 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

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

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

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

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

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.

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

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

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

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 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

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 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

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.

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

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

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.

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

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

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.

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.

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

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

It is generally believed that because the skull has low conductivity to electric current but is transparent to magnetic fields, the measurement sensitivity of the magnetoencephalography (MEG) in the brain region should be more concentrated than that of the electroencephalography (EEG). It is also believed that the information recorded by these techniques is very different. If this were indeed the case, it might be possible to justify the cost of MEG instrumentation which is at least 25 times higher than that of EEG instrumentation. The localization of measurement sensitivity using these techniques was evaluated quantitatively in an inhomogeneous spherical head model using a new concept called half-sensitivity volume (HSV). It is shown that the planar gradiometer has a far smaller HSV than the axial gradiometer. However, using the EEG it is possible to achieve even smaller HSV's than with whole-head planar gradiometer MEG devices. The micro-superconducting quantum interference device (SQUID) MEG device does have HSV's comparable to those of the EEG. The sensitivity distribution of planar gradiometers, however, closely resembles that of dipolar EEG leads and, therefore, the MEG and EEG record the electric activity of the brain in a very similar way.

Keywords: Anisotropy ; Cerebral Cortex/anatomy & histology ; Electric Conductivity ; Electrodes ; *Electroencephalography ; Equipment Design ; Head ; Human ; *Magnetoencephalography/instrumentation ; Models, Neurological ; Sensitivity and Specificity ; Skull/anatomy & histology ; 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.

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.

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

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

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 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

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 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.

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

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.

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.

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.

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.

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

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.

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

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

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

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

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 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

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

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

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.

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.

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).

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

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