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199 Spatio-temporal source imaging of the human visual cortex: A comparison of MEG and FMRI
78
Abstracts
/International
Journal
SYMPOSIUM 34: EEG and MEG Source Imaging of the Human Brain
I98 NEW DEVELOPMENTS IN SOURCE LOCALIZATION ALGORITHMS: CLINICAL EXAMPLES C.J. Aine*, M. Huang, Silveri, M. Weisend Nemoimaging Center, Radiology, Department ico School of Medicine,
R. Christner, J. Stephen, J. Meyer, J. VA Medical Center, Department of of Neurology, University of New MexAlbuquerque, New Mexico, USA
Significant advances have been made recently in hardware and software design for MEG studies. Several whole-head systems are now in place (e.g., Picker/Neuromag-122, Vector View; BTi Magnes, and CTF) and newer automated analyses are becoming available for source localization studies using MEG and EEG. These developments make it easier and faster to acquire and analyze MEG data than before and provide&e capability to image active regions throughout the head volume. New source localization algorithms provide more accurate and efficient multi-dipole, spatio-temporal localization of active regions, which make it feasible to apply these techniques in the clinic. Huang, Hamalainen, and Scherg will speak of recent developments in head models and source hodels. Scherg will also discuss recent attempts at integrating information from functional MRI and MEG/EEG measures. Aine will show results from two recently developed algorithms by Los Alamos National Laboratory and the University of Southern California (Multi-start Downhill Simplex Search by Huang and colleagues and RAP-MUSIC by Mosher and Leahy) using examples from clinical cases. These algorithms help circumvent several problems typically associated with source localization studies (e.g., the user no longer needs to specify the starting parameters, new search strategies help prevent the algorithm from becoming trapped in local minimal. Somatosensory studies in stroke and pre-surgical localization patients will be the focus. A square wave pulse of 0.2 ms duration and a repetition rate of 2 Hz was applied in random order to the left/right median and tibia1 nerves. Three hundred trials were acquired for each extremity using a Picker/Neuromag-122 whole-head system. The data were digitized at 1 kHz with high- and lowpass tilters set at l-330 Hz. Automated algorithms were applied to different intervals of time after an initial examination of the singular value decomposition (SVD) for these intervals, to aid in determining the number of dipoles contained in the data. In the somatosensory studies, 6-8 regions of activity were typically localized during a 250 ms interval of time, poststimu1~s. The source locations ranged from pre- and postcentral @I) sulcal regions (both contra- and ipsilateral sources) through secondary somatosensory (S21 regions (contra- and ipsilateral), as well as posterior parietal, middle cingulate, and
of Psychophysiology
30 (1998)
7-94
right superior temporal sulcus sources. The results also indicate: 1) Sl showed the expected somatotopy between median and tibia1 nerve stimulation; and 2) the representations of Sl and S2 are mirror images of each other as suggested by Pentield and Roberts (i.e., while the representation of feet in Sl is dorsal relative to the representation of the hand, the representations in S2 are reversed). We are currently in the process of assessing correlations between type of deficit (e.g., lack of secondary sources in the affected side) and recovery. MEG in combination with anatomical MRI can now provide a detailed account of sensory and cognitive processes in both spatial and temporal domains to help characterize functional pathology in the clinical environment. The new analyses are more comprehensive and efficient.
199 SPATIO-TEMPORAL SOURCE IMAGING HUMAN VISUAL CORTEX: A COMPARISON AND FMRI
OF THE OF MEG
M. Scherg’, R. Goebel’ ‘Department of Neurology, Section of Biomagnetism, University of Heidelberg, Heidelberg, Germany 2Max-Planck-Institute for Brain Research, Frankfurt, Germany Functional magnetic resonance imaging (fMR1) reveals taskrelated activation of circumscribed brain regions by imaging the enhanced oxygen metabolism. However, the rise-time of the blood oxygen level-dependent (BOLD) signal in the WRI is very slow as compared to the temporal dynamics of the neural processes. Therefore, only faster imaging techniques like EEG or MEG can fully reveal the temporal evolution and sequence of task-related activations in the brain. Spatio-temporal source analysis of event-related potentials or magnetic fields attempts to estimate the compound activation current of each brain region that a) is involved in the processing of the task, and b) contributes significantly to the surface EEG or MEG. In principle, this can be achieved by placing one equivalent dipole into a volume conductor model of the head at the center of each activated region. Then, the temporal evolution of all dipole currents (source waveforms) can be estimated by a system of linear equations. The crucial inverse problem, however, is to define appropriate equivalent source locations and orientations. For an approximate solution, strategies utilizing temporal information combined with exhaustive search methods appear most appropriate. Localizations obtained with these techniques can be contrasted with the locations defined by clusters of BOLD signal in the fMR1 provided that comparable experimental paradigms have been set up. A flowfield experiment contrasting the onset of moving and stationary dots was used to study the processing of visual motion with a whole-head MEG system (Neuromag-122TM) and fMR1 (Siemens Vision 1.5T) in 5 normal volunteers. Using spatio-temporal multiple source analysis (BESA), we
Abstracts
/International
Journal
estimated equivalent generators underlying the visual evoked fields. Fitted source locations were compared with dipoles seeded into the MEG head model at locations defined by fMRI clusters. An alternative model was obtained by using the seeded dipole locations and fitting the orientations to the MEG data. Source activity waveforms were compared between both approaches. Dipole locations fitted independently to the motion-related MEG activity were within 1.5 cm of the seeds in the visual motion complex (MT/MST) as determined by fMR1. Two major problems were encountered regarding the comparison of both techniques: First, MEG difference waveforms between conditions did not result in a sufficient suppression of brain activities unrelated to motion. Hence, MEG models required additional sources and/or spatial components as compared to the number of significant fMR1 clusters. Second, several fMR1 clusters in the visual cortex were in close proximity. Due to the noise in the MEG data, separation of these activities was limited even when using the fMR1 clusters as seeds for multiple source models. Despite these limitations and fundamental differences between both methods, the combination of MEG and fMR1 provides valuable information on the timing of brain processes in active fMR1 spots and demonstrates the value of spatiotemporal multiple source modeling.
200 COMPARING THE SOURCE LOCALIZATION ACCURACY OF EEG AND MEG FOR DIFFERENT HEAD MODELING TECHNIQUES USING A HUMAN SKULL PHANTOM M. Huang, R.M. Leahy, J.C. Mosher, M.E. Spencer Neuroimaging Center, VA Medical Center, Albuquerque, Mexico, USA
New
An important step in validating source localization techniques for EEG and MEG is to examine the localization accuracy in cases where the true locations and temporal activity of the sources are known. Studies of this type can be performed using computer simulations; however, the majority of published results that use computer simulations assume simplified models for the head, instrumentation and noise. Motivated by the desire to produce realistic data corresponding to complex spatio-temporal current sources and to include the effects of realistic head geometries, we developed a phantom consisting of 32 independently programmable and isolated dipoles which were inserted in a human skull for both EEG and MEG data acquisition. The interior of the skull was perfused with conductive gelatin, and the exterior was coated with an approximately three to five mm thick conductive latex to mimic the scalp. The majority of the dipoles forms two clusters, one near the left “central sulcus”, and the other in the left “occipital region”. The orientations of the dipoles vary from a few degrees to nearly ninety degrees with respect to the radial orientation defined by the local curvature, so there was no-bias
of Psychophysiology
30 (1998)
7-94
79
toward either EEG or MEG. The 32 dipoles were activated sequentially in time. The EEG data were collected at 64 sensor sites on the scalp using Neuroscan Synamps system. MEG data were collected using the Picker/Neuromag whole head MEG system containing 61 dual-channel planar gradiometers. A CT scan of the phantom was acquired using a Siemens Somatom Plus X-ray CT scanner to provide us the true locations of the dipoles, as well as the geometric information of the phantom. Both locally fitted spherical head models and the boundary element method (BEM) were tested as the forward models in the EEG and MEG localizations. RAP-MUSIC developed by Mosher and Leahy was adopted as the inverse source localization technique. The results show that the BEM model produces slightly smaller localization errors than the locally fitted spherical model for the 32 dipole configuration that we used. The mean errors of 2-3mm were obtained for the MEG data and 7-8mm for the EEG. The average errors in the tangential components for MEG and EEG using spherical and BEM forward models were all within 10 degrees, and there is no evidence in our data for significant differences in tangential orientation between MEG and EEG. Also, we note that with a widely distributed range of orientations, both MEG and EEG were able to produce reasonably accurate source localizations. This may indicate that some of the concerns expressed in the literature over the blindness of MEG to radial sources are possibly exaggerated. Furthermore, in order to understand the possible sources of errors that contributed to the MEG and EEG results using the skull phantom, carefully designed computer simulations were performed. We believe that the main source of error for MEG is the mis-registration error between the patient coordinate system and the X-ray CT coordinate system. The major erro; source for EEG may be discrepancies between the homogeneous isotropic shell models used in our forward computations and the true, probably anisotropic, nature of the phantom itself.
201 FOCAL AND DIFFUSE SOURCE MODELS IN MEG STUDIES Matti HamLl?iinen* Low Temperature Laboratory, Helsinki University of Technology, P.O. Box 2200,02015 HUT, Espoo, Finland Given a current distribution in the brain and an accurate description of the electromagnetic parameters of the surrounding tissues it is in principle straightforward to calculate the ensuing electromagnetic field. On the other hand, unique estimation of the currents from the measured magnetic field or the voltage distribution is possible only if suitable constraints are applied. The simplest physiologically sound model for the neural current distribution is a set of point sources, current dipoles. In the time-varying dipole model an epoch of data is modeled with a set of spatially lixed dipoles whose amplitudes vary with
Abstracts
/International
Journal
SYMPOSIUM 34: EEG and MEG Source Imaging of the Human Brain
I98 NEW DEVELOPMENTS IN SOURCE LOCALIZATION ALGORITHMS: CLINICAL EXAMPLES C.J. Aine*, M. Huang, Silveri, M. Weisend Nemoimaging Center, Radiology, Department ico School of Medicine,
R. Christner, J. Stephen, J. Meyer, J. VA Medical Center, Department of of Neurology, University of New MexAlbuquerque, New Mexico, USA
Significant advances have been made recently in hardware and software design for MEG studies. Several whole-head systems are now in place (e.g., Picker/Neuromag-122, Vector View; BTi Magnes, and CTF) and newer automated analyses are becoming available for source localization studies using MEG and EEG. These developments make it easier and faster to acquire and analyze MEG data than before and provide&e capability to image active regions throughout the head volume. New source localization algorithms provide more accurate and efficient multi-dipole, spatio-temporal localization of active regions, which make it feasible to apply these techniques in the clinic. Huang, Hamalainen, and Scherg will speak of recent developments in head models and source hodels. Scherg will also discuss recent attempts at integrating information from functional MRI and MEG/EEG measures. Aine will show results from two recently developed algorithms by Los Alamos National Laboratory and the University of Southern California (Multi-start Downhill Simplex Search by Huang and colleagues and RAP-MUSIC by Mosher and Leahy) using examples from clinical cases. These algorithms help circumvent several problems typically associated with source localization studies (e.g., the user no longer needs to specify the starting parameters, new search strategies help prevent the algorithm from becoming trapped in local minimal. Somatosensory studies in stroke and pre-surgical localization patients will be the focus. A square wave pulse of 0.2 ms duration and a repetition rate of 2 Hz was applied in random order to the left/right median and tibia1 nerves. Three hundred trials were acquired for each extremity using a Picker/Neuromag-122 whole-head system. The data were digitized at 1 kHz with high- and lowpass tilters set at l-330 Hz. Automated algorithms were applied to different intervals of time after an initial examination of the singular value decomposition (SVD) for these intervals, to aid in determining the number of dipoles contained in the data. In the somatosensory studies, 6-8 regions of activity were typically localized during a 250 ms interval of time, poststimu1~s. The source locations ranged from pre- and postcentral @I) sulcal regions (both contra- and ipsilateral sources) through secondary somatosensory (S21 regions (contra- and ipsilateral), as well as posterior parietal, middle cingulate, and
of Psychophysiology
30 (1998)
7-94
right superior temporal sulcus sources. The results also indicate: 1) Sl showed the expected somatotopy between median and tibia1 nerve stimulation; and 2) the representations of Sl and S2 are mirror images of each other as suggested by Pentield and Roberts (i.e., while the representation of feet in Sl is dorsal relative to the representation of the hand, the representations in S2 are reversed). We are currently in the process of assessing correlations between type of deficit (e.g., lack of secondary sources in the affected side) and recovery. MEG in combination with anatomical MRI can now provide a detailed account of sensory and cognitive processes in both spatial and temporal domains to help characterize functional pathology in the clinical environment. The new analyses are more comprehensive and efficient.
199 SPATIO-TEMPORAL SOURCE IMAGING HUMAN VISUAL CORTEX: A COMPARISON AND FMRI
OF THE OF MEG
M. Scherg’, R. Goebel’ ‘Department of Neurology, Section of Biomagnetism, University of Heidelberg, Heidelberg, Germany 2Max-Planck-Institute for Brain Research, Frankfurt, Germany Functional magnetic resonance imaging (fMR1) reveals taskrelated activation of circumscribed brain regions by imaging the enhanced oxygen metabolism. However, the rise-time of the blood oxygen level-dependent (BOLD) signal in the WRI is very slow as compared to the temporal dynamics of the neural processes. Therefore, only faster imaging techniques like EEG or MEG can fully reveal the temporal evolution and sequence of task-related activations in the brain. Spatio-temporal source analysis of event-related potentials or magnetic fields attempts to estimate the compound activation current of each brain region that a) is involved in the processing of the task, and b) contributes significantly to the surface EEG or MEG. In principle, this can be achieved by placing one equivalent dipole into a volume conductor model of the head at the center of each activated region. Then, the temporal evolution of all dipole currents (source waveforms) can be estimated by a system of linear equations. The crucial inverse problem, however, is to define appropriate equivalent source locations and orientations. For an approximate solution, strategies utilizing temporal information combined with exhaustive search methods appear most appropriate. Localizations obtained with these techniques can be contrasted with the locations defined by clusters of BOLD signal in the fMR1 provided that comparable experimental paradigms have been set up. A flowfield experiment contrasting the onset of moving and stationary dots was used to study the processing of visual motion with a whole-head MEG system (Neuromag-122TM) and fMR1 (Siemens Vision 1.5T) in 5 normal volunteers. Using spatio-temporal multiple source analysis (BESA), we
Abstracts
/International
Journal
estimated equivalent generators underlying the visual evoked fields. Fitted source locations were compared with dipoles seeded into the MEG head model at locations defined by fMRI clusters. An alternative model was obtained by using the seeded dipole locations and fitting the orientations to the MEG data. Source activity waveforms were compared between both approaches. Dipole locations fitted independently to the motion-related MEG activity were within 1.5 cm of the seeds in the visual motion complex (MT/MST) as determined by fMR1. Two major problems were encountered regarding the comparison of both techniques: First, MEG difference waveforms between conditions did not result in a sufficient suppression of brain activities unrelated to motion. Hence, MEG models required additional sources and/or spatial components as compared to the number of significant fMR1 clusters. Second, several fMR1 clusters in the visual cortex were in close proximity. Due to the noise in the MEG data, separation of these activities was limited even when using the fMR1 clusters as seeds for multiple source models. Despite these limitations and fundamental differences between both methods, the combination of MEG and fMR1 provides valuable information on the timing of brain processes in active fMR1 spots and demonstrates the value of spatiotemporal multiple source modeling.
200 COMPARING THE SOURCE LOCALIZATION ACCURACY OF EEG AND MEG FOR DIFFERENT HEAD MODELING TECHNIQUES USING A HUMAN SKULL PHANTOM M. Huang, R.M. Leahy, J.C. Mosher, M.E. Spencer Neuroimaging Center, VA Medical Center, Albuquerque, Mexico, USA
New
An important step in validating source localization techniques for EEG and MEG is to examine the localization accuracy in cases where the true locations and temporal activity of the sources are known. Studies of this type can be performed using computer simulations; however, the majority of published results that use computer simulations assume simplified models for the head, instrumentation and noise. Motivated by the desire to produce realistic data corresponding to complex spatio-temporal current sources and to include the effects of realistic head geometries, we developed a phantom consisting of 32 independently programmable and isolated dipoles which were inserted in a human skull for both EEG and MEG data acquisition. The interior of the skull was perfused with conductive gelatin, and the exterior was coated with an approximately three to five mm thick conductive latex to mimic the scalp. The majority of the dipoles forms two clusters, one near the left “central sulcus”, and the other in the left “occipital region”. The orientations of the dipoles vary from a few degrees to nearly ninety degrees with respect to the radial orientation defined by the local curvature, so there was no-bias
of Psychophysiology
30 (1998)
7-94
79
toward either EEG or MEG. The 32 dipoles were activated sequentially in time. The EEG data were collected at 64 sensor sites on the scalp using Neuroscan Synamps system. MEG data were collected using the Picker/Neuromag whole head MEG system containing 61 dual-channel planar gradiometers. A CT scan of the phantom was acquired using a Siemens Somatom Plus X-ray CT scanner to provide us the true locations of the dipoles, as well as the geometric information of the phantom. Both locally fitted spherical head models and the boundary element method (BEM) were tested as the forward models in the EEG and MEG localizations. RAP-MUSIC developed by Mosher and Leahy was adopted as the inverse source localization technique. The results show that the BEM model produces slightly smaller localization errors than the locally fitted spherical model for the 32 dipole configuration that we used. The mean errors of 2-3mm were obtained for the MEG data and 7-8mm for the EEG. The average errors in the tangential components for MEG and EEG using spherical and BEM forward models were all within 10 degrees, and there is no evidence in our data for significant differences in tangential orientation between MEG and EEG. Also, we note that with a widely distributed range of orientations, both MEG and EEG were able to produce reasonably accurate source localizations. This may indicate that some of the concerns expressed in the literature over the blindness of MEG to radial sources are possibly exaggerated. Furthermore, in order to understand the possible sources of errors that contributed to the MEG and EEG results using the skull phantom, carefully designed computer simulations were performed. We believe that the main source of error for MEG is the mis-registration error between the patient coordinate system and the X-ray CT coordinate system. The major erro; source for EEG may be discrepancies between the homogeneous isotropic shell models used in our forward computations and the true, probably anisotropic, nature of the phantom itself.
201 FOCAL AND DIFFUSE SOURCE MODELS IN MEG STUDIES Matti HamLl?iinen* Low Temperature Laboratory, Helsinki University of Technology, P.O. Box 2200,02015 HUT, Espoo, Finland Given a current distribution in the brain and an accurate description of the electromagnetic parameters of the surrounding tissues it is in principle straightforward to calculate the ensuing electromagnetic field. On the other hand, unique estimation of the currents from the measured magnetic field or the voltage distribution is possible only if suitable constraints are applied. The simplest physiologically sound model for the neural current distribution is a set of point sources, current dipoles. In the time-varying dipole model an epoch of data is modeled with a set of spatially lixed dipoles whose amplitudes vary with