Anatomical constraints on source models for high-resolution EEG and MEG derived from MRI.
Electroencephalography (EEG) remains the primary tool for measuring changes in dynamic brain function due to disease state with the millisecond temporal resolution of neuronal activity. In recent decades EEG has been supplanted by CT and MRI for the localization of tumors and lesions in the brain. In contrast to the excellent temporal resolution of EEG, the spatial information in EEG is limited by the volume conduction of currents through the tissues of the head. We have extracted source models (position and orientation) from MRI scans to investigate the theoretical relationship between brain sources and EEG recorded on the scalp. Although detailed information about the boundaries between different tissues can also be obtained from MRI, these models are only approximate because of our relatively poor knowledge of the conductivities of the different tissue compartments in living heads. We also compare the resolution of EEG with magnetoecephalography (MEG), which offers the advantage of requiring less detail about volume conduction in the head. The brain's magnetic field depends only on the position of sources in the brain and the position and orientation of the sensors. We demonstrate that EEG and MEG space average neural activity over comparably large volumes of the brain; however, they are preferentially sensitive to sources of different orientation suggesting a complementary role for EEG and MEG. High-resolution EEG methods potentially yield much better localization of source activity in superficial brain areas. These methods do not make any assumptions about the sources, and can be easily co-registered with the brain surface derived from MRI. While there is much information to be gained by using anatomical MRI to develop models of the generators of EEG/MEG, functional neuroimaging (e.g., fMRI) signals and EEG/MEG signals are not easily related.
Srinivasan
Ramesh
R
Department of Cognitive Sciences, University of California, 3151 SSPA, Irvine, CA 92697-5100, USA. r.srinivasan@uci.edu
D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology / Q000473:pathology*; D001931:Brain Mapping; D003198:Computer Simulation; D004569:Electroencephalography / Q000379:methods*; D004574:Electromagnetic Fields; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015225:Magnetoencephalography / Q000379:methods*; D015233:Models, Statistical; D008962:Models, Theoretical