EEG and ERP Imaging of Brain Function
The purpose of functional brain mapping is to localize patterns of neuronal activity associated with sensory, motor, and cognitive functions, or with disease processes. To be complete, an imaging modality needs near millimeter precision in localizing regions of activated tissue and sub-second temporal precision for characterizing changes in patterns of activation over time. Increasingly fine anatomical resolution is available with functional magnetic resonance imaging (fMRI). However, fMRI is an indirect measure of neuronal electrical activity whose temporal resolution is too gross to resolve the rapidly shifting patterns of activity that are characteristic of actual neurophysiological processes. In contrast, electroencephalography (EEG) and event-related potential (ERP) methods have a temporal resolution typically in the one to five millisecond range, depending on the AID rate. For simplicity the term EEG is used here in a general sense to refer both to recordings of brain electrical activity and, except where noted, to recordings of brain magnetic activity called magnetoencephalograms or MEGs. The nature of MEG recording technology and the relative strengths and weaknesses of EEG versus MEG approaches have been reviewed elsewhere (Cohen & Cuffin, 1991; Leahy et al., 1998; Williamson & Kaufman, 1987). From a broad perspective that considers all neuroimaging modalities, the differences between EEG and MEG are slight relative to their similarities.
KeywordsFatigue Covariance Coherence Immobilization Expense
Unable to display preview. Download preview PDF.
- Fender, D.H. (1987). Source localization of brain electrical activity. In A.S. Gevins & A. Rémond (Eds.), Methods of analysis of brain electrical and magnetic signals. Vol. 1 (pp. 355–403). Amsterdam: Elsevier.Google Scholar
- George, J.S., Aine, C.J., Mosher, J.C., Schmidt, D.M., Ranken, D.M., Schlitt, H.A., Wood, C.C., Lewine, J.D., Sanders, J.A., & Belliveau, J.W. (1995). Mapping function in the human brain with magnetoencephalography, anatomical magnetic resonance imaging, and functional magnetic resonance imaging. Journal of Clinical Neurophysiology, 12, 406–431.PubMedCrossRefGoogle Scholar
- Gersch, W. (1987). Non-stationary multichannel time series analysis. In A.S. Gevins & A. Rémond (Eds.), Methods of analysis of brain electrical and magnetic signals. Vol. 1 (pp. 261–296). Amsterdam: Elsevier.Google Scholar
- Gevins, A.S., & Bressler, S.L. (1988). Functional topography of the human brain. In G. Pfurtscheller (Ed.), Functional brain imaging (pp. 99–116). Toronto: Hans Huber Publishers.Google Scholar
- Gevins, A.S., Bressler, S.L., Morgan, N.H., Cutillo, B.A., White, R.M., Greer, D., & Illes, J. (1989a). Event-related covariances during a bimanual visuomotor task. Part I. Methods and analysis of stimulus and response-locked data. Electroencephalography and Clinical Neurophysiology, 74, 58–75.PubMedCrossRefGoogle Scholar
- Hillyard, S.A., & Picton, T.W. (1987). Electrophysiology of cognition. In V.B. Mountcastle & F. Plum (Eds.), Handbook of Physiology: Vol. 5. Higher Functions of the Brain (2nd ed., pp. 519–584). Bethesda, MD: American Physiological Society.Google Scholar
- Jasper, H.H. (1958). The ten-twenty electrode system of the International Federation. Electroencephalograph and Clinical Neurophysiology, 10, 371–375.Google Scholar
- Livanov, M.N. (1977). Spatial organization of cerebral processes. New York: Wiley.Google Scholar
- Mars, N.J., & Lopes da Silva, F.H. (1987). EEG analysis methods based on information theory. In A.S. Gevins & A. Remond (Eds.), Methods of Analysis of Brain Electrical and Magnetic Signals: Vol. 1 (pp. 297–307). Amsterdam: Elsevier.Google Scholar
- Nunez, P.L. (1981). Electric fields in the brain: The neurophysics of EEG. New York: Oxford University Press.Google Scholar
- Regan, D. (1989). Human brain electrophysiology. New York: Elsevier.Google Scholar
- Williamson, S.J., & Kaufman, L. (1987). In A.S. Gevins & A. Remond (Eds.), Handbook of electroencephalography and clinical neurophysiology, Vol. 1: Methods of analysis of brain electrical and magnetic signals (pp. 405–448). Amsterdam: Elsevier.Google Scholar