Use of prior knowledge in brain electromagnetic source analysis

SummaryUsing multichannel measurements of EEG and/or MEG, macroscopic source activities can be estimated in the human brain using brain electric source analysis (BESA, Scherg 1990). If a discrete number of brain areas is active, functional brain images which depict the locations and orientations of equivalent dipole sources as well as the dynamics of the local macroscopic currents can be obtained from such data - in principle -without external knowledge. However, given a certain number of sources or ‘neural masses’ (Freeman 1975) which contribute to an event related response (ERP), it can be difficult to find the correct solution due to background noise in the data and distortions from the head model. Prior knowledge based on anatomy and physiology can be useful to constrain spatial or temporal parameters of the model and to define better cost functions for fitting locations and orientations. An analysis of the auditory evoked N100 complex and of the auditory mismatch negativity (MMN) is presented which illustrates the use of spatial constraints. Also, the use of a modified cost function is demonstrated which limits source currents in certain time intervals.

[1]  Herbert G. Vaughan,et al.  Chapter 4 – The Analysis of Scalp-Recorded Brain Potentials , 1974 .

[2]  Donald O. Walter,et al.  Mass action in the nervous system , 1975 .

[3]  W. Freeman.  Use of Spatial Deconvolution to Compensate for Distortion of EEG by Volume Conduction , 1980, IEEE Transactions on Biomedical Engineering.

[4]  Yoshiwo Okamoto,et al.  Limitation of the Inverse Problem in Body Surface Potential Mapping , 1983, IEEE Transactions on Biomedical Engineering.

[5]  M Scherg,et al.  Spatio-temporal modelling of early auditory evoked potentials. , 1984, Revue de laryngologie - otologie - rhinologie.

[6]  M Scherg,et al.  A new interpretation of the generators of BAEP waves I-V: results of a spatio-temporal dipole model. , 1985, Electroencephalography and clinical neurophysiology.

[7]  M. Scherg,et al.  Two bilateral sources of the late AEP as identified by a spatio-temporal dipole model. , 1985, Electroencephalography and clinical neurophysiology.

[8]  M. Scherg,et al.  Evoked dipole source potentials of the human auditory cortex. , 1986, Electroencephalography and clinical neurophysiology.

[9]  H. Spekreijse,et al.  Principal components analysis for source localization of VEPs in man , 1987, Vision Research.

[10]  F. Perrin,et al.  Mapping of scalp potentials by surface spline interpolation. , 1987, Electroencephalography and clinical neurophysiology.

[11]  H. Spekreijse,et al.  Mathematical dipoles are adequate to describe realistic generators of human brain activity , 1988, IEEE Transactions on Biomedical Engineering.

[12]  D. Barth,et al.  Spatiotemporal Modeling of Somatosensory Evoked Magnetic Fields , 1989 .

[13]  M. Scherg,et al.  Frequency-Specific Sources of the Auditory N19-P30-P50 Response Detected by a Multiple Source Analysis of Evoked Magnetic Fields and Potentials , 1989 .

[14]  H. Haneishi,et al.  Discussion of Biomagnetic Imaging System and Reconstruction Algorithm , 1989 .

[15]  M. Scherg,et al.  A Source Analysis of the Late Human Auditory Evoked Potentials , 1989, Journal of Cognitive Neuroscience.

[16]  Samuel J. Williamson,et al.  Advances in Biomagnetism , 1990, Springer US.

[17]  J. D. Munck.  The estimation of time varying dipoles on the basis of evoked potentials. , 1990 .

[18]  M. Scherg.  Fundamentals if dipole source potential analysis , 1990 .

[19]  A. Ioannides,et al.  Continuous probabilistic solutions to the biomagnetic inverse problem , 1990 .

[20]  T W Picton,et al.  Separation and identification of event-related potential components by brain electric source analysis. , 1991, Electroencephalography and clinical neurophysiology. Supplement.

[21]  P. M. Rossini,et al.  Auditory evoked magnetic fields and electric potentials , 1991 .

[22]  M. Scherg,et al.  Somatosensory evoked potentials and magnetic fields: separation of multiple source activities. , 1993, Physiological measurement.

[23]  A. Achim,et al.  Methods for separating temporally overlapping sources of neuroelectric data , 2005, Brain Topography.