Scott Makeig, UCSD
Greg Worrell, Mayo Clinic
Simon Warfield, Harvard

The localization of epileptic sources (electric current dipoles) within the human brain is one of the major applications of inverse methods to electroencephalography (EEG). Independent component analysis (ICA) can be used to separate temporal and spatial EEG data into statistically independent components. From those components, Dr. Makeig and his group select just those that correspond to epileptic signals. They performed ICA on the EEG data from scalp surface electrodes and implanted cortical electrodes for an epilepsy patient; for each source component, they solved an inverse problem to locate the single dipole that best reproduced that component. For these patient-specific simulations, the Center built a heterogeneous, isotropic finite-element volume conductor model based on MRI data from the patient.