EEG source localization using a sparsity prior based on Brodmann areas

Abstract

Localizing the sources of electrical activity in the brain from electroencephalographic (EEG) data is an important tool for noninvasive study of brain dynamics. Generally, the source localization process involves a high-dimensional inverse problem that has an infinite number of solutions and thus requires additional constraints to be considered to have a unique solution. In this article, we propose a novel method for EEG source localization. The proposed method is based on dividing the cerebral cortex of the brain into a finite number of “functional zones” which correspond to unitary functional areas in the brain. To specify the sparsity profile of human brain activity more concisely, the pr..