Iterative Minimum Norm Methods for MEG Inverse Problem

摘要

Magnetoencephalography (MEG) is one of the non-invasive monitoring methods developed for monitoring the human brain activities. Among large numbers of algorithms developed to solve the MEG inverse problem, this paper focuses on the class of weighted minimum norm (WMN) methods with which less prior information of sources is required, and modifications for each of so-called magnetic field tomography (MFT) and source affine image reconstruction (SAFFIRE) are described.