Comparison of inverse problem linear and non-linear methods for localization source: a combined TMS-EEG study

TL;DR

This study compares linear and non-linear inverse methods for EEG source localization after TMS stimulation, aiming to establish criteria for selecting the most effective approach in brain activity analysis.

Contribution

It provides a comparative analysis of multiple inverse methods (sLORETA, MNE, dSPM, wMEM) using simulations to guide method selection for EEG source localization post-TMS.

Findings

wMEM shows improved localization accuracy in simulations

dSPM effectively captures brain activity dynamics

Comparison criteria for inverse methods are established

Abstract

The Electro-Encephalo-Graphy (EEG) technique consists of estimating the cortical distribution of signals over time of electrical activity and also of locating the zones of primary sensory projection. Moreover, it is able to record respectively the variations of potential and field magnetic waves generated by electrical activity in the brain every millisecond. Concerning, the study of the localization source, the brain localizationactivity requires the solution of a inverse problem. Many different imaging methods are used to solve the inverse problem.The aim of the presentstudy is to provide comparison criteria for choosing the least bad method. Hence, the transcranial magnetic stimulation (TMS) and electroencephalography (EEG) technique are combined for the sake of studying the dynamics of the brain at rest following a disturbance. The study focuses in the comparison of the following methods for EEG following stimulation by TMS: sLORETA (standardized Low Resolution Electromagnetic Tomography), MNE (Minimum Estimate of the standard), dSPM (dynamic Statistical Parametric Mapping) and wMEM (wavelet based on the Maximum Entropy on the Mean)in order to study the impact of TMS towards rest and to study inter and intra zone connectivity.The contribution of the comparison is demonstrated via the stages of the simulations.