ICA Analysis for Decision-Making Task on fMRI

Abstract

Brain functional activation of decision-making on fMRI experiment is seldom analyzed by data driven method to reveal the distinct brain functional network of decision-making. In this paper, a spatial independent component analysis (sICA) is presented to detect the functional network underlying decision-making by analyzing the unmixing matrices temporal components corresponding to spatial separated pattern. Our results show that ICA could separate various sub-functional activation networks to understand the neural mechanisms underlying decision making, which mainly include functional network of conflict detection, cognitive and emotion.