A GICA-TVGL framework to study sex differences in resting state fMRI dynamic connectivity
Abstract
Functional magnetic resonance imaging (fMRI) has been implemented widely to study brain connectivity. In particular, time-varying connectivity analysis has emerged as an important measure to uncover essential knowledge within the network. On the other hand, independent component analysis (ICA) has served as a powerful tool to preprocess fMRI data before performing network analysis. Together, they may lead to novel findings.We propose a new...
Paper Details
Title
A GICA-TVGL framework to study sex differences in resting state fMRI dynamic connectivity
Published Date
Feb 1, 2020
Volume
332
Pages
108531 - 108531
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