Characterizing functional connectivity differences in aging adults using machine learning on resting state fMRI data

The brain at rest consists of spatially distributed but functionally connected regions, called intrinsic connectivity networks (ICNs). Resting state functional magnetic resonance imaging (rs-fMRI) has emerged as a way to characterize brain networks without confounds associated with task fMRI such as...

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Bibliographic Details

Published in:	Frontiers in Computational Neuroscience
Main Authors:	Svyatoslav eVergun, Alok eDeshpande, Timothy B. Meier, Jie eSong, Dana L. Tudorascu, Veena A. Nair, Vikas eSingh, Bharat B. Biswal, Mary Elizabeth Meyerand, Rasmus M. Birn, Vivek ePrabhakaran
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2013-04-01
Subjects:	functional connectivity aging neuroscience resting state fMRI Support vector machine brain reorganization
Online Access:	http://journal.frontiersin.org/Journal/10.3389/fncom.2013.00038/full