A method for independent component graph analysis of resting-state fMRI.

ABSTRACT:

Introduction

Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non-contiguous regions. To date, the spatial patterns of the networks have been analyzed with techniques developed for volumetric data.

Objective

Here, we detail a graph building technique that allows these ICNs to be analyzed with graph theory.

Methods

First, ICA was performed at the single-subject level in 15 healthy volunteers using a 3T MRI scanner. The identification of nine networks was performed by a multiple-template matching procedure and a subsequent component classification base

SUBMITTER: Ribeiro de Paula D 

PROVIDER: S-EPMC5346515 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature