Normalized cut group clustering of resting-state FMRI data.

ABSTRACT:

Background

Functional brain imaging studies have indicated that distinct anatomical brain regions can show coherent spontaneous neuronal activity during rest. Regions that show such correlated behavior are said to form resting-state networks (RSNs). RSNs have been investigated using seed-dependent functional connectivity maps and by using a number of model-free methods. However, examining RSNs across a group of subjects is still a complex task and often involves human input in selecting meaningful networks.

Methodology/principal findings

We report on a voxel based model-free normalized cut graph clustering approach with whole brain coverage for group analysis of resting-state data, in which the number of RSNs is computed as an optimal clustering fit of the data. Inter-voxel

SUBMITTER: van den Heuvel M 

PROVIDER: S-EPMC2291558 | biostudies-literature | 2008 Apr

REPOSITORIES: biostudies-literature