Co-activation pattern alterations in autism spectrum disorder-A volume-wise hierarchical clustering fMRI study.

ABSTRACT:

Introduction

There has been a growing effort to characterize the time-varying functional connectivity of resting state (RS) fMRI brain networks (RSNs). Although voxel-wise connectivity studies have examined different sliding window lengths, nonsequential volume-wise approaches have been less common.

Methods

Inspired by earlier co-activation pattern (CAP) studies, we applied hierarchical clustering (HC) to classify the image volumes of the RS-fMRI data on 28 adolescents with autism spectrum disorder (ASD) and their 27 typically developing (TD) controls. We compared the distribution of the ASD and TD groups' volumes in CAPs as well as their voxel-wise means. For simplification purposes, we conducted a group independent component analysis to extract 14 major RSNs. The RSNs' ave

SUBMITTER: Paakki JJ 

PROVIDER: S-EPMC8213933 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature