Alteration of resting-state network dynamics in autism spectrum disorder based on leading eigenvector dynamics analysis

ABSTRACT:

Background

Neurobiological models to explain the vulnerability of autism spectrum disorders (ASDs) are scarce, and previous resting-state functional magnetic resonance imaging (rs-fMRI) studies mostly examined static functional connectivity (FC). Given that FC constantly evolves, it is critical to probe FC dynamic differences in ASD patients.

Methods

We characterized recurring phase-locking (PL) states during rest in 45 ASD patients and 47 age- and sex-matched healthy controls (HCs) using Leading Eigenvector Dynamics Analysis (LEiDA) and probed the organization of PL states across different fine grain sizes.

Results

Our results identified five different groups of discrete resting-state functional networks, which can be defined as recurrent PL state overtimes. Spe

SUBMITTER: Wang C 

PROVIDER: S-EPMC9892631 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature