Frontiers in psychiatry
Reduced causal connectivity in multiple resting-state networks in autism spectrum disorder detected by convergent cross mapping
By Zhang H, He L, Wang D and 5 others.
Abstract
Background
This study investigates alterations in causal connectivity within resting-state brain functional networks in patients with Autism Spectrum Disorder (ASD) using the Convergent Cross Mapping (CCM) method.
Methods
Data were obtained from the Autism Brain Imaging Data Exchange I (ABIDE I) public database. To minimize variability, resting-state functional magnetic resonance imaging (rs-fMRI) data were restricted to the NYU site, comprising 52 ASD patients and 52 matched typically developing controls. Based on the AAL template, time series were extracted from five resting-state networks: attention network, default mode network, sensorimotor network, visual network, and subcortical network. The CCM method was employed to analyze causal connectivity among these brain regions. Additionally, a support vector machine (SVM) classifier was utilized to assess the discriminative potential of the identified causal connectivity patterns.