Structural connectome alterations between individuals with autism and neurotypical controls using feature representation learning.

ABSTRACT: Autism spectrum disorder is one of the most common neurodevelopmental conditions associated with sensory and social communication impairments. Previous neuroimaging studies reported that atypical nodal- or network-level functional brain organization in individuals with autism was associated with autistic behaviors. Although dimensionality reduction techniques have the potential to uncover new biomarkers, the analysis of whole-brain structural connectome abnormalities in a low-dimensional latent space is underinvestigated. In this study, we utilized autoencoder-based feature representation learning for diffusion magnetic resonance imaging-based structural connectivity in 80 individuals with autism and 61 neurotypical controls that passed strict quality controls. We generated low-dimensional

SUBMITTER: Jang Y 

PROVIDER: S-EPMC10807082 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature