Unraveling the Autism Spectrum Heterogeneity: Insights From ABIDE I Database Using Data/Model‐Driven Permutation Testing Approaches
Francisco José Alcaide, Ignacio Alvarez Illan, Javier Ramírez, Juan Manuel Gorriz

TL;DR
This study examines brain differences in autism using the ABIDE I database but finds no significant structural differences due to variability across centers and small sample sizes.
Contribution
The study introduces data/model-driven permutation testing to assess multi-center variability in autism neuroimaging.
Findings
No statistically significant brain region differences were found between autism and control groups.
Multi-center variability and limited sample sizes hinder reliable detection of structural differences.
SAM mapping showed greater consistency with existing literature compared to SPM.
Abstract
Autism spectrum condition (ASC) is a neurodevelopmental condition characterized by impairments in communication, social interaction, and restricted or repetitive behaviors. Extensive research has aimed to identify structural brain distinctions between individuals with ASC and neurotypical individuals using neuroimaging techniques. However, limited attention has been given to evaluating how variations in image acquisition protocols across different centers influence these observed differences. This analysis focuses on structural magnetic resonance imaging (sMRI) data from the Autism Brain Imaging Data Exchange I (ABIDE I) database, considering both subjects' condition and individual centers to identify disparities between ASC and control groups. Statistical analysis, employing permutation tests, utilizes two distinct statistical mapping methods: statistical agnostic mapping (SAM) and…
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Taxonomy
TopicsAutism Spectrum Disorder Research · Functional Brain Connectivity Studies · Fetal and Pediatric Neurological Disorders
