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Updated: Jun 3, 2025
Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
Published on: September 12, 2011
Identifying Distinct Developmental Patterns of Brain Complexity in Autism: A Cross-Sectional Cohort Analysis Using
I-Jou Chi1, Shih-Jen Tsai1,2, Chun-Houh Chen3
1Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Aim:
Autistic traits exhibit neurodiversity with varying behaviors across developmental stages. Brain complexity theory, illustrating the dynamics of neural activity, may elucidate the evolution of autistic traits over time. Our study explored the patterns of brain complexity in autistic individuals from childhood to adulthood.
Methods:
We analyzed functional magnetic resonance imaging data from 1087 autistic participants and neurotypical controls aged 6 to 30 years within the ABIDE I (Autism Brain Imaging Data Exchange) data set. Sample entropy was calculated to measure brain complexity among 90 brain regions, utilizing an automated anatomical labeling template for voxel parcellation. Participants were grouped using sliding age windows with partial overlaps. We assessed the average brain complexity of the entire brain and brain regions for both groups across age categories. Cluster analysis was conducted using generalized association plots to identify brain regions with similar developmental complexity trajectories. Finally, the relationship between brain region complexity and autistic traits was examined.
Results:
Autistic individuals may tend toward higher whole-brain complexity during adolescence and lower complexity during childhood and adulthood, indicating possible distinct developmental trajectories. However, these results do not remain after Bonferroni correction. Two clusters of brain regions were identified, each with unique patterns of complexity changes over time. Correlations between brain region complexity, age, and autistic traits were also identified.
Conclusion:
The study revealed brain complexity trajectories in autistic individuals, providing insight into the neurodiversity of autism and suggesting that age-related changes in brain complexity could be a potential neurodevelopmental marker for the dynamic nature of autism.
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