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Updated: Jan 7, 2026

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
Published on: September 12, 2011
Brain morphological changes in autism spectrum disorder related to multiple behavioral spectrums: a behavioral-causal
Tianzheng Zhong1, Feng Wang1, Jianfeng Qiu2
1Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, No. 366 Taishan Street, Taian, China.
Background:
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by heterogeneities in behavioral symptoms and gray matter (GM) volume changes across the brain. However, progressive and causal GM volume changes and their associations with behavioral symptoms remain unclear. Our study aimed to explore the heterogeneity of causal GM volume changes in individuals with ASD across behavioral spectrums.
Methods:
Brain structural imaging and clinical data of 131 autistic individuals and 246 neurotypical individuals (NTs) were included, and were clustered into neuroanatomical subtypes. A novel behavioral-causal structural covariance network (BCaSCN) analysis approach was developed. GM volume maps from each ASD subtype were sequenced according to the social responsiveness scale (SRS) value and values from each behavioral domain of SRS, generating pseudo-time series data with disease progression. We performed BCaSCN analysis on the pseudo-time series data to explore the causal relationship of the GM volume changes across behavior spectrums among ASD subtypes.
Results:
Two neurosubtypes of ASD with distinct GM volume alterations were observed. CaSCN analysis revealed heterogeneity in causal GM volume alterations between the two ASD neurostypes. Furthermore, BCaSCN analysis across behavior spectrums demonstrated that subtype 1 exhibited higher overall out- and in-degree GC values in the cognition domain, whereas subtype 2 displayed higher overall out- and in-degree GC values in the domain of motivation, mannerism and communication.
Limitation:
CaSCN and BCaSCN applied pseudo time-series data rather than real time-series data, longitudinal data are needed to validate the results of this study in the future. Therefore, the results should be interpreted with caution.
Conclusions:
These findings suggest that ASD subtypes are associated with heterogeneous causal GM volume changes, which may be related to distinct behavioral domains.
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