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Unique Amygdala Signatures and Shared Prefrontal Deficits in Autism: Mapping Social Heterogeneity via Naturalistic functional Magnetic Resonance Imaging

Di, X.; Xu, T.; Castellanos, F. X.; Biswal, B. B.

2026-02-27 neuroscience
10.64898/2026.02.26.708280 bioRxiv
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BackgroundNaturalistic fMRI provides an ecologically valid window into social brain function, yet binary diagnostic labels may obscure neural signatures linked to the continuous spectrum of social deficits. We investigated whether social brain alterations in autism spectrum disorder (ASD) follow a categorical, dimensional, or "dual-track" architecture. MethodsWe analyzed fMRI data from 428 youth (262 ASD, 166 typically developing; ages 5-22) watching two films: The Present and Despicable Me. Using Principal Component Analysis (PCA) to quantify primary (PC1) and secondary (PC2) synchronization, we employed variance partitioning to disentangle the contributions of categorical diagnosis from continuous symptom severity (Social Responsiveness Scale-2, SRS-2). ResultsDuring The Present, reduced synchronization was widespread. In social-motivational hubs (medial prefrontal cortex, caudate), reductions were largely explained by variance shared between diagnosis and SRS-2 scores. In contrast, the left amygdala exhibited a unique dimensional association with SRS-2 scores independent of categorical diagnosis. Secondary response patterns (PC2), reflecting complex temporal integration, revealed further unique dimensional effects in the cuneus. Notably, these signatures were stimulus-dependent, manifesting during the emotionally complex narrative of The Present but not during the slapstick-oriented Despicable Me. ConclusionsWhile core social-motivational hubs reflect overlapping diagnostic and dimensional deficits, the amygdala and secondary visual patterns provide distinct, dimension-specific signatures of social impairment. This variance partitioning approach supports a Research Domain Criteria (RDoC) framework, highlighting the necessity of integrating dimensional assessments and narrative complexity to characterize the neural architecture of autism.

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