BACKGROUND Although neuroimaging research has identified atypical neuroanatomical substrates in individuals with autism spectrum disorder (ASD), it is at present unclear whether and to what extent disorder-selective gray matter (GM) alterations occur in this spectrum of conditions. In fact, a growing body of evidence shows a substantial overlap between the pathomorphological changes across different brain diseases, which may complicate identification of reliable neural markers and differentiation of the anatomical substrates of distinct psychopathologies. METHODS Using a novel data-driven and Bayesian methodology with published voxel-based morphometry data (849 peer-reviewed experiments and 22,304 clinical subjects), this study performs the first reverse inference investigation to explore the selective structural brain alteration profile of ASD. RESULTS We found that specific brain areas exhibit a > 90% probability of GM alteration selectivity for ASD: the bilateral precuneus (BAs 7), right inferior occipital gyrus (BA 18), left cerebellar lobule IX and Crus II, right cerebellar lobule VIIIA, and right Crus I. Of note, many brain voxels that are selective for ASD include areas that are posterior components of the default mode network. CONCLUSIONS The identification of these spatial GM alteration patterns offers new insights into understanding the complex neurobiological underpinnings of ASD, and opens attractive prospects for future neuroimaging-based interventions.

Revealing the Selectivity of Neuroanatomical Alteration in Autism Spectrum Disorder via Reverse Inference

Donato Liloia;Franco Cauda;Jordi Manuello
;
Lorenzo Mancuso;Tommaso Costa
Last
2023-01-01

Abstract

BACKGROUND Although neuroimaging research has identified atypical neuroanatomical substrates in individuals with autism spectrum disorder (ASD), it is at present unclear whether and to what extent disorder-selective gray matter (GM) alterations occur in this spectrum of conditions. In fact, a growing body of evidence shows a substantial overlap between the pathomorphological changes across different brain diseases, which may complicate identification of reliable neural markers and differentiation of the anatomical substrates of distinct psychopathologies. METHODS Using a novel data-driven and Bayesian methodology with published voxel-based morphometry data (849 peer-reviewed experiments and 22,304 clinical subjects), this study performs the first reverse inference investigation to explore the selective structural brain alteration profile of ASD. RESULTS We found that specific brain areas exhibit a > 90% probability of GM alteration selectivity for ASD: the bilateral precuneus (BAs 7), right inferior occipital gyrus (BA 18), left cerebellar lobule IX and Crus II, right cerebellar lobule VIIIA, and right Crus I. Of note, many brain voxels that are selective for ASD include areas that are posterior components of the default mode network. CONCLUSIONS The identification of these spatial GM alteration patterns offers new insights into understanding the complex neurobiological underpinnings of ASD, and opens attractive prospects for future neuroimaging-based interventions.
2023
8
11
1075
1083
Bayes factor modeling activation likelihood estimation structural MRI forward inference medial frontoparietal network cerebellum
Donato Liloia, Franco Cauda, Lucina Q. Uddin, Jordi Manuello, Lorenzo Mancuso, Roberto Keller, Andrea Nani, Tommaso Costa
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1844651
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