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Updated: Jan 10, 2026

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
Published on: September 12, 2011
Individualized cortical thickness asymmetry in autism spectrum disorder and schizophrenia
Marta Martín Echave1, Hugo G Schnack2,3, Covadonga M Díaz-Caneja1,4,5
1Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain.
Abstract:
Cortical thickness asymmetry has been proposed as a latent biomarker for autism spectrum disorder (ASD) and schizophrenia (SZ). However, the degree of abnormal asymmetry at the individual level in ASD and SZ remains unclear. To investigate this, we employed a normative modeling approach. Normative ranges for the whole brain and regional (160 cortical parcels) cortical thickness asymmetry index (AI) were established using a training set of healthy subjects (n = 4904, 45.15% male, age range: 6-95 years), controlling for age, sex, image quality, and scanner. We calculated z-scores to quantify individual deviations from the normative median in a test set consisting of healthy controls (HCtest, n = 526, 40% male), participants with ASD (n = 135, 83% male), and SZ (n = 287, 81% male). Regional deviance was assessed by counting the number of individuals with significant deviations below (infra-normal, z-score ≤ -1.96) or above (supra-normal, z-score ≥ 1.96) the normative median in each parcel. We also evaluated individual deviance by counting the number of regions with significant deviations for each participant. A multivariate approach was employed to determine whether regional deviance could separate the three groups. There were no differences for deviance of whole brain AI between any of the groups. Distributions of individual deviances overlapped across all 160 regions, with one superior temporal region in which SZ individuals showed a higher proportion of supra-normal AI values compared to HCtest (HCtest = 1.14%, SZ = 5.92%, χ2 = 15.45, PFDR < 0.05, ω = 0.14). The SZ group had a higher average number of regions with significant deviations than HCtest (infra-normal: z = 4.21, p < 0.01; supra-normal: z = 4.33, p < 0.01) but this group difference had limited predictive diagnostic accuracy at the individual level (Area Under the Curve≅60%). The multivariate analysis showed no association between regional deviance and diagnosis. Results were consistent when using a different parcellation, alternative asymmetry calculations, analysis restricted to males, and after controlling for handedness and IQ. Normative modelling revealed little to no evidence of atypical individualized cortical thickness asymmetry in ASD and SZ. The results of this study challenge the utility of cortical thickness asymmetry as a biomarker for ASD and SZ.
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