Analysis of Abnormal Brain Networks in Autism Based on fMRI
DOI:
https://doi.org/10.54097/kpk5n732Keywords:
Autism Spectrum Disorder, Functional Brain Networks, Network Analysis, Graph-theoretical Analysis, Topological StructureAbstract
Autism spectrum disorder (ASD) is characterized by widespread neurodevelopmental impairments, with emotional and behavioral deficits linked to abnormal local brain function and functional connectivity. Investigating whether the intrinsic functional brain network topology in ASD is altered is therefore of critical diagnostic importance. To identify aberrant brain networks in ASD, this study constructed functional networks based on 90 brain regions defined by an automated anatomical atlas, followed by network-based statistics (NBS) and graph-theoretical analyses. The findings were further validated using support vector machine (SVM) classification between ASD and neurotypical participants. NBS revealed that abnormalities in functional connectivity in ASD were predominantly located within the default mode and sensorimotor networks, involving regions in the temporal and frontal lobes, basal ganglia, and parts of the limbic system. Graph-theoretical analysis further indicated that topological alterations in ASD likely stem from dysregulated connectivity within these subnetworks, demonstrating significantly impaired efficiency in both information transfer and integration compared to controls—a finding potentially linked to characteristic ASD behavioral profiles. Using these aberrant connections as biological features, a systematic evaluation of multiple classifiers identified SVM as optimal. Through cross-validation and parameter tuning, classification achieved an accuracy of 84.86% on the NYU dataset. To further validate the generalizability of the identified network features, corresponding functional connections were extracted from the larger UM dataset (sample size >80), yielding a classification accuracy of 72.64%, confirming the clinical relevance of the detected network abnormalities. These results highlight abnormal topological organization in functional brain networks in ASD and provide novel insights into the neural mechanisms underlying communication deficits and repetitive behaviors in autism.
Downloads
References
[1] Wing L. The autistic spectrum. 1997, 350: 1761-1766. DOI: https://doi.org/10.1016/S0140-6736(97)09218-0
[2] Segal D L. Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR). The Corsini Encyclopedia of Psychology. 1-3.
[3] Daniel K L, Prue C, Taylor M K, et al. 'Learn the signs. Act early': a campaign to help every child reach his or her full potential. Public health, 2009, 123 Suppl 1: 11-16. DOI: https://doi.org/10.1016/j.puhe.2009.06.002
[4] Briggs R D, Stettler E M, Silver E J, et al. Social-emotional screening for infants and toddlers in primary care. Pediatrics, 2012, 129(2): 377-384. DOI: https://doi.org/10.1542/peds.2010-2211
[5] Weitzman C, Wegner L. Promoting optimal development: screening for behavioral and emotional problems. Pediatrics, 2015, 135(2): 384-395. DOI: https://doi.org/10.1542/peds.2015-0904
[6] Gabrielsen T P, Farley M, Speer L, et al. Identifying autism in a brief observation. Pediatrics, 2015, 135(2): 330-338. DOI: https://doi.org/10.1542/peds.2014-1428
[7] Barger B, Rice C, Wolf R, et al. Better together: Developmental screening and monitoring best identify children who need early intervention. Disability and health journal, 2018, 11(3): 420-426. DOI: https://doi.org/10.1016/j.dhjo.2018.01.002
[8] Lee H, Marvin A R, Watson T, et al. Accuracy of phenotyping of autistic children based on Internet implemented parent report. American journal of medical genetics Part B, Neuropsychiatric genetics: the official publication of the International Society of Psychiatric Genetics, 2010, 153b (6): 1119-1126. DOI: https://doi.org/10.1002/ajmg.b.31103
[9] Nagai Y, Kirino E, Tanaka S, et al. Functional connectivity in autism spectrum disorder evaluated using rs-fMRI and DKI. CEREBRAL CORTEX, 2023. DOI: https://doi.org/10.1093/cercor/bhad451
[10] Yan C G, Cheung B, Kelly C, et al. A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics. NeuroImage, 2013, 76: 183-201. DOI: https://doi.org/10.1016/j.neuroimage.2013.03.004
[11] Dawson G, Rogers S, Munson J, et al. Randomized, controlled trial of an intervention for toddlers with autism: the Early Start Denver Model. Pediatrics, 2010, 125(1): 17-23. DOI: https://doi.org/10.1542/peds.2009-0958
[12] Tzourio-Mazoyer N, Landeau B, Papathanassiou D, et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage, 2002, 15(1): 273-289. DOI: https://doi.org/10.1006/nimg.2001.0978
[13] Zalesky A, Fornito A, Bullmore E T. Network-based statistic: identifying differences in brain networks. NeuroImage, 2010, 53(4): 1197-1207. DOI: https://doi.org/10.1016/j.neuroimage.2010.06.041
[14] Pinto-Martin J A, Young L M, Mandell D S, et al. Screening strategies for autism spectrum disorders in pediatric primary care. Journal of developmental and behavioral pediatrics: JDBP, 2008, 29(5): 345-350. DOI: https://doi.org/10.1097/DBP.0b013e31818914cf
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Frontiers in Computing and Intelligent Systems

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

