title: Multivariate searchlight classification of structural magnetic resonance imaging in children and adolescents with autism.
abstract: BACKGROUND
  Autism spectrum disorders (ASD) are neurodevelopmental disorders with a prevalence of nearly 1:100. Structural imaging studies point to disruptions in multiple brain areas, yet the precise neuroanatomical nature of these disruptions remains unclear. Characterization of brain structural differences in children with ASD is critical for development of biomarkers that may eventually be used to improve diagnosis and monitor response to treatment.
  
  
  METHODS
  We use voxel-based morphometry along with a novel multivariate pattern analysis approach and searchlight algorithm to classify structural magnetic resonance imaging data acquired from 24 children and adolescents with autism and 24 age-, gender-, and IQ-matched neurotypical participants.
  
  
  RESULTS
  Despite modest voxel-based morphometry differences, multivariate pattern analysis revealed that the groups could be distinguished with accuracies of approximately 90% based on gray matter in the posterior cingulate cortex, medial prefrontal cortex, and bilateral medial temporal lobes-regions within the default mode network. Abnormalities in the posterior cingulate cortex were associated with impaired Autism Diagnostic Interview communication scores. Gray matter in additional prefrontal, lateral temporal, and subcortical structures also discriminated between groups with accuracies between 81% and 90%. White matter in the inferior fronto-occipital and superior longitudinal fasciculi, and the genu and splenium of the corpus callosum, achieved up to 85% classification accuracy.
  
  
  CONCLUSIONS
  Multiple brain regions, including those belonging to the default mode network, exhibit aberrant structural organization in children with autism. Brain-based biomarkers derived from structural magnetic resonance imaging data may contribute to identification of the neuroanatomical basis of symptom heterogeneity and to the development of targeted early interventions.
authors: Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
authors: Lucina Q
authors: LQ
authors: Uddin
authors: Vinod
authors: V
authors: Menon
authors: Christina B
authors: CB
authors: Young
authors: Srikanth
authors: S
authors: Ryali
authors: Tianwen
authors: T
authors: Chen
authors: Amirah
authors: A
authors: Khouzam
authors: Nancy J
authors: NJ
authors: Minshew
authors: Antonio Y
authors: AY
authors: Hardan
mesh_terms: D000293:Adolescent; D001321:Autistic Disorder / Q000473:pathology*; D002648:Child; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000145:classification / Q000379:methods*; D008297:Male; D009483:Neuropsychological Tests; D011569:Psychiatric Status Rating Scales; D060388:Support Vector Machine