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.
Key Words
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Article info
Publication history
Published online: September 05, 2011
Accepted:
July 12,
2011
Received in revised form:
July 11,
2011
Received:
March 11,
2011
Identification
Copyright
© 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
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- ErratumBiological PsychiatryVol. 70Issue 11
- PreviewErrors have been discovered in “Multivariate Searchlight Classification of Structural Magnetic Resonance Imaging in Children and Adolescents with Autism ” by Uddin et al., published in Biological Psychiatry (2011;70:833–841). These errors largely relate to the reported statistics of the support vector machine relationship with symptom severity, and require correction to Figure 3, Table 3, and the related results and discussion text. These are secondary results that do not otherwise affect the main focus of the paper.
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