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Errors 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.
Table 3Spearman Correlation Coefficients Between Diagnostic Criteria and Distance from Hyperplane
On page 834, under Participants, the corrected second sentence of paragraph two is: “Specific ADOS and ADI-R scores were unavailable for three participants because of accidental loss of primary data following confirmation of eligibility for the study.”
On page 836, the paragraph under Relationship Between SVM and Symptom Severity is now updated to reflect the corrected statistic: “We were interested in testing for relationships between GM in the DMN and autism symptom severity. Table 3 and Figure 3 show the relation between the scores on the diagnostic instruments (ADI-R and ADOS subscale scores) and GM in key DMN regions. This analysis revealed that subjects with the most severe autism as indexed by ADI-R communication subscale scores are better discriminators between groups on the basis of GM in the PCC region than subjects with less severe symptomatology (r = .533, p < .01). In other words, the most severely affected subjects are located farthest away from the hyperplane separating the two groups in the multivariate classification analysis. This relationship was marginally significant after Bonferroni corrections for multiple comparisons (for each region of interest individually). In addition, those with the most severe autism as indexed by the repetitive behavior (r = .450, p < .05) subscale of the ADI-R are better discriminators between groups on the basis of GM in the MPFC region than subjects with less severe symptomatology. However, Bonferroni correction renders this correlation insignificant.”
The first three sentences of paragraph two, on page 837 of the Discussion, now reflect this adjustment: “This study found that the PCC not only produced the highest classification accuracy, but an individual subject's distance from the hyperplane separating the two groups in the classification analysis were also weakly correlated with ADI-R scores. Specifically, children with the most elevated communication symptom score on the ADI-R (indicating the most severe deficits) were located farthest away from the hyperplane separating the autism and TD groups. These preliminary exploratory findings indicate that our classification analyses are sensitive not only in distinguishing between autism and TD groups but also may be useful in relating symptom severity with multivoxel brain measures.”
The corrected versions of Table 3, which appears on page 838, and Figure 3 and its associated legend, which appears on page 839, are printed below.
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.