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Although autism spectrum disorder (ASD) is a serious lifelong condition, its underlying neural mechanism remains unclear. Recently, neuroimaging-based classifiers for ASD and typically developed (TD) individuals were developed to identify the abnormality of functional connections (FCs). Due to over-fitting and

Although autism spectrum disorder (ASD) is a serious lifelong condition, its underlying neural mechanism remains unclear. Recently, neuroimaging-based classifiers for ASD and typically developed (TD) individuals were developed to identify the abnormality of functional connections (FCs). Due to over-fitting and interferential effects of varying measurement conditions and demographic distributions, no classifiers have been strictly validated for independent cohorts. Here we overcome these difficulties by developing a novel machine-learning algorithm that identifies a small number of FCs that separates ASD versus TD. The classifier achieves high accuracy for a Japanese discovery cohort and demonstrates a remarkable degree of generalization for two independent validation cohorts in the USA and Japan. The developed ASD classifier does not distinguish individuals with major depressive disorder and attention-deficit hyperactivity disorder from their controls but moderately distinguishes patients with schizophrenia from their controls. The results leave open the viable possibility of exploring neuroimaging-based dimensions quantifying the multiple-disorder spectrum.

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    Title
    • A Small Number of Abnormal Brain Connections Predicts Adult Autism Spectrum Disorder
    Date Created
    2016-04-14
    Resource Type
  • Text
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    Identifier
    • Digital object identifier: 10.1038/ncomms11254
    • Identifier Type
      International standard serial number
      Identifier Value
      2041-1723
    Note
    • The final version of this article, as published in Nature Communications, can be viewed online at: https://www.nature.com/articles/ncomms11254

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    This is a suggested citation. Consult the appropriate style guide for specific citation guidelines.

    Yahata, N., Morimoto, J., Hashimoto, R., Lisi, G., Shibata, K., Kawakubo, Y., . . . Kawato, M. (2016). A small number of abnormal brain connections predicts adult autism spectrum disorder. Nature Communications, 7, 11254. doi:10.1038/ncomms11254

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