Diagnosis of Autism Spectrum Disorders Using Multi-Level High-Order Functional Networks Derived From Resting-State Functional MRI

Feng Zhao, Han Zhang, Islem Rekik, Zhiyong An, Dinggang Shen

    Research output: Contribution to journalArticlepeer-review

    78 Citations (Scopus)

    Abstract

    Functional brain networks derived from resting-state functional magnetic resonance imaging (rs-fMRI) have been widely used for Autism Spectrum Disorder (ASD) diagnosis. Typically, these networks are constructed by calculating functional connectivity (FC) between any pair of brain regions of interest (ROIs), i.e., using Pearson's correlation between rs-fMRI time series. However, this can only be called as a low-order representation of the functional interaction, because the relationship is investigated just between two ROIs. Brain disorders might not only affect low-order FC, but also high-order FC, i.e., the higher-level relationship among multiple brain regions, which might be more crucial for diagnosis. To comprehensively characterize such relationship for better diagnosis of ASD, we propose a multi-level, high-order FC network representation that can nicely capture complex interactions among brain regions. Then, we design a feature selection method to identify those discriminative multi-level, high-order FC features for ASD diagnosis. Finally, we design an ensemble classifier with multiple linear SVMs, each trained on a specific level of FC networks, for boosting the final classification accuracy. Experimental results show that the integration of both low-order and first-level high-order FC networks achieves the best ASD diagnostic accuracy (81%). We further investigated those selected discriminative low-order and high-order FC features and found that the high-order FC features can provide complementary information to the low-order FC features in the ASD diagnosis.

    Original languageEnglish
    Article number184
    JournalFrontiers in Human Neuroscience
    Volume12
    DOIs
    Publication statusPublished - 2018 May 14

    Bibliographical note

    Publisher Copyright:
    © 2018 Zhao, Zhang, Rekik, An and Shen.

    Keywords

    • Autism spectrum disorder
    • Brain network
    • High-order functional connectivity
    • Learning-based classification
    • Resting-state fMRI

    ASJC Scopus subject areas

    • Neuropsychology and Physiological Psychology
    • Neurology
    • Psychiatry and Mental health
    • Biological Psychiatry
    • Behavioral Neuroscience

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