Abstract
The role of network metrics in exploring brain networks of mental illness is crucial. This study focuses on quantifying a node controllability index (CA-scores) and developing a novel framework for studying the dysfunction of attention deficit hyperactivity disorder (ADHD) brains. By analyzing fMRI data from 143 healthy controls and 102 ADHD patients, the controllability metric reveals distinct differences in nodes (brain regions) and subsystems (functional modules). There are significantly atypical CA-scores in the Rolandic operculum, superior medial orbitofrontal cortex, insula, posterior cingulate gyrus, supramarginal gyrus, angular gyrus, precuneus, heschl gyrus, and superior temporal gyrus of ADHD patients. A comparison with measures of connection strength, eigenvector centrality, and topology entropy suggests that the controllability index may be more effective in identifying abnormal regions in ADHD brains. Furthermore, our controllability index could be extended to investigate functional networks associated with other psychiatric disorders.
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Availability of data and materials
The datasets of the current study are available at http://fcon_1000.projects.nitrc.org/indi/adhd200/index.html.
Code availability
The MATLAB code here is available from the corresponding author, Dr. Weigang Sun, upon reasonable request.
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This work was supported by Guangxi Key Laboratory of Trusted Software (No. KX202309).
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B.C., W.S. and C.Y. contributed to the conception and design of the study. B.C. and W.S. performed the numerical results. B.C., W.S. and C.Y. wrote the manuscript.
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Chen, B., Sun, W. & Yan, C. Controllability in attention deficit hyperactivity disorder brains. Cogn Neurodyn (2024). https://doi.org/10.1007/s11571-023-10063-z
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DOI: https://doi.org/10.1007/s11571-023-10063-z