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Abstract #0890

A functional connectome-based interspecies model boosts classification in neuropsychiatric disorders

Yafeng Zhan1,2, Jianze Wei3, Jian Liang3, Ran He3, and Zheng Wang1,2,4

1Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, State Key laboratory of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai, China, 2University of Chinese Academy of Sciences, Beijing, China, 3Institute of Automation, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing, China, 4Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China, Kunming, China

Cross-species comparative connectomices based on resting-state functional MRI is a promising method to investigate large-scale brain organization. Here we leveraged a transgenic monkey model overexpressing MECP2 and developed a novel connectome-based interspecies machine learning algorithm for clinical diagnosis of individuals with neuropsychiatric disorders. This fully cross-validated algorithm based on cross-species mapping of regional features significantly boosts the diagnostic performance of ASD and OCD, but not for ADHD, in independent human cohorts, which paves a new avenue to establish a translational path to dissect the neural circuit mechanisms underlying complexity and heterogeneity of human mental disorders.

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