Reproducible coactivation patterns of functional brain networks reveal the aberrant dynamic state transition in schizophrenia
Hang Yang,
Hong Zhang,
Xin Di,
Shuai Wang,
Chun Meng,
Lin Tian,
Bharat Biswal
Affiliations
Hang Yang
The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
Hong Zhang
The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
Xin Di
The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, United States
Shuai Wang
Department of Psychiatry, The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi 214151, China
Chun Meng
The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; Corresponding author at: The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 2006, Xiyuan Avenue, Chengdu 611731, China.
Lin Tian
Department of Psychiatry, The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi 214151, China; Corresponding author at: Department of Psychiatry, The Affiliated Wuxi Mental Health Center of Nanjing Medical University, No. 156 Qianhu Road, Binhu District, Wuxi 214151, China.
Bharat Biswal
The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, United States; Corresponding author at: 607 Fenster Hall, University Height, Newark, NJ 07102, United States.
It is well documented that massive dynamic information is contained in the resting-state fMRI. Recent studies have identified recurring states dominated by similar coactivation patterns (CAPs) and revealed their temporal dynamics. However, the reproducibility and generalizability of the CAP analysis are unclear. To address this question, the effects of methodological pipelines on CAP are comprehensively evaluated in this study, including the preprocessing, network construction, cluster number and three independent cohorts. The CAP state dynamics are characterized by the fraction of time, persistence, counts, and transition probability. Results demonstrate six reliable CAP states and their dynamic characteristics are also reproducible. The state transition probability is found to be positively associated with the spatial similarity. Furthermore, the aberrant CAP states in schizophrenia have been investigated by using the reproducible method on three cohorts. Schizophrenia patients spend less time in CAP states that involve the fronto-parietal network, but more time in CAP states that involve the default mode and salience network. The aberrant dynamic characteristics of CAP states are correlated with the symptom severity. These results reveal the reproducibility and generalizability of the CAP analysis, which can provide novel insights into the neuropathological mechanism associated with aberrant brain network dynamics of schizophrenia.
