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

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Article number118193
JournalNeuroImage
Volume237
DOIs
StatePublished - Aug 15 2021

All Science Journal Classification (ASJC) codes

  • Neurology
  • Cognitive Neuroscience

Keywords

  • Coactivation patterns
  • Dynamics
  • Reproducibility
  • Schizophrenia
  • Triple-network

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