Reduced higher-dimensional resting state fMRI dynamism in clinical high-risk individuals for schizophrenia identified by meta-state analysis

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Eva Mennigen - , Department of Psychiatry and Psychotherapy, Lovelace Biomedical Research Institute, University of California at Irvine (Author)
  • Robyn L. Miller - , Lovelace Biomedical Research Institute (Author)
  • Barnaly Rashid - , Lovelace Biomedical Research Institute (Author)
  • Susanna L. Fryer - , University of California at Irvine, Department of Veterans Affairs (Author)
  • Rachel L. Loewy - , University of California at Irvine (Author)
  • Barbara K. Stuart - , University of California at Irvine (Author)
  • Daniel H. Mathalon - , University of California at Irvine, Department of Veterans Affairs (Author)
  • Vince D. Calhoun - , Lovelace Biomedical Research Institute, Eastern New Mexico University (Author)

Abstract

New techniques to investigate functional network connectivity in resting state functional magnetic resonance imaging data have recently emerged. One novel approach, called meta-state analysis, goes beyond the mere cross-correlation of time courses of distinct brain areas and explores temporal dynamisminmore detail, allowing for connectivity states to overlap in time and capturing global dynamic behavior. Previous studies have shown that patients with chronic schizophrenia exhibit reduced neural dynamism compared to healthy controls, but it is not known whether these alterations extend to earlier phases of the illness. In this study, we analyzed individuals at clinical high-risk (CHR, n = 53) for developing psychosis, patients in an early stage of schizophrenia (ESZ, n= 58), and healthy controls (HC, n = 70). ESZ individuals exhibit reduced neural dynamismacross all domains compared to HC. CHR individuals also show reduced neural dynamism but only in 2 out of 4 domains investigated. Overall, meta-state analysis adds information about dynamic fluidity of functional connectivity. (C) 2018 Elsevier B.V. All rights reserved.

Details

Original languageEnglish
Pages (from-to)217-223
Number of pages7
JournalSchizophrenia research
Volume201
Publication statusPublished - Nov 2018
Peer-reviewedYes

External IDs

PubMed 29907493
Scopus 85048338313
ORCID /0000-0001-5099-0274/work/142249096

Keywords

Keywords

  • Functional connectivity, Group independent component analysis, Meta-state analysis, Psychosis risk, Resting-state fMRI