Transient Patterns of Functional Dysconnectivity in Clinical High Risk and Early Illness Schizophrenia Individuals Compared with Healthy Controls

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

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

Abstract

Schizophrenia shows abnormal dynamic functional network connectivity (dFNC), but it is unclear whether these abnormalities are present early in the illness course or precede illness onset in individuals at clinical high risk (CHR) for psychosis. We examined dFNC from resting-state functional magnetic resonance imaging data in CHR (n = 53), early illness schizophrenia (ESZ; n = 58), and healthy control (HC; n = 70) individuals. We applied a sliding temporal window approach capturing five distinct dFNC states. In ESZ patients, the likelihood of transitioning from state 4, a state that exhibited greater cortical-subcortical hyperconnectivity and also lacked typically observed anticorrelation between the default mode network and other functional networks, to a hypoconnected state was increased compared with HC and CHR groups. Furthermore, we investigated the interaction of group and state on dFNC. Overall, HC individuals showed significant changes of connectivity between states that were absent or altered in ESZ patients and CHR individuals. Connectivity differences between groups were identified primarily in two out of the five states, in particular, between HC and ESZ groups. In summary, it appears that the interaction effect was mostly driven by (1) dynamic connectivity changes in HC that were abnormal in CHR and ESZ individuals and (2) the fact that dysconnectivity between groups was only present in some states. These findings underscore the likelihood that abnormalities are present not only in static FNC but also in dFNC, in individuals at CHR for schizophrenia.

Details

Original languageEnglish
Pages (from-to)60-76
Number of pages17
JournalBrain connectivity
Volume9
Issue number1
Publication statusPublished - Feb 2019
Peer-reviewedYes

External IDs

PubMed 29855202
Scopus 85061982607
ORCID /0000-0001-5099-0274/work/142249098

Keywords

Keywords

  • Clinical high risk, Dysconnectivity, Independent component analysis, Schizophrenia