Dynamic functional connectivity impairments in early schizophrenia and clinical high-risk for psychosis

Publikation: Beitrag in FachzeitschriftÜbersichtsartikel (Review)BeigetragenBegutachtung

Beitragende

  • Yuhui Du - , Lovelace Biomedical Research Institute, Shanxi University (Autor:in)
  • Susanna L. Fryer - , University of California at Irvine (Autor:in)
  • Zening Fu - , Lovelace Biomedical Research Institute (Autor:in)
  • Dongdong Lin - , Lovelace Biomedical Research Institute (Autor:in)
  • Jing Sui - , Lovelace Biomedical Research Institute, University of Chinese Academy of Sciences (Autor:in)
  • Jiayu Chen - , Lovelace Biomedical Research Institute (Autor:in)
  • Eswar Damaraju - , Lovelace Biomedical Research Institute (Autor:in)
  • Eva Mennigen - , Klinik und Poliklinik für Psychiatrie und Psychotherapie, Lovelace Biomedical Research Institute, Eastern New Mexico University, University of Maribor (Autor:in)
  • Barbara Stuart - , University of California at Irvine (Autor:in)
  • Rachel L. Loewy - , University of California at Irvine (Autor:in)
  • Daniel H. Mathalon - , University of California at Irvine (Autor:in)
  • Vince D. Calhoun - , Lovelace Biomedical Research Institute, Eastern New Mexico University (Autor:in)

Abstract

Individuals at clinical high-risk (CHR) for psychosis are characterized by attenuated psychotic symptoms. Only a minority of CHR individuals convert to full-blown psychosis. Therefore, there is a strong interest in identifying neurobiological abnormalities underlying the psychosis risk syndrome. Dynamic functional connectivity (DFC) captures time-varying connectivity over short time scales, and has the potential to reveal complex brain functional organization. Based on resting-state functional magnetic resonance imaging (fMRI) data from 70 healthy controls (HCs), 53 CHR individuals, and 58 early illness schizophrenia (ESZ) patients, we applied a novel group information guided ICA (GIG-ICA) to estimate inherent connectivity states from DFC, and then investigated group differences. We found that ESZ patients showed more aberrant connectivities and greater alterations than CHR individuals. Results also suggested that disease-related connectivity states occurred in CHR and ESZ groups. Regarding the dominant state with the highest contribution to dynamic connectivity, ESZ patients exhibited greater impairments than CHR individuals primarily in the cerebellum, frontal cortex, thalamus and temporal cortex, while CHR and ESZ populations shared common aberrances mainly in the supplementary motor area, parahippocampal gyrus and postcentral cortex. CHR-specific changes were also found in the connections between the superior frontal gyrus and calcarine cortex in the dominant state. Our findings suggest that CHR individuals generally show an intermediate functional connectivity pattern between HCs and SZ patients but also have unique connectivity alterations.

Details

OriginalspracheEnglisch
Seiten (von - bis)632-645
Seitenumfang14
FachzeitschriftNeuroImage
Jahrgang180
PublikationsstatusVeröffentlicht - 15 Okt. 2018
Peer-Review-StatusJa

Externe IDs

PubMed 29038030
Scopus 85032821048
ORCID /0000-0001-5099-0274/work/142249095

Schlagworte

Schlagwörter

  • Clinical high-risk, Connectivity state, Dynamic functional connectivity, Ica, Schizophrenia, fMRI