Abstract
Although emerging evidence suggests that altered functional connectivity (FC) of large-scale neural networks is associated with disturbances in individuals at high-risk for psychosis, the findings are still far to be conclusive. We conducted a meta-analysis of seed-based resting-state functional magnetic resonance imaging studies that compared individuals at clinical high-risk for psychosis (CHR), first-degree relatives of patients with schizophrenia, or subjects who reported psychotic-like experiences with healthy controls. Twenty-nine studies met the inclusion criteria. The MetaNSUE method was used to analyze connectivity comparisons and symptom correlations. Our results showed a significant hypo-connectivity within the salience network (p = 0.012, uncorrected) in the sample of CHR individuals (n = 810). Additionally, we found a positive correlation between negative symptom severity and FC between the default mode network and both the salience network (p < 0.001, r = 0.298) and the central executive network (p = 0.003, r = 0.23) in the CHR group. This meta-analysis lends support for the hypothesis that large-scale network dysfunctions represent a core neural deficit underlying psychosis development.
Originalsprache | Englisch |
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Zeitschrift | Neuroscience and Biobehavioral Reviews |
Jahrgang | 128 |
Seiten (von - bis) | 90-101 |
Seitenumfang | 12 |
ISSN | 0149-7634 |
DOIs | |
Publikationsstatus | Veröffentlicht - 09.2021 |
Strategische Forschungsbereiche und Zentren
- Forschungsschwerpunkt: Gehirn, Hormone, Verhalten - Center for Brain, Behavior and Metabolism (CBBM)
DFG-Fachsystematik
- 2.23-04 Kognitive, systemische und Verhaltensneurobiologie
- 2.23-10 Klinische Psychiatrie, Psychotherapie und Kinder- und Jugendpsychiatrie
- 2.23-09 Biologische Psychiatrie