期刊
BIOLOGICAL PSYCHIATRY
卷 93, 期 2, 页码 167-177出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.biopsych.2022.06.013
关键词
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This study conducted an image-based meta-analysis of functional magnetic resonance imaging studies and found no significant differences in brain activation patterns between individuals at risk of schizophrenia and healthy control subjects in response to negative emotional stimuli.
BACKGROUND: Impaired emotion processing constitutes a key dimension of schizophrenia and a possible endophenotype of this illness. Empirical studies consistently report poorer emotion recognition performance in patients with schizophrenia as well as in individuals at enhanced risk of schizophrenia. Functional magnetic resonance imaging studies also report consistent patterns of abnormal brain activation in response to emotional stimuli in patients, in particular, decreased amygdala activation. In contrast, brain-level abnormalities in at-risk individuals are more elusive. We address this gap using an image-based meta-analysis of the functional magnetic resonance imaging literature. METHODS: Functional magnetic resonance imaging studies investigating brain responses to negative emotional stimuli and reporting a comparison between at-risk individuals and healthy control subjects were identified. Frequentist and Bayesian voxelwise meta-analyses were performed separately, by implementing a random-effect model with unthresholded group-level T-maps from individual studies as input. RESULTS: In total, 17 studies with a cumulative total of 677 at-risk individuals and 805 healthy control subjects were included. Frequentist analyses did not reveal significant differences between at-risk individuals and healthy control subjects. Similar results were observed with Bayesian analyses, which provided strong evidence for the absence of meaningful brain activation differences across the entire brain. Region of interest analyses specifically focusing on the amygdala confirmed the lack of group differences in this region. CONCLUSIONS: These results suggest that brain activation patterns
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