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• W4308452476 abstract "It is widely accepted that there are some common network patterns in the human brain. However, the existence of stable and strong functional connections in the human brain and whether they change in schizophrenia is still a question. By setting 1% connections with the smallest coefficient of variation, we found a widespread brain functional network (frame network) in healthy people(n = 380, two datasets from public databases). We then explored the alterations in a medicated group (60 subjects with schizophrenia vs 71 matched controls) and a drug-naive first-episode group (68 subjects with schizophrenia vs 45 matched controls). A linear support vector classifier (SVC) was constructed to distinguish patients and controls using the medicated patients' frame network. We found most frame connections of healthy people had high strength, which were symmetrical and connected the left and right hemispheres. Conversely, significant differences in frame connections were observed in both patient groups, which were positively correlated with negative symptoms (mainly language dysfunction). Additionally, patients' frame network were more left-lateralized, concentrating on the left frontal lobe, and was quite accurate at distinguishing medicated patients from controls (classifier accuracy was 78.63%, sensitivity was 86.67%, specificity was 76.06%, and the area under the curve (AUC) was 0.83). Furthermore, the results were repeated in the drug-naive set (accuracy was 84.96%, sensitivity was 85.29%, specificity was 88.89%, and AUC was 0.93). These findings indicate that the abnormal pattern of frame network in subjects with schizophrenia might provide new insights into the dysconnectivity in schizophrenia." @default.
• W4308452476 created "2022-11-12" @default.
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• W4308452476 date "2022-11-04" @default.
• W4308452476 modified "2023-10-06" @default.
• W4308452476 title "Alteration of a brain network with stable and strong functional connections in subjects with schizophrenia" @default.
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• W4308452476 doi "https://doi.org/10.1038/s41537-022-00305-0" @default.
• W4308452476 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36333328" @default.
• W4308452476 hasPublicationYear "2022" @default.
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