ArticleSchizophrenia (Heidelberg, Germany)2022
Alteration of a brain network with stable and strong functional connections in subjects with schizophrenia.
Article in Schizophrenia (Heidelberg, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- A frame network study of first-episode schizophrenia, ultra-high risk, and healthy populations.Schizophrenia (Heidelberg, Germany) · 2025Article
- Investigating Connectivity Gradients in Schizophrenia: Integrating Functional, Structural, and Genetic Perspectives.Brain sciences · 2025Article
- Functional Connectivity-Based Searchlight Multivariate Pattern Analysis for Discriminating Schizophrenia Patients and Predicting Clinical Variables.Schizophrenia bulletin · 2024Article
- Abnormal Dynamic Reconstruction of Overlapping Communities in Schizophrenia Patients.Brain sciences · 2024Article
- Review of the Brain's Behaviour after Injury and Disease for Its Application in an Agent-Based Model (ABM).Biomimetics (Basel, Switzerland) · 2024Review
- Altered brain network organization in adults with Asperger's syndrome: decreased connectome transitivity and assortativity with increased global efficiency.Frontiers in psychiatry · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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