4.6 Article

Altered Dynamic Functional Connectivity of Cuneus in Schizophrenia Patients: A Resting-State fMRI Study

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APPLIED SCIENCES-BASEL
卷 11, 期 23, 页码 -

出版社

MDPI
DOI: 10.3390/app112311392

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schizophrenia; static functional connectivity; dynamic functional connectivity; sliding window; cuneus; variability; mean strength; standard deviation; rsFMRI; COBRE

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This study investigated dynamic functional connectivity in the cuneus between SZ patients and healthy controls based on rsfMRI data from the COBRE dataset. The results showed decreased mean strength connectivity between the cuneus and certain brain regions in SZ patients, suggesting that dynamic functional connectivity analysis could reveal patterns not evident in static functional connectivity, providing important insights into schizophrenia.
Objective: Schizophrenia (SZ) is a functional mental condition that has a significant impact on patients' social lives. As a result, accurate diagnosis of SZ has attracted researchers' interest. Based on previous research, resting-state functional magnetic resonance imaging (rsfMRI) reported neural alterations in SZ. In this study, we attempted to investigate if dynamic functional connectivity (dFC) could reveal changes in temporal interactions between SZ patients and healthy controls (HC) beyond static functional connectivity (sFC) in the cuneus, using the publicly available COBRE dataset. Methods: Sliding windows were applied to 72 SZ patients' and 74 healthy controls' (HC) rsfMRI data to generate temporal correlation maps and, finally, evaluate mean strength (dFC-Str), variability (dFC-SD and ALFF) in each window, and the dwelling time. The difference in functional connectivity (FC) of the cuneus between two groups was compared using a two-sample t-test. Results: Our findings demonstrated decreased mean strength connectivity between the cuneus and calcarine, the cuneus and lingual gyrus, and between the cuneus and middle temporal gyrus (TPOmid) in subjects with SZ. Moreover, no difference was detected in variability (standard deviation and the amplitude of low-frequency fluctuation), the dwelling times of all states, or static functional connectivity (sFC) between the groups. Conclusions: Our verdict suggest that dynamic functional connectivity analyses may play crucial roles in unveiling abnormal patterns that would be obscured in static functional connectivity, providing promising impetus for understanding schizophrenia disease.

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