ORIGINAL RESEARCH article
Front. Psychiatry
Sec. Neuroimaging
Volume 16 - 2025 | doi: 10.3389/fpsyt.2025.1584071
The Changes in Brain Network Functional Gradients and Dynamic Functional Connectivity in SeLECTS Patients Revealing Disruptive and Compensatory Mechanisms in Brain Networks
Provisionally accepted
Linfeng Song
Guangrong Wu
Jiaren Zhang
Benqing Liu
Xuejin MaXu Chen
Wang Junjun
Xiaoyu Gu
BinLin TIAN
Li Yongzhe
anjie zhang
Lin Jiang*- Department of Radiology, The Third Affiliated Hospital of Zunyi Medical University (The First People’s Hospital of Zunyi), Zunyi, China
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Background: Self-limited epilepsy with centrotemporal spikes (SeLECTS), a common childhood focal epilepsy syndrome, is linked to cognitive impairments and poorly understood neuropathological mechanisms. Methods: This study explored dynamic functional connectivity (dFC) and functional gradients (FG) alterations in key brain networks using resting-state MRI (rs-MRI) data from 34 SeLECTS patients and 32 healthy controls (HCs). Results: The results revealed significant dFC changes between the Default Mode Network (DMN) and Sensorimotor Network (SMN) in SeLECTS patients compared to HCs. Specifically, the first gradient of the DMN showed decreased gradient scores in the bilateral dorsolateral superior frontal gyrus and increased scores in the left inferior temporal gyrus. In the first gradient of the SMN, increased scores were found in the bilateral supplementary motor area, while decreases occurred in the right precentral gyrus. Support vector machine (SVM) analysis showed that FG-based features could effectively identify abnormalities in specific brain networks of SeLECTS (AUC = 0.819). Further correlation analysis linked FG alterations in the DMN to cognitive measures (working memory, processing speed, and full-scale IQ) and in the SMN to disease duration and language comprehension. Conclusion: These findings suggest that significant changes in FG and dFC of DMN-and SMN-related brain regions in SeLECTS may reflect both disruptions and compensatory mechanisms in brain networks, offering new insights into the neuropathological basis of the disorder and potential diagnostic biomarkers.
Keywords: Self-limited epilepsy with centrotemporal spikes, Functional gradient, Dynamic Functional Connectivity, brain network, machine learning
Received: 26 Feb 2025; Accepted: 17 Apr 2025.
Copyright: © 2025 Song, Wu, Zhang, Liu, Ma, Chen, Junjun, Gu, TIAN, Yongzhe, zhang and Jiang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Lin Jiang, Department of Radiology, The Third Affiliated Hospital of Zunyi Medical University (The First People’s Hospital of Zunyi), Zunyi, China
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