• Jiapei Xie, Weidong Zhang, Chen Yu, Wei Wei, Yan Bai, Yu Shen, Xipeng Yue, Xinhui Wang, Xianchang Zhang, Guofeng Shen, and Meiyun Wang.
• Department of Medical Imaging, The People's Hospital of Zhengzhou University & Henan Provincial People's Hospital, Zhengzhou, China. Electronic address: 1454314461@qq.com.
• Neuroscience. 2024 Aug 30; 554: 263326-33.

AbstractIn order to comprehensively understand the changes of brain networks in patients with chronic tinnitus, this study combined static and dynamic analysis methods to explore the abnormalities of brain networks. Thirty-two patients with chronic tinnitus and 30 age-, sex- and education-matched healthy controls (HC) were recruited. Independent component analysis was used to identify resting-state networks (RSNs). Static and dynamic functional network connectivity (FNC) were performed. The temporal properties of brain network including mean dwell time (MDT), fraction time (FT) and numbers of transitions (NT) were calculated. Two-sample t test and Spearman's correlation were used for group compares and correlation analysis. Four RSNs showed abnormal FNC including auditory network (AUN), default mode network (DMN), attention network (AN) and sensorimotor network (SMN). For static analysis, tinnitus patients showed significantly decreased FNC in AUN-DMN, AUN-AN, DMN-AN, and DMN-SMN than HC [p < 0.05, false discovery rate (FDR) corrected]. For dynamic analysis, tinnitus patients showed significantly decreased FNC in DMN-AN in state 3 (p < 0.05, FDR corrected). MDT in state 3 was significantly decreased in tinnitus patients (t = 2.039, P = 0.046). In the tinnitus group, the score of tinnitus functional index (TFI) was negatively correlated with MDT and FT in state 4, and the duration of tinnitus was positively correlated with FT in state 1 and NT. Chronic tinnitus causes abnormal brain network connectivity. These abnormal brain networks help to clarify the mechanism of tinnitus generation and chronicity, and provide a potential basis for the treatment of tinnitus.Copyright © 2024 IBRO. Published by Elsevier Inc. All rights reserved.

24 keywords...

hide…