Xing Chunhua, Zhang Juan, Cui Jinluan, Yong Wei, Hu Jinghua, Yin Xindao, Wu Yuanqing, Chen Yu-Chen
Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
Department of Neurology, Nanjing Yuhua Hospital, Yuhua Branch of Nanjing First Hospital, Nanjing, China.
Front Aging Neurosci. 2020 Aug 12;12:246. doi: 10.3389/fnagi.2020.00246. eCollection 2020.
: Individuals with presbycusis often show deficits in cognitive function, however, the exact neurophysiological mechanisms are not well understood. This study explored the alterations in intra- and inter-network functional connectivity (FC) of multiple networks in presbycusis patients, and further correlated FC with cognitive assessment scores to assess their ability to predict cognitive impairment. : Resting-state functional magnetic resonance imaging (rs-fMRI) was performed in 40 presbycusis patients and 40 matched controls, and 12 resting-state networks (RSNs) were identified by independent component analysis (ICA) approach. A two-sample -test was carried out to detect the intra-network FC differences, and functional network connectivity (FNC) was calculated to compare the inter-network FC differences. Pearson or Spearman correlation analysis was subsequently used to explore the correlation between altered FC and cognitive assessment scores. : Our study demonstrated that patients with presbycusis showed significantly decreased FC in the subcortical limbic network (scLN), default mode network (DMN), executive control network (ECN), and attention network (AN) compared with the control group. Moreover, the connectivity for scLN-AUN (auditory network) and VN (visual network)-DMN were found significantly increased while AN-DMN was found significantly decreased in presbycusis patients. Ultimately, this study revealed the intra- and inter-network alterations associated with some cognitive assessment scores. : This study observed intra- and inter-network FC alterations in presbycusis patients, and investigated that presbycusis can lead to abnormal connectivity of RSNs and plasticity compensation mechanism, which may be the basis of cognitive impairment, suggesting that FNC can be used to predict potential cognitive impairment in their early stage.
老年聋患者常表现出认知功能缺陷，然而，确切的神经生理机制尚不清楚。本研究探讨了老年聋患者多个脑网络内及网络间功能连接（FC）的改变，并进一步将FC与认知评估得分进行关联，以评估其预测认知障碍的能力。：对40例老年聋患者和40例匹配的对照组进行静息态功能磁共振成像（rs-fMRI）检查，并采用独立成分分析（ICA）方法识别出12个静息态网络（RSN）。进行双样本t检验以检测网络内FC差异，并计算功能网络连接性（FNC）以比较网络间FC差异。随后采用Pearson或Spearman相关分析来探讨FC改变与认知评估得分之间的相关性。：我们的研究表明，与对照组相比，老年聋患者在皮质下边缘网络（scLN）、默认模式网络（DMN）、执行控制网络（ECN）和注意网络（AN）中的FC显著降低。此外，发现老年聋患者scLN-听觉网络（AUN）和视觉网络（VN）-DMN之间的连接性显著增加，而AN-DMN之间的连接性显著降低。最终，本研究揭示了与一些认知评估得分相关的网络内和网络间改变。：本研究观察到老年聋患者网络内和网络间FC的改变，并研究发现老年聋可导致RSN的连接异常和可塑性补偿机制，这可能是认知障碍的基础，提示FNC可用于预测其早期潜在的认知障碍。
