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DOI 10.3389/fnagi.2020.00246

Медицинская библиотека · Frontiers in aging neuroscience · 2020

Disrupted Functional Network Connectivity Predicts Cognitive Impairment in Presbycusis Patients.

Xing Chunhua, Zhang Juan, Cui Jinluan, Yong Wei, Hu Jinghua, Yin Xindao, Wu Yuanqing, Chen Yu-Chen

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Аннотация

Purpose: 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.

Methods

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 t-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.

Results

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.

Conclusion

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.

Для цитирования: Xing Chunhua, Zhang Juan, Cui Jinluan, Yong Wei, Hu Jinghua, Yin Xindao, Wu Yuanqing, Chen Yu-Chen. Disrupted Functional Network Connectivity Predicts Cognitive Impairment in Presbycusis Patients.. Frontiers in aging neuroscience. 2020. DOI: 10.3389/fnagi.2020.00246.
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