Frontiers in Aging Neuroscience (Aug 2020)

Disrupted Functional Network Connectivity Predicts Cognitive Impairment in Presbycusis Patients

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

DOI
https://doi.org/10.3389/fnagi.2020.00246
Journal volume & issue
Vol. 12

Abstract

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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.

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