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Resting-State Functional Connectivity Predicts Cochlear-Implant Speech Outcomes.

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Resting-state functional connectivity, measured by average clustering coefficient, predicts cochlear implant (CI) speech understanding outcomes. This brain imaging metric offers insights into hearing restoration variability in CI users.

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Area of Science:

  • Neuroscience
  • Audiology
  • Medical Imaging

Background:

  • Cochlear implants (CIs) offer hearing restoration but show variable outcomes.
  • Predicting CI success remains challenging despite factors like age and deafness duration.
  • Brain plasticity is hypothesized to influence CI outcomes.

Purpose of the Study:

  • To investigate resting-state functional connectivity (FC) using functional near-infrared spectroscopy (fNIRS) for predicting CI speech understanding.
  • To assess if the average clustering coefficient in FC networks can explain outcome variability.
  • To evaluate FC as a predictive measure pre- and post-CI implantation.

Main Methods:

  • Twenty-three CI candidates underwent resting-state fNIRS pre- and post-implantation.
  • Speech understanding was assessed 1 year after implantation.
  • Resting-state FC networks were analyzed using regularized partial correlation, focusing on the average clustering coefficient.

Main Results:

  • A significant correlation was found between the average clustering coefficient of resting-state functional networks and speech understanding outcomes.
  • This correlation was observed both before and after cochlear implantation.
  • The average clustering coefficient serves as a predictive measure for CI success.

Conclusions:

  • Resting-state FC, specifically the average clustering coefficient, is a viable metric for predicting speech understanding in CI recipients.
  • This brain imaging approach provides an easily deployable method to understand CI outcome variability.
  • Findings highlight the role of brain network properties in auditory rehabilitation.