Cortical Activation in Response to Speech Differs between Prelingually Deafened Cochlear Implant Users with Good or Poor Speech-in-Noise Understanding: An fNIRS Study

Michal Levin, Michal Balberg, Yael Zaltz

Research output: Contribution to journalArticlepeer-review

Abstract

Cochlear implant (CI) users with prelingual deafness (hearing impairment started before language development was completed) show variable speech-in-noise (SIN) understanding. The present study aimed to assess cortical activation patterns to speech-in-quiet (SIQ) and SIN in prelingual CI users and compared to individuals with normal hearing (NH), using functional Near-Infrared Spectroscopy (fNIRS). Participants included 15 NH who listened to natural speech, 15 NH who listened via 8-channel noise-excited vocoder, and 14 prelingual CI users. fNIRS data were collected in a block design that included three conditions: SIQ, SIN in a signal-to-noise ratio of 0 dB, and noise. Speech reception thresholds in noise (SRTn) were also assessed. Results revealed different patterns of activation between the NH and CI participants in channels covering mainly the right and left middle temporal gyrus (MTG), depending on the SRTn of the CI users. Specifically, while the NH group showed large response to SIQ and SIN in the MTG areas, prelingual CI users with poor SRTn showed significantly smaller response to SIQ, and inversed response (a reduction in activation) to SIN in the same brain areas. These novel findings support the notion that the MTG can serve as a neural marker for speech understanding in CI patients.

Original languageEnglish
Article number12063
JournalApplied Sciences (Switzerland)
Volume12
Issue number23
DOIs
StatePublished - Dec 2022

Keywords

  • cochlear implant
  • cortical activation
  • fNIRS
  • prelingual deafness
  • speech perception
  • speech-in-noise

All Science Journal Classification (ASJC) codes

  • General Engineering
  • Instrumentation
  • Fluid Flow and Transfer Processes
  • Process Chemistry and Technology
  • General Materials Science
  • Computer Science Applications

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