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Speech-evoked cortical activities and speech recognition in adult cochlear implant listeners: a review of functional near-infrared spectroscopy studies.

Reed FarrarSamin AshjaeiMeisam K Arjmandi
Published in: Experimental brain research (2024)
Cochlear implants (CIs) are the most successful neural prostheses, enabling individuals with severe to profound hearing loss to access sounds and understand speech. While CI has demonstrated success, speech perception outcomes vary largely among CI listeners, with significantly reduced performance in noise. This review paper summarizes prior findings on speech-evoked cortical activities in adult CI listeners using functional near-infrared spectroscopy (fNIRS) to understand (a) speech-evoked cortical processing in CI listeners compared to normal-hearing (NH) individuals, (b) the relationship between these activities and behavioral speech recognition scores, (c) the extent to which current fNIRS-measured speech-evoked cortical activities in CI listeners account for their differences in speech perception, and (d) challenges in using fNIRS for CI research. Compared to NH listeners, CI listeners had diminished speech-evoked activation in the middle temporal gyrus (MTG) and in the superior temporal gyrus (STG), except one study reporting an opposite pattern for STG. NH listeners exhibited higher inferior frontal gyrus (IFG) activity when listening to CI-simulated speech compared to natural speech. Among CI listeners, higher speech recognition scores correlated with lower speech-evoked activation in the STG, higher activation in the left IFG and left fusiform gyrus, with mixed findings in the MTG. fNIRS shows promise for enhancing our understanding of cortical processing of speech in CI listeners, though findings are mixed. Challenges include test-retest reliability, managing noise, replicating natural conditions, optimizing montage design, and standardizing methods to establish a strong predictive relationship between fNIRS-based cortical activities and speech perception in CI listeners.
Keyphrases
  • hearing loss
  • machine learning
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