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Lookup NU author(s): Professor Tim GriffithsORCiD
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
© 2020 The Author(s)Understanding speech in noise (SiN) is a complex task that recruits multiple cortical subsystems. There is a variance in individuals’ ability to understand SiN that cannot be explained by simple hearing profiles, which suggests that central factors may underlie the variance in SiN ability. Here, we elucidated a few cortical functions involved during a SiN task and their contributions to individual variance using both within- and across-subject approaches. Through our within-subject analysis of source-localized electroencephalography, we investigated how acoustic signal-to-noise ratio (SNR) alters cortical evoked responses to a target word across the speech recognition areas, finding stronger responses in left supramarginal gyrus (SMG, BA40 the dorsal lexicon area) with quieter noise. Through an individual differences approach, we found that listeners show different neural sensitivity to the background noise and target speech, reflected in the amplitude ratio of earlier auditory-cortical responses to speech and noise, named as an internal SNR. Listeners with better internal SNR showed better SiN performance. Further, we found that the post-speech time SMG activity explains a further amount of variance in SiN performance that is not accounted for by internal SNR. This result demonstrates that at least two cortical processes contribute to SiN performance independently: pre-target time processing to attenuate neural representation of background noise and post-target time processing to extract information from speech sounds.
Author(s): Kim S, Schwalje AT, Liu AS, Gander PE, McMurray B, Griffiths TD, Choi I
Publication type: Article
Publication status: Published
Journal: NeuroImage
Year: 2021
Volume: 228
Print publication date: 01/03/2021
Online publication date: 30/12/2020
Acceptance date: 23/01/2020
Date deposited: 10/11/2023
ISSN (print): 1053-8119
ISSN (electronic): 1095-9572
Publisher: Academic Press Inc.
URL: https://doi.org/10.1016/j.neuroimage.2020.117699
DOI: 10.1016/j.neuroimage.2020.117699
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