Evidence map›Paper›PMID 40046437›Full record

ArticleFrontiers in neuroscience2025

P300 as an index of speech-in-noise understanding in complex acoustic environments in young and older adults.

Dylan V Pearson, Yi Shen, William P Hetrick, Brian F O'Donnell, Nancy B Lundin, J Devin McAuley, Gary R Kidd

Abstract read
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Article in Frontiers in neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Dylan V PearsonDepartment of Speech, Language, and Hearing Sciences, Indiana University, Bloomington, IN, United States.
Yi ShenDepartment of Speech and Hearing Sciences, University of Washington, Seattle, WA, United States.
William P HetrickDepartment of Psychological and Brain Sciences, Indiana University, Bloomington, IN, United States.
Brian F O'DonnellDepartment of Psychological and Brain Sciences, Indiana University, Bloomington, IN, United States.
Nancy B LundinDepartment of Psychological and Brain Sciences, Indiana University, Bloomington, IN, United States.
J Devin McAuleyDepartment of Psychology, Michigan State University, East Lansing, MI, United States.
Gary R KiddDepartment of Speech, Language, and Hearing Sciences, Indiana University, Bloomington, IN, United States.

Funding

Understanding speech in noise_The roles of aging and attentional entrainmentR01DC013538 · NIDCD · TRUSTEES OF INDIANA UNIVERSITY · PI KIDD, GARY R, MCAULEY, J. DEVIN · 2014 to 2018
$1.6M
Individualized Assessment and Prediction of Speech-Recognition Performance In Adults with Age-related Hearing LossR01DC017988 · NIDCD · UNIVERSITY OF WASHINGTON · PI SHEN, YI · 2019 to 2023
$1.5M
NIDCD NIH HHS R01 DC013538NIDCD NIH HHS R01 DC017988
6 · The paper itself

Abstract

Introduction: Aging is associated with decrements in speech-in-noise perception which make communication in real world environments difficult. However, the neural correlates of these difficulties are not well characterized and finding correlations between speech-in-noise performance and electrophysiological measures has been difficult due in part to the fact that speech-in-noise perception is a multi-faceted process. The current study used a wide range of speech-in-noise tasks in an attempt to more completely capture speech-in-noise performance and compared these with electrophysiological measures. Methods: P300 event related brain responses were elicited in young and older adult listeners to spoken isochronous syllable sequences presented in quiet and noisy (i.e., multi-talker babble) background conditions. To investigate the extent to which P300 responses are associated with speech-in-noise understanding, listeners also completed a separate battery of speech-in-noise recognition tasks. Results: Overall P300 amplitudes measured in noisy conditions, but not in quiet conditions, were associated with performance on a variety of speech recognition tasks and were positively correlated with a composite measure of speech understanding in noise based on the full battery. In addition, older adults had P300 responses to deviant and omitted speech stimuli with lower amplitudes, longer latencies, and relatively greater frontal topographies than young adults. Discussion: The results demonstrate that P300 amplitudes elicited in competing noise were a strong predictor of speech-in-noise understanding. This, in addition to the age-related differences in P300 responses, highlights the relevance of neural attentional mechanisms for understanding age-related differences in speech understanding in noise.

Indexed as

agingP300speech entrainmentspeech-in-noise (SIN) perceptionspeech rhythm

Identifiers

PMID40046437
PMCPMC11879943

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.