Evidence map›Paper›PMID 39253477›Full record

ArticlebioRxiv : the preprint server for biology2024

Reduced neural distinctiveness of speech representations in the middle-aged brain.

Zhe-Chen Guo, Jacie R McHaney, Aravindakshan Parthasarathy, Bharath Chandrasekaran

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Zhe-Chen GuoRoxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL, USA.ORCID 0000-0003-0870-8321
Jacie R McHaneyRoxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL, USA.ORCID 0000-0002-1148-4018
Aravindakshan ParthasarathyDepartment of Communication Science and Disorders, University of Pittsburgh, Pittsburgh, PA, USA.ORCID 0000-0002-4573-8004
Bharath ChandrasekaranRoxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL, USA.ORCID 0000-0002-3673-9435

Funding

Supplement to cortical contributions to frequency-following response generation and modulationR01DC013315 · NIDCD · UNIVERSITY OF TEXAS AT AUSTIN · PI ABEL, TAYLOR JOHN, CHANDRASEKARAN, BHARATH · 2014 to 2025
$5.5M
Research Supplement - Luz AndrinoR21DC018882 · NIDCD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI PARTHASARATHY, ARAVINDAKSHAN · 2022 to 2024
$666k
Neural Mechanisms of Speech Perception in Noise in Middle-AgeF31DC020085 · NIDCD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MCHANEY, JACIE R · 2022 to 2022
$49k
NIDCD NIH HHS F31 DC020085NIDCD NIH HHS R01 DC013315NIDCD NIH HHS R21 DC018882
6 · The paper itself

Abstract

Speech perception declines independent of hearing thresholds in middle-age, and the neurobiological reasons are unclear. In line with the age-related neural dedifferentiation hypothesis, we predicted that middle-aged adults show less distinct cortical representations of phonemes and acoustic-phonetic features relative to younger adults. In addition to an extensive audiological, auditory electrophysiological, and speech perceptual test battery, we measured electroencephalographic responses time-locked to phoneme instances (phoneme-related potential; PRP) in naturalistic, continuous speech and trained neural network classifiers to predict phonemes from these responses. Consistent with age-related neural dedifferentiation, phoneme predictions were less accurate, more uncertain, and involved a broader network for middle-aged adults compared with younger adults. Representational similarity analysis revealed that the featural relationship between phonemes was less robust in middle-age. Electrophysiological and behavioral measures revealed signatures of cochlear neural degeneration (CND) and speech perceptual deficits in middle-aged adults relative to younger adults. Consistent with prior work in animal models, signatures of CND were associated with greater cortical dedifferentiation, explaining nearly a third of the variance in PRP prediction accuracy together with measures of acoustic neural processing. Notably, even after controlling for CND signatures and acoustic processing abilities, age-group differences in PRP prediction accuracy remained. Overall, our results reveal "fuzzier" phonemic representations, suggesting that age-related cortical neural dedifferentiation can occur even in middle-age and may underlie speech perceptual challenges, despite a normal audiogram.

Indexed as

cortical speech processingelectroencephalographymiddle-aged adultsneural dedifferentiationphoneme representation

Identifiers

PMID39253477
PMCPMC11383304

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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.