Evidence map›Paper›PMID 31379494›Full record

ArticleFrontiers in neuroscience2019

Effects of Age, Cognition, and Neural Encoding on the Perception of Temporal Speech Cues.

Lindsey Roque, Hanin Karawani, Sandra Gordon-Salant, Samira Anderson

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
4.7field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 1 synthesis or guideline pooled it, 58 citations in OpenAlex.

  1. Pooled it
  2. Rate Discrimination Training May Partially Restore Temporal Processing Abilities from Age-Related Deficits.Journal of the Association for Research in Otolaryngology : JARO · 2022
    Trial
  3. Nonword Repetition Assessing Auditory and Cognitive Abilities in Adult Cochlear Implant Users.Journal of speech, language, and hearing research : JSLHR · 2026
    Article
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  20. Neural Presbyacusis in Humans Inferred from Age-Related Differences in Auditory Nerve Function and Structure.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Lindsey RoqueDepartment of Hearing and Speech Sciences, University of Maryland, College Park, College Park, MD, United States.
Hanin KarawaniDepartment of Hearing and Speech Sciences, University of Maryland, College Park, College Park, MD, United States.
Sandra Gordon-SalantDepartment of Hearing and Speech Sciences, University of Maryland, College Park, College Park, MD, United States.
Samira AndersonDepartment of Hearing and Speech Sciences, University of Maryland, College Park, College Park, MD, United States.
University of Maryland, College Park · USUniversity of Haifa · IL

Funding

Age-related changes in neural encoding and perception of temporal speech cuesR21DC015843 · NIDCD · UNIV OF MARYLAND, COLLEGE PARK · PI ANDERSON, SAMIRA B · 2016 to 2018
$436k
NIDCD NIH HHS R21 DC015843
6 · The paper itself

Abstract

Older adults commonly report difficulty understanding speech, particularly in adverse listening environments. These communication difficulties may exist in the absence of peripheral hearing loss. Older adults, both with normal hearing and with hearing loss, demonstrate temporal processing deficits that affect speech perception. The purpose of the present study is to investigate aging, cognition, and neural processing factors that may lead to deficits on perceptual tasks that rely on phoneme identification based on a temporal cue - vowel duration. A better understanding of the neural and cognitive impairments underlying temporal processing deficits could lead to more focused aural rehabilitation for improved speech understanding for older adults. This investigation was conducted in younger (YNH) and older normal-hearing (ONH) participants who completed three measures of cognitive functioning known to decline with age: working memory, processing speed, and inhibitory control. To evaluate perceptual and neural processing of auditory temporal contrasts, identification functions for the contrasting word-pair WHEAT and WEED were obtained on a nine-step continuum of vowel duration, and frequency-following responses (FFRs) and cortical auditory-evoked potentials (CAEPs) were recorded to the two endpoints of the continuum. Multiple linear regression analyses were conducted to determine the cognitive, peripheral, and/or central mechanisms that may contribute to perceptual performance. YNH participants demonstrated higher cognitive functioning on all three measures compared to ONH participants. The slope of the identification function was steeper in YNH than in ONH participants, suggesting a clearer distinction between the contrasting words in the YNH participants. FFRs revealed better response waveform morphology and more robust phase-locking in YNH compared to ONH participants. ONH participants also exhibited earlier latencies for CAEP components compared to the YNH participants. Linear regression analyses revealed that cortical processing significantly contributed to the variance in perceptual performance in the WHEAT/WEED identification functions. These results suggest that reduced neural precision contributes to age-related speech perception difficulties that arise from temporal processing deficits.

Indexed as

agingcognitioncortical auditory-evoked potentialsfrequency-following responsespeech perceptiontemporal processing

Identifiers

PMID31379494
PMCPMC6659127
OpenAlexW2955744872

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.