Evidence map›Paper›PMID 40041963›Full record

ArticleProceedings. Biological sciences2025

Predicting speech-in-noise ability with static and dynamic auditory figure-ground analysis using structural equation modelling.

Xiaoxuan Guo, Ester Benzaquén, Emma Holmes, Joel Isaac Berger, Inga Charlotte Brühl, William Sedley, Steven P Rushton, Tim Griffiths

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

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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

8 authors.

Xiaoxuan GuoBiosciences Institute, Newcastle University, Newcastle upon Tyne, UK.ORCID 0000-0002-2018-3583
Ester BenzaquénBiosciences Institute, Newcastle University, Newcastle upon Tyne, UK.ORCID 0000-0002-1760-8085
Emma HolmesDepartment of Speech Hearing and Phonetic Sciences, UCL, London, UK.
Joel Isaac BergerHuman Brain Research Laboratory, Department of Neurosurgery, University of Iowa Hospitals and Clinics, Iowa, IA, USA.ORCID 0000-0002-1960-9487
Inga Charlotte BrühlMaastricht University, Maastricht, The Netherlands.ORCID 0009-0005-1045-8116
William SedleyBiosciences Institute, Newcastle University, Newcastle upon Tyne, UK.
Steven P RushtonSchool of Biology, Newcastle University, Newcastle upon Tyne, UK.
Tim GriffithsBiosciences Institute, Newcastle University, Newcastle upon Tyne, UK.

Funding

Medical Research Council MR/T032553/1
6 · The paper itself

Abstract

Auditory figure-ground paradigms assess the ability to extract a foreground figure from a random background, a crucial part of central hearing. Previous studies have shown that the ability to extract static figures predicts speech-in-noise ability. In this study, we assessed both fixed and dynamic figures: the latter comprised component frequencies that vary over time like natural speech. We examined how well speech-in-noise ability (for words and sentences) could be predicted by age, peripheral hearing, static and dynamic figure-ground with 159 participants. Regression demonstrated that in addition to audiogram and age, low-frequency dynamic figure-ground accounted for an independent variance of both word- and sentence-in-noise perception, higher than the static figure-ground. The structural equation models showed that a combination of all types of figure-ground tasks and age and audiogram could explain up to 89% of the variance in speech-in-noise, and figure-ground predicted speech-in-noise with a higher effect size than the audiogram or age. Age influenced word perception in noise directly but sentence perception indirectly via effects on peripheral and central hearing. Overall, this study demonstrates that dynamic figure-ground predicts a significant variance in real-life listening better than the prototype figure-ground. The combination of figure-ground tasks predicts real-life listening better than audiogram or age.

Indexed as

NoiseSpeech PerceptionAdolescentAdultAgedFemaleHumansLatent Class AnalysisMaleMiddle AgedYoung Adultauditory figure-groundnew hearing measurepitch perceptionpure-tone audiogramspeech-in-noise perceptionstructural equation modelling

Identifiers

PMID40041963
PMCPMC11881018

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Registered trials

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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.