Evidence map›Paper›PMID 41712463›Full record

ArticleTrends in hearing

Predicting Spectro-Temporal Modulation Detection Thresholds With a Functional Auditory Model.

Lily Cassandra Paulick, Torsten Dau, Helia Relaño-Iborra

Abstract read
In one paragraph

Article in Trends in hearing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Lily Cassandra PaulickHearing Systems, Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark.ORCID 0009-0004-7458-7665
Torsten DauHearing Systems, Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark.ORCID 0000-0001-8110-4343
Helia Relaño-IborraEriksholm Research Centre, Snekkersten, Denmark.ORCID 0000-0002-2899-1673

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spectro-temporal modulation (STM) sensitivity has been proposed as a sensitive marker of speech intelligibility in challenging listening conditions, yet the underlying auditory mechanisms involved in STM detection remain incompletely understood. The present study measured STM detection thresholds in young normal-hearing and older hearing-impaired listeners and evaluated whether the revised Computational Auditory Signal Processing and Perception model (CASP) can account for individual performance. Thresholds were obtained for six modulation detection conditions, defined by combinations of spectral (0, 1, and 2 c/o) and temporal (4 and 12 Hz) rates. To individualize CASP, outer and inner hair cell loss estimates were obtained from audiometric and Adaptive Categorical Loudness Scaling (ACALOS) data. The results showed systematically elevated thresholds in older hearing-impaired listeners as compared to the young normal-hearing group, particularly at higher spectral rates. The model simulations reproduced overall threshold patterns, but substantially underestimated group differences and interindividual variability in the data. Moreover, the simulations showed limited sensitivity to estimates of outer and inner hair cell loss, supporting the idea that additional supra-threshold mechanisms contribute to STM deficits. While these findings demonstrate the potential of auditory models to predict STM performance, they also highlight the need for refined representations of peripheral and central processing to account for individual STM detection thresholds.

Indexed as

Auditory ThresholdHearing Loss, SensorineuralPersons with Hearing DisabilitiesSignal Detection, PsychologicalSpeech PerceptionAcoustic StimulationAdultAgedAge FactorsAudiometry, Pure-ToneAuditory AcuityAuditory PathwaysCase-Control StudiesComputer SimulationFemaleHair Cells, Auditory, Innerauditory modelingsensorineural hearing lossspectro-temporal modulation processingsupra-threshold processing

Identifiers

PMID41712463
PMCPMC12925006

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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.