Evidence map›Paper›PMID 41038940›Full record

ArticleScientific reports2025

Dynamic assessment of listening effort by EEG alpha oscillations during an adaptive speech-in-noise test.

Davide Simeone, Edoardo Maria Polo, Riccardo Barbieri, Alessia Paglialonga

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

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

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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

4 authors.

Davide SimeoneCnr-Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni (CNR-IEIIT), Piazza Leonardo da Vinci, 32, 20133, Milan, Italy. davidesimeone@cnr.it.
Edoardo Maria PoloPolitecnico di Milano, Piazza Leonardo da Vinci, 32, 20133, Milan, Italy.
Riccardo BarbieriPolitecnico di Milano, Piazza Leonardo da Vinci, 32, 20133, Milan, Italy.
Alessia PaglialongaCnr-Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni (CNR-IEIIT), Piazza Leonardo da Vinci, 32, 20133, Milan, Italy.

Funding

Capita Foundation WHISPER (2020 and 2022 Auditory Research grant)Ministero dell'Università e della Ricerca PNC0000007 (Fit4MedRob - Fit for Medical Robotics)
6 · The paper itself

Abstract

The task of speech recognition in noisy environments can be cognitively demanding for both hearing-impaired and normal-hearing individuals. Recent research emphasized brain oscillations, particularly alpha rhythms (8-13 Hz) from the electroencephalogram (EEG), as potential markers of processing auditory information in challenging listening contexts. However, most studies examined fixed listening demand with meaningful speech. Our study explores how alpha rhythms may quantify listening effort during an adaptive speech-in-noise task with reduced semantic complexity. For analysis, 11 participants with normal hearing were selected, and the individual speech recognition threshold was used to define two conditions with different task demands. Within each condition, multiple auditory stimuli were presented at different signal-to-noise ratios. The difference in listening demand between these conditions was reflected by reaction time and speech recognition performance. A cluster-based permutation test on EEG time-frequency data identified a fronto-central cluster in the alpha band. In-depth analysis of EEG dynamics revealed a significant difference in post-stimulus alpha event-related synchronization in a fronto-central cluster and a near-significant difference at central electrodes, providing preliminary support to the inhibition hypothesis. These findings further validate EEG-derived measures towards an accurate quantitative assessment of short-term neural responses in the context of a simple adaptive speech-in-noise test.

Indexed as

Alpha RhythmElectroencephalographyNoiseSpeech PerceptionAcoustic StimulationAdultFemaleHumansMaleReaction TimeSignal-To-Noise RatioYoung AdultElectroencephalogramListening effortSpeech-in-noiseTask demand

Identifiers

PMID41038940
PMCPMC12491493

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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.