ArticleImaging neuroscience (Cambridge, Mass.)2025
Neural speech tracking in noise reflects the opposing influence of SNR on intelligibility and attentional effort.
Article in Imaging neuroscience (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Real-time brain-controlled selective hearing enhances speech perception in multi-talker environments.Nature neuroscience · 2026Article
- From Selective Listening to Brain-Controlled Hearing: A Perspective on the Future of Auditory Technology.Journal of the Association for Research in Otolaryngology : JARO · 2026Review
- Integrating Eye Tracking in Acoustic Research: Methods for Sound Localization, Event Detection, Multimodal Sensing, and Perceptual Analysis.Sensors (Basel, Switzerland) · 2026Review
- A Brain-Computer Interface for Improving Auditory Attention in Multi-Talker Environments.IEEE access : practical innovations, open solutions · 2025Article
Corrections and comments
- Update of
Authors and funding
3 authors.
Funding
Abstract
Understanding speech in noise depends on several interacting factors, including the signal-to-noise ratio (SNR), speech intelligibility (SI), and attentional engagement. However, how these factors relate to selective neural speech tracking remains unclear. In this study, we recorded EEG and eye-tracking data while participants performed a selective listening task involving a target talker in the presence of a competing masker talker and background noise across a wide range of SNRs. Our results revealed a non-linear relationship, where neural tracking of the target speech first increased with SNR but then paradoxically decreased as SNR continued to improve. To explain this, we quantified SI behaviorally, estimated attentional effort (AE) using gaze velocity, and measured behavioral performance (BP) via a repeated-word detection task. Our analysis showed that neural tracking of the target speech increased with both SI and attentional engagement. However, when intelligibility reached ceiling levels, selective neural speech tracking decreased as AE declined. Statistical modeling indicated that SI and AE were reliable predictors of neural tracking, while SNR showed no independent contribution after accounting for these factors. Our results demonstrate that improved SNR influences selective neural speech tracking primarily by increasing SI and simultaneously reducing AE, which have opposing effects on neural tracking. These findings underscore the importance of jointly considering these factors in studies of speech perception in noise.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.