{"title":"Neural speech tracking in noise reflects the opposing influence of SNR on intelligibility and attentional effort.","authors":"Xiaomin He, Vinay S Raghavan, Nima Mesgarani","doi":"10.1162/IMAG.a.126","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12395281/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Imaging neuroscience (Cambridge, Mass.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1162/IMAG.a.126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.