![]() ![]() It remains unclear how attention influences the neural encoding of target and non-target speech and how this encoding depends on whether speech is glimpsed or masked. At the same time, many studies have demonstrated behavioral evidence for non-target speech processing, including informational masking, priming, and own-name recognition. Nevertheless, humans can reliably comprehend the target and ignore the background over a range of signal-to-noise ratios (SNRs). These variations make stream segregation particularly challenging because they may require different means of handling the glimpsed and masked portions of speech for target and non-target talkers. ![]() Due to the natural temporal variations of speech, multitalker speech inherently contains simpler moments when the target talker is louder than the background (glimpsed target) and more difficult moments when non-target speech is louder than the target (masked target or glimpsed non-target). It is thought that this process relies on local spectrotemporal structure, including onset and offset synchrony, harmonicity, and fundamental frequency continuity. One of the main challenges in these environments is stream segregation, or the isolation of a sound stream from the complex mixture. Humans can converse in complex, multitalker acoustic environments in which one talker is of interest and one or more background talkers can be ignored. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist The individual quantitative observations underlying the data summarized in Figs 2– 6 and S2 are available at (DOI: 10.5281/zenodo.7859760).įunding: This work was supported by the National Institutes of Health (NIH), National Institute on Deafness and Other Communication Disorders (NIDCD) (DC014279 to NM). The data that support the findings of this study are available upon request from the Scientific Platforms team at the Zuckerman Institute of Columbia University ( The code for pre-processing iEEG signals ( ) and extracting stimulus features ( ) is available online. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: There are restrictions to the availability of this dataset due to the protection of human subjects who participated in this study. Received: AugAccepted: ApPublished: June 6, 2023Ĭopyright: © 2023 Raghavan et al. Bizley, University College London, UNITED KINGDOM PLoS Biol 21(6):Īcademic Editor: Jennifer K. These findings suggest separate mechanisms for encoding glimpsed and masked speech and provide neural evidence for the glimpsing model of speech perception.Ĭitation: Raghavan VS, O’Sullivan J, Bickel S, Mehta AD, Mesgarani N (2023) Distinct neural encoding of glimpsed and masked speech in multitalker situations. In contrast, encoding of masked phonetic features was found only for the target, with a greater response latency and distinct anatomical organization compared to glimpsed phonetic features. We found that glimpsed speech is encoded at the level of phonetic features for target and non-target talkers, with enhanced encoding of target speech in non-primary AC. ![]() To clarify this issue, we directly recorded from primary and non-primary auditory cortex (AC) in neurosurgical patients as they attended to one talker in multitalker speech and trained temporal response function models to predict high-gamma neural activity from glimpsed and masked stimulus features. Other models, however, require the recovery of the masked regions. Some models suggest that perception can be achieved through glimpses, which are spectrotemporal regions where a talker has more energy than the background. Humans can easily tune in to one talker in a multitalker environment while still picking up bits of background speech however, it remains unclear how we perceive speech that is masked and to what degree non-target speech is processed. ![]()
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