Suppr超能文献

噪声和奖励对单词检测任务中瞳孔大小和脑电图语音追踪的影响。

Effects of Noise and Reward on Pupil Size and Electroencephalographic Speech Tracking in a Word-Detection Task.

作者信息

Iotzov Ivan, Parra Lucas C

机构信息

Department of Biomedical Engineering, City College of New York, New York, New York, USA.

出版信息

Eur J Neurosci. 2025 Feb;61(3):e70009. doi: 10.1111/ejn.70009.

Abstract

Speech is hard to understand when there is background noise. Speech intelligibility and listening effort both affect our ability to understand speech, but the relative contribution of these factors is hard to disentangle. Previous studies suggest that speech intelligibility could be assessed with EEG speech tracking and listening effort via pupil size. However, these measures may be confounded, because poor intelligibility may require a larger effort. To address this, we developed a novel word-detection paradigm that allows for a rapid behavioural assessment of speech processing. In this paradigm, words appear on the screen during continuous speech, similar to closed captioning. In two listening experiments with a total of 51 participants, we manipulated intelligibility by changing signal-to-noise ratios (SNRs) and modulated effort by varying monetary reward. Increasing SNR improved detection performance along with EEG speech tracking. Additionally, we find that pupil size increases with increased SNR. Surprisingly, when we modulated both reward and SNR, we found that reward modulated only pupil size, whereas SNR modulated only EEG speech tracking. We interpret this as the effects of arousal and listening effort on pupil size and of intelligibility on EEG speech tracking. The experimental paradigm developed here may be beneficial when assessing hearing devices in terms of speech intelligibility and listening effort.

摘要

当存在背景噪音时,语音很难理解。语音清晰度和听觉努力都会影响我们理解语音的能力,但这些因素的相对贡献很难区分。先前的研究表明,可以通过脑电图语音跟踪来评估语音清晰度,并通过瞳孔大小来评估听觉努力。然而,这些测量可能会相互混淆,因为清晰度差可能需要更大的努力。为了解决这个问题,我们开发了一种新颖的单词检测范式,该范式可以对语音处理进行快速行为评估。在这个范式中,单词在连续语音期间出现在屏幕上,类似于隐藏式字幕。在总共51名参与者的两项听力实验中,我们通过改变信噪比(SNR)来操纵清晰度,并通过改变金钱奖励来调节努力程度。增加信噪比可提高检测性能以及脑电图语音跟踪。此外,我们发现瞳孔大小随着信噪比的增加而增大。令人惊讶的是,当我们同时调节奖励和信噪比时,我们发现奖励仅调节瞳孔大小,而信噪比仅调节脑电图语音跟踪。我们将此解释为唤醒和听觉努力对瞳孔大小的影响以及清晰度对脑电图语音跟踪的影响。这里开发的实验范式在根据语音清晰度和听觉努力评估听力设备时可能会有所帮助。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验