Physiological markers of listening effort and their dependence on age

语音理解是人类听力的一项关键功能，在学习、专业和学习中具有重要作用 社会功能。衰老与语音识别的困难增加有关，特别是在噪音较大的情况下 背景：尽管传统的临床测试经常不能解释主观的言语感知 困难。越来越多的研究发现，认知资源的补偿性使用总体上有所增加 被称为听力努力(LE)，这是老龄化和听力受损人群中的一项关键变化。 因此，LE的准确测量可以作为量化主观的关键客观诊断工具 言语知觉缺陷。虽然已经提出了多种量化LE的方法，但对LE的了解却很少 这些衡量标准是否反映了对相同基本认知过程的使用，特别是在 在其他有意义的言语掩蔽者在场的情况下连续讲话。此外，人们几乎不知道是否 LE的变化影响较低和较高级别特征的处理(例如，声学包络与词汇惊奇) 在整个听觉皮质层级中。这项提议将解决我们知识中的这些重要差距。在……里面 目标1，我们将通过改变语音识别中的信噪比或空间线索来操纵LE需求 任务使用被竞争言语掩盖的孤立句子，同时测量三个常用的衡量标准 LE(自我报告、瞳孔大小和阿尔法波段功率的神经测量)。然后，我们将把这些措施关联起来 以确定它们是否类似地受到可理解性操作的调制，指示 共同的潜在认知过程。在目标2中，我们将解决两个关键问题。首先，我们要测试一下 在目标1中使用的LE度量在更自然主义的背景下表现出彼此类似的关系， 连续语音，更接近于模仿语音感知困难普遍存在的场景 遇到了。其次，我们将使用高级基于模型的分析来分解语音诱发 脑电活动对注意和忽略的低水平和高水平特征的反应 并评估LE操作如何调节这些表征。这样做，我们将获得新的见解 高阶认知过程与语言加工通路之间的相互作用 大脑皮层，潜在地揭示了LE的新的神经特征。最后，为了更深入地了解衰老的影响 在LE和语音处理方面，我们将评估每个目标的关键指标如何随着年龄的变化而变化。这 这项工作将为未来的研究提供基础，旨在更详细地描述不同 注意和忽略言语的大脑皮层加工中的认知加工 在语音处理缺陷诊断中的应用，特别是在标准临床测试的情况下 未能检测到损害，在测试语音感知时，受益于听力中使用的新算法 辅助设备。

Speech understanding is a key function of human audition with important roles in learning, professional, and social functions. Ageing is associated with increased difficulties with speech recognition, particularly in noisy backgrounds, although traditional clinical tests frequently fail to account for subjective speech perception difficulties. A growing body of work has identified increased compensatory use of cognitive resources, collectively known as listening effort (LE), as a key change within the ageing and hearing-impaired populations. Consequently, accurate measures of LE may serve as critical objective diagnostic tools for quantifying subjective speech perception deficits. While multiple methods for quantifying LE have been proposed, little is known about whether these measures reflect usage of the same underlying cognitive processes, particularly in the context of continuous speech in the presence of other meaningful speech maskers. Moreover, little is known about whether changes in LE affect processing of lower- and higher-level features (e.g., acoustic envelope vs. lexical surprisal) throughout the auditory cortical hierarchy. This proposal will address these important gaps in our knowledge. In Aim 1, we will manipulate LE demands via changes in signal-to-noise ratio or spatial cues in a speech recognition task utilizing isolated sentences masked by competing speech, while measuring three commonly used measures of LE (self-report, pupil size, and neural measure of alpha band power). We will then correlate these measures with one another to determine whether they are similarly modulated by intelligibility manipulations, indicating common underlying cognitive processes. In Aim 2, we will address two key questions. First, we will test whether the LE measures used in Aim 1 exhibit similar relationships with one another in the context of more naturalistic, continuous speech, more closely mimicking scenarios in which speech perception difficulties are commonly encountered. Second, we will use advanced model-based analyses to decompose speech-evoked electroencephalographic activity into responses to lower- and higher-level features of both attended and ignored speech and assess how LE manipulations modulate these representations. Doing so, we will gain novel insights into the interaction between higher-order cognitive processes and the language processing pathways in the cortex, potentially revealing new neural signatures of LE. Finally, to gain deeper understanding of aging effects on LE and speech processing, we will assess how each Aim’s key measures change as a function of age. This work will provide foundation for future studies aimed at a more detailed characterization of the effects of different cognitive processes involved in LE on cortical processing of attended and ignored speech, with potential applications in diagnostics of speech processing deficits, particularly in scenarios where standard clinical tests fail to detect an impairment, and in testing speech-perception benefits from new algorithms used in hearing- assisting devices.