Neurophysiological Mechanisms of Speech Intelligibility in Noise - A Quantitative Framework

噪声中言语清晰度的神经生理学机制 - 定量框架

• 批准号: 9788035
• 负责人: Vibha Viswanathan
• 金额: $ 4.5万
• 依托单位: PURDUE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9788035
• 关键词: Acoustic Nerve; Address; Age; Attention; Auditory; Auditory system; Brain; Brain Stem; Clinic; Clinical; Cochlea; Cochlear Implants; Code; Cognitive; Complement; Computer Simulation; Data; Data Collection; Development; Diagnostic; Electroencephalography; Environment; Etiology; Foundations; Functional disorder; Future; Goals; Hearing; Hearing Aids; Human; Impairment; Individual; Individual Differences; Inner Hair Cells; Intervention; Knowledge; Labyrinth; Link; Maps; Measurement; Measures; Modeling; Nature; Neurosciences; Noise; Output; Participant; Performance; Process; Psychophysics; Research; Resources; Sensory; Shapes; Solid; Source; Speech; Speech Intelligibility; Stimulus; Techniques; Testing; Training; Variant; attentional control; attentional modulation; aural rehabilitation; base; career; cochlear synaptopathy; cognitive ability; cognitive process; design; experience; experimental study; hearing impairment; individual patient; interest; neurophysiology; neurotransmission; noise perception; normal hearing; otoacoustic emission; rehabilitation strategy; relating to nervous system; response; selective attention; signal processing; sound; speech in noise; statistics; success

Project Summary/Abstract Communicating in noisy environments with many sound sources places enormous demands on the auditory system. Successfully extracting target speech information in such scenarios requires a combination of precise cochlear transduction and neural coding of sound information, and effective downstream cognitive processes that use the encoded information to segregate and selectively process the target speech of interest. Speech-in- noise problems (e.g., in old age or hearing loss) can thus arise from impaired “bottom-up” coding of information, or from declines in cognitive ability. Although the existence of these two components is well recognized, there is currently no integrative framework for quantifying the relative contributions of each to speech intelligibility in noise, and for identifying which aspect is deficient in an individual who is experiencing listening problems. The specific aims of this proposal are designed to address this gap by measuring the neurophysiological representation of envelope information and investigating how that varies with both “bottom- up” manipulations and “top-down” manipulations in the same individuals. First, envelope coding in the brainstem and cortex will be directly measured using electroencephalography (EEG). The EEG metrics will then be linked to perceptual intelligibility by examining how they covary as the speech is presented with different levels and types of background noise, and how they covary across individuals (Aim 1). Next, for the same individuals, the effect of attentional focus on the same envelope coding measures as Aim 1 will be examined by keeping the input speech mixture constant and manipulating which speech source is the focus of selective attention (Aim 2). This approach helps isolate the top-down component. Importantly, conducting all intelligibility and EEG measurements in the same individual subjects allows us to leverage individual differences and use regression techniques to characterize the relative contributions of bottom-up and top-down mechanisms to performance. Finally, for the speech-noise mixtures used in Aim 1, we will calculate the same envelope coding metrics at the output of a computational auditory-nerve model (Aim 3). Key mechanisms of cochlear dysfunction will be incorporated into the model to characterize their effects on envelope coding of speech in noise. By comparing “model” (Aim 3) and “neural” metrics (Aims 1 and 2), we will test whether cochlear mechanisms can account for the individual differences in bottom-up coding. The knowledge gained through the proposed set of experiments will be foundational in the development of objective diagnostics and interventions tailored for the specific nature of speech-in-noise problems that an individual patient is experiencing. Project completion will also provide the applicant with training in computational modeling, psychophysical and EEG experiment design, data collection, analysis, and interpretation, as well as scientific hypothesis testing. This complements her existing background in signal processing and statistics, and will set her on a solid path towards her long-term goal of an academic research career in auditory neuroscience.

项目摘要/摘要 在噪音环境中与许多声音来源在听觉上提出了巨大的需求 系统。在这种情况下成功提取目标语音信息需要精确的结合 声音信息的耳蜗转移和神经编码，以及有效的下游认知过程 使用编码的信息来分离并有选择地处理感兴趣的目标语音。言语 因此 信息，或从认知能力下降。尽管这两个组成部分的存在很好 公认，目前尚无综合框架来量化每个框架的相对贡献 噪音中的语音清晰度，以及确定正在经历的个人中哪个方面不足 听力问题。该提案的具体目的旨在通过测量 神经生理学的神经生理学表示，并研究了这两个“底部”如何变化 在同一个人中进行的“操纵和“自上而下”的操作。首先，在编码中编码 脑干和皮层将使用脑电图（EEG）直接测量。脑电图指标将 然后通过研究演讲的呈现方式来与知觉的理解性联系在一起 背景噪声的不同级别和类型，以及它们如何在个人之间的群体（AIM 1）。接下来，为 同一个人，注意力集中在AIM 1的同一信封编码措施上的影响将是 通过保持输入语音混合物的恒定并操纵哪种语音来源来检查 选择性关注（目标2）。这种方法有助于隔离自上而下的组件。重要的是，进行全部 在同一单个受试者中的可理解性和脑电图测量使我们能够利用个人 差异并使用回归技术来表征自下而上和自上而下的相对贡献 性能的机制。最后，对于AIM 1中使用的语音噪声混合物，我们将计算相同的 在计算听觉障碍模型的输出时，包络编码指标（AIM 3）。关键机制 耳蜗功能障碍将纳入模型，以表征其对信封编码的影响 噪音的讲话。通过比较“模型”（AIM 3）和“神经”指标（AIMS 1和2），我们将测试是否测试 人工耳蜗机制可以解释自下而上编码的个体差异。知识获得了 通过拟议的一组实验将是客观诊断和开发的基础 针对单个患者是毫无疑问问题的特定性质量身定制的干预措施 体验。项目完成还将为申请人提供计算建模的培训， 心理物理和脑电图实验设计，数据收集，分析和解释以及科学 假设检验。这完成了她现有的信号处理和统计的背景，并将设置 她迈向了她在听觉神经科学领域的学术研究生涯的长期目标。