Neurophysiological Mechanisms of Speech Intelligibility in Noise - A Quantitative Framework

项目总结/摘要 在具有许多声源的嘈杂环境中进行通信对听觉提出了巨大的要求 系统在这样的场景中成功地提取目标语音信息需要精确的 耳蜗传导和声音信息的神经编码，以及有效的下游认知过程 其使用编码的信息来分离和选择性地处理感兴趣的目标语音。在- 噪声问题（例如，在老年或听力损失），因此可能是由于受损的“自下而上”编码， 信息，或认知能力下降。虽然这两种成分的存在是好的， 认识到，目前还没有一个综合框架来量化每一个方面的相对贡献， 噪声中的语音可懂度，以及用于识别正在经历的个体的哪个方面有缺陷。 听力问题。本提案的具体目标是通过衡量 神经生理学表示的信封信息，并调查如何变化与“底部， “自上而下”的操纵和“自上而下”的操纵。首先， 将使用脑电图（EEG）直接测量脑干和皮层。EEG指标将 然后通过检查它们在语音呈现时如何协变来与感知可懂度联系起来。 不同水平和类型的背景噪音，以及它们如何在个体之间协变（目标1）。接下来，对于 同样的人，注意力集中在目标1相同的信封编码措施的影响将是 通过保持输入语音混合恒定并操纵哪个语音源是焦点来检查 选择性注意（目标2）。这种方法有助于隔离自上而下的组件。重要的是，所有 在同一个体受试者中的可懂度和EEG测量使我们能够利用个体 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 从机制到业绩。最后，对于目标1中使用的语音噪声混合物，我们将计算相同的 计算神经元模型输出端的包络编码度量（目标3）。关键机制 耳蜗功能障碍将被纳入模型，以表征其对包络编码的影响。 噪音中的言语通过比较“模型”（目标3）和“神经”指标（目标1和2），我们将测试 耳蜗机制可以解释自下而上编码中的个体差异。获得的知识 通过拟议的一系列实验，将是客观诊断发展的基础， 针对个体患者所面临的噪声中言语问题的特定性质而定制的干预措施 体验。项目完成还将为申请人提供计算建模方面的培训， 心理物理学和脑电图实验设计，数据收集，分析和解释，以及科学 假设检验这补充了她在信号处理和统计学方面的现有背景， 她在一个坚实的道路上对她的长期目标的学术研究生涯在听觉神经科学。

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.