AUDIOVISUAL INTEGRATION, AGE, AND HEARING LOSS

摘要 如果听力受损的人能够使用视觉信号来识别，他们可能会受益良多 演讲。可悲的是，随着人们年龄的增长，他们经常会经历听力和听力的下降 他们的唇读能力，这样他们的视听语音感知就可以 最大限度地受益于视觉语音信息，他们利用它的能力最低。理解 这些现象之间的联系一直是两种认知能力的长期挑战 科学和听觉康复，但我们认为这种联系提供了一条重要线索 理解日常言语感知中的个体差异和年龄差异。多数 研究人员假设存在一个明显的整合阶段，而且整合能力 随着年龄的增长而减少。然而，我们最新的发现表明，单峰频率的差异 表现，而不是综合能力的差异，是个人和年龄相关的基础 视听言语知觉的差异。因此，拟议的研究采取了 既关注唇读技能个体差异的原因，又关注唇读技能个体差异的独特方法 论唇读作为视听言语知觉差异的原因。对于具体目标1，我们 将使用我们的新特征分析方法来预测视听语音感知 参与者的单峰(即纯听觉和纯视觉)表现。我们将评估 认知能力、知觉能力、言语能力和凝视能力的相对贡献 视听言语中个体差异和年龄差异的行为 感知力。对于特定的目标2，我们将使用我们的语音检测和口述的修改- 自己的任务，以及功能磁共振成像，以评估之间的对应关系的差异 支持语音产生和感知的语音表示法。最后，对于目标3，我们 将使用fMRI识别纯视觉和视听语音感知的神经关联。这个 目标1和目标2的结果将帮助我们确定感兴趣的区域。我们将专注于发动机前置 因为我们假设言语产生和视觉言语之间的联系 感知对于理解人们如何识别视觉语音信号至关重要，我们将 直接比较言语产生和感知过程中运动前皮质的激活 使用代表性相似性分析，这是一种优雅的多变量分析技术。到了最后 在赠款周期中，我们的目标是开发一个统一的神经认知框架 理解唇读和视听言语的个体差异和年龄差异 感知力。这一框架和我们的实验结果也将提供基于证据的 为言语感知训练和听觉康复咨询提供指导。

ABSTRACT People with hearing loss might benefit greatly if they could use the visual signal to recognize speech. Sadly, as people age, they often experience a decline in both their hearing ability and their lipreading ability, so that at the very time their audiovisual speech perception could maximally benefit from visual speech information, they are least able to utilize it. Understanding the linkage between these phenomena has been a longstanding challenge for both cognitive science and aural rehabilitation, yet we believe this linkage provides a major clue to understanding both individual and age-related differences in everyday speech perception. Most researchers assume that there is a distinct integration stage and that integrative ability diminishes with age. Our most recent findings, however, suggest that differences in unimodal performance, and not differences in integrative abilities, underlie both individual and age-related differences in audiovisual speech perception. Accordingly, the proposed research takes the unique approach of focusing on both the causes of individual differences in lipreading skill and on lipreading as a cause of differences in audiovisual speech perception. For Specific Aim 1, we will use our new feature analysis methods to predict audiovisual speech perception based on participants' unimodal (i.e., auditory-only and vision-only) performance. We will evaluate the relative contributions of cognitive, perceptual, and speech production abilities as well as gaze behavior to both individual and age-related differences in vision-only and audiovisual speech perception. For Specific Aim 2, we will use a modification of our speech detection and lipread- yourself tasks, along with fMRI, to assess differences in the correspondence between the phonetic representations that support speech production and perception. Finally, for Aim 3, we will identify neural correlates of vision-only and audiovisual speech perception using fMRI. The results from Aims 1 and 2 will help us identify the regions of interest. We will focus on premotor areas because we hypothesize that the linkage between speech production and visual speech perception is critical for understanding how people recognize visual speech signals, and we will directly compare the activation in premotor cortex during both speech production and perception using representational similarity analysis, an elegant multi-variate analytic technique. By the end of the grant cycle, our goal is to have developed a unified neurocognitive framework for understanding both individual and age-related differences in lipreading and audiovisual speech perception. This framework and our experimental results will also provide evidence-based guidance for both speech perception training and aural rehabilitation counselling.