Flexible representation of speech in human auditory cortex

项目总结/摘要 从声学到语言相关语音类别的映射并不固定;相反，语音识别 适应听力环境。例如，bear和pear的发音相差多达16个频谱时间 声学尺寸相对重要性（即，这些声学维度中每一个的感知权重 在信号熊与梨的变化与上下文因素，如是否收听环境是安静的， 是否嘈杂，以及说话者是否用本地口音或不熟悉的口音说话。这种灵活性或适应性可塑性是 重要的组成部分，大脑如何保持强大的语音感知，尽管相当大的变化， 语音声学事实上，不灵活的感觉处理被认为是两者知觉缺陷的来源。 听力障碍和神经系统疾病。然而，适应性可塑性的神经机制， 人们对语音感知知之甚少。为了解决这一差距，拟议的研究将利用访问 通过脑内立体定向脑电图（sEEG）获得的人类听觉皮层深处， 通过同时使用sEEG与头皮脑电图（EEG）和成熟的行为 测量适应性可塑性的任务。目的1将调用语音感知与声学自适应可塑性 噪声或模仿“口音”的短期输入分布的变化，并将 声学维度相对于基线的感知权重（即，清晰的语言）到神经系统的变化 听觉皮层的反应模式目标2将量化sEEG和 EEG以确定自适应可塑性的脑内特征与头皮EEG相关的程度 在一般人群中可测量的签名;这也将有助于EEG的区域特异性解释。 这项工作将提供新的见解皮层机制的适应性可塑性在言语知觉， 这对神经生物学模型和临床应用具有重要意义。我们的创新组合， 具有空间特异性、高信噪比sEEG的同步头皮EEG将创建高度信息化的 无创和颅内电生理学的联系。项目完成后还将提供申请人 接受过言语感知、脑内电生理学和方法的认知神经科学培训， 有效整合脑内和头皮EEG。这种训练将补充她的强壮 工程/定量背景和博士学位听觉时间编码、场景分析和EEG培训。 这将推进她在国际上成功开展独立学术研究事业的目标。 人类听觉和言语感知的神经科学。

PROJECT SUMMARY/ABSTRACT The mapping from acoustics to linguistically relevant speech categories is not fixed; rather, speech recognition adapts to listening context. For example, the utterances bear and pear differ by as many as 16 spectrotemporal acoustic dimensions. The relative importance (i.e., the perceptual weight) of each of these acoustic dimensions in signaling bear vs. pear changes with contextual factors like whether the listening environment is quiet or noisy and whether the talker speaks in a native or unfamiliar accent. This flexibility or adaptive plasticity is an important component of how the brain maintains robust speech perception despite considerable variation in speech acoustics. Indeed, inflexible sensory processing is implicated as a source of perceptual deficits in both hearing impairment and neurological disorders. Yet, the neural mechanisms underlying adaptive plasticity in speech perception are poorly understood. To address this gap, the proposed research will leverage access deep within human auditory cortex obtained through intracerebral stereotactic electroencephalography (sEEG), by employing sEEG simultaneously with scalp electroencephalography (EEG) and well-established behavioral tasks for measuring adaptive plasticity. Aim 1 will invoke adaptive plasticity in speech perception with acoustic noise or a change in short-term input distributions mimicking an ‘accent’ and will relate behavioral changes in the perceptual weights of acoustic dimensions relative to baseline (i.e., clear speech) to changes in the neural response profile across the auditory cortical hierarchy. Aim 2 will quantify the relationships between sEEG and EEG to establish the extent to which intracerebral signatures of adaptive plasticity relate to scalp EEG signatures measurable in the general population; this will also facilitate region-specific interpretation of EEG. The work will provide novel insight into the cortical mechanisms of adaptive plasticity in speech perception, with implications for neurobiological models and clinical applications. Our innovative combination of simultaneous scalp EEG with spatially specific, high signal-to-noise ratio sEEG will create a highly informative link across noninvasive and intracranial electrophysiology. Project completion also will provide the applicant with training in cognitive neuroscience of speech perception, intracerebral electrophysiology, and approaches to effectively integrate intracerebral and scalp EEG. This training will complement her strong engineering/quantitative background and Ph.D. training in auditory temporal coding, scene analysis, and EEG. This will advance her goal of undertaking a successful independent academic research career in the neuroscience of human audition and speech perception.