Flexible representation of speech in human auditory cortex

项目摘要/摘要 从声学到语言相关的语音类别的映射并不是固定的；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个频域 声学尺寸。这些声学维度中每一个的相对重要性(即知觉权重 在发出信号时，熊与梨会随着语境因素的变化而变化，比如听的环境是安静的还是 嘈杂，以及说话者说话时是母语口音还是陌生口音。这种灵活性或适应性可塑性是一种 大脑如何保持强大的言语知觉的重要组成部分，尽管在 语音声学。事实上，僵化的感觉处理被认为是两者知觉缺陷的一个来源 听力障碍和神经紊乱。然而，适应性可塑性背后的神经机制 人们对言语感知知之甚少。为了解决这一差距，拟议的研究将利用访问 在通过脑内立体定向脑电(SEEG)获得的人类听觉皮质深处， 通过同时使用sEEG和头皮脑电(EEG)和良好的行为 测量适应性可塑性的任务。目标1将在语音感知中启用声学自适应可塑性 噪声或短期输入分布的变化，模仿口音，并将行为变化与 声学维度相对于基线(即清晰的语音)相对于神经变化的知觉权重 整个听觉皮质层级的反应轮廓。目标2将量化sEEG和 EEG以确定脑内适应性可塑性特征与头皮EEG的关系程度 可在普通人群中测量到的特征；这也将促进对脑电的特定区域解释。 这项工作将为语音感知中自适应可塑性的皮质机制提供新的见解， 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 同时头皮脑电与空间特定的，高信噪比脑电将创造一个高度信息量 与非侵入性和颅内电生理学有关。项目完成也将为申请者提供 接受过语言感知、脑内电生理学和方法方面的认知神经科学培训 为了有效地整合脑内和头皮脑电。这次训练将补充她的强项。 在听觉时间编码、场景分析和脑电方面的工程/定量背景和博士培训。 这将推进她的目标，即在 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.