Neural Encoding and Connectivity in human speech perception

描述(由申请人提供)：定义支持言语和语言功能的基本神经机制是对诸如失语症或阅读障碍等沟通障碍的临床洞察的根本挑战。更好地理解言语的神经基础也可能导致神经假体设备的开发，以使影响沟通能力的神经障碍失效(例如，肌萎缩侧索硬化症或中风)。为了实现这些目标，必须解决两个关键挑战。首先，语音是如何通过皮质活动表现出来的？尽管说话者和环境条件有很大的差异，人类仍然能够流畅地理解语音，但支持这种不变识别能力的潜在神经表示从根本上是未知的。第二，大脑皮层语音表征的解剖学基础是什么？理论模型和非人类动物数据表明，听觉物体识别可能是按层次组织的，但人类大脑中是否存在这种结构仍不清楚。本项目将通过研究神经外科患者对用微电极阵列测量的语音的颅内(皮质脑电，ECoG)反应，来关注这两个关键问题，神经表征和连接性。在指导的K99阶段，第一个具体目标将使用神经编码模型方法来研究高阶听觉皮质中语音的神经表征。神经编码模型定量描述了特定大脑区域编码的语音特征，并预测了神经对新的语音刺激的反应。将通过将表示音素级别类别之间的声学不变性的语音模型与基于语音谱图的线性谱时间模型进行比较来测试分类语音表示的存在。在独立的R00阶段，第二个具体目标将使用电皮质刺激(ECS)和功能连接性分析来研究支持语音感知的神经回路的连接性。ECS直接映射受刺激的大脑部位的解剖连接，而功能连接分析确定这些 连接在语音感知过程中被调制。将连接图与拟合编码模型的特征选择性(目标1)进行比较，将提供高阶听觉皮质中语音表征的功能组织的全面视图。理解人类大脑皮层中语音识别的表征和连通性对于许多健康应用具有重要意义。精确的编码模型可以用于从神经活动中解码语音，并形成用于通信的假肢设备的基础。此外，绘制语音的功能组织图将允许在神经外科手术中更准确地确定关键的语音位置，并将提供对潜在沟通障碍(如失语症和发育性阅读障碍)的关键大脑区域和回路的洞察。

DESCRIPTION (provided by applicant): Defining the basic neural mechanisms supporting speech and language function is a fundamental challenge for clinical insights into communication disorders such as aphasia or dyslexia. Better understanding of the neural basis of speech may also lead to development of neural prosthetic devices for disabling neurological disorders affecting communication ability (e.g., ALS or stroke). To achieve these goals, two key challenges must be addressed. First, how is speech sounds represented by cortical activity? Humans fluidly understand speech despite large variations in speakers and environmental conditions, but the underlying neural representations that support this invariant recognition ability are fundamentally unknown. Second, what is the anatomical substrate of cortical speech representation? Theoretical models and nonhuman animal data suggest auditory object recognition may be organized hierarchically, but it remains unknown if this architecture is present in the human brain. This project will focus on these two key questions, neural representation and connectivity, by investigating intracranial (electrocorticographic, ECoG) responses to speech measured with microelectrode arrays in neurosurgical patients. During the mentored K99 phase, the first specific aim will investigate the neural representation of speech in higher order auditory cortex using a neural encoding model approach. A neural encoding model describes quantitatively what speech features are encoded by specific brain areas and predicts the neural response to novel speech stimuli. The presence of a categorical phonetic speech representation will be tested by comparing a phonetic model, which represents acoustic invariance among phone-level categories, to a linear spectrotemporal model based on the speech spectrogram. During the independent R00 phase, the second specific aim will investigate the connectivity of neural circuits supporting speech perception using electrical cortical stimulation (ECS) and functional connectivity analysis. ECS directly maps anatomical connectivity of stimulated brain sites, while functional connectivity analysis identifies how these connections are modulated during speech perception. Comparison of the connectivity maps to the feature selectivity of fitted encoding models (Aim 1) will provide a comprehensive view of the functional organization of speech representation in higher order auditory cortex. Understanding the representation and connectivity of speech recognition in human cortex has significant implications for a number of health applications. Accurate encoding models can be used to decode speech from neural activity and form the basis of prosthetic devices for communication. Furthermore, mapping the functional organization of speech will allow more precise determination of critical speech sites during neurosurgical procedures and will provide insights into key brain areas and circuits underlying communication disorders such as aphasia and developmental dyslexia.