The spatiotemporal dynamics of cortical speech representation

皮层言语表征的时空动态

• 批准号: 8783620
• 负责人: J Liberty S Hamilton
• 金额: $ 4.99万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2017-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8783620
• 关键词: Acoustics; Anatomy; Anterior; Aphasia; Area; Auditory area; Autistic Disorder; Base of the Brain; Basic Science; Brain; Categories; Clinical; Cochlear Implants; Code; Communication impairment; Complement; Complex; Computing Methodologies; Coupled; Data; Development; Diagnosis; Dimensions; Dyslexia; Electrocorticogram; Electrodes; Electroencephalography; Epilepsy; Exhibits; Frequencies; Functional Magnetic Resonance Imaging; Gender; Goals; Human; Implant; Implanted Electrodes; Intractable Epilepsy; Joints; Language Development; Language Disorders; Lead; Learning; Linear Models; Linear Regressions; Linguistics; Maps; Measures; Methods; Modeling; Neurons; Noise; Non-linear Models; Participant; Patients; Pattern; Pharmaceutical Preparations; Phase; Phonetics; Population; Process; Property; Reaction Time; Refractory; Research; Resolution; Signal Transduction; Site; Speech; Speech Perception; Speech Sound; Stimulus; Stream; Superior temporal gyrus; Surface; Temporal Lobe; Time; Voice; Work; awake; base; brain machine interface; cell assembly; density; design; human subject; improved; millimeter; millisecond; neural circuit; neurophysiology; public health relevance; receptive field; relating to nervous system; research study; response; sound; spatiotemporal; speech processing; vector

DESCRIPTION (provided by applicant): The purpose of the proposed research is to investigate the organization of speech sound representation across the auditory cortex and the spatiotemporal interactions between cortical areas during speech perception. The brain's ability to parse meaning from incoming acoustic information arises from complex interactions within cortical networks, but how these networks are organized remains unclear. High-density intracranial electrocorticography (ECoG) will be used to record neural activity from speech-selective areas in the auditory cortex of awake, behaving human subjects. These subjects are patients with medication refractory epilepsy who have electrodes implanted based on clinical criteria. By combining multiple computational approaches this work will elucidate (1) the acoustic feature selectivity of single electrodes on the ECoG array, (2) the spatial organization of this feature selectivity, and (3) the spatiotemporal dynamics of neural population responses to speech sounds, with the goal of uncovering emergent properties within the population level analysis that cannot be recovered from single sites alone. Participants will listen passively to sentences spoken by a variety of speakers and of different genders while the ECoG signal is recorded. Additional sound stimuli will include environmental sounds and modulation limited noise ripples. Spectrotemporal receptive field models will be built from the neural responses to these sentences using maximally informative dimensions (MID) analysis and different parameterizations of the sound stimuli, including decomposition of the sounds into their corresponding spectrotemporal modulations and identification of the presence or absence of linguistic parameters such as manner of articulation. This will uncover the selectivity of each sit for low-level and high-level sound features as well as the organization of this selectivity across the anatomy of the cortical surface. Comparing this mapping for different types of sound stimuli will reveal whether organization differs for speech and non-speech sounds, or whether organization is based purely on acoustic properties of the sound signal. Vector autoregressive models and phase coupled oscillator models will be used to describe population-level interactions within areas of the auditory cortex. These interactions may manifest as speech-dependent cell assemblies across space that segregate processing for different phonetic features that cannot be uncovered at the single electrode level. Results from these experiments have implications for understanding neural coding as a whole, and will reveal the importance of population activity versus single electrode computations in speech processing. Elucidating how the brain represents low-level and high-level features important for speech is critical for understanding, diagnosing, and treating communication disorders including delayed language learning, aphasias, dyslexia, and autism. In addition, this work may help to improve brain machine interface design, including cochlear implants.

描述（由申请人提供）：拟议研究的目的是调查听觉皮层语音表征的组织以及语音感知过程中皮层区域之间的时空相互作用。大脑从传入的声音信息中解析含义的能力源于皮质网络内复杂的相互作用，但这些网络是如何组织的仍不清楚。高密度颅内皮层电图（ECoG）将用于记录清醒、有行为的人类受试者听觉皮层言语选择性区域的神经活动。这些受试者是药物难治性癫痫患者，根据临床标准植入了电极。通过结合多种计算方法，这项工作将阐明（1）ECoG 阵列上单个电极的声学特征选择性，（2）该特征选择性的空间组织，以及（3）神经群体对语音反应的时空动态，其目标是揭示群体水平分析中无法单独从单个站点恢复的新兴属性。在记录 ECoG 信号的同时，参与者将被动地聆听不同性别的不同说话者所说的句子。额外的声音刺激将包括环境声音和调制受限的噪声波纹。谱时感受野模型将使用最大信息维度（MID）分析和声音刺激的不同参数化，根据对这些句子的神经反应来构建，包括将声音分解为其相应的谱时调制以及识别语言参数（例如发音方式）是否存在。这将揭示每个位置对低级和高级声音特征的选择性，以及这种选择性在皮质表面解剖结构中的组织。比较不同类型声音刺激的映射将揭示语音和非语音的组织是否不同，或者组织是否纯粹基于声音信号的声学特性。矢量自回归模型和相位耦合振荡器模型将用于描述听觉皮层区域内的群体水平相互作用。这些相互作用可能表现为跨空间的语音依赖性细胞组装，这些细胞组装分离了对不同语音特征的处理，而这些语音特征无法在单个电极水平上发现。这些实验的结果对于理解整个神经编码具有重要意义，并将揭示群体活动与单电极计算在语音处理中的重要性。阐明大脑如何代表对言语很重要的低级和高级特征对于理解、诊断和治疗沟通障碍（包括语言学习延迟、失语症、阅读障碍和自闭症）至关重要。此外，这项工作可能有助于改进脑机接口设计，包括人工耳蜗。