The Neurophysiological Dynamics of Lexical and Sub-Lexical Representations

词汇和亚词汇表征的神经生理学动力学

• 批准号: 8751743
• 负责人: Matthew Kanter Leonard
• 金额: $ 5.6万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2015-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8751743
• 关键词: Access to Information; Acoustics; Aphasia; Area; Auditory; Autistic Disorder; Base of the Brain; Bilateral; Brain; Brain imaging; Characteristics; Chronic; Cochlear Implants; Code; Complex; Comprehension; Contralateral; Data; Diagnosis; Dimensions; Disease; Dyslexia; Electrocorticogram; Electrodes; Epilepsy; Feedback; Frequencies; Functional Magnetic Resonance Imaging; Hearing; Human; Image; Implant; Individual; Inferior; Injury; Intractable Epilepsy; Language; Language Development; Language Disorders; Lateral; Lead; Length; Linguistics; Magnetoencephalography; Methods; Modality; Participant; Patients; Pattern; Phonetics; Population; Population Control; Probability; Process; Property; Resolution; Sampling; Self-Help Devices; Semantics; Sensory; Series; Signal Transduction; Speech; Speech Disorders; Speech Perception; Speech Sound; Stimulus; Stream; Structure; Superior temporal gyrus; Surface; Techniques; Temporal Lobe; Time; Training; Translating; abstracting; cognitive function; density; developmental disease; encephalography; healthy volunteer; imaging modality; improved; indexing; language processing; lexical; lexical processing; meetings; millisecond; neurophysiology; prevent; public health relevance; relating to nervous system; response; sensory input; sound; spatiotemporal; specific language impairment; statistics

DESCRIPTION (provided by applicant): The broad objective of this proposal is to investigate how the brain constructs word-form and lexical representations of spoken words from lower-level acoustic-phonetic and phonemic information. The brain's ability to parse meaning from acoustic sensory inputs within a few hundred milliseconds may arise from multiple levels of representation that increase in abstraction as information is processed through local and long-distance cortical circuits in the classical language network. These processes will be studied using an integrated, multimodal neurophysiological approach that combines high-resolution invasive electrocorticography (ECoG) in epilepsy patients implanted with chronic subdural electrodes, and non-invasive magnetoencephalography (MEG), which provides whole-brain coverage of neural activity. The techniques are highly complementary and will provide unprecedented spatiotemporal resolution to characterize lexical processing as it unfolds on the millisecond level across adjacent neural populations. The primary analysis for ECoG and MEG data will involve constructing a neural "state-space", which represents the common activity across electrodes. Recently-developed methods allow the activity to be visualized in the state-space across time as neural trajectories. Participants will hear a list of words, each spoken by four different speakers, and the neural trajectories will be traced from the acoustic onset to the hypothesized lexical and semantic representations between 200-400ms later. It is hypothesized that different instances of the same word will begin in different parts of the state-space (due to acoustic differences across speakers), and will eventually converge into areas that represent neural activity associated with a particular lexical item. These analyses will be performed with data from ECoG in epilepsy patients, and will also be confirmed with healthy controls in MEG. MEG will provide additional information about these trajectories, since it is able to sample the entire cortex, and may detect relevant activity in areas that are not covered by the ECoG grids (for example, areas in the contralateral hemisphere). Finally, since the stimuli will be carefully controlled for linguistic features such as lexical frequency and phonotactic probability, it will b possible to examine how stimulus-level statistical properties are encoded by hypothesized prediction mechanisms in the brain. In general, these approaches will elucidate the processes of abstraction and higher-level representation for words in the brain, and will be among the first studies to characterize the neural code for speech perception from the perspective of dynamic, interactive processes. Understanding how the brain constructs word-level representations that contain a rich, malleable, and complex meaning is crucial for characterizing, diagnosing, and treating disorders that impair language learning and processing. It may also help improve assistive technologies like cochlear implants. The ability to decode neural representations at this level will further our understanding of fundamental brain processes that underlie many aspects of higher cognitive function.

描述（由申请人提供）：本提案的广泛目标是研究大脑如何从较低级别的声学语音和音素信息构建口语单词的单词形式和词汇表征。大脑在几百毫秒内从听觉感官输入中解析意义的能力可能源于多层次的表征，随着信息通过经典语言网络中的局部和长距离皮层回路进行处理，这些表征在抽象方面有所增加。这些过程将使用一种综合的多模式神经生理学方法进行研究，该方法将植入慢性硬膜下电极的癫痫患者的高分辨率侵入性皮层脑电图（ECoG）和非侵入性脑磁图（MEG）结合起来，后者提供神经活动的全脑覆盖。这些技术是高度互补的，并将提供前所未有的时空分辨率来表征词汇处理，因为它在相邻的神经种群之间的毫秒级上展开。对ECoG和MEG数据的主要分析将涉及构建神经“状态空间”，其表示跨电极的共同活动。最近开发的方法允许活动在状态空间中跨时间可视化为神经轨迹。参与者将听到一系列单词，每个单词由四个不同的说话者说出，神经轨迹将在200- 400 ms后从声学开始到假设的词汇和语义表征进行追踪。假设同一单词的不同实例将在状态空间的不同部分（由于说话者之间的声学差异）开始开始，并且将最终会聚到表示与特定词汇项相关联的神经活动的区域。这些分析将使用癫痫患者的ECoG数据进行，也将使用MEG中的健康对照进行确认。MEG将提供有关这些轨迹的额外信息，因为它能够对整个皮层进行采样，并且可以检测未被ECoG网格覆盖的区域中的相关活动（例如，对侧半球中的区域）。最后，由于刺激将被仔细控制的语言特征，如词频和语音的概率，它将B可能检查如何刺激水平的统计特性编码的假设预测机制在大脑中。总的来说，这些方法将阐明大脑中单词的抽象和更高层次的表征过程，并将成为从动态交互过程的角度来表征语音感知神经代码的首批研究之一。了解大脑如何构建包含丰富，可塑性和复杂意义的单词级表征对于表征，诊断和治疗损害语言学习和处理的疾病至关重要。它还可能有助于改善人工耳蜗等辅助技术。这种解码神经表征的能力 这一水平将进一步加深我们对大脑基本过程的理解，这些过程是高级认知功能许多方面的基础。