Neural mechanisms: Learned audio-visuo-motor integration

神经机制：习得的视听运动整合

• 批准号: 7166038
• 负责人: JOHN W BELLIVEAU
• 金额: $ 70.22万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7166038
• 关键词: Adult; Area; Association Learning; Auditory; Automobile Driving; Behavioral; Binding; Biological Neural Networks; Brain; Cell Nucleus; Cerebellum; Cognition; Complement; Computer Simulation; Data; Data Analyses; Data Collection; Databases; Depth; Development; Diffusion; Distant; Educational process of instructing; Electroencephalography; Equation; Etiology; Exhibits; Experimental Designs; Functional Magnetic Resonance Imaging; Goals; Human; Image; Individual; Japanese Population; Language; Learning; Letters; Magnetic Resonance Imaging; Magnetoencephalography; Measurement; Medial; Methods; Modality; Modeling; Monitor; Motor; Motor Cortex; Names; Network-based; Neurocognitive; Neurosciences; Output; Perception; Phase; Process; Production; Property; Psychophysiology; Range; Reading; Relative (related person); Research; Research Personnel; Role; Semantics; Sensory; Short-Term Memory; Signal Transduction; Stimulus; Structure; System; Techniques; Temporal Lobe; Testing; Time; Visual; Work; Writing; abstracting; association cortex; base; classical conditioning; long term memory; memory encoding; millimeter; millisecond; neuroinformatics; neuromechanism; neurophysiology; novel; relating to nervous system; response; spatiotemporal; visual motor; visual stimulus

DESCRIPTION (provided by applicant): This study answers fundamental questions of large-scale neural networks in the human brain supporting crossmodal cognition. To reveal how auditory and visual stimuli and motor acts are arbitrarily combined as a result of crossmodal learning and integrated to supramodal symbolic representations, we will study the neural representations of the letters of the Roman alphabet. These consist of four unimodal representations (visual, auditory, and motor representations for writing and speaking) and learned connections between these, that is, the processes that underlie their audiovisual recognition and motor production. Accurate experimental control is facilitated by the fact that letters exhibit all the necessary properties of symbolic crossmodal representations but in a physically simple and exact format carrying no semantic associations that could confound the neurophysiological interpretation of results. Combined 3-Tesla functional magnetic resonance imaging (fMRI) and 306-channel magnetoencephalographic / 128-channel electroencephalographic (MEG/EEG) techniques with simultaneous behavioral recordings will be applied to pinpoint the exact underlying neural mechanisms. This approach combines the advantages of spatially accurate fMRI with temporally specific MEG/EEG, enabling accurate spatiotemporal characterization of brain activity totally noninvasively. To directly observe how large-scale neurocognitive networks evolve during crossmodal associative learning, we will also conduct fMRI/MEG/EEG measurements before and after our subjects are taught (previously unfamiliar) Japanese kana-letters. The specific aims are to elucidate structure, function, and oscillatory mechanisms of fully established crossmodal neural networks based on previous extensive associative learning (Roman letters) and currently evolving networks representing novel crossmodal associations (Japanese letters). We will characterize the relative roles of deep brain nuclei, cerebellum, medial temporal lobe, and sensory-specific and multisensory association cortices in such networks. The multidimensional experimental design allows isolation of neural mechanisms utilized by perception, working memory, memory encoding, and recall.

描述（由申请人提供）：本研究回答了支持跨模式认知的人脑大脑中大规模神经网络的基本问题。为了揭示通过跨模式学习而任意合并的听觉和视觉刺激和运动行为并将其整合到超大型符号表示形式中，我们将研究罗马字母的字母的神经表示。这些由四个单峰表示（视觉，听觉和运动表示）组成，并学到了它们之间的联系，即其视听识别和运动产生的过程。准确的实验控制促进了以下事实：字母表现出符号交叉模式表示的所有必要特性，但在物理上简单且精确的格式中，没有任何语义关联可以混淆结果的神经生理解释。结合使用同时行为记录的组合3-TESLA功能磁共振成像（fMRI）和306通道磁脑电图 / 128通道脑电图（MEG / EEG）技术将应用于同时行为记录。这种方法将空间精确的fMRI的优势与时间特定的MEG/EEG结合在一起，从而完全无创地实现了脑活动的准确时空表征。为了直接观察在跨模式关联学习过程中大规模的神经认知网络的发展，我们还将在教授受试者（以前不熟悉的日本卡纳语言）之前和之后进行fMRI/MEG/EEG测量。具体目的是阐明基于以前的广泛关联学习（罗马字母）以及目前代表新型跨模式关联（日本字母）的目前不断发展的网络的完全建立的跨模式神经网络的结构，功能和振荡机制。我们将表征深脑核，小脑，内侧颞叶和感觉特异性和多感官关联皮层在此类网络中的相对作用。多维实验设计允许通过感知，工作记忆，记忆编码和召回来隔离神经机制。