Neural mechanisms: Learned audio-visuo-motor integration

神经机制：习得的视听运动整合

• 批准号: 7033274
• 负责人: JOHN W BELLIVEAU
• 金额: $ 71.54万
• 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/7033274
• 关键词: association learning; behavioral /social science research tag; bioimaging /biomedical imaging; brain electrical activity; brain imaging /visualization /scanning; brain mapping; clinical research; computational neuroscience; functional magnetic resonance imaging; human subject; magnetoencephalography; memory; neural information processing; neuropsychology; nonEnglish language; psychomotor function; psychophysiology; sound perception; speech; verbal behavior; visual perception

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（申请人提供）：本研究回答了人脑中支持跨模态认知的大规模神经网络的基本问题。为了揭示听觉和视觉刺激和运动行为是如何作为跨模态学习的结果任意组合并整合到超模态符号表征中，我们将研究罗马字母的神经表征。这些包括四种单模态表征（写作和说话的视觉、听觉和运动表征）以及这些表征之间的习得联系，即构成其视听识别和运动产生的过程。字母表现出符号跨模态表征的所有必要属性，但在物理上简单而精确的格式中没有可能混淆神经生理学结果解释的语义关联，这一事实有助于精确的实验控制。结合3-特斯拉功能磁共振成像（fMRI）和306通道脑磁图/ 128通道脑电图（MEG/EEG）技术，同时进行行为记录，以查明确切的潜在神经机制。该方法结合了空间精确的fMRI和时间特异性的MEG/EEG的优势，使大脑活动的准确时空特征完全无创。为了直接观察跨模态联想学习过程中大规模神经认知网络的演变，我们还将在受试者学习（之前不熟悉的）日语假名字母之前和之后进行fMRI/MEG/EEG测量。具体目的是阐明基于先前广泛的联想学习（罗马字母）和当前发展的网络代表新的跨模态关联（日本字母）的完全建立的跨模态神经网络的结构、功能和振荡机制。我们将描述脑深部核、小脑、内侧颞叶、感觉特异性和多感觉关联皮层在这些网络中的相对作用。多维实验设计允许隔离感知、工作记忆、记忆编码和回忆所利用的神经机制。