Neural mechanisms: Learned audio-visuo-motor integration

描述(申请人提供)：这项研究回答了人脑中支持跨模式认知的大规模神经网络的基本问题。为了揭示听觉、视觉刺激和运动行为如何作为跨通道学习的结果被任意组合，并整合到超通道符号表征中，我们将研究罗马字母表中字母的神经表征。这些包括四种单峰表征(用于书写和说话的视觉、听觉和运动表征)和它们之间的习得联系，也就是他们的视听识别和运动产生的基础过程。准确的实验控制是因为字母表现出符号交叉模式表征的所有必要属性，但以物理上简单和准确的格式，没有可能混淆结果的神经生理学解释的语义联系。3-特斯拉功能磁共振成像(FMRI)和306通道脑磁图/128通道脑电(MEG/EEG)技术与同步行为记录相结合，将被用于精确定位潜在的神经机制。这种方法结合了空间上精确的fMRI和时间上特定的脑磁图/脑电的优点，能够完全非侵入性地准确地描述大脑活动的时空特征。为了直接观察大规模神经认知网络在跨模式联想学习过程中的演变，我们还将在受试者学习(以前不熟悉的)日语假名字母之前和之后进行fMRI/MEG/EEG测量。其具体目的是阐明完全建立的跨模式神经网络的结构、功能和振荡机制，该网络基于先前的广泛联想学习(罗马字母)和当前代表新的跨模式联想的网络(日语字母)。我们将描述大脑深部核团、小脑、内侧颞叶以及特定感觉和多感觉联合皮质在这些网络中的相对作用。多维实验设计允许分离感知、工作记忆、记忆编码和回忆所使用的神经机制。

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.