Neural mechanisms: Learned audio-visuo-motor integration

这项研究回答了大规模神经网络在人脑支持中的基本问题 跨通道认知。为了揭示听觉和视觉刺激以及运动行为是如何作为一种 跨通道学习的结果，并集成到超通道符号表征，我们将研究 罗马字母表中字母的神经表示。它们由四个单峰表示组成 (书写和说话的视觉、听觉和运动表征)和习得的联系 这些，也就是他们视听识别和马达生产的基础过程。准确 字母显示了符号的所有必要属性，这一事实促进了实验控制 跨通道表达，但在物理上简单而准确，没有语义关联 这可能会扰乱对结果的神经生理学解释。组合式3特斯拉功能磁铁 磁共振成像(FMRI)和306通道脑磁图/128通道 具有同步行为记录的脑电(MEG/EEG)技术将应用于 找出确切的潜在神经机制。这种方法结合了空间上的 精确的fMRI和时间上特定的脑磁图/脑电，使大脑的准确时空特征成为可能 完全非侵入性的活动。为了直接观察大规模神经认知网络是如何在 跨模式联想学习，我们还将在我们的治疗前后进行fMRI/MEG/EEG测量 科目是教授(以前不熟悉的)日语假名字母。其具体目的是为了澄清 完全建立的交叉模式神经网络的结构、功能和振荡机制 以前广泛的联想学习(罗马字母)和目前代表小说的不断发展的网络 跨模式协会(日文字母)。我们将描述大脑深部核团的相对作用， 小脑、内侧颞叶、感觉特异区和多感觉区 网络。多维实验设计允许隔离由 感知、工作记忆、记忆编码和回忆。

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 spatiotemproal 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.