A New Application of MEG and DTI on Word Recognition

Lu Meng, J. Xiang, Dazhe Zhao, Hong Zhao
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Abstract

This paper presented a novel application of Magneto encephalography (MEG) and diffusion tensor image (DTI) on word recognition, in which the spatiotemporal signature and the neural network of brain activation associated with word recognition were investigated. The word stimuli consisted of matched and mismatched words, which were visually and acoustically presented simultaneously. Twenty participants were recruited to distinguish and gave different reactions to these two types of stimuli. The neural activations caused by their reactions were recorded by MEG system and 3T magnetic DTI scanner. Virtual sensor technique and wavelet beam former source analysis, which were state-of-the-art methods, were used to study the MEG and DTI data. Three responses were evoked in the MEG waveform and M160 was identified in the left temporal-occipital junction. All the results coincided with the previous studies’ conclusions, which indicated that the integration of virtual sensor and wavelet beam former were effective techniques in analyzing the MEG and DTI data.
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MEG和DTI在单词识别中的新应用
本文提出了脑磁图(MEG)和弥散张量图像(DTI)在词识别中的新应用,研究了词识别过程中脑活动的时空特征和神经网络。单词刺激包括匹配和不匹配的单词,这些单词在视觉和听觉上同时呈现。20名参与者被招募来区分这两种类型的刺激,并给出不同的反应。脑磁图系统和3T磁DTI扫描仪记录了反应引起的神经激活。采用虚拟传感器技术和小波波束前源分析技术对脑磁图和DTI数据进行了研究。在脑磁图波形中诱发了三种反应,并在左侧颞枕交界处识别出M160。这些结果与前人的研究结论一致,表明虚拟传感器与小波波束成原相结合是分析脑磁图和DTI数据的有效技术。
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