{"title":"A New Application of MEG and DTI on Word Recognition","authors":"Lu Meng, J. Xiang, Dazhe Zhao, Hong Zhao","doi":"10.1109/ICPR.2010.605","DOIUrl":null,"url":null,"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.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 20th International Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2010.605","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.