{"title":"基于脑电/脑磁图数据和dMR信息的大型脑有效网络","authors":"Brahim Belaoucha, T. Papadopoulo","doi":"10.1109/PRNI.2017.7981511","DOIUrl":null,"url":null,"abstract":"Over the past 30 years, neuroimaging has become a predominant technique. One might envision that over the next years it will play a major role in disclosing the brain’s functional interactions. In this work, we use information coming from diffusion magnetic resonance imaging (dMRI) to reconstruct effective brain network from two functional modalities: electroencephalography (EEG) and magnetoencephalography (MEG).","PeriodicalId":429199,"journal":{"name":"2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Large brain effective network from EEG/MEG data and dMR information\",\"authors\":\"Brahim Belaoucha, T. Papadopoulo\",\"doi\":\"10.1109/PRNI.2017.7981511\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Over the past 30 years, neuroimaging has become a predominant technique. One might envision that over the next years it will play a major role in disclosing the brain’s functional interactions. In this work, we use information coming from diffusion magnetic resonance imaging (dMRI) to reconstruct effective brain network from two functional modalities: electroencephalography (EEG) and magnetoencephalography (MEG).\",\"PeriodicalId\":429199,\"journal\":{\"name\":\"2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PRNI.2017.7981511\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PRNI.2017.7981511","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Large brain effective network from EEG/MEG data and dMR information
Over the past 30 years, neuroimaging has become a predominant technique. One might envision that over the next years it will play a major role in disclosing the brain’s functional interactions. In this work, we use information coming from diffusion magnetic resonance imaging (dMRI) to reconstruct effective brain network from two functional modalities: electroencephalography (EEG) and magnetoencephalography (MEG).
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