{"title":"癫痫患者脑功能连通性的EEG-fMRI测量","authors":"Teresa Murta, P. Figueiredo, A. Leal","doi":"10.1109/ENBENG.2011.6026094","DOIUrl":null,"url":null,"abstract":"A study of the epileptic seizure dynamics using simultaneous recording of electroencephalography correlated functional magnetic resonance imaging (EEG-fMRI) data from 5 focal epilepsy patients undergoing pre-surgical evaluation was realised with the aim of identifying the focus and propagation network seizure-involved. A method based on the General Linear Model (GLM) at different neurophysiology regressor lags (LasgM), a connectivity model-based method, Dynamic Causal Modelling (DCM), and a data-driven method, Granger Causality (GC) were investigated. DCM analysis provided meaningful and significant results when a sufficient number of seizure events was recorded, but suffered from the generally poor data signal-to-noise ratio (SNR). The concordance between the LagsM results and the clinical expectation suggests that LagsM can be useful as a complementary approach. Intending to establish the validity of a GC approach for the problem addressed, a simulation study was performed and the results showed that it is not appropriated.","PeriodicalId":206538,"journal":{"name":"1st Portuguese Biomedical Engineering Meeting","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"EEG-fMRI measures of functional brain connectivity in epilepsy\",\"authors\":\"Teresa Murta, P. Figueiredo, A. Leal\",\"doi\":\"10.1109/ENBENG.2011.6026094\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A study of the epileptic seizure dynamics using simultaneous recording of electroencephalography correlated functional magnetic resonance imaging (EEG-fMRI) data from 5 focal epilepsy patients undergoing pre-surgical evaluation was realised with the aim of identifying the focus and propagation network seizure-involved. A method based on the General Linear Model (GLM) at different neurophysiology regressor lags (LasgM), a connectivity model-based method, Dynamic Causal Modelling (DCM), and a data-driven method, Granger Causality (GC) were investigated. DCM analysis provided meaningful and significant results when a sufficient number of seizure events was recorded, but suffered from the generally poor data signal-to-noise ratio (SNR). The concordance between the LagsM results and the clinical expectation suggests that LagsM can be useful as a complementary approach. Intending to establish the validity of a GC approach for the problem addressed, a simulation study was performed and the results showed that it is not appropriated.\",\"PeriodicalId\":206538,\"journal\":{\"name\":\"1st Portuguese Biomedical Engineering Meeting\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1st Portuguese Biomedical Engineering Meeting\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ENBENG.2011.6026094\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1st Portuguese Biomedical Engineering Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ENBENG.2011.6026094","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
EEG-fMRI measures of functional brain connectivity in epilepsy
A study of the epileptic seizure dynamics using simultaneous recording of electroencephalography correlated functional magnetic resonance imaging (EEG-fMRI) data from 5 focal epilepsy patients undergoing pre-surgical evaluation was realised with the aim of identifying the focus and propagation network seizure-involved. A method based on the General Linear Model (GLM) at different neurophysiology regressor lags (LasgM), a connectivity model-based method, Dynamic Causal Modelling (DCM), and a data-driven method, Granger Causality (GC) were investigated. DCM analysis provided meaningful and significant results when a sufficient number of seizure events was recorded, but suffered from the generally poor data signal-to-noise ratio (SNR). The concordance between the LagsM results and the clinical expectation suggests that LagsM can be useful as a complementary approach. Intending to establish the validity of a GC approach for the problem addressed, a simulation study was performed and the results showed that it is not appropriated.