Hi all I am using the resting state MEG signal for constructing the inverse problem by eLoreta, and as it is resting state, the covariance matrix needs to be used, so I am going to use HCP R-noise to construct the covariance matrix, but there are two main issues which I need your help. 1- as I am going to use preprocess data for resting state, do I need process the noise as well? if it is so, I can't find the time series of the noise in the raw data after using ft_read_header. 2- do I need to redefine the time series which add the noise time series at the beginning of the signal and then add the resting state time series so I can use the below code for computing the covariance?
cfg= [] cfg.covariance = 'yes'; % I dont know how to enter the noise covariance to the data cfg.covariancewindow = [-inf 0]; timelockanalysis = ft_timelockanalysis(cfg, inputdata); I look forward to hearing from you. *Mehdy Dousty* *Hotchkiss Brain Institute* *University of Calgary* *HSC Building, Room 2932B* *3330 Hospital Drive NW* *Calgary, AB T2N 4N1* *Email [email protected]* _______________________________________________ HCP-Users mailing list [email protected] http://lists.humanconnectome.org/mailman/listinfo/hcp-users
