generates 'music playing' block-type regressors for fmri data [names,vals] = fmri_regress_music_playing(pinfo,minfo,sess) called by fmri_generate_regress REQUIRES RETURNS names = cell array of six regressor names vals = volume X regressor matrix containing motion regressors FB 2009.11.05
0001 function [names,vals] = fmri_regress_music_playing(pinfo,minfo,sess) 0002 0003 % generates 'music playing' block-type regressors for fmri data 0004 % 0005 % [names,vals] = fmri_regress_music_playing(pinfo,minfo,sess) 0006 % 0007 % called by fmri_generate_regress 0008 % 0009 % REQUIRES 0010 % 0011 % RETURNS 0012 % names = cell array of six regressor names 0013 % vals = volume X regressor matrix containing motion regressors 0014 % 0015 % FB 2009.11.05 0016 0017 % init output vars 0018 names = {'music_playing'}; 0019 vals = []; 0020 0021 % get presentation data, stimulus onsets 0022 sfilt.include.all = minfo.response_filter; 0023 sinfo = ensemble_filter(pinfo,sfilt); 0024 sc = set_var_col_const(sinfo.vars); 0025 onsets = sinfo.data{sc.RUN_REL_TIME}/1000; 0026 0027 % Durations and amplitude 0028 durs = ones(size(onsets))*minfo.music_dur; 0029 amp = ones(size(onsets)); 0030 0031 % Now build the regressor 0032 vals = fmri_convolve_regress(onsets,durs,amp,... 0033 pinfo.scanner.TR,pinfo.scanner.dt,pinfo.scanner.actual_nvol);