fmri_regress_velten_onset

 generates fmri data regressors for onset of velten sentence stimuli
 
   [names,vals] = fmri_regress_velten_onset(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 2010.03.16

0001 function [names,vals] = fmri_regress_velten_onset(pinfo,minfo,sess)
0002 
0003 % generates fmri data regressors for onset of velten sentence stimuli
0004 %
0005 %   [names,vals] = fmri_regress_velten_onset(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 2010.03.16
0016 
0017 % init output vars
0018 names = {};
0019 vals = [];
0020 
0021 if isempty(strfind(pinfo.presfname,'velten')), return, end
0022 
0023 onfilt.include.all.EVENT_CODE = {'pic_*'};
0024 onfilt.include.all.EVENT_TYPE = {'Picture'};
0025 ondata = ensemble_filter(pinfo,onfilt);
0026 pc = set_var_col_const(pinfo.vars);
0027 ons = ondata.data{pc.RUN_REL_TIME}/1000;
0028 nons = length(ons);
0029 
0030 if ~nons
0031   fprintf(1,'%s regressor skipped: no onsets found\n',regid);
0032   return
0033 end
0034 
0035 names = {pinfo.regid};
0036 
0037 % calculate durations, amplitude
0038 amp = ones(1,nons);
0039 durs = amp';
0040 
0041 % Now build the regressor
0042 vals = fmri_convolve_regress(ons,durs,amp,pinfo.scanner.TR,...
0043     pinfo.scanner.dt,pinfo.scanner.actual_nvol);