rfchop_batch

 
  Specifications for batch processing data from selective attention to
  timbre study (ts1).

0001 %
0002 %  Specifications for batch processing data from selective attention to
0003 %  timbre study (ts1).
0004 %
0005 
0006 % 5/15/00 PJ - coded for Schubert study
0007 % 6/16/00 PJ - modfied for ts1 study
0008 % 2/19/01 PJ - modified for re-analysis.  Among other things, the model now has
0009 % a peak at the beginning of the attend conditions to better capture the
0010 % attentional orienting phase that most subjects report experiencing at the
0011 % beginning of the excerpt
0012 
0013 %
0014 %  GLOBAL variables
0015 %
0016 
0017 global subject_ids proc_subs use_model_proto sinfo
0018 global rootpath
0019 
0020 global COREG_WITH_MUTUAL_INFO        % Perform coregistration using mutual
0021                                         % information method rather than the
0022                                         % standard method.  This hopefully
0023                                         % overcomes some of the distortions due
0024                                         % to the FIL EPI template.
0025 
0026 global model_action regressors2add created_model_specs % these are initialized by RUN_MODEL
0027 global group_analyses            % group statistics analyses
0028 
0029 rootpath = '/data1/ts1/';
0030 
0031 %
0032 %  STRUCTURE CONTAINING LIST OF ANALYSES TO PERFORM
0033 %
0034 %  The analyses structure is created dynamically based on the list of desired
0035 %  analyses
0036 %
0037 
0038 SET_GENERAL_DEFS = 1;
0039 
0040 %
0041 % PREPROCESSING OPTIONS
0042 %
0043 
0044 REALIGN_EPI = 0;
0045 CREATE_MEAN_EPI = 0;
0046 
0047 COREG_WITH_MUTUAL_INFO = 1;
0048 COREG_MEAN_EPI = 0;
0049 COREG_FIRST_EPI = 0;            % I don't usually do this
0050 
0051 COREG_COPLANAR_2_HIRES = 0;
0052 COREG_HIRES_2_TEMPLATE = 0;            % I don't usually do this
0053 
0054 RESLICE_EPI = 0;            % I don't usually do this
0055 
0056 NORM_COPLANAR_2_TEMPLATE = 0;            % I don't usually do this
0057 
0058 NORM_EPI_2_TEMPLATE = 0;
0059 NORM_EPI_2_TEMPLATE_CUST_BB = 0;
0060 NORM_EPI_2_TEMPLATE_SPM99_DEF_BB = 0;    % This is the one I usually choose
0061 NORM_EPI_2_TEMPLATE_SPM99_BB4 = 0;
0062 
0063 NORM_HIRES_2_TEMPLATE = 0;    % You have to do this if your voxel size in
0064                                 % normalized hires volumes is smaller than the
0065                                 % voxel size in normalized EPI volumes
0066 
0067 SMOOTH_rEPI = 0;   % I don't usually do this because I haven't resliced
0068 SMOOTH_nEPI = 0;
0069 
0070 %
0071 % MODELLING OPTIONS
0072 %
0073 
0074 RUN_MODEL_INDIV = 0;            % Create and evaluate model of single
0075                                         % subject, unnormalized data
0076 RUN_MODEL_NORM = 0;            % Create and evaluate model of single
0077                                         % subject, normalized data (for group analyses)
0078     
0079 model_action = 'spec_and_estimate'; %{'specify','review','estimate','spec_and_estimate'}
0080 regressors2add = {'linear','motion'};
0081                     
0082 COMPUTE_CONTRASTS_INDIV = 0;
0083 COMPUTE_CONTRASTS_NORM = 1;
0084 
0085 COMPUTE_GROUP = 1;
0086 group_outdir = 'group';
0087 group_analysis_list = {'_all_t'};    % specify _all_t to do all
0088 
0089 THRESH_SUM = 0; THRESHSUM_CONTRAST=2;
0090 
0091 %
0092 %  SUBJECT INFO
0093 %
0094 sinfo = get_ts1_sinfo;
0095 
0096 subject_ids = cellstr(char(sinfo(:).id))
0097 
0098 nsub = length(subject_ids);
0099 proc_subs = [1:12]            % 1:12 - original, 13:17 - thin slices
0100 
0101 %proc_subs = [14 15];                % try non mutual info coreg w/IO and RP
0102 
0103 %
0104 %  LIST OF ANALYSIS TYPES
0105 %
0106 
0107 type = {'defaults_edit','model','contrasts','headers',...
0108 'means','realign','coreg','normalize','smooth','display','threshsum','stats'};
0109 
0110 %
0111 %  GROUP ANALYSIS PARAMETERS
0112 %
0113 
0114 anal_list = strvcat(type);
0115 
0116 analyses = struct('type',[],'index',[],'work_dir',[],'mfile',[]);
0117 
0118 na = length(analyses.type);
0119 
0120 %
0121 %  LIST OF WORK DIRECTORIES
0122 %
0123 
0124 work_dir = {rootpath, fullfile(rootpath, 'group'), ...
0125       };
0126 
0127 for isub = 1:nsub
0128   work_dir{end+1} = fullfile(rootpath, subject_ids{isub}, 'single');
0129 end
0130  
0131 for isub = 1:nsub
0132   work_dir{end+1} = fullfile(rootpath, subject_ids{isub}, 'normalized');
0133 end
0134 
0135 %
0136 %  SPECIFY ANALYSES TO RUN
0137 %
0138 
0139 if SET_GENERAL_DEFS
0140   disp('Will set general defaults ...')
0141   na = na+1;
0142   analyses.type(na) = strmatch('defaults_edit', anal_list,'exact');
0143   analyses.index(na) = 1;
0144   analyses.work_dir(na) = 1;
0145   analyses.mfile(na) = 1;   
0146 end
0147 
0148 if REALIGN_EPI
0149   disp('Will realign EPI runs ...')
0150   na = na+1;
0151   analyses.type(na) = strmatch('realign', anal_list,'exact');
0152   analyses.index(na) = 1;
0153   analyses.work_dir(na) = 1;
0154   analyses.mfile(na) = 2;
0155 end
0156 
0157 if CREATE_MEAN_EPI
0158   disp('Will create mean resliced EPI image ...')
0159   na = na+1;
0160   analyses.type(na) = strmatch('realign', anal_list,'exact');
0161   analyses.index(na) = 2;
0162   analyses.work_dir(na) = 1;
0163   analyses.mfile(na) = 2;
0164 end
0165 
0166 if COREG_MEAN_EPI
0167   disp('Will coregister mean EPI with coplanars ...')
0168   na = na+1;
0169   analyses.type(na) = strmatch('coreg', anal_list,'exact');
0170   analyses.index(na) = 1;
0171   analyses.work_dir(na) = 1;
0172   analyses.mfile(na) = 2;
0173 end
0174 
0175 if COREG_FIRST_EPI
0176   disp('Will coregister first EPI of first run with coplanars ...')
0177   na = na+1;
0178   analyses.type(na) = strmatch('coreg', anal_list,'exact');
0179   analyses.index(na) = 2;
0180   analyses.work_dir(na) = 1;
0181   analyses.mfile(na) = 2;
0182 end
0183 
0184 if COREG_COPLANAR_2_HIRES
0185    disp('Will coregister the coplanars to the hires  ...')
0186    na = na+1;
0187    analyses.type(na) = strmatch('coreg', anal_list,'exact');
0188    analyses.index(na) = 3;
0189    analyses.work_dir(na) = 1;
0190    analyses.mfile(na) = 2;
0191 end  
0192 
0193 if COREG_HIRES_2_TEMPLATE
0194    disp('Will coregister the hires to the template ...')
0195    na = na+1;
0196    analyses.type(na) = strmatch('coreg', anal_list,'exact');
0197    analyses.index(na) = 4; 
0198    analyses.work_dir(na) = 1;
0199    analyses.mfile(na) = 2;
0200 end
0201    
0202 if RESLICE_EPI
0203   disp('Will reslice EPI images ...')
0204   na = na+1;
0205   analyses.type(na) = strmatch('realign', anal_list, 'exact');
0206   analyses.index(na) = 3;
0207   analyses.work_dir(na) = 1;
0208   analyses.mfile(na) = 2;
0209 end
0210 
0211 
0212 if NORM_COPLANAR_2_TEMPLATE
0213   disp('will normalize coplanars to template (parameter&reslice) ... ')
0214   na = na+1;
0215   analyses.type(na) = strmatch('normalize', anal_list, 'exact');
0216   analyses.index(na) = 2;
0217   analyses.work_dir(na) = 1;
0218   analyses.mfile(na) = 2;
0219 end
0220 
0221 if NORM_EPI_2_TEMPLATE
0222   disp('will normalize EPIs to template (parameters&reslice) ... ')
0223   na = na+1;
0224   analyses.type(na) = strmatch('normalize', anal_list, 'exact');
0225   analyses.index(na) = 3;
0226   analyses.work_dir(na) = 1;
0227   analyses.mfile(na) = 2;
0228 end
0229 
0230 if NORM_EPI_2_TEMPLATE_CUST_BB
0231   disp('will normalize EPIs to template using custom bounding box(parameters&reslice) ... ')
0232   na = na+1;
0233   analyses.type(na) = strmatch('normalize', anal_list, 'exact');
0234   analyses.index(na) = 4;
0235   analyses.work_dir(na) = 1;
0236   analyses.mfile(na) = 2;  
0237 end
0238 
0239 if NORM_EPI_2_TEMPLATE_SPM99_DEF_BB
0240   disp('will normalize EPIs to template using SPM99 default bounding box (parameters&reslice) ... ')
0241   na = na+1;
0242   analyses.type(na) = strmatch('normalize', anal_list, 'exact');
0243   analyses.index(na) = 5;
0244   analyses.work_dir(na) = 1;
0245   analyses.mfile(na) = 2;  
0246 end
0247 
0248 if NORM_EPI_2_TEMPLATE_SPM99_BB4
0249   disp('will normalize EPIs to template using SPM99 bounding box 4 (parameters&reslice) ... ')
0250   na = na+1;
0251   analyses.type(na) = strmatch('normalize', anal_list, 'exact');
0252   analyses.index(na) = 6;
0253   analyses.work_dir(na) = 1;
0254   analyses.mfile(na) = 2;  
0255 end
0256 
0257 if NORM_HIRES_2_TEMPLATE 
0258   disp('will normalize hires to template (parameter&reslice) ... ')
0259   na = na+1;
0260   analyses.type(na) = strmatch('normalize', anal_list, 'exact');
0261   analyses.index(na) = 1;
0262   analyses.work_dir(na) = 1;
0263   analyses.mfile(na) = 2;
0264 end
0265   
0266 if SMOOTH_rEPI
0267   disp('will smooth resliced EPIs (individuals) ... ')
0268   na = na+1;
0269   analyses.type(na) = strmatch('smooth', anal_list, 'exact');
0270   analyses.index(na) = 1;
0271   analyses.work_dir(na) = 1;
0272   analyses.mfile(na) = 3;
0273 end
0274 
0275 if SMOOTH_nEPI 
0276   disp('will smooth normalized EPIs ... ')
0277   na = na+1;
0278   analyses.type(na) = strmatch('smooth', anal_list, 'exact');
0279   analyses.index(na) = 2;
0280   analyses.work_dir(na) = 1;
0281   analyses.mfile(na) = 3;
0282 end
0283 
0284 if RUN_MODEL_INDIV
0285   disp('will run model - individual data ...')
0286 
0287   use_model_proto = 1;
0288   
0289   nsub_proc = length(proc_subs);
0290   
0291   for isub = 1:nsub_proc
0292     na = na+1;
0293     analyses.type(na) = strmatch('model', anal_list, 'exact');
0294     analyses.index(na) = proc_subs(isub);
0295     work_dir_idx = 2*length(work_dir) - nsub + proc_subs(isub);
0296     analyses.work_dir(na) = work_dir_idx;
0297     analyses.mfile(na) = 4;
0298 
0299     % Create analysis directory for single subject data if necessary
0300     if ~exist(work_dir{work_dir_idx},'dir')
0301       disp(sprintf('Creating directory: %s', work_dir{work_dir_idx}))
0302       unix(['mkdir ' work_dir{work_dir_idx}]);
0303     end
0304   end
0305 end
0306 
0307 if RUN_MODEL_NORM
0308   disp('will run model - normalized data...')
0309 
0310   use_model_proto = 2;
0311 
0312   created_model_specs = 0;
0313   
0314   nsub_proc = length(proc_subs);
0315   
0316   for isub = 1:nsub_proc
0317     na = na+1;
0318     analyses.type(na) = strmatch('model', anal_list, 'exact');
0319     analyses.index(na) = proc_subs(isub);
0320     work_dir_idx = length(work_dir) - nsub + proc_subs(isub);
0321     analyses.work_dir(na) = work_dir_idx;
0322     analyses.mfile(na) = 5;
0323 
0324     % Create normalized directory if necessary
0325     if ~exist(work_dir{work_dir_idx},'dir')
0326       disp(sprintf('Creating directory: %s', work_dir{work_dir_idx}))
0327       unix(['mkdir ' work_dir{work_dir_idx}]);
0328     end
0329   end
0330 end
0331 
0332 if COMPUTE_CONTRASTS_INDIV
0333   disp('will compute contrasts - individual data ...')
0334 
0335   nsub_proc = length(proc_subs);
0336   
0337   for isub = 1:nsub_proc
0338     na = na+1;
0339     analyses.type(na) = strmatch('contrasts', anal_list, 'exact');
0340     analyses.index(na) = 1;
0341     work_dir_idx = 2*length(work_dir) - nsub + proc_subs(isub);
0342     analyses.work_dir(na) = work_dir_idx;
0343     analyses.mfile(na) = 6;
0344   end
0345 
0346 end
0347 
0348 if COMPUTE_CONTRASTS_NORM
0349   disp('will compute contrasts - normalized data ...')
0350 
0351   nsub_proc = length(proc_subs);
0352   
0353   for isub = 1:nsub_proc
0354     na = na+1;
0355     analyses.type(na) = strmatch('contrasts', anal_list, 'exact');
0356     analyses.index(na) = proc_subs(isub);
0357     work_dir_idx = length(work_dir) - nsub + proc_subs(isub);
0358     analyses.work_dir(na) = work_dir_idx;
0359     analyses.mfile(na) = 6;
0360   end
0361 
0362 end
0363 
0364 % NOTE: COMPUTE_GROUP has to come after models and contrasts otherwise working
0365 % directories get screwed up
0366 if COMPUTE_GROUP
0367   disp('will compute group statistics - normalized data ...')
0368     
0369   % Make sure the group directory exists
0370   groupdir = fullfile(rootpath, group_outdir);
0371   if ~exist(groupdir,'dir')
0372     disp(sprintf('Creating directory: %s', groupdir))
0373     unix(['mkdir ' groupdir]);
0374   end
0375 
0376   % if group_analyses is specified as '_all_t', then execute the contrasts
0377   % script to get all the names of the T contrasts and expand group_analyses to
0378   % include all of these
0379   
0380   ts1_contrasts
0381   
0382   if strmatch('_all_t', group_analysis_list, 'exact')
0383     ng = 0;
0384     for ic = 1:length(contrasts(1).names)
0385       if contrasts(1).types{ic} == 'T'
0386     ng = ng+1;
0387     group_analyses{ng} = contrasts(1).names{ic};
0388       end
0389     end
0390   else
0391     group_analyses = group_analysis_list;
0392   end
0393   
0394   ngroup_anal = length(group_analyses);
0395   
0396   for ig = 1:ngroup_anal
0397     
0398     % Set up the stats
0399     na = na+1;
0400     analyses.type(na) = strmatch('stats', anal_list, 'exact');
0401     analyses.index(na) = ig;
0402     work_dir{end+1} = fullfile(groupdir,group_analyses{ig});
0403     work_dir_idx = length(work_dir);
0404     analyses.work_dir(na) = work_dir_idx;
0405     if ~exist(work_dir{work_dir_idx},'dir')
0406       disp(sprintf('Creating directory: %s', work_dir{work_dir_idx}))
0407       unix(['mkdir ' work_dir{work_dir_idx}]);
0408     end
0409     analyses.mfile(na) = 10;
0410     
0411     % Compute the associated contrasts
0412     na = na+1;
0413     analyses.type(na) = strmatch('contrasts', anal_list, 'exact');
0414     analyses.index(na) = nsub+ig;
0415     analyses.work_dir(na) = work_dir_idx;
0416     analyses.mfile(na) = 6;
0417   end
0418 end
0419 
0420 if THRESH_SUM
0421     disp('will sum thresholded images ...')
0422     na = na+1;
0423     analyses.type(na) = strmatch('threshsum', anal_list, 'exact');
0424     analyses.index(na) = THRESHSUM_CONTRAST;
0425     analyses.work_dir(na) = 2;
0426     analyses.mfile(na) = 9;
0427 end
0428 
0429 %
0430 % SPECIFY MFILES ASSOCIATED WITH EACH ANALYSIS TYPE
0431 %
0432 % file names are either full pathname or relative to work_dir
0433 
0434 mfile = ...
0435     { '/data1/matlab/ts1/ts1_defaults.m', ...
0436       '/data1/matlab/ts1/ts1_realign.m', ...      
0437       '/data1/matlab/ts1/ts1_smooth.m', ...      
0438       '/data1/matlab/ts1/ts1_model_indiv.m', ...      
0439       '/data1/matlab/ts1/ts1_model_norm.m', ...      
0440       '/data1/matlab/ts1/ts1_contrasts.m', ...      
0441       '/data1/matlab/ts1/ts1_group.m', ...      
0442       '/data1/matlab/ts1/ts1_display.m', ...      
0443       '/data1/matlab/ts1/ts1_threshsum.m', ...      
0444       '/data1/matlab/ts1/ts1_stats.m' ...
0445       };
0446