Merge branch 'develop' into 'master'

Including the outlier censoring.

.gitignore

@@ -1,3 +1,9 @@
 mccExcludedFiles.log
 readme.txt
 requiredMCRProducts.txt
+bin/
+templates/parcellations/
+*.asv
+*.nii
+*.mat
+._*

matlab_code/analyses_v2.m

@@ -101,17 +101,41 @@ function analyses_v2(config_path)
 
     disp('subject_motion_numbers_TXT_parse_BIDS complete')
 
-    subject_power_2014_FD_only_parse_BIDS(FD_movement_files, skip_seconds, ...
-        epi_TR, expected_contiguous_frame_count, result_dir, taskname)
+    mat_file = subject_power_2014_FD_only_parse_BIDS(FD_movement_files, skip_seconds, ...
+        epi_TR, expected_contiguous_frame_count, result_dir, taskname);
     subject_power_2014_motion_parse_opt_BIDS(FD_movement_files, ...
-        skip_seconds, epi_TR, expected_contiguous_frame_count, result_dir, taskname)
+        skip_seconds, epi_TR, expected_contiguous_frame_count, result_dir, taskname);
     motion_summary_BIDS([result_dir filesep taskname '_motion_numbers.mat'], ...
         [result_dir filesep taskname '_power_2014_FD_only.mat'], result_dir, taskname);
 
+    %% Make the outlier mat files
+    dtseries = dir(fullfile(path_ciftis, '*.dtseries.nii'));
+    if ~isempty(dtseries)
+        dtseries_files = {};
+        for i = 1:length(dtseries)
+            dtseries_files{i} = fullfile(dtseries(i).folder,dtseries(i).name);
+        end
+        n_dtseries = length(dtseries_files);
+        disp([num2str(n_dtseries) ...
+            ' individual dtseries files were identified'])
+        for i=1:n_dtseries
+            try
+                filename = dtseries_files{i};
+                [~, name, ~] = fileparts(filename);
+
+                subject_outliers_parse_BIDS(path_wb_c, mat_file, dtseries, ...
+                    result_dir, taskname)
+
+            catch
+                disp([name 'does not exist'])
+            end
+        end
+    end
+
     %% Make the csv timecourses
     dummy = dir(fullfile(path_ciftis, '*ptseries*'));
     if ~isempty(dummy)
-        ptseries_files = {}
+        ptseries_files = {};
         for i = 1:length(dummy)
             ptseries_files{i} = fullfile(dummy(i).folder,dummy(i).name);
         end

matlab_code/framewise_displacement/outlier_censoring.m

@@ -0,0 +1,27 @@
+function output_removal_vector = outlier_censoring(wb_command, dtseries, input_removal_vector)
+
+outlier_removal_vector = zeros(size(input_removal_vector,1), size(input_removal_vector,2));
+
+[status,cmdout] = system([wb_command ' -cifti-stats ' dtseries ' -reduce STDEV']);
+
+if status ~= 0
+    return
+end
+
+% parse standard deviation values
+stdevs = cell2mat(textscan(cmdout, '%f\n'));
+
+% find the kept frames
+input_idx = find(~input_removal_vector);
+
+% find outliers
+outlier_vector = isoutlier(stdevs(input_idx),'median');
+
+% find indices of outliers within the kept frames
+outlier_idx = find(outlier_vector);
+
+% put the outlier flags into the outliers vector as ones (to censor)
+outlier_removal_vector( input_idx(outlier_idx) ) = 1;
+
+% convert outliers flags vector to a strict logical vector
+output_removal_vector = logical(outlier_removal_vector);

matlab_code/framewise_displacement/subject_outliers_parse_BIDS.m

@@ -0,0 +1,37 @@
+function subject_outliers_parse_BIDS(wb_command,motion_data_file,dtseries,output_dir,output_prefix)
+% FD parsing Nipype wrapper pulling in list of motion files
+% Modified to read DVAR_pre_reg, DVAR_post_reg, and DVAR_post_all and store
+% values appropriately in the 51x51x3 cell array of structs
+%
+% All variables (skips, TR, CurrentDirectory) set within Nipype
+% Iterates over range of values from 0.1 to maximum of 0.5 FD threshold
+% Outputs to .mat file
+% FD_movement_files = {'motion_numbers0.txt', 'motion_numbers1.txt', 'motion_numbers2.txt'};
+% FD_movement_files can be TXT or DAT files
+% varargin (brain_radius_in_mm) only needs to be provided for DAT file inputs
+
+load(motion_data_file);
+FD_range_max = motion_data{length(motion_data)}.FD_threshold;
+FD_range = 0:0.01:FD_range_max;
+
+for i = 1:length(motion_data)
+
+    motion_data{i}.fd_removal = motion_data{i}.frame_removal;
+    motion_data{i}.outlier_removal = double(outlier_censoring(wb_command, dtseries, motion_data{i}.frame_removal));
+    motion_data{i}.combined_removal = double(motion_data{i}.fd_removal | motion_data{i}.outlier_removal);
+
+    motion_data{i}.fd_format_string = format_generator(motion_data{i}.fd_removal);
+    motion_data{i}.outlier_format_string = format_generator(motion_data{i}.outlier_removal);
+    motion_data{i}.combined_format_string = format_generator(motion_data{i}.combined_removal);
+
+    motion_data{i}.remaining_fd_count = motion_data{i}.total_frame_count - sum(motion_data{i}.fd_removal);
+    motion_data{i}.remaining_outlier_count = motion_data{i}.total_frame_count - sum(motion_data{i}.outlier_removal);
+    motion_data{i}.remaining_combined_count = motion_data{i}.total_frame_count - sum(motion_data{i}.combined_removal);
+
+    motion_data{i}.remaining_fd_seconds = motion_data{i}.remaining_fd_count * motion_data{i}.epi_TR;
+    motion_data{i}.remaining_outlier_seconds = motion_data{i}.remaining_outlier_count * motion_data{i}.epi_TR;
+    motion_data{i}.remaining_combined_seconds = motion_data{i}.remaining_combined_count * motion_data{i}.epi_TR;
+
+end
+
+save([output_dir filesep output_prefix '_outliers_power_2014_FD_only.mat'],'motion_data');

matlab_code/framewise_displacement/subject_power_2014_FD_only_parse_BIDS.m

@@ -1,4 +1,4 @@
-function subject_power_2014_FD_only_parse_BIDS(movement_files,skip_seconds,epi_TR,expected_contiguous_frame_count,output_dir,output_prefix)
+function output_mat = subject_power_2014_FD_only_parse_BIDS(movement_files,skip_seconds,epi_TR,expected_contiguous_frame_count,output_dir,output_prefix)
 % FD parsing Nipype wrapper pulling in list of motion files
 % Modified to read DVAR_pre_reg, DVAR_post_reg, and DVAR_post_all and store
 % values appropriately in the 51x51x3 cell array of structs
@@ -10,7 +10,7 @@ function subject_power_2014_FD_only_parse_BIDS(movement_files,skip_seconds,epi_T
 % FD_movement_files can be TXT or DAT files
 % varargin (brain_radius_in_mm) only needs to be provided for DAT file inputs
 
-FD_range = 0:0.01:0.5;
+FD_range = 0:0.01:1.0;
 motion_data = cell(1,length(FD_range));
 run_count = length(movement_files);
 
@@ -57,4 +57,5 @@ function subject_power_2014_FD_only_parse_BIDS(movement_files,skip_seconds,epi_T
 
 end
 %this_path=pwd;
-save([output_dir filesep output_prefix '_power_2014_FD_only.mat'],'motion_data');
+output_mat = [output_dir filesep output_prefix '_power_2014_FD_only.mat'];
+save(output_mat,'motion_data');