update connectivity

unfinished_examples/extract_and_prep_for_connectomics.m

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+% Extract data from each region in a standardized atlas, averaging over voxels in the region
+
+% Method 1
+% pass fmri_data object img into canlab_connectivity_preproc, using the 'extract_roi' keyword and passing in the atlas
+img = load_image_set('emotionreg');  % a sample fmri_data object; insert your single-subject 4-D time series object here
+
+% Replace img with your single-subject 4-D time series object here, which
+% would usually be image data corresponding to one run.  You'd save the
+% output for each run, and concatenate across runs along with a metadata
+% table describing the task conditions and sessions.
+
+my_atlas = load_atlas('canlab2018_2mm');
+[img_preprocessed, region_average_data] = canlab_connectivity_preproc(img, 'extract_roi', my_atlas, 'unique_mask_values');
+
+% NOTE: Customize additional inputs to canlab_connectivity_preproc by
+% passing in nuisance regressors (outlier 'spikes', movement-related
+% regressors)
+
+% Method 2
+b = brainpathway;
+img = load_image_set('emotionreg');  % a sample fmri_data object; insert your single-subject 4-D time series object here
+img = resample_space(img, b.region_atlas); % resample the image to the voxel space/dims of atlas stored in b
+b.voxel_dat = img.dat;
+
+region_average_data = b.region_dat; % images x brain regions
+region_labels = b.region_atlas.labels; % labels (names) for the brain regions
+
+% next: Run canlab_connectivity_preproc, bandpass filtering and nuisance
+% regression
+% Create an image object storing the region averages
+% Pass the image object into canlab_connectivity_preproc
+