groovy

ConnPort preprocessing for resting-state fMRI data.

Groovy is a number of MATLAB scripts using SPM functions to pre-process resting-state fMRI data.

Requirements

• MATLAB r2014a (tested)
• SPM12

Installation

Download and unzip the scripts to a directory, then be sure to add that directory to MATLAB's search path. You can test installation by typing which batch_preprocess in MATLAB and checking the file path.

Configuration

Groovy takes unprocessed, uncompressed NIFTI EPI files as input.

The params.m file has settings to adjust. It's best to copy or move params.m to the parent directory of subject data. Then you can save different settings for different scans as separate params.m files.

Specifying the input data directory

In params.m, the complete file path to your data will be:

{global_params.fdata_root}/{subject}/{rs_dir}/{sub_struct.raw_filter}.nii

The variable global_params.fdata_root will by default be the MATLAB current working directory. You can also specify a different path in params.m.

The all_subjects variable contains a list of subject IDs. The script will look for those IDs as separate directories when running. By default, all_subjects is populated with all the directories in the global_params.fdata_root.

Within those subject ID directories, the script will look into rs_dir, which can be a filepath with multiple directories (just separate with the usual /). By default, this is set to the my_sesses variable, which by default contains all the directories within each subject directory. If you don't have separate sessions, set my_sesses = ''; and rs_dir to whatever directory inside the subject directory the data is in. Set rs_dir = ''; if the images are within the subject directories themselves. The value of rs_dir can specify longer filepaths, for example, rs_dir = '<top_level_dir>/<lower_level_dir>'.

Finally, the script has a regular expression filter, sub_struct.raw_filter, to find input files within rs_dir directories. Construct a regular expression pattern that will match all unprocessed files you wish to preprocess.

Specify other scan-specific parameters

Other important parameters to review in params.m include

• TR: sub_struct.TR
• number of volumes: ntrs

The number of slices per volume is calculated per image (using spm_vol). The slice time duration is calculated as TR/(number of slices per volume).

Running

After configuring params.m, simply run batch_preprocess in MATLAB to preprocess the data. (batch_preprocess needs to be in MATLAB's search path).

Output

Preprocessed files are placed in the same directory as the input data. Prefixes are attached to the filenames to signify that they are the output of a certain preprocessing step.

The prefixes:

• r{filename} slice-time corrected
• ar{filename} realigned
• war{filename} normalized to MNI space

NOTE

If MATLAB displays an error containing "cannot load any more object with static TLS", try increasing the Java heap memory to the maximum amount (Home>Preferences>General>Java Heap Memory>Java Heap Size) and then restart MATLAB