ROI Calculation

With a predefined atlas-like ROI file and a descriptive number-label table, the current function can extract mean time series from ROIs and voxels, and calculate Pearson’s correlation as well as its Fisher-z transform. An option is provided to calculate partial correlation between each pair of ROIs, with mean signals of other ROIs as covariates.

_images/roi_calculation.png

  • roi file: ROIs in one nifti file

  • roi index(*): optional. labels of tagged ROIs in a *.csv file. For example:

    1,SFG
2,MFG
3,IFG

  • clustersize thr: threshold of cluster size.

  • mask: could be whole brain mask or gray matter mask.

  • id index: identifier to find unique string for each subject

  • filetype: files in the filetype will be searched in input directories.

  • 4D nifti files: if the input data is 4D, check this item. Otherwise uncheck.

  • input dirs: directories can be input either using a *.txt file or spm select window.

  • extract mean: extract mean time series for each ROI

  • roi to roi correlation: calculate correlation between pairs of ROI

  • roi to whole brain correlation: calculate correlation between each ROI’s mean time series and voxels in the mask.

  • Partial correlation: (check to use Partial correlation, uncheck to use Pearson’s correlation) when calculating correlation, between one roi mean time series and voxels/other time series, the rest of roi mean time serieses will be regressed out from the calculation.

  • out dir: output directory for saving results.

  • Buttons:
    • S: Save parameters of the current panel to a *.mat file. The *.mat can be further loaded for the panel or be used in a script processing.
    • L: Load parameters from *.mat for the current panel.
    • ?: Help information.