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Population Receptive Field (pRF) Modeling Code

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Population Receptive Field (pRF)

Code for fitting population receptive fields (Dumoulin & Wandell, 2008) for multidimensional models. Includes optional compressive spatial summation exponential parameter (Kay et al., 2013).


Demonstration

  1. Add pathing to pRF package

    addpath(genpath('PathToPackage'));
  2. Open demopRF.m

    open demopRF
  3. Edit Pathing to Directories

    • Edit directories section as based on your computer's pathing

    % paths = createPaths(); % initialize paths structure
    % paths.data = fullfile(paths.main, 'DemoData'); % path to demostration data directory
    % paths.results = fullfile(paths.main, 'DemoExampleResults'); % path to output results directory
    % paths = createPaths(paths); % create paths if they do not already exist
  4. Run demopRF.m

    • Estimates pRF parameters, mu & sigma & exp, along with Boynton HRF parameters, tau & delta, for the demonstration data
    • Plots histogram of estimated pRF parameters mu, sigma, exp, and corr
    • Plots pRF model predicted voxel time courses vs. actual voxel time courses
    • Plots estimated Boynton HRF as a function of time

Tutorial

I've written a tutorial that walks through the concepts of pRF modeling in case you're new to the topic.

pRF Tutorial


Latest Version

Version 3.0

  • createScan.m can now also take in FreeSurfer .nii, .nii.gz, .mgz files along with .label files (to select ROIs)
  • Edited HRF options, can now provide other parameterized HRF function other than the BoyntonHRF such as the TwoGammaHRF from SPM
  • Edited HRF estimating methods, can now iteratively fit HRF parameters either voxels that past a correlation threshold and/or are in the top percentage of initial correlation fits
  • Incorporated timing interpolation if stimulus image and voxel time courses were collected at different sampling rates
  • Add plotHRF.m to visualize the HRF used to fit the pRF model
  • Optimizing for redundant code calls and efficiency. Also reduced nested structure layers
  • General documentation editing for spelling errors and clarity

Version Log


Contributor(s)

Kelly Chang - @kellychang4 - [email protected]


Dependencies


References

Dumoulin, S. O., & Wandell, B. A. (2008). Population receptive field estimates in human visual cortex. Neuroimage, 39(2), 647-660.

Kay, K. N., Winawer, J., Mezer, A., & Wandell, B. A. (2013). Compressive spatial summation in human visual cortex. Journal of neurophysiology, 110(2), 481-494.

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Population Receptive Field (pRF) Modeling Code

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