Voxelwise modeling tutorials#
Welcome to the voxelwise modeling tutorials from the GallantLab.
If you use these tutorials for your work, consider citing the corresponding paper:
Dupré la Tour, T., Visconti di Oleggio Castello, M., & Gallant, J. L. (2024). The Voxelwise Modeling framework: a tutorial introduction to fitting encoding models to fMRI data. https://doi.org/10.31234/osf.io/t975e
You can find a copy of the paper here.
Getting started#
This website contains tutorials describing how to use the voxelwise modeling framework.
To explore these tutorials, one can:
read the rendered examples in the tutorials gallery of examples (recommended)
run the Python scripts (tutorials directory)
run the Jupyter notebooks (tutorials/notebooks directory)
run the notebooks in Google Colab: all notebooks or only the notebooks about model fitting
The tutorials are best explored in order, starting with the Shortclips tutorial.
The project is available on GitHub at gallantlab/voxelwise_tutorials. On top of the tutorials
scripts, the GitHub repository contains a Python package called
voxelwise_tutorials, which contains useful functions to download the data
sets, load the files, process the data, and visualize the results. Install
instructions are available here.
Cite as#
If you use one of our packages in your work (voxelwise_tutorials
[p1], himalaya [p2], pycortex
[p3], or pymoten [p4]), please cite the
corresponding publications.
If you use one of our public datasets in your work (vim-2 [3b], shortclips [4b]), please cite the corresponding publications.