Welcome to the voxelwise modeling tutorial from the Gallantlab.

This repository contains tutorials describing how to use the voxelwise modeling framework. Voxelwise modeling is a framework to perform functional magnetic resonance imaging (fMRI) data analysis, fitting encoding models at the voxel level.

To explore these tutorials, one can:

• read the rendered examples in the tutorials website (recommended)
• run the Python scripts (tutorials directory)
• run the Jupyter notebooks (tutorials/notebooks directory)
• run the merged notebook in Colab.

The tutorials are best explored in order, starting with the "Movies" tutorial.

To run the tutorials, this repository contains a small Python package called voxelwise_tutorials, with useful functions to download the data sets, load the files, process the data, and visualize the results.

To install the voxelwise_tutorials package, run:

pip install voxelwise_tutorials

To also download the tutorial scripts and notebooks, clone the repository via:

git clone https://github.com/gallantlab/voxelwise_tutorials.git
cd voxelwise_tutorials
pip install .

Developers can also install the package in editable mode via:

pip install --editable .

The package voxelwise_tutorials has the following dependencies: numpy, scipy, h5py, scikit-learn, matplotlib, networkx, nltk, pycortex, himalaya, pymoten.

If you use one of our packages in your work (voxelwise_tutorials [1], himalaya [2], pycortex [3], or pymoten [4]), please cite the corresponding publications: