Voxelwise modeling tutorials

Welcome to the voxelwise modeling tutorial from the Gallantlab.

Tutorials

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.

Helper Python package

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.

Installation

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 .

Requirements

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

Cite as

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:

[1]	Deniz, F., Visconti di Oleggio Castello, M., Dupré La Tour, T., & Gallant, J. L. (2022). Voxelwise encoding models in functional MRI. In preparation.

[2]	Dupré La Tour, T., Eickenberg, M., & Gallant, J. L. (2022). Variance decomposition with banded ridge regression. In preparation.

[3]	Gao, J. S., Huth, A. G., Lescroart, M. D., & Gallant, J. L. (2015). Pycortex: an interactive surface visualizer for fMRI. Frontiers in neuroinformatics, 23.