Tutorial#

For an in-depth introduction to encoding/decoding models and the braincoder-package follow the Tutorial.

Quick start#

Welcome to Braincoder’s documentation!#

Braincoder is a package to fit encoding models to neural data (for now fMRI) and to then invert those model to decode stimulus information from neural data.

Important links#

Official source code repo: https://github.com/Gilles86/braincoder/tree/main
HTML documentation (stable release): https://braincoder-devs.github.io/

Installation#

Note that you need a environment with both tensorflow-probability and tensorflow.

Set up miniforge#

(Only do this if you don’t have conda installed) I reccomend to use miniforge, make sure you use the mamba-solver and set channel-priority to strict:

# Install mamba solver and set channel priority
conda install mamba -n base -c conda-forge
conda config --set channel_priority strict.

Install braincoder#

Here we create a new environment called braincoder with the required packages:

mamba create --name braincoder tensorflow-probability tensorflow -c conda-forge
mamba activate braincoder
pip install git+https://github.com/Gilles86/braincoder.git

Usage#

Please have a look at the tutorials to get started.