braincoder

Encoding models for fMRI implemented in tensorflow

https://github.com/gilles86/braincoder

Repository

Encoding models for fMRI implemented in tensorflow

README.rst

Welcome to Braincoder's documentation!
======================================

**Braincoder** is a package to fit encoding models to neural data (for now fMRI) and
to then *invert* those models 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 an environment with both `tensorflow-probability` and
`tensorflow`.

Set up miniforge
-----------------

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

.. code-block:: bash

        # 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:

.. code-block:: bash

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

How to Cite
===========

If you use **Braincoder** in your research, please cite it using the following information:

> de Hollander, G., Renkert, M., Ruff, C. C., & Knapen, T. H. (2024). *Braincoder: A package for fitting encoding models to neural data and decoding stimulus features*. `Zenodo `_. DOI: `10.5281/zenodo.10778413 `_.

Alternatively, use this BibTeX entry:

.. code-block:: bibtex

    @software{deHollander2024braincoder,
      author       = {Gilles de Hollander and Maike Renkert and Christian C. Ruff and Tomas H. Knapen},
      title        = {braincoder: A package for fitting encoding models to neural data and decoding stimulus features},
      year         = {2024},
      publisher    = {Zenodo},
      doi          = {10.5281/zenodo.10778413},
      url          = {https://github.com/Gilles86/braincoder}
    }

By citing this software, you help support open-source development and proper crediting in academic research.

Usage
=====

Please have a look at the `tutorials `_ to get started.

Owner

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it using the metadata below."
title: "braincoder"
version: 0.3.0
doi: 10.5281/zenodo.10778413
authors:
  - name: "Gilles de Hollander"
    orcid: "0000-0002-XXXX-XXXX"
  - name: "Maike Renkert"
    orcid: "0000-0002-4809-4216"
  - name: "Christian C. Ruff"
    orcid: "0000-0002-3964-2364"
  - name: "Tomas H. Knapen"
    orcid: "0000-0001-5863-8689"
repository-code: "https://github.com/Gilles86/braincoder"
date-released: "2024-12-06"
abstract: |
  braincoder is a Python package designed to help researchers fit encoding models to neural data 
  and decode stimulus features from unseen neural data. It leverages computational modeling to 
  bridge neuroscience and data analysis, providing robust tools for understanding neural representation.

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