Braincoder

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. It wraps stimulus handling, model definition, HRF convolution, and optimization into a single Keras 3-based toolkit that runs on TensorFlow, JAX, or PyTorch.

Highlights

• Composable models. Pick from ready-made encoding models (Gaussian PRF, HRF-aware, linear) or subclass EncodingModel to implement your own.
• End-to-end workflow. Utilities for simulation, fitting, and decoding stay in pandas/tensor-friendly formats.
• Backend-agnostic. Runs on TensorFlow, JAX, or PyTorch via Keras 3.

Links

• Source code: https://github.com/Gilles86/braincoder
• Documentation: https://braincoder-devs.github.io/

Installation

The quickest way to get started is with conda/mamba. Clone the repo, then create the environment:

git clone https://github.com/Gilles86/braincoder.git
cd braincoder
conda env create -f environment.yml
conda activate braincoder

This installs braincoder in editable mode (pip install -e .) along with a TensorFlow backend and dev tools. See the installation docs for other backends (JAX, PyTorch) and pip-only setups.

Quick start

import numpy as np
import pandas as pd
from braincoder.models import GaussianPRF

paradigm = pd.DataFrame({"x": np.linspace(-5, 5, 100)},
                        index=pd.Index(np.arange(100), name="time"))
parameters = pd.DataFrame({"mu": [0.0, 1.0], "sd": [1.0, 2.0], "amplitude": [1.0, 1.0], "baseline": [0.0, 0.0]},
                          index=pd.Index(["v1", "v2"], name="voxel"))

model = GaussianPRF()
predicted = model.predict(paradigm=paradigm, parameters=parameters)

See the tutorials for full fitting and decoding pipelines.

How to cite

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.

@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}
}