brainsets 0.1.0

A package for processing neural datasets

brainsets

Documentation | Paper

brainsets is a Python package for processing neural data into a standardized format.

Installation

brainsets is available for Python 3.8 to Python 3.11

To install the package, run the following command:

pip install brainsets

Using the brainsets CLI

Configuring data directories

First, configure the directories where brainsets will store raw and processed data:

brainsets config

You will be prompted to enter the paths to the raw and processed data directories.

$> brainsets config
Enter raw data directory: ./data/raw
Enter processed data directory: ./data/processed

You can update the configuration at any time by running the config command again.

Listing available datasets

You can list the available datasets by running the list command:

brainsets list

Preparing data

You can prepare a dataset by running the prepare command:

brainsets prepare <brainset>

Data preparation involves downloading the raw data from the source then processing it, following a set of rules defined in pipelines/<brainset>/.

For example, to prepare the Perich & Miller (2018) dataset, you can run:

brainsets prepare perich_miller_population_2018 --cores 8

Contributing

If you are planning to contribute to the package, you can install the package in development mode by running the following command:

pip install -e ".[dev]"

Install pre-commit hooks:

pre-commit install

Unit tests are located under test/. Run the entire test suite with

pytest

or test individual files via, e.g., pytest test/test_enum_unique.py

Cite

Please cite our paper if you use this code in your own work:

@inproceedings{
    azabou2023unified,
    title={A Unified, Scalable Framework for Neural Population Decoding},
    author={Mehdi Azabou and Vinam Arora and Venkataramana Ganesh and Ximeng Mao and Santosh Nachimuthu and Michael Mendelson and Blake Richards and Matthew Perich and Guillaume Lajoie and Eva L. Dyer},
    booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
    year={2023},
}