autoMEA#

autoMEA (Automated analysis of MEA datasets) is a open-source Python package for the analysis of Micro-Electrode Array (MEA) datasets.

How does autoMEA work?#

Bursts are detected using the Max Interval Method. Users can manually set Max Interval Parameters, or can use a machine learning model that dynamically predicts optimal parameters for specific recording times. Several models are distributed with automea, and users are free to fine-tune the existing models for their specific needs, or upload new models completely.

The machine-learning-based burst detection routine is explained in the paper accompanying the package.

Tutorials and documentation can be found on https://automea.readthedocs.io.

Installation#

The preferred way to install autoMEA is using Conda.

Create a new environment with Python 3.10 and activate it:

conda create -n automea_env python=3.10
conda activate automea_env

Install autoMEA using pip:

pip install automea

Reproducibility#

All the data used to train and evaluate the machine learning models distributed with autoMEA can be found on zenodo.

Citing#

If you have used autoMEA for work that has led to a scientific publication, please cite it as

@article {Hernandes2024.05.08.593078,
	author = {Hernandes, Vinicius and Heuvelmans, Anouk M. and Gualtieri, Valentina and Meijer, Dimphna H. and van Woerden, Geeske M. and Greplova, Eliska},
	title = {autoMEA: Machine learning-based burst detection for multi-electrode array datasets},
	elocation-id = {2024.05.08.593078},
	year = {2024},
	doi = {10.1101/2024.05.08.593078},
	publisher = {Cold Spring Harbor Laboratory},
	URL = {https://www.biorxiv.org/content/early/2024/05/08/2024.05.08.593078},
	journal = {bioRxiv}
}

@dataset{hernandes_2024_12685150,
  author       = {Hernandes, Vinicius and
                  Heuvelmans, Anouk M. and
                  Gualtieri, Valentina and
                  Meijer, Dimphna H. and
                  van Woerden, Geeske M. and
                  Greplova, Eliska},
  title        = {{Data and scripts used in: "autoMEA: Machine 
                   learning-based burst detection for multi-electrode
                   array datasets"}},
  month        = jul,
  year         = 2024,
  publisher    = {Zenodo},
  doi          = {10.1101/2024.05.08.593078},
  url          = {https://doi.org/10.1101/2024.05.08.593078}
}

Authors#

Here is a list of authors who have contributed to this project:

Vinicius Hernandes
Anouk M. Heuvelmans
Valentina Gualtieri
Dimphna H. Meijer
Geeske M. van Woerden
Eliska Greplova

Contributing#

autoMEA is an open source package, and we invite you to contribute! You contribute by opening issues, fixing them, and spreading the word about autoMEA.

License#

This work is licensed under a MIT License

autoMEA

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