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 of installing autoMEA is to use pip:

pip install automea

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