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


The preferred way of installing autoMEA is to use pip:

pip install automea


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


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.


This work is licensed under a MIT License