Call for community review of Neo

INCF is asking for your help to review the Neo object model for electrophysiology data, to assess its value as a community standard.

Neo is an object model for handling electrophysiology data in multiple formats. It is suitable for representing data acquired from electroencephalographic, intracellular, or extracellular recordings, or generated from simulations. Neo has been implemented as a Python package for working with electrophysiology data, together with support for reading a wide range of neurophysiology file formats (including Spike2, NeuroExplorer, AlphaOmega, Axon, Blackrock, Plexon, Tdt, Igor Pro), and support for writing to a subset of these formats plus non-proprietary formats including Kwik and HDF5. 

Feedback from the community is an important part of our review process; it helps us ensure that the standard has community support and is useful and practical to the community. By commenting, you contribute to improving the standard for current and future users!

Participating is simple; read the INCF SBP committee review report and leave your feedback in the comments.

Read more about Neo:
Neo project page: https://neuralensemble.org/neo/
Neo documentation: https://neo.readthedocs.io/en/stable/
Neo on Github: https://github.com/NeuralEnsemble/python-neo
Paper: https://www.frontiersin.org/articles/10.3389/fninf.2014.00010/full

Read more about the INCF endorsement process:
Why and how to comment on standards and best practices: https://www.incf.org/how-provide-feedback-incf-call-community-review
INCF criteria for endorsement: https://incf.org/incf-standards-review-criteria-v20   
How the endorsement process works: https://incf.org/activities/endorse