Dear all, INCF is asking for your help to review the Neo object model <https://www.incf.org/sbp/neo>for electrophysiology data, to assess its value as a community standard. Participating is simple; read the INCF SBP committee review report <https://f1000research.com/documents/11-658> on F1000 and leave your feedback in the comments! You can comment to express your support, to point out possibilities for improvement - or both. We are especially interested in hearing from Neo users and from tool developers who have implemented support for Neo or use Neo as part of their workflow. Please give us your feedback in a comment as soon as possible, but latest September 29: f1000research.com/documents/11-658 More information: Neo <https://www.incf.org/sbp/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. Read more about Neo: Project page <https://neuralensemble.org/neo/> Documentation <https://neo.readthedocs.io/en/stable/> Github <https://github.com/NeuralEnsemble/python-neo> Paper <https://www.frontiersin.org/articles/10.3389/fninf.2014.00010/full> -- Malin Sandström, PhD Community Engagement Officer malin.sandstrom@incf.org ORCID: 0000-0002-8464-2494 International Neuroinformatics Coordinating Facility Karolinska Institutet Nobels väg 15 A SE-171 77 Stockholm Sweden http://www.incf.org