We debuted our new collection of community resources at SfN 2023, and since we, for the first time ever at SfN, ran out of the printed collection we’re now sharing it here as well! This collection includes information on six key INCF tools and resources that help demystify and streamline the process of data sharing.
The Global Alliance for Genomics and Health (GA4GH) and the International Neuroinformatics Coordinating Facility (INCF) launched a new group to lay the groundwork for connecting global neuroscience and genomic data.
INCF has been working to facilitate data sharing in neuroscience since 2005 by supporting community-driven standardization and interoperability efforts, and ensuring impact through training and advocacy activities. Your contribution enables us to provide open science resources and training activities to the global neuroscience community.
INCF will apply to be a mentor organization in Google Summer of Code for the 13th time running. Want to join us? If your project supports or implements INCF endorsed standards or best practices, we especially encourage you to apply!
Mathworks and INCF held a pilot round last summer of engaging current or recently graduated students as trainees to work on MATLAB neuroscience toolboxes. Four trainees worked with mentors from the toolboxes Automatic Analysis, EEGLAB, FieldTrip and MatNWB.
SfN starts tomorrow - Sat Nov 12 - and we look forward to seeing you there! Here is a list of the INCF member activities that will be taking place during the week. Note that we may add to this list as the week goes on, so feel free to check back!
Infrastructure Committee is trying to identify barriers to data sharing and reuse among neuroscience researchers worldwide, with a brief anonymous survey. The results will be made public, and will be used by INCF to develop strategies and activities for supporting the global neuroscience community.
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.