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Virtual INCF Neuroinformatics Training Weeks 2021

INCF is proud to announce its first virtual training event! The INCF Training Weeks are scheduled to take place from August 23 to September 3rd.

There will be practical, interactive workshops on topics like cloud computing, Neurodata Without Borders (NWB), data and metadata management with NIX, and DataJoint elements, and tutorials on using standards such as NeuroML, BIDS, and NIDM tools.

New INCF Working Group: INCF/OCNS Software WG
The Software Working Group is a joint collaboration between INCF and the Organization for Computational Neuroscience (OCNS). The working group focuses on evaluating and improving computational neuroscience tools: finding them, testing them, learning how they work, and informing developers of issues to ensure that these tools remain in good shape by having communities looking after them.
INCF staff walk the Neuropromenaden to benefit research on neurological diseases

For this year's Neuro walk (Neuropromenaden), the whole INCF secretariat joined up as Team Neuroinformagicians, and walked over 500 kilometers together, while enjoying the Swedish spring.

10+ years of Brainhack: an open, inclusive culture for neuro tool developers at all levels

Brainhacks and similar formats are increasingly recognized as a new way of providing academic training and conducting research that extends traditional settings. There is a new paper out in Neuron, by 200+ authors, describing the format and what makes it valuable to the community. This post aims to highlight some of the core themes of the paper.

The critical window for becoming a FAIR researcher

Commentary on the critical window for becoming a FAIR researcher by Heidi Kleven and Ingvild E. Bjerke, Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Norway.

2021 ISI/WSC Summer Course: Data Science and Predictive Analytics (June 16-17, 2021)

A 2-day Summer Course on Data Science and Predictive Analytics including computational neuroscience applications. Intermediate to advanced data science training including collecting, managing, processing, interrogating, analyzing and interpreting complex health and biomedical datasets using R. Participants will gain skills and acquire a tool-chest of methods, software tools, and protocols that can be applied to a broad spectrum of Big Data problems.