Brief introduction to Research Resource Identifiers (RRIDs), persistent and unique identifiers for referencing a research resource. 

Computational models provide a framework for integrating data across spatial scales and for exploring hypotheses about the biological mechanisms underlying neuronal and network dynamics. However, as models increase in complexity, additional barriers emerge to the creation, exchange, and re-use of models. Successful projects have created standards for describing complex models in neuroscience and provide open source tools to address these issues. This lecture provides an overview of these projects and make a case for expanded use of resources in support of reproducibility and validation of models against experimental data.

NWB: An ecosystem for neurophysiology data standardization

EEGLAB is an interactive Matlab toolbox for processing continuous and event-related EEG, MEG and other electrophysiological data incorporating independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data. EEGLAB runs under Linux, Unix, Windows, and Mac OS X.

This module covers many of the types of non-invasive neurotech and neuroimaging devices including Electroencephalography (EEG), Electromyography (EMG), Electroneurography (ENG), Magnetoencephalography (MEG), functional Near-Infrared Spectroscopy (fNRIs), Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), and Computed Tomography

Learn how to build and share extensions in NWB

Learn how to build custom APIs for extension

Learn how to handle writing very large data in PyNWB

Learn how to handle writing very large data in MatNWB

This video explains what metadata is, why it is important, and how you can organise your metadata to increase the FAIRness of your data on EBRAINS.