Video coming soon. 

In this lesson you will learn about current efforts towards integrating multimodal human brain data using the open source SCORE HED library schema. 

This talk covers the differences between applying HED annotation to fMRI datasets versus other neuroimaging practices, and also introduces an analysis pipeline using HED tags. 

This lecture discusses the FAIR principles as they apply to electrophysiology data and metadata, the building blocks for community tools and standards, platforms and grassroots initiatives, and the challenges therein.

This lecture contains an overview of electrophysiology data reuse within the EBRAINS ecosystem.

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

This lesson provides an overview of the current status in the field of neuroscientific ontologies, presenting examples of data organization and standards, particularly from neuroimaging and electrophysiology. 

This lecture contains an overview of the Distributed Archives for Neurophysiology Data Integration (DANDI) archive, its ties to FAIR and open-source, integrations with other programs, and upcoming features.

This lecture contains an overview of the China-Cuba-Canada neuroinformatics ecosystem for Quantitative Tomographic EEG Analysis (qEEGt).