This presentation discusses the impact of data sharing in stroke.

This talks presents an overview of the potential for data federation in stroke research.

This lesson discusses FAIR principles and methods currently in development for assessing FAIRness.

This lecture provides an overview of successful open-access projects aimed at describing complex neuroscientific models, and makes a case for expanded use of resources in support of reproducibility and validation of models against experimental data.

This lecture provides an introduction to the Brain Imaging Data Structure (BIDS), a standard for organizing human neuroimaging datasets.

This lesson provides an overview of Neurodata Without Borders (NWB), an ecosystem for neurophysiology data standardization. The lecture also introduces some NWB-enabled tools. 

This lesson outlines Neurodata Without Borders (NWB), a data standard for neurophysiology which provides neuroscientists with a common standard to share, archive, use, and build analysis tools for neurophysiology data.

This lecture covers the rationale for developing the DAQCORD, a framework for the design, documentation, and reporting of data curation methods in order to advance the scientific rigour, reproducibility, and analysis of data.

This tutorial demonstrates how to use PyNN, a simulator-independent language for building neuronal network models, in conjunction with the neuromorphic hardware system SpiNNaker. 

In this lesson, you will learn in more detail about neuromorphic computing, that is, non-standard computational architectures that mimic some aspect of the way the brain works. 

This video provides a very quick introduction to some of the neuromorphic sensing devices, and how they offer unique, low-power applications.

This is an introductory lecture on whole-brain modelling, delving into the various spatial scales of neuroscience, neural population models, and whole-brain modelling. Additionally, the clinical applications of building and testing such models are characterized. 

This lecture covers FAIR atlases, including their background and construction, as well as how they can be created in line with the FAIR principles.

This lesson discusses the need for and approaches to integrating data across the various temporal and spatial scales in which brain activity can be measured. 

This lesson consists of lecture and tutorial components, focusing on resources and tools which facilitate multi-scale brain modeling and simulation. 

In this talk, challenges of handling complex neuroscientific data are discussed, as well as tools and services for the annotation, organization, storage, and sharing of these data. 

This lecture describes the neuroscience data respository G-Node Infrastructure (GIN), which provides platform independent data access and enables easy data publishing. 

This lecture provides an introduction to optogenetics, a biological technique to control the activity of neurons or other cell types with light.

This lesson consists of a talk about the history and future of academic publishing and the need for transparency, as well as a live demo of an alpha version of NeuroLibre, a preprint server that goes beyond the PDF to complement research articles. This video was part of a virutal QBIN SciComm seminar.

This lecture discusses differential privacy and synthetic data in the context of medical data sharing in clinical neurosciences.