Skip to main content
Course:

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

Difficulty level: Beginner
Duration: 1:30
Speaker: : Anita Bandrowski

This talk highlights a set of platform technologies, software, and data collections that close and shorten the feedback cycle in research. 

Difficulty level: Beginner
Duration: 57:52
Speaker: : Satrajit Ghosh

This lesson provides an overview of the database of Genotypes and Phenotypes (dbGaP), which was developed to archive and distribute the data and results from studies that have investigated the interaction of genotype and phenotype in humans.

Difficulty level: Beginner
Duration: 48:22
Speaker: : Michael Feolo

This lesson provides an overview of how to conceptualize, design, implement, and maintain neuroscientific pipelines in via the cloud-based computational reproducibility platform Code Ocean. 

Difficulty level: Beginner
Duration: 17:01
Speaker: : David Feng

This lesson provides an overview of how to construct computational pipelines for neurophysiological data using DataJoint.

Difficulty level: Beginner
Duration: 17:37
Speaker: : Dimitri Yatsenko

This hands-on tutorial walks you through DataJoint platform, highlighting features and schema which can be used to build robost neuroscientific pipelines. 

Difficulty level: Beginner
Duration: 26:06
Speaker: : Milagros Marin

This lesson provides an introduction to the DataLad, a free and open source distributed data management system that keeps track of your data, creates structure, ensures reproducibility, supports collaboration, and integrates with widely used data infrastructure.

Difficulty level: Beginner
Duration: 22:56

This lesson introduces several open science tools like Docker and Apptainer which can be used to develop portable and reproducible software environments. 

Difficulty level: Beginner
Duration: 17:22
Speaker: : Joanes Grandjean

This lecture provides a detailed description of how to incorporate HED annotation into your neuroimaging data pipeline. 

Difficulty level: Beginner
Duration: 33:36
Speaker: : Dung Truong

This lecture covers a wide range of aspects regarding neuroinformatics and data governance, describing both their historical developments and current trajectories. Particular tools, platforms, and standards to make your research more FAIR are also discussed.

Difficulty level: Beginner
Duration: 54:58
Speaker: : Franco Pestilli

This talk covers the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC), a free one-stop-shop collaboratory for science researchers that need resources such as neuroimaging analysis software, publicly available data sets, or computing power.

Difficulty level: Beginner
Duration: 1:00:10
Speaker: : David Kennedy

This lecture covers how to make modeling workflows FAIR by working through a practical example, dissecting the steps within the workflow, and detailing the tools and resources used at each step.

Difficulty level: Beginner
Duration: 15:14
Course:

This session provides users with an introduction to tools and resources that facilitate the implementation of FAIR in their research.

 

 

Difficulty level: Beginner
Duration: 38:36
Course:

This session will include presentations of infrastructure that embrace the FAIR principles developed by members of the INCF Community.

 

This lecture provides an overview of The Virtual Brain Simulation Platform.

 

Difficulty level: Beginner
Duration: 9:36
Speaker: : Petra Ritter

This lesson consists of a demonstration of the BRIAN Simulator. BRIAN is a free, open-source simulator for spiking neural networks. It is written in the Python programming language and is available on almost all platforms, and is designed to be easy to learn and use, highly flexible, and easily extensible.

Difficulty level: Beginner
Duration: 1:27:32
Speaker: : Marcel Stimberg

This lesson provides a demonstration of NeuroFedora, a volunteer-driven initiative to provide a ready-to-use Fedora-based free and open-source software platform for neuroscience. By making the tools used in the scientific process easier to use, NeuroFedora aims to aid reproducibility, data sharing, and collaboration in the research community.The CompNeuro Fedora Lab was specially to enable computational neuroscience.

Difficulty level: Beginner
Duration: 1:06:08
Speaker: : Ankur Sinha

This lesson provides an introduction and live demonstration of neurolib, a computational framework for simulating coupled neural mass models written in Python. Neurolib provides a simulation and optimization framework which allows you to easily implement your own neural mass model, simulate fMRI BOLD activity, analyse the results and fit your model to empirical data.

Difficulty level: Beginner
Duration: 1:06:53
Speaker: : Çağlar Çakan

In this lesson, you will learn about the GeNN (GPU-enhanced Neuronal Networks) framework, which aims to facilitate the use of graphics accelerators for computational models of large-scale neuronal networks. GeNN is an open-source library that generates code to accelerate the execution of network simulations on NVIDIA GPUs, through a flexible and extensible interface, which does not require in-depth technical knowledge from the users.

Difficulty level: Beginner
Duration: 59:00

This video gives a short introduction to the EBRAINS data sharing platform, why it was developed, and how it contributes to open data sharing.

Difficulty level: Beginner
Duration: 17:32
Speaker: : Ida Aasebø

This video demonstrates how to find, access, and download data on EBRAINS.

Difficulty level: Beginner
Duration: 14:27