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This is the first of two workshops on reproducibility in science, during which participants are introduced to concepts of FAIR and open science. After discussing the definition of and need for FAIR science, participants are walked through tutorials on installing and using Github and Docker, the powerful, open-source tools for versioning and publishing code and software, respectively.

Difficulty level: Intermediate
Duration: 1:20:58

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 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

Research Resource Identifiers (RRIDs) are ID numbers assigned to help researchers cite key resources (e.g., antibodies, model organisms, and software projects) in biomedical literature to improve the transparency of research methods.

Difficulty level: Beginner
Duration: 1:01:36
Speaker: : Maryann Martone
Course:

KnowledgeSpace is a community-based encyclopedia that links brain research concepts to data, models, and literature. It provides users with access to anatomy, gene expression, models, morphology, and physiology data from over 15 different neuroscience data/model repositories, such as Allen Institute for Brain Science and the Human Brain Project.

Difficulty level: Beginner
Duration: 0:58
Speaker: : Tom Gillespie

This talk deals with Identifiers.org, a central infrastructure for findable, accessible, interoperable and re-usable (FAIR) data, which provides a range of services  to promote the citability of individual data providers and integration with e-infrastructures.

Difficulty level: Beginner
Duration: 36:41

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

This lecture will provide an overview of the INCF Training Suite, a collection of tools that embraces the FAIR principles developed by members of the INCF Community. This will include an overview of TrainingSpace, Neurostars, and KnowledgeSpace.

Difficulty level: Beginner
Duration: 09:50
Speaker: : Mathew Abrams
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

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

Difficulty level: Beginner
Duration: 17:23
Speaker: : Ulrike Schlegel

This video introduces the importance of writing a Data Descriptor to accompany your dataset on EBRAINS. It gives concrete examples on what information to include and highlights how this makes your data more FAIR.

Difficulty level: Beginner
Duration: 9:48
Speaker: : Ingrid Reiten
Course:

KnowledgeSpace (KS) is a data discoverability portal and neuroscience encyclopedia that was developed to make it easier for the neuroscience community to find publicly available datasets that adhere to the FAIR Principles and to provide an integrated view of neuroscience concepts found in Wikipedia and NeuroLex linked with PubMed and 17 of the world's leading neuroscience repositories. In short, KS provides a single point of entry where reseaerchers can search for a neuroscience concept of interest and receive results that include: i. a description of the term found in Wikipedia/NeuroLex, ii. links to publicly available datasets related to the concept of interest, and iii. up-to-date references that support the concept of interests found in PubMed. APIs are available so that developers of other neuroscience research infrastructures can integrate KS components in their infrastructures. If your repository or your favorite repository is not indexed in KS, please contact us.

 

Difficulty level: Beginner
Duration: 6:14
Speaker: : Heather Topple

In this lesson, users will learn about the importance of proper citation of software resources and tools used in neuroscientific research. 

Difficulty level: Beginner
Duration: 58:00

This lecture describes the principles of EEG electrode placement in both 2- and 3-dimensional formats. 

Difficulty level: Intermediate
Duration: 12:16
Speaker: : Mike X. Cohen

This tutorial walks users through performing Fourier Transform (FFT) spectral analysis of a single EEG channel using MATLAB. 

Difficulty level: Intermediate
Duration: 13:39
Speaker: : Mike X. Cohen

This tutorial builds on the previous lesson's demonstration of spectral analysis of one EEG channel. Here, users will learn how to compute and visualize spectral power from all EEG channels using MATLAB. 

Difficulty level: Intermediate
Duration: 12:34
Speaker: : Mike X. Cohen

In this lesson, users will learn more about the steady-state visually evoked potential (SSEVP), as well as how to create and interpret topographical maps derived from such studies. 

Difficulty level: Intermediate
Duration: 9:10
Speaker: : Mike X. Cohen

This lesson teaches users how to extract edogenous brain waves from EEG data, specifically oscillations constrained to the 8-12 Hz frequency band, conventionally named alpha. 

Difficulty level: Intermediate
Duration: 13:23
Speaker: : Mike X. Cohen

In the final lesson of this module, users will learn how to correlate endogenous alpha power with SSVEP amplitude from EEG data using MATLAB.

Difficulty level: Intermediate
Duration: 12:36
Speaker: : Mike X. Cohen