Lesson type
Difficulty level
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
Speaker: : Neil Chue Hong & Daniel Katz
Since their introduction in 2016, the FAIR data principles have gained increasing recognition and adoption in global neuroscience. FAIR defines a set of high level principles and practices for making digital objects, including data, software and workflows, Findable, Accessible, Interoperable and Reusable. But FAIR is not a specification; it leaves many of the specifics up to individual scientific disciplines to define. INCF has been leading the way in promoting, defining and implementing FAIR data practices for neuroscience. We have been bringing together researchers, infrastructure providers, industry and publishers through our programs and networks.
Difficulty level: Beginner
Duration: 1:28
This lesson breaks down the principles of Bayesian inference and how it relates to cognitive processes and functions like learning and perception. It is then explained how cognitive models can be built using Bayesian statistics in order to investigate how our brains interface with their environment.
This lesson corresponds to slides 1-64 in the PDF below.
Difficulty level: Intermediate
Duration: 1:28:14
Speaker: : Andreea Diaconescu
This is a tutorial on designing a Bayesian inference model to map belief trajectories, with emphasis on gaining familiarity with Hierarchical Gaussian Filters (HGFs).
This lesson corresponds to slides 65-90 of the PDF below.
Difficulty level: Intermediate
Duration: 1:15:04
Speaker: : Daniel Hauke
This tutorial walks participants through the application of dynamic causal modelling (DCM) to fMRI data using MATLAB. Participants are also shown various forms of DCM, how to generate and specify different models, and how to fit them to simulated neural and BOLD data.
This lesson corresponds to slides 158-187 of the PDF below.
Difficulty level: Advanced
Duration: 1:22:10
Speaker: : Peter Bedford, Povilas Karvelis