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This lesson contains practical exercises which accompanies the first few lessons of the Neuroscience for Machine Learners (Neuro4ML) course. 

Difficulty level: Intermediate
Duration: 5:58
Speaker: : Dan Goodman

This video briefly goes over the exercises accompanying Week 6 of the Neuroscience for Machine Learners (Neuro4ML) course, Understanding Neural Networks.

Difficulty level: Intermediate
Duration: 2:43
Speaker: : Marcus Ghosh

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 is a hands-on tutorial on PLINK, the open source whole genome association analysis toolset. The aims of this tutorial are to teach users how to perform basic quality control on genetic datasets, as well as to identify and understand GWAS summary statistics. 

Difficulty level: Intermediate
Duration: 1:27:18
Speaker: : Dan Felsky

In this third and final hands-on tutorial from the Research Workflows for Collaborative Neuroscience workshop, you will learn about workflow orchestration using open source tools like DataJoint and Flyte. 

Difficulty level: Intermediate
Duration: 22:36
Speaker: : Daniel Xenes

In this hands-on session, you will learn how to explore and work with DataLad datasets, containers, and structures using Jupyter notebooks. 

Difficulty level: Beginner
Duration: 58:05

This video will document the process of uploading data into a brainlife project using ezBIDS.

Difficulty level: Beginner
Duration: 6:15
Speaker: :

This short video walks you through the steps of publishing a dataset on brainlife, an open-source, free and secure reproducible neuroscience analysis platform.

Difficulty level: Beginner
Duration: 1:18
Speaker: :

This video will document the process of visualizing the provenance of each step performed to generate a data object on brainlife.

Difficulty level: Beginner
Duration: 0:21
Speaker: :

This video will document the process of downloading and running the "reproduce.sh" script, which will automatically run all of the steps to generate a data object locally on a user's machine.

Difficulty level: Beginner
Duration: 3:44
Speaker: :

This video will document the process of creating a pipeline rule for batch processing on brainlife.

Difficulty level: Intermediate
Duration: 0:57
Speaker: :

This short video shows how a brainlife.io publication can be opened from the Data Deposition page of the journal Nature Scientific Data.

Difficulty level: Beginner
Duration: 2:25
Speaker: :

In this tutorial, you will learn the basic features of uploading and versioning your data within OpenNeuro.org.

Difficulty level: Beginner
Duration: 5:36
Speaker: : OpenNeuro

This tutorial shows how to share your data in OpenNeuro.org.

Difficulty level: Beginner
Duration: 1:22
Speaker: : OpenNeuro

Following the previous two tutorials on uploading and sharing data with OpenNeuro.org, this tutorial briefly covers how to run various analyses on your datasets.

Difficulty level: Beginner
Duration: 2:26
Speaker: : OpenNeuro

This video introduces the key principles for data organization and explains how you could make your data FAIR for data sharing on EBRAINS.

Difficulty level: Beginner
Duration: 10:54

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

This lesson provides a hands-on tutorial for generating simulated brain data within the EBRAINS ecosystem. 

Difficulty level: Beginner
Duration: 32:58
Speaker: : Jil Meier