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In this lesson, the simulation of a virtual epileptic patient is presented as an example of advanced brain simulation as a translational approach to deliver improved clinical results. You will learn about the fundamentals of epilepsy, as well as the concepts underlying epilepsy simulation. By using an iPython notebook, the detailed process of this approach is explained step by step. In the end, you are able to perform simple epilepsy simulations your own.

Difficulty level: Beginner
Duration: 1:28:53
Speaker: : Julie Courtiol

In this lesson you will learn how to simulate seizure events and epilepsy in The Virtual Brain. We will look at the paper On the Nature of Seizure Dynamics, which describes a new local model called the Epileptor, and apply this same model in The Virtual Brain. This is part 1 of 2 in a series explaining how to use the Epileptor. In this part, we focus on setting up the parameters.

Difficulty level: Beginner
Duration: 4:44
Speaker: : Paul Triebkorn

This lesson discusses both state-of-the-art detection and prevention schema in working with neurodegenerative diseases. 

Difficulty level: Beginner
Duration: 1:02:29
Speaker: : Nir Giladi

This lesson continues with the second workshop on reproducible science, focusing on additional open source tools for researchers and data scientists, such as the R programming language for data science, as well as associated tools like RStudio and R Markdown. Additionally, users are introduced to Python and iPython notebooks, Google Colab, and are given hands-on tutorials on how to create a Binder environment, as well as various containers in Docker and Singularity.

Difficulty level: Beginner
Duration: 1:16:04

This lesson contains both a lecture and a tutorial component. The lecture (0:00-20:03 of YouTube video) discusses both the need for intersectional approaches in healthcare as well as the impact of neglecting intersectionality in patient populations. The lecture is followed by a practical tutorial in both Python and R on how to assess intersectional bias in datasets. Links to relevant code and data are found below. 

Difficulty level: Beginner
Duration: 52:26
Course:

Maximize Your Research With Cloud Workspaces is a talk aimed at researchers who are looking for innovative ways to set up and execute their life science data analyses in a collaborative, extensible, open-source cloud environment. This panel discussion is brought to you by MetaCell and scientists from leading universities who share their experiences of advanced analysis and collaborative learning through the Cloud.

 

Difficulty level: Beginner
Duration: 55:43

This talk describes the relevance and power of using brain atlases as part of one's data integration pipeline. 

Difficulty level: Beginner
Duration: 15:37
Speaker: : Timo Dickscheid

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 lesson provides a thorough description of neuroimaging development over time, both conceptually and technologically. You will learn about the fundamentals of imaging techniques such as MRI and PET, as well as how the resultant data may be used to generate novel data visualization schemas. 

Difficulty level: Beginner
Duration: 1:43:57
Speaker: : Jack Van Horn

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 video will demonstrate how to create and launch a pipeline using FreeSurfer on brainlife.io.

Difficulty level: Beginner
Duration: 0:25
Speaker: :
Course:

This lecture covers the description and characterization of an input-output relationship in a information-theoretic context. 

Difficulty level: Beginner
Duration: 1:35:33

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 lesson provides instruction on how to infer results from incomplete data.

Difficulty level: Beginner
Duration: 4:28
Speaker: : Barton Poulson

This lesson provides instruction on finding parameter values, computing confidence levels, and other various statistical methods employed in data investigation.

Difficulty level: Beginner
Duration: 08:04
Speaker: : Barton Poulson

In this lesson, statistical methods and tools are described for estimating parameters in your dataset.

Difficulty level: Beginner
Duration: 5:29
Speaker: : Barton Poulson

This lesson covers how to measure the correspondece between data and model.

Difficulty level: Beginner
Duration: 3:30
Speaker: : Barton Poulson

In this lesson, you will learn the concepts behind choosing useful variables, as well as various analyses and tools to do so.

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