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This tutorial demonstrates how to perform cell-type deconvolution in order to estimate how proportions of cell-types in the brain change in response to various conditions. While these techniques may be useful in addressing a wide range of scientific questions, this tutorial will focus on the cellular changes associated with major depression (MDD). 

Difficulty level: Intermediate
Duration: 1:15:14
Speaker: : Keon Arbabi

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

Explore how to setup an epileptic seizure simulation with the TVB graphical user interface. This lesson will show you how to program the epileptor model in the brain network to simulate a epileptic seizure originating in the hippocampus. It will also show how to upload and view mouse connectivity data, as well as give a short introduction to the python script interface of TVB.

Difficulty level: Intermediate
Duration: 58:06
Speaker: : Paul Triebkorn

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
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 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 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 lesson introduces the EEGLAB toolbox, as well as motivations for its use.

Difficulty level: Beginner
Duration: 15:32
Speaker: : Arnaud Delorme

In this lesson, you will learn about the biological activity which generates and is measured by the EEG signal.

Difficulty level: Beginner
Duration: 6:53
Speaker: : Arnaud Delorme

This lesson goes over the characteristics of EEG signals when analyzed in source space (as opposed to sensor space). 

Difficulty level: Beginner
Duration: 10:56
Speaker: : Arnaud Delorme

This lesson describes the development of EEGLAB as well as to what extent it is used by the research community.

Difficulty level: Beginner
Duration: 6:06
Speaker: : Arnaud Delorme

This lesson provides instruction as to how to build a processing pipeline in EEGLAB for a single participant. 

Difficulty level: Beginner
Duration: 9:20
Speaker: :

Whereas the previous lesson of this course outlined how to build a processing pipeline for a single participant, this lesson discusses analysis pipelines for multiple participants simultaneously. 

Difficulty level: Beginner
Duration: 10:55
Speaker: : Arnaud Delorme

In addition to outlining the motivations behind preprocessing EEG data in general, this lesson covers the first step in preprocessing data with EEGLAB, importing raw data. 

Difficulty level: Beginner
Duration: 8:30
Speaker: : Arnaud Delorme

Continuing along the EEGLAB preprocessing pipeline, this tutorial walks users through how to import data events as well as EEG channel locations.

Difficulty level: Beginner
Duration: 11:53
Speaker: : Arnaud Delorme

This tutorial instructs users how to visually inspect partially pre-processed neuroimaging data in EEGLAB, specifically how to use the data browser to investigate specific channels, epochs, or events for removable artifacts, biological (e.g., eye blinks, muscle movements, heartbeat) or otherwise (e.g., corrupt channel, line noise). 

Difficulty level: Beginner
Duration: 5:08
Speaker: : Arnaud Delorme

This tutorial provides instruction on how to use EEGLAB to further preprocess EEG datasets by identifying and discarding bad channels which, if left unaddressed, can corrupt and confound subsequent analysis steps. 

Difficulty level: Beginner
Duration: 13:01
Speaker: : Arnaud Delorme

Users following this tutorial will learn how to identify and discard bad EEG data segments using the MATLAB toolbox EEGLAB. 

Difficulty level: Beginner
Duration: 11:25
Speaker: : Arnaud Delorme

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