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This lesson provides an introduction to the lifecycle of EEG/ERP data, describing the various phases through which these data pass, from collection to publication.

Difficulty level: Beginner
Duration: 35:30

In this lesson you will learn about experimental design for EEG acquisition, as well as the first phases of the EEG/ERP data lifecycle. 

Difficulty level: Beginner
Duration: 30:04

This lesson provides an overview of the current regulatory measures in place regarding experimental data security and privacy. 

Difficulty level: Beginner
Duration: 31:00

In this lesson, you will learn the appropriate methods for collection of both data and associated metadata during EEG experiments.

Difficulty level: Beginner
Duration: 29:14

This lesson goes over methods for managing EEG/ERP data after it has been collected, from annotation to publication. 

Difficulty level: Beginner
Duration: 39:25

In this final lesson of the course, you will learn broadly about EEG signal processing, as well as specific applications which make this kind of brain signal valuable to researchers and clinicians. 

Difficulty level: Beginner
Duration: 34:51

This lecture contains an overview of the Australian Electrophysiology Data Analytics Platform (AEDAPT), how it works, how to scale it, and how it fits into the FAIR ecosystem.

Difficulty level: Beginner
Duration: 18:56
Speaker: : Tom Johnstone
Course:

An introduction to data management, manipulation, visualization, and analysis for neuroscience. Students will learn scientific programming in Python, and use this to work with example data from areas such as cognitive-behavioral research, single-cell recording, EEG, and structural and functional MRI. Basic signal processing techniques including filtering are covered. The course includes a Jupyter Notebook and video tutorials.

 

Difficulty level: Beginner
Duration: 1:09:16
Speaker: : Aaron J. Newman

This lesson gives a description of the BrainHealth Databank, a repository of many types of health-related data, whose aim is to accelerate research, improve care, and to help better understand and diagnose mental illness, as well as develop new treatments and prevention strategies. 

 

This lesson corresponds to slides 46-78 of the PDF below. 

Difficulty level: Beginner
Duration: 1:12:25
Speaker: : Joanna Yu

This hands-on tutorial walks you through DataJoint platform, highlighting features and schema which can be used to build robost neuroscientific pipelines. 

Difficulty level: Beginner
Duration: 26:06
Speaker: : Milagros Marin

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 focuses on the structured validation process within computational neuroscience, including the tools, services, and methods involved in simulation and analysis.

Difficulty level: Beginner
Duration: 14:19
Speaker: : Michael Denker

This lecture discusses the FAIR principles as they apply to electrophysiology data and metadata, the building blocks for community tools and standards, platforms and grassroots initiatives, and the challenges therein.

Difficulty level: Beginner
Duration: 8:11
Speaker: : Thomas Wachtler
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
Course:

This session will include presentations of infrastructure that embrace the FAIR principles developed by members of the INCF Community.

 

This lecture provides an overview of The Virtual Brain Simulation Platform.

 

Difficulty level: Beginner
Duration: 9:36
Speaker: : Petra Ritter

This lesson gives a tour of how popular virtualization tools like Docker and Singularity are playing a crucial role in improving reproducibility and enabling high-performance computing in neuroscience.

Difficulty level: Beginner
Duration: 2:51:34
Speaker: : Peer Herholz

This lesson gives an in-depth introduction of ethics in the field of artificial intelligence, particularly in the context of its impact on humans and public interest. As the healthcare sector becomes increasingly affected by the implementation of ever stronger AI algorithms, this lecture covers key interests which must be protected going forward, including privacy, consent, human autonomy, inclusiveness, and equity. 

Difficulty level: Beginner
Duration: 1:22:06
Speaker: : Daniel Buchman

This lecture picks up from the previous lesson, providing an overview of neuroimaging techniques and their clinical applications.

Difficulty level: Beginner
Duration: 41:00
Speaker: : Dafna Ben Bashat

This lesson provides a basic introduction to clinical presentation of schizophrenia, its etiology, and current treatment options.

Difficulty level: Beginner
Duration: 51:49

This lecture focuses on the rationale for employing neuroimaging methods for movement disorders.

Difficulty level: Beginner
Duration: 1:04:04
Speaker: : Bogdan Draganski