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This lecture provides an introduction to the Brain Imaging Data Structure (BIDS), a standard for organizing human neuroimaging datasets.

Difficulty level: Intermediate
Duration: 56:49

This lecture covers the rationale for developing the DAQCORD, a framework for the design, documentation, and reporting of data curation methods in order to advance the scientific rigour, reproducibility, and analysis of data.

Difficulty level: Intermediate
Duration: 17:08
Speaker: : Ari Ercole

In this lesson, you will learn in more detail about neuromorphic computing, that is, non-standard computational architectures that mimic some aspect of the way the brain works. 

Difficulty level: Intermediate
Duration: 10:08
Speaker: : Dan Goodman

This video provides a very quick introduction to some of the neuromorphic sensing devices, and how they offer unique, low-power applications.

Difficulty level: Intermediate
Duration: 2:37
Speaker: : Dan Goodman

This is a continuation of the talk on the cellular mechanisms of neuronal communication, this time at the level of brain microcircuits and associated global signals like those measureable by electroencephalography (EEG). This lecture also discusses EEG biomarkers in mental health disorders, and how those cortical signatures may be simulated digitally.

Difficulty level: Intermediate
Duration: 1:11:04
Speaker: : Etay Hay

This lecture gives an overview of how to prepare and preprocess neuroimaging (EEG/MEG) data for use in TVB.  

Difficulty level: Intermediate
Duration: 1:40:52
Speaker: : Paul Triebkorn

This lesson describes the principles underlying functional magnetic resonance imaging (fMRI), diffusion-weighted imaging (DWI), tractography, and parcellation. These tools and concepts are explained in a broader context of neural connectivity and mental health. 

Difficulty level: Intermediate
Duration: 1:47:22

This lecture presents an overview of functional brain parcellations, as well as a set of tutorials on bootstrap agregation of stable clusters (BASC) for fMRI brain parcellation.

Difficulty level: Advanced
Duration: 50:28
Speaker: : Pierre Bellec

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

While the previous lesson in the Neuro4ML course dealt with the mechanisms involved in individual synapses, this lesson discusses how synapses and their neurons' firing patterns may change over time. 

Difficulty level: Intermediate
Duration: 4:48
Speaker: : Marcus Ghosh