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This video gives a brief introduction to Neuro4ML's lessons on neuromorphic computing - the use of specialized hardware which either directly mimics brain function or is inspired by some aspect of the way the brain computes. 

Difficulty level: Intermediate
Duration: 3:56
Speaker: : Dan Goodman

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 lesson contains the first part of the lecture Data Science and Reproducibility. You will learn about the development of data science and what the term currently encompasses, as well as how neuroscience and data science intersect. 

Difficulty level: Beginner
Duration: 32:18
Speaker: : Ariel Rokem

The lecture provides an overview of the core skills and practical solutions required to practice reproducible research.

Difficulty level: Beginner
Duration: 1:25:17
Speaker: : Fernando Perez

This lecture provides an introduction to reproducibility issues within the fields of neuroimaging and fMRI, as well as an overview of tools and resources being developed to alleviate the problem.

Difficulty level: Beginner
Duration: 1:03:07
Speaker: : Russell Poldrack

This lecture provides a historical perspective on reproducibility in science, as well as the current limitations of neuroimaging studies to date. This lecture also lays out a case for the use of meta-analyses, outlining available resources to conduct such analyses. 

Difficulty level: Beginner
Duration: 55:39
Speaker: : Angela Laird

Serving as good refresher, this lesson explains the maths and logic concepts that are important for programmers to understand, including sets, propositional logic, conditional statements, and more.

This compilation is courtesy of freeCodeCamp.

Difficulty level: Beginner
Duration: 1:00:07
Speaker: : Shawn Grooms

This lesson provides a useful refresher which will facilitate the use of Matlab, Octave, and various matrix-manipulation and machine-learning software.

This lesson was created by RootMath.

Difficulty level: Beginner
Duration: 1:21:30
Speaker: :

This lecture covers the history of behaviorism and the ultimate challenge to behaviorism. 

Difficulty level: Beginner
Duration: 1:19:08

This lecture covers various learning theories.

Difficulty level: Beginner
Duration: 1:00:42

This lesson characterizes different types of learning in a neuroscientific and cellular context, and various models employed by researchers to investigate the mechanisms involved. 

Difficulty level: Intermediate
Duration: 3:54
Speaker: : Dan Goodman

In this lesson, you will learn about different approaches to modeling learning in neural networks, particularly focusing on system parameters such as firing rates and synaptic weights impact a network. 

Difficulty level: Intermediate
Duration: 9:40
Speaker: : Dan Goodman

In this lecture, you will learn about current methods, approaches, and challenges to studying human neuroanatomy, particularly through the lense of neuroimaging data such as fMRI and diffusion tensor imaging (DTI). 

Difficulty level: Intermediate
Duration: 1:35:14
Speaker: : Matt Glasser

This module covers some basic anatomy such as the brain’s major divisions (brainstem, cerebellum, cerebrum), the cerebral lobes (frontal, temporal, parietal, and occipital), the central and peripheral nervous systems, theories of cognition, and brain orientation terms.

Difficulty level: Beginner
Duration: 11:54
Speaker: : Harrison Canning