Skip to main content

This lecture provides an introductory overview of some of the most important concepts in software engineering.

Difficulty level: Beginner
Duration: 32:59
Speaker: : Jeff Muller

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 describes the fundamentals of genomics, from central dogma to design and implementation of GWAS, to the computation, analysis, and interpretation of polygenic risk scores. 

Difficulty level: Intermediate
Duration: 1:28:16
Speaker: : Dan Felsky

This lesson provides an overview of the database of Genotypes and Phenotypes (dbGaP), which was developed to archive and distribute the data and results from studies that have investigated the interaction of genotype and phenotype in humans.

Difficulty level: Beginner
Duration: 48:22
Speaker: : Michael Feolo

This lesson contains practical exercises which accompanies the first few lessons of the Neuroscience for Machine Learners (Neuro4ML) course. 

Difficulty level: Intermediate
Duration: 5:58
Speaker: : Dan Goodman

This video briefly goes over the exercises accompanying Week 6 of the Neuroscience for Machine Learners (Neuro4ML) course, Understanding Neural Networks.

Difficulty level: Intermediate
Duration: 2:43
Speaker: : Marcus Ghosh
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

This lesson is part 1 of 2 of a tutorial on statistical models for neural data.

Difficulty level: Beginner
Duration: 1:45:48
Speaker: : Jonathan Pillow

This lesson is part 2 of 2 of a tutorial on statistical models for neural data.

Difficulty level: Beginner
Duration: 1:50:31
Speaker: : Jonathan Pillow

This lesson provides an introduction to modeling single neurons, as well as stability analysis of neural models.

Difficulty level: Intermediate
Duration: 1:26:06
Speaker: : Bard Ermentrout

This lesson continues a thorough description of the concepts, theories, and methods involved in the modeling of single neurons. 

Difficulty level: Intermediate
Duration: 1:25:38
Speaker: : Bard Ermentrout

In this lesson you will learn about fundamental neural phenomena such as oscillations and bursting, and the effects these have on cortical networks. 

Difficulty level: Intermediate
Duration: 1:24:30
Speaker: : Bard Ermentrout

This lesson continues discussing properties of neural oscillations and networks. 

Difficulty level: Intermediate
Duration: 1:31:57
Speaker: : Bard Ermentrout

In this lecture, you will learn about rules governing coupled oscillators, neural synchrony in networks, and theoretical assumptions underlying current understanding.

Difficulty level: Intermediate
Duration: 1:26:02
Speaker: : Bard Ermentrout

This lesson provides a continued discussion and characterization of coupled oscillators. 

Difficulty level: Intermediate
Duration: 1:24:44
Speaker: : Bard Ermentrout

This lesson gives an overview of modeling neurons based on firing rate. 

Difficulty level: Intermediate
Duration: 1:26:42
Speaker: : Bard Ermentrout

This lesson characterizes the pattern generation observed in visual system hallucinations.

Difficulty level: Intermediate
Duration: 1:20:42
Speaker: : Bard Ermentrout

This lesson gives an introduction to stability analysis of neural models.

Difficulty level: Intermediate
Duration: 1:26:06
Speaker: : Bard Ermentrout

This lesson continues from the previous lectures, providing introduction to stability analysis of neural models.

Difficulty level: Intermediate
Duration: 1:25:38
Speaker: : Bard Ermentrout