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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

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

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

In this lesson, you will learn about phenomena of neural populations such as synchrony, oscillations, and bursting.

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

This lesson continues from the previous lecture, giving an overview of various neural phenomena such as oscillations and bursting. 

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

This lesson provides more context around weakly coupled oscillators.

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

This lesson builds upon previous lectures in this series, providing an overview of coupled oscillators.

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

In this lesson, you will learn about neuronal models based on their spike rate. 

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

In this lesson, you will learn about neural activity pattern generation in visual system hallucinations.

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

This lesson describes how DataLad allows you to track and mange both your data and analysis code, thereby facilitating reliable, reproducible, and shareable research.

Difficulty level: Intermediate
Duration: 59:34

This tutorial covers the fundamentals of collaborating with Git and GitHub.

Difficulty level: Intermediate
Duration: 2:15:50
Speaker: : Elizabeth DuPre