Course:

In this tutorial on simulating whole-brain activity using Python, participants can follow along using corresponding code and repositories, learning the basics of neural oscillatory dynamics, evoked responses and EEG signals, ultimately leading to the design of a network model of whole-brain anatomical connectivity.

Difficulty level: Intermediate

Duration: 1:16:10

Speaker: : John Griffiths

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

Speaker: : Andreea Diaconescu

Similarity Network Fusion (SNF) is a computational method for data integration across various kinds of measurements, aimed at taking advantage of the common as well as complementary information in different data types. This workshop walks participants through running SNF on EEG and genomic data using RStudio.

Difficulty level: Intermediate

Duration: 1:21:38

Speaker: : Dan Felsky

This lecture goes into detailed description of how to process workflows in the virtual research environment (VRE), including approaches for standardization, metadata, containerization, and constructing and maintaining scientific pipelines.

Difficulty level: Intermediate

Duration: 1:03:55

Speaker: : Patrik Bey

In this third and final hands-on tutorial from the *Research Workflows for Collaborative Neuroscience *workshop, you will learn about workflow orchestration using open source tools like DataJoint and Flyte.

Difficulty level: Intermediate

Duration: 22:36

Speaker: : Daniel Xenes

Course:

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

Course:

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

Course:

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

Course:

This lesson continues discussing properties of neural oscillations and networks.

Difficulty level: Intermediate

Duration: 1:31:57

Speaker: : Bard Ermentrout

Course:

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

Course:

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

Difficulty level: Intermediate

Duration: 1:24:44

Speaker: : Bard Ermentrout

Course:

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

Difficulty level: Intermediate

Duration: 1:26:42

Speaker: : Bard Ermentrout

Course:

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

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