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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 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

This is a tutorial on designing a Bayesian inference model to map belief trajectories, with emphasis on gaining familiarity with Hierarchical Gaussian Filters (HGFs).

 

This lesson corresponds to slides 65-90 of the PDF below. 

Difficulty level: Intermediate
Duration: 1:15:04
Speaker: : Daniel Hauke

This lecture covers computational principles that growth cones employ to detect and respond to environmental chemotactic gradients, focusing particularly on growth-cone shape dynamics.

Difficulty level: Intermediate
Duration: 26:12
Speaker: : Geoff Goodhill

In this lecture you will learn that in developing mouse somatosensory cortex, endogenous Btbd3 translocate to the cell nucleus in response to neuronal activity and oriente primary dendrites toward active axons in the barrel hollow.

Difficulty level: Intermediate
Duration: 27:32
Speaker: : Tomomi Shimogori

In this presentation, the speaker describes some of their recent efforts to characterize the transcriptome of the developing human brain, and and introduction to the BrainSpan project.

Difficulty level: Intermediate
Duration: 30:45
Speaker: : Nenad Sestan

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 tutorial introduces pipelines and methods to compute brain connectomes from fMRI data. With corresponding code and repositories, participants can follow along and learn how to programmatically preprocess, curate, and analyze functional and structural brain data to produce connectivity matrices. 

Difficulty level: Intermediate
Duration: 1:39:04

In this lesson, you will learn about the connectome, the collective system of neural pathways in an organism, with a closer look at the neurons, synapses, and connections of particular species. 

Difficulty level: Intermediate
Duration: 6:48
Speaker: : Marcus Ghosh

This lesson delves into the human nervous system and the immense cellular, connectomic, and functional sophistication therein. 

Difficulty level: Intermediate
Duration: 8:41
Speaker: : Marcus Ghosh

In this lesson, you will hear about some of the open issues in the field of neuroscience, as well as a discussion about whether neuroscience works, and how can we know?

Difficulty level: Intermediate
Duration: 6:54
Speaker: : Marcus Ghosh

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