This lesson reviews theoretical and mathematical descriptions of correlated spike trains.

Difficulty level: Intermediate

Duration: 2:54

Speaker: : Florence I. Kleberg

This lesson investigates the effect of correlated spike trains on spike-timing dependent plasticity (STDP).

Difficulty level: Intermediate

Duration: 1:43

Speaker: : Florence I. Kleberg

This lesson goes over synaptic normalisation, the homeostatic process by which groups of weighted inputs scale up or down their biases.

Difficulty level: Intermediate

Duration: 2:58

Speaker: : Florence I. Kleberg

In this lesson, you will learn about the intrinsic plasticity of single neurons.

Difficulty level: Intermediate

Duration: 2:08

Speaker: : Florence I. Kleberg

This lesson covers short-term facilitation, a process whereby a neuron's synaptic transmission is enhanced for a short (sub-second) period.

Difficulty level: Intermediate

Duration: 1:58

Speaker: : Florence I. Kleberg

This lesson describes short-term depression, a reduction of synaptic information transfer between neurons.

Difficulty level: Intermediate

Duration: 1:40

Speaker: : Florence I. Kleberg

This lesson briefly wraps up the course on Computational Modeling of Neuronal Plasticity.

Difficulty level: Intermediate

Duration: 0:37

Speaker: : Florence I. Kleberg

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

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

Course:

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

Speaker: : Erin Dickie and John Griffiths

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

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