Skip to main content

This lesson goes over various potential inputs to neuronal synapses, loci of neural communication.

Difficulty level: Intermediate
Duration: 1:20

This lesson describes the how and why behind implementing integration time steps as part of a neuronal model.

Difficulty level: Intermediate
Duration: 1:08

In this lesson, you will learn about neural spike trains which can be characterized as having a Poisson distribution.

Difficulty level: Intermediate
Duration: 1:18

This lesson covers spike-rate adaptation, the process by which a neuron's firing pattern decays to a low, steady-state frequency during the sustained encoding of a stimulus.

Difficulty level: Intermediate
Duration: 1:26

This lesson provides a brief explanation of how to implement a neuron's refractory period in a computational model.

Difficulty level: Intermediate
Duration: 0:42

In this lesson, you will learn a computational description of the process which tunes neuronal connectivity strength, spike-timing-dependent plasticity (STDP).

Difficulty level: Intermediate
Duration: 2:40

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

Difficulty level: Intermediate
Duration: 2:54

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

Difficulty level: Intermediate
Duration: 1:43

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

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

Difficulty level: Intermediate
Duration: 2:08

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

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

Difficulty level: Intermediate
Duration: 1:40

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

Difficulty level: Intermediate
Duration: 0:37

This lesson provides an overview of The Virtual Brain integrated workflows on EBRAINS.

Difficulty level: Intermediate
Duration: 32:21
Speaker: : Petra Ritter

This lesson walks users through the Image Processing Pipeline, an integral part of the TVB on EBRAINS integrated workflows.

Difficulty level: Intermediate
Duration: 24:31
Speaker: : Michael Schirner

This lesson gives an overview of The Virtual Brain simulator and its integration into the Human Brain Project Cloud and EBRAINS infrastructure.

Difficulty level: Intermediate
Duration: 24:55
Speaker: : Lia Domide

In this lesson, users will get an overview of the EBRAINS integrated Fast TVB, a C implementation of TVB that is orders of magnitude faster than the original Python TVB, and capable of performing parallelizable simulations in the cloud.

Difficulty level: Intermediate
Duration: 8:38
Speaker: : Michael Schirner

In this lesson you will learn about the Bayesian Virtual Epileptic Patient (BVEP), a research use case using TVB supported on the EBRAINS infrastructure.

Difficulty level: Intermediate
Duration: 15:39
Speaker: : Meysam Hashemi

This lesson gives a brief overview of the multi-scale co-simulation between TVB-NEST and Elephant on the EBRAINS infrastructure.

Difficulty level: Intermediate
Duration: 6:05
Speaker: : Wouter Klijn

In this lesson, you will learn about the process of constructing models for TVB automatically on the EBRAINS infrastructure.

Difficulty level: Intermediate
Duration: 23:11