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This lecture and tutorial focuses on measuring human functional brain networks, as well as how to account for inherent variability within those networks. 

Difficulty level: Intermediate
Duration: 50:44
Speaker: : Caterina Gratton

This lesson provides an overview of Jupyter notebooks, Jupyter lab, and Binder, as well as their applications within the field of neuroimaging, particularly when it comes to the writing phase of your research. 

Difficulty level: Intermediate
Duration: 50:28
Speaker: : Elizabeth DuPre

This lesson introduces population models and the phase plane, and is part of the The Virtual Brain (TVB) Node 10 Series, a 4-day workshop dedicated to learning about the full brain simulation platform TVB, as well as brain imaging, brain simulation, personalised brain models, and TVB use cases.

Difficulty level: Intermediate
Duration: 1:10:41
Speaker: : Michael Schirner

This lesson introduces TVB-multi-scale extensions and other TVB tools which facilitate modeling and analyses of multi-scale data. 

Difficulty level: Intermediate
Duration: 36:10

This lecture delves into cortical (i.e., surface-based) brain simulations, as well as subcortical (i.e., deep brain) stimulations, covering the definitions, motivations, and implementations of both. 

Difficulty level: Intermediate
Duration: 39:05
Speaker: : Jil Meier

This lecture provides an introduction to entropy in general, and multi-scale entropy (MSE) in particular, highlighting the potential clinical applications of the latter. 

Difficulty level: Intermediate
Duration: 39:05
Speaker: : Jil Meier

This lecture gives an overview of how to prepare and preprocess neuroimaging (EEG/MEG) data for use in TVB.  

Difficulty level: Intermediate
Duration: 1:40:52
Speaker: : Paul Triebkorn

In this lecture, you will learn about various neuroinformatic resources which allow for 3D reconstruction of brain models. 

Difficulty level: Intermediate
Duration: 1:36:57
Speaker: : Michael Schirner

This lecture provides an general introduction to epilepsy, as well as why and how TVB can prove useful in building and testing epileptic models. 

Difficulty level: Intermediate
Duration: 37:12
Speaker: : Julie Courtiol

This lesson provides a brief introduction to the Computational Modeling of Neuronal Plasticity.

Difficulty level: Intermediate
Duration: 0:40

In this lesson, you will be introducted to a type of neuronal model known as the leaky integrate-and-fire (LIF) model.

Difficulty level: Intermediate
Duration: 1:23

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