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This lesson delves into the the structure of one of the brain's most elemental computational units, the neuron, and how said structure influences computational neural network models. 

Difficulty level: Intermediate
Duration: 6:33
Speaker: : Marcus Ghosh

In this lesson you will learn how machine learners and neuroscientists construct abstract computational models based on various neurophysiological signalling properties. 

Difficulty level: Intermediate
Duration: 10:52
Speaker: : Dan Goodman

This lesson describes spike timing-dependent plasticity (STDP), a biological process that adjusts the strength of connections between neurons in the brain, and how one can implement or mimic this process in a computational model. You will also find links for practical exercises at the bottom of this page. 

Difficulty level: Intermediate
Duration: 12:50
Speaker: : Dan Goodman

 In this lesson, you will learn about some of the many methods to train spiking neural networks (SNNs) with either no attempt to use gradients, or only use gradients in a limited or constrained way. 

Difficulty level: Intermediate
Duration: 5:14
Speaker: : Dan Goodman

In this lesson, you will learn how to train spiking neural networks (SNNs) with a surrogate gradient method. 

Difficulty level: Intermediate
Duration: 11:23
Speaker: : Dan Goodman

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 discusses a gripping neuroscientific question: why have neurons developed the discrete action potential, or spike, as a principle method of communication? 

Difficulty level: Intermediate
Duration: 9:34
Speaker: : Dan Goodman

Along the example of a patient with bi-temporal epilepsy, we show step by step how to develop a Virtual Epileptic Patient (VEP) brain model and integrate patient-specific information such as brain connectivity, epileptogenic zone and MRI lesions. The patient's brain network model is then evaluated via simulation, data fitting and mathematical analysis. This lecture demonstrates how to develop novel personalized strategies towards therapy and intervention using TVB.

Difficulty level: Intermediate
Duration: 48:57
Speaker: : Julie Courtiol

This lecture focuses on higher-level simulation scenarios using stimulation protocols. We demonstrate how to build stimulation patterns in TVB, and use them in a simulation to induced activity dissipating into experimentally known resting-state networks in human and mouse brain, a well as to obtain EEG recordings reproducing empirical findings of other researchers.

Difficulty level: Intermediate
Duration: 47:14
Speaker: : Andreas Spiegler

Learn how to create a standard extracellular electrophysiology dataset in NWB using Python.

Difficulty level: Intermediate
Duration: 23:10
Speaker: : Ryan Ly

Learn how to create a standard calcium imaging dataset in NWB using Python.

Difficulty level: Intermediate
Duration: 31:04
Speaker: : Ryan Ly

In this tutorial, you will learn how to create a standard intracellular electrophysiology dataset in NWB using Python.

Difficulty level: Intermediate
Duration: 20:23
Speaker: : Pamela Baker

In this tutorial, you will learn how to use the icephys-metadata extension to enter meta-data detailing your experimental paradigm.

Difficulty level: Intermediate
Duration: 27:18
Speaker: : Oliver Ruebel

In this tutorial, users learn how to create a standard extracellular electrophysiology dataset in NWB using MATLAB.

Difficulty level: Intermediate
Duration: 45:46
Speaker: : Ben Dichter

Learn how to create a standard calcium imaging dataset in NWB using MATLAB.

Difficulty level: Intermediate
Duration: 39:10
Speaker: : Ben Dichter

Learn how to create a standard intracellular electrophysiology dataset in NWB.

Difficulty level: Intermediate
Duration: 20:22
Speaker: : Pamela Baker

This lesson gives an overview of the Brainstorm package for analyzing extracellular electrophysiology, including preprocessing, spike sorting, trial alignment, and spectrotemporal decomposition.

Difficulty level: Intermediate
Duration: 47:47

This lesson provides an overview of the CaImAn package, as well as a demonstration of usage with NWB.

Difficulty level: Intermediate
Duration: 44:37

This lesson gives an overview of the SpikeInterface package, including demonstration of data loading, preprocessing, spike sorting, and comparison of spike sorters.

Difficulty level: Intermediate
Duration: 1:10:28
Speaker: : Alessio Buccino

In this lesson, users will learn about the NWBWidgets package, including coverage of different data types, and information for building custom widgets within this framework.

Difficulty level: Intermediate
Duration: 47:15
Speaker: : Ben Dichter