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This lesson provides an introduction to biologically detailed computational modelling of neural dynamics, including neuron membrane potential simulation and F-I curves. 

Difficulty level: Intermediate
Duration: 8:21
Speaker: : Mike X. Cohen

In this lesson, users learn how to use MATLAB to build an adaptive exponential integrate and fire (AdEx) neuron model. 

Difficulty level: Intermediate
Duration: 22:01
Speaker: : Mike X. Cohen

In this lesson, users learn about the practical differences between MATLAB scripts and functions, as well as how to embed their neuronal simulation into a callable function.  

Difficulty level: Intermediate
Duration: 11:20
Speaker: : Mike X. Cohen

This lesson teaches users how to generate a frequency-current (F-I) curve, which describes the function that relates the net synaptic current (I) flowing into a neuron to its firing rate (F). 

Difficulty level: Intermediate
Duration: 20:39
Speaker: : Mike X. Cohen

This is the first of two workshops on reproducibility in science, during which participants are introduced to concepts of FAIR and open science. After discussing the definition of and need for FAIR science, participants are walked through tutorials on installing and using Github and Docker, the powerful, open-source tools for versioning and publishing code and software, respectively.

Difficulty level: Intermediate
Duration: 1:20:58

This is a hands-on tutorial on PLINK, the open source whole genome association analysis toolset. The aims of this tutorial are to teach users how to perform basic quality control on genetic datasets, as well as to identify and understand GWAS summary statistics. 

Difficulty level: Intermediate
Duration: 1:27:18
Speaker: : Dan Felsky

This is a tutorial on using the open-source software PRSice to calculate a set of polygenic risk scores (PRS) for a study sample. Users will also learn how to read PRS into R, visualize distributions, and perform basic association analyses. 

Difficulty level: Intermediate
Duration: 1:53:34
Speaker: : Dan Felsky

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

This lesson contains practical exercises which accompanies the first few lessons of the Neuroscience for Machine Learners (Neuro4ML) course. 

Difficulty level: Intermediate
Duration: 5:58
Speaker: : Dan Goodman

This lesson introduces some practical exercises which accompany the Synapses and Networks portion of this Neuroscience for Machine Learners course. 

Difficulty level: Intermediate
Duration: 3:51
Speaker: : Dan Goodman

Explore how to setup an epileptic seizure simulation with the TVB graphical user interface. This lesson will show you how to program the epileptor model in the brain network to simulate a epileptic seizure originating in the hippocampus. It will also show how to upload and view mouse connectivity data, as well as give a short introduction to the python script interface of TVB.

Difficulty level: Intermediate
Duration: 58:06
Speaker: : Paul Triebkorn

Brain network reconstruction from empirical data is of key importance to generate personalized virtual brain models. This lecture will introduce the basic concepts of preprocessing structural, functional and diffusion weighted neuroimages. It highlights the latest methods and pipelines to extract structural as well as functional connectomes according to a multimodal parcellation.

Difficulty level: Intermediate
Duration: 1:17:32
Speaker: : Michael Schirner

This lecture presents two recent clinical case studies using TVB: stroke recovery and dementia (due to Alzheimer’s Disease (AD)). Using a multi-scale neurophysiological model based on empirical multi-modal neuroimaging data, we show how local and global biophysical parameters characterize changes in individualized patient-specific brain dynamics, predict recovery of motor function for stroke patients, and correlate with individual differences in cognition for AD patients.

Difficulty level: Intermediate
Duration: 32:11
Speaker: : Randy McIntosh

This tutorial provides instruction on how to simulate brain tumors with TVB (reproducing publication: Marinazzo et al. 2020 Neuroimage). This tutorial comprises a didactic video, jupyter notebooks, and full data set for the construction of virtual brains from patients and health controls.

Difficulty level: Intermediate
Duration: 10:01

The tutorial on modelling strokes in TVB includes a didactic video and jupyter notebooks (reproducing publication: Falcon et al. 2016 eNeuro).

Difficulty level: Intermediate
Duration: 7:43

This tutorial covers the fundamentals of collaborating with Git and GitHub.

Difficulty level: Intermediate
Duration: 2:15:50
Speaker: : Elizabeth DuPre

This tutorial covers how to import appropriate data into The Virtual Brain, as well as how to begin constructing detailed brain models.

Difficulty level: Intermediate
Duration: 23:03
Speaker: : Patrik Bey

In this tutorial, you will learn how to run a typical TVB simulation. 

Difficulty level: Intermediate
Duration: 1:29:13
Speaker: : Paul Triebkorn

This tutorial introduces The Virtual Mouse Brain (TVMB), walking users through the necessary steps for performing simulation operations on animal brain data. 

Difficulty level: Intermediate
Duration: 42:43
Speaker: : Patrik Bey

In this tutorial, you will learn the necessary steps in modeling the brain of one of the most commonly studied animals among non-human primates, the macaque. 

Difficulty level: Intermediate
Duration: 1:00:08
Speaker: : Julie Courtiol