Skip to main content
Lecture title:

2nd part of the lecture. This lecture will discuss how understanding and applying simple neuroanatomical rules, one can localize the damage along the neuroaxis, the first crucial step toward making the correct clinical diagnosis and initiating treatment.

Difficulty level: Beginner
Duration: 42:35
Speaker: : Eitan Auriel
Lecture title:

This lecture provides an overview of depression (epidemiology and course of the disorder), clinical presentation, somatic co-morbidity, and treatment options.

Difficulty level: Beginner
Duration: 37:51
Lecture title:

Introduction to simple spiking neuron models.

Difficulty level: Beginner
Duration: 48 Slides
Speaker: : Zubin Bhuyan
Lecture title:

Introduction to simple spiking neuron models.

Difficulty level: Beginner
Duration: 48 Slides
Speaker: : Zubin Bhuyan
Lecture title:

Audio slides presentation to accompany the paper titled: An automated pipeline for constructing personalized virtual brains from multimodal neuroimaging data. Authors: M. Schirner, S. Rothmeier, V. Jirsa, A.R. McIntosh, P. Ritter.

Difficulty level: Beginner
Duration: 4:56
Speaker: :
Lecture title:

A brief overview of the Python programming language, with an emphasis on tools relevant to data scientists. This lecture was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Beginner
Duration: 1:16:36
Speaker: : Tal Yarkoni
Lecture title:

Tutorial on collaborating with Git and GitHub. This tutorial was part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

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

This lecture covers an Introduction to neuron anatomy and signaling, and different types of models, including the Hodgkin-Huxley model.

Difficulty level: Beginner
Duration: 1:23:01
Speaker: : Gaute Einevoll
Lecture title:

The Virtual Brain is an open-source, multi-scale, multi-modal brain simulation platform. In this lesson, you get introduced to brain simulation in general and to The Virtual brain in particular. Prof. Ritter will present the newest approaches for clinical applications of The Virtual brain - that is, for stroke, epilepsy, brain tumors and Alzheimer’s disease - and show how brain simulation can improve diagnostics, therapy and understanding of neurological disease.

Difficulty level: Beginner
Duration: 1:35:08
Speaker: : Petra Ritter
Lecture title:

The concept of neural masses, an application of mean field theory, is introduced as a possible surrogate for electrophysiological signals in brain simulation. The mathematics of neural mass models and their integration to a coupled network are explained. Bifurcation analysis is presented as an important technique in the understanding of non-linear systems and as a fundamental method in the design of brain simulations. Finally, the application of the described mathematics is demonstrated in the exploration of brain stimulation regimes.

Difficulty level: Beginner
Duration: 1:49:24
Speaker: : Andreas Spiegler
Lecture title:

The simulation of the virtual epileptic patient is presented as an example of advanced brain simulation as a translational approach to deliver improved results in clinics. The fundamentals of epilepsy are explained. On this basis, the concept of epilepsy simulation is developed. By using an iPython notebook, the detailed process of this approach is explained step by step. In the end, you are able to perform simple epilepsy simulations your own.

Difficulty level: Beginner
Duration: 1:28:53
Speaker: : Julie Courtiol
Lecture title:

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
Lecture title:

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
Lecture title:

This lecture presents the Graphical (GUI) and Command Line (CLI) User Interface of TVB. Alongside with the speakers, explore and interact with all means necessary to generate, manipulate and visualize connectivity and network dynamics. Speakers: Paula Popa & Mihai Andrei

Difficulty level: Beginner
Duration: 1:02:16
Speaker: :
Lecture title:

This lecture briefly introduces The Virtual Brain (TVB), a multi-scale, multi-modal neuroinformatics platform for full brain network simulations using biologically realistic connectivity, as well as its potential neuroscience applications: for example with epilepsy.

Difficulty level: Beginner
Duration: 8:53
Speaker: : Petra Ritter
Lecture title:

This lecture introduces the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components.

Difficulty level: Beginner
Duration:
Speaker: : Randy McIntosh
Lecture title:

Computational models provide a framework for integrating data across spatial scales and for exploring hypotheses about the biological mechanisms underlying neuronal and network dynamics. However, as models increase in complexity, additional barriers emerge to the creation, exchange, and re-use of models. Successful projects have created standards for describing complex models in neuroscience and provide open source tools to address these issues. This lecture provides an overview of these projects and make a case for expanded use of resources in support of reproducibility and validation of models against experimental data.

Difficulty level: Beginner
Duration: 1:00:39
Speaker: : Sharon Crook