Learn how to simulate strokes with the simulation platform, The Virtual Brain. We will go through two papers: Functional Mechanisms of Recovery after Stroke: Modeling with The Virtual Brain and The Virtual Brain: Modeling Biological Correlates of Recovery After Chronic Stroke, and apply the same processes with our own structural connectivity data set in The Virtual Brain.
Learn how to simulate seizure events and epilepsy in The Virtual Brain. We will look at the paper: On the Nature of Seizure Dynamics which describes a new local model called the Epileptor, and apply this same model in The Virtual Brain. This is part 1 of 2 in a series explaining how to use the Epileptor. In this part, we focus on setting up the parameters.
In this lecture we will focus on a paper called “The Virtual Epileptic Patient: Individualized whole-brain models of epilepsy spread”. Within their work, the authors used the epileptor model to simulate a patient's individual seizure. To understand the concept we will have a closer look at the equations of the epileptor model and particular the epileptogenicity index which controls the excitability of each brain region. Subsequently, we will begin to setup the epileptogenic zone in our own brain network model with TVB.
After introducing the local epileptor model in the previous 2 videos we will now use it in a large scale brain simulation. We again focus on the paper “The Virtual Epileptic Patient: Individualized whole-brain models of epilepsy spread”. Two simulations with different epileptogenicity across the network are visualized to show the difference in seizure spread across the cortex.
This lecture gives an overview on the article “Individual brain structure and modelling predict seizure propagation” where 15 subjects with epilepsy were modelled to predict individual epileptogenic zones. With the TVB GUI we will model seizure spread and the effect of lesioning the connectome. The impact of cutting edges in the network on seizure spreading will be visualized.
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
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.
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.
The landscape of scientific research is changing. Today’s researchers need to participate in large-scale collaborations, obtain and manage funding, share data, publish, and undertake knowledge translation activities in order to be successful. As per these increasing demands, Science Management is now a vital piece of the environment.
Tutorial on how to use the image processing pipeline with the HBP collab. Authors: M. Schirner, P. Triebkorn, P. Ritter
Tutorial on how to perform multi-scale simulation of Alzheimer's disease on The Virtual Brain Simulation Platform. Authors: L. Stefanovski, P. Triebkorn, M.A. Diaz-Cortes, A. Solodkin, V. Jirsa, A.R. McIntosh, P. Ritter
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.
Supplement video for the publication: Inferring multi-scale neural mechanisms with brain network modelling. Authors: M. Schirner, A.R. McIntosh, V. Jirsa, G. Deco, P. Ritter
Longitudinal Online Research and Imaging System (LORIS) is a web-based data and project management software for neuroimaging research studies. It is an open source framework for storing and processing behavioural, clinical, neuroimaging and genetic data. LORIS also makes it easy to manage large datasets acquired over time in a longitudinal study, or at different locations in a large multi-site study.
Tutorial on how to simulate brain tumor brains 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. Authors: Hannelore Aerts, Michael Schirner, Ben Jeurissen, DIrk Van Roost, Eric Achten, Petra Ritter, Daniele Marinazzo
The tutorial comprises a didactic video and jupyter notebooks (reproducing publication: Falcon et al. 2016 eNeuro). Contributors: Daniele Marinazzo, Petra Ritter, Paul Triebkorn, Ana Solodkin
Learn how to create a standard extracellular electrophysiology dataset in NWB using Python