After introducing the local epileptor model in the previous two 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, in which 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.

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 (e.g., epilepsy cases).

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.

This tutorial demonstrates how to use the image processing pipeline with the HBP collab.

This tutorial provides instruction on how to use the TVB-NEST toolbox co-simulation in HBP collab.

In this tutorial, you will learn how to use TVB-NEST toolbox on your local computer.

This tutorial provides instruction on how to perform multi-scale simulation of Alzheimer's disease on The Virtual Brain Simulation Platform.

This presentation accompanies the paper entitled: An automated pipeline for constructing personalized virtual brains from multimodal neuroimaging data (see link below to download publication). 

This lesson consists of a supplementary video for the publication: Inferring multi-scale neural mechanisms with brain network modelling.

This lesson describes the Neuroscience Gateway , which facilitates access and use of National Science Foundation High Performance Computing resources by neuroscientists.

This lesson introduces the EEGLAB toolbox, as well as motivations for its use.

In this lesson, you will learn about the biological activity which generates and is measured by the EEG signal.

This lesson goes over the characteristics of EEG signals when analyzed in source space (as opposed to sensor space). 

This lesson describes the development of EEGLAB as well as to what extent it is used by the research community.

This lesson provides instruction as to how to build a processing pipeline in EEGLAB for a single participant. 

Whereas the previous lesson of this course outlined how to build a processing pipeline for a single participant, this lesson discusses analysis pipelines for multiple participants simultaneously. 

In addition to outlining the motivations behind preprocessing EEG data in general, this lesson covers the first step in preprocessing data with EEGLAB, importing raw data. 

Continuing along the EEGLAB preprocessing pipeline, this tutorial walks users through how to import data events as well as EEG channel locations.