Changes for page User Story: TVB

Last modified by ldomide on 2024/05/20 08:51
From version 19.1
edited by michaels
on 2020/06/02 08:59
Change comment: There is no comment for this version
To version 24.1
edited by evanhancock
on 2020/07/22 13:57
Change comment: There is no comment for this version

Summary

Details

Page properties
Author
... ... @@ -1,1 +1,1 @@
1 -XWiki.michaels
1 +XWiki.evanhancock
Content
... ... @@ -2,10 +2,16 @@
2 2  (((
3 3  (% class="container" %)
4 4  (((
5 -= From MRI to personalized brain simulation =
5 += From MRI to personalized brain simulation using TVB-EBRAINS integrated workflows =
6 6  
7 7  Here we explain step by step how to use The Virtual Brain (TVB) tools for end-to-end personalized brain simulation. We start by finding shared MRI data using KnowledgeGraph, create a brain model from extracted connectomes using TVB pipeline, and simulate neural activity using TVB brain network model simulators. We will use Jupyter notebooks on EBRAINS Collab platforms for frontend operations and supercomputers in the backend for intensive number crunching.
8 8  
9 +Watch these videos to learn more:
10 +
11 +* [[TVB on EBRAINS (short version)>>https://www.youtube.com/watch?v=EETRdGskiWQ&t=2s]]
12 +* [[TVB on EBRAINS (long version)>>https://www.youtube.com/watch?v=VYhR9RNRIpA&t=2s]]
13 +* [[Series of mini videos>>https://www.youtube.com/playlist?list=PLVtblERyzDeLcVv4BbW3BvmO8D-qVZxKf]]
14 +
9 9  [[image:export_overview_new2.png]]
10 10  )))
11 11  )))
... ... @@ -16,7 +16,7 @@
16 16  (((
17 17  == TVB pipeline: Extract connectomes ==
18 18  
19 -As a first step we browse through KnowledgeGraph in order to find a suitable dataset to construct a brain model. The dataset must contain diffusion-weighted MRI data, in order to extract a structural connectome, which will form the basis of a brain network model. Structural connectivity extracted from diffusion MRI is used to quantify how strongly brain regions interact in the brain model. Next, the data set must contain functional MRI (fMRI) data, because a common approach is to tune the parameters of the brain model such that the simulated fMRI functional connectivity fits with the empirical fMRI data. For fitting, we usually compute functional connectivity matrices from simulated and empirical data. Finally, we need anatomical T1-weighted MRI to extract cortical surfaces and to perform a parcellation of the brain into different regions.
25 +As a first step we browse through The Knowledge Graph in order to find a suitable dataset to construct a brain model. The dataset must contain diffusion-weighted MRI data, in order to extract a structural connectome, which will form the basis of a brain network model. Structural connectivity extracted from diffusion MRI is used to quantify how strongly brain regions interact in the brain model. Next, the data set must contain functional MRI (fMRI) data, because a common approach is to tune the parameters of the brain model such that the simulated fMRI functional connectivity fits with the empirical fMRI data. For fitting, we usually compute functional connectivity matrices from simulated and empirical data. Finally, we need anatomical T1-weighted MRI to extract cortical surfaces and to perform a parcellation of the brain into different regions.
20 20  
21 21  
22 22  * Open KG in browser: [[https:~~/~~/kg.ebrains.eu/search/>>url:https://kg.ebrains.eu/search/||rel="noopener noreferrer" target="_blank"]]
... ... @@ -117,7 +117,7 @@
117 117  
118 118  TVB EduPack provides didactic use cases for The Virtual Brain. Typically a use case consists of a jupyter notebook and a didactic video. EduPack use cases help the user to reproduce TVB based publications or to get started quickly with TVB. EduCases demonstrate for example how to use TVB via the Collaboratory of the Human Brain Project, how to run multi-scale co-simulations with other simulators such as NEST, how to process imaging data to construct personalized virtual brains of healthy individuals and patients.
119 119  
120 -[[https:~~/~~/training.incf.org/studytrack/virtual-brain-simulation-platform>>https://training.incf.org/studytrack/virtual-brain-simulation-platform||rel=" noopener noreferrer" target="_blank"]]
126 +[[https:~~/~~/training.incf.org/studytrack/virtual-brain-simulation-platform>>https://training.incf.org/studytrack/virtual-brain-simulation-platform||rel="noopener noreferrer" target="_blank"]]
121 121  
122 122  
123 123  )))
Collaboratory.Apps.Collab.Code.CollabClass[0]
Description
... ... @@ -1,0 +1,1 @@
1 +TVB User Story: From MRI to personalized brain simulation using TVB-EBRAINS integrated workflows. Here we explain step by step how to use The Virtual Brain (TVB) tools for end-to-end personalized brain simulation.