Changes for page User Story: TVB

Last modified by ldomide on 2024/05/20 08:51
From version 9.1
edited by michaels
on 2020/05/12 09:32
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To version 6.1
edited by michaels
on 2020/05/12 09:28
Change comment: There is no comment for this version

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5 -= From MRI to personal brain simulation =
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7 -Here we explain step by step how to use 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.
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7 +My collab's subtitle
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17 -== TVB pipeline: extract connectomes ==
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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.
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22 -* Open KG in browser: [[https:~~/~~/kg.ebrains.eu/search/>>url:https://kg.ebrains.eu/search/]]
23 -* Browse through KG and look for a data set that contains the above-mentioned MRI modalities. To find a suitable data set you may use the “Filter” sidebar on the left and e.g. select “Homo sapiens” or “magnetic resonance imaging”. In the following we are going to use the data set “Individual Brain Charting: ARCHI Social”. [[https:~~/~~/kg.ebrains.eu/search/instances/Dataset/f8c40aadc4939ad493bf7c839b82cb40>>https://kg.ebrains.eu/search/instances/Dataset/f8c40aadc4939ad493bf7c839b82cb40]]
24 -* The data-set can be downloaded from [[https:~~/~~/openneuro.org/datasets/ds000244/versions/1.0.0>>url:https://openneuro.org/datasets/ds000244/versions/1.0.0]]
23 +Describe the audience of this collab.
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1 -XWiki.michaels
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