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5 = Building personalized brain network models with TVB =
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7 Spase Petkoski, Damien Depannemaecker and Pierpaolo Sorrentino
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15 = What can I find here? =
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17 This collab contains access to the notebooks and reading materials that will be used during the EBRAINS Baltic-Nordic summer school 2024 [[https:~~/~~/lsmu.lt/en/events/ebrains/>>https://lsmu.lt/en/events/ebrains/]].
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19 The objective is to give to the participants an overview to building whole-brain network models with TVB. We will begin with the [[First steps of TVB>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20EBRAINS%20Baltic-Nordic%20school%202024/1_TVB_First_steps.ipynb||style="background-color: rgb(255, 255, 255);"]], where we will describe the building blocks of TVB through the paradigm of resting state activity. This will be followed by [[Modelling Epilepsy>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20EBRAINS%20Baltic-Nordic%20school%202024/2_TVB_Modelling_Epilepsy.ipynb||style="background-color: rgb(255, 255, 255);"]], where seizure propagation will be modeled. Then, there is one tutorial describing a deeper analysis of [[BOLD monitors>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20EBRAINS%20Baltic-Nordic%20school%202024/3_TVB_BOLD_digging_deeper.ipynb||style="background-color: rgb(255, 255, 255);"]].  Finally, a [[Bayesian approach>>https://wiki.ebrains.eu/bin/view/Collabs/ebrains-task-3-3/Drive#notebooks/EITN_tutorial||style="background-color: rgb(255, 255, 255);"]] is used on synthetic data to infer the posterior of the parameters.  These can all be found in the drive and accessed through the lab.
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21 = Requirements =
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23 School participants should have EBRAINS accounts to be able to access and work on the tutorials.
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25 They are also advised to install TVB locally in case of connection issues. After installation from the following link: https:~/~/www.thevirtualbrain.org/tvb/zwei/brainsimulator-software users can access many more tutorials.
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27 = Other tutorials =
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29 In addition to these notebooks, we also refer to the readers to the collab for the Showcase 1 of HBP: "Degeneracy in neuroscience - when is Big Data big enough"
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31 [[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/sga3-d1-5-showcase-1/>>url:https://wiki.ebrains.eu/bin/view/Collabs/sga3-d1-5-showcase-1/]]
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33 = References =
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38 Sanz-Leon P, Knock SA, Spiegler A, Jirsa VK. [[Mathematical framework for large-scale brain network modeling in The Virtual Brain>>https://www.sciencedirect.com/science/article/pii/S1053811915000051]]. Neuroimage. 2015 May 1;111:385-430.
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42 Schirner M, Domide L, Perdikis D, Triebkorn P, Stefanovski L, Pai R, Prodan P, Valean B, Palmer J, Langford C, Blickensdörfer A. [[Brain simulation as a cloud service: The Virtual Brain on EBRAINS>>https://www.sciencedirect.com/science/article/pii/S1053811922001021]]. NeuroImage. 2022 May 1;251:118973.
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44 Lavanga M, Stumme J, Yalcinkaya BH, Fousek J, Jockwitz C, Sheheitli H, Bittner N, Hashemi M, Petkoski S, Caspers S, Jirsa V. [[The virtual aging brain: Causal inference supports interhemispheric dedifferentiation in healthy aging>>https://www.sciencedirect.com/science/article/pii/S1053811923005542]]. NeuroImage. 2023 Dec 1;283:120403.
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48 Wang HE, Triebkorn P, Breyton M, Dollomaja B, Lemarechal JD, Petkoski S, Sorrentino P, Depannemaecker D, Hashemi M, Jirsa VK. [[Virtual brain twins: from basic neuroscience to clinical use>>https://academic.oup.com/nsr/article/11/5/nwae079/7616087]]. National Science Review. 2024 May;11(5):nwae079.
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50 Baldy N, Woodman M, Jirsa V, Hashemi M. [[Dynamic Causal Modeling in Probabilistic Programming Languages>>https://www.biorxiv.org/content/10.1101/2024.11.06.622230v1.abstract]]. bioRxiv. 2024:2024-11.
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54 Ziaeemehr A, Woodman M, Domide L, Petkoski S, Jirsa V, Hashemi M. [[Virtual Brain Inference (VBI): A flexible and integrative toolkit for efficient probabilistic inference on virtual brain models>>https://www.biorxiv.org/content/10.1101/2025.01.21.633922v1.abstract]] bioRxiv. 2025:2025-01.
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61 {{box title="**Contents**"}}
62 {{toc/}}
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