Wiki source code of TVB EBRAINS hands-on

Last modified by petkoski on 2025/10/09 12:30

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7.1	5	= Building personalized brain network models with TVB =
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19.2	7	Spase Petkoski and Marmaduke Woodman
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	15	= What can I find here? =
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21.1	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/]] and then recycled for the TVB tutorials at [[ICANN 2025>>https://e-nns.org/icann2025/]] conference and at the EnvironMENTAL project's [[Summer School on environmental and computational neuroscience>>https://www.environmental-project.org/participants/environmental-summer-school-environmental-and-computational-neuroscience/]].
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19.3	19	The objective is to give to the participants an overview to building whole-brain network models with TVB.
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23.1	21	We will begin with the [[First steps of TVB>>https://lab.jsc.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20EBRAINS%20hands-on/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.
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23.1	23	This will be followed by [[Modelling Epilepsy>>https://lab.jsc.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20EBRAINS%20hands-on/2_TVB_Modelling_Epilepsy.ipynb\|\|style="background-color: rgb(255, 255, 255);"]], where seizure propagation will be modeled.
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23.1	25	Then, there is one tutorial describing a deeper analysis of [[BOLD monitors>>https://lab.jsc.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20EBRAINS%20hands-on/3_TVB_BOLD_digging_deeper.ipynb\|\|style="background-color: rgb(255, 255, 255);"]].
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23.1	27	There is also a fourth tutorial which describes application of a fast back-end implementation of the Montbrio-Pazo-Roxin model used for modeling [[resting state fMRI >>https://lab.jsc.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20EBRAINS%20hands-on/MPR_rs.ipynb]]. This is a based on a more detailed showcase [[Degeneracy in neuroscience>>https://wiki.ebrains.eu/bin/view/Collabs/sga3-d1-5-showcase-1/]], which described the interpersonal variability analyzed by the [[Virtual Ageing Brain>>https://www.sciencedirect.com/science/article/pii/S1053811923005542?via%3Dihub]] study.
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23.1	30	Finally, the collab contains one tutorial where a [[Bayesian approach>>https://lab.jsc.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20EBRAINS%20hands-on/DCM_ERPs_MCMC_ebrains.ipynb\|\|style="background-color: rgb(255, 255, 255);"]] is used on synthetic data to infer the posterior of the parameters for a single brain region.
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	33	These can all be found in the drive and accessed through the lab.
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12.1	35	= Requirements =
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13.1	37	School participants should have EBRAINS accounts to be able to access and work on the tutorials.
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18.2	39	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. For inference, other tools such as Numpyro ([[https:~~/~~/github.com/ins-amu/DCM_ERP_PPLs>>https://github.com/ins-amu/DCM_ERP_PPLs]]) or VBI tool ([[https:~~/~~/github.com/ins-amu/vbi>>https://github.com/ins-amu/vbi]]) will be required.
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10.1	41	= Other tutorials =
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13.1	43	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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10.1	45	[[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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16.2	47	[[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/automatic-dcm/>>https://wiki.ebrains.eu/bin/view/Collabs/automatic-dcm/]]
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7.1	49	= References =
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16.2	54	* 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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16.2	58	* 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.
	59	* 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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16.2	63	* 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.
	64	* 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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16.2	68	* 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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	75	{{box title="Contents"}}
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