Changes for page TVB EBRAINS hands-on

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1 -TVB EBRAINS hands-on
1 +EBRAINS Baltic-Nordic school 2024
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2 2  (((
3 3  (% class="container" %)
4 4  (((
5 -= Building personalized brain network models with TVB =
5 += My Collab's Extended Title =
6 6  
7 -Spase Petkoski and Marmaduke Woodman
7 +My collab's subtitle
8 8  )))
9 9  )))
10 10  
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14 14  (((
15 15  = What can I find here? =
16 16  
17 -This collab contains access to notebooks and reading materials for TVB that were used at various events, such as EBRAINS Baltic-Nordic summer school 2024 [[https:~~/~~/lsmu.lt/en/events/ebrains/>>https://lsmu.lt/en/events/ebrains/]], [[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/]].
17 +* Notice how the table of contents on the right
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18 18  
19 -The objective is to give to the participants an overview to building whole-brain network models with TVB.
21 += Who has access? =
20 20  
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.
22 -
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.
24 -
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);"]].
26 -
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.
28 -
29 -
30 -For more advanced applications, TVB with neuromodulation, through the example of dopaminergic D1 neuromodulation, is available at [[https:~~/~~/search.kg.ebrains.eu/?category=Model&q=preti#49cea23b-97f6-4525-bdb3-aafe70490624>>https://search.kg.ebrains.eu/?category=Model&q=preti#49cea23b-97f6-4525-bdb3-aafe70490624]] and [[https:~~/~~/github.com/giapre/dopamine_model>>https://github.com/giapre/dopamine_model]] . The github contains the model and several usecases based on //jax// implementation that is verified with the standard TVB.
31 -
32 -
33 -The collab also 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, but only for a single brain region.
34 -
35 -
36 -These can all be found in the drive and accessed through the lab.
37 -
38 -= Requirements =
39 -
40 -School participants should have EBRAINS accounts to be able to access and work on the tutorials.
41 -
42 -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.
43 -
44 -= Other tutorials =
45 -
46 -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"
47 -
48 -[[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/]]
49 -
50 -[[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/automatic-dcm/>>https://wiki.ebrains.eu/bin/view/Collabs/automatic-dcm/]]
51 -
52 -= References =
53 -
54 -(((
55 -
56 -
57 -* 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.
23 +Describe the audience of this collab.
58 58  )))
59 59  
60 -(((
61 -* 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.
62 -* 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.
63 -)))
64 64  
65 -(((
66 -* 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.
67 -* 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.
68 -)))
69 -
70 -(((
71 -* 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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78 78  {{box title="**Contents**"}}
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