Last modified by mhashemi on 2025/03/12 11:20
From version 8.1
edited by petkoski
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To version 15.2
edited by mhashemi
on 2025/03/12 11:12
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1 -EBRAINS Baltic-Nordic school 2024
1 +TVB EBRAINS Baltic-Nordic school 2024
Author
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1 -XWiki.petkoski
1 +XWiki.mhashemi
Content
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14 14  (((
15 15  = What can I find here? =
16 16  
17 -* A current topic in system neuroscience literature is the presence of brain activity in the absence of a task condition. These task-negative, spontaneous fluctuations occur in the so-called **rest state**, and a recurring theme of these fluctuations is that they have a network structure. Because TVB uses the structural connectivity of the brain as the backbone for simulating spontaneous activity, resting state activity and its network structure is a prime candidate for modeling in TVB.
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/]].
18 18  
19 -= Who has access? =
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.
20 20  
21 -Describe the audience of this collab.
21 += Requirements =
22 22  
23 +School participants should have EBRAINS accounts to be able to access and work on the tutorials.
23 23  
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.
26 +
27 += Other tutorials =
28 +
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"
30 +
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/]]
32 +
24 24  = References =
25 25  
26 -* (((
27 -(Palesi et al., 2020): Palesi, F., Lorenzi, R. M., Casellato, C., Ritter, P., Jirsa, V., Wheeler- kingshott, C. A. M. G., and Angelo, E. D. (2020). **The importance of cerebellar connectivity on simulated brain dynamics. **Frontiers in Cellular Neuroscience, 14,1–11.
35 +(((
36 +
37 +
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.
28 28  )))
29 -* (((
30 -(Monteverdi et al., 2022): Monteverdi A, Palesi F, Costa A, Vitali P, Pichiecchio A, Cotta Ramusino M, Bernini S, Jirsa V, Gandini Wheeler-Kingshott CAM and D’Angelo E (2022) **Subject-specific features of excitation/inhibition profiles in neurodegenerative diseases.** Front. Aging Neurosci. 14:868342. doi: 10.3389/fnagi.2022.868342
40 +
41 +(((
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.
43 +
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.
31 31  )))
46 +
47 +(((
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.
49 +
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.
32 32  )))
33 33  
53 +(((
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.
55 +)))
56 +)))
34 34  
58 +
35 35  (% class="col-xs-12 col-sm-4" %)
36 36  (((
37 37  {{box title="**Contents**"}}