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Summary

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5 -= TVB for brain states and pathological brain dynamics =
5 += My Collab's Extended Title =
6 6  
7 -Emre Baspinar and Damien Depannemaecker
7 +My collab's subtitle
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9 9  )))
10 10  
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14 14  (((
15 15  = What can I find here? =
16 16  
17 -This collab contains the materials which will be used during the hands-on session on 4 June 2024, during EBRAINS Brain Simulation Workshop taking place in Bilbao: [[https:~~/~~/www.bcamath.org/events/ebrains2024/en/>>https://www.bcamath.org/events/ebrains2024/en/]].
17 +* Notice how the table of contents on the right
18 +* is automatically updated
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18 18  
19 -The objective of this hands-on session is to create a familiarity of TVB for the participant by performing simulations related to different brain states and epileptic dynamics. At the beginning, we will describe the TVB framework and its building blocks. Then, in Part I, we will see a mean-field framework modeling neuronal population dynamics. We will use this framework to simulate brain states at population level. In Part II, we will see a generalization of this framework to the whole-brain scale via TVB. In Part III, we will see an example epileptic scenario of seizure propagation by using TVB. All these parts can be found in the drive, and they are accessible in the lab.
21 += Who has access? =
20 20  
21 -= Requirements =
22 -
23 -Access to the notebooks and materials requires to have an EBRAINS account.
24 -
25 -Participants are also suggested to download the materials and install TVB locally in case of connection issues. The installation can be done via the following link: [[https:~~/~~/www.thevirtualbrain.org/tvb/zwei/brainsimulator-software>>https://www.thevirtualbrain.org/tvb/zwei/brainsimulator-software]] .
26 -
27 -= References =
28 -
29 -* (((
30 -Sanz-Leon P., Knock S. A., Spiegler A., Jirsa V. K. (2015) [[Mathematical framework for large-scale brain network modeling in The Virtual Brain>>url:https://www.sciencedirect.com/science/article/pii/S1053811915000051]]. Neuroimage. 2015 May 1; 111:385-430.
23 +Describe the audience of this collab.
31 31  )))
32 -* (((
33 -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>>url:https://www.sciencedirect.com/science/article/pii/S1053811922001021]]. NeuroImage. 2022 May 1;251:118973.
34 -)))
35 -* (((
36 -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>>url:https://www.sciencedirect.com/science/article/pii/S1053811923005542]]. NeuroImage. 2023 Dec 1;283:120403.
37 -)))
38 -* (((
39 -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>>url:https://academic.oup.com/nsr/article/11/5/nwae079/7616087]]. National Science Review. 2024 May;11(5):nwae079.
40 -)))
41 -* (((
42 -Baspinar, E., Cecchini, G., DePass, M., Andujar, M., Pani, P., Ferraina, S., Moreno-Bote, R., Cos, I., Destexhe, A. (2023). A biologically plausible decision-making model based on interacting cortical columns. bioRxiv, 2023-02.
43 43  
44 -[3]: Di Volo, M., Romagnoni, A., Capone, C., Destexhe, A. (2019). Biologically realistic mean-field models of conductance-based networks of spiking neurons with adaptation. Neural Computation, 31(4), 653-680.
45 45  
46 -[1]: Goldman, J. S., Kusch, L., Aquilue, D., Yalçınkaya, B. H., Depannemaecker, D., Ancourt, K., Nghiem, T. E., Jirsa, V., Destexhe, A. (2023). A comprehensive neural simulation of slow-wave sleep and highly responsive wakefulness dynamics. Frontiers in Computational Neuroscience, 16, 1058957.
47 -)))
48 -* (((
49 -[2]: Sacha, M., Goldman, J. S., Kusch, L., Destexhe, A. (2024). Asynchronous and slow-wave oscillatory states in connectome-based models of mouse, monkey and human cerebral cortex. Applied Sciences, 14(3), 1063.
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56 56  {{box title="**Contents**"}}
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