Building personalized brain network models with TVB
Spase Petkoski and Marmaduke Woodman
What can I find here?
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/.
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, where we will describe the building blocks of TVB through the paradigm of resting state activity.
This will be followed by Modelling Epilepsy, where seizure propagation will be modeled.
Then, there is one tutorial describing a deeper analysis of BOLD monitors.
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 . This is a based on a previous showcase Degeneracy in neuroscience, which described the interpersonal variability analyzed by the Virtual Ageing Brain study.
Lavanga, M., Stumme, J., Yalcinkaya, B. H., Fousek, J., Jockwitz, C., Sheheitli, H., Bittner, N., Hashemi, M., Petkoski, S., Caspers, S., & Jirsa, V. (2023). The virtual aging brain: Causal inference supports interhemispheric dedifferentiation in healthy aging. NeuroImage, 283, 120403.
Finally, the collab contains one tutorial where a Bayesian approach is used on synthetic data to infer the posterior of the parameters foir a single brain region.
These can all be found in the drive and accessed through the lab.
Requirements
School participants should have EBRAINS accounts to be able to access and work on the tutorials.
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) or VBI tool (https://github.com/ins-amu/vbi) will be required.
Other tutorials
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"
https://wiki.ebrains.eu/bin/view/Collabs/sga3-d1-5-showcase-1/
https://wiki.ebrains.eu/bin/view/Collabs/automatic-dcm/
References
- Sanz-Leon P, Knock SA, Spiegler A, Jirsa VK. Mathematical framework for large-scale brain network modeling in The Virtual Brain. Neuroimage. 2015 May 1;111:385-430.
- 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. NeuroImage. 2022 May 1;251:118973.
- 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. NeuroImage. 2023 Dec 1;283:120403.
- 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. National Science Review. 2024 May;11(5):nwae079.
- Baldy N, Woodman M, Jirsa V, Hashemi M. Dynamic Causal Modeling in Probabilistic Programming Languages. bioRxiv. 2024:2024-11.
- 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 bioRxiv. 2025:2025-01.