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Hi,
I would suggest first have a look at the references and prepared documents/notebooks to figure out what is the problem and what is the related issues.
You can have a close look at Stan tutorials, in particular, Michael Betancourt's writing (https://betanalpha.github.io/).
You can start then with forward simulations of Epileptor model using TVB (or an example notebook using JIT) and use Stan/PyMC3 (your choice) to invert the model. Since we are not allowed to reveal the patient info, we have taken care of replicability using synthetic data.
First, inverting a single 2D-Epileptor model can be a good starting point (https://github.com/ins-amu/BVEP/blob/master/Stan/FittingEpileptor2D.ipynb).
Then, the whole brain (N coupled) Epileptor model to fit the source-brain activity as the observation and the noncentered parametrization applied there to improve the estimation (https://github.com/ins-amu/BVEP/blob/master/Stan/BVEP_noncen_stan_patient1.ipynb).
Finally, you can invert the whole brain of Epileptor model from SEEG signals (https://github.com/ins-amu/BVEP/blob/master/Stan/BVEP_seeg_noncentered_stan_patient1.ipynb).
Hopefully, the notebooks will be helpful for you.
Best,
Meysam
Hello, I'm very interested in your project. Can you give me some guidance on how to use the project.
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