Region-wise model parameters fitting

[pedro...@gmail.com]

Dear all,

I am currently using the Reduced Wong Wang model in my analysis, in which I explore a space of parameters combination in order to fit the model simulations to empirical rsFMRI data. This parameters exploration has been done so far at the global level, i.e., the parameters are applied for all the brain regions (in other words, I am sending a single value for the parameters on the function). 

Is it possible to explore the parameters at the region level, e.g., by sending a vector of values to the function with a size equal to the number of regions?

If that is not possible using the Reduced Wong Wang model, are there any models on TVB that would allow me to fit the model parameters region-wise?

Thank you very much for your help!

Kind regards,

Pedro

[Julie Courtiol]

Hi Pedro,

Yes, it is possible to append different parameter values for each brain region in TVB. One of the best examples is with the Epileptor model where you define different epileptogenic zones.

For the Reduced Wong Wang, you can apply it in a similar way:

w1 = 0.9

w2 = 1.0

rww = models.ReducedWongWang()

rww.w = numpy.array((number_of_regions)) * (w1)  #for all regions

rww.w[[1,2,3]] = np.ones((3)) * (w2)  #for specific regions

Best,

Julie

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Best regards,

Julie Courtiol

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[Pedro Costa Klein]

Dear Julie,

Thank you very much for your quick answer and for kindly providing this example.

Kind regards,

Pedro

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Pedro Costa Klein (https://pedrocklein.github.io/)

PhD Student

Universität zu Köln

pedro...@gmail.com

pcos...@smail.uni-koeln.de

pedro.co...@uk-koeln.de