[Neuroimaging] Interest in modeling library for NiPy

[Marmaduke Woodman]

hi

I'm writing to poll for interest in a community oriented, NiPy-brand
modeling library [1], for generic dynamical systems models such as those in
DCM but also more realistic models e.g.  neural mass models, DWI connectome
based networks thereof, forward models for fMRI/EEG/MEG. Methods therein
would include both forward simulation schemes (Euler-Maruyama etc) and
model inversion using e.g. HMC or variational schemes in PyMC3.

Most these elements are already implemented, across various NiPy libs and
TVB, but the
 hope would be to make their cross-section, ie. nonlinear dynamical network
modeling, a more accessible tool in the neuroimaging toolbox, by forming a
library bringing all those elements together.


Any questions, suggestions, criticisms are welcome.

Marmaduke Woodman


[1] I'm aware that many libs implement e.g. MVAR methods which is also
model-based, but here I mean nonlinear, continuous time models, such as
Jansen-Rit model of visual evoked potentials.
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