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ANOVA and PCE for Biological Neural Networks

Joint work with Minseok Choi, postdoc in the lab of Yannis Kevrekidis as Princeton.

We propose, and illustrate via a neural network example, two different approaches to coarse-graining large heterogeneous networks. Both approaches are inspired from, and use tools developed in, methods for uncertainty quantification (UQ) in systems with multiple uncertain parameters in our case, the parameters are heterogeneously distributed on the network nodes. The approach shows promise in accelerating large scale network simulations as well as coarse-grained fixed point, periodic solution computation and stability analysis. We also demonstrate that the approach can successfully deal with structural as well as intrinsic heterogeneities.

Published in European Physical Journal Special Topics : Choi, M., Bertalan, T., Laing, C. et al. Eur. Phys. J. Spec. Top. (2016) 225: 1165. doi:10.1140/epjst/e2016-02662-3