Computer Science – Computational Engineering – Finance – and Science
Scientific paper
2009-03-15
Int. J. Bifurcation and Chaos 20, No. 1 (2010) 121-134
Computer Science
Computational Engineering, Finance, and Science
Scientific paper
We show how the Equation-Free approach for multi-scale computations can be exploited to systematically study the dynamics of neural interactions on a random regular connected graph under a pairwise representation perspective. Using an individual-based microscopic simulator as a black box coarse-grained timestepper and with the aid of simulated annealing we compute the coarse-grained equilibrium bifurcation diagram and analyze the stability of the stationary states sidestepping the necessity of obtaining explicit closures at the macroscopic level. We also exploit the scheme to perform a rare-events analysis by estimating an effective Fokker-Planck describing the evolving probability density function of the corresponding coarse-grained observables.
Siettos Constantinos I.
Spiliotis Konstantinos G.
No associations
LandOfFree
Multiscale Computations on Neural Networks: From the Individual Neuron Interactions to the Macroscopic-Level Analysis does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Multiscale Computations on Neural Networks: From the Individual Neuron Interactions to the Macroscopic-Level Analysis, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Multiscale Computations on Neural Networks: From the Individual Neuron Interactions to the Macroscopic-Level Analysis will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-166222