Multiscale Computations on Neural Networks: From the Individual Neuron Interactions to the Macroscopic-Level Analysis

Spiliotis, K; Siettos, C

dc.contributor.author	Spiliotis, K	en
dc.contributor.author	Siettos, C	en
dc.date.accessioned	2014-03-01T01:58:00Z
dc.date.available	2014-03-01T01:58:00Z
dc.date.issued	2009	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/28592
dc.relation.uri	http://arxiv.org/abs/0903.2641	en
dc.relation.uri	http://www.informatik.uni-trier.de/~ley/db/journals/corr/corr0903.html#abs-0903-2641	en
dc.subject	Bifurcation Analysis	en
dc.subject	Bifurcation Diagram	en
dc.subject	Coarse Grained	en
dc.subject	Connected Graph	en
dc.subject	Probability Density Function	en
dc.subject	Rare Event	en
dc.subject	Simulated Annealing	en
dc.subject	Stationary State	en
dc.subject	fokker planck	en
dc.subject	Neural Network	en
dc.title	Multiscale Computations on Neural Networks: From the Individual Neuron Interactions to the Macroscopic-Level Analysis	en
heal.type	journalArticle	en
heal.publicationDate	2009	en
heal.abstract	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	en
heal.journalName	Computing Research Repository	en