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Dynamical Systems and Convergence

  • Mario NegrelloEmail author
Chapter
  • 470 Downloads
Part of the Springer Series in Cognitive and Neural Systems book series (SSCNS, volume 1)

Abstract

Dynamical systems can be coupled to other dynamical systems to cover organismic phenomenon on many scales, as they provides a general frame applicable to an ample range of phenomena. Describing a system as coupled systems highlights interfaces. Interfaces reflect the locus of organized transitions, or level crossings, places where constancy and variability merge. At interfaces there is convergence and/or divergence, so the vicissitudes of variation coalesce in meaningful averages; whereas conversely, constancy may drift and spread into variation. These transformations depend crucially on a number of processes, which are regimented by particular types of physical interactions. Variability may coalesce in averages, whereas constancy may drift. Mutatis mutandis, the same operating principles – large numbers and physical laws – means smear again in variation. In a functioning system, these two stances of constancy and variation complement and define each other.

Keywords

Motor Neuron Neuromuscular Junction Spike Train Rate Code Recurrent Neural Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Okinawa Institute of Science and TechnologyOkinawaJapan

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