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Study of Nitric Oxide Effect in the Hebbian Learning: Towards a Diffusive Hebb’s Law

  • C. P. Suárez Araujo
  • P. Fernández López
  • P. García Báez
  • J. Regidor García
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3696)

Abstract

The Computational Neuroscience has as main goal the understanding of the computational style of the brain and developing artificial systems with brain capabilities. Our paper belongs to this field. We will use an Hebbian neural ensemble which follow a non-linear differential equation system namely Hebbian System (HS), which represent the neurodynamics and the adaptation in accordance with the Hebb’s postulate, to study the influence of the NO diffusion in the Hebbian learning. Considering that the postsynaptic neurons provide retrograde signals to the presynaptic neurons [1] we suggest the NO as a probable biological support to the Hebb’s law propounding a new mathematical formulation of that learning law, the diffusive Hebb’s law. We will present a study of the behavior of the diffusive Hebb’s law using a Diffusive Hebbian System (DHS).

Keywords

Nitric Oxide Postsynaptic Neuron Hebbian Learning Computational Neuroscience Weight Dynamic 
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-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • C. P. Suárez Araujo
    • 1
  • P. Fernández López
    • 1
  • P. García Báez
    • 2
  • J. Regidor García
    • 1
  1. 1.Institute for CyberneticsUniversity of Las Palmas de Gran CanariaSpain
  2. 2.Dept. of Statistics, Operations Research and ComputationUniversity of la LagunaSpain

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