Please use this identifier to cite or link to this item:
Title: Study of nitric oxide effect in the hebbian learning: towards a diffusive hebb's law
Authors: Suárez Araujo, C. P. 
Fernández López, P. 
García Báez, Patricio 
Regidor García,José 
UNESCO Clasification: 120304 Inteligencia artificial
Issue Date: 2005
Journal: Lecture Notes in Computer Science 
Conference: 15th International Conference on Artificial Neural Networks (ICANN 2005) 
15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005 
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).
ISBN: 978-3-540-28752-0
ISSN: 0302-9743
DOI: 10.1007/11550822_40
Source: Duch W., Kacprzyk J., Oja E., Zadrożny S. (eds) Artificial Neural Networks: Biological Inspirations – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3696. Springer, Berlin, Heidelberg
Appears in Collections:Actas de congresos
Show full item record

Page view(s)

checked on Jul 24, 2021

Google ScholarTM




Export metadata

Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.