|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
|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  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).||URI:||http://hdl.handle.net/10553/54385||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|
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