Probabilistic versus incremental presynaptic learning in biological plausible synapses

Ropero Peláez, Javier and Andina de la Fuente, Diego (2011). Probabilistic versus incremental presynaptic learning in biological plausible synapses. In: "4th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011", 30/05/2011 - 03/06/2011, La Palma, Islas Canarias, España. ISBN 978-3-642-21343-4. pp. 80-89. https://doi.org/10.1007/978-3-642-21344-1_9.

Description

Title: Probabilistic versus incremental presynaptic learning in biological plausible synapses
Author/s:
  • Ropero Peláez, Javier
  • Andina de la Fuente, Diego
Item Type: Presentation at Congress or Conference (Article)
Event Title: 4th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011
Event Dates: 30/05/2011 - 03/06/2011
Event Location: La Palma, Islas Canarias, España
Title of Book: Proceedings of 4th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011
Date: 2011
ISBN: 978-3-642-21343-4
Subjects:
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

In this paper, the presynaptic rule, a classical rule for hebbian learning, is revisited. It is shown that the presynaptic rule exhibits relevant synaptic properties like synaptic directionality, and LTP metaplasticity (long-term potentiation threshold metaplasticity). With slight modifications, the presynaptic model also exhibits metaplasticity of the long-term depression threshold, being also consistent with Artola, Brocher and Singer’s (ABS) influential model. Two asymptotically equivalent versions of the presynaptic rule were adopted for this analysis: the first one uses an incremental equation while the second, conditional probabilities. Despite their simplicity, both types of presynaptic rules exhibit sophisticated biological properties, specially the probabilistic version

More information

Item ID: 13266
DC Identifier: http://oa.upm.es/13266/
OAI Identifier: oai:oa.upm.es:13266
DOI: 10.1007/978-3-642-21344-1_9
Official URL: http://link.springer.com/chapter/10.1007/978-3-642-21344-1_9
Deposited by: Memoria Investigacion
Deposited on: 28 Nov 2012 10:57
Last Modified: 21 Apr 2016 12:34
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