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<identifier>oai:HAL:hal-00115420v1</identifier>
<datestamp>2018-01-11</datestamp>
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<publisher>HAL CCSD</publisher>
<title lang=en>Learning and discrimination through STDP in a top-down modulated associative memory</title>
<creator>Mouraud, Anthony</creator>
<creator>Paugam-Moisy, Hélène</creator>
<contributor>Institut des Sciences Cognitives (ISC) ; Université Claude Bernard Lyon 1 (UCBL) - Centre National de la Recherche Scientifique (CNRS)</contributor>
<contributor>Groupe de Recherche en Informatique et Mathématiques Appliquées Antilles-Guyane (GRIMAAG) ; Université des Antilles et de la Guyane (UAG)</contributor>
<description>International audience</description>
<source>Proceedings of 14 European Symposium on Artificial Neural Networks (ESANN 2006)</source>
<contributor>M. Verleysen</contributor>
<publisher>D-side publications, Evere, Belgium</publisher>
<identifier>hal-00115420</identifier>
<identifier>https://hal.archives-ouvertes.fr/hal-00115420</identifier>
<identifier>https://hal.archives-ouvertes.fr/hal-00115420/document</identifier>
<identifier>https://hal.archives-ouvertes.fr/hal-00115420/file/esann06_HAL.pdf</identifier>
<source>https://hal.archives-ouvertes.fr/hal-00115420</source>
<source>M. Verleysen. Mar 2006, D-side publications, Evere, Belgium, pp.611-616, 2006</source>
<identifier>ARXIV : cs.NE/0611104</identifier>
<relation>info:eu-repo/semantics/altIdentifier/arxiv/cs.NE/0611104</relation>
<language>en</language>
<subject lang=en>Associative Memories</subject>
<subject lang=en>Top-Down influences</subject>
<subject lang=en>Spike Time Dependent Plasticity</subject>
<subject lang=en>Neural Networks</subject>
<subject>[INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]</subject>
<subject>[INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG]</subject>
<subject>[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]</subject>
<subject>[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation</subject>
<subject>[SCCO.COMP] Cognitive science/Computer science</subject>
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<type>Conference papers</type>
<description lang=en>This article underlines the learning and discrimination capabilities of a model of associative memory based on artificial networks of spiking neurons. Inspired from neuropsychology and neurobiology, the model implements top-down modulations, as in neocortical layer V pyramidal neurons, with a learning rule based on synaptic plasticity (STDP), for performing a multimodal association learning task. A temporal correlation method of analysis proves the ability of the model to associate specific activity patterns to different samples of stimulation. Even in the absence of initial learning and with continuously varying weights, the activity patterns become stable enough for discrimination.</description>
<date>2006-03</date>
</dc>
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