Neural computing with concurrent synchrony

Victor Parque; Masakazu Kobayashi; Masatake Higashi

Neural computing with concurrent synchrony

Victor Parque, Masakazu Kobayashi, Masatake Higashi

Research output: Contribution to journal › Article › peer-review

Abstract

Neural networks are important modeling tools to implement intelligent behaviour in a wide variety of phenomena. We introduce the concept of concurrent synchrony in spikes to enable the efficient representation of neural networks to process sensory stimuli. Using different sensory modalities, we show that information processing from stimuli can be represented compactly. This approach aims at introducing homeostasis into the behavior of neural populations in order to construct diverse and sophisticated control rules without increasing network complexity.

Original language	English
Pages (from-to)	304-311
Number of pages	8
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8834
Publication status	Published - 2014 Jan 1
Externally published	Yes

Keywords

Concurrency
Neural representation
Spiking networks
Synchrony

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Cite this

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AB - Neural networks are important modeling tools to implement intelligent behaviour in a wide variety of phenomena. We introduce the concept of concurrent synchrony in spikes to enable the efficient representation of neural networks to process sensory stimuli. Using different sensory modalities, we show that information processing from stimuli can be represented compactly. This approach aims at introducing homeostasis into the behavior of neural populations in order to construct diverse and sophisticated control rules without increasing network complexity.

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KW - Synchrony

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Neural computing with concurrent synchrony

Abstract

Keywords

ASJC Scopus subject areas

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