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Cognitive Computation
Erschienen in: Cognitive Computation 2/2009

01.06.2009

Artificial Cognitive Systems: From VLSI Networks of Spiking Neurons to Neuromorphic Cognition

verfasst von: Giacomo Indiveri, Elisabetta Chicca, Rodney J. Douglas

Erschienen in: Cognitive Computation | Ausgabe 2/2009

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Abstract

Neuromorphic engineering (NE) is an emerging research field that has been attempting to identify neural types of computational principles, by implementing biophysically realistic models of neural systems in Very Large Scale Integration (VLSI) technology. Remarkable progress has been made recently, and complex artificial neural sensory-motor systems can be built using this technology. Today, however, NE stands before a large conceptual challenge that must be met before there will be significant progress toward an age of genuinely intelligent neuromorphic machines. The challenge is to bridge the gap from reactive systems to ones that are cognitive in quality. In this paper, we describe recent advancements in NE, and present examples of neuromorphic circuits that can be used as tools to address this challenge. Specifically, we show how VLSI networks of spiking neurons with spike-based plasticity mechanisms and soft winner-take-all architectures represent important building blocks useful for implementing artificial neural systems able to exhibit basic cognitive abilities.
Nächster Artikel On the Natural Hierarchical Composition of Cliques in Cell Assemblies

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Metadaten
Titel
Artificial Cognitive Systems: From VLSI Networks of Spiking Neurons to Neuromorphic Cognition
verfasst von
Giacomo Indiveri
Elisabetta Chicca
Rodney J. Douglas
Publikationsdatum
01.06.2009
Verlag
Springer-Verlag
Erschienen in
Cognitive Computation / Ausgabe 2/2009
Print ISSN: 1866-9956
Elektronische ISSN: 1866-9964
DOI
https://doi.org/10.1007/s12559-008-9003-6

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