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Neuromorphic silicon neuron circuits

Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain-machine interfaces. The specific circuit solutions used to implement silicon n...

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Hauptverfasser: Indiveri, Giacomo (VerfasserIn) , Linares-Barranco, Bernabe (VerfasserIn) , Hamilton, Tara (VerfasserIn) , van Schaik, André (VerfasserIn) , Etienne-Cummings, Ralph (VerfasserIn) , Delbruck, Tobi (VerfasserIn) , Liu, Shih-Chii (VerfasserIn) , Dudek, Piotr (VerfasserIn) , Häfliger, Philipp (VerfasserIn) , Renaud, Sylvie (VerfasserIn) , Schemmel, Johannes (VerfasserIn) , Cauwenberghs, Gert (VerfasserIn) , Arthur, John (VerfasserIn) , Hynna, Kai (VerfasserIn) , Folowosele, Fopefolu (VerfasserIn) , SAÏGHI, Sylvain (VerfasserIn) , Serrano-Gotarredona, Teresa (VerfasserIn) , Wijekoon, Jayawan (VerfasserIn) , Wang, Yingxue (VerfasserIn) , Boahen, Kwabena (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 31 May 2011
In: Frontiers in neuroscience
Year: 2011, Jahrgang: 5, Pages: 1-23
ISSN:1662-453X
DOI:10.3389/fnins.2011.00073
Online-Zugang:Resolving-System, kostenfrei, Volltext: https://doi.org/10.3389/fnins.2011.00073
Verlag, kostenfrei, Volltext: https://www.frontiersin.org/article/10.3389/fnins.2011.00073
Volltext
Verfasserangaben:Giacomo Indiveri, Bernabe Linares-Barranco, Tara Hamilton, André van Schaik, Ralph Etienne-Cummings, Tobi Delbruck, Shih-Chii Liu, Piotr Dudek, Philipp Häfliger, Sylvie Renaud, Johannes Schemmel, Gert Cauwenberghs, John Arthur, Kai Hynna, Fopefolu Folowosele, Sylvain SAÏGHI, Teresa Serrano-Gotarredona, Jayawan Wijekoon, Yingxue Wang and Kwabena Boahen
Beschreibung
Zusammenfassung:Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain-machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this paper we describe the most common building blocks and techniques used to implement these circuits, and present an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance-based Hodgkin-Huxley models to bi-dimensional generalized adaptive integrate and fire models. We compare the different design methodologies used for each silicon neuron design described, and demonstrate their features with experimental results, measured from a wide range of fabricated VLSI chips.
Beschreibung:Gesehen am 01.07.2022
Beschreibung:Online Resource
ISSN:1662-453X
DOI:10.3389/fnins.2011.00073

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