A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator

Autores
Stoliar, Pablo Alberto; Tranchant, Julien; Corraze, Benoit; Janod, Etienne; Besland, Marie Paule; Tesler, Federico Ariel; Rozenberg, Marcelo Javier; Cario, Laurent
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
During the last half century, the tremendous development of computers based on von Neumann architecture has led to the revolution of the information technology. However, von Neumann computers are outperformed by the mammal brain in numerous data-processing applications such as pattern recognition and data mining. Neuromorphic engineering aims to mimic brain-like behavior through the implementation of artificial neural networks based on the combination of a large number of artificial neurons massively interconnected by an even larger number of artificial synapses. In order to effectively implement artificial neural networks directly in hardware, it is mandatory to develop artificial neurons and synapses. A promising advance has been made in recent years with the introduction of the components called memristors that might implement synaptic functions. In contrast, the advances in artificial neurons have consisted in the implementation of silicon-based circuits. However, so far, a single-component artificial neuron that will bring an improvement comparable to what memristors have brought to synapses is still missing. Here, a simple two-terminal device is introduced, which can implement the basic functions leaky integrate and fire of spiking neurons. Remarkably, it has been found that it is realized by the behavior of strongly correlated narrow-gap Mott insulators subject to electric pulsing.
Fil: Stoliar, Pablo Alberto. CIC NanoGUNE; España
Fil: Tranchant, Julien. Centre de Recherche de Nantes; Francia. Centre National de la Recherche Scientifique; Francia. Institut des Matériaux Jean Rouxel; Francia
Fil: Corraze, Benoit. Centre de Recherche de Nantes; Francia. Centre National de la Recherche Scientifique; Francia. Institut des Matériaux Jean Rouxel; Francia
Fil: Janod, Etienne. Centre de Recherche de Nantes; Francia. Centre National de la Recherche Scientifique; Francia. Institut des Matériaux Jean Rouxel; Francia
Fil: Besland, Marie Paule. Centre de Recherche de Nantes; Francia. Centre National de la Recherche Scientifique; Francia. Institut des Matériaux Jean Rouxel; Francia
Fil: Tesler, Federico Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Rozenberg, Marcelo Javier. Université Paris Sud; Francia. Centre National de la Recherche Scientifique; Francia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Cario, Laurent. Centre de Recherche de Nantes; Francia. Centre National de la Recherche Scientifique; Francia. Institut des Matériaux Jean Rouxel; Francia
Materia
Leaky Integrate And Fire
Mott Insulators
Neurons
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/59976
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/59976
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott InsulatorStoliar, Pablo AlbertoTranchant, JulienCorraze, BenoitJanod, EtienneBesland, Marie PauleTesler, Federico ArielRozenberg, Marcelo JavierCario, LaurentLeaky Integrate And FireMott InsulatorsNeuronshttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1During the last half century, the tremendous development of computers based on von Neumann architecture has led to the revolution of the information technology. However, von Neumann computers are outperformed by the mammal brain in numerous data-processing applications such as pattern recognition and data mining. Neuromorphic engineering aims to mimic brain-like behavior through the implementation of artificial neural networks based on the combination of a large number of artificial neurons massively interconnected by an even larger number of artificial synapses. In order to effectively implement artificial neural networks directly in hardware, it is mandatory to develop artificial neurons and synapses. A promising advance has been made in recent years with the introduction of the components called memristors that might implement synaptic functions. In contrast, the advances in artificial neurons have consisted in the implementation of silicon-based circuits. However, so far, a single-component artificial neuron that will bring an improvement comparable to what memristors have brought to synapses is still missing. Here, a simple two-terminal device is introduced, which can implement the basic functions leaky integrate and fire of spiking neurons. Remarkably, it has been found that it is realized by the behavior of strongly correlated narrow-gap Mott insulators subject to electric pulsing.Fil: Stoliar, Pablo Alberto. CIC NanoGUNE; EspañaFil: Tranchant, Julien. Centre de Recherche de Nantes; Francia. Centre National de la Recherche Scientifique; Francia. Institut des Matériaux Jean Rouxel; FranciaFil: Corraze, Benoit. Centre de Recherche de Nantes; Francia. Centre National de la Recherche Scientifique; Francia. Institut des Matériaux Jean Rouxel; FranciaFil: Janod, Etienne. Centre de Recherche de Nantes; Francia. Centre National de la Recherche Scientifique; Francia. Institut des Matériaux Jean Rouxel; FranciaFil: Besland, Marie Paule. Centre de Recherche de Nantes; Francia. Centre National de la Recherche Scientifique; Francia. Institut des Matériaux Jean Rouxel; FranciaFil: Tesler, Federico Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Rozenberg, Marcelo Javier. Université Paris Sud; Francia. Centre National de la Recherche Scientifique; Francia. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cario, Laurent. Centre de Recherche de Nantes; Francia. Centre National de la Recherche Scientifique; Francia. Institut des Matériaux Jean Rouxel; FranciaWiley VCH Verlag2017-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/59976Stoliar, Pablo Alberto; Tranchant, Julien; Corraze, Benoit; Janod, Etienne; Besland, Marie Paule; et al.; A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator; Wiley VCH Verlag; Advanced Functional Materials; 27; 11; 3-2017; 1-7; 16047401616-301XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1002/adfm.201604740info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1002/adfm.201604740info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:19:17Zoai:ri.conicet.gov.ar:11336/59976instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:19:18.013CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator
title A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator
spellingShingle A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator
Stoliar, Pablo Alberto
Leaky Integrate And Fire
Mott Insulators
Neurons
title_short A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator
title_full A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator
title_fullStr A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator
title_full_unstemmed A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator
title_sort A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator
dc.creator.none.fl_str_mv Stoliar, Pablo Alberto
Tranchant, Julien
Corraze, Benoit
Janod, Etienne
Besland, Marie Paule
Tesler, Federico Ariel
Rozenberg, Marcelo Javier
Cario, Laurent
author Stoliar, Pablo Alberto
author_facet Stoliar, Pablo Alberto
Tranchant, Julien
Corraze, Benoit
Janod, Etienne
Besland, Marie Paule
Tesler, Federico Ariel
Rozenberg, Marcelo Javier
Cario, Laurent
author_role author
author2 Tranchant, Julien
Corraze, Benoit
Janod, Etienne
Besland, Marie Paule
Tesler, Federico Ariel
Rozenberg, Marcelo Javier
Cario, Laurent
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Leaky Integrate And Fire
Mott Insulators
Neurons
topic Leaky Integrate And Fire
Mott Insulators
Neurons
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv During the last half century, the tremendous development of computers based on von Neumann architecture has led to the revolution of the information technology. However, von Neumann computers are outperformed by the mammal brain in numerous data-processing applications such as pattern recognition and data mining. Neuromorphic engineering aims to mimic brain-like behavior through the implementation of artificial neural networks based on the combination of a large number of artificial neurons massively interconnected by an even larger number of artificial synapses. In order to effectively implement artificial neural networks directly in hardware, it is mandatory to develop artificial neurons and synapses. A promising advance has been made in recent years with the introduction of the components called memristors that might implement synaptic functions. In contrast, the advances in artificial neurons have consisted in the implementation of silicon-based circuits. However, so far, a single-component artificial neuron that will bring an improvement comparable to what memristors have brought to synapses is still missing. Here, a simple two-terminal device is introduced, which can implement the basic functions leaky integrate and fire of spiking neurons. Remarkably, it has been found that it is realized by the behavior of strongly correlated narrow-gap Mott insulators subject to electric pulsing.
Fil: Stoliar, Pablo Alberto. CIC NanoGUNE; España
Fil: Tranchant, Julien. Centre de Recherche de Nantes; Francia. Centre National de la Recherche Scientifique; Francia. Institut des Matériaux Jean Rouxel; Francia
Fil: Corraze, Benoit. Centre de Recherche de Nantes; Francia. Centre National de la Recherche Scientifique; Francia. Institut des Matériaux Jean Rouxel; Francia
Fil: Janod, Etienne. Centre de Recherche de Nantes; Francia. Centre National de la Recherche Scientifique; Francia. Institut des Matériaux Jean Rouxel; Francia
Fil: Besland, Marie Paule. Centre de Recherche de Nantes; Francia. Centre National de la Recherche Scientifique; Francia. Institut des Matériaux Jean Rouxel; Francia
Fil: Tesler, Federico Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Rozenberg, Marcelo Javier. Université Paris Sud; Francia. Centre National de la Recherche Scientifique; Francia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Cario, Laurent. Centre de Recherche de Nantes; Francia. Centre National de la Recherche Scientifique; Francia. Institut des Matériaux Jean Rouxel; Francia
description During the last half century, the tremendous development of computers based on von Neumann architecture has led to the revolution of the information technology. However, von Neumann computers are outperformed by the mammal brain in numerous data-processing applications such as pattern recognition and data mining. Neuromorphic engineering aims to mimic brain-like behavior through the implementation of artificial neural networks based on the combination of a large number of artificial neurons massively interconnected by an even larger number of artificial synapses. In order to effectively implement artificial neural networks directly in hardware, it is mandatory to develop artificial neurons and synapses. A promising advance has been made in recent years with the introduction of the components called memristors that might implement synaptic functions. In contrast, the advances in artificial neurons have consisted in the implementation of silicon-based circuits. However, so far, a single-component artificial neuron that will bring an improvement comparable to what memristors have brought to synapses is still missing. Here, a simple two-terminal device is introduced, which can implement the basic functions leaky integrate and fire of spiking neurons. Remarkably, it has been found that it is realized by the behavior of strongly correlated narrow-gap Mott insulators subject to electric pulsing.
publishDate 2017
dc.date.none.fl_str_mv 2017-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/59976
Stoliar, Pablo Alberto; Tranchant, Julien; Corraze, Benoit; Janod, Etienne; Besland, Marie Paule; et al.; A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator; Wiley VCH Verlag; Advanced Functional Materials; 27; 11; 3-2017; 1-7; 1604740
1616-301X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/59976
identifier_str_mv Stoliar, Pablo Alberto; Tranchant, Julien; Corraze, Benoit; Janod, Etienne; Besland, Marie Paule; et al.; A Leaky-Integrate-and-Fire Neuron Analog Realized with a Mott Insulator; Wiley VCH Verlag; Advanced Functional Materials; 27; 11; 3-2017; 1-7; 1604740
1616-301X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1002/adfm.201604740
info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1002/adfm.201604740
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Wiley VCH Verlag
publisher.none.fl_str_mv Wiley VCH Verlag
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.982451

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