Emergent Orientation Selectivity from Random Networks in Mouse Visual Cortex

Autores
Pattadkal, Jagruti J.; Mato, German; van Vreeswijk, Carl; Priebe, Nicholas J.; Hansel, David
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The connectivity principles underlying the emergence of orientation selectivity in primary visual cortex (V1) of mammals lacking an orientation map (such as rodents and lagomorphs) are poorly understood. We present a computational model in which random connectivity gives rise to orientation selectivity that matches experimental observations. The model predicts that mouse V1 neurons should exhibit intricate receptive fields in the two-dimensional frequency domain, causing a shift in orientation preferences with spatial frequency. We find evidence for these features in mouse V1 using calcium imaging and intracellular whole-cell recordings. Pattadkal et al. show that orientation selectivity can emerge from random connectivity, and offer a distinct perspective for how computations occur in the neocortex. They propose that a random convergence of inputs can provide signals for orientation preference in contrast with the dominant model that requires a precise arrangement.
Fil: Pattadkal, Jagruti J.. University of Texas at Austin; Estados Unidos
Fil: Mato, German. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: van Vreeswijk, Carl. Centre National de la Recherche Scientifique; Francia
Fil: Priebe, Nicholas J.. University of Texas at Austin; Estados Unidos
Fil: Hansel, David. Centre National de la Recherche Scientifique; Francia
Materia
BALANCE OF EXCITATION AND INHIBITION
CONDUCTANCE-BASED MODELING
ORIENTATION SELECTIVITY
RECURRENT NEURONAL NETWORKS
VISUAL CORTEX
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/98018

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spelling Emergent Orientation Selectivity from Random Networks in Mouse Visual CortexPattadkal, Jagruti J.Mato, Germanvan Vreeswijk, CarlPriebe, Nicholas J.Hansel, DavidBALANCE OF EXCITATION AND INHIBITIONCONDUCTANCE-BASED MODELINGORIENTATION SELECTIVITYRECURRENT NEURONAL NETWORKSVISUAL CORTEXhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1The connectivity principles underlying the emergence of orientation selectivity in primary visual cortex (V1) of mammals lacking an orientation map (such as rodents and lagomorphs) are poorly understood. We present a computational model in which random connectivity gives rise to orientation selectivity that matches experimental observations. The model predicts that mouse V1 neurons should exhibit intricate receptive fields in the two-dimensional frequency domain, causing a shift in orientation preferences with spatial frequency. We find evidence for these features in mouse V1 using calcium imaging and intracellular whole-cell recordings. Pattadkal et al. show that orientation selectivity can emerge from random connectivity, and offer a distinct perspective for how computations occur in the neocortex. They propose that a random convergence of inputs can provide signals for orientation preference in contrast with the dominant model that requires a precise arrangement.Fil: Pattadkal, Jagruti J.. University of Texas at Austin; Estados UnidosFil: Mato, German. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: van Vreeswijk, Carl. Centre National de la Recherche Scientifique; FranciaFil: Priebe, Nicholas J.. University of Texas at Austin; Estados UnidosFil: Hansel, David. Centre National de la Recherche Scientifique; FranciaElsevier2018-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/98018Pattadkal, Jagruti J.; Mato, German; van Vreeswijk, Carl; Priebe, Nicholas J.; Hansel, David; Emergent Orientation Selectivity from Random Networks in Mouse Visual Cortex; Elsevier; Cell Reports; 24; 8; 8-2018; 2042-2050; e62211-1247CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.celrep.2018.07.054info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S2211124718311574info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:48:12Zoai:ri.conicet.gov.ar:11336/98018instacron: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:34982025-09-29 09:48:12.725CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Emergent Orientation Selectivity from Random Networks in Mouse Visual Cortex
title Emergent Orientation Selectivity from Random Networks in Mouse Visual Cortex
spellingShingle Emergent Orientation Selectivity from Random Networks in Mouse Visual Cortex
Pattadkal, Jagruti J.
BALANCE OF EXCITATION AND INHIBITION
CONDUCTANCE-BASED MODELING
ORIENTATION SELECTIVITY
RECURRENT NEURONAL NETWORKS
VISUAL CORTEX
title_short Emergent Orientation Selectivity from Random Networks in Mouse Visual Cortex
title_full Emergent Orientation Selectivity from Random Networks in Mouse Visual Cortex
title_fullStr Emergent Orientation Selectivity from Random Networks in Mouse Visual Cortex
title_full_unstemmed Emergent Orientation Selectivity from Random Networks in Mouse Visual Cortex
title_sort Emergent Orientation Selectivity from Random Networks in Mouse Visual Cortex
dc.creator.none.fl_str_mv Pattadkal, Jagruti J.
Mato, German
van Vreeswijk, Carl
Priebe, Nicholas J.
Hansel, David
author Pattadkal, Jagruti J.
author_facet Pattadkal, Jagruti J.
Mato, German
van Vreeswijk, Carl
Priebe, Nicholas J.
Hansel, David
author_role author
author2 Mato, German
van Vreeswijk, Carl
Priebe, Nicholas J.
Hansel, David
author2_role author
author
author
author
dc.subject.none.fl_str_mv BALANCE OF EXCITATION AND INHIBITION
CONDUCTANCE-BASED MODELING
ORIENTATION SELECTIVITY
RECURRENT NEURONAL NETWORKS
VISUAL CORTEX
topic BALANCE OF EXCITATION AND INHIBITION
CONDUCTANCE-BASED MODELING
ORIENTATION SELECTIVITY
RECURRENT NEURONAL NETWORKS
VISUAL CORTEX
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The connectivity principles underlying the emergence of orientation selectivity in primary visual cortex (V1) of mammals lacking an orientation map (such as rodents and lagomorphs) are poorly understood. We present a computational model in which random connectivity gives rise to orientation selectivity that matches experimental observations. The model predicts that mouse V1 neurons should exhibit intricate receptive fields in the two-dimensional frequency domain, causing a shift in orientation preferences with spatial frequency. We find evidence for these features in mouse V1 using calcium imaging and intracellular whole-cell recordings. Pattadkal et al. show that orientation selectivity can emerge from random connectivity, and offer a distinct perspective for how computations occur in the neocortex. They propose that a random convergence of inputs can provide signals for orientation preference in contrast with the dominant model that requires a precise arrangement.
Fil: Pattadkal, Jagruti J.. University of Texas at Austin; Estados Unidos
Fil: Mato, German. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: van Vreeswijk, Carl. Centre National de la Recherche Scientifique; Francia
Fil: Priebe, Nicholas J.. University of Texas at Austin; Estados Unidos
Fil: Hansel, David. Centre National de la Recherche Scientifique; Francia
description The connectivity principles underlying the emergence of orientation selectivity in primary visual cortex (V1) of mammals lacking an orientation map (such as rodents and lagomorphs) are poorly understood. We present a computational model in which random connectivity gives rise to orientation selectivity that matches experimental observations. The model predicts that mouse V1 neurons should exhibit intricate receptive fields in the two-dimensional frequency domain, causing a shift in orientation preferences with spatial frequency. We find evidence for these features in mouse V1 using calcium imaging and intracellular whole-cell recordings. Pattadkal et al. show that orientation selectivity can emerge from random connectivity, and offer a distinct perspective for how computations occur in the neocortex. They propose that a random convergence of inputs can provide signals for orientation preference in contrast with the dominant model that requires a precise arrangement.
publishDate 2018
dc.date.none.fl_str_mv 2018-08
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/11336/98018
Pattadkal, Jagruti J.; Mato, German; van Vreeswijk, Carl; Priebe, Nicholas J.; Hansel, David; Emergent Orientation Selectivity from Random Networks in Mouse Visual Cortex; Elsevier; Cell Reports; 24; 8; 8-2018; 2042-2050; e6
2211-1247
CONICET Digital
CONICET
url http://hdl.handle.net/11336/98018
identifier_str_mv Pattadkal, Jagruti J.; Mato, German; van Vreeswijk, Carl; Priebe, Nicholas J.; Hansel, David; Emergent Orientation Selectivity from Random Networks in Mouse Visual Cortex; Elsevier; Cell Reports; 24; 8; 8-2018; 2042-2050; e6
2211-1247
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.celrep.2018.07.054
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S2211124718311574
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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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