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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/98018
Ver los metadatos del registro completo
id |
CONICETDig_3c582796fa05e4525d1141ac0ed81873 |
---|---|
oai_identifier_str |
oai:ri.conicet.gov.ar:11336/98018 |
network_acronym_str |
CONICETDig |
repository_id_str |
3498 |
network_name_str |
CONICET Digital (CONICET) |
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 |
_version_ |
1844613498832683008 |
score |
13.070432 |