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
.jpg)
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/98018
Ver los metadatos del registro completo
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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 Técnicas2025-10-22T11:17:02Zoai: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:34982025-10-22 11:17:02.935CONICET 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. |
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2018 |
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2018-08 |
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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 |
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http://hdl.handle.net/11336/98018 |
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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 |
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