We developed a model to investigate possible mechanisms underlying the shape of contrast (CRF) and tuning (OT) curves of neurons in the primary visual cortex, V1. We determine analytically the conditions for the structure of the afferent LGN and recurrent V1 inputs that lead to contrast-invariance width of the OT curve and to the nonlinear shape of the CRF. We investigate what are the relative contributions of single neuron and network properties in shaping the OT and the CRF. We test our model with numerical simulations of conductance-based model (CBM). The results indicate that the main effect of a cortex of neurons with accelerating transfer-functions, described here by a power-law, is sharpening. Thus, the OT curves of V1 neurons are more tuned, and their CRF is steeper, than those of their inputs. Last, we show that we are able to account for the heterogeneity in the measured CRFs, by introducing inhomogeneities either in single neuron properties or in the input to the neurons. Correlations among the CRF parameters are different for the different sources for diversity. Comparison with experimental data shows that both sources contribute about equally to heterogeneity in V1.
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We developed a model to investigate possible mechanisms underlying the shape of contrast (CRF) and tuning (OT) curves of neurons in the primary visual cortex, V1. We determine analytically the conditions for the structure of the afferent LGN and recurrent V1 inputs that lead to contrast-invariance width of the OT curve and to the nonlinear shape of the CRF. We investigate what are the relative contributions of single neuron and network properties in shaping the OT and the CRF. We test our model with numerical simulations of conductance-based model (CBM). The results indicate that the main effect of a cortex of neurons with accelerating transfer-functions, described here by a power-law, is sharpening. Thus, the OT curves of V1 neurons are more tuned, and their CRF is steeper, than those of their inputs. Last, we show that we are able to account for the heterogeneity in the measured CRFs, by introducing inhomogeneities either in single neuron properties or in the input to the neurons. Correlations among the CRF parameters are different for the different sources for diversity. Comparison with experimental data shows that both sources contribute about equally to heterogeneity in V1.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Persi ErezPhD, physics, Pierre et Marie Curie MSc, physics, program of neural computation, Tel-Aviv University BSc, physics, Tel-Aviv UniversityAutor/Autorin: Hansel DavidPhD, physics, Pierre et Marie Curie MSc, physics,. N° de réf. du vendeur 4966583
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - We developed a model to investigate possible mechanisms underlying the shape of contrast (CRF) and tuning (OT) curves of neurons in the primary visual cortex, V1. We determine analytically the conditions for the structure of the afferent LGN and recurrent V1 inputs that lead to contrast-invariance width of the OT curve and to the nonlinear shape of the CRF. We investigate what are the relative contributions of single neuron and network properties in shaping the OT and the CRF. We test our model with numerical simulations of conductance-based model (CBM). The results indicate that the main effect of a cortex of neurons with accelerating transfer-functions, described here by a power-law, is sharpening. Thus, the OT curves of V1 neurons are more tuned, and their CRF is steeper, than those of their inputs. Last, we show that we are able to account for the heterogeneity in the measured CRFs, by introducing inhomogeneities either in single neuron properties or in the input to the neurons. Correlations among the CRF parameters are different for the different sources for diversity. Comparison with experimental data shows that both sources contribute about equally to heterogeneity in V1. N° de réf. du vendeur 9783639201307
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Taschenbuch. Etat : Neu. Contrast and tuning properties of neurons in the visual cortex | Modeling and data analysis | Erez Persi (u. a.) | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639201307 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 101334033
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