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A unified neural network model of spatiotemporal processing in X and Y retinal ganglion cells. II. Temporal adaptation and simulation of experimental data.
Gaudiano, P.
Afiliación
  • Gaudiano P; Department of Cognitive & Neural Systems, Boston University, MA 02215.
Biol Cybern ; 67(1): 23-34, 1992.
Article en En | MEDLINE | ID: mdl-1606241
ABSTRACT
This article makes use of a push-pull shunting network, which was introduced in the companion article, to model certain properties of X and Y retinal ganglion cells. Input to the push-pull network is preprocessed by a nonlinear mechanism for temporal adaptation, which is ascribed here to photoreceptor dynamics. The complete circuit is used to show that a simple change in receptive field morphology within a single model equation can change the network's response characteristics to closely resemble those of either X or Y cells. Specifically, an increase in width of the receptive field center mechanism is sufficient to account for generation of on-off (Y-like) instead of null (X-like) responses to modulated gratings. In agreement with experimental data, the Y cell on-off response is independent of spatial phase. Also, the model accurately predicts that on-off responses can be observed in X cells for particular stimulus configurations. Taken together, the results show how the retina combines individually inadequate modules to efficiently handle the tasks required for accurate spatial and temporal visual information processing. The model is also able to clarify a number of controversial experimental findings on the nature of spatiotemporal visual processing in the retina.
Asunto(s)
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Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Células Fotorreceptoras / Células Ganglionares de la Retina / Visión Ocular / Redes Neurales de la Computación / Modelos Neurológicos Tipo de estudio: Prognostic_studies Idioma: En Revista: Biol Cybern Año: 1992 Tipo del documento: Article
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Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Células Fotorreceptoras / Células Ganglionares de la Retina / Visión Ocular / Redes Neurales de la Computación / Modelos Neurológicos Tipo de estudio: Prognostic_studies Idioma: En Revista: Biol Cybern Año: 1992 Tipo del documento: Article