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R Moreno-Díaz

Publications and source records attributed to R Moreno-Díaz.

5 recordsLinked to original sources

A model for non-linear processing in cat's retina.

The model is based on the concept that non-linear lateral interaction at the inner plexiform layer accounts for most of the specialization and marked non-linearities in cat's retinal ganglion cell responses. The inputs to the lateral interaction processes are a spatio-temporal signal and its retarded, as suggested by the behaviour of simple ganglion cells. Lateral interaction in the model consists of lateral linear inhibition followed by local half wave rectification. The resulting signals are weighted and summated by the ganglion cell thereafter. A transparent and general expression is obtained for the response of the cell model which, albeit its simplicity, leads to most of known types of non-linear responses, including the rarely encountered specialized cells in cat's, retina, except colour coding units. For negligible lateral interaction, the model reduces to spatio-temporal linear models under the two paths hypothesis. A discussion of the possible role of anatomical units in these retinal processes in presented, where a general interpretation for visual processing in cat's retina evolves from.

Animals↗

A layered model for visual processing in avian retina.

Visual processing in avian retina is interpreted by means of a layered model in which: a) outer layers provide with spatio temporal fast and retarded versions of the stimuli incident on the retina; a possibility is that horizontal cells are involved in isotropically generating the retarded version which is transversally translated; b) prominent specialization of ganglion cells is the result of local non-linear lateral interaction at the inner plexiform layer, mediated by amacrines which return, also isotropically, the translated retarded signals. Small though systematic deviations in the sites of the lateral interaction result in anisotropic but uniform receptive fields for some ganglion cells. A simple though general expression for the model is derived which includes the various types of recorded avian ganglion retinal cells responses, which also permits a unified interpretation of visual processing in avian and cat's retinae.

Animals↗

A theoretical proposal to account for visual computation in a frog's retina.

Our theoretical account for visual computation in a frog's retina is based on the concepts that: (a) outer retinal layers provide three spatial channels of information pertaining to local spatio-temporal properties of retinal stimuli; (b) prominent specialisation in a frog's retina is the result of a non-linear lateral interaction at the inner plexiform layer; (c) ganglion cell firing frequency is determined by a local computation wherein signals from processes above are either excitatory, facilitatory or defacilitatory. General though concrete expressions for the processing at different layers are developed from these concepts. They result in a unified model for ganglion retinal cells in frog, from which the various extreme groups of ganglia can be deduced. The model leaves a natural margin to fit intermediate types, both found and likely to be found.

Animals↗

Computer programs to implement retinal models.

To implement retinal models of some complexity a set of computer programs, coordinated by a main program is required. A set of said programs is presented here which permits the design and the experimentation with linear and non-linear retinal layered models. A main program, called RETINA, is the basis for the building of a model, the generation of the input stimuli and the experimentation with the overall system.

Computers↗

A theoretical model for layered visual processing.

A theoretical general model of layered computation in the retina is presented. Each layer is functional in the sense that it may correspond or not to an anatomical layer. It is formed by computing elements which can perform in principle any non-linear arbitrary function on a three-dimensional input space. This space consists of 2 spatial dimensions, plus time. The function performed by each computing element of a layer is simplified for the cases of invariance, space or time linearity and for time independence. Two illustrations are also presented. The first is a model of the simple ganglion cells in cat's retina. The second, a model of the group 2 ganglion cell of the frog's retina.

Animals↗