A Computational Framework for Realistic Retina Modeling.

Computational simulations of the retina have led to valuable insights about the biophysics of its neuronal activity and processing principles. A great number of retina models have been proposed to reproduce the behavioral diversity of the different visual processing pathways. While many of these models share common computational stages, previous efforts have been more focused on fitting specific retina functions rather than generalizing them beyond a particular model.

Visual training and emotional state of people with retinitis pigmentosa.

The purpose of the study was to improve the visual functioning of people with restriction in contrast sensitivity (CS), such as retinitis pigmentosa (RP), by means of a visual training program. Twenty-six volunteers with RP participated, distributed in two groups: 15 who made up the experimental group (who received the training program) and 11 who participated as a control group (without training). Participants were evaluated before beginning training, on completion, and 3 mo following completion for CS with the Pelli-Robson Contrast Sensitivity (P&R) test, visual functioning with the Visual Function Questionnaire (VFQ), and in emotional state with the Beck Depression Inventory (BDI).

Visual system based on artificial retina for motion detection.

We present a bioinspired model for detecting spatiotemporal features based on artificial retina response models. Event-driven processing is implemented using four kinds of cells encoding image contrast and temporal information. We have evaluated how the accuracy of motion processing depends on local contrast by using a multiscale and rank-order coding scheme to select the most important cues from retinal inputs.