Real-time simulation of the retina allowing visualization of each processing stage

Jeffrey L. Teeters; Frank S. Werblin

doi:10.1117/12.45555

9 July 1991 Real-time simulation of the retina allowing visualization of each processing stage

Jeffrey L. Teeters, Frank S. Werblin

Proceedings Volume 1473, Visual Information Processing: From Neurons to Chips; (1991) https://doi.org/10.1117/12.45555
Event: Orlando '91, 1991, Orlando, FL, United States

Abstract

The retina computes to let us see, but can we see the retina compute? Until now, the answer has been 'no' because the unconscious nature of the processing hides it from our view. Here we overcome the barrier of our closeness and describe what (to our knowledge) is the first method of seeing computations performed throughout the retina. This is achieved by using neurophysiological data to construct a model of the retina, and using a special purpose image processing computer (PIPE) to implement the model in real time. Processing in the model is organized into stages corresponding to computations performed by each retinal cell type. The final stage is the iransient (change detecting) ganglion cell. A CCD camera forms the input image and the activity of a selected retinal cell type is the output which is displayed on a TV monitor. By changing the retina cell driving the monitor, the progressive transformations of the image by the retina can be observed. Our simulations demonstrate the ubiquitous presence of temporal and spatial variations in the patterns of activity generated by the retina which are fed into the brain. The dynamical aspects make these patterns very different from those generated by the common DOG (Difference of Gaussian) model of receptive field. Because the retina is so successful in biological vision systems, the processing we describe here may be useful in machine vision.

Citation Download Citation

Jeffrey L. Teeters and Frank S. Werblin "Real-time simulation of the retina allowing visualization of each processing stage", Proc. SPIE 1473, Visual Information Processing: From Neurons to Chips, (9 July 1991); https://doi.org/10.1117/12.45555

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