Cell-based model of the Limulus lateral eye.

Abstract

We present a cell-based model of the Limulus lateral eye that computes the eye's input to the brain in response to any specified scene. Based on the results of extensive physiological studies, the model simulates the optical sampling of visual space by the array of retinal receptors (ommatidia), the transduction of light into receptor potentials, the integration of excitatory and inhibitory signals into generator potentials, and the conversion of generator potentials into trains of optic nerve impulses. By simulating these processes at the cellular level, model ommatidia can reproduce response variability resulting from noise inherent in the stimulus and the eye itself, and they can adapt to changes in light intensity over a wide operating range. Programmed with these realistic properties, the model eye computes the simultaneous activity of its ensemble of optic nerve fibers, allowing us to explore the retinal code that mediates the visually guided behavior of the animal in its natural habitat. We assess the accuracy of model predictions by comparing the response recorded from a single optic nerve fiber to that computed by the model for the corresponding receptor. Correlation coefficients between recorded and computed responses were typically >95% under laboratory conditions. Parametric analyses of the model together with optic nerve recordings show that animal-to-animal variation in the optical and neural properties of the eye do not alter significantly its response to objects having the size and speed of horseshoe crabs. The eye appears robustly designed for encoding behaviorally important visual stimuli. Simulations with the cell-based model provide insights about the design of the Limulus eye and its encoding of the animal's visual world.