Copyright 2005 Society of Photo-Optical Instrumentation Engineers. This paper was published in Proceedings of SPIE Vol. 5783, pp. 292–303, 2005 (SPIE Defense and Security Symposium, Infrared Technology and Applications Conference, Orlando, FL, March-April 2005), and is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. Insect-based visual motion detection with contrast adaptation Patrick A. Shoemaker a , David C. O’Carroll b a Tanner Research, Inc., 2650 East Foothill Blvd., Pasadena, CA 91107, USA b Discipline of Physiology, University of Adelaide, Adelaide, SA 5005, Australia ABSTRACT The visual pathway that leads from the retina to the tangential cells in the third optical ganglion of the fly is a sophisticated system for the detection of visual motion. The tangential cells, whose responses are thought to characterize the state of egomotion of the animal, show a remarkable ability to encode velocity information about optic flow patterns to which they are sensitive, independent of the structure and contrast of viewed scenery. We describe a simulation study based on a model that accounts for key physiological features observed in the biological system, which contains nonlinear features that we expect to contribute to this capability. One of these features is motion adaptation, a phenomenon on which recent research has shed new light. We conclude that our models significantly reduce dependence of response on variable natural scenery, although they still do not perform as well in this respect as the biological neurons. This biological system has inspired an implementation of visual motion processing in analog VLSI technology. The neuromorphic circuits are intended for eventual on- or near-focal plane integration with photosensing. We describe the design approach and present results from preliminary versions of these circuits. 1. INTRODUCTION Although insects are relatively simple organisms compared to vertebrates, with nervous systems of limited size and complexity, they nonetheless do a remarkable job of controlling flight and other behaviors based on their low-resolution visual sense. Detection of visual motion plays a critical role in these behaviors. A class of widely-studied cells in the third optical ganglion of the true flies (dipterans), the tangential neurons, displays sensitivity to patterns of optic flow across broad swaths of the visual field, and almost certainly comprises a system for estimation of the state of egomotion of the organism. Some of these cells, for example, have been linked to stabilization about the yaw axis in hovering flight 1 , in certain species of flies. Other classes of neurons have also been found in this region of the brain that, although as yet less well-characterized, appear to be selective for different classes of visual motion; one in particular shows a remarkable selectivity for the motion of small targets against background 2 . We consider the chain of processing that leads from photoreception to the wide-field, egomotion-detecting tangential neurons in the insect brain. If this system is to provide the organism with information about its state of motion, it must estimate this information from time-varying patterns that depend on the absolute luminance, spectral content, contrast, and spatial structure of the visual scene, as transduced by the low-resolution imaging sensor that is the insect compound eye. The difficulty of this problem becomes clear when one considers that motion sensing should properly be invariant with respect to all of those parameters, because while they characterize the visual scene, they bear no relation to motion in or of that scene. They do, however, affect the response of neurons early in the visual pathway, and as well influence the response of models for the fundamental operations of motion detection in insects. In spite of this, tangential neurons display a remarkable insensitivity to variations of these parameters in natural scenery, which, although not entirely understood, seems due in large part to various stages of nonlinear processing in the signal path. We discuss this processing in brief, and focus in particular on the phenomenon of motion adaptation, which we have studied