Flying insects possess remarkable navigation abilities, and may be used as an inspiration for the design of fast, low-power, robust autonomous robots. Essential to visual insect navigation is complex motion detection circuitry. A neuronally-based model for elementary motion detectors (EMDs) in the fly has been previously proposed, but there are a number of computational features that are not supported by this model. We propose an expanded version of the model incorporating saturation and motion adaptation, and show simulation results that match recordings of the electrical activity of fly motion-sensitive interneurons. Our expanded model is used to explain data which suggests adaptation of the EMD filter parameters and the results of genetic experiments in which cells proposed to be involved in motion detection were successfully blocked in flies. In addition, we have identified a possible mechanism through which insects could extract speed information from the projected retinal image.
Zuley Rivera-Alvidrez, "Computational modeling of neurons involved in fly motion detection," MS thesis (advisor: Charles M. Higgins), Department of Electrical and Computer Engineering, The University of Arizona, August 2005.