Abstract
We propose a new bio-plausible model based on the visual systems of Drosophila for estimating angular velocity of image motion in insects’ eyes. The model implements both preferred direction motion enhancement and non-preferred direction motion suppression which is discovered in Drosophila’s visual neural circuits recently to give a stronger directional selectivity. In addition, the angular velocity detecting model (AVDM) produces a response largely independent of the spatial frequency in grating experiments which enables insects to estimate the flight speed in cluttered environments. This also coincides with the behaviour experiments of honeybee flying through tunnels with stripes of different spatial frequencies.
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This research is supported by EU FP7-IRSES Project LIVCODE (295151), HAZCEPT (318907) and HORIZON project STEP2DYNA (691154).
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Wang, H., Peng, J., Baxter, P., Zhang, C., Wang, Z., Yue, S. (2018). A Model for Detection of Angular Velocity of Image Motion Based on the Temporal Tuning of the Drosophila. In: Kůrková, V., Manolopoulos, Y., Hammer, B., Iliadis, L., Maglogiannis, I. (eds) Artificial Neural Networks and Machine Learning – ICANN 2018. ICANN 2018. Lecture Notes in Computer Science(), vol 11140. Springer, Cham. https://doi.org/10.1007/978-3-030-01421-6_4
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