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Journal Article

Citation

Bagheri ZM, Wiederman SD, Cazzolato BS, Grainger S, O'Carroll DC. J. R. Soc. Interface 2015; 12(108): 20150083.

Affiliation

Adelaide Centre for Neuroscience Research, The University of Adelaide, Adelaide, South Australia 5005, Australia Department of Biology, Lund University, Sölvegatan 35, S-22362 Lund, Sweden.

Copyright

(Copyright © 2015, Royal Society)

DOI

10.1098/rsif.2015.0083

PMID

26063815

PMCID

PMC4528576

Abstract

Although flying insects have limited visual acuity (approx. 1°) and relatively small brains, many species pursue tiny targets against cluttered backgrounds with high success. Our previous computational model, inspired by electrophysiological recordings from insect 'small target motion detector' (STMD) neurons, did not account for several key properties described from the biological system. These include the recent observations of response 'facilitation' (a slow build-up of response to targets that move on long, continuous trajectories) and 'selective attention', a competitive mechanism that selects one target from alternatives. Here, we present an elaborated STMD-inspired model, implemented in a closed loop target-tracking system that uses an active saccadic gaze fixation strategy inspired by insect pursuit. We test this system against heavily cluttered natural scenes. Inclusion of facilitation not only substantially improves success for even short-duration pursuits, but it also enhances the ability to 'attend' to one target in the presence of distracters. Our model predicts optimal facilitation parameters that are static in space and dynamic in time, changing with respect to the amount of background clutter and the intended purpose of the pursuit. Our results provide insights into insect neurophysiology and show the potential of this algorithm for implementation in artificial visual systems and robotic applications.


Language: en

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