title: Properties of neuronal facilitation that improve target tracking in natural pursuit simulations.
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.
authors.affiliation: Adelaide Centre for Neuroscience Research, The University of Adelaide, Adelaide, South Australia 5005, Australia School of Mechanical Engineering, The University of Adelaide, Adelaide, South Australia 5005, Australia zahra.bagheri@adelaide.edu.au.
authors.forename: Zahra M
authors.identifier: http://orcid.org/0000-0002-1749-3441
authors.initials: ZM
authors.lastname: Bagheri
authors.affiliation: Adelaide Centre for Neuroscience Research, The University of Adelaide, Adelaide, South Australia 5005, Australia.
authors.forename: Steven D
authors.identifier: http://orcid.org/0000-0002-0902-803X
authors.initials: SD
authors.lastname: Wiederman
authors.affiliation: School of Mechanical Engineering, The University of Adelaide, Adelaide, South Australia 5005, Australia.
authors.forename: Benjamin S
authors.identifier: http://orcid.org/0000-0003-2308-799X
authors.initials: BS
authors.lastname: Cazzolato
authors.affiliation: School of Mechanical Engineering, The University of Adelaide, Adelaide, South Australia 5005, Australia.
authors.forename: Steven
authors.initials: S
authors.lastname: Grainger
authors.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.
authors.forename: David C
authors.identifier: http://orcid.org/0000-0002-2352-4320
authors.initials: DC
authors.lastname: O'Carroll
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D005426:Flight, Animal / Q000502:physiology*; D007313:Insecta / Q000502:physiology*; D008959:Models, Neurological
keywords: bioinspired system; insect physiology; insect vision; motion detection; selective attention; target tracking