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Properties of neuronal facilitation that improve target tracking in natural pursuit simulations.

Bagheri, Zahra M; Wiederman, Steven D; Cazzolato, Benjamin S; Grainger, Steven and O'Carroll, David LU (2015) In Journal of the Royal Society Interface 12(108).
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... (More)
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. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of the Royal Society Interface
volume
12
issue
108
publisher
Royal Society
external identifiers
  • pmid:26063815
  • wos:000358824600020
  • scopus:84936775265
ISSN
1742-5662
DOI
10.1098/rsif.2015.0083
language
English
LU publication?
yes
id
051fcbb3-c614-4ead-b55d-d79b64cff36a (old id 7486893)
date added to LUP
2015-08-13 09:01:11
date last changed
2017-10-29 03:15:28
@article{051fcbb3-c614-4ead-b55d-d79b64cff36a,
  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.},
  articleno    = {20150083},
  author       = {Bagheri, Zahra M and Wiederman, Steven D and Cazzolato, Benjamin S and Grainger, Steven and O'Carroll, David},
  issn         = {1742-5662},
  language     = {eng},
  number       = {108},
  publisher    = {Royal Society},
  series       = {Journal of the Royal Society Interface},
  title        = {Properties of neuronal facilitation that improve target tracking in natural pursuit simulations.},
  url          = {http://dx.doi.org/10.1098/rsif.2015.0083},
  volume       = {12},
  year         = {2015},
}