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Salience invariance with divisive normalization in higher-order insect neurons

Evans, Bernard J E LU ; O'Carroll, David C. LU and Wiederman, Steven D (2016) 6th European Workshop on Visual Information Processing, EUVIP 2016 In Proceedings of the 2016 6th European Workshop on Visual Information Processing, EUVIP 2016
Abstract

We present a biologically inspired model for estimating the position of a moving target that is invariant to the target's contrast. Our model produces a monotonic relationship between position and output activity using a divisive normalization between the 'receptive fields' of two overlapping, wide-field, small-target motion detector (STMD) neurons. These visual neurons found in flying insects, likely underlie the impressive ability to pursue prey within cluttered environments. Individual STMD responses confound the properties of target contrast, size, velocity and position. Inspired by results from STMD recordings we developed a model using a division operation to overcome the inherent positional ambiguities of integrative neurons. We... (More)

We present a biologically inspired model for estimating the position of a moving target that is invariant to the target's contrast. Our model produces a monotonic relationship between position and output activity using a divisive normalization between the 'receptive fields' of two overlapping, wide-field, small-target motion detector (STMD) neurons. These visual neurons found in flying insects, likely underlie the impressive ability to pursue prey within cluttered environments. Individual STMD responses confound the properties of target contrast, size, velocity and position. Inspired by results from STMD recordings we developed a model using a division operation to overcome the inherent positional ambiguities of integrative neurons. We used genetic algorithms to determine the plausibility of such an operation arising and existing over multiple generations. This method allows the lost information to be recovered without needing additional neuronal pathways.

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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Biological Neural Networks, Biological System Modeling, Cellular Biophysics, Genetic Algorithms, Physiology
in
Proceedings of the 2016 6th European Workshop on Visual Information Processing, EUVIP 2016
publisher
Institute of Electrical and Electronics Engineers Inc.
conference name
6th European Workshop on Visual Information Processing, EUVIP 2016
external identifiers
  • scopus:85011298725
ISBN
9781509027811
DOI
10.1109/EUVIP.2016.7764588
language
English
LU publication?
yes
id
2a4ac523-0ddd-468a-8599-98386c1bab6a
date added to LUP
2017-02-16 09:37:34
date last changed
2017-04-23 04:58:05
@inproceedings{2a4ac523-0ddd-468a-8599-98386c1bab6a,
  abstract     = {<p>We present a biologically inspired model for estimating the position of a moving target that is invariant to the target's contrast. Our model produces a monotonic relationship between position and output activity using a divisive normalization between the 'receptive fields' of two overlapping, wide-field, small-target motion detector (STMD) neurons. These visual neurons found in flying insects, likely underlie the impressive ability to pursue prey within cluttered environments. Individual STMD responses confound the properties of target contrast, size, velocity and position. Inspired by results from STMD recordings we developed a model using a division operation to overcome the inherent positional ambiguities of integrative neurons. We used genetic algorithms to determine the plausibility of such an operation arising and existing over multiple generations. This method allows the lost information to be recovered without needing additional neuronal pathways.</p>},
  author       = {Evans, Bernard J E and O'Carroll, David C. and Wiederman, Steven D},
  booktitle    = {Proceedings of the 2016 6th European Workshop on Visual Information Processing, EUVIP 2016},
  isbn         = {9781509027811},
  keyword      = {Biological Neural Networks,Biological System Modeling,Cellular Biophysics,Genetic Algorithms,Physiology},
  language     = {eng},
  month        = {12},
  publisher    = {Institute of Electrical and Electronics Engineers Inc.},
  title        = {Salience invariance with divisive normalization in higher-order insect neurons},
  url          = {http://dx.doi.org/10.1109/EUVIP.2016.7764588},
  year         = {2016},
}