A Dynamical Systems Model for Face Perception

Abraham Boyarsky; Paweł Góra

doi:doi:10.11648/j.ajmcm.20210604.13

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A Dynamical Systems Model for Face Perception

Abraham Boyarsky, Paweł Góra

Published in American Journal of Mathematical and Computer Modelling (Volume 6, Issue 4)

Received: 29 November 2021 Accepted: 11 December 2021 Published: 24 December 2021

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Abstract

The fusiform face area, or FFA, is a small region found on the inferior (bottom) surface of the temporal lobe. It is located in a gyrus called the fusiform gyrus.Studies in humans have shown that the FFA is sensitive to both face parts and face configurations. Recoding activity in the FFA showed that most of the neurons in the FFA are active in response to facial imagery, but not in response to images of other body parts or objects. Visual sensory neurons sensitive to a face feature and possessing a related firing rate activate an associated cluster of neurons in the FFA. This results in a partition of the FFA into clusters that respond to the various facial features. Once an entire face stimulus activates the FFA, interneurons redistribute the initial activation via the neural network. In this article a novel approach to modelling the function of the network is presented. We define by a transition matrix that describes probabilistically how one cluster, firing at a synchronous rate, affects the others in the FFA. The initial face stimulation in the FFA together with the transition matrix defines a dynamical system which possesses a stationary probability function. We claim that a stationary probability function uniquely represents a face. Among the properties of this probability function are: 1) response magnitude invariance, 2) repurposing of clusters to define new stationary probability function on the FFA partition; 3) stability of stationary probabilities under perturbations.

Published in	American Journal of Mathematical and Computer Modelling (Volume 6, Issue 4)
DOI	10.11648/j.ajmcm.20210604.13
Page(s)	76-80
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Dynamical Systems, Model for Face Perception, Fusiform Face Area (FFA), Face Parts, Stationary Measure, Stability

References

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Abraham Boyarsky, Paweł Góra. (2021). A Dynamical Systems Model for Face Perception. American Journal of Mathematical and Computer Modelling, 6(4), 76-80. https://doi.org/10.11648/j.ajmcm.20210604.13

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ACS Style

Abraham Boyarsky; Paweł Góra. A Dynamical Systems Model for Face Perception. Am. J. Math. Comput. Model. 2021, 6(4), 76-80. doi: 10.11648/j.ajmcm.20210604.13

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AMA Style

Abraham Boyarsky, Paweł Góra. A Dynamical Systems Model for Face Perception. Am J Math Comput Model. 2021;6(4):76-80. doi: 10.11648/j.ajmcm.20210604.13

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@article{10.11648/j.ajmcm.20210604.13,
  author = {Abraham Boyarsky and Paweł Góra},
  title = {A Dynamical Systems Model for Face Perception},
  journal = {American Journal of Mathematical and Computer Modelling},
  volume = {6},
  number = {4},
  pages = {76-80},
  doi = {10.11648/j.ajmcm.20210604.13},
  url = {https://doi.org/10.11648/j.ajmcm.20210604.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmcm.20210604.13},
  abstract = {The fusiform face area, or FFA, is a small region found on the inferior (bottom) surface of the temporal lobe. It is located in a gyrus called the fusiform gyrus.Studies in humans have shown that the FFA is sensitive to both face parts and face configurations. Recoding activity in the FFA showed that most of the neurons in the FFA are active in response to facial imagery, but not in response to images of other body parts or objects. Visual sensory neurons sensitive to a face feature and possessing a related firing rate activate an associated cluster of neurons in the FFA. This results in a partition of the FFA into clusters that respond to the various facial features. Once an entire face stimulus activates the FFA, interneurons redistribute the initial activation via the neural network. In this article a novel approach to modelling the function of the network is presented. We define by a transition matrix that describes probabilistically how one cluster, firing at a synchronous rate, affects the others in the FFA. The initial face stimulation in the FFA together with the transition matrix defines a dynamical system which possesses a stationary probability function. We claim that a stationary probability function uniquely represents a face. Among the properties of this probability function are: 1) response magnitude invariance, 2) repurposing of clusters to define new stationary probability function on the FFA partition; 3) stability of stationary probabilities under perturbations.},
 year = {2021}
}

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TY  - JOUR
T1  - A Dynamical Systems Model for Face Perception
AU  - Abraham Boyarsky
AU  - Paweł Góra
Y1  - 2021/12/24
PY  - 2021
N1  - https://doi.org/10.11648/j.ajmcm.20210604.13
DO  - 10.11648/j.ajmcm.20210604.13
T2  - American Journal of Mathematical and Computer Modelling
JF  - American Journal of Mathematical and Computer Modelling
JO  - American Journal of Mathematical and Computer Modelling
SP  - 76
EP  - 80
PB  - Science Publishing Group
SN  - 2578-8280
UR  - https://doi.org/10.11648/j.ajmcm.20210604.13
AB  - The fusiform face area, or FFA, is a small region found on the inferior (bottom) surface of the temporal lobe. It is located in a gyrus called the fusiform gyrus.Studies in humans have shown that the FFA is sensitive to both face parts and face configurations. Recoding activity in the FFA showed that most of the neurons in the FFA are active in response to facial imagery, but not in response to images of other body parts or objects. Visual sensory neurons sensitive to a face feature and possessing a related firing rate activate an associated cluster of neurons in the FFA. This results in a partition of the FFA into clusters that respond to the various facial features. Once an entire face stimulus activates the FFA, interneurons redistribute the initial activation via the neural network. In this article a novel approach to modelling the function of the network is presented. We define by a transition matrix that describes probabilistically how one cluster, firing at a synchronous rate, affects the others in the FFA. The initial face stimulation in the FFA together with the transition matrix defines a dynamical system which possesses a stationary probability function. We claim that a stationary probability function uniquely represents a face. Among the properties of this probability function are: 1) response magnitude invariance, 2) repurposing of clusters to define new stationary probability function on the FFA partition; 3) stability of stationary probabilities under perturbations.
VL  - 6
IS  - 4
ER  -

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Author Information

Abraham Boyarsky

Department of Mathematics and Statistics, Concordia University, 1455 de Maisonneuve Blvd. West, Montreal, Quebec H3G 1M8, Canada
Paweł Góra

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APA Style

Abraham Boyarsky, Paweł Góra. (2021). A Dynamical Systems Model for Face Perception. American Journal of Mathematical and Computer Modelling, 6(4), 76-80. https://doi.org/10.11648/j.ajmcm.20210604.13

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ACS Style

Abraham Boyarsky; Paweł Góra. A Dynamical Systems Model for Face Perception. Am. J. Math. Comput. Model. 2021, 6(4), 76-80. doi: 10.11648/j.ajmcm.20210604.13

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AMA Style

Abraham Boyarsky, Paweł Góra. A Dynamical Systems Model for Face Perception. Am J Math Comput Model. 2021;6(4):76-80. doi: 10.11648/j.ajmcm.20210604.13

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@article{10.11648/j.ajmcm.20210604.13,
  author = {Abraham Boyarsky and Paweł Góra},
  title = {A Dynamical Systems Model for Face Perception},
  journal = {American Journal of Mathematical and Computer Modelling},
  volume = {6},
  number = {4},
  pages = {76-80},
  doi = {10.11648/j.ajmcm.20210604.13},
  url = {https://doi.org/10.11648/j.ajmcm.20210604.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmcm.20210604.13},
  abstract = {The fusiform face area, or FFA, is a small region found on the inferior (bottom) surface of the temporal lobe. It is located in a gyrus called the fusiform gyrus.Studies in humans have shown that the FFA is sensitive to both face parts and face configurations. Recoding activity in the FFA showed that most of the neurons in the FFA are active in response to facial imagery, but not in response to images of other body parts or objects. Visual sensory neurons sensitive to a face feature and possessing a related firing rate activate an associated cluster of neurons in the FFA. This results in a partition of the FFA into clusters that respond to the various facial features. Once an entire face stimulus activates the FFA, interneurons redistribute the initial activation via the neural network. In this article a novel approach to modelling the function of the network is presented. We define by a transition matrix that describes probabilistically how one cluster, firing at a synchronous rate, affects the others in the FFA. The initial face stimulation in the FFA together with the transition matrix defines a dynamical system which possesses a stationary probability function. We claim that a stationary probability function uniquely represents a face. Among the properties of this probability function are: 1) response magnitude invariance, 2) repurposing of clusters to define new stationary probability function on the FFA partition; 3) stability of stationary probabilities under perturbations.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - A Dynamical Systems Model for Face Perception
AU  - Abraham Boyarsky
AU  - Paweł Góra
Y1  - 2021/12/24
PY  - 2021
N1  - https://doi.org/10.11648/j.ajmcm.20210604.13
DO  - 10.11648/j.ajmcm.20210604.13
T2  - American Journal of Mathematical and Computer Modelling
JF  - American Journal of Mathematical and Computer Modelling
JO  - American Journal of Mathematical and Computer Modelling
SP  - 76
EP  - 80
PB  - Science Publishing Group
SN  - 2578-8280
UR  - https://doi.org/10.11648/j.ajmcm.20210604.13
AB  - The fusiform face area, or FFA, is a small region found on the inferior (bottom) surface of the temporal lobe. It is located in a gyrus called the fusiform gyrus.Studies in humans have shown that the FFA is sensitive to both face parts and face configurations. Recoding activity in the FFA showed that most of the neurons in the FFA are active in response to facial imagery, but not in response to images of other body parts or objects. Visual sensory neurons sensitive to a face feature and possessing a related firing rate activate an associated cluster of neurons in the FFA. This results in a partition of the FFA into clusters that respond to the various facial features. Once an entire face stimulus activates the FFA, interneurons redistribute the initial activation via the neural network. In this article a novel approach to modelling the function of the network is presented. We define by a transition matrix that describes probabilistically how one cluster, firing at a synchronous rate, affects the others in the FFA. The initial face stimulation in the FFA together with the transition matrix defines a dynamical system which possesses a stationary probability function. We claim that a stationary probability function uniquely represents a face. Among the properties of this probability function are: 1) response magnitude invariance, 2) repurposing of clusters to define new stationary probability function on the FFA partition; 3) stability of stationary probabilities under perturbations.
VL  - 6
IS  - 4
ER  -

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