Startseite Understanding visual processing of motion: completing the picture using experimentally driven computational models of MT
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Understanding visual processing of motion: completing the picture using experimentally driven computational models of MT

  • Parvin Zarei Eskikand EMAIL logo , David B. Grayden , Tatiana Kameneva , Anthony N. Burkitt und Michael R. Ibbotson
Veröffentlicht/Copyright: 20. September 2023
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Abstract

Computational modeling helps neuroscientists to integrate and explain experimental data obtained through neurophysiological and anatomical studies, thus providing a mechanism by which we can better understand and predict the principles of neural computation. Computational modeling of the neuronal pathways of the visual cortex has been successful in developing theories of biological motion processing. This review describes a range of computational models that have been inspired by neurophysiological experiments. Theories of local motion integration and pattern motion processing are presented, together with suggested neurophysiological experiments designed to test those hypotheses.


Corresponding author: Parvin Zarei Eskikand, Department of Biomedical Engineering, The University of Melbourne, Parkville 3052, Australia, E-mail:

  1. Research ethics: Not applicable.

  2. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: The authors state no conflict of interest.

  4. Research funding: None declared.

  5. Data availability: Not applicable.

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Received: 2023-05-08
Accepted: 2023-09-02
Published Online: 2023-09-20
Published in Print: 2024-04-25

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