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Visual illusions via neural dynamics: Wilson-Cowan-type models and the efficient representation principle.

Marcelo Bertalmío1, Luca Calatroni2, Valentina Franceschi3

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Wilson-Cowan models can replicate visual illusions, but are suboptimal. A modified variational approach improves illusion reproduction by adhering to efficient representation principles.

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Area of Science:

  • Computational neuroscience
  • Visual perception modeling

Background:

  • Wilson-Cowan (WC) models are foundational for neuronal dynamics.
  • Replicating visual illusions like brightness and orientation-dependent phenomena tests model fidelity.
  • The efficient representation principle guides optimal neural activity.

Purpose of the Study:

  • To investigate Wilson-Cowan models' ability to reproduce visual illusions.
  • To assess WC model compliance with the efficient representation principle.
  • To develop an improved model for enhanced visual illusion reproduction.

Main Methods:

  • Reproducing visual illusions using Wilson-Cowan (WC) type models.
  • Formally proving the absence of a minimized energy functional for WC dynamics.
  • Employing variational modeling and local histogram equalization (LHE).
  • Extending the model for V1 architecture with orientation dependence.

Main Results:

  • WC equations can reproduce brightness and orientation-dependent visual illusions.
  • WC dynamics do not minimize an energy functional, indicating suboptimality.
  • A modified variational model (LHE) shows superior illusion reproduction compared to WC.
  • A cortical extension of LHE effectively reproduces complex orientation-dependent illusions.

Conclusions:

  • Wilson-Cowan models demonstrate capacity for reproducing certain visual illusions.
  • The efficient representation principle is crucial for accurate neural modeling.
  • Variational modeling, particularly LHE and its cortical extension, offers a more effective approach to modeling visual perception and illusions.