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Hierarchical Novelty-Familiarity Representation in the Visual System by Modular Predictive Coding.

Boris Vladimirskiy1, Robert Urbanczik1, Walter Senn1

  • 1Department of Physiology, University of Bern, Bühlplatz 5, 3012 Bern, Switzerland.

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Modular predictive coding offers a new feedforward framework for the visual system. This approach efficiently represents visual information by separating novelty and familiarity, enhancing processing speed and representational power.

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Area of Science:

  • Computational Neuroscience
  • Visual System Modeling
  • Information Theory

Background:

  • Predictive coding is a hierarchical framework for visual processing.
  • Existing models involve dynamic subtraction of predicted activity and backward projections.
  • Hierarchical processing is crucial for understanding visual perception.

Purpose of the Study:

  • Introduce modular predictive coding (MPC) as a novel feedforward hierarchy.
  • Investigate the segregation of visual input into novelty and familiarity components.
  • Evaluate the biological realism and efficiency of MPC for visual information processing.

Main Methods:

  • Developed a feedforward hierarchy of prediction modules without back-projections.
  • Incorporated recurrent dynamics within each module for input segregation.
  • Simulated image compression and reconstruction using MPC principles.

Main Results:

  • MPC rapidly forms familiarity-novelty representations.
  • Familiarity information is propagated to higher levels, while novelty is processed locally.
  • Natural images are compressed and reconstructed effectively by familiarity neurons.
  • Novelty neurons identify missing information across spatial scales.
  • Non-classical receptive field properties emerge due to recurrent connectivity.

Conclusions:

  • Modular predictive coding provides a biologically plausible model for the visual system.
  • MPC efficiently extracts novelty and propagates familiarity information across hierarchical levels.
  • This framework enhances representational power and processing speed compared to traditional predictive coding.