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Brightness perception, illusory contours, and corticogeniculate feedback

A Gove1, S Grossberg, E Mingolla

  • 1MIT Lincoln Laboratory, Lexington, MA, USA.

Visual Neuroscience
|November 1, 1995
PubMed
Summary
This summary is machine-generated.

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A neural network model explains how visual cortex feedback creates illusory contours and filled-in brightness. This model simulates visual perception using thalamocortical interactions and boundary-surface mechanisms.

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Computer Vision

Background:

  • Visual perception involves complex interactions between the thalamus and cortex.
  • Understanding how the brain processes visual information, such as boundaries and surfaces, is a key challenge in neuroscience.

Purpose of the Study:

  • To develop a neural network model that explains visual thalamocortical interactions.
  • To simulate the generation of boundary percepts (e.g., illusory contours) and surface percepts (e.g., filled-in brightnesses).

Main Methods:

  • Modeled top-down feedback loops between the lateral geniculate nucleus (LGN) and cortical areas V1 and V2.
  • Incorporated corticogeniculate feedback for matching and enhancing LGN cell activities.
  • Modeled a second feedback loop within V1 and V2 for boundary representation and feature binding.

Related Experiment Videos

  • Simulated brightness perception using diffusive filling-in processes within surface representations gated by boundary signals.
  • Tested the model with various visual stimuli including Ehrenstein disks, Kanizsa squares, Glass patterns, and café wall patterns.

    • Main Results:

    • The model successfully simulated illusory contours and surface brightness percepts across different contrast configurations.
    • Demonstrated the role of corticogeniculate feedback in enhancing LGN activity and contributing to brightness perception.
    • Showcased how feedback loops generate boundary representations that bind distributed cortical features.
    • Illustrated context-sensitive perception, including amodal recognition of illusory contours.
    • Highlighted the differential contributions of simple and bipole cell groupings in V1 and V2.
    • Explained the interaction of double-opponent, filling-in, and boundary segmentation mechanisms in V4 for surface brightness perception.

    Conclusions:

    • Thalamocortical feedback loops are crucial for generating complex visual percepts like illusory contours and surface brightness.
    • The model provides a computational framework for understanding how boundary and surface mechanisms interact to create context-sensitive visual experiences.
    • This work offers insights into the neural basis of visual perception and its susceptibility to various stimulus configurations.