Complementary surrounds explain diverse contextual phenomena across visual modalities.

Area of Science:

• Neuroscience
• Computational Neuroscience
• Visual Perception

Background:

• Context significantly influences stimulus perception, leading to various visual illusions.
• The neural mechanisms underlying contextual processing in the visual cortex are not fully understood.

Purpose of the Study:

• To present a recurrent network model of classical and extraclassical receptive fields.
• To explain the neural basis of contextual visual illusions.
• To propose a novel taxonomy for organizing these phenomena.

Main Methods:

• Developed a recurrent neural network model constrained by visual cortex anatomy and physiology.
• Incorporated near and far extraclassical receptive fields with facilitatory and suppressive roles.
• Tested the model's ability to account for diverse contextual illusions.

Main Results:

• The model successfully explains a range of contextual illusions, including orientation tilt and chromatic induction.
• It reveals commonalities between different perceptual phenomena by modeling center-surround interactions.
• Explains enhanced perceptual shifts with specific patterned background stimuli.

Conclusions:

• The model provides computational evidence for a canonical circuit shared across visual modalities.
• It offers a unified framework for understanding contextual influences on visual perception.
• Highlights the complementary roles of near and far extraclassical receptive fields.