This collaborative study aims to advance the understanding of visual object recognition by combining electrophysiology, computational, modeling and psychophysics to probe the implications of newly discovered properties of neurons in visual cortical area V4, an important intermediate stage in the shape processing pathway of the brain.

V4 neurons respond selectively to a variety of shape attributes, but recent studies demonstrate that they are also selective for the contrast polarity of stimuli and can be broadly classified into four categories based on their preference for the luminance contrast of shapes relative to a uniform background. Specifically, Equiluminance cells respond best to stimuli defined purely by a chromatic contrast with no luminance contrast while Bright, Dark and Contrast cells respond best to positive contrasts, negative contrasts or either, respectively. Because these categories are based on simple stimuli, it remains unknown how these cells respond to more naturalistic stimuli, where boundaries are seldom defined by a fixed luminance contrast, and whether the different cell classes have different functional roles for encoding objects. Characterizing V4 neurons with a parameterized set of naturalistic stimuli that are developed with rigorous psychophysical testing will provide novel insights into underlying circuitry and function and open new understanding about V4 and the ventral stream.

Computational models of visual form processing in the brain have also been limited: they have not taken account of realistic physiological cell types known to exist from the retina to the visual cortex, they have been largely aimed at processing achromatic signals, and have relied heavily on feedfoward processing. This study will generate models that overcome these limitations and are invaluable for gaining insights into the circuits and mechanisms underlying form processing. These models will be available in an open, online framework designed to set a standard for ease of use and transparency, to spur further collaboration between theoreticians and experimentalists, and to facilitate education.

Finally, there has been a longstanding debate in vision science, motivated from the psychophysical literature, that questions whether and how chromatic signals contribute to form processing. The traditional view has been that boundary detection and segmentation are solely based on luminance contrast. Color then paints a surface within the confines of the identified boundary. Recent psychophysical and theoretical studies are at odds with this view and argue that color is important for segmentation and form processing in natural scenes, for example, fruit amidst leaves, where detection based on luminance contrast is very difficult. The experiments in this study will inject much needed physiology data into this debate and the models developed here will shed light on the functional organization of cortical pathways at multiple stages, revealing how different aspects of our natural visual input contribute to form perception.

This award is being co-funded by NSF's Office of the Director, International Science and Engineering. A companion project is being funded by the German Ministry of Education and Research (BMBF).

National Science Foundation (NSF)
Division of Information and Intelligent Systems (IIS)
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Kenneth C. Whang
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University of Washington
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