Brightness and Darkness as Perceptual Dimensions

A common-sense assumption concerning visual perception states that brightness and darkness cannot coexist at a given spatial location. One corollary of this assumption is that achromatic colors, or perceived grey shades, are contained in a one-dimensional (1-D) space varying from bright to dark. The results of many previous psychophysical studies suggest, by contrast, that achromatic colors are represented as points in a color space composed of two or more perceptual dimensions. The nature of these perceptual dimensions, however, presently remains unclear. Here we provide direct evidence that brightness and darkness form the dimensions of a two-dimensional (2-D) achromatic color space. This color space may play a role in the representation of object surfaces viewed against natural backgrounds, which simultaneously induce both brightness and darkness signals. Our 2-D model generalizes to the chromatic dimensions of color perception, indicating that redness and greenness (blueness and yellowness) also form perceptual dimensions. Collectively, these findings suggest that human color space is composed of six dimensions, rather than the conventional three

Edge integration and the perception of brightness and darkness

How do induced brightness and darkness signals from local and remote surfaces interact to determine the final achromatic color percept of a target surface? An emerging theory of achromatic color perception posits that brightness and darkness percepts are computed by weighting and summing the induction signals generated at edges in a scene. This theory also characterizes how neighboring edges interact to modulate the gain of brightness and darkness signals induced from one another. Here we assess evidence for this edge integration theory by means of computational modeling and a psychophysical experiment. We quantitatively show how local and remote edge induction signals in disk-ring displays give rise to either contrast or assimilation effects. Spatial integration of same-polarity edge signals supports a contrast effect, whereas integration of opposite- polarity signals supports an assimilation effect, particularly when the remote induction signal is much stronger than the local induction signal. The results confirm a key prediction of edge integration theory, namely, that strong assimilation effects can lead subjects to ignore the polarity of local edge information when setting achromatic color matches. The conditions necessary for strong assimilation effects are also associated with greater difficulty in setting matches, suggesting that caution is required when interpreting matching data in terms of gain control. We describe several avenues for further study of contrast, assimilation, and gain control

An Animal Model of Emotional Blunting in Schizophrenia

Schizophrenia is often associated with emotional blunting—the diminished ability to respond to emotionally salient stimuli—particularly those stimuli representative of negative emotional states, such as fear. This disturbance may stem from dysfunction of the amygdala, a brain region involved in fear processing. The present article describes a novel animal model of emotional blunting in schizophrenia. This model involves interfering with normal fear processing (classical conditioning) in rats by means of acute ketamine administration. We confirm, in a series of experiments comprised of cFos staining, behavioral analysis and neurochemical determinations, that ketamine interferes with the behavioral expression of fear and with normal fear processing in the amygdala and related brain regions. We further show that the atypical antipsychotic drug clozapine, but not the typical antipsychotic haloperidol nor an experimental glutamate receptor 2/3 agonist, inhibits ketamine's effects and retains normal fear processing in the amygdala at a neurochemical level, despite the observation that fear-related behavior is still inhibited due to ketamine administration. Our results suggest that the relative resistance of emotional blunting to drug treatment may be partially due to an inability of conventional therapies to target the multiple anatomical and functional brain systems involved in emotional processing. A conceptual model reconciling our findings in terms of neurochemistry and behavior is postulated and discussed

Chromatic aberration and the roles of double-opponent and color-luminance neurons in color vision

How does the visual cortex encode color? I summarize a theory in which cortical double-opponent color neurons perform a role in color constancy and a complementary set of color-luminance neurons function to selectively correct for color fringes induced by chromatic aberration in the eye. The theory may help to resolve an ongoing debate concerning the functional properties of cortical receptive fields involved in color coding. (c) 2006 Elsevier Ltd. All rights reserved

A unified account of perceptual layering and surface appearance in terms of gamut relativity.

When we look at the world--or a graphical depiction of the world--we perceive surface materials (e.g. a ceramic black and white checkerboard) independently of variations in illumination (e.g. shading or shadow) and atmospheric media (e.g. clouds or smoke). Such percepts are partly based on the way physical surfaces and media reflect and transmit light and partly on the way the human visual system processes the complex patterns of light reaching the eye. One way to understand how these percepts arise is to assume that the visual system parses patterns of light into layered perceptual representations of surfaces, illumination and atmospheric media, one seen through another. Despite a great deal of previous experimental and modelling work on layered representation, however, a unified computational model of key perceptual demonstrations is still lacking. Here we present the first general computational model of perceptual layering and surface appearance--based on a boarder theoretical framework called gamut relativity--that is consistent with these demonstrations. The model (a) qualitatively explains striking effects of perceptual transparency, figure-ground separation and lightness, (b) quantitatively accounts for the role of stimulus- and task-driven constraints on perceptual matching performance, and (c) unifies two prominent theoretical frameworks for understanding surface appearance. The model thereby provides novel insights into the remarkable capacity of the human visual system to represent and identify surface materials, illumination and atmospheric media, which can be exploited in computer graphics applications