The 3D LAMINART neural model is developed to explain how the visual cortex gives rise to 3D percepts of stratification, transparency, and neon color spreading in response to 2D pictures and 3D scenes. Such percepts are sensitive to whether contiguous image regions have the same contrast polarity and ocularity. The model predicts how like-polarity competition at V1 simple cells in layer 4 may cause these percepts when it interacts with other boundary and surface processes in V1, V2, and V4. The model also explains how: the Metelli Rules cause transparent percepts, bistable transparency percepts arise, and attention influences transparency reversal.

Most people see movement in Figure 1, although the image is static. Motion is seen from black 3 blue 3 white 3 yellow 3 black. Many hypotheses for the illusory motion have been proposed, although none have been tested physiologically. We found that the illusion works well even if it is achromatic: yellow is replaced with light gray, and blue is replaced with dark gray. We show that the critical feature for inducing illusory motion is the luminance relationship of the static elements. Illusory motion is seen from black 3 dark gray 3 white 3 light gray 3 black. In psychophysical experiments, we found that all four pairs of adjacent elements when presented alone each produced illusory motion consistent with the original illusion, a result not expected from any current models. We also show that direction-selective neurons in macaque visual cortex gave directional responses to the same static element pairs, also in a direction consistent with the illusory motion. This is the first demonstration of directional responses by single neurons to static displays and supports a model in which low-level, first-order motion detectors interpret contrast-dependent differences in response timing as motion. We demonstrate that this illusion is a static version of four-stroke apparent motion.

The goal of this study was to investigate how cognitive factors influence performance in a multi-talker, “cocktail-party” like environment in musicians and non-musicians. This was achieved by relating performance in a spatial hearing task to cognitive processing abilities assessed using measures of executive function (EF) and visual attention in musicians and non-musicians. For the spatial hearing task, a speech target was presented simultaneously with two intelligible speech maskers that were either colocated with the target (0° azimuth) or were symmetrically separated from the target in azimuth (at ±15°). EF assessment included measures of cognitive flexibility, inhibition control and auditory working memory. Selective attention was assessed in the visual domain using a multiple object tracking task (MOT). For the MOT task, the observers were required to track target dots (n = 1,2,3,4,5) in the presence of interfering distractor dots. Musicians performed significantly better than non-musicians in the spatial hearing task. For the EF measures, musicians showed better performance on measures of auditory working memory compared to non-musicians. Furthermore, across all individuals, a significant correlation was observed between performance on the spatial hearing task and measures of auditory working memory. This result suggests that individual differences in performance in a cocktail party-like environment may depend in part on cognitive factors such as auditory working memory. Performance in the MOT task did not differ between groups. However, across all individuals, a significant correlation was found between performance in the MOT and spatial hearing tasks. A stepwise multiple regression analysis revealed that musicianship and performance on the MOT task significantly predicted performance on the spatial hearing task. Overall, these findings confirm the relationship between musicianship and cognitive factors including domain-general selective attention and working memory in solving the “cocktail party problem”.

The watercolor effect (WCE) is a filling-in phenomenon in a region demarcated by two thin abutting lines. The perceived chromaticity of the region is similar to that of the interior line. We develop a series of achromatic WCE stimuli to induce lightness changes analogous to the induced chromaticity in the chromatic version of the WCE. We use a variation of the paired-comparison paradigm to quantify the induced lightness of the filled-in regions to regions with real luminance variations. The luminance of the inner line is fixed, while the luminance of the outer line varies across stimuli. Data from seven subjects (five naive) confirm that an achromatic WCE exists. Moreover, outer lines with both high and low luminances can generate a WCE with an inner line of a moderate luminance. All subjects show a single peak of the effect strength for both polarity conditions, which is never at the extreme luminance levels. Most subjects show an inverted U curve for effect strength as a function of the contrast of the outer lines against the background. Results suggest that the contrast difference between the outer line and the inner line affects the existence and the strength of the achromatic WCE in a nonlinear way.

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Under natural viewing conditions, a single depthful percept of the world is consciously seen. When dissimilar images are presented to corresponding regions of the two eyes, binocular rivalry may occur, during which the brain consciously perceives alternating percepts through time. How do the same brain mechanisms that generate a single depthful percept of the world also cause perceptual bistability, notably binocular rivalry? What properties of brain representations correspond to consciously seen percepts? A laminar cortical model of how cortical areas V1, V2, and V4 generate depthful percepts is developed to explain and quantitatively simulate binocular rivalry data. The model proposes how mechanisms of cortical development, perceptual grouping, and figure-ground perception lead to single and rivalrous percepts. Quantitative model simulations of perceptual grouping circuits demonstrate influences of contrast changes that are synchronized with switches in the dominant eye percept, gamma distribution of dominant phase durations, piecemeal percepts, and coexistence of eye-based and stimulus-based rivalry. The model as a whole also qualitatively explains data about the involvement of multiple brain regions in rivalry, the effects of object attention on switching between superimposed transparent surfaces, monocular rivalry, Marroquin patterns, the spread of suppression during binocular rivalry, binocular summation, fusion of dichoptically presented orthogonal gratings, general suppression during binocular rivalry, and pattern rivalry. These data explanations follow from model brain mechanisms that assure non-rivalrous conscious percepts.

Humans are capable of rapidly determining whether regions in a visual scene appear as figures in the foreground or as background, yet how figure-ground segregation occurs in the primate visual system is unknown. Figures in the environment are perceived to own their borders, and recent neurophysiology has demonstrated that certain cells in primate visual area V2 have border-ownership selectivity. We present a dynamic model based on physiological data that indicates areas V1, V2, and V4 act as an interareal network to determine border-ownership. Our model predicts that competition between curvature- sensitive cells in V4 that have on-surround receptive fields of different sizes can determine likely figure locations and rapidly propagate the information interareally to V2 border-ownership cells that receive contrast information from V1. In the model border-ownership is an emergent property produced by the dynamic interactions between V1, V2, and V4, one which could not be determined by any single cortical area alone.

Common situations that result in different perceptions of grouping and border ownership, such as shadows and occlusion, have distinct sign-of-contrast relationships at their edge-crossing junctions. Here we report a property of end stopping in V1 that distinguishes among different sign-of-contrast situations, thereby obviating the need for explicit junction detectors. We show that the inhibitory effect of the end zones in end-stopped cells is highly selective for the relative sign of contrast between the central activating stimulus and stimuli presented at the end zones. Conversely, the facilitatory effect of end zones in length-summing cells is not selective for the relative sign of contrast between the central activating stimulus and stimuli presented at the end zones. This finding indicates that end stopping belongs in the category of cortical computations that are selective for sign of contrast, such as direction selectivity and disparity selectivity, but length summation does not.Vision is an active integrative process: information from one part of the scene can drive the interpretation of features in other parts 1 . The information in an image is concentrated at contours and terminations 2 . Line ends, corners and junctions are singularities that are crucial for form perception, object recognition, depth ordering and motion processing (refs. 1 ,3-7 ). The physiological correlates of the perceptual phenomena of terminator detection and contour completion must begin with the well-known single-cell physiological properties of end stopping and length summation. Selective responsiveness to terminators (by end-stopped cells) probably provides the initial step both in depth ordering of contours and surfaces, and in solving the aperture problem for stereo and motion 8-10 . Similarly, the physiological property of length summation must provide the initial step in the process of contour integration.To identify correctly the end of a contour, the brain must ignore changes in contrast caused by nonuniform illumination and respond only to those changes caused by the ending of the contour. Contrast polarity can be used to differentiate between these situations. If a change in contrast is due to an alteration in illumination, such as a shadow, then contrast polarity will be preserved along the contour. Conversely, contrast polarity inversion along a contour usually signals the end of the contour. Many instances of surface stratification and border ownership, such as shadow, transparency, occlusion and neon color spreading, have different ordinal contrast configurations at T and X junctions (Fig. 1). A long-standing issue is how the visual cortex uses contrast information to distinguish among different ordinal relations within these junctional singularities. Are there explicit junction detectors in the visual cortex?Although, perceptually, sign-of-contrast information at junctions is crucial, it is generally assumed that by the complex-cell stage of V1 information about sign of contrast has been pooled 11 and is t...