ABSTRACT The spectral power distribution (SPD) of the light reflected from a matte surface patch in a three-dimensional complex scene depends not only on the surface reflectance of the patch but also on the SPD of the light incident on the patch. When there are multiple light sources in the scene that differ in location, SPD, and spatial extent, the SPD of the incident light depends on the location and the orientation of the patch.

When this" pacman" oscillates with a small amplitude about the axis perpendicular to its center, the physical changes in the image are limited to the right visual field. Yet, human observers perceive the entire object as oscillating, including the stationary portion in the left visual field.

Abstract Researchers studying surface color perception have typically used stimuli that consist of a small number of matte patches (real or simulated) embedded in a plane perpendicular to the line of sight (a “Mondrian,” Land & McCann, 1971). Reliable estimation of the color of a matte surface is a difficult if not impossible computational problem in such limited scenes (Maloney, 1999).

PURPOSE We aimed to investigate white matter diffusivity abnormalities in hereditary spastic paraplegia with thin corpus callosum (HSP-TCC) patients in relation with electrophysiological findings. MATERIALS AND METHODS Brain magnetic resonance imaging (MRI) and diffusion tensor imaging were performed on four HSP-TCC patients and 15 age-matched healthy subjects.

Motion perception of first-and second-order stimuli has been proposed to be mediated by separate mechanisms. Whereas luminance-based stimuli are analyze by energy-based motion detectors, uncertainty remains as to the mechanisms involved in the processing of second-order stimuli. The aim of this experiment was to determine the nature of mechanisms accounting for detection of fractal rotation (Benton, O'Brien & Curran, 2007) in comparison with those responsible for first-order rotation. To reproduce

Abstract. Rigidity and reflectance are key object properties, important in their own rights, and they are key properties that stratify motion reconstruction algorithms. However, the inference of rigidity and reflectance are both difficult without additional information about the object's shape, the environment, or lighting. For humans, relative motions of object and observer provides rich information about object shape, rigidity, and reflectivity.

Abstract. We propose a method for rapidly classifying surface reflectance directly from the output of spatio-temporal filters applied to an image sequence of rotating objects. Using image data from only a single frame, we compute histograms of image velocities and classify these as being generated by a specular or a diffusely reflecting object. Exploiting characteristics of material-specific image velocities we show that our classification approach can predict the reflectance of novel 3D objects, as well as human perception.

Abstract Previous research on surface color perception has typically used Mondrian stimuli consisting of a small number of matte surface patches in a plane perpendicular to the line of sight. In such scenes, reliable estimation of the color of a surface is a difficult if not impossible computational problem (Maloney, 1999). In three-dimensional scenes consisting of surfaces at many different orientations it is at least in theory possible to estimate surface color.

In complex scenes, the light absorbed and re-emitted by one surface can serve as a source of illumination for a second. We examine whether observers systematically discount this secondary illumination when estimating surface color. We asked six naïve observers to make achromatic settings of a small test patch adjacent to a brightly colored orange cube in rendered scenes. The orientation of the test patch with respect to the cube was varied from trial to trial, altering the amount of secondary illumination reaching the test patch. Observers systematically took orientation into account in making their settings, discounting the added secondary illumination more at orientations where it was more intense. Overall, they tended to under-compensate for the added secondary illumination.

We examined the effect of perceived orientation on the perceived color of matte surfaces in rendered three-dimensional scenes illuminated by a blue diffuse light and a yellow punctate light. On each trial, observers first adjusted the color of a matte test patch, placed near the center of the scene, until it appeared achromatic, and then estimated its orientation by adjusting a monocular gradient probe. The orientation of the test patch was varied from trial to trial by the experimental program, effectively varying the chromaticity of the light mixture from the two light sources that would be absorbed and reemitted by a neutral test patch. We found that observers' achromatic settings varied with perceived orientation but that observers only partially discounted orientation in making achromatic settings. We developed an equivalent illuminant model for our task in which we assumed that observers discount orientation using possibly erroneous estimates of the chromaticities of the light sources and/or their spatial distribution. We found that the observers' failures could be explained by two factors: errors in estimating the direction to the punctate light source and errors in estimating the chromaticities of the two light sources. We discuss the pattern of errors in estimating these factors across observers.

In the present study we used a hue scaling technique to examine human color constancy performance in simulated three-dimensional scenes. These scenes contained objects of various shape and materials and a matte test patch at the center of the scene.

Many critical perceptual judgments, from telling whether fruit is ripe, to determining whether the ground is slippery, involve estimating the material properties of surfaces. Very little is known about how the brain recognizes materials, even though the problem is likely as important for survival as navigating or recognizing objects. Though previous research has focused nearly exclusively on the properties of static images , recent evidence suggests that motion may affect the appearance of surface material . However, what kind of information motion conveys and how this information may be used by the brain is still unknown. Here, we have identified three motion cues that the brain could rely on to distinguish between matte and shiny surfaces. We show that these motion measurements can override static cues, leading to dramatic changes in perceived material depending on the image motion characteristics. A classifier algorithm based on these cues correctly predicts both successes and some striking failures of human material perception. Together these results reveal a previously unknown use for optic flow in the perception of surface material properties.

Expectations and prior knowledge strongly affect and even shape our visual perception. Specifically, valid expectations speed up perceptual decisions, and determine what we see in a noisy stimulus. Bayesian models have been remarkably successful to capture the behavioral effects of expectation. On the other hand several more mechanistic neural models have also been put forward, which will be referred as “predictive computation models” here. Both Bayesian and predictive computation models treat perception as a probabilistic inference process, and combine prior information and sensory input. Despite the well-established effects of expectation on recognition or decision-making, its effects on low-level visual processing, and the computational mechanisms underlying those effects remain elusive. Here we investigate how expectations affect early visual processing at the threshold level. Specifically, we measured temporal thresholds (shortest duration of presentation to achieve a certain success level) for detecting the spatial location of an intact image, which could be either a house or a face image. Task-irrelevant cues provided prior information, thus forming an expectation, about the category of the upcoming intact image. The validity of the cue was set to 100, 75 and 50% in different experimental sessions. In a separate session the cue was neutral and provided no information about the category of the upcoming intact image. Our behavioral results showed that valid expectations do not reduce temporal thresholds, rather violation of expectation increases the thresholds specifically when the expectation validity is high. Next, we implemented a recursive Bayesian model, in which the prior is first set using the validity of the specific experimental condition, but in subsequent iterations it is updated using the posterior of the previous iteration. Simulations using the model showed that the observed increase of the temporal thresholds in the unexpected trials is not due to a change in the internal parameters of the system (e.g. decision threshold or internal uncertainty). Rather, further processing is required for a successful detection when the expectation and actual input disagree. These results reveal some surprising behavioral effects of expectation at the threshold level, and show
that a simple parsimonious computational model can successfully predict those effects.

The occipital lobe contains a substantial part of the neural machinery involved in visual perception. Mutations in the LAMC3 gene have recently been shown to cause complex bilateral occipital cortical gyration abnormalities. However, to what extent these structural changes impact visual behavior is not known. We recorded responses for two screening test batteries targeting visual function (Leuven - Perceptual Organization Screening Test, Cortical Vision Screening Test) and measured eye fixation performance in a visual attention experiment from a patient with homozygous LAMC3 gene mutation. Using voxel-based morphometry (VBM) we quantitatively assessed the extent of structural changes brought on by the genetic mutation by comparing mean cortical curvature, cortical thickness, and gray matter volume in 34 cortical areas between patient and an age-, sex-, and education-matched control group. Anatomical connectivity between these cortical areas was investigated by a structural covarianc...

Expectations and prior knowledge strongly affect and even shape our visual perception. Specifically, valid expectations speed up perceptual decisions, and determine what we see in a noisy stimulus. Bayesian models have been remarkably successful to capture the behavioral effects of expectation. On the other hand several more mechanistic neural models have also been put forward, which will be referred as 'predictive computation models' here. Both Bayesian and predictive computation models treat perception as a probabilistic inference process, and combine prior information and sensory input. Despite the well-established effects of expectation on recognition or decision-making, its effects on low-level visual processing, and the computational mechanisms underlying those effects remain elusive. Here we investigate how expectations affect early visual processing at the threshold level. Specifically, we measured temporal thresholds (shortest duration of presentation to achieve a c...

The effect of prior knowledge and expectations on perceptual and decision-making processes have been extensively studied. Yet, the computational mechanisms underlying those effects have been a controversial issue. Recently, using a recursive Bayesian updating scheme, unmet expectations have been shown to entail further computations, and consequently delay perceptual processes. Here we take a step further and model these empirical findings with a recurrent cortical model, which was previously suggested to approximate Bayesian inference (Heeger, 2017). Our model fitting results show that the cortical model can successfully predict the behavioral effects of expectation. That is, when the actual sensory input does not match with the expectations, the sensory process needs to be completed with additional, and consequently longer, computations. We suggest that this process underlies the delay in perceptual thresholds in unmet expectations. Overall our findings demonstrate that a parsimoni...