Motion-Defined Form Perception in Deprivation Amblyopia.

Purpose: The purpose of this study was to assess motion-defined form perception, including the association with clinical and sensory factors that may drive performance, in each eye of children with deprivation amblyopia due to unilateral cataract. Methods: Coherence thresholds for orientation discrimination of motion-defined form were measured using a staircase procedure in 30 children with deprivation amblyopia and 59 age-matched controls. Visual acuity, stereoacuity, fusion, and interocular suppression were also measured. Fixation stability and fellow-eye global motion thresholds were measured in a subset of children. Results: Motion-defined form coherence thresholds were elevated in 90% of children with deprivation amblyopia when viewing with the amblyopic eye and in 40% when viewing with the fellow eye. The deficit was similar in children with a cataract that had been visually significant at birth (congenital) and in children for whom the cataract appeared later in infancy or childhood (developmental). Poorer motion-defined form perception in amblyopic eyes was associated with poorer visual acuity, poorer binocular function, greater interocular suppression, and the presence of nystagmus. Fellow-eye deficits were not associated with any of these factors, but a temporo-nasal asymmetry for global motion perception in favor of nasalward motion suggested a general disruption in motion perception. Conclusions: Deficits in motion-defined form perception are common in children with deprivation amblyopia and may reflect a problem in motion processing that relies on binocular mechanisms.

Toward a theory of perspective perception in pictures.

This paper reviews projection models and their perception in realistic pictures, and proposes hypotheses for three-dimensional (3D) shape and space perception in pictures. In these hypotheses, eye fixations, and foveal vision play a central role. Many past theories and experimental studies focus solely on linear perspective. Yet, these theories fail to explain many important perceptual phenomena, including the effectiveness of nonlinear projections. Indeed, few classical paintings strictly obey linear perspective, nor do the best distortion-avoidance techniques for wide-angle computational photography. The hypotheses here employ a two-stage model for 3D human vision. When viewing a picture, the first stage perceives 3D shape for the current gaze. Each fixation has its own perspective projection, but, owing to the nature of foveal and peripheral vision, shape information is obtained primarily for a small region of the picture around the fixation. As a viewer moves their eyes, the second stage continually integrates some of the per-gaze information into an overall interpretation of a picture. The interpretation need not be geometrically stable or consistent over time. It is argued that this framework could explain many disparate pictorial phenomena, including different projection styles throughout art history and computational photography, while being consistent with the constraints of human 3D vision. The paper reviews open questions and suggests new studies to explore these hypotheses.

Subicular neurons encode concave and convex geometries.

Animals in the natural world constantly encounter geometrically complex landscapes. Successful navigation requires that they understand geometric features of these landscapes, including boundaries, landmarks, corners and curved areas, all of which collectively define the geometry of the environment1-12. Crucial to the reconstruction of the geometric layout of natural environments are concave and convex features, such as corners and protrusions. However, the neural substrates that could underlie the perception of concavity and convexity in the environment remain elusive. Here we show that the dorsal subiculum contains neurons that encode corners across environmental geometries in an allocentric reference frame. Using longitudinal calcium imaging in freely behaving mice, we find that corner cells tune their activity to reflect the geometric properties of corners, including corner angles, wall height and the degree of wall intersection. A separate population of subicular neurons encode convex corners of both larger environments and discrete objects. Both corner cells are non-overlapping with the population of subicular neurons that encode environmental boundaries. Furthermore, corner cells that encode concave or convex corners generalize their activity such that they respond, respectively, to concave or convex curvatures within an environment. Together, our findings suggest that the subiculum contains the geometric information needed to reconstruct the shape and layout of naturalistic spatial environments.

Visual perception: On the trail of high-level shape aftereffects.

The representation of visual shape is a critical component of our perception of the objects around us. A new study exploited shape aftereffects to reveal the high-dimensional space of geometric features our brains use to represent shape.

Representation of Natural Contours by a Neural Population in Monkey V4.

The cortical visual area, V4, has been considered to code contours that contribute to the intermediate-level representation of objects. The neural responses to the complex contour features intrinsic to natural contours are expected to clarify the essence of the representation. To approach the cortical coding of natural contours, we investigated the simultaneous coding of multiple contour features in monkey (Macaca fuscata) V4 neurons and their population-level representation. A substantial number of neurons showed significant tuning for two or more features such as curvature and closure, indicating that a substantial number of V4 neurons simultaneously code multiple contour features. A large portion of the neurons responded vigorously to acutely curved contours that surrounded the center of classical receptive field, suggesting that V4 neurons tend to code prominent features of object contours. The analysis of mutual information (MI) between the neural responses and each contour feature showed that most neurons exhibited similar magnitudes for each type of MI, indicating that many neurons showing the responses depended on multiple contour features. We next examined the population-level representation by using multidimensional scaling analysis. The neural preferences to the multiple contour features and that to natural stimuli compared with silhouette stimuli increased along with the primary and secondary axes, respectively, indicating the contribution of the multiple contour features and surface textures in the population responses. Our analyses suggested that V4 neurons simultaneously code multiple contour features in natural images and represent contour and surface properties in population.

Exploring watercolor illusion spreading between dissected stimulus parts.

The watercolor illusion (WCI) occurs when an achromatic region is surrounded by an outer contour and inner chromatic fringe, resulting in an apparent pale tint of the same hue as the fringe. The WCI both fills in and spreads out, with the previous literature suggesting it always spreads out in the absence of an enclosing border. We examined how global stimulus configuration affects this illusion by dissecting various WCI-inducing stimuli into parts. Specifically, would color spread out of the unenclosed ends of the disconnected parts? Participants provided WCI illusion magnitude ratings and shading data indicating perceived locations of color spreading for a variety of stimulus configurations. Instead of the WCI spreading modally into the spaces between the disconnected parts, we found a global reorganization of the stimuli occurred. The dissected WCI stimuli were perceived as either amodally completed behind a white illusory surface perceptually different than the physically identical background or, as empty space between separate objects depending in part on the distance between dissected parts. This study demonstrates the WCI does not always spread outside of unenclosed borders when the global interpretation interferes with spreading. These findings highlight the importance of global configuration and perceptual organization in the WCI.

Perception of 3D shape integrates intuitive physics and analysis-by-synthesis.

Many surface cues support three-dimensional shape perception, but humans can sometimes still see shape when these features are missing-such as when an object is covered with a draped cloth. Here we propose a framework for three-dimensional shape perception that explains perception in both typical and atypical cases as analysis-by-synthesis, or inference in a generative model of image formation. The model integrates intuitive physics to explain how shape can be inferred from the deformations it causes to other objects, as in cloth draping. Behavioural and computational studies comparing this account with several alternatives show that it best matches human observers (total n = 174) in both accuracy and response times, and is the only model that correlates significantly with human performance on difficult discriminations. We suggest that bottom-up deep neural network models are not fully adequate accounts of human shape perception, and point to how machine vision systems might achieve more human-like robustness.

Interaction of contour geometry and optic flow in determining relative depth of surfaces.

Dynamic occlusion, such as the accretion and deletion of texture near a boundary, is a major factor in determining relative depth of surfaces. However, the shape of the contour bounding the dynamic texture can significantly influence what kind of 3D shape, and what relative depth, are conveyed by the optic flow. This can lead to percepts that are inconsistent with traditional accounts of shape and depth from motion, where accreting/deleting texture can indicate the figural region, and/or 3D rotation can be perceived despite the constant speed of the optic flow. This suggests that the speed profile of the dynamic texture and the shape of its bounding contours combine to determine relative depth in a way that is not explained by existing models. Here, we investigated how traditional structure-from-motion principles and contour geometry interact to determine the relative-depth interpretation of dynamic textures. We manipulated the consistency of the dynamic texture with rotational or translational motion by varying the speed profile of the texture. In Experiment 1, we used a multi-region figure-ground display consisting of regions with dots moving horizontally in opposite directions in adjacent regions. In Experiment 2, we used stimuli including two regions separated by a common border, with dot textures moving horizontally in opposite directions. Both contour geometry (convexity) and the speed profile of the dynamic dot texture influenced relative-depth judgments, but contour geometry was the stronger factor. The results underscore the importance of contour geometry, which most current models disregard, in determining depth from motion.

Modeling the Role of Contour Integration in Visual Inference.

Under difficult viewing conditions, the brain's visual system uses a variety of recurrent modulatory mechanisms to augment feedforward processing. One resulting phenomenon is contour integration, which occurs in the primary visual (V1) cortex and strengthens neural responses to edges if they belong to a larger smooth contour. Computational models have contributed to an understanding of the circuit mechanisms of contour integration, but less is known about its role in visual perception. To address this gap, we embedded a biologically grounded model of contour integration in a task-driven artificial neural network and trained it using a gradient-descent variant. We used this model to explore how brain-like contour integration may be optimized for high-level visual objectives as well as its potential roles in perception. When the model was trained to detect contours in a background of random edges, a task commonly used to examine contour integration in the brain, it closely mirrored the brain in terms of behavior, neural responses, and lateral connection patterns. When trained on natural images, the model enhanced weaker contours and distinguished whether two points lay on the same versus different contours. The model learned robust features that generalized well to out-of-training-distribution stimuli. Surprisingly, and in contrast with the synthetic task, a parameter-matched control network without recurrence performed the same as or better than the model on the natural-image tasks. Thus, a contour integration mechanism is not essential to perform these more naturalistic contour-related tasks. Finally, the best performance in all tasks was achieved by a modified contour integration model that did not distinguish between excitatory and inhibitory neurons.

Gestalt neurons and emergent properties in visual perception: A novel concept for the transformation from local to global processing.

Gestalten in visual perception are defined by emergent properties of the whole, which cannot be predicted from the sum of its parts; rather, they arise by virtue of inherent principles, the Laws of Seeing. This review attempts to assign neurophysiological correlates to select emergent properties in motion and contour perception and proposes parallels to the processing of local versus global attributes by classical versus contextual receptive fields. The aim is to identify Gestalt neurons in the visual system to account for the Laws of Seeing in causal terms and to explain "Why do things look as they do" (Koffka, 1935, p. 76).

Curvature-based interface restoration algorithm using phase-field equations.

In this study, we propose a restoration algorithm for distorted objects using a curvature-driven flow. First, we capture the convex-hull shaped contour of the distorted object using the mean curvature flow. With the supplemented mass on the captured feature, we evolve the constraint mean curvature flow to a steady state, preserving the non-distorted region. With respect to the mass, we select a restorative shape by considering the square of the curvature derivative. The Allen-Cahn and Cahn-Hilliard equations are applied to the generated restored image from the implicit curvature motions represented by the order parameter. We impose the Dirichlet boundary condition for the order parameter and the Neumann boundary for the chemical potential to fix the feature and to inherit the mass conservation, respectively. We provided examples of the restoration of half-circle and parentheses-shaped objects to reconstruct a circle shape.

Reconstructing visual illusory experiences from human brain activity.

Visual illusions provide valuable insights into the brain's interpretation of the world given sensory inputs. However, the precise manner in which brain activity translates into illusory experiences remains largely unknown. Here, we leverage a brain decoding technique combined with deep neural network (DNN) representations to reconstruct illusory percepts as images from brain activity. The reconstruction model was trained on natural images to establish a link between brain activity and perceptual features and then tested on two types of illusions: illusory lines and neon color spreading. Reconstructions revealed lines and colors consistent with illusory experiences, which varied across the source visual cortical areas. This framework offers a way to materialize subjective experiences, shedding light on the brain's internal representations of the world.

Illusory optical defocus generated by shaded surface texture.

The human visual system is tasked with the problem of extracting information about the world from images that contain a conflated mixture of environmental sources and optical artifacts generated by the focal properties of our eyes. In most contexts, our brains manage to distinguish these sources, but this is not always the case. Recent work showed that shading gradients generated by smooth three-dimensional (3D) surfaces can elicit strong illusory percepts of optical defocus1,2 - the perception of illusory blur is only eliminated when the surface appears attached to self-occluding contours3, surface discontinuities1, or sharp specular reflections1,2, which all generate sharp ('high spatial frequency') image structure. This suggests that it should also be possible to eliminate the illusory blur elicited by shaded surfaces by altering the surface geometry to include small-scale surface relief, which would also generate high-frequency image structure. We report the surprising result here that this manipulation fails to eliminate the perception of blur; the fine texture fails to perceptually 'bind' to the low-frequency image structure when there is a sufficient gap between the spatial scales of the fine and coarse surface structure. These findings suggest that discontinuous 'gaps' in the spatial scale of textures are a segmentation cue the visual system uses to extract multiple causes of image structure.

Aging and temporal integration in the visual perception of object shape.

It has been known for more than 160 years that highly occluded objects that would normally be visually unrecognizable can be successfully identified when they move. This anorthoscopic perception relies on the visual system's ability to integrate information over time to complete the perception of an entire object's shape. In this experiment, 16 younger and older adults (mean ages were 20.5 and 74.6 years, respectively) were familiarized with the (unoccluded) shapes of five naturally-shaped objects (bell peppers, Capsicum annuum) until they could be easily identified (i.e., with accuracies of at least 90 percent correct). All observers then viewed the stimulus objects anorthoscopically as they moved behind narrow slits; only small object fragments could be seen at any given time, because the objects were almost totally occluded from view. Even though the object identification performance for all observers was equivalent when whole object shapes were visible, a large age-related deficit in object identification emerged during anorthoscopic viewing such that the younger adults' identification performance was 45.4 percent higher than that of the older adults. This first ever study of aging and anorthoscopic perception demonstrates that there is an age-related deficit in performing the temporal integration needed for successful object recognition.

β1,3-galactosyltransferase on chromosome 6 is essential for the formation of Lewis a structure on N-glycan in Oryza sativa.

β1,3-galactose is the component of outer-chain elongation of complex N-glycans that, together with α1,4-fucose, forms Lewis ^a structures in plants. Previous studies have revealed that N-glycan maturation is mediated by sequential attachment of β1,3-galactose and α1,4-fucose by individual β1,3-galactosyltransferase (GalT) and α1,4-fucosyltransferase (1,4-FucT), respectively. Although GalT from several species has been studied, little information about GalT from rice is available. I therefore characterized three GalT candidate genes on different chromosomes in Oryza sativa. Seeds of rice lines that had T-DNA insertions in regions corresponding to individual putative GalT genes were obtained from a Rice Functional Genomic Express Database and plants grown until maturity. Homozygotes were selected from the next generation by genotyping PCR, and used for callus induction. Callus extracts of two independent T-DNA mutant rice which have T-DNA insertions at the same gene on chromosome 6 but in different exons showed highly reduced band intensity on a western blots using an anti-Lewis ^a antibody. Cell extracts and cultured media from suspension culture of the one of these mutant rice were further analysed by N-glycan profiling using matrix-associated laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF). Identified N-glycan species containing β1,3-galactose from both cell extracts and cultured media of knock-out mutant were less than 0.5% of total N-glycans while that of WT cells were 9.8% and 49.1%, respectively. This suggests that GalT located on rice chromosome 6 plays a major role in N-glycan galactosylation, and mutations within it lead to blockage of Lewis ^a epitope formation.

Planning to revisit: Neural activity in refixation precursors.

Eye tracking studies suggest that refixations-fixations to locations previously visited-serve to recover information lost or missed during earlier exploration of a visual scene. These studies have largely ignored the role of precursor fixations-previous fixations on locations the eyes return to later. We consider the possibility that preparations to return later are already made during precursor fixations. This process would mark precursor fixations as a special category of fixations, that is, distinct in neural activity from other fixation categories such as refixations and fixations to locations visited only once. To capture the neural signals associated with fixation categories, we analyzed electroencephalograms (EEGs) and eye movements recorded simultaneously in a free-viewing contour search task. We developed a methodological pipeline involving regression-based deconvolution modeling, allowing our analyses to account for overlapping EEG responses owing to the saccade sequence and other oculomotor covariates. We found that precursor fixations were preceded by the largest saccades among the fixation categories. Independent of the effect of saccade length, EEG amplitude was enhanced in precursor fixations compared with the other fixation categories 200 to 400 ms after fixation onsets, most noticeably over the occipital areas. We concluded that precursor fixations play a pivotal role in visual perception, marking the continuous occurrence of transitions between exploratory and exploitative modes of eye movement in natural viewing behavior.

Visual perception: Contours that crack the ambiguity conundrum.

A new study shows how the brain exploits the parts of images where surfaces curve out of view to recover both the three-dimensional shape and material properties of objects. This sheds light on a long-standing 'chicken-and-egg' problem in perception research.

What good is goodness? The effects of reference points on discrimination and categorization of shapes.

Earlier research reported a category boundary effect on perception: differences between stimuli belonging to the same category are perceived as smaller than differences between stimuli belonging to different categories even when the physical dissimilarity between the stimuli in the pairs is the same. In this article, we propose that the existence of reference points (i.e., exemplars that serve as a point of comparison) can explain the occurrence of the category boundary effect as well as the directional asymmetries in within-category pairs. We investigated how reference points influence categorization and discrimination performance, using three different tasks: categorization, successive discrimination, and similarity judgment. We used both recognizable and non-recognizable morph figures as stimuli, assuming that recognizable series have clearer reference points. We replicated the overall category boundary effect for both discrimination and similarity and show the effect's dependence on the strength of the reference points involved. The general category boundary effect is not a proper category boundary effect, however: rather than the type of stimulus pair presented (i.e., within- or between-category) one needs to take into account the distance from the reference points for each of the individual stimuli in the pair to actually predict discrimination performance and similarity judgments. These results provide evidence that reference points on a dimension and their strength have tangible consequences for how we perceive, categorize, and react to stimuli on that dimension. Moreover, our findings remind us of the danger of averaging without looking at underlying data patterns, and of the gains that can be made by seriously exploring consistent variability in extensive data sets. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The Emergence of Tuning to Global Shape Properties of Radial Frequency Patterns in the Ventral Visual Pathway.

Radial frequency (RF) patterns, created by sinusoidal modulations of a circle's radius, are processed globally when RF is low. These closed shapes therefore offer a useful way to interrogate the human visual system for global processing of curvature. RF patterns elicit greater responses than those to radial gratings in V4 and more anterior face-selective regions of the ventral visual pathway. This is largely consistent with work on nonhuman primates showing curvature processing emerges in V4, but is evident also higher up the ventral visual stream. Rather than contrasting RF patterns with other stimuli, we presented them at varied frequencies in a regimen that allowed tunings to RF to be derived from 8 human participants (3 female). We found tuning to low RF in lateral occipital areas and to some extent in V4. In a control experiment, we added a high-frequency ripple to the stimuli disrupting the local contour. Low-frequency tuning to these stimuli remained in the ventral visual stream, underscoring its role in global processing of shape curvature. We then used representational similarity analysis to show that, in lateral occipital areas, the neural representation was related to stimulus similarity, when it was computed with a model that captured how stimuli are perceived. We therefore show that global processing of shape curvature emerges in the ventral visual stream as early as V4, but is found more strongly in lateral occipital regions, which exhibit responses and representations that relate well to perception.SIGNIFICANCE STATEMENT We show that tuning to low radial frequencies, known to engage global shape processing mechanisms, was localized to lateral occipital regions. When low-level stimulus properties were accounted for such tuning emerged in V4 and LO2 in addition to the object-selective region LO. We also documented representations of global shape properties in lateral occipital regions, and these representations were predicted well by a proxy of the perceptual difference between the stimuli.

Qualitative perception of 3D shape from patterns of luminance curvature.

A new source of information is proposed for the perception of three-dimensional (3D) shape from shading that identifies surface concavities from the curvature of the luminance field. Two experiments measured the abilities of human observers to identify concavities on smoothly curved shaded surfaces depicted with several different patterns of illumination and several different material properties. Observers were required to identify any apparent concavities along designated cross sections of the depicted objects and to mark each concavity with an adjustable dot. To analyze the results, we computed both the surface curvature and the luminance curvature along each image cross section. The results revealed that most responses were in concave regions of the luminance profiles, although they were often shifted in phase relative to the curvature of the depicted surfaces. This pattern of performance was surprisingly robust over large changes in the pattern of illumination or surface material properties. Our analysis predicts that observers should make false alarm responses in regions where a luminance concavity does not correspond to a surface concavity, and our empirical results confirm that prediction.