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Articles by Daniel Kersten in JoVE

 JoVE Neuroscience

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

1Brain and Behavior Discovery Institute, Georgia Health Sciences University, 2Vision Discovery Institute, Georgia Health Sciences University, 3Department of Opthalmology, Georgia Health Sciences University, 4Intelligent Systems Laboratory, Palo Alto Research Center, 5Pattern Recognition Systems, Palo Alto Research Center, 6Department of Psychology, University of Minnesota


JoVE 3358

We describe a novel methodology for creating naturalistic 3-D objects and object categories with precisely defined feature variations. We use simulations of the biological processes of morphogenesis and phylogenesis to create novel, naturalistic virtual 3-D objects and object categories that can then be rendered as visual images or haptic objects.

Other articles by Daniel Kersten on PubMed

Illusions, Perception and Bayes

Shape Perception Reduces Activity in Human Primary Visual Cortex

Visual perception involves the grouping of individual elements into coherent patterns that reduce the descriptive complexity of a visual scene. The physiological basis of this perceptual simplification remains poorly understood. We used functional MRI to measure activity in a higher object processing area, the lateral occipital complex, and in primary visual cortex in response to visual elements that were either grouped into objects or randomly arranged. We observed significant activity increases in the lateral occipital complex and concurrent reductions of activity in primary visual cortex when elements formed coherent shapes, suggesting that activity in early visual areas is reduced as a result of grouping processes performed in higher areas. These findings are consistent with predictive coding models of vision that postulate that inferences of high-level areas are subtracted from incoming sensory information in lower areas through cortical feedback.

Bayesian Models of Object Perception

The human visual system is the most complex pattern recognition device known. In ways that are yet to be fully understood, the visual cortex arrives at a simple and unambiguous interpretation of data from the retinal image that is useful for the decisions and actions of everyday life. Recent advances in Bayesian models of computer vision and in the measurement and modeling of natural image statistics are providing the tools to test and constrain theories of human object perception. In turn, these theories are having an impact on the interpretation of cortical function.

Three-dimensional Symmetric Shapes Are Discriminated More Efficiently Than Asymmetric Ones

Objects with bilateral symmetry, such as faces, animal shapes, and many man-made objects, play an important role in everyday vision. Because they occur frequently, it is reasonable to conjecture that the brain may be specialized for symmetric objects. We investigated whether the human visual system processes three-dimensional (3D) symmetric objects more efficiently than asymmetric ones. Human subjects, having learned a symmetric wire object, discriminated which of two distorted copies of the learned object was more similar to the learned one. The distortion was achieved by adding 3D Gaussian positional perturbations at the vertices of the wire object. In the asymmetric condition, the perturbation was independent from one vertex to the next. In the symmetric condition, independent perturbations were added to only half of the object; perturbations on the other half retained the symmetry of the object. We found that subjects' thresholds were higher in the symmetric condition. However, since the perturbation in the symmetric condition was correlated, a stimulus image provided less information in the symmetric condition. Taking this in to consideration, an ideal-observer analysis revealed that subjects were actually more efficient at discriminating symmetric objects. This reversal in interpretation underscores the importance of ideal-observer analysis. A completely opposite, and wrong, conclusion would have been drawn from analyzing only human discrimination thresholds. Given the same amount of information, the visual system is actually better able to discriminate symmetric objects than asymmetric ones.

Is Color an Intrinsic Property of Object Representation?

The role of color in object representation was examined by using a variation of the Stroop paradigm in which observers named the displayed colors of objects or words. In experiment 1, colors of color-diagnostic objects were manipulated to be either typical or atypical of the object (eg a yellow banana versus a purple banana). A Stroop-like effect was obtained, with faster color-naming times for the typical as compared to the atypical condition. In experiment 2, naming colors on words specifying these same color-diagnostic objects reversed this pattern, with the typical condition producing longer response times than the atypical condition. In experiment 3, a blocked condition design that used the same words and colors as experiment 2 produced the standard Stroop-like facilitation for the typical condition. These results indicate that color is an intrinsic property of an object's representation at multiple levels. In experiment 4, we examined the specific level(s) at which color-shape associations arise by following the tasks used in experiments 1 and 2 with a lexical-decision task in which some items were conceptually related to items shown during color naming (eg banana/monkey). Priming for these associates was observed following color naming of words, but not pictures, providing further evidence that the color-shape associations responsible for the differing effects obtained in experiments 1 and 2 are due to the automatic activation of color-shape associations at different levels of representation.

Bootstrapped Learning of Novel Objects

Recognition of familiar objects in cluttered backgrounds is a challenging computational problem. Camouflage provides a particularly striking case, where an object is difficult to detect, recognize, and segment even when in "plain view." Current computational approaches combine low-level features with high-level models to recognize objects. But what if the object is unfamiliar? A novel camouflaged object poses a paradox: A visual system would seem to require a model of an object's shape in order to detect, recognize, and segment it when camouflaged. But, how is the visual system to build such a model of the object without easily segmentable samples? One possibility is that learning to identify and segment is opportunistic in the sense that learning of novel objects takes place only when distinctive clues permit object segmentation from background, such as when target color or motion enables segmentation on single presentations. We tested this idea and discovered that, on the contrary, human observers can learn to identify and segment a novel target shape, even when for any given training image the target object is camouflaged. Further, perfect recognition can be achieved without accurate segmentation. We call the ability to build a shape model from high-ambiguity presentations bootstrapped learning.

Visuomotor Sensitivity to Visual Information About Surface Orientation

We measured human visuomotor sensitivity to visual information about three-dimensional surface orientation by analyzing movements made to place an object on a slanted surface. We applied linear discriminant analysis to the kinematics of subjects' movements to surfaces with differing slants (angle away form the fronto-parallel) to derive visuomotor d's for discriminating surfaces differing in slant by 5 degrees. Subjects' visuomotor sensitivity to information about surface orientation was very high, with discrimination "thresholds" ranging from 2 to 3 degrees. In a first experiment, we found that subjects performed only slightly better using binocular cues alone than monocular texture cues and that they showed only weak evidence for combining the cues when both were available, suggesting that monocular cues can be just as effective in guiding motor behavior in depth as binocular cues. In a second experiment, we measured subjects' perceptual discrimination and visuomotor thresholds in equivalent stimulus conditions to decompose visuomotor sensitivity into perceptual and motor components. Subjects' visuomotor thresholds were found to be slightly greater than their perceptual thresholds for a range of memory delays, from 1 to 3 s. The data were consistent with a model in which perceptual noise increases with increasing delay between stimulus presentation and movement initiation, but motor noise remains constant. This result suggests that visuomotor and perceptual systems rely on the same visual estimates of surface slant for memory delays ranging from 1 to 3 s.

Object Perception As Bayesian Inference

We perceive the shapes and material properties of objects quickly and reliably despite the complexity and objective ambiguities of natural images. Typical images are highly complex because they consist of many objects embedded in background clutter. Moreover, the image features of an object are extremely variable and ambiguous owing to the effects of projection, occlusion, background clutter, and illumination. The very success of everyday vision implies neural mechanisms, yet to be understood, that discount irrelevant information and organize ambiguous or noisy local image features into objects and surfaces. Recent work in Bayesian theories of visual perception has shown how complexity may be managed and ambiguity resolved through the task-dependent, probabilistic integration of prior object knowledge with image features.

BOLD FMRI and Psychophysical Measurements of Contrast Response to Broadband Images

We have measured the relationship between image contrast, perceived contrast, and BOLD fMRI activity in human early visual areas, for natural, whitened, pink noise, and white noise images. As root-mean-square contrast increases, BOLD response to natural images is stronger and saturates more rapidly than response to the whitened images. Perceived contrast and BOLD fMRI responses are higher for pink noise than for white noise patterns, by the same ratio as between natural and whitened images. Spatial phase structure has no measurable effect on perceived contrast or BOLD fMRI response. The fMRI and perceived contrast response results can be described by models of spatial frequency response in V1, that match the contrast sensitivity function at low contrasts, and have more uniform spatial frequency response at high contrasts.

Perceptual Grouping and the Interactions Between Visual Cortical Areas

Visual perception involves the grouping of individual elements into coherent patterns, such as object representations, that reduce the descriptive complexity of a visual scene. The computational and physiological bases of this perceptual remain poorly understood. We discuss recent fMRI evidence from our laboratory where we measured activity in a higher object processing area (LOC), and in primary visual cortex (V1) in response to visual elements that were either grouped into objects or randomly arranged. We observed significant activity increases in the LOC and concurrent reductions of activity in V1 when elements formed coherent shapes, suggesting that activity in early visual areas is reduced as a result of grouping processes performed in higher areas. In light of these results we review related empirical findings of context-dependent changes in activity, recent neurophysiology research related to cortical feedback, and computational models that incorporate feedback operations. We suggest that feedback from high-level visual areas reduces activity in lower areas in order to simplify the description of a visual image-consistent with both predictive coding models of perception and probabilistic notions of 'explaining away.'

Is Prior Knowledge of Object Geometry Used in Visually Guided Reaching?

We investigated whether humans use prior knowledge of the geometry of faces in visually guided reaching. When viewing the inside of a mask of a face, the mask is often perceived as being a normal (convex) face, instead of the veridical, hollow (concave) shape. In this "hollow-face illusion," prior knowledge of the shape of faces dominates perception, even when in conflict with information from binocular disparity. Computer images of normal and hollow faces were presented, such that depth information from binocular disparity was consistent or in conflict with prior knowledge of the geometry. Participants reached to touch either the nose or cheek of the faces or gave verbal estimates of the corresponding distances. We found that reaching to touch was dominated by prior knowledge of face geometry. However, hollow faces were estimated to be flatter than normal faces. This suggests that the visual system combines binocular disparity and prior assumptions, rather than completely discounting one or the other. When comparing the magnitude of the hollow-face illusion in reaching and verbal tasks, we found that the flattening effect of the illusion was similar for verbal and reaching tasks.

Orientation-tuned FMRI Adaptation in Human Visual Cortex

Adaptation is a general property of almost all neural systems and has been a longstanding tool of psychophysics because of its power to isolate and temporarily reduce the contribution of specific neural populations. Recently, adaptation designs have been extensively applied in functional MRI (fMRI) studies to infer neural selectivity in specific cortical areas. However, there has been considerable variability in the duration of adaptation used in these experiments. In particular, although long-term adaptation has been solidly established in psychophysical and neurophysiological studies, it has been incorporated into few fMRI studies. Furthermore, there has been little validation of fMRI adaptation using stimulus dimensions with well-known adaptive properties (e.g., orientation) and in better understood regions of cortex (e.g., primary visual cortex, V1). We used an event-related fMRI experiment to study long-term orientation adaptation in the human visual cortex. After long-term adaptation to an oriented pattern, the fMRI response in V1, V2, V3/VP, V3A, and V4 to a test stimulus was proportional to the angular difference between the adapting and test stimuli. However, only V3A and V4 showed this response pattern with short-term adaptation. In a separate experiment, we measured behavioral contrast detection thresholds after adaptation and found that the fMRI signal in V1 closely matched the psychophysically derived contrast detection thresholds. Similar to the fMRI results, adaptation induced threshold changes strongly depended on the duration of adaptation. In addition to supporting the existence of adaptable orientation-tuned neurons in human visual cortex, our results show the importance of considering timing parameters in fMRI adaptation experiments.

Spatially Specific FMRI Repetition Effects in Human Visual Cortex

The functional MRI (fMRI) response to a pair of identical, successively presented stimuli can result in a smaller signal than the presentation of two nonidentical stimuli. This "repetition effect" has become a frequently used tool to make inferences about neural selectivity in specific cortical areas. However, little is known about the mechanism(s) underlying the effect. In particular, despite many successful applications of the technique in higher visual areas, repetition effects in lower visual areas [e.g., primary visual cortex (V1)] have been more difficult to characterize. One property that is well understood in early visual areas is the mapping of visual field locations to specific areas of the cortex (i.e., retinotopy). We used the retinotopic organization of V1 to activate progressively different populations of neurons in a rapid fMRI experimental design. We observed a repetition effect (reduced signal) when localized stimulus elements were repeated in identical locations. We show that this effect is spatially tuned and largely independent of both interstimulus interval (100-800 ms) and the focus of attention. Using the same timing parameters for which we observed a large effect of spatial position, we also examined the response to orientation changes and observed no effect of an orientation change on the response to repeated stimuli in V1 but significant effects in other retinotopic areas. Given these results, we discuss the possible causes of these repetition effects as well as the implications for interpreting other experiments that use this potentially powerful imaging technique.

The Representation of Perceived Angular Size in Human Primary Visual Cortex

Two objects that project the same visual angle on the retina can appear to occupy very different proportions of the visual field if they are perceived to be at different distances. What happens to the retinotopic map in primary visual cortex (V1) during the perception of these size illusions? Here we show, using functional magnetic resonance imaging (fMRI), that the retinotopic representation of an object changes in accordance with its perceived angular size. A distant object that appears to occupy a larger portion of the visual field activates a larger area in V1 than an object of equal angular size that is perceived to be closer and smaller. These results demonstrate that the retinal size of an object and the depth information in a scene are combined early in the human visual system.

Vision As Bayesian Inference: Analysis by Synthesis?

We argue that the study of human vision should be aimed at determining how humans perform natural tasks with natural images. Attempts to understand the phenomenology of vision from artificial stimuli, although worthwhile as a starting point, can lead to faulty generalizations about visual systems, because of the enormous complexity of natural images. Dealing with this complexity is daunting, but Bayesian inference on structured probability distributions offers the ability to design theories of vision that can deal with the complexity of natural images, and that use 'analysis by synthesis' strategies with intriguing similarities to the brain. We examine these strategies using recent examples from computer vision, and outline some important implications for cognitive science.

Responses to Lightness Variations in Early Human Visual Cortex

Lightness is the apparent reflectance of a surface, and it depends not only on the actual luminance of the surface but also on the context in which the surface is viewed [1-10]. The cortical mechanisms of lightness processing are largely unknown, and the role of early cortical areas is still a matter of debate [11-17]. We studied the cortical responses to lightness variations in early stages of the human visual system with functional magnetic resonance imaging (fMRI) while observers were performing a demanding fixation task. The set of dynamically presented visual stimuli included the rectangular version of the classic Craik-O'Brien stimulus [3, 18, 19] and a variant that led to a weaker lightness effect, as well as a pattern with actual luminance variations. We found that the cortical activity in retinotopic areas, including the primary visual cortex (V1), is correlated with context-dependent lightness variations.

Fragment-based Learning of Visual Object Categories

When we perceive a visual object, we implicitly or explicitly associate it with a category we know. It is known that the visual system can use local, informative image fragments of a given object, rather than the whole object, to classify it into a familiar category. How we acquire informative fragments has remained unclear. Here, we show that human observers acquire informative fragments during the initial learning of categories. We created new, but naturalistic, classes of visual objects by using a novel "virtual phylogenesis" (VP) algorithm that simulates key aspects of how biological categories evolve. Subjects were trained to distinguish two of these classes by using whole exemplar objects, not fragments. We hypothesized that if the visual system learns informative object fragments during category learning, then subjects must be able to perform the newly learned categorization by using only the fragments as opposed to whole objects. We found that subjects were able to successfully perform the classification task by using each of the informative fragments by itself, but not by using any of the comparable, but uninformative, fragments. Our results not only reveal that novel categories can be learned by discovering informative fragments but also introduce and illustrate the use of VP as a versatile tool for category-learning research.

Preferential Responses to Occluded Objects in the Human Visual Cortex

How do we see an object when it is partially obstructed from view? The neural mechanisms of this intriguing process are unclear, in part because studies of visual object perception heretofore have largely used stimuli of individual objects, such as faces or common inanimate objects, each presented alone. But in natural images, visual objects are typically occluded by other objects. Computational studies indicate that the perception of an occluded object requires processes that are substantially different from those for an unoccluded object in plain view. We studied the neural substrates of the perception of occluded objects using functional magnetic resonance imaging (fMRI) of human subjects viewing stimuli that were designed to elicit or not elicit the percept of an occluded object but were physically very similar. We hypothesized the regions that are selective for occluded objects, if they exist, will be differentially active during the two conditions. We found two regions, one in the ventral object processing pathway and another in the dorsal object processing pathway, that were significantly responsive to occluded objects. More importantly, both regions were significantly more responsive to occluded objects than to unoccluded objects, and this enhanced response was not attributable to low-level differences in the stimuli, amodal completion per se, or the behavioral task. Our results identify regions in the visual cortex that are preferentially responsive to occluded objects relative to other stimuli tested and indicate that these regions are likely to play an important role in the perception of occluded objects.

Use of the Microscope in Endodontics: Results of a Questionnaire

The purpose of this study was to investigate the frequency and characteristics of operating microscope (OM) utilization among endodontists in the United States. The study also investigated how OM use has changed since a similar study was published nearly a decade ago. A web-based survey regarding OM usage was e-mailed to 2340 active members of the American Association of Endodontists (AAE) in the United States. Data from 1091 questionnaires indicated that 90% of the endodontists surveyed have access to and use the OM in their practice. The frequency of use as a function of years since completing endodontic training was as follows: <10 years, 95%; 10-15 years, 90%; 16-20 years, 82%; >21 years, 78%. Previous studies found that shorter operators needed to adopt a strained position to view mandibular molars. Our results indicated with strong correlation (r = 0.90) that shorter endodontists used the microscope more often than taller endodontists. The OM was used most frequently for root-end inspection, locating canal orifices, and root-end filling, respectively. Of the practitioners who used the OM, 59% used it without limitation, 86% used it equally between the maxillary and mandibular arch, and 84% used it as often as anticipated. The most common limitations to OM use were positional difficulty, limited field of view, and inconvenience, respectfully. The use of the OM by endodontists increased from 52% in 1999 to 90% in 2007.

Attention-dependent Representation of a Size Illusion in Human V1

One of the most fundamental properties of human primary visual cortex (V1) is its retinotopic organization, which makes it an ideal candidate for encoding spatial properties, such as size, of objects. However, three-dimensional (3D) contextual information can lead to size illusions that are reflected in the spatial pattern of activity in V1 [1]. A critical question is how complex 3D contextual information can influence spatial activity patterns in V1. Here, we assessed whether changes in the spatial distribution of activity in V1 depend on the focus of attention, which would be suggestive of feedback of 3D contextual information from higher visual areas. We presented two 3D rings at close and far apparent depths in a 3D scene. When subjects fixated its center, the far ring appeared to be larger and occupy a more eccentric portion of the visual field, relative to the close ring. Using functional magnetic resonance imaging, we found that the spatial distribution of V1 activity induced by the far ring was also shifted toward a more eccentric representation of the visual field, whereas that induced by the close ring was shifted toward the foveal representation, consistent with their perceptual appearances. This effect was significantly reduced when the focus of spatial attention was narrowed with a demanding central fixation task. We reason that focusing attention on the fixation task resulted in reduced activity in--and therefore reduced feedback from--higher visual areas that process the 3D depth cues.

Perceptual Grouping and Inverse FMRI Activity Patterns in Human Visual Cortex

We used functional magnetic resonance imaging (fMRI) to measure activity in human visual cortex, including a higher object processing area, the lateral occipital complex (LOC), and primary visual cortex (V1), in response to a perceptually bistable stimulus whose elements were perceived as either grouped into a shape or randomly arranged. We found activity increases in the LOC and simultaneous reductions of activity in V1 when the elements were perceived as a coherent shape. Consistent with a number of inferential models of visual processing, our results suggest that feedback from higher visual areas to lower visual areas serves to reduce activity during perceptual grouping. The implications of these findings with respect to these models are discussed.

Border Ownership Selectivity in Human Early Visual Cortex and Its Modulation by Attention

Natural images are usually cluttered because objects occlude one another. A critical aspect of recognizing these visual objects is to identify the borders between image regions that belong to different objects. However, the neural coding of border ownership in human visual cortex is largely unknown. In this study, we designed two simple but compelling stimuli in which a slight change of contextual information could induce a dramatic change of border ownership. Using functional MRI adaptation, we found that border ownership selectivity in V2 was robust and reliable across subjects, and it was largely dependent on attention. Our study provides the first human evidence that V2 is a critical area for the processing of border ownership and that this processing depends on the modulation from higher-level cortical areas.

Ideal Observers and Efficiency: Commemorating 50 Years of Tanner and Birdsall: Introduction

Within- and Cross-modal Distance Information Disambiguate Visual Size-change Perception

Perception is fundamentally underconstrained because different combinations of object properties can generate the same sensory information. To disambiguate sensory information into estimates of scene properties, our brains incorporate prior knowledge and additional "auxiliary" (i.e., not directly relevant to desired scene property) sensory information to constrain perceptual interpretations. For example, knowing the distance to an object helps in perceiving its size. The literature contains few demonstrations of the use of prior knowledge and auxiliary information in combined visual and haptic disambiguation and almost no examination of haptic disambiguation of vision beyond "bistable" stimuli. Previous studies have reported humans integrate multiple unambiguous sensations to perceive single, continuous object properties, like size or position. Here we test whether humans use visual and haptic information, individually and jointly, to disambiguate size from distance. We presented participants with a ball moving in depth with a changing diameter. Because no unambiguous distance information is available under monocular viewing, participants rely on prior assumptions about the ball's distance to disambiguate their -size percept. Presenting auxiliary binocular and/or haptic distance information augments participants' prior distance assumptions and improves their size judgment accuracy-though binocular cues were trusted more than haptic. Our results suggest both visual and haptic distance information disambiguate size perception, and we interpret these results in the context of probabilistic perceptual reasoning.

Vision: when Does Looking Bigger Mean Seeing Better?

A recent study shows that our ability to discriminate the orientation of a visual pattern improves if the pattern appears larger.

Perceptual Grouping-dependent Lightness Processing in Human Early Visual Cortex

Lightness, the perceived relative achromatic reflectance of a surface, depends strongly on the context within which the surface is viewed. Modest changes in the two-dimensional configuration or three-dimensional scene geometry may lead to profound variations in lightness even though the surface luminance remains constant. Despite recent progress, we are far from a complete understanding of how various aspects of spatial context affect lightness processing in the cortex. Here we use a novel stimulus to show that perceptual grouping through occluders can affect lightness. We first report behavioral results showing how lightness across occlusion depends on spatially distant image features, including luminance and contrast. Next using functional magnetic resonance imaging (fMRI) we show that human early visual cortex responds strongly to occlusion-dependent lightness variations with little or no attention. These results suggest that elements of three-dimensional scene interpretation play a role in early cortical processing of lightness.

A Link Between Visual Disambiguation and Visual Memory

Sensory information in the retinal image is typically too ambiguous to support visual object recognition by itself. Theories of visual disambiguation posit that to disambiguate, and thus interpret, the incoming images, the visual system must integrate the sensory information with previous knowledge of the visual world. However, the underlying neural mechanisms remain unclear. Using functional magnetic resonance imaging (fMRI) of human subjects, we have found evidence for functional specialization for storing disambiguating information in memory versus interpreting incoming ambiguous images. Subjects viewed two-tone, "Mooney" images, which are typically ambiguous when seen for the first time but are quickly disambiguated after viewing the corresponding unambiguous color images. Activity in one set of regions, including a region in the medial parietal cortex previously reported to play a key role in Mooney image disambiguation, closely reflected memory for previously seen color images but not the subsequent disambiguation of Mooney images. A second set of regions, including the superior temporal sulcus, showed the opposite pattern, in that their responses closely reflected the subjects' percepts of the disambiguated Mooney images on a stimulus-to-stimulus basis but not the memory of the corresponding color images. Functional connectivity between the two sets of regions was stronger during those trials in which the disambiguated percept was stronger. This functional interaction between brain regions that specialize in storing disambiguating information in memory versus interpreting incoming ambiguous images may represent a general mechanism by which previous knowledge disambiguates visual sensory information.

How Haptic Size Sensations Improve Distance Perception

Determining distances to objects is one of the most ubiquitous perceptual tasks in everyday life. Nevertheless, it is challenging because the information from a single image confounds object size and distance. Though our brains frequently judge distances accurately, the underlying computations employed by the brain are not well understood. Our work illuminates these computions by formulating a family of probabilistic models that encompass a variety of distinct hypotheses about distance and size perception. We compare these models' predictions to a set of human distance judgments in an interception experiment and use Bayesian analysis tools to quantitatively select the best hypothesis on the basis of its explanatory power and robustness over experimental data. The central question is: whether, and how, human distance perception incorporates size cues to improve accuracy. Our conclusions are: 1) humans incorporate haptic object size sensations for distance perception, 2) the incorporation of haptic sensations is suboptimal given their reliability, 3) humans use environmentally accurate size and distance priors, 4) distance judgments are produced by perceptual "posterior sampling". In addition, we compared our model's estimated sensory and motor noise parameters with previously reported measurements in the perceptual literature and found good correspondence between them. Taken together, these results represent a major step forward in establishing the computational underpinnings of human distance perception and the role of size information.

Visual Motion and the Perception of Surface Material

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 identify 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.

Object Recognition in Clutter: Cortical Responses Depend on the Type of Learning

Theoretical studies suggest that the visual system uses prior knowledge of visual objects to recognize them in visual clutter, and posit that the strategies for recognizing objects in clutter may differ depending on whether or not the object was learned in clutter to begin with. We tested this hypothesis using functional magnetic resonance imaging (fMRI) of human subjects. We trained subjects to recognize naturalistic, yet novel objects in strong or weak clutter. We then tested subjects' recognition performance for both sets of objects in strong clutter. We found many brain regions that were differentially responsive to objects during object recognition depending on whether they were learned in strong or weak clutter. In particular, the responses of the left fusiform gyrus (FG) reliably reflected, on a trial-to-trial basis, subjects' object recognition performance for objects learned in the presence of strong clutter. These results indicate that the visual system does not use a single, general-purpose mechanism to cope with clutter. Instead, there are two distinct spatial patterns of activation whose responses are attributable not to the visual context in which the objects were seen, but to the context in which the objects were learned.

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