Constraints on long range interactions mediating contour detection

Performance on a contour integration task as a function of contour shape in schizophrenia and controls

Contour Integration (CI) is the ability to integrate elemental features into objects and is a basic visual process essential for object perception and recognition, and for functioning in visual environments. It is now well documented that people with schizophrenia (SZ), in addition to having cognitive impairments, also have several visual perceptual deficits, including in CI. Here, we retrospectively characterize the performance of both SZ and neurotypical individuals (NT) on a series of contour shapes, made up of Gabor elements, that varied in terms of closure and curvature. Participants in both groups performed a CI training task that included 7 different families of shapes (Lines, Ellipse, Blobs, Squiggles, Spiral, Circle and Letters) for up to 40 sessions. Two parameters were manipulated in the training task: Orientation Jitter (OJ, i.e., orientation deviations of individual Gabor elements from ideal for each shape) and Inducer Number (IN, i.e., number of Gabor elements defining the shape). Results show that both OJ and IN thresholds significantly differed between the groups, with higher (OJ) and lower (IN) thresholds observed in the controls. Furthermore, we found significant effects as a function of the contour shapes, with differences between groups emerging with contours that were considered more complex, e.g., due to having a higher degree of curvature (Blobs, Spiral, Letters). These data can inform future work that aims to characterize visual integration impairments in schizophrenia.

Classical-Contextual Interactions in V1 May Rely on Dendritic Computations

A signature feature of the neocortex is the dense network of horizontal connections (HCs) through which pyramidal neurons (PNs) exchange "contextual" information. In primary visual cortex (V1), HCs are thought to facilitate boundary detection, a crucial operation for object recognition, but how HCs modulate PN responses to boundary cues within their classical receptive fields (CRF) remains unknown. We began by "asking" natural images, through a structured data collection and ground truth labeling process, what function a V1 cell should use to compute boundary probability from aligned edge cues within and outside its CRF. The "answer" was an asymmetric 2-D sigmoidal function, whose nonlinear form provides the first normative account for the "multiplicative" center-flanker interactions previously reported in V1 neurons (Kapadia et al., 1995, 2000; Polat et al., 1998). Using a detailed compartmental model, we then show that this boundary-detecting classical-contextual interaction function can be computed by NMDAR-dependent spatial synaptic interactions within PN dendrites - the site where classical and contextual inputs first converge in the cortex. In additional simulations, we show that local interneuron circuitry activated by HCs can powerfully leverage the nonlinear spatial computing capabilities of PN dendrites, providing the cortex with a highly flexible substrate for integration of classical and contextual information.

The Contribution of Shape Features and Demographic Variables to Disembedding Abilities

Humans naturally perceive visual patterns in a global manner and are remarkably capable of extracting object shapes based on properties such as proximity, closure, symmetry, and good continuation. Notwithstanding the role of these properties in perceptual grouping, studies highlighted differences in disembedding performance across individuals, which are summarized by the field dependence dimension. Evidence suggests that age and educational attainment explain part of this variability, whereas the role of sex is still highly debated. Also, which stimulus features primarily influence inter-individual variations in perceptual grouping has still to be fully determined. Building upon these premises, we assessed the role of age, education level, and sex on performance at the Leuven Embedded Figure Test—a proxy of disembedding abilities—in 391 cisgender individuals. We also investigated to what extent shape symmetry, closure, complexity, and continuation relate to task accuracy. Overall, target asymmetry, closure, and good continuation with the embedding context increase task difficulty. Simpler shapes are more difficult to detect than those with more lines, yet context complexity impairs the recognition of complex targets (i.e., those with 6 lines or more) to a greater extent. Concerning demographic data, we confirm that age and educational attainment are significantly associated with disembedding abilities and reveal a perceptual advantage in males. In summary, our study further highlights the role of shape properties in disembedding performance and unveils sex differences not reported so far.

Collinear facilitation and contour integration in autistic adults: Examining lateral and feedback connectivity

Alongside difficulties with communication and social interaction, autism is often accompanied by unusual sensory and perceptual experiences including enhanced visual performance on tasks that involve separating local parts from global context. This superiority may be the result of atypical integrative processing, involving feedback and lateral connections between visual neurons. The current study investigated the integrity of these connections in autistic adults by examining two psychophysics tasks that rely on these processes - collinear facilitation and contour integration. The relative contribution of feedback and lateral connectivity was studied by altering the timing of the target relative to the flankers in the collinear facilitation task, in 16 autistic and 16 non-autistic adults. There were no significant differences in facilitation between the autistic and non-autistic groups, indicating that for this task and participant sample, lateral and feedback connectivity appear relatively intact in autistic individuals. Contour integration was examined in a different group of 20 autistic and 18 non-autistic individuals, for open and closed contours to assess the closure effect (improved detection of closed compared to open contours). Autistic individuals showed a reduced closure effect at both short (150 ms) and longer (500 ms) stimulus presentation durations that was driven by better performance of the autistic group for the open contours. These results suggest that reduced closure in a simple contour detection paradigm is unlikely to be due to slower global processing. Reduced closure has implications for understanding sensory overload by contributing to reduced figure-ground segregation of salient visual features.

Edge-Enhanced Disruptive Camouflage Impairs Shape Discrimination

Disruptive colouration (DC) is a form of camouflage comprised of areas of pigmentation across a target's surface that form false edges, which are said to impede detection by disguising the outline of the target. In nature, many species with DC also exhibit edge enhancement (EE); light areas have lighter edges and dark areas have darker edges. EE DC has been shown to undermine not only localisation but also identification of targets, even when they are not hidden (Sharman, Moncrieff, & Lovell, 2018). We use a novel task, where participants judge which "snake" is more "wiggly," to measure shape discrimination performance for three colourations (uniform, DC, and EE DC) and two backgrounds (leafy and uniform). We show that EE DC impairs shape discrimination even when targets are not hidden in a textured background. We suggest that this mechanism may contribute to misidentification of EE DC targets.

Shape representation modulating the effect of motion on visual search performance

The effect of motion on visual search has been extensively investigated, but that of uniform linear motion of display on search performance for tasks with different target-distractor shape representations has been rarely explored. The present study conducted three visual search experiments. In Experiments 1 and 2, participants finished two search tasks that differed in target-distractor shape representations under static and dynamic conditions. Two tasks with clear and blurred stimuli were performed in Experiment 3. The experiments revealed that target-distractor shape representation modulated the effect of motion on visual search performance. For tasks with low target-distractor shape similarity, motion negatively affected search performance, which was consistent with previous studies. However, for tasks with high target-distractor shape similarity, if the target differed from distractors in that a gap with a linear contour was added to the target, and the corresponding part of distractors had a curved contour, motion positively influenced search performance. Motion blur contributed to the performance enhancement under dynamic conditions. The findings are useful for understanding the influence of target-distractor shape representation on dynamic visual search performance when display had uniform linear motion.

Responses in early visual areas to contour integration are context dependent

It has been shown that early visual areas are involved in contour processing. However, it is not clear how local and global context interact to influence responses in those areas, nor has the interarea coordination that yields coherent structural percepts been fully studied, especially in human observers. In this study, we used functional magnetic resonance imaging (fMRI) to measure activity in early visual cortex while observers performed a contour detection task in which alignment of Gabor elements and background clutter were manipulated. Six regions of interest (two regions, containing either the cortex representing the target or the background clutter, in each of areas V1, V2, and V3) were predefined using separate target versus background functional localizer scans. The first analysis using a general linear model showed that in the presence of background clutter, responses in V1 and V2 target regions of interest were significantly stronger to aligned than unaligned contours, whereas when background clutter was absent, no significant difference was observed. The second analysis using interarea correlations showed that with background clutter, there was an increase in V1–V2 coordination within the target regions when perceiving aligned versus unaligned contours; without clutter, however, correlations between V1 and V2 were similar no matter whether aligned contours were present or not. Both the average response magnitude and the connectivity analysis suggest different mechanisms support contour processing with or without background distractors. Coordination between V1 and V2 may play a major role in coherent structure perception, especially with complex scene organization.

The Effect of Local Orientation Change on the Detection of Contours Defined by Constant Curvature: Psychophysics and Image Statistics

In the present study, we investigated the detection of contours defined by constant curvature and the statistics of curved contours in natural scenes. In Experiment 1, we examined the degree to which human sensitivity to contours is affected by changing the curvature angle and disrupting contour curvature continuity by varying the orientation of end elements. We find that (1) changing the angle of contour curvature decreased detection performance, while (2) end elements oriented in the direction (i.e., clockwise) of curvature facilitated contour detection regardless of the curvature angle of the contour. In Experiment 2 we further established that the relative effect of end—element orientation on contour detection was not only dependent on their orientation (collinear or cocircular), but also their spatial separation from the contour, and whether the contour shape was curved or not (i.e., C-shaped or S-shaped). Increasing the spatial separation of end-elements reduced contour detection performance regardless of their orientation or the contour shape. However, at small separations, cocircular end-elements facilitated the detection of C-shaped contours, but not S-shaped contours. The opposite result was observed for collinear end-elements, which improved the detection of S- shaped, but not C-shaped contours. These dissociative results confirmed that the visual system specifically codes contour curvature, but the association of contour elements occurs locally. Finally, we undertook an analysis of natural images that mapped contours with a constant angular change and determined the frequency of occurrence of end elements with different orientations. Analogous to our behavioral data, this image analysis revealed that the mapped end elements of constantly curved contours are likely to be oriented clockwise to the angle of curvature. Our findings indicate that the visual system is selectively sensitive to contours defined by constant curvature and that this might reflect the properties of curved contours in natural images.

Perceptually Motivated Image Features Using Contours

Dong et al. examined the ability of 51 computational feature sets to estimate human perceptual texture similarity; however, none performed well for this task. While it is well-known that the human visual system is extremely adept at exploiting longer-range aperiodic (and periodic) "contour" characteristics in images, none of the investigated feature sets exploit higher order statistics (HOS) over larger image regions ( > 19×19 pixels). We, therefore, hypothesise that long-range HOS, in the form of contour data, are useful for perceptual texture similarity estimation. We present the results of a psychophysical experiment that shows that contour data are more important, than local image patches, or global second-order data, to human observers for this task. Inspired by this finding, we propose a set of perceptually motivated image features (PMIF) that encode the long-range HOS computed from spatial and angular distributions of contour segments. We use two perceptual texture similarity estimation tasks to compare PMIF against the 51 feature sets referred to above and four commonly used contour representations. This new feature set is also examined in the context of two additional tasks: sketch-based image retrieval and natural scene recognition. The results show that the proposed feature set performs better, or at least comparably to, all the other feature sets. We attribute this promising performance to the fact that the proposed feature set exploits both short-range and long-range HOS.

The role of shape complexity in the detection of closed contours

The detection of contours in noise has been extensively studied, but the detection of closed contours, such as the boundaries of whole objects, has received relatively little attention. Closed contours pose substantial challenges not present in the simple (open) case, because they form the outlines of whole shapes and thus take on a range of potentially important configural properties. In this paper we consider the detection of closed contours in noise as a probabilistic decision problem. Previous work on open contours suggests that contour complexity, quantified as the negative log probability (Description Length, DL) of the contour under a suitably chosen statistical model, impairs contour detectability; more complex (statistically surprising) contours are harder to detect. In this study we extended this result to closed contours, developing a suitable probabilistic model of whole shapes that gives rise to several distinct though interrelated measures of shape complexity. We asked subjects to detect either natural shapes (Exp. 1) or experimentally manipulated shapes (Exp. 2) embedded in noise fields. We found systematic effects of global shape complexity on detection performance, demonstrating how aspects of global shape and form influence the basic process of object detection.

Contour complexity and contour detection

Itis well-known that "smooth" chains of oriented elements-contours-are more easily detected amid background noise than more undulating (i.e., "less smooth") chains. Here, we develop a Bayesian framework for contour detection and show that it predicts that contour detection performance should decrease with the contour's complexity, quantified as the description length (DL; i.e., the negative logarithm of probability integrated along the contour). We tested this prediction in two experiments in which subjects were asked to detect simple open contours amid pixel noise. In Experiment 1, we demonstrate a consistent decline in performance with increasingly complex contours, as predicted by the Bayesian model. In Experiment 2, we confirmed that this effect is due to integrated complexity along the contour, and does not seem to depend on local stretches of linear structure. The results corroborate the probabilistic model of contours, and show how contour detection can be understood as a special case of a more general process-the identification of organized patterns in the environment.

Ensemble Empirical Mode Decomposition Analysis of EEG Data Collected during a Contour Integration Task

We discuss a data-driven analysis of EEG data recorded during a combined EEG/fMRI study of visual processing during a contour integration task. The analysis is based on an ensemble empirical mode decomposition (EEMD) and discusses characteristic features of event related modes (ERMs) resulting from the decomposition. We identify clear differences in certain ERMs in response to contour vs noncontour Gabor stimuli mainly for response amplitudes peaking around 100 [ms] (called P100) and 200 [ms] (called N200) after stimulus onset, respectively. We observe early P100 and N200 responses at electrodes located in the occipital area of the brain, while late P100 and N200 responses appear at electrodes located in frontal brain areas. Signals at electrodes in central brain areas show bimodal early/late response signatures in certain ERMs. Head topographies clearly localize statistically significant response differences to both stimulus conditions. Our findings provide an independent proof of recent models which suggest that contour integration depends on distributed network activity within the brain.

Collinear facilitation and contour integration in autism: evidence for atypical visual integration

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social interaction, atypical communication and a restricted repertoire of interests and activities. Altered sensory and perceptual experiences are also common, and a notable perceptual difference between individuals with ASD and controls is their superior performance in visual tasks where it may be beneficial to ignore global context. This superiority may be the result of atypical integrative processing. To explore this claim we investigated visual integration in adults with ASD (diagnosed with Asperger's Syndrome) using two psychophysical tasks thought to rely on integrative processing-collinear facilitation and contour integration. We measured collinear facilitation at different flanker orientation offsets and contour integration for both open and closed contours. Our results indicate that compared to matched controls, ASD participants show (i) reduced collinear facilitation, despite equivalent performance without flankers; and (ii) less benefit from closed contours in contour integration. These results indicate weaker visuospatial integration in adults with ASD and suggest that further studies using these types of paradigms would provide knowledge on how contextual processing is altered in ASD.

The development of contour processing: evidence from physiology and psychophysics

Object perception and pattern vision depend fundamentally upon the extraction of contours from the visual environment. In adulthood, contour or edge-level processing is supported by the Gestalt heuristics of proximity, collinearity, and closure. Less is known, however, about the developmental trajectory of contour detection and contour integration. Within the physiology of the visual system, long-range horizontal connections in V1 and V2 are the likely candidates for implementing these heuristics. While post-mortem anatomical studies of human infants suggest that horizontal interconnections reach maturity by the second year of life, psychophysical research with infants and children suggests a considerably more protracted development. In the present review, data from infancy to adulthood will be discussed in order to track the development of contour detection and integration. The goal of this review is thus to integrate the development of contour detection and integration with research regarding the development of underlying neural circuitry. We conclude that the ontogeny of this system is best characterized as a developmentally extended period of associative acquisition whereby horizontal connectivity becomes functional over longer and longer distances, thus becoming able to effectively integrate over greater spans of visual space.

Shape detection of Gaborized outline versions of everyday objects

We previously tested the identifiability of six versions of Gaborized outlines of everyday objects, differing in the orientations assigned to elements inside and outside the outline. We found significant differences in identifiability between the versions, and related a number of stimulus metrics to identifiability [Sassi, M., Vancleef, K., Machilsen, B., Panis, S., & Wagemans, J. (2010). Identification of everyday objects on the basis of Gaborized outline versions. i-Perception, 1(3), 121–142]. In this study, after retesting the identifiability of new variants of three of the stimulus versions, we tested their robustness to local orientation jitter in a detection experiment. In general, our results replicated the key findings from the previous study, and allowed us to substantiate our earlier interpretations of the effects of our stimulus metrics and of the performance differences between the different stimulus versions. The results of the detection task revealed a different ranking order of stimulus versions than the identification task. By examining the parallels and differences between the effects of our stimulus metrics in the two tasks, we found evidence for a trade-off between shape detectability and identifiability. The generally simple and smooth shapes that yield the strongest contour integration and most robust detectability tend to lack the distinguishing features necessary for clear-cut identification. Conversely, contours that do contain such identifying features tend to be inherently more complex and, therefore, yield weaker integration and less robust detectability.

The human visual system uses a global closure mechanism

Research asserting that the visual system instantiates a global closure heuristic in contour integration has been challenged by an argument that behaviorally-detected closure enhancement could be accounted for by low-level local mechanisms driven by collinearity or "good continuation" interacting with proximity. The present study investigated this issue in three experiments. Exp. 1 compared the visibility of closed and open contours using circles and S-contours from low to moderately high angles of path curvature in a temporal alternative-forced choice task. Circles were more detectable than S-contours, an effect that increased with curvature. The closure enhancement observed can, however, be explained by the fact that circles contain more 'contiguity' than S-contours. Additional tests added discontinuities to otherwise closed paths to control for the effects of good continuation and closure independently. Exp. 2 compared the visibility of incomplete circles (C-contours) and S-contours derived from the full circles and S-contours in Exp. 1. Exp. 3a compared the visibility of arc pairs arranged in an enclosed position similar to "()" and a non-enclosed position similar to ")(". Results consistently showed enhanced visibility of contour configurations enclosing a region even after controlling for differences in contiguity and changes of curvature direction. A control test (Exp. 3b) demonstrated that the gap in the contours of Exp. 3a was too large to be bridged by local-level collinearity/proximity alone. The combination of good continuation and proximity alone does not explain the closure effects observed across these tests, as demonstrated through the application of a Bayesian model of collinearity and proximity (Geisler et al., 2001) to the stimuli in Exps. 3a and 3b. These results argue for the presence of a global closure-driven contour enhancing mechanism in human vision.

Cortical Surround Interactions and Perceptual Salience via Natural Scene Statistics

Spatial context in images induces perceptual phenomena associated with salience and modulates the responses of neurons in primary visual cortex (V1). However, the computational and ecological principles underlying contextual effects are incompletely understood. We introduce a model of natural images that includes grouping and segmentation of neighboring features based on their joint statistics, and we interpret the firing rates of V1 neurons as performing optimal recognition in this model. We show that this leads to a substantial generalization of divisive normalization, a computation that is ubiquitous in many neural areas and systems. A main novelty in our model is that the influence of the context on a target stimulus is determined by their degree of statistical dependence. We optimized the parameters of the model on natural image patches, and then simulated neural and perceptual responses on stimuli used in classical experiments. The model reproduces some rich and complex response patterns observed in V1, such as the contrast dependence, orientation tuning and spatial asymmetry of surround suppression, while also allowing for surround facilitation under conditions of weak stimulation. It also mimics the perceptual salience produced by simple displays, and leads to readily testable predictions. Our results provide a principled account of orientation-based contextual modulation in early vision and its sensitivity to the homogeneity and spatial arrangement of inputs, and lends statistical support to the theory that V1 computes visual salience.

The Effect of Contour Closure on Shape Recognition

Recent research on the Gestalt principle of closure has focused on how the presence of closure affects the ability to detect contours hidden in cluttered visual arrays. Some of the earliest research on closure, however, dealt with encoding and recognizing closed and open shapes, rather than detection. This research re-addresses the relation between closure and shape memory, focusing on how contour closure affects the ability to learn to recognize novel contour shapes. Of particular interest is whether closed contour shapes are easier to learn to recognize and, if so, whether this benefit is due to better encoding of closed contour shapes or easier comparison of closed contour shapes to already learned shapes. The results show that closed contours are indeed easier to recognize and, further, that this advantage appears to be related to better encoding.

Peripheral vision and pattern recognition: a review

We summarize the various strands of research on peripheral vision and relate them to theories of form perception. After a historical overview, we describe quantifications of the cortical magnification hypothesis, including an extension of Schwartz's cortical mapping function. The merits of this concept are considered across a wide range of psychophysical tasks, followed by a discussion of its limitations and the need for non-spatial scaling. We also review the eccentricity dependence of other low-level functions including reaction time, temporal resolution, and spatial summation, as well as perimetric methods. A central topic is then the recognition of characters in peripheral vision, both at low and high levels of contrast, and the impact of surrounding contours known as crowding. We demonstrate how Bouma's law, specifying the critical distance for the onset of crowding, can be stated in terms of the retinocortical mapping. The recognition of more complex stimuli, like textures, faces, and scenes, reveals a substantial impact of mid-level vision and cognitive factors. We further consider eccentricity-dependent limitations of learning, both at the level of perceptual learning and pattern category learning. Generic limitations of extrafoveal vision are observed for the latter in categorization tasks involving multiple stimulus classes. Finally, models of peripheral form vision are discussed. We report that peripheral vision is limited with regard to pattern categorization by a distinctly lower representational complexity and processing speed. Taken together, the limitations of cognitive processing in peripheral vision appear to be as significant as those imposed on low-level functions and by way of crowding.

Model cortical association fields account for the time course and dependence on target complexity of human contour perception

Can lateral connectivity in the primary visual cortex account for the time dependence and intrinsic task difficulty of human contour detection? To answer this question, we created a synthetic image set that prevents sole reliance on either low-level visual features or high-level context for the detection of target objects. Rendered images consist of smoothly varying, globally aligned contour fragments (amoebas) distributed among groups of randomly rotated fragments (clutter). The time course and accuracy of amoeba detection by humans was measured using a two-alternative forced choice protocol with self-reported confidence and variable image presentation time (20-200 ms), followed by an image mask optimized so as to interrupt visual processing. Measured psychometric functions were well fit by sigmoidal functions with exponential time constants of 30-91 ms, depending on amoeba complexity. Key aspects of the psychophysical experiments were accounted for by a computational network model, in which simulated responses across retinotopic arrays of orientation-selective elements were modulated by cortical association fields, represented as multiplicative kernels computed from the differences in pairwise edge statistics between target and distractor images. Comparing the experimental and the computational results suggests that each iteration of the lateral interactions takes at least ms of cortical processing time. Our results provide evidence that cortical association fields between orientation selective elements in early visual areas can account for important temporal and task-dependent aspects of the psychometric curves characterizing human contour perception, with the remaining discrepancies postulated to arise from the influence of higher cortical areas.

Current computer vision algorithms reproducing the feed-forward features of the primate visual pathway still fall far behind the capabilities of human subjects in detecting objects in cluttered backgrounds. Here we investigate the possibility that recurrent lateral interactions, long hypothesized to form cortical association fields, can account for the dependence of object detection accuracy on shape complexity and image exposure time. Cortical association fields are thought to aid object detection by reinforcing global image features that cannot easily be detected by single neurons in feed-forward models. Our implementation uses the spatial arrangement, relative orientation, and continuity of putative contour elements to compute the lateral contextual support. We designed synthetic images that allowed us to control object shape and background clutter while eliminating unintentional cues to the presence of an otherwise hidden target. In contrast, real objects can vary uncontrollably in shape, are camouflaged to different degrees by background clutter, and are often associated with non-shape cues, making results using natural image sets difficult to interpret. Our computational model of cortical association fields matches many aspects of the time course and object detection accuracy of human subjects on statistically identical synthetic image sets. This implies that lateral interactions may selectively reinforce smooth object global boundaries.

Context modulates the ERP signature of contour integration

We investigated how the electrophysiological signature of contour integration is changed by the context in which a contour is embedded. Specifically, we manipulated the orientations of Gabor elements surrounding an embedded shape outline. The amplitudes of early visual components over posterior scalp regions were changed by the presence of a contour, and by the orientation of elements surrounding the contour. Differences in context type had an effect on the early P1 and N1 components, but not on the later P2 component. The presence of a contour had an effect on the N1 and P2 components, but not on the earlier P1 component. A modulatory effect of context on contour integration was observed on the N1 component. These results highlight the importance of the context in which contour integration takes place.

Encoding of complexity, shape, and curvature by macaque infero-temporal neurons

We recorded responses of macaque infero-temporal (IT) neurons to a stimulus set of Fourier boundary descriptor shapes wherein complexity, general shape, and curvature were systematically varied. We analyzed the response patterns of the neurons to the different stimuli using multidimensional scaling. The resulting neural shape space differed in important ways from the physical, image-based shape space. We found a particular sensitivity for the presence of curved versus straight contours that existed only for the simple but not for the medium and highly complex shapes. Also, IT neurons could linearly separate the simple and the complex shapes within a low-dimensional neural shape space, but no distinction was found between the medium and high levels of complexity. None of these effects could be derived from physical image metrics, either directly or by comparing the neural data with similarities yielded by two models of low-level visual processing (one using wavelet-based filters and one that models position and size invariant object selectivity through four hierarchically organized neural layers). This study highlights the relevance of complexity to IT neural encoding, both as a neurally independently represented shape property and through its influence on curvature detection.

Structuring process and closure principle in spatial and temporal reproduction tasks

The goal of the experiment reported was to replicate the previous Sarrazin's (2000) study in order to verify, with an adequate methodological procedure, whether or not the closure principle applied in spatial and temporal reproduction tasks. The hypothesis defended was that the closure of the pattern is an intrinsic property of the structuring process in spatial memory. The stimuli consisted of eight visually presented dots that appeared sequentially with inter-dot distances corresponding to inter-dot durations. After a learning phase, participants reproduced the spatial (space condition) or temporal (time condition) characteristics of the target 60 times in succession. We analyzed the variance level for both element location and Inter-Element-Interval (IEI) on spatial and temporal responses. Two main results emerge from this experiment: (1) the critical dependency of the closure principle to the nature (spatial or temporal) of the response, (2) the importance to consider both locations and intervals as complementary information. These results are discussed in the light of physical system, in particular in term of compensation phenomenon and we proposed a mathematical model that replicates the qualitative feature of variance for both space and time conditions.

Adaptive pseudo dilation for gestalt edge grouping and contour detection

We consider the problem of detecting object contours in natural images. In many cases, local luminance changes turn out to be stronger in textured areas than on object contours. Therefore, local edge features, which only look at a small neighborhood of each pixel, cannot be reliable indicators of the presence of a contour, and some global analysis is needed. We introduce a new morphological operator, called adaptive pseudo-dilation (APD), which uses context dependent structuring elements in order to identify long curvilinear structure in the edge map. We show that grouping edge pixels as the connected components of the output of APD results in a good agreement with the gestalt law of good continuation. The novelty of this operator is that dilation is limited to the Voronoi cell of each edge pixel. An efficient implementation of APD is presented. The grouping algorithm is then embedded in a multithreshold contour detector. At each threshold level, small groups of edges are removed, and contours are completed by means of a generalized reconstruction from markers. The use of different thresholds makes the algorithm much less sensitive to the values of the input parameters. Both qualitative and quantitative comparison with existing approaches prove the superiority of the proposed contour detector in terms of larger amount of suppressed texture and more effective detection of low-contrast contours.

Contour integration by 6-month-old infants: discrimination of distinct contour shapes

Previous research has indicated that the ability to integrate individual elements in the presence of noise is immature in 3-month-old infants. The present study extended the developmental timeline by investigating 6-month-olds' ability to integrate individual elements into whole contours through an assessment of their capability to discriminate circle and square contours constructed from oriented Gabor patches via a newly designed cueing paradigm for infants. If infants discriminate the centrally-presented contour cues, then their eye movements would correctly anticipate subsequent target presentation at a rate greater than chance. The results indicated that infants integrated the contours and discriminated the different shapes, but, consistent with past research, this ability is still fairly immature at this age, tolerating limited amount of noise.

Geometric determinants of shape segmentation: tests using segment identification

The geometric determinants of shape decomposition were studied using a performance-based method. Observers' identification of contour segments was shown to be systematically modulated by their curvature properties, and by the geometric properties of the enclosed region. Specifically, negative minima of contour curvature provided the best segment boundaries. Segments with negative-minima boundaries were identified with greater accuracy than those with positive maxima or inflection boundaries of comparable length. Additionally, segment identification was shown to be determined by contour length, the turning angle at part boundaries, and the width at the part's base (hence the part's protrusion). The results indicate that part decomposition is an automatic process. Moreover, this process is graded, i.e. parts are more strongly segmented, or more likely to be perceived, according to the strength of many geometric determinants.

Cortical specialization for concentric shape processing

It is current dogma that neurons in primary visual cortex extract local edges from the scene, from which later visual areas reconstruct more meaningful shapes. In intermediate areas, such as area V4, responses are driven by features more complex than local oriented edges but more basic than meaningful shapes. The present study was motivated by the proposal that concentric (circular) shape processing is an important aspect of intermediate shape processing and is proposed to occur in area V4. However, previous studies are not able to discriminate between the number of orientations within the image nor how these orientations vary across space (orientation gradient, contrast or curvature) as opposed to concentric shape processing per se. We address the question whether V4 responses are driven by curvature or circularity. We use fMRI and tightly controlled narrowband stimuli with identical local and global properties. These patterns either form random or circular patterns with tightly matched orientation gradients and therefore similar curvature. We find stronger responses to circular patterns in areas V3/VP and V4. Our results suggest that extracting circular shape is an important step in intermediate shape processing.

The electrophysiological correlate of contour integration is similar for color and luminance mechanisms

Contour integration perceptually links together similarly oriented line elements hidden between randomly oriented distracters. To investigate how contour integration depends on early sensory processing, we compared the electrophysiological correlate of contour integration of elements defined by luminance (black-and-white) or isoluminant color (red-and-green) contrasts. Detection performance for color- and luminance-defined contours (both open and closed) was matched. Detectable contours elicited a negative shift over posterior electrodes starting 220 ms after stimulus onset. The shift occurred for both color and luminance contrasts, even when possible luminance artifacts in red-and-green stimuli were masked. This indicates a common physiological processing stream for orientation-based contour integration of red-and-green and black-and-white elements.

Closure facilitates contour integration

Closed contours are often better perceived than those not fully enclosing an area, i.e., open contours. This facilitation of contour integration by closure, however, has been questioned arguing that in earlier studies closed contours were often "smoother" than open ones, because open contours usually had turning points. To solve this controversy, we compared detection performance for closed circles or ellipses of a higher curvature with open contours of a lower curvature neither having any turning points. Performance for circles and ellipses declined with increasing gap size and recovered only for contours with very low curvatures. Furthermore, performance increased with increasing number of contour elements and was better for smooth compared to S-shaped contours that change direction of curvature. Our results clearly demonstrate that closure improves contour detection, even though this advantage might be minor. The advantage of closed contours is maximal compared to open contours of similar curvature.

Bayesian contour extrapolation: geometric determinants of good continuation

We investigated whether observers use rate of change of curvature in visually extrapolating contour shape. Arcs of Euler spirals with positive or negative rate of change of curvature gamma (hence linearly increasing or decreasing curvature) disappeared behind the straight-edge of a half-disk occluder. Observers adjusted the position and the orientation of a line probe around the curved portion of the occluder to optimize the percept of extrapolation. These paired measurements were obtained at multiple distances from the point of occlusion in order to map out the extended shape of visually extrapolated contours. An Euler-spiral model was fit to the extrapolation data corresponding to each inducing contour. Maximum-likelihood estimates of extrapolation rate of change of curvature gamma/\ were consistently found to be negative, indicating that visually extrapolated contours are characterized by decaying curvature, irrespective of whether inducer curvature is increasing or decreasing as it approaches the occluder. Moreover, extrapolation gamma/\ was found to exhibit no systematic dependence on inducer gamma. The results indicate that the visual system does not extrapolate rate of change of contour curvature. They support a Bayesian model of contour extrapolation, in which the decay in extrapolation curvature derives from an interaction between a likelihood bias to continue estimated contour curvature, and a prior bias to minimize contour curvature. Rate of change of curvature does not play a role.

Perceptual grouping in disorganized schizophrenia

This study evaluated visual perceptual grouping in schizophrenia to test the hypothesis that the disorganization syndrome in schizophrenia is related to a deficit in cognitive coordination. Perceptual grouping was examined with three psychophysically well-controlled tasks in patients with disorganized schizophrenia (n=11), non-disorganized schizophrenia (n=24), psychotic disorders other than schizophrenia (n=31) and non-psychotic psychiatric disorders (n=35). These measures assessed processing of both concurrent and preceding stimulus context. Deficits in perceptual grouping were observed on all three tasks in disorganized schizophrenia patients. Dysfunctional perceptual grouping mechanisms produced both enhanced and impaired task performance suggesting that the pattern of performance observed was the result of a specific deficit in the grouping of stimulus elements. We interpret these data as further support for the hypothesis that the disorganization syndrome in schizophrenia reflects a widespread deficit in the cognitive coordination of contextually related stimuli, leading to dysfunctional grouping of stimulus features in vision, thought and language.

It looks easy! Heuristics for combinatorial optimization problems

Human performance on instances of computationally intractable optimization problems, such as the travelling salesperson problem (TSP), can be excellent. We have proposed a boundary-following heuristic to account for this finding. We report three experiments with TSPs where the capacity to employ this heuristic was varied. In Experiment 1, participants free to use the heuristic produced solutions significantly closer to optimal than did those prevented from doing so. Experiments 2 and 3 together replicated this finding in larger problems and demonstrated that a potential confound had no effect. In all three experiments, performance was closely matched by a boundary-following model. The results implicate global rather than purely local processes. Humans may have access to simple, perceptually based, heuristics that are suited to some combinatorial optimization tasks.

Synchronous Activity in Cat Visual Cortex Encodes Collinear and Cocircular Contours

We explored how contour information in primary visual cortex might be embedded in the simultaneous activity of multiple cells recorded with a 100-electrode array. Synchronous activity in cat visual cortex was more selective and predictable in discriminating between drifting grating and concentric ring stimuli than changes in firing rate. Synchrony was found even between cells with wholly different orientation preferences when their receptive fields were circularly aligned, and membership in synchronous groups was orientation and curvature dependent. The existence of synchrony between cocircular cells reinforces its role as a general mechanism for contour integration and shape detection as predicted by association field concepts. Our data suggest that cortical synchrony results from common and synchronous input from earlier visual areas and that it could serve to shape extrastriate response selectivity.

Reduced top-down influences in contour detection in schizophrenia

INTRODUCTION

Chronic schizophrenia patients have previously demonstrated performance deficits in contour integration tasks. The purpose of this study was to investigate whether schizophrenia patients, spanning a range of illness severity, would demonstrate responsiveness to manipulations that recruit top-down processing strategies involving learning and sequencing effects in a contour integration task.

METHODS

We administered a contour integration test over four consecutive days and in two different presentation conditions each day. In one condition, the stimuli were administered in order of increasing difficulty, and in the other they were presented in random order. The order in which these two conditions were presented was counterbalanced across days and participants. In addition, a nonschizophrenia psychotic disorders control group was included to determine if past findings of a contour integration deficit in schizophrenia could be replicated in the presence of a symptomatically similar control group.

RESULTS

All groups demonstrated similar learning curves across the four days and generally similar overall levels of performance, with the exception of the group of the most chronic schizophrenia patients. In addition, the order in which the stimuli were presented to subjects affected their performance, with higher scores achieved for all groups in the condition where the stimuli were presented in increasing order of difficulty. Interaction effects revealed that the effects of order presentation were greater for nonpatient than for psychotic patients.

CONCLUSIONS

These data are further evidence that perceptual organization impairments in schizophrenia are illness severity-related, and that schizophrenia patients as a whole are less sensitive to top-down manipulations in this type of task.

Enhancement of perceptually salient contours using a parallel artificial cortical network

In this paper we present a parallel artificial cortical network inspired by the Human visual system, which enhances the salient contours of an image. The network consists of independent processing elements, which are organized into hypercolumns. They process concurrently the distinct orientations of all the edges of the image. These processing elements are a new set of orientation kernels appropriate for the discrete lattice of the hypercolumns. The Gestalt laws of proximity and continuity that describe the process of saliency extraction in the human brain are encoded by means of weights. These weights interconnect the kernels according to a novel connection pattern based on co-exponentiality. The output of every kernel is modulated by the outputs of its neighboring kernels, according to a new affinity function. This function takes into account the degree of difference between the facilitation of the two lobes of the kernel. Saliency enhancement results as a consequence of the local interactions between the kernels. The network was tested on real and synthetic images and displays promising results for both. Comparisons with other methods with the same scope, demonstrate that the proposed method performs adequately. Furthermore it exhibits O(N) complexity with execution times that have never been reported by any other method so far, even though it is executed on a conventional PC.

Perceptual grouping in Gabor lattices: Proximity and alignment

We propose the Gabor lattice as a new stimulus designed to deal with multiple organizations in perceptual grouping, allowing both comparison between psychophysical data and neural findings and a systematic investigation of grouping based on several low-level characteristics and their interactions. A Gabor lattice is a geometric lattice with Gabor patches, evoking a multistable global orientation percept. Visual grouping in Gabor lattices with elements aligned in a global orientation was compared with grouping of nonaligned Gabor patches and of Gaussian blobs. The effect sizes of proximity and alignment were estimated in logistic regression analyses. The results confirmed the importance of proximity and local element alignment as factors in dynamic grouping. We also found a small but consistent enhancement of grouping along the global vector orthogonal to the local patch orientations. In light of these results, we further motivate the relevance of these stimuli and the associated experimental paradigm.

Task-dependent modulation of target-flanker lateral interactions in vision

Visibility of a central target Gabor element often improves in the presence of collinear flankers. Such lateral interactions may reflect fundamental mechanisms underlying the perceptual integration of contours in early vision. We recently reported (Freeman, Sagi, & Driver, 2001) attentional modulation of these interactions. Here, we test whether this modulation is task dependent. Subjects had to detect a near-threshold central target while performing a secondary discrimination task on one pair of flankers that could appear with another distractor pair (one pair collinear with the target, the other orthogonal). Central target thresholds were lowered when collinear flankers were judged for the secondary task, but only when this task concerned the global spatial relationship between these flankers (discrimination of their Vernier offset or global orientation). Other secondary tasks involving discriminating the local orientations, contrasts, or colors of the relevant flanker pair produced no such attentional modulation. However, this task-dependent modulation was observed only when two flanker pairs were present, not for displays with only a single flanker pair. Top-down modulation of lateral interactions may function to select between overlapping potential contours whenever the global spatial properties of one are task relevant.

Rapid contour integration in macaque monkeys

Integration of oriented elements into a contour has been investigated extensively in human psychophysics whereas electrophysiological experiments exploring the neuronal mechanism of contour integration were most often done with macaque monkeys. To bridge the gap between human psychophysics and physiology we estimated spatial and temporal constraints of contour integration in two macaque monkeys. Our results show that contour integration in monkeys depends in a similar way on element distance and alignment between contour path and contour elements as in human subjects. The grouping process was surprisingly fast: In a backward masking experiment we show that a stimulus duration of 30-60 ms is sufficient to perceive a contour and to identify its shape.

Dynamic competition between contour integration and contour segmentation probed with moving stimuli

Line-ends, corners and junctions are important singularities for form analysis, object recognition, depth ordering or motion processing. In this study, we investigate the extent to which processing the motion of line ends depends on the spatial configuration of their immediate surround. To that aim, we used two vertical collinear line segments, translating clockwise or anti-clockwise along a circular path, together with a direction discrimination task. Direction discrimination was measured independently for outer line-ends--at both segments extremities--and inner line-ends--in between collinear segments--using line segments partially occluded by invisible masks such that the direction of either inner or outer line-ends' motion was restricted to a sinusoidal translation along a horizontal axis, and thus irrelevant for the motion task. Under these conditions, access to the direction of inner line-ends is longer and more difficult than it is for outer line-ends. Subsequent experiments show that these effects depend on the degree of collinearity between line segments. Similar experiments were performed after volunteers took a dose of Lorazepam, a benzodiazepine that facilitates the fixation of GABA on GABAA receptors. The results show that the differences between the processing of inner and outer line-ends is reduced, suggesting that the effect of the surround is modulated by inhibitory mechanisms. Using a simple model, we propose that this effect can be explained by a competition between a segmentation process based on surround suppression and contour integration through long-range horizontal connections, at or prior to motion processing stages.

Contour grouping: closure effects are explained by good continuation and proximity

Previous experimental studies have provided evidence that closed contours are easier to detect than open contours in random-element displays, and previous theoretical studies have shown that these effects might be explained by an active neural mechanism (e.g., a "reverberating neural circuit") sensitive to closure. To test this hypothesis, detection thresholds were measured in five experiments designed to control for the effects of uncertainty, eccentricity, and element density. In four of the experiments, we found that closed contours were no easier to detect than open contours, and in the remaining experiment the effects were consistent with the predictions of probability summation. Thus, we could find no evidence for an active neural mechanism that enhances detectability of closed contours more than open contours, although some form of closure mechanism may play a significant role in image interpretation.