Illusory Contour Stimuli Research Articles

The strength of feedback processing is associated with resistance to visual backward masking during Illusory Contour processing in adult humans

Re-entrant feedback processing is a key mechanism of visual object-recognition, especially under compromised viewing conditions where only sparse information is available and object features must be interpolated. Illusory Contour stimuli are commonly used in conjunction with Visual Evoked Potentials (VEP) to study these filling-in processes, with characteristic modulation of the VEP in the ∼100-150 ms timeframe associated with this re-entrant processing. Substantial inter-individual variability in timing and amplitude of feedback-related VEP modulation is observed, raising the question whether this variability might underlie inter-individual differences in the ability to form strong perceptual gestalts. Backward masking paradig ms have been used to study inter-individual variance in the ability to form robust object perceptions before processing of the mask interferes with object-recognition. Some individuals recognize objects when the time between target object and mask is extremely short, whereas others struggle to do so even at longer target-to-mask intervals. We asked whether timing and amplitude of feedback-related VEP modulations were associated with individual differences in resistance to backward masking. Participants (N=40) showed substantial performance variability in detecting Illusory Contours at intermediate target-to-mask intervals (67 ms and 117 ms), allowing us to use kmeans clustering to divide the population into four performance groups (poor, low-average, high-average, superior). There was a clear relationship between the amplitude (but not the timing) of feedback-related VEP modulation and Illusory Contour detection during backward masking. We conclude that individual differences in the strength of feedback processing in neurotypical humans lead to differences in the ability to quickly establish perceptual awareness of incomplete visual objects.

Classification Images Reveal that Deep Learning Networks Fail to Perceive Illusory Contours

Background: Deep learning networks show impressive object recognition performance and learned filters within them show correlates with neural activity in human visual areas. However, deep learning networks can also be easily fooled by adversarial examples which do not affect human recognition. We used the classification image method developed in psychophysics to probe whether a deep learning model employs the same features as humans in perceiving real and illusory contours. Method: We adapted a standard deep learning network, Convolutional Neural Networks (CNNs), pre-trained on the ImageNet dataset with 1.2 million natural images. The network was trained to perform shape discrimination in the "fat/thin" task (Ringach & Shapley, 1996) by replacing the last decision layer with a perceptron. The perceptron used the set of 4096 activations of the CNN's penultimate layer's units as input and was trained to do a novel classification between 'fat' and 'thin' shapes with 12,000 examples of these stimuli. After training, we tested with real and illusory contour stimuli contaminated with Gaussian luminance noise. The network's decisions on shape discrimination were used to combine noise fields to compute classification images. Results: Networks coupled with the new decision layer discriminated between fat and thin shapes with high accuracy (98.56%). For real contours, classification images showed behavioral receptive fields consistent with human classification images. However, in displays with gaps, where humans perceive illusory contours, the classification images from the CNN failed to reveal behavioral receptive field activity along illusory contours. Conclusions: Deep learning networks trained on natural images can be readily altered by introducing a new decision layer to discriminate between psychophysical stimuli with an extremely high degree of accuracy. However, deep learning networks do not appear to perceive illusory contours from corner inducing elements, a process readily and automatically performed in the human visual system (Gold et al, 2000). Meeting abstract presented at VSS 2017

The effort to close the gap: Tracking the development of illusory contour processing from childhood to adulthood with high-density electrical mapping

The adult human visual system can efficiently fill-in missing object boundaries when low-level information from the retina is incomplete, but little is known about how these processes develop across childhood. A decade of visual-evoked potential (VEP) studies has produced a theoretical model identifying distinct phases of contour completion in adults. The first, termed a perceptual phase, occurs from approximately 100–200ms and is associated with automatic boundary completion. The second is termed a conceptual phase occurring between 230 and 400ms. The latter has been associated with the analysis of ambiguous objects which seem to require more effort to complete. The electrophysiological markers of these phases have both been localized to the lateral occipital complex, a cluster of ventral visual stream brain regions associated with object-processing. We presented Kanizsa-type illusory contour stimuli, often used for exploring contour completion processes, to neurotypical persons ages 6–31 (N=63), while parametrically varying the spatial extent of these induced contours, in order to better understand how filling-in processes develop across childhood and adolescence. Our results suggest that, while adults complete contour boundaries in a single discrete period during the automatic perceptual phase, children display an immature response pattern—engaging in more protracted processing across both timeframes and appearing to recruit more widely distributed regions which resemble those evoked during adult processing of higher-order ambiguous figures. However, children older than 5years of age were remarkably like adults in that the effects of contour processing were invariant to manipulation of contour extent.

Early electrophysiological indices of illusory contour processing within the lateral occipital complex are virtually impervious to manipulations of illusion strength.

The visual system can automatically interpolate or "fill-in" the boundaries of objects when inputs are fragmented or incomplete. A canonical class of visual stimuli known as illusory-contour (IC) stimuli has been extensively used to study this contour interpolation process. Visual evoked potential (VEP) studies have identified a neural signature of these boundary completion processes, the so-called IC-effect, which typically onsets at 90-110 ms and is generated within the lateral occipital complex (LOC). Here we set out to determine the delimiting factors of automatic boundary completion with the use of illusory contour stimuli and high-density scalp recordings of brain activity. Retinal eccentricity, ratio of real to illusory contours (i.e. support ratio), and inducer diameter were each varied parametrically, and any resulting effects on the amplitude and latency of the IC-effect were examined. Somewhat surprisingly, the amplitude of the IC-effect was found to be impervious to all changes in these stimulus parameters, manipulations that are known to impact perceived illusion strength. Thus, this automatic stage of object processing appears to be a binary process in which, so-long as minimal conditions are met, contours are automatically completed. At the same time, the latency of the IC-effect was found to vary inversely with support ratio, likely reflecting the additional time necessary to interpolate across the relatively longer induced boundaries of the implied object. These data are interpreted in the context of a two stage object-recognition model that parses processing into an early automatic perceptual stage that is followed by a more effortful conceptual processing stage.

Electrical neuroimaging of early sensory processing in first-episode psychosis

Event Abstract Back to Event Electrical neuroimaging of early sensory processing in first-episode psychosis Jean-François Knebel1*, Lucas Spierer1, Philippe Baumann1, Carina Ferrari1, Andrea Polari1, Tanja Teichmann1, Kim Q. Do1, Philippe Conus1 and Micah M. Murray1 1 CHUV/UNIL, Switzerland Low-level, early auditory and visual impairments have been documented in patients with schizophrenia and their first-degree relatives. More recently, such findings have been extended to first-episode psychotics. At present, it remains under-determined the precise mechanism leading to these impairments, including but not limited to whether any impairments reflect general sensory processing deficits or specific functional deficits in processing particular stimulus properties, as well as whether impairments in one sensory modality are co-occur with those in another sensory modality. We performed electrical neuroimaging analyses of event-related potentials recorded from 16 (all males; 13 right-handed) first-episode psychosis patients and 14 (10 males; 12 right-handed) age-matched controls. The visual task entailed the presentation of Kanizsa-type illusory contour stimuli, allowing for the parallel investigation of impairments in visual sensory processing and completion processes. The auditory task entailed an oddball paradigm. The frequent stimulus (70% of trials) was a 1000Hz centrally-presented sound of 100ms duration. The infrequent stimuli (10% of trials each) varied in pitch (1200Hz), perceived lateralization (700µs), or duration (150ms) Remaining parameters matched the frequent stimulus. While we were able to replicate prior findings of impaired early visual responses in first-episode patients using analyses of individual scalp electrodes, this was not evident in analyses of global features of the electric field. By contrast, there was evidence for sensory and functional auditory processing impairments at all levels of analysis. We discuss our findings in the context of attempts to establish biomarkers of psychosis. Funding: NCCR “SYNAPSY”-National Science Foundation (n° 51AU40_125759)- the SNF (to MMM)-the Leenaards Foundation-the Loterie Romande. Keywords: Auditory and visual impairments, Perception Conference: XI International Conference on Cognitive Neuroscience (ICON XI), Palma, Mallorca, Spain, 25 Sep - 29 Sep, 2011. Presentation Type: Poster Presentation Topic: Poster Sessions: Neurophysiology of Sensation and Perception Citation: Knebel J, Spierer L, Baumann P, Ferrari C, Polari A, Teichmann T, Do KQ, Conus P and Murray MM (2011). Electrical neuroimaging of early sensory processing in first-episode psychosis. Conference Abstract: XI International Conference on Cognitive Neuroscience (ICON XI). doi: 10.3389/conf.fnhum.2011.207.00478 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 25 Nov 2011; Published Online: 28 Nov 2011. * Correspondence: Dr. Jean-François Knebel, CHUV/UNIL, Lausanne, Switzerland, jean-francois.knebel@chuv.ch Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Jean-François Knebel Lucas Spierer Philippe Baumann Carina Ferrari Andrea Polari Tanja Teichmann Kim Q Do Philippe Conus Micah M Murray Google Jean-François Knebel Lucas Spierer Philippe Baumann Carina Ferrari Andrea Polari Tanja Teichmann Kim Q Do Philippe Conus Micah M Murray Google Scholar Jean-François Knebel Lucas Spierer Philippe Baumann Carina Ferrari Andrea Polari Tanja Teichmann Kim Q Do Philippe Conus Micah M Murray PubMed Jean-François Knebel Lucas Spierer Philippe Baumann Carina Ferrari Andrea Polari Tanja Teichmann Kim Q Do Philippe Conus Micah M Murray Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Staying within the lines: the formation of visuospatial boundaries influences multisensory feature integration

The brain processes multisensory features of an object (e.g., its sound and shape) in separate cortical regions. A key question is how representations of these features bind together to form a coherent percept (the 'binding problem'). Here we tested the hypothesis that the determination of an object's visuospatial boundaries is paramount to the linking of its multisensory features (i.e., that the refinement of attended space through the formation of visual boundaries establishes the boundaries for multisensory feature integration). We recorded both scalp and intracranial electrophysiological data in response to Kanizsa-type illusory contour stimuli (in which pacman-like elements give the impression of a single object), their non-illusory counterparts, and auditory stimuli. Participants performed a visual task and ignored sounds. Enhanced processing of task-irrelevant sounds when paired with attended visual stimuli served as our metric for multisensory feature integration [e.g., Busse et al. (2005) Proc. Natl Acad. Sci. USA 102: 18751-18756]. According to our hypothesis, task-irrelevant sounds paired with Kanizsa-type illusory contour stimuli (which have well-defined boundaries) should receive enhanced processing relative to task-irrelevant sounds paired with non-illusory contour stimuli (which have ambiguous boundaries). The scalp data clearly support this prediction and, combined with the intracranial data, advocate for an important extension of models for multisensory feature integration. We propose a model in which (i) the visual boundaries of an object are established through processing in occipitotemporal cortex, and (ii) attention then spreads to cortical regions that process features that fall within the object's established visual boundaries, including its task-irrelevant multisensory features.

Edge-induced illusory contours and visual detection: Subthreshold summation or spatial cueing?

Findings that illusory contours can facilitate visual detection of a subthreshold real line (Dresp & Bonnet, 1995) were not replicated, when line-induced instead of edge-induced illusory contour stimuli were used (Salvano-Pardieu et al., 2006). Rather, the results of the latter study supported the importance of spatial cues. The present study was designed to investigate whether spatial cueing might also facilitate detection of targets superimposed on edge-induced illusory contours. In Experiment 1, a target line was superimposed on the illusory contour of a Kanizsa square, presented between dots with a precise or distant location to the target, or on a homogeneous field (control). Detection of the target was poorest for the control, followed by the distant-dots and Kanizsa conditions, whereas it was best for precisely cueing dots. Experiment 2 replicated the conditions in Experiment 1 (Kanizsa, precisely cueing dots, and control) with additional controls for possible luminance effects. The two new conditions matched the Kanizsa condition for overall luminance and preciseness of spatial cueing without generating illusory contours. Performance was best in the dot condition and worst in the control, but the same across the Kanizsa and matched luminance conditions. In Experiments 3 and 4, the stimuli presented were matched more closely to those used by Dresp and Bonnet, but still the results confirmed those obtained in our Experiments 1 and 2. Together, these experiments strongly suggest that detection is also facilitated by spatial cueing rather than subthreshold summation, in the case of edge-induced illusory contours.

Early processing in the human lateral occipital complex is highly responsive to illusory contours but not to salient regions

Human electrophysiological studies support a model whereby sensitivity to so-called illusory contour stimuli is first seen within the lateral occipital complex. A challenge to this model posits that the lateral occipital complex is a general site for crude region-based segmentation, based on findings of equivalent hemodynamic activations in the lateral occipital complex to illusory contour and so-called salient region stimuli, a stimulus class that lacks the classic bounding contours of illusory contours. Using high-density electrical mapping of visual evoked potentials, we show that early lateral occipital cortex activity is substantially stronger to illusory contour than to salient region stimuli, whereas later lateral occipital complex activity is stronger to salient region than to illusory contour stimuli. Our results suggest that equivalent hemodynamic activity to illusory contour and salient region stimuli probably reflects temporally integrated responses, a result of the poor temporal resolution of hemodynamic imaging. The temporal precision of visual evoked potentials is critical for establishing viable models of completion processes and visual scene analysis. We propose that crude spatial segmentation analyses, which are insensitive to illusory contours, occur first within dorsal visual regions, not the lateral occipital complex, and that initial illusory contour sensitivity is a function of the lateral occipital complex.

Critical Spatial Frequencies for Illusory Contour Processing in Early Visual Cortex

Single neurons in primate V2 and cat A18 exhibit identical orientation tuning for sinewave grating and illusory contour stimuli. This cue invariance is also manifested in similar orientation maps to these stimuli, but in V1/A17 the illusory contour maps appear reversed. We hypothesized that this map reversal depends upon the spatial frequencies of the inducers in the illusory contours, relative to the spatial selectivities of these brain areas. We employed intrinsic signal optical imaging to measure orientation maps in cat A17/18 to illusory contours with inducers at spatial frequencies from 0.15 to 1.6 cpd. A17 illusory contour maps were indeed reversed compared with grating-driven maps for inducer spatial frequencies <1.3 cpd, whereas A18 maps were invariant. Simulations based on known neurophysiology demonstrated that map reversal can arise from linear filtering, and map invariance can be explained by a nonlinear (filter-rectify-filter) mechanism. The simulation also correctly predicted that A17 could show invariant maps when the inducer spatial frequency is sufficiently high (1.6 cpd), and that A18 maps could reverse at lower inducer frequencies (0.18 cpd). Thus, the map reversal or invariance to illusory contours depends critically on the relationship of the inducer spatial frequencies to the spatial filtering properties of neurons in each brain area.

An analysis of MEG responses to illusory-contour stimuli in the quadrant visual fields

An analysis of MEG responses to illusory-contour stimuli in the quadrant visual fields

Categorical Perception of Illusory Contour Defined Shapes

Categorical perception (CP) is the phenomenon when people are better able to distinguish between stimuli of different categories than between stimuli of the same category and it appears for innate and learned stimuli of various sensory modalities. We tested if CP occurs also for illusory contour stimuli. First, in an ABX paradigm the shape discrimination capacity of subjects was tested for convex (‘fat’) or concave (‘thin’) Kanizsa-square-like shapes (cf Rubin, 1996 Perception25 Supplement, 3; pre-category-learning test). The proportion of correct responses and response latency were measured. Second, subjects were instructed that every stimulus belongs to either the ‘fat’ or the ‘thin’ category, and they were trained to categorise the individual stimuli using a 2AFC paradigm with corrective feedback until 90% of correct responses. Third, we measured the shape discrimination capacity of subjects, by repeating the first ABX paradigm (post-category-learning test). Comparison of the ratio of correct responses in the post/pre discrimination tests showed that discrimination of illusory shapes of different categories is enhanced but discrimination of members of the same category is made more difficult by category training. In a second experiment, by increasing the physical differences between the extreme ‘fat’ and extreme ‘thin’ stimuli (increased range of the opening-angle of the Kanizsa-square inducer pacmen), we made the categorisation task easier for the subjects and tested if discrimination capacity is altered by the modified difficulty of the categorisation task. We discuss the effect of difficulty on CP and the relation of illusory CP to that of real luminance contour stimuli.

Stochastic completion fields; a neural model of illusory contour shape and salience.

We describe an algorithm- and representation-level theory of illusory contour shape and salience. Unlike previous theories, our model is derived from a single assumption: that the prior probability distribution of boundary completion shape can be modeled by a random walk in a lattice whose points are positions and orientations in the image plane (i.e., the space that one can reasonably assume is represented by neurons of the mammalian visual cortex). Our model does not employ numerical relaxation or other explicit minimization, but instead relies on the fact that the probability that a particle following a random walk will pass through a given position and orientation on a path joining two boundary fragments can be computed directly as the product of two vector-field convolutions. We show that for the random walk we define, the maximum likelihood paths are curves of least energy, that is, on average, random walks follow paths commonly assumed to model the shape of illusory contours. A computer model is demonstrated on numerous illusory contour stimuli from the literature.

Abrupt Transitions in the Perception of Illusory Contours Triggered by Specific Visual Stimuli

Two forms of learning have been identified in previous studies. Gradual improvement is observed for many perceptual tasks; it is often stimulus-specific and is consequently thought to involve synaptic modifications in early visual cortical areas. In contrast, sudden transitions, either cognitive (‘insight’) or perceptual (eg in the Dalmatian dog picture) are generally thought to occur more centrally. Here we report that a sudden transition in the perception of illusory-contour stimuli can be triggered by specific visual stimuli, rather than by verbal instructions, leading to an abrupt improvement in psychophysical performance. Subjects discriminated between two classes of Kanizsa-like shapes where the (illusory) edges were slightly curved into ‘thin’ or ‘fat’ figures (D L Ringach, R Shapley, 1993 Perception22 Supplement, 51). In the first (‘test’) block, only small amounts of curvature (1° – 3°) were given; subjects performed poorly in that block. In the second (‘training’) block, stimuli with larger curvature (4° – 6°) were added to the set. Performance for the 1° – 3° stimuli improved abruptly—often within seconds—compared to the first block: the pooled responses of eight naive subjects showed a marked jump, followed by maintained elevation, of the fraction-correct responses as a function of time. Good performance was retained in a third (re-test) block, with a stimulus set identical to that of the first block. Control experiments verified that the subjects understood the task from the beginning. Furthermore, the learned performance did not transfer to a different (smaller) retinal size. Thus the jump in performance is a perceptual, stimulus-specific phenomenon (rather than a cognitive one), although it exhibits characteristics of ‘insightful’ understanding.

Object Discrimination Based on Depth-from-Occlusion

We present a model of how objects can be visually discriminated based on the extraction of depth-from-occlusion. Object discrimination requires consideration of both the binding problem and the problem of segmentation. We propose that the visual system binds contours and surfaces by identifying “proto-objects”—compact regions bounded by contours. Proto-objects can then be linked into larger structures. The model is simulated by a system of interconnected neural networks. The networks have biologically motivated architectures and utilize a distributed representation of depth. We present simulations that demonstrate three robust psychophysical properties of the system. The networks are able to stratify multiple occluding objects in a complex scene into separate depth planes. They bind the contours and surfaces of occluded objects (for example, if a tree branch partially occludes the moon, the two "half-moons" are bound into a single object). Finally, the model accounts for human perceptions of illusory contour stimuli.

Depth capture and transparency of regions bounded by illusory and chromatic contours

Spillmann and Redies noted that when a transparent textured pattern is held above the Ehrenstein figure, the subjective surfaces appear to lie not in the plane of the figures but in the plane of the overlying texture. In Experiment 1, we tested this phenomenon with chromatic squares and found that the perceived depth of regions bounded by the chromatic contours was captured by overlying texture planes when the square was equiluminous with the background. We then tested this phenomenon with a variety of illusory contour stimuli and found that it only occurs with figures involving fine line terminators, and not, for example, with the solid Kanizsa triangle. These results suggest that chromatic contours and the illusory contours induced by line terminators provide only weak binocular disparity signals and that these signals are easily overwhelmed by the disparity signals from the overlying luminance texture.