Seeing more than meets the eye: processing of illusory contours in animals

This review article illustrates that mammals, birds and insects are able to perceive illusory contours. Illusory contours lack a physical counterpart, but monkeys, cats, owls and bees perceive them as if they were real borders. In all of these species, a neural correlate for such perceptual completion phenomena has been described. The robustness of neuronal responses and the abundance of cells argue that such neurons might indeed represent a neural correlate for illusory contour perception. The internal state of an animal subject (i.e., alert and behaving) seems to be an important factor when correlating neural activity with perceptual phenomena. The fact that the neural network necessary for illusory contour perception has been found in relatively early visual brain areas in all tested animals suggests that bottom-up processing is largely sufficient to explain such perceptual abilities. However, recent findings in monkeys indicate that feedback loops within the visual system may provide additional modulation. The detection of illusory contours by independently evolved visual systems argues that processing of edges in the absence of contrast gradients reflects fundamental visual constraints and not just an artifact of visual processing.     

Gamma band neural synchronization deficits for auditory steady state responses in bipolar disorder patients

Periodic auditory click stimulation has been reported to elicit an auditory steady state response (ASSR). The ASSR has been suggested to reflect the efficiency of γ-amino butyric acid (GABA) inhibitory interneuronal activity. Although a potential role for GABAergic dysfunction has been previously proposed, the role of neural synchronization in the ASSR in people with bipolar disorder (BD) has received little attention. In the current study, we investigated ASSRs to 20 Hz, 30 Hz, 40 Hz and 80 Hz click trains in BD patients. A total of 14 (4 males) BD patients and 25 (10 males) healthy controls participated in this study. ASSRs were obtained using whole-head 306-channel magnetoencephalography to calculate, ASSR power values and phase locking factors (PLF). BD patients exhibited significantly reduced mean ASSR power and PLF values bilaterally at frequencies of 30, 40, and 80 Hz (p<0.05 for these frequencies). At 20 Hz, bipolar patients showed no significant reduction in mean ASSR power and PLF values. There was a significant negative correlation between 80 Hz-ASSR-power values obtained from the right hemisphere and scores on the Hamilton Depression Rating Scale (rho = −0.86, p = 0.0003). The current study showed reduced low and high gamma band ASSR power and PLF bilaterally with no significant beta band ASSR reduction in BD patients. BD patients are characterized by deficits in gamma band oscillations, which may be associated with GABA inhibitory interneuronal activity dysfunction.     

Motion-based mechanisms of illusory contour synthesis

Neurophysiological studies and computational models of illusory contour formation have focused on contour orientation as the underlying determinant of illusory contour shape in both static and moving displays. Here, we report a class of motion-induced illusory contours that demonstrate the existence of novel mechanisms of illusory contour synthesis. In a series of experiments, we show that the velocity of contour terminations and the direction of motion of a partially occluded figure regulate the perceived shape and apparent movement of illusory contours formed from moving image sequences. These results demonstrate the existence of neural mechanisms that reconstruct occlusion relationships from both real and inferred image velocities, in contrast to the static geometric mechanisms that have been the focus of studies to date.     

Top-Down Control in Contour Grouping

Human observers tend to group oriented line segments into full contours if they follow the Gestalt rule of ''good continuation''. It is commonly assumed that contour grouping emerges automatically in early visual cortex. In contrast, recent work in animal models suggests that contour grouping requires learning and thus involves top-down control from higher brain structures. Here we explore mechanisms of top-down control in perceptual grouping by investigating synchronicity within EEG oscillations. Human participants saw two micro-Gabor arrays in a random order, with the task to indicate whether the first (S1) or the second stimulus (S2) contained a contour of collinearly aligned elements. Contour compared to non-contour S1 produced a larger posterior post-stimulus beta power (15–21 Hz). Contour S2 was associated with a pre-stimulus decrease in posterior alpha power (11–12 Hz) and in fronto-posterior theta (4–5 Hz) phase couplings, but not with a post-stimulus increase in beta power. The results indicate that subjects used prior knowledge from S1 processing for S2 contour grouping. Expanding previous work on theta oscillations, we propose that long-range theta synchrony shapes neural responses to perceptual groupings regulating lateral inhibition in early visual cortex.     

Central neural mechanisms for detecting second-order motion.

Single-unit neurophysiology and human psychophysics have begun to reveal distinct neural mechanisms for processing visual stimuli defined by differences in contrast or texture (second-order motion) rather than by luminance (first-order motion). This processing begins in early visual cortical areas, with subsequent extrastriate specialization, and may provide a basis for form-cue invariant analyses of image structure, such as figure-ground segregation and detection of illusory contours.     

Dependence of V2 illusory contour response on V1 cell properties and topographic organization

An illusory contour is an image that is perceived as a contour in the absence of typical contour characteristics, such as a change in luminance or chromaticity across the stimulus. In cats and primates, cells that respond to illusory contours are sparse in cortical area V1, but are found in greater numbers in cortical area V2. We propose a model capable of illusory contour detection that is based on a realistic topographic organization of V1 cells, which reproduces the responses of individual cell types measured experimentally. The model allows us to explain several experimentally observed properties of V2 cells including variability in orientation tuning and inducer spacing preference. As a practical application, the model can be used to estimate the relationship between the severity of a cortical injury in the primary visual cortex and the deterioration of V2 cell responses to real and illusory contours.     

Computational modeling and exploration of contour integration for visual saliency

We propose a computational model of contour integration for visual saliency. The model uses biologically plausible devices to simulate how the representations of elements aligned collinearly along a contour in an image are enhanced. Our model adds such devices as a dopamine-like fast plasticity, local GABAergic inhibition and multi-scale processing of images. The fast plasticity addresses the problem of how neurons in visual cortex seem to be able to influence neurons they are not directly connected to, for instance, as observed in contour closure effect. Local GABAergic inhibition is used to control gain in the system without using global mechanisms which may be non-plausible given the limited reach of axonal arbors in visual cortex. The model is then used to explore not only its validity in real and artificial images, but to discover some of the mechanisms involved in processing of complex visual features such as junctions and end-stops as well as contours. We present evidence for the validity of our model in several phases, starting with local enhancement of only a few collinear elements. We then test our model on more complex contour integration images with a large number of Gabor elements. Sections of the model are also extracted and used to discover how the model might relate contour integration neurons to neurons that process end-stops and junctions. Finally, we present results from real world images. Results from the model suggest that it is a good current approximation of contour integration in human vision. As well, it suggests that contour integration mechanisms may be strongly related to mechanisms for detecting end-stops and junction points. Additionally, a contour integration mechanism may be involved in finding features for objects such as faces. This suggests that visual cortex may be more information efficient and that neural regions may have multiple roles.     

Abnormal Contextual Modulation of Visual Contour Detection in Patients with Schizophrenia

Schizophrenia patients demonstrate perceptual deficits consistent with broad dysfunction in visual context processing. These include poor integration of segments forming visual contours, and reduced visual contrast effects (e.g. weaker orientation-dependent surround suppression, ODSS). Background image context can influence contour perception, as stimuli near the contour affect detection accuracy. Because of ODSS, this contextual modulation depends on the relative orientation between the contour and flanking elements, with parallel flankers impairing contour perception. However in schizophrenia, the impact of abnormal ODSS during contour perception is not clear. It is also unknown whether deficient contour perception marks genetic liability for schizophrenia, or is strictly associated with clinical expression of this disorder. We examined contour detection in 25 adults with schizophrenia, 13 unaffected first-degree biological relatives of schizophrenia patients, and 28 healthy controls. Subjects performed a psychophysics experiment designed to quantify the effect of flanker orientation during contour detection. Overall, patients with schizophrenia showed poorer contour detection performance than relatives or controls. Parallel flankers suppressed and orthogonal flankers enhanced contour detection performance for all groups, but parallel suppression was relatively weaker for schizophrenia patients than healthy controls. Relatives of patients showed equivalent performance with controls. Computational modeling suggested that abnormal contextual modulation in schizophrenia may be explained by suppression that is more broadly tuned for orientation. Abnormal flanker suppression in schizophrenia is consistent with weaker ODSS and/or broader orientation tuning. This work provides the first evidence that such perceptual abnormalities may not be associated with a genetic liability for schizophrenia.     

Adaptive Filtering Methods for Identifying Cross-Frequency Couplings in Human EEG

Oscillations have been increasingly recognized as a core property of neural responses that contribute to spontaneous, induced, and evoked activities within and between individual neurons and neural ensembles. They are considered as a prominent mechanism for information processing within and communication between brain areas. More recently, it has been proposed that interactions between periodic components at different frequencies, known as cross-frequency couplings, may support the integration of neuronal oscillations at different temporal and spatial scales. The present study details methods based on an adaptive frequency tracking approach that improve the quantification and statistical analysis of oscillatory components and cross-frequency couplings. This approach allows for time-varying instantaneous frequency, which is particularly important when measuring phase interactions between components. We compared this adaptive approach to traditional band-pass filters in their measurement of phase-amplitude and phase-phase cross-frequency couplings. Evaluations were performed with synthetic signals and EEG data recorded from healthy humans performing an illusory contour discrimination task. First, the synthetic signals in conjunction with Monte Carlo simulations highlighted two desirable features of the proposed algorithm vs. classical filter-bank approaches: resilience to broad-band noise and oscillatory interference. Second, the analyses with real EEG signals revealed statistically more robust effects (i.e. improved sensitivity) when using an adaptive frequency tracking framework, particularly when identifying phase-amplitude couplings. This was further confirmed after generating surrogate signals from the real EEG data. Adaptive frequency tracking appears to improve the measurements of cross-frequency couplings through precise extraction of neuronal oscillations.     

Optimality of human contour integration

For processing and segmenting visual scenes, the brain is required to combine a multitude of features and sensory channels. It is neither known if these complex tasks involve optimal integration of information, nor according to which objectives computations might be performed. Here, we investigate if optimal inference can explain contour integration in human subjects. We performed experiments where observers detected contours of curvilinearly aligned edge configurations embedded into randomly oriented distractors. The key feature of our framework is to use a generative process for creating the contours, for which it is possible to derive a class of ideal detection models. This allowed us to compare human detection for contours with different statistical properties to the corresponding ideal detection models for the same stimuli. We then subjected the detection models to realistic constraints and required them to reproduce human decisions for every stimulus as well as possible. By independently varying the four model parameters, we identify a single detection model which quantitatively captures all correlations of human decision behaviour for more than 2000 stimuli from 42 contour ensembles with greatly varying statistical properties. This model reveals specific interactions between edges closely matching independent findings from physiology and psychophysics. These interactions imply a statistics of contours for which edge stimuli are indeed optimally integrated by the visual system, with the objective of inferring the presence of contours in cluttered scenes. The recurrent algorithm of our model makes testable predictions about the temporal dynamics of neuronal populations engaged in contour integration, and it suggests a strong directionality of the underlying functional anatomy.     

Perception of illusory contours enhanced in motion

Investigation on illusory contours is important for understanding the mechanisms underlying the object recognition of human visual system. Numerous researches have shown that illusory contours formed in motion and stereopsis are generated by the unmatched features. Here we conduct three psychophysical experiments to test if Kanizsa illusory contours are also caused by unmatched information. Different types of motion (including horizontal translation, radial expanding and shrinking) are utilized in the experiments. The results show that no matter under what kind of motion, when figures or background move separately illusory contours are perceived stronger, and there is no significant difference between the perceived strength in these two types of motion. However, no such enhancement of perceived strength is found when figures and background move together. It is found that the strengthened unmatched features generate the enhancement effect of illusory contour perception in motion. Thus the results suggest that the process of unmatched information in visual system is a critical step in the formation of illusory contours.     

Perception of illusory contours enhanced in motion

Object perception is one of the most important components of visual perception of human beings and mammalian animals. It is a most confusing problem on object perception that how we separate object from background and obtain the picture of the whole object. In many cases one object partly occludes the other one in natural world. When the brightness of the occluding object is the same as or similar to that of the background, though there is no difference between visual stimuli, we can still ret…     

Influence of Visual Motion,Suggestion, and Illusory Motion on Self-Motion Perception in the Horizontal Plane

A moving visual field can induce the feeling of self-motion or vection. Illusory motion from static repeated asymmetric patterns creates a compelling visual motion stimulus, but it is unclear if such illusory motion can induce a feeling of self-motion or alter self-motion perception. In these experiments, human subjects reported the perceived direction of self-motion for sway translation and yaw rotation at the end of a period of viewing set visual stimuli coordinated with varying inertial stimuli. This tested the hypothesis that illusory visual motion would influence self-motion perception in the horizontal plane. Trials were arranged into 5 blocks based on stimulus type: moving star field with yaw rotation, moving star field with sway translation, illusory motion with yaw, illusory motion with sway, and static arrows with sway. Static arrows were used to evaluate the effect of cognitive suggestion on self-motion perception. Each trial had a control condition; the illusory motion controls were altered versions of the experimental image, which removed the illusory motion effect. For the moving visual stimulus, controls were carried out in a dark room. With the arrow visual stimulus, controls were a gray screen. In blocks containing a visual stimulus there was an 8s viewing interval with the inertial stimulus occurring over the final 1s. This allowed measurement of the visual illusion perception using objective methods. When no visual stimulus was present, only the 1s motion stimulus was presented. Eight women and five men (mean age 37) participated. To assess for a shift in self-motion perception, the effect of each visual stimulus on the self-motion stimulus (cm/s) at which subjects were equally likely to report motion in either direction was measured. Significant effects were seen for moving star fields for both translation (p = 0.001) and rotation (p<0.001), and arrows (p = 0.02). For the visual motion stimuli, inertial motion perception was shifted in the direction consistent with the visual stimulus. Arrows had a small effect on self-motion perception driven by a minority of subjects. There was no significant effect of illusory motion on self-motion perception for either translation or rotation (p>0.1 for both). Thus, although a true moving visual field can induce self-motion, results of this study show that illusory motion does not.     

Sounds reset rhythms of visual cortex and corresponding human visual perception

An event in one sensory modality can phase reset brain oscillations concerning another modality. In principle, this may result in stimulus-locked periodicity in behavioral performance. Here we considered this possible cross-modal impact of a sound for one of the best-characterized rhythms arising from the visual system, namely occipital alpha-oscillations (8-14 Hz). We presented brief sounds and concurrently recorded electroencephalography (EEG) and/or probed visual cortex excitability (phosphene perception) through occipital transcranial magnetic stimulation (TMS). In a first, TMS-only experiment, phosphene perception rate against time postsound showed a periodic pattern cycling at ~10 Hz phase-aligned to the sound. In a second, combined TMS-EEG experiment, TMS-trials reproduced the cyclical phosphene pattern and revealed a ~10 Hz pattern also for EEG-derived measures of occipital cortex reactivity to the TMS pulses. Crucially, EEG-data from intermingled trials without TMS established cross-modal phase-locking of occipitoparietal alpha oscillations. These independently recorded variables, i.e., occipital cortex excitability and reactivity and EEG phase dynamics, were significantly correlated. This shows that cross-modal phase locking of oscillatory visual cortex activity can arise in the human brain to affect perceptual and EEG measures of visual processing in a cyclical manner, consistent with occipital alpha oscillations underlying a rapid cycling of neural excitability in visual areas.     

Deriving behavioural receptive fields for visually completed contours

The visual system is constantly faced with the problem of identifying partially occluded objects from incomplete images cast on the retinae. Phenomenologically, the visual system seems to fill in missing information by interpolating illusory and occluded contours at points of occlusion, so that we perceive complete objects. Previous behavioural [1] [2] [3] [4] [5] [6] [7] and physiological [8] [9] [10] [11] [12] studies suggest that the visual system treats illusory and occluded contours like luminance-defined contours in many respects. None of these studies has, however, directly shown that illusory and occluded contours are actually used to perform perceptual tasks. Here, we use a response-classification technique [13] [14] [15] [16] [17] [18] [19] [20] to answer this question directly. This technique provides pictorial representations - 'classification images' - that show which parts of a stimulus observers use to make perceptual decisions, effectively deriving behavioural receptive fields. Here we show that illusory and occluded contours appear in observers' classification images, providing the first direct evidence that observers use perceptually interpolated contours to recognize objects. These results offer a compelling demonstration of how visual processing acts on completed representations, and illustrate a powerful new technique for constraining models of visual completion.     

Globally consistent depth sorting of overlapping 2D surfaces in a model using local recurrent interactions

The human visual system utilizes depth information as a major cue to group together visual items constituting an object and to segregate them from items belonging to other objects in the visual scene. Depth information can be inferred from a variety of different visual cues, such as disparity, occlusions and perspective. Many of these cues provide only local and relative information about the depth of objects. For example, at occlusions, T-junctions indicate the local relative depth precedence of surface patches. However, in order to obtain a globally consistent interpretation of the depth relations between the surfaces and objects in a visual scene, a mechanism is necessary that globally propagates such local and relative information. We present a computational framework in which depth information derived from T-junctions is propagated along surface contours using local recurrent interactions between neighboring neurons. We demonstrate that within this framework a globally consistent depth sorting of overlapping surfaces can be obtained on the basis of local interactions. Unlike previous approaches in which locally restricted cell interactions could merely distinguish between two depths (figure and ground), our model can also represent several intermediate depth positions. Our approach is an extension of a previous model of recurrent V1–V2 interaction for contour processing and illusory contour formation. Based on the contour representation created by this model, a recursive scheme of local interactions subsequently achieves a globally consistent depth sorting of several overlapping surfaces. Within this framework, the induction of illusory contours by the model of recurrent V1–V2 interaction gives rise to the figure-ground segmentation of illusory figures such as a Kanizsa square.     

Detection of a gabor patch superimposed on an illusory contour

Interactions between visual stimuli have been found to be specific to the spatial frequency, orientation and phase of the interacting stimuli. We asked if there are any interactions between luminance-defined Gabor patches and Kanizsa-type illusory contours. In psychophysical experiments we studied whether induction of a vertical illusory line affects detection thresholds for a Gabor patch superimposed on this line and whether these effects depend on the orientation, spatial frequency and phase of the Gabor elements. Employing a 2AFC method with a staircase procedure we measured contrast detection thresholds and varied the orientation, spatial frequency and phase of the test Gabor patch and the separation between the two pacmen in four experimental series. The results show that in a situation where the two inducers generate perception of an illusory line, the contrast detection of the Gabor patch is facilitated relative to a control condition where the rotated pacmen do not induce illusory contours. This facilitation was more pronounced for test Gabor signals that were collinear to the illusory line, but the observer's performance was not altered by changes in the spatial frequency or phase of the Gabor stimuli. With increasing spatial separation of the two pacmen (and, consequently, with a decreasing support ratio), the difference between performance in the test and control conditions diminished. From the data obtained we cannot infer that we have measured some neural interactions between Gabor patches and Kanizsa-type illusory contours, and nor can we draw a unique conclusion about what causes the facilitation of detection of the test Gabor patch in the experimental situation that allows induction of the illusory line. We discuss possible mechanisms of the facilitation, such as contextual influences or a reduction of uncertainty about spatial location of the test Gabor patch.     

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.     

Selective attention in dogs from energy characteristics of neocortical potentials in the 1-220 Hz band

The state of selective attention was studied in dogs in the course of instrumental conditioning. During interstimuli intervals, this state was manifested in the state of strained waiting for conditioned stimuli. Electrical activity of different areas in both hemispheres was analyzed using the Fast Fourier Transformation. It was shown that in the process of development of selective attention, the high-frequency EEG components (40-200 Hz) in the motor area of the right hemisphere and the visual and parietal areas of the left hemisphere had a predominant significance over the traditional EEG frequencies of 1-30 Hz. The state of selective attention was characterized by another functional mosaic organization of the neocortical potentials.     

Recurrent V1–V2 interaction in early visual boundary processing

A majority of cortical areas are connected via feedforward and feedback fiber projections. In feedforward pathways we mainly observe stages of feature detection and integration. The computational role of the descending pathways at different stages of processing remains mainly unknown. Based on empirical findings we suggest that the top-down feedback pathways subserve a context-dependent gain control mechanism. We propose a new computational model for recurrent contour processing in which normalized activities of orientation selective contrast cells are fed forward to the next processing stage. There, the arrangement of input activation is matched against local patterns of contour shape. The resulting activities are subsequently fed back to the previous stage to locally enhance those initial measurements that are consistent with the top-down generated responses. In all, we suggest a computational theory for recurrent processing in the visual cortex in which the significance of local measurements is evaluated on the basis of a broader visual context that is represented in terms of contour code patterns. The model serves as a framework to link physiological with perceptual data gathered in psychophysical experiments. It handles a variety of perceptual phenomena, such as the local grouping of fragmented shape outline, texture surround and density effects, and the interpolation of illusory contours. Received: 28 October 1998 / Accepted in revised form: 19 March 1999