2 - The human visual system described through visual illusions

Visual illusions occur around us all the time, which present in nature and appear when you least expect it. It is well known that visual illusions can have a dramatic effect upon our visual perception of an object 's size and position. However, whether visual illusions have a similar influence on visual guided action or not, it remains the subject of much debate. The purpose of this study is to explore whether the visual information used to identify and categorize an object would be similar to the visual information used to plan and control visually guided movements directed toward that object. The outcome of this study will be helpful for designers to understand our visual information system and apply that knowledge to the design practice. In order to achieve the purpose of this study mentioned above, three visual illusions as the experiment's apparatus are applied to examine the relative effect of visual illusions on both the visual perceived center of an object and the position of a grasp on that object when a balanced lift is required. The results of the experiment show that (1) Illusions influence both the perceived and the grasped estimates of the center position, but the grasp center is more veridical; (2) Judd-illusion, one of the three visual illusions, has a bigger degree of effect than two other illusions on both the perceived and the grasped estimates of the center position; (3) By providing the participants with a mean to guide their visual perception of these illusions, the errors from the estimation of the center position can be significantly reduced.

The science and technology of image transmission and display has evolved primarily from the diciplines of computer science, electrical engineering and physics. Thus, it is only natural that techniques and attitudes which have developed are characterized by the style in which people in these areas approach the subject of images and their transmission, display, and processing. For example, one finds many important differences between the methods of television and those of photography. Moreover, an even greater contrast is found when comparing the methods of electrical engineering, physics, television and photography with those now understood to be employed by the human eye and the human visual system. Specifically, let us contrast the method by which television, photography and the human visual system, represent image information. In television (particularly digital imaging), image values are represented by signals analogous to quantities of light. They are called intensities. In photography, on the other hand, the representing quantities are concentrations of silver or dyes. Consequently, due to the natural exponentiating laws governing the interaction of light with these media, they are analogous to the logarithm of quantities of light. They are called densities. The human visual system, on the other hand, (while being generally logarithmically sensitive) moves a large step further away from representation by physical quantities of light and produces at very early stages in its processing highly modified versions of the patterns of light or their logarithms. The natural question then arrises, why should the human visual system try to do this; and since it does, what consequences are implied in terms of the television and photographic presentations normally employed?

Coupled map lattices (CMLs) offer a new framework for modelling visual information processes. The framework involves computing with non-stationary patterns of synchronized activity. In this framework structural features of the visual field emerge through the lateral interaction of locally coupled non-linear maps. Invariant representations develop independent of top-down, or re-entrant, feedback. These representations distort certain features of the pattern, giving rise to visual field illusions. Boundary contours, among others, are emphasized, which suggests that special cases of boundary contour problem could be solved by the system. Simulation studies were performed to test the hypothesis that the system represents visual patterns in a solid/outline invariant manner. A standard back-propagation neural network trained with a CML-filtered set of solid images and tested with CML-filtered outline versions of the same set of images (or vice versa) showed perfect generalization. Generalization failed to occur for unfiltered or contour-filtered images. The CML representations, therefore, were concluded to be solid/outline invariant.

The processing and perception of visual stimuli are greatly dependent on the context in which those stimuli are presented. While this is not always (and indeed is probably not supposed to be) evident when viewing real-world scenes, the abundance of contextual effects is revealed for example by the vast number of different visual illusions. Context can profoundly change the way the visual system processes single visual stimuli. In contrast masking, surround suppression, and crowding, distracting stimuli impair the observer's ability to detect, identify, and make other judgements about visual stimuli. These perceptual phenomena presumably reflect the operation of neural mechanisms that adjust the operating range of the visual system according to the prevailing conditions, or act to reduce responses to redundant stimulus features. This work first investigates the relationship between masking, which is caused by stimuli that are spatially superimposed on a target stimulus, and surround suppression, which is caused by spatially displaced stimuli. This was done using a temporal masking paradigm and measuring the time-courses of masking and surround suppression. The results reveal how the effects of these suppressive interactions are delicately dependent on stimulus timing and suggest that surround suppression acts extremely fast, having an effect on the early part of the neural response. Finally, contextual effects such as surround suppression and crowding are often considered to be automatic processes that occur over fixed areas in the visual field. The final part of this work shows how changing the spatial layout, and consequently the perceptual organization, of the stimuli can dramatically reduce surround suppression and crowding effects, even in conditions where the current models would predict strong effects. Surround suppression and crowding seem to operate only within perceptually homogeneous areas, while stimuli that are perceptually separate, the ones that stand out, are not affected.

Luria (Luria, Cognitive development: Its cultural and social foundations, Harvard University Press, 1976) famously observed that people who never learnt to read and write do not perceive visual illusions. We conducted a conceptual replication of the Luria study of the effect of literacy on the processing of visual illusions. We designed two carefully controlled experiments with 161 participants with varying literacy levels ranging from complete illiterates to high literates in Chennai, India. Accuracy and reaction time in the identification of visual shape and color illusions and the identification of appropriate control images were measured. Separate statistical analyses of Experiments 1 and 2 as well as pooled analyses of both experiments do not provide any support for the notion that literacy affects the perception of visual illusions. Our large sample, carefully controlled study strongly suggests that literacy does not meaningfully affect the identification of visual illusions and raises some questions about other reports of cultural effects on illusion perception.

In addition to visual display, force-feedback will play an important role in interactive interface design for computers. Although the human visual system is generally more sensitive than haptics, the visual system is subject to optical illusions. In this study, we have conducted experiments to obtain visual and/or haptical sensitivity of recognition of the features of figures, such as the deformation of a circle or the bend of a line, under optical illusion. It was found that the figure which the subject judges to be a true circle or a line without bend is closer to the true figure, when using haptic exploration compared to that chosen by visual recognition. However, the probable error by haptics is larger than that by vision. Recognition using both haptics and vision causes conflict because of optical illusion, resulting in almost the same amount of errors as by vision alone.

Seizures originating in the occipital areas are relatively uncommon. They are usually characterized by visual hallucinations and illusions or other symptoms related to the eyes and vision. In a 54-year-old woman with occipital lobe epilepsy, complex visual hallucinations, illusions, and migraine-like headache constitute the major clinical manifestations. During focal status epilepticus, ictal electroencephalography revealed rhythmic focal spikes in the right occipital region, rapidly propagating to the right parietal and contralateral occipital areas. Ictal brain single-photon emission computed topography revealed hyperperfusion of the right occipital region. Using a full-field pattern-shift visual evoked potential (VEP) study, we found that the P100 responses on both sides were markedly attenuated in amplitude during occipital focal status epilepticus, whereas the latencies of the VEPs were normal. The amplitude and morphology of P100 responses on both sides, however, returned to the normal range 7 days after cessation of the seizures. In addition to clinical seizure semiology, scalp EEG, SPECT and neuroimaging studies, VEP studies may be used as a supplementary examination tool to provide further information in the patients with occipital lobe seizures or epilepsies.

Uncertainty in visual processes predicts geometrical optical illusions

Visual illusions affect both movement planning and on-line control: A multiple cue position on bias and goal-directed action

Chapter 6 Visual evoked potentials

Although the zebrafish has become an important model in visual neuroscience, little has been done to examine the processing of its higher visual centers. The purpose of this work was twofold. The first purpose was to examine the physiology of the zebrafish retinotectal system and its relationship to retinal physiology. Spectral sensitivity functions were derived from visually evoked tectal responses and these functions were compared to the functions of electroretinogram (ERG) responses obtained using the same stimulus conditions. The second purpose was to examine the recovery of visual functioning of the tectum following optic nerve damage. The optic nerves of adult zebrafish were damaged (crushed), and tectal visual processing was assessed following damage. The results showed that the spectral sensitivity functions based on the On-responses of the tectum and ERG were qualitatively similar. The functions based on each response type received similar cone contributions including both nonopponent and opponent contributions. However, the spectral sensitivity functions based on the Off-responses of the tectum and ERG differed. The results also showed that the zebrafish visual system is capable of neural regeneration. By 90 days following an optic nerve crush, the spectral sensitivity function based on the tectal On-response was similar to functions obtained from normal zebrafish. Although the tectal Off-response did recover, the spectral sensitivity based on the Off-response was not the same as the function of normal zebrafish. These results support the notion that different levels of the visual system process information differently and that the zebrafish visual system, like those of other lower vertebrates, is capable of functional regeneration.

The visual system is highly sensitive to spatial context for encoding luminance patterns. Context sensitivity inspired the proposal of many neural mechanisms for explaining the perception of luminance (brightness). Here we propose a novel computational model for estimating the brightness of many visual illusions. We hypothesize that many aspects of brightness can be explained by a dynamic filtering process that reduces the redundancy in edge representations on the one hand, while non-redundant activity is enhanced on the other. The dynamic filter is learned for each input image and implements context sensitivity. Dynamic filtering is applied to the responses of (model) complex cells in order to build a gain control map. The gain control map then acts on simple cell responses before they are used to create a brightness map via activity propagation. Our approach is successful in predicting many challenging visual illusions, including contrast effects, assimilation, and reverse contrast with the same set of model parameters.

The effects of screen luminance, contrast and saturation of HDR video presented on QLED display on visual system were investigated. Results showed that contrast and saturation, rather than luminance, influenced visual neural systems controlling eye movements, and affected subjective display quality and viewing preference.

The color appearance of a stimulus depends on the context in which it is viewed. Well-known examples of context effects include simultaneous color contrast and color constancy. In simultaneous contrast, the color immediately surrounding a test influences its appearance. In color constancy, the visual system adapts to the ambient illumination to keep surface color approximately constant. Color constancy is a context effect because the way that the visual system interprets the light reaching the eye depends on the context defined by the ambient illumination.To predict accurately the color appearance of stimuli rendered on a CRT monitor, we need a theory of color context effects that applies to such stimuli. Simultaneous contrast suggests that the color perceived at a particular monitor location may vary with the immediate context provided by the image at other locations on the monitor (the monitor context). Color constancy suggests that the color appearance of stimuli displayed on a monitor may vary with the ambient illumination of the room in which the monitor is viewed (the illumination context), at least if images from a monitor are processed by the visual system in the same way as reflective surfaces.In this paper, we report initial experiments designed to measure psychophysically how the monitor context and the illumination context influence the appearance of stimuli presented on CRT color monitors. Our emphasis, however, is on the effect of the illumination context.

Interactive visual clustering allows the user to be involved into the clustering through visualizing process via interactive visualization. In order to perform effective interaction in the visual clustering process, the efficient feature selection methods are required to identify the most dominating features. Hence, in this paper an improved visual clustering system is proposed using an efficient feature selection method. The relevant features for visual clustering are identified based on their contribution to the entropy. Experimental results show that the proposed method works well in finding the best cluster.