Visual Hierarchy Research Articles

Visual working memory contaminates perception

Indirect evidence suggests that the contents of visual working memory may be maintained within sensory areas early in the visual hierarchy. We tested this possibility using a well-studied motion repulsion phenomenon in which perception of one direction of motion is distorted when another direction of motion is viewed simultaneously. We found that observers misperceived the actual direction of motion of a single motion stimulus if, while viewing that stimulus, they were holding a different motion direction in visual working memory. Control experiments showed that none of a variety of alternative explanations could account for this repulsion effect induced by working memory. Our findings provide compelling evidence that visual working memory representations directly interact with the same neural mechanisms as those involved in processing basic sensory events.

Concordance between perceptual and categorical repetition effects in the ventral visual stream

The process of object categorization is an integral part of human cognition. In the present study, we have used a repetition suppression paradigm to determine the degree to which the ventral visual cortex is sensitive to categorical relationships. By using images of animals and tools, suppression across perceptual (stimulus level) and categorical repetitions (basic level and domain level) was compared and contrasted across the domain-selective and hierarchical organization of the ventral visual stream. Both perceptual and categorical repetition effects were insensitive to domain-selective tuning, with suppression most prominent in regions responding maximally to images, irrespective of stimulus domain. Likewise, both perceptual and categorical repetition produced overlapping suppression across multiple regions of the visual hierarchy. Some divergent patterns were observed. The right superior temporal sulcus demonstrated repetition suppression only at the basic level (different examples of the same basic object), and the right anterior fusiform gyrus was sensitive to direct stimulus repetition but not basic-level categorical repetition. Because of the high concordance between the response profiles of perceptual and categorical repetition effects, we conclude they arise from a common cognitive mechanism.

Hirarkhi Visual sebagai Faktor Kesesatan Konsumen pada Desain Kemasan Samar Identitas

Packaging vague identity, is the packaging that does not give clear information about the contents of the packed product, in this case are specific to the product needs of the household / consumer products, often everyday, more obvious when you're shopping at the supermarket, sensation very stunning visual eye, the colors, images and shapes capable of stopping the views of prospective consumers in packaging that 'teasing', it was due to good aesthetic qualities, but in reality many packaging designs negligent in giving the perception of 'immediately' to the identity of the contents of the packed product , this issue becomes crucial because it can be misleading or wrong perception of users, by taking random samples of products circulating in the community, trying to describe and analyze a simple through the principle of Visual Communication Design, hoping the result will remind the designers more aware of packaging labels will set out the communication function in media packaging, to provide specific information with respect to visual hierarchy to yield a clear identity of the product packaged.

Face inversion reduces the persistence of global form and its neural correlates.

Face inversion produces a detrimental effect on face recognition. The extent to which the inversion of faces and other kinds of objects influences the perceptual binding of visual information into global forms is not known. We used a behavioral method and functional MRI (fMRI) to measure the effect of face inversion on visual persistence, a type of perceptual memory that reflects sustained awareness of global form. We found that upright faces persisted longer than inverted versions of the same images; we observed a similar effect of inversion on the persistence of animal stimuli. This effect of inversion on persistence was evident in sustained fMRI activity throughout the ventral visual hierarchy, including the lateral occipital area (LO), two face-selective visual areas—the fusiform face area (FFA) and the occipital face area (OFA)—and several early visual areas. V1 showed the same initial fMRI activation to upright and inverted forms but this activation lasted longer for upright stimuli. The inversion effect on persistence-related fMRI activity in V1 and other retinotopic visual areas demonstrates that higher-tier visual areas influence early visual processing via feedback. This feedback effect on figure-ground processing is sensitive to the orientation of the figure.

Sparse coding in striate and extrastriate visual cortex

Theoretical studies of mammalian cortex argue that efficient neural codes should be sparse. However, theoretical and experimental studies have used different definitions of the term "sparse" leading to three assumptions about the nature of sparse codes. First, codes that have high lifetime sparseness require few action potentials. Second, lifetime-sparse codes are also population-sparse. Third, neural codes are optimized to maximize lifetime sparseness. Here, we examine these assumptions in detail and test their validity in primate visual cortex. We show that lifetime and population sparseness are not necessarily correlated and that a code may have high lifetime sparseness regardless of how many action potentials it uses. We measure lifetime sparseness during presentation of natural images in three areas of macaque visual cortex, V1, V2, and V4. We find that lifetime sparseness does not increase across the visual hierarchy. This suggests that the neural code is not simply optimized to maximize lifetime sparseness. We also find that firing rates during a challenging visual task are higher than theoretical values based on metabolic limits and that responses in V1, V2, and V4 are well-described by exponential distributions. These findings are consistent with the hypothesis that neurons are optimized to maximize information transmission subject to metabolic constraints on mean firing rate.

Analysis of Thematic Maps Published in Two Geographical Journals in the Twentieth Century

This article examines changes in the design of thematic maps in two geographical journals (the Annals of the Association of American Geographers and The Geographical Journal) over the course of the twentieth century. We analyzed the design of thematic maps using both qualitative and quantitative content analyses. The qualitative content analysis involved writing positive and negative comments pertaining to eleven map design elements. For the quantitative content analysis, we created a set of seventeen items based on many of these same map design elements, but for each item there was a fixed set of possible nominal or ordinal-level responses. We also rated the overall effectiveness of map design using a ten-point scale. The overall design rating revealed a significant, albeit gradual, improvement in map design over the twentieth century, with considerable variation for individual years. The quantitative content analysis suggested that the improvement in map design over time was a function of improved readability and visual hierarchy and to some extent an improved logic of symbology (the latter was not significant over time). Perhaps more interesting were the summary statistics for certain map design elements. For instance, a source was not included on the majority of maps even though we felt that the maps could have been interpreted more effectively if a source were included. Another interesting finding was that thematic maps frequently fell in to what we describe as a miscellaneous category. Choropleth, dot, and other familiar thematic map symbolization types were much less common and their frequency varied considerably from year to year. Overall, our results are disconcerting because the quality of map design in these journals did not reflect our discipline's long interest in mapping and the importance of cartography to geography.

Stimulus-Dependent Modulation of Suppressive Influences in MT

Surround suppression contributes to important functions in visual processing, such as figure-ground segregation; however, this benefit comes at the cost of decreased neuronal sensitivity. Studies of receptive fields at several levels of the visual hierarchy have demonstrated that surround suppression is reduced for low contrast stimuli, thereby improving neuronal sensitivity. We investigated whether this reduction of surround suppression reflects a general processing strategy to boost sensitivity for weak signals by summing them over a larger region of the visual field (spatial integration) or if the reduction is limited to specialized stimulus conditions. To do this, we used stochastic motion stimuli to measure surround suppression in area MT of alert macaque monkeys. While varying stimulus size we also varied the strength of two other critical stimulus features: contrast and coherence (i.e., the proportion of dots moving in the preferred direction of the neuron). We found that reducing stimulus contrast weakened surround suppression, but reducing stimulus coherence had the opposite effect, indicating that diminished surround suppression is not a universal response to stimuli of low signal-to-noise. This can be partially explained by our other finding, which is that surrounds in MT are very broadly direction tuned. Instead of producing a reduction of surround suppression that would improve the ability of the neuron to integrate preferred direction motion, low coherence stimuli activated the broadly tuned surrounds relatively better than the centers, which are generally more direction selective. Our results are consistent with a normalization mechanism of surround suppression that pools broadly across multiple stimulus dimensions.

Expectation and Surprise Determine Neural Population Responses in the Ventral Visual Stream

Visual cortex is traditionally viewed as a hierarchy of neural feature detectors, with neural population responses being driven by bottom-up stimulus features. Conversely, "predictive coding" models propose that each stage of the visual hierarchy harbors two computationally distinct classes of processing unit: representational units that encode the conditional probability of a stimulus and provide predictions to the next lower level; and error units that encode the mismatch between predictions and bottom-up evidence, and forward prediction error to the next higher level. Predictive coding therefore suggests that neural population responses in category-selective visual regions, like the fusiform face area (FFA), reflect a summation of activity related to prediction ("face expectation") and prediction error ("face surprise"), rather than a homogenous feature detection response. We tested the rival hypotheses of the feature detection and predictive coding models by collecting functional magnetic resonance imaging data from the FFA while independently varying both stimulus features (faces vs houses) and subjects' perceptual expectations regarding those features (low vs medium vs high face expectation). The effects of stimulus and expectation factors interacted, whereby FFA activity elicited by face and house stimuli was indistinguishable under high face expectation and maximally differentiated under low face expectation. Using computational modeling, we show that these data can be explained by predictive coding but not by feature detection models, even when the latter are augmented with attentional mechanisms. Thus, population responses in the ventral visual stream appear to be determined by feature expectation and surprise rather than by stimulus features per se.

Eye-centered encoding of visual space in scene-selective regions

We used functional magnetic resonance imaging (fMRI) to investigate the reference frames used to encode visual information in scene-responsive cortical regions. At early levels of the cortical visual hierarchy, neurons possess spatially selective receptive fields (RFs) that are yoked to specific locations on the retina. In lieu of this eye-centered organization, we speculated that visual areas implicated in scene processing, such as the parahippocampal place area (PPA), the retrosplenial complex (RSC), and transverse occipital sulcus (TOS) might instead possess RFs defined in head-, body-, or world-centered reference frames. To test this, we scanned subjects while they viewed objects and scenes presented at four screen locations while they maintained fixation at one of three possible gaze positions. We then examined response profiles as a function of either fixation-referenced or screen-referenced position. Contrary to our prediction, the PPA and TOS exhibited position-response curves that moved with the fixation point rather than being anchored to the screen, a pattern indicative of eye-centered encoding. RSC, on the other hand, did not exhibit a position-response curve in either reference frame. By showing an important commonality between the PPA/TOS and other visually responsive regions, the results emphasize the critical involvement of these regions in the visual analysis of scenes.

Perceptual learning of parametric face categories leads to the integration of high-level class-based information but not to high-level pop-out

To date, the relative contribution of the different levels of the visual hierarchy during perceptual decisions remains unclear. Typical models of visual processing, with the reverse hierarchy theory (RHT) as a prominent example, strongly emphasize the role of higher levels and interpret lower levels as sequence of simple feature detectors. Here, we investigate this issue based on two analyses. Using a novel combination of perceptual learning based on two classes of parametric faces and a subsequent odd-one-out paradigm, we first test a vital prediction of RHT: high-level pop-out. With this experimental approach, we overcome the low-level confounds of previous studies while still introducing distinct high-level representations. Contrary to previous findings, our analyses show that there is no high-level pop-out, despite very early, near-perfect classification accuracy and extensive training of our subjects. Second, we explore the underlying form of category representation during subsequent stages of perceptual training. This is accomplished by including class-external and class-internal target-distractor combinations. Whereas the subjects' responses during the first sessions are best explained instance-based and dependent on low-level metric differences, later patterns exhibit the inclusion of high-level, class-based information that is independent of target-stimulus similarity. Finally, we show that the utilized level of information is highly task-dependent.

A model of primate visual cortex based on category-specific redundancies in natural images

Neurophysiological and computational studies have proposed that properties of natural images have a prominent role in shaping selectivity of neurons in the visual cortex. An important property of natural images that has been studied extensively is the inherent redundancy in these images. In this paper, the concept of category-specific redundancies is introduced to describe the complex pattern of dependencies between responses of linear filters to natural images. It is proposed that structural similarities between images of different object categories result in dependencies between responses of linear filters in different spatial scales. It is also proposed that the brain gradually removes these dependencies in different areas of the ventral visual hierarchy to provide a more efficient representation of its sensory input. The authors proposed a model to remove these redundancies and trained it with a set of natural images using general learning rules that are developed to remove dependencies between responses of neighbouring neurons. Results of experiments demonstrate the close resemblance of neuronal selectivity between different layers of the model and their corresponding visual areas.

Neural Mechanisms of Motion Detection, Integration, and Segregation: From Biology to Artificial Image Processing Systems

Object motion can be measured locally by neurons at different stages of the visual hierarchy. Depending on the size of their receptive field apertures they measure either localized or more global configurationally spatiotemporal information. In the visual cortex information processing is based on the mutual interaction of neuronal activities at different levels of representation and scales. Here, we utilize such principles and propose a framework for modelling neural computational mechanisms of motion in primates using biologically inspired principles. In particular, we investigate motion detection and integration in cortical areas V1 and MT utilizing feedforward and modulating feedback processing and the automatic gain control through center-surround interaction and activity normalization. We demonstrate that the model framework is capable of reproducing challenging data from experimental investigations in psychophysics and physiology. Furthermore, the model is also demonstrated to successfully deal with realistic image sequences from benchmark databases and technical applications.

A New Viewpoint on Faces

Part of the brain's visual hierarchy appears to be specialized for recognizing faces from any viewpoint.

69 Computational modeling and molecular optimization of stabilized alpha-helical peptides targeting NOTCH-CSL transcriptional complexes

Recovery to normal or near normal visual acuity after an optic neuritis episode is common, despite frequent persistence of conduction abnormalities, evident in prolonged visual evoked potential (VEP) latencies. Improvement of visual function is commonly attributed to peripheral nerve recovery. However, central reorganization processes may also be involved. To assess this, we compared the patterns of fMRI activation, elicited by stimulation of the affected and the normal eye, along the visual cortical hierarchy. Activation was assessed in 8 subjects, which recovered clinically from an episode of optic neuritis but still had prolonged VEP latencies. In all patients, reduced fMRI activation was seen in V1 during stimulation of the affected eye, compared to the normal eye. The fMRI signal difference decreased in magnitude with progression along the visual hierarchy, and in some regions within the lateral occipital complex even showed the opposite preference (for the affected eye). These results may indicate a built-in robustness of the object-related areas to disruption of the visual input. Alternatively, it could reflect an adaptive functional reorganization of the cortical response to an abnormal input.

Spatially extensive summation of contrast energy is revealed by contrast detection of micro-pattern textures

Vision must analyze the retinal image over both small and large areas to represent fine-scale spatial details and extensive textures. The long-range neuronal convergence that this implies might lead us to expect that contrast sensitivity should improve markedly with the contrast area of the image. But this is at odds with the orthodox view that contrast sensitivity is determined merely by probability summation over local independent detectors. To address this puzzle, I aimed to assess the summation of luminance contrast without the confounding influence of area-dependent internal noise. I measured contrast detection thresholds for novel Battenberg stimuli that had identical overall dimensions (to clamp the aggregation of noise) but were constructed from either dense or sparse arrays of micro-patterns. The results unveiled a three-stage visual hierarchy of contrast summation involving (i) spatial filtering, (ii) long-range summation of coherent textures, and (iii) pooling across orthogonal textures. Linear summation over local energy detectors was spatially extensive (as much as 16 cycles) at Stage 2, but the resulting model is also consistent with earlier classical results of contrast summation (J. G. Robson & N. Graham, 1981), where co-aggregation of internal noise has obscured these long-range interactions.

Top-down modulations in the visual form pathway revealed with dynamic causal modeling.

Perception entails interactions between activated brain visual areas and the records of previous sensations, allowing for processes like figure–ground segregation and object recognition. The aim of this study was to characterize top-down effects that originate in the visual cortex and that are involved in the generation and perception of form. We performed a functional magnetic resonance imaging experiment, where subjects viewed 3 groups of stimuli comprising oriented lines with different levels of recognizable high-order structure (none, collinearity, and meaning). Our results showed that recognizable stimuli cause larger activations in anterior visual and frontal areas. In contrast, when stimuli are random or unrecognizable, activations are greater in posterior visual areas, following a hierarchical organization where areas V1/V2 were less active with “collinearity” and the middle occipital cortex was less active with “meaning.” An effective connectivity analysis using dynamic causal modeling showed that high-order visual form engages higher visual areas that generate top-down signals, from multiple levels of the visual hierarchy. These results are consistent with a model in which if a stimulus has recognizable attributes, such as collinearity and meaning, the areas specialized for processing these attributes send top-down messages to the lower levels to facilitate more efficient encoding of visual form.

Faith Tweets: Ambient Religious Communication and Microblogging Rituals

Faith Tweets: Ambient Religious Communication and Microblogging Rituals

Aftereffect of adaptation to glass patterns

Our visual systems constantly adapt their representation of the environment to match the prevailing input. Adaptation phenomena provide striking examples of perceptual plasticity and offer valuable insight into the mechanisms of sensory coding. Here, we describe an aftereffect of adaptation to a spatially structured image whereby an unstructured test stimulus takes on illusory structure locally perpendicular to that of the adaptor. Objective measurement of the strength of the aftereffect for different patterns suggests a neural locus of adaptation prior to the extraction of complex form in the visual processing hierarchy, probably at the level of primary visual cortex. This view is supported by further experiments showing that the aftereffect exhibits partial interocular transfer but complete transfer across opposite contrast polarities. However, the aftereffect does show weak position invariance, suggesting that adaptation at higher levels of the visual system may also contribute to the effect.

Cognitively Inspired and Perceptually Salient Graphic Displays for Efficient Spatial Inference Making

Developing a visual hierarchy in map displays that is congruent with thematic levels of relevance is a fundamental cartographic design task. Cartographers employ a set of visual variables (e.g., size, color hue, color value, orientation, etc.) for 2-D, static maps to systematically match levels of thematically relevant information to a perceptual hierarchy based on figure–ground relationships. In this article, we empirically investigate the relationship of thematic relevance and perceptual salience in static weather map displays. We are particularly interested in how novices' viewing patterns are modified when thematically relevant items are made perceptually more salient through design. In essence, we are asking whether perceptually salient elements draw novice viewers' attention to thematically relevant information, whether or not users have domain knowledge. In a factorial experiment, we ask novice participants to evaluate the wind direction in weather maps before and after training all participants on meteorological principles. Our empirical results suggest that display design (i.e., saliency) does not influence the accuracy of response, whether participants have prior knowledge or not (i.e., training). Analysis of the eye-movement patterns, however, suggests that display design does affect viewing behavior and response time. These findings provide rare empirical evidence for generally accepted design practices within the cartographic community (e.g., the effects of visual variables). We chose weather map displays as one typical example of commonly used maps for our study, but the methods employed are generic enough to be applicable to any spatial display (static or interactive) that might be produced by GIScientists, cartographers, geographic information system (GIS) practitioners, and others.

Criteria for optimizing cortical hierarchies with continuous ranges

In a recent paper (Reid et al., 2009) we introduced a method to calculate optimal hierarchies in the visual network that utilizes continuous, rather than discrete, hierarchical levels, and permits a range of acceptable values rather than attempting to fit fixed hierarchical distances. There, to obtain a hierarchy, the sum of deviations from the constraints that define the hierarchy was minimized using linear optimization. In the short time since publication of that paper we noticed that many colleagues misinterpreted the meaning of the term “optimal hierarchy”. In particular, a majority of them were under the impression that there was perhaps only one optimal hierarchy, but a substantial difficulty in finding that one. However, there is not only more than one optimal hierarchy but also more than one option for defining optimality. Continuing the line of this work we look at additional options for optimizing the visual hierarchy: minimizing the number of violated constraints and minimizing the maximal size of a constraint violation using linear optimization and mixed integer programming. The implementation of both optimization criteria is explained in detail. In addition, using constraint sets based on the data from Felleman and Van Essen (1991), optimal hierarchies for the visual network are calculated for both optimization methods.