The influence of the tested item on serial dependence in perceptual decisions.

Serial dependence in vision reflects how perceptual decisions can be biased by what we have recently perceived. Serial dependence studies test single items' effects on perceptual decisions. However, our visual world contains multiple objects at any given moment, so it's important to understand how past experiences affect not only a single object but also perception in a more general sense. Here we asked the question: What effect does a single item have when there is more than one subsequently presented test item? We displayed a single line (inducer) at the screen center, then either a single test-line or two simultaneous test-lines, varying in orientation space to the inducer. Next, participants reported test-line orientation using a left or right located response circle (to indicate which test-line should be reported). The results demonstrated that the inducer influenced subsequent perceptual judgments of a test-line even when two test-lines were presented. Distant items caused repulsive serial dependence, while close items caused attractive serial dependence. This shows how a single inducer can influence test-line judgments, even when two test-lines are presented, and can produce attractive and repulsive serial dependence biases when the item to report is revealed after it has disappeared.

Extracting statistical information about shapes in the visual environment.

It is well known that observers can use so-called summary statistics of visual ensembles to simplify perceptual processing. The assumption has been that instead of representing feature distributions in detail the visual system extracts the mean and variance of visual ensembles. But recent evidence from implicit testing using a method called feature distribution learning showed that far more detail of the distributions is retained than the summary statistic literature indicates. Observers also encode higher-order statistics such as the kurtosis of feature distributions of orientation and color. But this sort of learning has not been shown for more intricate aspects of visual information. Here we tested the learning of distractor ensembles for shape, using the feature distribution learning method. Using a linearized circular shape space, we found that learning of detailed distributions of shape does not occur for this shape space while observers were able to learn the mean and range of the distributions. Previous demonstrations of feature distribution learning involved simpler feature dimensions than the more complex shape space tested here, and our findings may therefore reveal important boundary conditions of feature distribution learning.

Temporal integration of feature probability distributions.

Humans are surprisingly good at learning the statistical characteristics of their visual environment. Recent studies have revealed that not only can the visual system learn repeated features of visual search distractors, but also their actual probability distributions. Search times were determined by the frequency of distractor features over consecutive search trials. The search displays applied in these studies involved many exemplars of distractors on each trial and while there is clear evidence that feature distributions can be learned from large distractor sets, it is less clear if distributions are well learned for single targets presented on each trial. Here, we investigated potential learning of probability distributions of single targets during visual search. Over blocks of trials, observers searched for an oddly colored target that was drawn from either a Gaussian or a uniform distribution. Search times for the different target colors were clearly influenced by the probability of that feature within trial blocks. The same search targets, coming from the extremes of the two distributions were found significantly slower during the blocks where the targets were drawn from a Gaussian distribution than from a uniform distribution indicating that observers were sensitive to the target probability determined by the distribution shape. In Experiment 2, we replicated the effect using binned distributions and revealed the limitations of encoding complex target distributions. Our results demonstrate detailed internal representations of target feature distributions and that the visual system integrates probability distributions of target colors over surprisingly long trial sequences.

What kind of empirical evidence is needed for probabilistic mental representations? An example from visual perception.

Recent accounts of perception and cognition propose that the brain represents information probabilistically. While this assumption is common, empirical support for such probabilistic representations in perception has recently been criticized. Here, we evaluate these criticisms and present an account based on a recently developed psychophysical methodology, Feature Distribution Learning (FDL), which provides promising evidence for probabilistic representations by avoiding these criticisms. The method uses priming and role-reversal effects in visual search. Observers' search times reveal the structure of perceptual representations, in which the probability distribution of distractor features is encoded. We explain how FDL results provide evidence for a stronger notion of representation that relies on structural correspondence between stimulus uncertainty and perceptual representations, rather than a mere co-variation between the two. Moreover, such an account allows us to demonstrate what kind of empirical evidence is needed to support probabilistic representations as posited in current probabilistic Bayesian theories of perception.

You see what you look for: Targets and distractors in visual search can cause opposing serial dependencies.

Visual perception is, at any given moment, strongly influenced by its temporal context-what stimuli have recently been perceived and in what surroundings. We have previously shown that to-be-ignored items produce a bias upon subsequent perceptual decisions that acts in parallel with other biases induced by attended items. However, our previous investigations were confined to biases upon the perceived orientation of a visual search target, and it is unclear whether these biases influence perceptual decisions in a more general sense. Here, we test whether the biases from visual search targets and distractors affect the perceived orientation of a neutral test line, one that is neither a target nor a distractor. To do so, we asked participants to search for an oddly oriented line among distractors and report its location for a few trials and next presented a test line irrelevant to the search task. Participants were asked to report the orientation of the test line. Our results indicate that in tasks involving visual search, targets induce a positive bias upon a neutral test line if their orientations are similar, whereas distractors produce an attractive bias for similar test lines and a repulsive bias if the orientations of the test line and the average orientation of the distractors are far apart in feature space. In sum, our results show that both attentional role and proximity in feature space between previous and current stimuli determine the direction of biases in perceptual decisions.

Dissociating implicit and explicit ensemble representations reveals the limits of visual perception and the richness of behavior.

Our senses provide us with a rich experience of a detailed visual world, yet the empirical results seem to suggest severe limitations on our ability to perceive and remember. In recent attempts to reconcile the contradiction between what is experienced and what can be reported, it has been argued that the visual world is condensed to a set of summary statistics, explaining both the rich experience and the sparse reports. Here, we show that explicit reports of summary statistics underestimate the richness of ensemble perception. Our observers searched for an odd-one-out target among heterogeneous distractors and their representation of distractor characteristics was tested explicitly or implicitly. Observers could explicitly distinguish distractor sets with different mean and variance, but not differently-shaped probability distributions. In contrast, the implicit assessment revealed that the visual system encodes the mean, the variance, and even the shape of feature distributions. Furthermore, explicit measures had common noise sources that distinguished them from implicit measures. This suggests that explicit judgments of stimulus ensembles underestimate the richness of visual representations. We conclude that feature distributions are encoded in rich detail and can guide behavior implicitly, even when the information available for explicit summary judgments is coarse and limited.

Optimizing perception: Attended and ignored stimuli create opposing perceptual biases.

Humans have remarkable abilities to construct a stable visual world from continuously changing input. There is increasing evidence that momentary visual input blends with previous input to preserve perceptual continuity. Most studies have shown that such influences can be traced to characteristics of the attended object at a given moment. Little is known about the role of ignored stimuli in creating this continuity. This is important since while some input is selected for processing, other input must be actively ignored for efficient selection of the task-relevant stimuli. We asked whether attended targets and actively ignored distractor stimuli in an odd-one-out search task would bias observers' perception differently. Our observers searched for an oddly oriented line among distractors and were occasionally asked to report the orientation of the last visual search target they saw in an adjustment task. Our results show that at least two opposite biases from past stimuli influence current perception: A positive bias caused by serial dependence pulls perception of the target toward the previous target features, while a negative bias induced by the to-be-ignored distractor features pushes perception of the target away from the distractor distribution. Our results suggest that to-be-ignored items produce a perceptual bias that acts in parallel with other biases induced by attended items to optimize perception. Our results are the first to demonstrate how actively ignored information facilitates continuity in visual perception.

Representing color and orientation ensembles: Can observers learn multiple feature distributions?

Objects have a variety of different features that can be represented as probability distributions. Recent findings show that in addition to mean and variance, the visual system can also encode the shape of feature distributions for features like color or orientation. In an odd-one-out search task we investigated observers' ability to encode two feature distributions simultaneously. Our stimuli were defined by two distinct features (color and orientation) while only one was relevant to the search task. We investigated whether the irrelevant feature distribution influences learning of the task-relevant distribution and whether observers also encode the irrelevant distribution. Although considerable learning of feature distributions occurred, especially for color, our results also suggest that adding a second irrelevant feature distribution negatively affected the encoding of the relevant one and that little learning of the irrelevant distribution occurred. There was also an asymmetry between the two different features: Searching for the oddly oriented target was more difficult than searching for the oddly colored target, which was reflected in worse learning of the color distribution. Overall, the results demonstrate that it is possible to encode information about two feature distributions simultaneously but also reveal considerable limits to this encoding.

The dress and individual differences in the perception of surface properties.

This study investigates systematic individual differences in the way observers perceive different kinds of surface properties and their relationship to the dress, which shows striking individual differences in colour perception. We tested whether these individual differences have a common source, namely differences in perceptual strategies according to which observers attribute features in two-dimensional images to surfaces or to their illumination. First, we reanalysed data from two previous experiments on the dress and colour constancy. The comparison of the two experiments revealed that the colour perception of the dress is strongly related to individual differences in colour constancy. Second, two online surveys measured individual differences in the perception of colour-ambiguous images including the dress, in colour constancy, in gloss perception, in the subjective grey-point, in colour naming, and in the perception of an image with ambiguous shading. The results of the surveys replicated and extended previous findings according to which individual differences in the colour perception of the dress are due to implicit assumptions about the illumination. However, results also showed that the individual differences for other phenomena were independent of the dress and of each other. Overall, these results suggest that the striking individual differences in dress colour perception are due to individual differences in the interpretation of illumination cues to achieve colour constancy. At the same time, they undermine the idea of an overall perceptual strategy that encompasses other phenomena more generally related to the interpretation of illumination and surface properties.

Contextual effects on real bicolored glossy surfaces.

The material property of glossiness, which is attributed to many objects in our daily life, is physically independent of the objects' color. However, perceived glossiness can change with the contrast between the highlight and the area around the specular highlight. Hitherto, experiments mainly investigated gloss on unicolored surfaces. It is well known that the context in which a surface is embedded can influence its perceived lightness. Here we investigated whether similar contextual effects exist also for gloss perception by presenting single surfaces containing two different colors. We tested the influence of the second color on participants' gloss judgments with both real surfaces and photographs of those surfaces. In both conditions, participants were influenced by the second color on the surface even though they were asked to ignore it. We found contrasting contextual effects on the bicolored surfaces. However, when explicitly asked to rate the global gloss on the bicolored surfaces, participants took both parts of the surface equally into account.

A Glossy Simultaneous Contrast: Conjoint Measurements of Gloss and Lightness.

Interactions between the albedo and the gloss on a surface are commonplace. Darker surfaces are perceived glossier (contrast gloss) than lighter surfaces and darker backgrounds can enhance perceived lightness of surfaces. We used maximum likelihood conjoint measurements to simultaneously quantify the strength of those effects. We quantified the extent to which albedo can influence perceived gloss and physical gloss can influence perceived lightness. We modeled the contribution of lightness and gloss and found that increasing lightness reduced perceived gloss by about 32% whereas gloss had a much weaker influence on perceived lightness of about 12%. Moreover, we also investigated how different backgrounds contribute to the perception of lightness and gloss of a surface placed in front. We found that a glossy background reduces slightly perceived lightness of the center and simultaneously enhances its perceived gloss. Lighter backgrounds reduce perceived gloss and perceived lightness. Conjoint measurements lead us to a better understanding of the contextual effects in gloss and lightness perception. Not only do we confirm the importance of contrast in gloss perception and the reduction of the simultaneous contrast with glossy backgrounds, but we also quantify precisely the strength of those effects.

Gaze movements and spatial working memory in collision avoidance: a traffic intersection task.

Street crossing under traffic is an everyday activity including collision detection as well as avoidance of objects in the path of motion. Such tasks demand extraction and representation of spatio-temporal information about relevant obstacles in an optimized format. Relevant task information is extracted visually by the use of gaze movements and represented in spatial working memory. In a virtual reality traffic intersection task, subjects are confronted with a two-lane intersection where cars are appearing with different frequencies, corresponding to high and low traffic densities. Under free observation and exploration of the scenery (using unrestricted eye and head movements) the overall task for the subjects was to predict the potential-of-collision (POC) of the cars or to adjust an adequate driving speed in order to cross the intersection without collision (i.e., to find the free space for crossing). In a series of experiments, gaze movement parameters, task performance, and the representation of car positions within working memory at distinct time points were assessed in normal subjects as well as in neurological patients suffering from homonymous hemianopia. In the following, we review the findings of these experiments together with other studies and provide a new perspective of the role of gaze behavior and spatial memory in collision detection and avoidance, focusing on the following questions: (1) which sensory variables can be identified supporting adequate collision detection? (2) How do gaze movements and working memory contribute to collision avoidance when multiple moving objects are present and (3) how do they correlate with task performance? (4) How do patients with homonymous visual field defects (HVFDs) use gaze movements and working memory to compensate for visual field loss? In conclusion, we extend the theory of collision detection and avoidance in the case of multiple moving objects and provide a new perspective on the combined operation of external (bottom-up) and internal (top-down) cues in a traffic intersection task.