In crowding, perception of a target is strongly deteriorated by nearby elements. Crowding is often explained by pooling models predicting that adding flankers increases crowding. In contrast, the centroid hypothesis proposes that adding flankers decreases crowding--"bigger is better." In foveal vision, we have recently shown that adding flankers can increase or decrease crowding depending on whether the target groups or ungroups from the flankers. We have further shown how configural effects, such as good and global Gestalt, determine crowding. Foveal and peripheral crowding do not always reveal the same characteristics. Here, we show that the very same grouping and Gestalt results of foveal vision are also found in the periphery. These results can neither be explained by simple pooling nor by centroid models. We discuss when bigger is better and how grouping might shape crowding.

Observers perceive objects in the world as stable over space and time, even though the visual experience of those objects is often discontinuous and distorted due to masking, occlusion, camouflage, or noise. How are we able to easily and quickly achieve stable perception in spite of this constantly changing visual input? It was previously shown that observers experience serial dependence in the perception of features and objects, an effect that extends up to 15 seconds back in time. Here, we asked whether the visual system utilizes an object's prior physical location to inform future position assignments in order to maximize location stability of an object over time. To test this, we presented subjects with small targets at random angular locations relative to central fixation in the peripheral visual field. Subjects reported the perceived location of the target on each trial by adjusting a cursor's position to match its location. Subjects made consistent errors when reporting the perceived position of the target on the current trial, mislocalizing it toward the position of the target in the preceding two trials (Experiment 1). This pull in position perception occurred even when a response was not required on the previous trial (Experiment 2). In addition, we show that serial dependence in perceived position occurs immediately after stimulus presentation, and it is a fast stabilization mechanism that does not require a delay (Experiment 3). This indicates that serial dependence occurs for position representations and facilitates the stable perception of objects in space. Taken together with previous work, our results show that serial dependence occurs at many stages of visual processing, from initial position assignment to object categorization.

In crowding, the perception of a target strongly deteriorates when neighboring elements are presented. Crowding is usually assumed to have the following characteristics. (a) Crowding is determined only by nearby elements within a restricted region around the target (Bouma's law). (b) Increasing the number of flankers can only deteriorate performance. (c) Target-flanker interference is feature-specific. These characteristics are usually explained by pooling models, which are well in the spirit of classic models of object recognition. In this review, we summarize recent findings showing that crowding is not determined by the above characteristics, thus, challenging most models of crowding. We propose that the spatial configuration across the entire visual field determines crowding. Only when one understands how all elements of a visual scene group with each other, can one determine crowding strength. We put forward the hypothesis that appearance (i.e., how stimuli look) is a good predictor for crowding, because both crowding and appearance reflect the output of recurrent processing rather than interactions during the initial phase of visual processing.

In object recognition, features are thought to be processed in a hierarchical fashion from low-level analysis (edges and lines) to complex figural processing (shapes and objects). Here, we show that figural processing determines low-level processing. Vernier offset discrimination strongly deteriorated when we embedded a vernier in a square. This is a classic crowding effect. Surprisingly, crowding almost disappeared when additional squares were added. We propose that figural interactions between the squares precede low-level suppression of the vernier by the single square, contrary to hierarchical models of object recognition.

We are continuously surrounded by a noisy and ever-changing environment. Instead of analyzing all the elements in a scene, our visual system has the ability to compress an enormous amount of visual information into ensemble representations, such as perceiving a forest instead of every single tree. Still, it is unclear why such complex scenes appear to be the same from moment to moment despite fluctuations, noise, and discontinuities in retinal images. The general effects of change blindness are usually thought to stabilize scene perception, making us unaware of minor inconsistencies between scenes. Here, we propose an alternative, that stable scene perception is actively achieved by the visual system through global serial dependencies: the appearance of scene gist is sequentially dependent on the gist perceived in previous moments. To test this hypothesis, we used summary statistical information as a proxy for “gist” level, global information in a scene. We found evidence for serial dependence in summary statistical representations. Furthermore, we show that this kind of serial dependence occurs at the ensemble level, where local elements are already merged into global representations. Taken together, our results provide a mechanism through which serial dependence can promote the apparent consistency of scenes over time.