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Abstract When a piece of fruit is in a bowl, and the bowl is on a table, we appreciate not only the individual objects and their features, but also the relations containment and support, which abstract away from the particular objects involved. Independent representation of roles (e.g., containers vs. supporters) and “fillers” of those roles (e.g., bowls vs. cups, tables vs. chairs) is a core principle of language and higher-level reasoning. But does such role-filler independence also arise in automatic visual processing? Here, we show that it does, by exploring a surprising error that such independence can produce. In four experiments, participants saw a stream of images containing different objects arranged in force-dynamic relations—e.g., a phone contained in a basket, a marker resting on a garbage can, or a knife sitting in a cup. Participants had to respond to a single target image (e.g., a phone in a basket) within a stream of distractors presented under time constraints. Surprisingly, even though participants completed this task quickly and accurately, they false-alarmed more often to images matching the target’s relational category than to those that did not—even when those images involved completely different objects. In other words, participants searching for a phone in a basket were more likely to mistakenly respond to a knife in a cup than to a marker on a garbage can. Follow-up experiments ruled out strategic responses and also controlled for various confounding image features. We suggest that visual processing represents relations abstractly, in ways that separate roles from fillers. 

Memory often fills in what is not there. A striking example of this is boundary extension, whereby observers mistakenly recall a view that extends beyond what was seen. However, not all visual memories extend in this way, which suggests that this process depends on specific scene properties. What factors determine when visual memories will include details that go beyond perceptual experience? Here, seven experiments (N = 1,100 adults) explored whether spatial scale—specifically, perceived viewing distance—drives boundary extension. We created fake miniatures by exploiting tilt shift, a photographic effect that selectively reduces perceived distance while preserving other scene properties (e.g., making a distant railway appear like a model train). Fake miniaturization increased boundary extension for otherwise identical scenes: Participants who performed a scene-memory task misremembered fake- miniaturized views as farther away than they actually were. This effect went beyond low-level image changes and generalized to a completely different distance manipulation. Thus, visual memory is modulated by the spatial scale at which the environment is viewed. 

Visual scenes are often remembered as if they were observed from a different viewpoint. Some scenes are remembered as farther than they appeared, and others as closer. These memory distortions—also known as boundary extension and contraction—are strikingly consistent for a given scene, but their cause remains unknown. We tested whether these distortions can be explained by an inferential process that adjusts scene memories toward high-probability views, using viewing depth as a test case. We first carried out a large-scale analysis of depth maps of natural indoor scenes to quantify the statistical probability of views in depth. We then assessed human observers’ memory for these scenes at various depths and found that viewpoint judgments were consistently biased toward the modal depth, even when just a few seconds elapsed between viewing and reporting. Thus, scenes closer than the modal depth showed a boundary-extension bias (remembered as farther-away), and scenes farther than the modal depth showed a boundary-contraction bias (remembered as closer). By contrast, scenes at the modal depth did not elicit a consistent bias in either direction. This same pattern of results was observed in a follow-up experiment using tightly controlled stimuli from virtual environments. Together, these findings show that scene memories are biased toward statistically probable views, which may serve to increase the accuracy of noisy or incomplete scene representations.