The ability to perceive and remember the spatial layout of a scene is critical to understanding the visual world, both for navigation and for other complex tasks that depend upon the structure of the current environment. However, surprisingly little work has investigated how and when scene layout information is maintained in memory. One prominent line of work investigating this issue is a scene-priming paradigm (e.g., Sanocki & Epstein, 1997), in which different types of previews are presented to participants shortly before they judge which of two regions of a scene is closer in depth to the viewer. Experiments using this paradigm have been widely cited as evidence that scene layout information is stored across brief delays and have been used to investigate the structure of the representations underlying memory for scene layout. In the present experiments, we better characterize these scene-priming effects. We find that a large amount of visual detail rather than the presence of depth information is necessary for the priming effect; that participants show a preview benefit for a judgment completely unrelated to the scene itself; and that preview benefits are susceptible to masking and quickly decay. Together, these results suggest that "scene priming" effects do not isolate scene layout information in memory, and that they may arise from low-level visual information held in sensory memory. This broadens the range of interpretations of scene priming effects and suggests that other paradigms may need to be developed to selectively investigate how we represent scene layout information in memory.

“Similarity” is often thought to dictate memory errors. For example, in visual memory, memory judgements of lures are related to their psychophysical similarity to targets: an approximately exponential function in stimulus space (Schurgin et al. 2020). However, similarity is ill-defined for more complex stimuli, and memory errors seem to depend on all the remembered items, not just pairwise similarity. Such effects can be captured by a model that views similarity as a byproduct of Bayesian generalization (Tenenbaum & Griffiths, 2001). Here we ask whether the propensity of people to generalize from a set to an item predicts memory errors to that item. We use the “number game” generalization task to collect human judgements about set membership for symbolic numbers and show that memory errors for numbers are consistent with these generalization judgements rather than pairwise similarity. These results suggest that generalization propensity, rather than “similarity”, drives memory errors.

People can store thousands of real-world objects in visual long-term memory with high precision. But are these objects stored as unitary, bound entities, as often assumed, or as bundles of separable features? We tested this in several experiments. In the first series of studies, participants were instructed to remember specific exemplars of real-world objects presented in a particular state (e.g., open/closed, full/empty, etc.), and then were asked to recognize either which exemplars they had seen (e.g., I saw this coffee mug), or which exemplar-state conjunctions they had seen (e.g., I saw this coffee mug and it was full). Participants had a large number of within-category confusions, for example misremembering which states went with which exemplars, while simultaneously showing strong memory for the features themselves (e.g., which states they had seen, which exemplars they had seen). In a second series of studies, we found further evidence of independence: participants were very good at remembering which exemplars they had seen independently of whether these items were presented in a new or old state, but the same did not occur for features known to be truly holistically represented. Thus, we find through 2 lines of evidence that the features of real-world objects that support exemplar discrimination and state discrimination are not bound, suggesting visual objects are not inherently unitary entities in memory. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

People can quickly and accurately compute not only the mean size of a set of items but also the size variability of the items. However, it remains unknown how these statistics are estimated. Here we show that neither parallel access to all items nor random subsampling of just a few items is sufficient to explain participants' estimations of size variability. In three experiments, we had participants compare two arrays of circles with different variability in their sizes. In the first two experiments, we manipulated the congruency of the range and variance of the arrays. The arrays with congruent range and variability information were judged more accurately, indicating the use of range as a proxy for variability. Experiments 2B and 3 showed that people also are not invariant to low- or mid-level visual information in the arrays, as comparing arrays with different low-level characteristics (filled vs. outlined circles) led to systematic biases. Together, these experiments indicate that range and low- or mid-level properties are both utilized as proxies for variability discrimination, and people are flexible in adopting these strategies. These strategies are at odds with the claim of parallel extraction of ensemble statistics per se and random subsampling strategies previously proposed in the literature.

Prevailing theories of visual working memory assume that each encoded item is stored or forgotten as a separate unit independent from other items. Here, we show that items are not independent and that the recalled orientation of an individual item is strongly influenced by the summary statistical representation of all items (ensemble representation). We find that not only is memory for an individual orientation substantially biased toward the mean orientation, but the precision of memory for an individual item also closely tracks the precision with which people store the mean orientation (which is, in turn, correlated with the physical range of orientations). Thus, individual items are reported more precisely when items on a trial are more similar. Moreover, the narrower the range of orientations present on a trial, the more participants appear to rely on the mean orientation as representative of all individuals. This can be observed not only when the range is carefully controlled, but also shown even in randomly generated, unstructured displays, and after accounting for the possibility of location-based 'swap' errors. Our results suggest that the information about a set of items is represented hierarchically, and that ensemble information can be an important source of information to constrain uncertain information about individuals. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Is there a fixed limit on how many objects we can hold actively in mind? Generally, researchers have found participants are worse at remembering a small number of objects if those objects are more complex, suggesting a limited resource rather than a fixed number of objects best explains working memory performance. However, some evidence has suggested that stimulus similarity better accounts for these effects and that, after accounting for such similarity, the data support a slot-based fixed item limit for working memory. Much of the evidence used to support the latter claim relies on working memory displays containing different categories of items. It has been found that, for large, across-category changes, performance does not differ for different kinds of complex stimuli. However, many of these studies fail to adequately control for the potential use of ensemble information in discriminating such large changes. Here, we sought to identify how much ensemble representations may explain performance across these tasks. In Experiment 1, we observed that, as set size increased from four to 12 items, capacity estimates for across-category changes increased linearly as well, providing evidence against the claim of a fixed capacity. In Experiment 2, we controlled for stimulus complexity and similarity but varied the utility of ensemble representations for the change-detection task. We observed significantly greater capacity when ensemble information could be used. Altogether, these results are contrary to a slot-like, fixed-object constraint on working memory capacity and consistent with object complexity and ensemble representations strongly affecting working memory performance.

Although Bastin et al. propose a useful model for thinking about the structure of memory and memory deficits, their distinction between entities and relational encoding is incompatible with data showing that even individual objects - prototypical "entities" - are made up of distinct features which require binding. Thus, "entity" and "relational" brain regions may need to solve fundamentally the same problems.

How do people use human-made objects (artifacts) to learn about the people and actions that created them? We test the richness of people’s reasoning in this domain, focusing on the task of judging whether social transmission has occurred (i.e. whether one person copied another). We develop a formal model of this reasoning process as a form of rational inverse planning, which predicts that rather than solely focusing on artifacts’ similarity to judge whether copying occurred, people should also take into account availability constraints (the materials available), and functional constraints (which materials work). Using an artifact-building task where two characters build tools to solve a puzzle box, we find that this inverse planning model predicts trial-by-trial judgments, whereas simpler models that do not consider availability or functional constraints do not. This suggests people use a process like inverse planning to make flexible inferences from artifacts’ features about the source of design ideas.

Existing knowledge shapes and distorts our memories, serv-ing as a prior for newly encoded information. Here, we in-vestigate the role of stable long-term priors (e.g. categoricalknowledge) in conjunction with priors arising from recentlyencountered information (e.g. ’serial dependence’) in visualworking memory for color. We use an iterated reproductionparadigm to allow a model-free assessment of the role of suchpriors. In Experiment 1, we find that participants’ reports re-liably converge to certain areas of color space, but that thisconvergence is largely distinct for different individuals, sug-gesting responses are biased by more than just shared categoryknowledge. In Experiment 2, we explicitly manipulate trialn-1 and find recent history plays a major role in participants’reports. Thus, we find that both global prior knowledge and re-cent trial information have biasing influences on visual work-ing memory, demonstrating an important role for both short-and long-term priors in actively maintained information.