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Setting the scene for boundary extension: Methods, findings, connections, and theories

A previously viewed scene is often remembered as containing a larger extent of the background than was actually present, and information that was likely present just outside the boundaries of that view is often incorporated into the representation of that scene. This has been referred to as boundary extension. Methodologies used in studies on boundary extension (terminology, stimulus presentation, response measures) are described. Empirical findings regarding effects of characteristics of the stimulus (whether the stimulus depicts a scene, semantics of the scene, view angle, object size, object cropping, object orientation, object color, number of objects, depth of field, object distance, viewpoint production, scene orientation, motion, faces, emotions, modality, whether the scene is multimodal), characteristics of the display (aperture shape, aperture size, target duration, retention interval), and characteristics of the observer (allocation of attention, imagination, age, expectations and strategies, eye fixation, eye movements, monocular or binocular view, vantage point, confinement, prior exposure, expertise, arousal, pathology) on boundary extension are reviewed. Connections of boundary extension to other cognitive phenomena and processes (evolutionary adaptation, Gestalt principles, illusions, psychophysics, invariant physical principles, aesthetics, temporal boundary extension, normalization) are noted, and theories and theoretical considerations regarding boundary extension (multisource model, boundary transformation, mental imagery, 4E cognition, cognitive modularity, neurological mechanisms of scene representation) are discussed.

A generative model of memory construction and consolidation

Episodic memories are (re)constructed, share neural substrates with imagination, combine unique features with schema-based predictions and show schema-based distortions that increase with consolidation. Here we present a computational model in which hippocampal replay (from an autoassociative network) trains generative models (variational autoencoders) to (re)create sensory experiences from latent variable representations in entorhinal, medial prefrontal and anterolateral temporal cortices via the hippocampal formation. Simulations show effects of memory age and hippocampal lesions in agreement with previous models, but also provide mechanisms for semantic memory, imagination, episodic future thinking, relational inference and schema-based distortions including boundary extension. The model explains how unique sensory and predictable conceptual elements of memories are stored and reconstructed by efficiently combining both hippocampal and neocortical systems, optimizing the use of limited hippocampal storage for new and unusual information. Overall, we believe hippocampal replay training generative models provides a comprehensive account of memory construction, imagination and consolidation.

Systematic transition from boundary extension to contraction along an object-to-scene continuum

After viewing a picture of an environment, our memory of it typically extends beyond what was presented, a phenomenon referred to as boundary extension. But, sometimes memory errors show the opposite pattern-boundary contraction-and the relationship between these phenomena is controversial. We constructed virtual three-dimensional environments and created a series of views at different distances, from object close-ups to wide-angle indoor views, and tested for memory errors along this object-to-scene continuum. Boundary extension was evident for close-scale views and transitioned parametrically to boundary contraction for far-scale views. However, this transition point was not tied to a specific position in the environment (e.g., the point of reachability). Instead, it tracked with judgments of the best-looking view of the environment, in both rich-object and low-object environments. We offer a dynamic-tension account, where competition between object-based and scene-based affordances determines whether a view will extend or contract in memory. This study demonstrates that boundary extension and boundary contraction are not two separate phenomena but rather two parts of a continuum, suggesting a common underlying mechanism. The transition point between the two is not fixed but depends on the observer's judgment of the best-looking view of the environment. These findings provide new insights into how we perceive and remember a view of environment.

Spatial Scene Memories Are Biased Towards a Fixed Amount of Semantic Information

Scene memory has known spatial biases. Boundary extension is a well-known bias whereby observers remember visual information beyond an image's boundaries. While recent studies demonstrate that boundary contraction also reliably occurs based on intrinsic image properties, the specific properties that drive the effect are unknown. This study assesses the extent to which scene memory might have a fixed capacity for information. We assessed both visual and semantic information in a scene database using techniques from image processing and natural language processing, respectively. We then assessed how both types of information predicted memory errors for scene boundaries using a standard rapid serial visual presentation (RSVP) forced error paradigm. A linear regression model indicated that memories for scene boundaries were significantly predicted by semantic, but not visual, information and that this effect persisted when scene depth was considered. Boundary extension was observed for images with low semantic information, and contraction was observed for images with high semantic information. This suggests a cognitive process that normalizes the amount of semantic information held in memory.

Perceived Distance Alters Memory for Scene Boundaries

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.

A tutorial on capturing mental representations through drawing and crowd-sourced scoring

When we draw, we are depicting a rich mental representation reflecting a memory, percept, schema, imagination, or feeling. In spite of the abundance of data created by drawings, drawings are rarely used as an output measure in the field of psychology, due to concerns about their large variance and their difficulty of quantification. However, recent work leveraging pen-tracking, computer vision, and online crowd-sourcing has revealed new ways to capture and objectively quantify drawings, to answer a wide range of questions across fields of psychology. Here, I present a tutorial on modern methods for drawing experiments, ranging from how to quantify pen-and-paper type studies, up to how to administer a fully closed-loop online experiment. I go through the concrete steps of designing a drawing experiment, recording drawings, and objectively quantifying them through online crowd-sourcing and computer vision methods. Included with this tutorial are code examples at different levels of complexity and tutorials designed to teach basic lessons about web architecture and be useful regardless of skill level. I also discuss key methodological points of consideration, and provide a series of potential jumping points for drawing studies across fields in psychology. I hope this tutorial will arm more researchers with the skills to capture these naturalistic snapshots of a mental image.