Publications by authors named "Steven L Franconeri"

We investigate variability overweighting, a previously undocumented bias in line graphs, where estimates of average value are biased toward areas of higher variability in that line. We found this effect across two preregistered experiments with 140 and 420 participants. These experiments also show that the bias is reduced when using a dot encoding of the same series.

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While past work has focused on the representational format of mental imagery, and the similarities of its operation and neural substrate to online perception, surprisingly little has tested the boundaries of the level of detail that mental imagery can generate. To answer this question, we take inspiration from the visual short-term memory literature, a related field which has found that memory capacity is affected by the number of items, whether they are unique, and whether and how they move. We test these factors of set size, color heterogeneity, and transformation in mental imagery through both subjective (Exp 1; Exp 2) and objective (Exp 2) measures - difficulty ratings and a change detection task, respectively - to determine the capacity limits of our mental imagery, and find that limits on mental imagery are similar to those for visual short-term memory.

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Science, Technology, Engineering, and Mathematics (STEM) domains require people to recognize and transform complex visuospatial displays that appear to vastly exceed the limits of visuospatial working memory. Here, we consider possible domain-general mechanisms that may explain this advantage: capitalizing on symmetry, a structural regularity that can produce more efficient representations. Participants briefly viewed a structure made up of three-dimensional connected cubes of different colors, which was either asymmetrical or symmetrical.

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Visual working memory (VWM) is typically measured using arrays of two-dimensional isolated stimuli with simple visual identities (e.g., color or shape), and these studies typically find strong capacity limits.

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Article Synopsis
  • Good data visuals help people understand patterns in things like science, health, and policy.
  • Badly made visuals can confuse people and make them distrustful, especially if they don't know much about graphs.
  • To make good visuals, designers should think about who will see them and follow certain guidelines that make them easy to understand.
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Bar charts are among the most frequently used visualizations, in part because their position encoding leads them to convey data values precisely. Yet reproductions of single bars or groups of bars within a graph can be biased. Curiously, some previous work found that this bias resulted in an overestimation of reproduced data values, while other work found an underestimation.

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Humans have a uniquely sophisticated ability to see past superficial features and to understand the relational structure of the world around us. This ability often requires that we compare structures, finding commonalities and differences across visual depictions that are arranged in space, such as maps, graphs, or diagrams. Although such visual comparison of relational structures is ubiquitous in classrooms, textbooks, and news media, surprisingly little is known about how to facilitate this process.

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Some types of object features, such as color, shape, or location, can be processed separately within the visual system, requiring that they be correctly "bound" to a single object via attentional selection of a subset of visual information. Forcing selection to spread too widely can cause an illusion where these features misbind to objects, creating illusory objects that were never present. Here, we present a novel display that produces a robust color-location misbinding illusion that we call foveal gravity (viewable at https://osf.

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Across the natural world as well as the artificial worlds of maps, diagrams, and data visualizations, feature similarity (e.g., color and shape) links spatially separate areas into sets.

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Our visual system organizes spatially distinct areas with similar features into perceptual groups. To better understand the underlying mechanism of grouping, one route is to study its capacity and temporal progression. Intuitively, that capacity seems unlimited, and the temporal progression feels immediate.

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Recent visualization research efforts have incorporated experimental techniques and perceptual models from the vision science community. Perceptual laws such as Weber's law, for example, have been used to model the perception of correlation in scatterplots. While this thread of research has progressively refined the modeling of the perception of correlation in scatterplots, it remains unclear as to why such perception can be modeled using relatively simple functions, e.

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Abstracting the structure or 'rules' underlying observed patterns is central to mature cognition, yet research with infants suggests this far-reaching capacity is initially restricted to certain stimuli. Infants successfully abstract rules from auditory sequences (e.g.

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How do individuals compare images-for example, two graphs or diagrams-to identify differences between them? We argue that categorical relations between objects play a critical role. These relations divide continuous space into discrete categories, such as "above" and "below," or "containing" and "overlapping," which are remembered and compared more easily than precise metric values. These relations should lead to categorical perception, such that viewers find it easier to notice a change that crosses a category boundary (one object is now above, rather than below, another, or now contains, rather than overlaps with, another) than a change of equal magnitude that does not cross a boundary.

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We argue that people compare values in graphs with a - attending to data values in an ordered pattern over time. Do these visual routines exist to manage capacity limitations in how many values can be encoded at once, or do they actually affect the relations that are extracted? We measured eye movements while people judged configurations of a two-bar graph based on size only ("[short tall] or [tall short]?") and contrast only ("[light dark] or [dark light]?"). Participants exhibited visual routines in which they systematically attended to a specific feature (or "anchor point") in the graph; in the size task, most participants inspected the taller bar first, and in the contrast task, most participants attended to the darker bar first.

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Linking relations described in text with relations in visualizations is often difficult. We used eye tracking to measure the optimal way to extract such relations in graphs, college students, and young children (6- and 8-year-olds). Participants compared relational statements ("Are there more blueberries than oranges?") with simple graphs, and two systematic patterns emerged: eye movements that followed the verbal order of the question (inspecting the "blueberry" value first) versus those that followed a left-first bias (regardless of the left value's identity).

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The connected scatterplot visualizes two related time series in a scatterplot and connects the points with a line in temporal sequence. News media are increasingly using this technique to present data under the intuition that it is understandable and engaging. To explore these intuitions, we (1) describe how paired time series relationships appear in a connected scatterplot, (2) qualitatively evaluate how well people understand trends depicted in this format, (3) quantitatively measure the types and frequency of misinter pretations, and (4) empirically evaluate whether viewers will preferentially view graphs in this format over the more traditional format.

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Creative ideas seem often to appear when we close our eyes, stare at a blank wall, or gaze out of a window--all signs of shutting out distractions and turning attention inward. Prior research has demonstrated that attention-related brain areas are differently active when people solve problems with sudden insight (the Aha! phenomenon), relative to deliberate, analytic solving. We directly investigated the relationship between attention deployment and problem solving by recording eye movements and blinks, which are overt indicators of attention, as people solved short, visually presented problems.

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When interacting with the world, people can dynamically split attention across multiple objects in the environment, both when the objects are stationary and when the objects are moving. This type of visual processing is commonly studied in lab settings using either static selection tasks or moving tracking tasks. We describe performance limits that are common to both tasks, including limits on capacity, crowding, visual hemifield arrangement, and speed.

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Although mental rotation is a core component of scientific reasoning, little is known about its underlying mechanisms. For instance, how much visual information can someone rotate at once? We asked participants to rotate a simple multipart shape, requiring them to maintain attachments between features and moving parts. The capacity of this aspect of mental rotation was strikingly low: Only one feature could remain attached to one part.

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According to appraisal theories of emotion, cognitive reappraisal is a successful emotion regulation strategy because it involves cognitively changing our thoughts, which, in turn, change our emotions. However, recent evidence has challenged the importance of cognitive change and, instead, has suggested that attentional deployment may at least partly explain the emotion regulation success of cognitive reappraisal. The purpose of the current study was to examine the causal relationship between attentional deployment and emotion regulation success.

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The brain has finite processing resources so that, as tasks become harder, performance degrades. Where do the limits on these resources come from? We focus on a variety of capacity-limited buffers related to attention, recognition, and memory that we claim have a two-dimensional 'map' architecture, where individual items compete for cortical real estate. This competitive format leads to capacity limits that are flexible, set by the nature of the content and their locations within an anatomically delimited space.

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The brain receives input from multiple sensory modalities simultaneously, yet we experience the outside world as a single integrated percept. This integration process must overcome instances where perceptual information conflicts across sensory modalities. Under such conflicts, the relative weighting of information from each modality typically depends on the given task.

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Objects in the world do not have a surface that can be objectively labeled the "front." We impose this designation on one surface of an object according to several cues, including which surface is associated with the most task-relevant information or the direction of motion of an object. However, when these cues are competing, weak, or absent, we can also flexibly assign one surface as the front.

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Moving objects in the world present a challenge to the visual system, in that they often move in and out of view as they are occluded by other surfaces. Nevertheless, the ability to track multiple objects through periods of occlusion is surprisingly robust. Here, we identify a simple heuristic that underlies this ability: Pre- and postocclusion views of objects are linked together solely by their spatial proximity.

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