How do people build up visual memory representations from sensory evidence? Revisiting two classic models of choice.

In many decision tasks, we have a set of alternative choices and are faced with the problem of how to use our latent beliefs and preferences about each alternative to make a single choice. Cognitive and decision models typically presume that beliefs and preferences are distilled to a scalar latent strength for each alternative, but it is also critical to model how people use these latent strengths to choose a single alternative. Most models follow one of two traditions to establish this link.

Repeated rock, paper, scissors play reveals limits in adaptive sequential behavior.

How do people adapt to others in adversarial settings? Prior work has shown that people often violate rational models of adversarial decision-making in repeated interactions. In particular, in mixed strategy equilibrium (MSE) games, where optimal action selection entails choosing moves randomly, people often do not play randomly, but instead try to outwit their opponents. However, little is known about the adaptive reasoning that underlies these deviations from random behavior.

Local but not global graph theoretic measures of semantic networks generalize across tasks.

"Dogs" are connected to "cats" in our minds, and "backyard" to "outdoors." Does the structure of this semantic knowledge differ across people? Network-based approaches are a popular representational scheme for thinking about how relations between different concepts are organized. Recent research uses graph theoretic analyses to examine individual differences in semantic networks for simple concepts and how they relate to other higher-level cognitive processes, such as creativity.

Structured visuospatial representations revealed through serial reproduction.

Working memory is a reconstructive process that requires integrating multiple hierarchical representations of objects. This hierarchical reconstruction allows us to overcome perceptual uncertainty and limited cognitive capacity but yields systematic biases in working memory as individual items are influenced by the ensemble statistics of the scene, or of their particular group. Given the importance of the hierarchical encoding of a display, we aim to characterize what structures people use to encode visual scenes using a nonparametric data-driven approach.

Modeling face similarity in police lineups.

Police investigators worldwide use lineups to test an eyewitness's memory of a perpetrator. A typical lineup consists of one suspect (who is innocent or guilty) plus five or more fillers who resemble the suspect and who are known to be innocent. Although eyewitness identification decisions were once biased by police pressure and poorly constructed lineups, decades of social science research led to the development of reformed lineup procedures that provide a more objective test memory.

Designing and detecting lies by reasoning about other agents.

How do people detect lies from the content of messages, and design lies that go undetected? Lying requires strategic reasoning about how others think and respond. We propose a unified framework underlying lie design and detection, formalized as recursive social reasoning. Senders design lies by inferring the likelihood the receiver detects potential lies; receivers detect lies by inferring if and how the sender would lie.

Triadic conflict "primitives" can be reduced to welfare trade-off ratios.

Pietraszewski proposes four triadic "primitives" for representing social groups. We argue that, despite surface differences, these triads can all be reduced to similar underlying welfare trade-off ratios, which are a better candidate for social group primitives. Welfare trade-off ratios also have limitations, however, and we suggest there are multiple computational strategies by which people recognize and reason about social groups.

Ongoing dynamic calibration produces unstable number estimates.

Whether estimating the size of a crowd or rating a restaurant on a five-star scale, humans frequently navigate between subjective sensory experiences and shared formal systems. Here we ask how people manage this in the case of estimating number. We present participants with arrays of dots and ask them to report how many dots there are.

Eyewitness Identification Is a Visual Search Task.

The simultaneous six-pack photo lineup is a standard eyewitness identification procedure, consisting of one police suspect plus five physically similar fillers. The photo lineup is either a target-present array (the suspect is guilty) or a target-absent array (the suspect is innocent). The eyewitness is asked to search the six photos in the array with respect to a target template stored in memory (namely, the memory of the perpetrator's face).

The role of kinematic properties in multiple object tracking.

People commonly track objects moving in complex natural displays and their performance in the multiple object tracking paradigm has been used to study such visual attention for more than three decades. Given the theoretical and practical importance of object tracking, it is critical to understand how people solve the correspondence problem to track objects; however, it remains unclear what information people use to achieve this feat. In particular, although people can track multiple moving objects based on their positions, there is ambiguity about whether people can track objects via higher order kinematic information, such as velocity.

Integration by Parts: Collaboration and Topic Structure in the CogSci Community.

Is cognitive science interdisciplinary or multidisciplinary? We contribute to this debate by examining the authorship structure and topic similarity of contributions to the Cognitive Science Society from 2000 to 2019. Our analysis focuses on graph theoretic features of the co-authorship network-edge density, transitivity, and maximum subgraph size-as well as clustering within the space of scientific topics. We also combine structural and semantic information with an analysis of how authors choose their collaborators based on their interests and prior collaborations.

The structure of illusory conjunctions reveals hierarchical binding of multipart objects.

The world around us is filled with complex objects, full of color, motion, shape, and texture, and these features seem to be represented separately in the early visual system. Anne Treisman pointed out that binding these separate features together into coherent conscious percepts is a serious challenge, and she argued that selective attention plays a critical role in this process. Treisman also showed that, consistent with this view, outside the focus of attention we suffer from illusory conjunctions: misperceived pairings of features into objects.

Perceptual features predict word frequency asymmetry across modalities.

The relationships between word frequency and various perceptual features have been used to study the cognitive processes involved in word production and recognition, as well as patterns in language use over time. However, little work has been done comparing spoken and written frequencies against each other, which leaves open the question of whether there are modality-specific relationships between perceptual features and frequency. Words have different frequencies in speech and written texts, with some words occurring disproportionately more often in one modality than the other.

Models of lineup memory.

Face recognition memory is often tested by the police using a photo lineup, which consists of one suspect, who is either innocent or guilty, and five or more physically similar fillers, all of whom are known to be innocent. For many years, lineups were investigated in lab studies without guidance from standard models of recognition memory. More recently, signal detection theory has been used to conceptualize lineup memory and to motivate receiver operating characteristic (ROC) analysis of lineup performance.

How effective is incidental learning of the shape of probability distributions?

The idea that people learn detailed probabilistic generative models of the environments they interact with is intuitively appealing, and has received support from recent studies of implicit knowledge acquired in daily life. The goal of this study was to see whether people efficiently induce a probability distribution based upon incidental exposure to an unknown generative process. Subjects played a 'whack-a-mole' game in which they attempted to click on objects appearing briefly, one at a time on the screen.

Scanning the horizon: towards transparent and reproducible neuroimaging research.

Functional neuroimaging techniques have transformed our ability to probe the neurobiological basis of behaviour and are increasingly being applied by the wider neuroscience community. However, concerns have recently been raised that the conclusions that are drawn from some human neuroimaging studies are either spurious or not generalizable. Problems such as low statistical power, flexibility in data analysis, software errors and a lack of direct replication apply to many fields, but perhaps particularly to functional MRI.

Fragile associations coexist with robust memories for precise details in long-term memory.

What happens to memories as we forget? They might gradually lose fidelity, lose their associations (and thus be retrieved in response to the incorrect cues), or be completely lost. Typical long-term memory studies assess memory as a binary outcome (correct/incorrect), and cannot distinguish these different kinds of forgetting. Here we assess long-term memory for scalar information, thus allowing us to quantify how different sources of error diminish as we learn, and accumulate as we forget.

Ensemble clustering in visual working memory biases location memories and reduces the Weber noise of relative positions.

People seem to compute the ensemble statistics of objects and use this information to support the recall of individual objects in visual working memory. However, there are many different ways that hierarchical structure might be encoded. We examined the format of structured memories by asking subjects to recall the locations of objects arranged in different spatial clustering structures.

One and done? Optimal decisions from very few samples.

In many learning or inference tasks human behavior approximates that of a Bayesian ideal observer, suggesting that, at some level, cognition can be described as Bayesian inference. However, a number of findings have highlighted an intriguing mismatch between human behavior and standard assumptions about optimality: People often appear to make decisions based on just one or a few samples from the appropriate posterior probability distribution, rather than using the full distribution. Although sampling-based approximations are a common way to implement Bayesian inference, the very limited numbers of samples often used by humans seem insufficient to approximate the required probability distributions very accurately.

Hierarchical encoding makes individuals in a group seem more attractive.

In the research reported here, we found evidence of the cheerleader effect-people seem more attractive in a group than in isolation. We propose that this effect arises via an interplay of three cognitive phenomena: (a) The visual system automatically computes ensemble representations of faces presented in a group, (b) individual members of the group are biased toward this ensemble average, and (c) average faces are attractive. Taken together, these phenomena suggest that individual faces will seem more attractive when presented in a group because they will appear more similar to the average group face, which is more attractive than group members' individual faces.

Multiply-constrained semantic search in the Remote Associates Test.

Many important problems require consideration of multiple constraints, such as choosing a job based on salary, location, and responsibilities. We used the Remote Associates Test to study how people solve such multiply-constrained problems by asking participants to make guesses as they came to mind. We evaluated how people generated these guesses by using Latent Semantic Analysis to measure the similarity between the guesses, cues, and answers.

Quantifying error distributions in crowding.

When multiple objects are in close proximity, observers have difficulty identifying them individually. Two classes of theories aim to account for this crowding phenomenon: spatial pooling and spatial substitution. Variations of these accounts predict different patterns of errors in crowded displays.