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Tulving's introduction of episodic memory and the metaphor of mental time travel has immensely enriched our understanding of human cognition. However, his focus on human psychology, with limited consideration of evolutionary perspectives, led to the entrenched notion that mental time travel is uniquely human. We contend that adopting a phylogenetic perspective offers a deeper insight into cognition, revealing it as a continuous evolutionary process. Adherence to the uniqueness of pre-defined psychological concepts obstructs a more complete understanding. We offer a concise natural history to elucidate how events that occurred hundreds of millions of years ago have been pivotal for our ability to mentally time travel. We discuss how the human brain, utilizing parts with ancient origins in a networked manner, enables mental time travel. This underscores that episodic memories and mental time travel are not isolated mental constructs but integral to our perception and representation of the world. We conclude by examining recent evidence of neuroanatomical correlates found only in great apes, which show great variability, indicating the ongoing evolution of mental time travel in humans.This article is part of the theme issue 'Elements of episodic memory: lessons from 40 years of research'.

Over the course of his research, Endel Tulving offered a number of somewhat different characterizations of episodic memory. Do they indicate that he changed his mind over time as to what episodic memory is, or did his core understanding of the nature of episodic memory stay the same? In this article, we offer some support for the latter claim, and in particular for thinking that, throughout his life, Tulving took as a defining feature of episodic memory the distinctive awareness of the self in time it involves. We argue that it is easier to see the continuities rather than the discontinuities in Tulving's writings once their historical context is taken into account, where this involves both the authors who influenced his thinking, as well as the intellectual climate at the different times he was writing. We also discuss two recent bodies of work on episodic memory that take aspects of Tulving's writings as their point of departure, but try to factor out into separate ingredients what he arguably saw as a unitary phenomenon. Considering aspects of the dialectic between them and Tulving's view might shed further light on some of the motivations behind the latter.This article is part of the theme issue 'Elements of episodic memory: lessons from 40 years of research'.

One apparent feature of mental time travel is the ability to recursively embed temporal perspectives across different times: humans can remember how we anticipated the future and anticipate how we will remember the past. This recursive structure of mental time travel might be formalized in terms of a 'grammar' that is reflective of but more general than linguistic notions of absolute and relative tense. Here, I provide a foundation for this grammatical framework, emphasizing a bounded (rather than unbounded) recursive function that supports mental time travel to a limited temporal depth and to actual and possible scenarios. Anticipated counterfactual thinking, for instance, entails three levels of mental time travel to a possible scenario ('in the future, I will reflect on how my past self could have taken a different future action') and is centrally implicated in complex human decision-making. This perspective calls for further research into the mechanisms, ontogeny, functions and phylogeny of recursive mental time travel, and revives the question of links with other recursive forms of thinking such as theory of mind. This article is part of the theme issue 'Elements of episodic memory: lessons from 40 years of research'.

While many aspects of cognition have been shown to be shared between humans and non-human animals, there remains controversy regarding whether the capacity to mentally time travel is a uniquely human one. In this paper, we argue that there are four ways of representing when some event happened: four kinds of temporal representation . Distinguishing these four kinds of temporal representation has five benefits. First, it puts us in a position to determine the particular benefits these distinct temporal representations afford an organism. Second, it provides the conceptual resources to foster a discussion about which of these representations is necessary for an organism to count as having the capacity to mentally time travel. Third, it enables us to distinguish stricter from more liberal views of mental time travel that differ regarding which kind(s) of temporal representation is taken to be necessary for mental time travel. Fourth, it allows us to determine the benefits of taking a stricter or more liberal view of mental time travel. Finally, it ensures that disagreement about whether some species can mentally time travel is not merely the product of unrecognized disagreement about which temporal representation is necessary for mental time travel. We argue for a more liberal view, on the grounds that it allows us to view mental time travel as an evolutionarily continuous phenomenon and to recognize that differences in the ways that organisms mentally time travel might reflect different temporal representations, or combinations thereof, that they employ. Our ultimate aim, however, is to create a conceptual framework for further discussion regarding what sorts of temporal representations are required for mental time travel.This article is part of the theme issue 'Elements of episodic memory: lessons from 40 years of research'.

The concept of episodic memory (EM) faces significant challenges by two claims: EM might not be a distinct memory system, and EM might be an epiphenomenon of a more general capacity for mental time travel (MTT). Nevertheless, the observations leading to these arguments do not preclude the existence of a mechanically and functionally distinct EM system. First, modular systems, like cognition, can have distinct subsystems that may not be distinguishable in the system's final output. EM could be such a subsystem, even though its effects may be difficult to distinguish from those of other subsystems. Second, EM could have a distinct and consistent low-level function, which is used in diverse high-level functions such as MTT. This article introduces the scenario construction framework, proposing that EM crucially rests on memory traces containing the gist of an episodic experience. During retrieval, EM traces trigger the reconstruction of semantic representations, which were active during the remembered episode, and are further enriched with semantic information, to generate a scenario of the past experience. This conceptualization of EM is consistent with studies on the neural basis of EM and resolves the two challenges while retaining the key properties associated with EM. This article is part of the theme issue 'Elements of episodic memory: lessons from 40 years of research'.

In Tulving's initial characterization, episodic memory was one of multiple memory systems. It was postulated, in pursuit of explanatory depth, as displaying proprietary operations, representations and substrates such as to explain a range of cognitive, behavioural and experiential phenomena. Yet the subsequent development of this research programme has, paradoxically, introduced surprising doubts about the nature, and indeed existence, of episodic memory. On dominant versions of the 'common system' view, on which a single simulation system underlies both remembering and imagining, there are no processes unique to memory to support robust generalizations with inductive potential. Eliminativism about episodic memory seems to follow from the claim that it has no dedicated neurocognitive system of its own. After identifying this under-noticed threat, we push back against modern eliminativists by surveying recent evidence that still indicates specialized mechanisms, computations and representations that are distinctly mnemic in character. We argue that contemporary realists about episodic memory can retain lessons of the common system approach while resisting the further move to eliminativism. This article is part of the theme issue 'Elements of episodic memory: lessons from 40 years of research'.

Ever since Tulving's influential 1985 article 'Memory and consciousness', it has become traditional to think of autonoetic consciousness as necessary for episodic memory. This paper questions this claim. Specifically, it argues that the construct of autonoetic consciousness lacks validity and that, even if it was valid, it would still not be necessary for episodic memory. The paper ends with a proposal to go back to a functional/computational characterization of episodic memory in which its characteristic phenomenology is a contingent feature of the retrieval process and, as a result, open to empirical scrutiny. The proposal also dovetails with recent taxonomies of memory that are independent of conscious awareness and suggests strategies to evaluate within- and between-individual variability in the conscious experience of episodic memories in human and non-human agents. This article is part of the theme issue 'Elements of episodic memory: lessons from 40 years of research'.

This article allows readers to assess their ability to detect errors in thinking in seven case histories of psychologists' thoughts about cognitive science. It explains the nature of the errors and shows that some of them reflect faulty reasoning. It presents a "model method" to improve reasoning. It is based on the theory of mental models, which gives a general account of how individuals think, both deductively and indicatively, and which postulates that individuals construct mental models of possibilities in the world. The model method enhances both the accuracy and speed of reasoning. The article concludes with some general reflections on the role of knowledge of meanings, the world, and context in thinking., Competing Interests: The author declares no competing financial interests., (Copyright © 2024 Johnson-Laird.)

Determining the compositional structure and dimensionality of psychological constructs lies at the heart of many research questions in developmental science. Structural equation modeling (SEM) provides a versatile framework for formalizing and estimating the relationships among multiple latent constructs. While the flexibility of SEM can accommodate many complex assumptions on the underlying structure of psychological constructs, it makes a priori estimation of statistical power and required sample size challenging. This difficulty is magnified when comparing non-nested SEMs, which prevents the use of traditional likelihood-ratio tests. Sample size estimates for SEM model fit comparisons typically rely on generic rules of thumb. Such heuristics can be misleading because statistical power in SEM depends on a variety of model properties. Here, we demonstrate a Monte Carlo simulation approach for estimating a priori statistical power for model selection when comparing non-nested models in an SEM framework. We provide a step-by-step guide to this approach based on an example from our memory development research in children., (© 2024. The Author(s).)

The implementation of meta-learning targeted by Binz et al. inherits benefits and drawbacks from its nature as a connectionist model. Drawing from historical debates around bottom-up and top-down approaches to modeling in cognitive science, we should continue to bridge levels of analysis by constraining meta-learning and meta-learned models with complementary evidence from across the cognitive and computational sciences.

When two cognitive processes contribute to a behavioral output-each process producing a specific distribution of the behavioral variable of interest-and when the mixture proportion of these two processes varies as a function of an experimental condition, a common density point should be present in the observed distributions of the data across said conditions. In principle, one can statistically test for the presence (or absence) of a fixed point in experimental data to provide evidence in favor of (or against) the presence of a mixture of processes, whose proportions are affected by an experimental manipulation. In this paper, we provide an empirical diagnostic of this test to detect a mixture of processes. We do so using resampling of real experimental data under different scenarios, which mimic variations in the experimental design suspected to affect the sensitivity and specificity of the fixed-point test (i.e., mixture proportion, time on task, and sample size). Resampling such scenarios with real data allows us to preserve important features of data which are typically observed in real experiments while maintaining tight control over the properties of the resampled scenarios. This is of particular relevance considering such stringent assumptions underlying the fixed-point test. With this paper, we ultimately aim at validating the fixed-point property of binary mixture data and at providing some performance metrics to researchers aiming at testing the fixed-point property on their experimental data., (© 2023. The Author(s).)

'Everyone knows what attention is' according to William James. Much work on attention in psychology and neuroscience cites this famous phrase only to quickly dismiss it. But James is right about this: 'attention' was not introduced into psychology and neuroscience as a theoretical concept. I argue that we should therefore study attention with broadly the same methodology that David Marr has applied to the study of perception. By focusing more on Marr's Computational Level of analysis, we arrive at a unified answer to the question of what attention is, what role it plays in the mind, and why organisms like us have that capacity. I propose a methodology for studying attention at Marr's Computational Level that optimizes in a three-dimensional space: it should capture core aspects of our first-person experience of attention, be explanatorily powerful in psychology and neuroscience, and fertile in an interdisciplinary context. I show how this methodology leads to what I call the priority structure account of attention. Attention is what organizes current information to make it more useful for the organism. We can identify it by four features. Attention, in this way, helps a cognitive system to integrate its informational state with its current motivational state. I describe how this account improves on alternatives and shows why attention is a useful concept in many disciplines and for connecting them. This article is categorized under: Philosophy > Psychological Capacities Psychology > Attention Philosophy > Foundations of Cognitive Science., (© 2022 The Author. WIREs Cognitive Science published by Wiley Periodicals LLC.)

Because the spread of pandemics depends heavily on human choices and behaviors, dealing with COVID-19 requires insights from cognitive science which integrates psychology, neuroscience, computer modeling, philosophy, anthropology, and linguistics. Cognitive models can explain why scientists adopt hypotheses about the causes and treatments of disease based on explanatory coherence. Irrational deviations from good reasoning are explained by motivated inference in which conclusions are influenced by personal goals that contribute to emotional coherence. Decisions about COVID-19 can also be distorted by well-known psychological and neural mechanisms. Cognitive science provides advice about how to improve human behavior in pandemics by changing beliefs and by improving behaviors that result from intention-action gaps., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Experiments in research on memory, language, and in other areas of cognitive science are increasingly being analyzed using Bayesian methods. This has been facilitated by the development of probabilistic programming languages such as Stan, and easily accessible front-end packages such as brms. The utility of Bayesian methods, however, ultimately depends on the relevance of the Bayesian model, in particular whether or not it accurately captures the structure of the data and the data analyst's domain expertise. Even with powerful software, the analyst is responsible for verifying the utility of their model. To demonstrate this point, we introduce a principled Bayesian workflow (Betancourt, 2018) to cognitive science. Using a concrete working example, we describe basic questions one should ask about the model: prior predictive checks, computational faithfulness, model sensitivity, and posterior predictive checks. The running example for demonstrating the workflow is data on reading times with a linguistic manipulation of object versus subject relative clause sentences. This principled Bayesian workflow also demonstrates how to use domain knowledge to inform prior distributions. It provides guidelines and checks for valid data analysis, avoiding overfitting complex models to noise, and capturing relevant data structure in a probabilistic model. Given the increasing use of Bayesian methods, we aim to discuss how these methods can be properly employed to obtain robust answers to scientific questions. All data and code accompanying this article are available from https://osf.io/b2vx9/. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Bayesian inference has become a powerful and popular technique for understanding psychological phenomena. However, compared with frequentist statistics, current methods employing Bayesian statistics typically require time-intensive computations, often hindering our ability to evaluate alternatives in a thorough manner. In this article, we advocate for an alternative strategy for performing Bayesian inference, called variational Bayes (VB). VB methods posit a parametric family of distributions that could conceivably contain the target posterior distribution, and then attempt to identify the best parameters for matching the target. In this sense, acquiring the posterior becomes an optimization problem, rather than a complex integration problem. VB methods have enjoyed considerable success in fields such as neuroscience and machine learning, yet have received surprisingly little attention in fields such as psychology. Here, we identify and discuss both the advantages and disadvantages of using VB methods. In our consideration of possible strategies to make VB methods appropriate for psychological models, we develop the differential evolution variational inference algorithm, and compare its performance with a widely used VB algorithm. As test problems, we evaluate the algorithms on their ability to recover the posterior distribution of the linear ballistic accumulator model and a hierarchical signal detection model. Although we cannot endorse VB methods in their current form as a complete replacement for conventional methods, we argue that their accuracy and speed warrant inclusion within the cognitive scientist's toolkit. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

There is a rich tradition of building computational models in cognitive science, but modeling, theoretical, and experimental research are not as tightly integrated as they could be. In this paper, we show that computational techniques-even simple ones that are straightforward to use-can greatly facilitate designing, implementing, and analyzing experiments, and generally help lift research to a new level. We focus on the domain of artificial grammar learning, and we give five concrete examples in this domain for (a) formalizing and clarifying theories, (b) generating stimuli, (c) visualization, (d) model selection, and (e) exploring the hypothesis space., (© 2019 The Authors. Topics in Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.)

Quantitative survey findings are important in measuring health-related phenomena, including on sensitive topics such as respectful maternity care (RMC). But how well do survey results truly capture respondent experiences and opinions? Quantitative tool development and piloting often involve translating questions from other settings and assessing the mechanics of implementation, which fails to deeply explore how respondents understand survey questions and response options. To address this gap, we conducted cognitive interviews on survey questions (n = 88) adapted from validated RMC instruments used in Ethiopia, Kenya and elsewhere in India. Cognitive interviews with rural women (n = 21) in Madhya Pradesh, India involved asking the respondent the survey question, recording her response, then interviewing her about what the question and response options meant to her. We analysed the interviews to revise the tool and identify question failures, which we grouped into six areas: issues with sequencing, length and sensitivity; problematic response options; inappropriate vocabulary; temporal and spatial confusion; accessing different cognitive domains; and failure to resonate with the respondent's worldview and reality. Although women tended to provide initial answers to the survey questions, cognitive interviews revealed widespread mismatch between respondent interpretation and question intent. Likert scale response options were generally incomprehensible and questions involving hypothetical scenarios could be interpreted in unexpected ways. Many key terms and concepts from the international RMC literature did not translate well and showed low resonance with respondents, including consent and being involved in decisions about one's care. This study highlights the threat to data quality and the validity of findings when translating quantitative surveys between languages and cultures and showcases the value of cognitive interviews in identifying question failures. While survey tool revision can address many of these issues, further critical discussion is needed on the use of standardized questions to assess the same domains across contexts., (© The Author(s) 2019. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.)

Causal judgments are widely known to be sensitive to violations of both prescriptive norms (e.g., immoral events) and statistical norms (e.g., improbable events). There is ongoing discussion as to whether both effects are best explained in a unified way through changes in the relevance of counterfactual possibilities, or whether these two effects arise from unrelated cognitive mechanisms. Recent work has shown that moral norm violations affect causal judgments of agents, but not inanimate artifacts used by those agents. These results have been interpreted as showing that prescriptive norm violations only affect causal reasoning about intentional agents, but not the use of inanimate artifacts, thereby providing evidence that the effect of prescriptive norm violations arises from mechanisms specific to reasoning about intentional agents, and thus casting doubt on a unified counterfactual analysis of causal reasoning. Four experiments explore this recent finding and provide clear support for a unified counterfactual analysis. Experiment 1 demonstrates that these newly observed patterns in causal judgments are closely mirrored by judgments of counterfactual relevance. Experiment 2 shows that the relationship between causal and counterfactual judgments is moderated by causal structure, as uniquely predicted by counterfactual accounts. Experiment 3 directly manipulates the relevance of counterfactual alternatives and finds that causal judgments of intentional agents and inanimate artifacts are similarly affected. Finally, Experiment 4 shows that prescriptive norm violations (in which artifacts malfunction) affect causal judgments of inanimate artifacts in much the same way that prescriptive norm violations (in which agents act immorally) affect causal judgments of intentional agents., (© 2019 Cognitive Science Society, Inc.)

Sharing information and memories is a key feature of social interactions, making social contexts important for developing and transmitting accurate memories and also false memories. False memory transmission can have wide-ranging effects, including shaping personal memories of individuals as well as collective memories of a network of people. This paper reviews a collection of key findings and explanations in cognitive research on the transmission of false memories in small groups. It also reviews the emerging experimental work on larger networks and collective false memories. Given the reconstructive nature of memory, the abundance of misinformation in everyday life, and the variety of social structures in which people interact, an understanding of transmission of false memories has both scientific and societal implications., (© 2018 Cognitive Science Society, Inc.)

ACT-R is a hybrid cognitive architecture. It is comprised of a set of programmable information processing mechanisms that can be used to predict and explain human behavior including cognition and interaction with the environment. We start by reviewing its history, which shapes its current form, contrasts and relates it to other architectures, and helps readers to anticipate where it is going. Based on this history, we then describe it as a theory of cognition that is realized as a computer program. After this, we briefly discuss tools for working with ACT-R, and also note several major accomplishments that have been gained by working with ACT-R in both basic and applied science, including summarizing some of the insights about human behavior. We conclude by discussing its future, which we believe will include adding emotions and physiology, increasing usability, and the use of nongenerative models. This article is categorized under: Computer Science > Artificial Intelligence Psychology > Reasoning and Decision Making Psychology > Theory and Methods., (© 2018 Wiley Periodicals, Inc.)

The role of semantic memory in creativity is theoretically assumed, but far from understood. In recent years, computational network science tools have been applied to investigate this role. These studies shed unique quantitative insights on the role of semantic memory structure in creativity, via measures of connectivity, distance, and structure., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Artificial deep neural networks (DNNs) initially inspired by the brain enable computers to solve cognitive tasks at which humans excel. In the absence of explanations for such cognitive phenomena, in turn cognitive scientists have started using DNNs as models to investigate biological cognition and its neural basis, creating heated debate. Here, we reflect on the case from the perspective of philosophy of science. After putting DNNs as scientific models into context, we discuss how DNNs can fruitfully contribute to cognitive science. We claim that beyond their power to provide predictions and explanations of cognitive phenomena, DNNs have the potential to contribute to an often overlooked but ubiquitous and fundamental use of scientific models: exploration., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Global challenges such as climate change or the refugee crises emphasize the necessity of altruism and cooperation. In a large-scale 9-month intervention study, we investigated the malleability of prosociality by three distinct mental trainings cultivating attention, socio-affective, or socio-cognitive skills. We assessed numerous established measures of prosociality that capture three core facets: Altruistically motivated behaviours, norm motivated behaviours, and self-reported prosociality. Results of multiple time point confirmatory factor analyses support the validity and temporal stability of this model. Furthermore, linear mixed effects models reveal differential effects of mental trainings on the subcomponents of prosociality: Only training care and compassion effectively boosted altruistically motivated behaviour. No effects were revealed for norm-based behaviour. Self-reported prosociality increased with all training modules; this increase was, however, unrelated to changes in task-based measures of altruistic behaviour. These findings corroborate our motivation-based framework of prosociality, challenge economic views of fixed preferences by showing that socio-affective training boosts altruism, and inform policy makers and society about how to increase global cooperation.

Automatic imitation is the finding that movement execution is facilitated by compatible and impeded by incompatible observed movements. In the past 15 years, automatic imitation has been studied to understand the relation between perception and action in social interaction. Although research on this topic started in cognitive science, interest quickly spread to related disciplines such as social psychology, clinical psychology, and neuroscience. However, important theoretical questions have remained unanswered. Therefore, in the present meta-analysis, we evaluated seven key questions on automatic imitation. The results, based on 161 studies containing 226 experiments, revealed an overall effect size of g z = 0.95, 95% CI [0.88, 1.02]. Moderator analyses identified automatic imitation as a flexible, largely automatic process that is driven by movement and effector compatibility, but is also influenced by spatial compatibility. Automatic imitation was found to be stronger for forced choice tasks than for simple response tasks, for human agents than for nonhuman agents, and for goalless actions than for goal-directed actions. However, it was not modulated by more subtle factors such as animacy beliefs, motion profiles, or visual perspective. Finally, there was no evidence for a relation between automatic imitation and either empathy or autism. Among other things, these findings point toward actor-imitator similarity as a crucial modulator of automatic imitation and challenge the view that imitative tendencies are an indicator of social functioning. The current meta-analysis has important theoretical implications and sheds light on longstanding controversies in the literature on automatic imitation and related domains. (PsycINFO Database Record, ((c) 2018 APA, all rights reserved).)

Online experimentation is emerging in many areas of cognitive psychology as a viable alternative or supplement to classical in-lab experimentation. While performance- and reaction-time-based paradigms are covered in recent studies, one instrument of cognitive psychology has not received much attention up to now: eye tracking. In this study, we used JavaScript-based eye tracking algorithms recently made available by Papoutsaki et al. (International Joint Conference on Artificial Intelligence, 2016) together with consumer-grade webcams to investigate the potential of online eye tracking to benefit from the common advantages of online data conduction. We compared three in-lab conducted tasks (fixation, pursuit, and free viewing) with online-acquired data to analyze the spatial precision in the first two, and replicability of well-known gazing patterns in the third task. Our results indicate that in-lab data exhibit an offset of about 172 px (15% of screen size, 3.94° visual angle) in the fixation task, while online data is slightly less accurate (18% of screen size, 207 px), and shows higher variance. The same results were found for the pursuit task with a constant offset during the stimulus movement (211 px in-lab, 216 px online). In the free-viewing task, we were able to replicate the high attention attribution to eyes (28.25%) compared to other key regions like the nose (9.71%) and mouth (4.00%). Overall, we found web technology-based eye tracking to be suitable for all three tasks and are confident that the required hard- and software will be improved continuously for even more sophisticated experimental paradigms in all of cognitive psychology.

This commentary explores the relationships between the construct of successful aging and the experimental psychology of human aging-cognitive gerontology. What can or should cognitive gerontology contribute to understanding, defining, and assessing successful aging? Standards for successful aging reflect value judgments that are culturally and historically situated. Fundamentally, they address social policy; they are prescriptive. If individuals or groups are deemed to be aging successfully, then their characteristics or situations can be emulated. If an individual or a group is deemed to be aging unsuccessfully, then intervention should be considered. Although science is never culture-free or ahistorical, cognitive gerontology is primarily descriptive of age-related change. It is not prescriptive. It is argue that cognitive gerontology has little to contribute to setting standards for successful aging. If, however, better cognitive function is taken as a marker of more successful aging-something not universally accepted-then cognitive gerontology can play an important assessment role. It has a great deal to contribute in determining whether an individual or a group evidences better cognitive function than another. More importantly, cognitive gerontology can provide tools to evaluate the effects of interventions. It can provide targeted measures of perception, attention, memory, executive function, and other facets of cognition that are more sensitive to change than most clinical measures. From a deep understanding of factors affecting cognitive function, cognitive gerontology can also suggest possible interventions. A brief narrative review of interventions that have and have not led to improved cognitive function in older adults. Finally, the enormous range is addressed in the estimates of the proportion of the population that meets a standard for aging successfully, from less than 10% to more than 90%. For research purposes, it would be better to replace absolute cutoffs with correlational approaches (e.g., Freund & Baltes, 1998, Psychology and Aging, 13, 531-543). For policy purposes, cutoffs are necessary, but we propose that assessments of successful aging be based not on absolute cutoffs but on population proportions. An example of one possible standard is this: Those more than 1 standard deviation above the mean are aging successfully; those more than 1 standard deviation below the mean are aging unsuccessfully; those in between are aging usually. Adoption of such a standard may reduce the wide discrepancies in the incidence of successful aging reported in the literature.

Stereotype Content Model (SCM) emphasizes the content rather than the underlying processes of the stereotypes and the content might be influenced by several cultural dimensions (e.g., individualism vs. collectivism). The main dimensions of SCM-namely warmth and competence-underlying various contents are assumed to be universal. However, from a cognitive science paradigm, we argue that different research methods (i.e., data collections and data analysis) might also yield different stereotype contents that might impact the universality versus specificity problem in the SCM. Indeed, using a sample from a collectivistic country (i.e., Romania), we found that using different methods in data collection (i.e., unstructured vs. semi-structured vs. structured interview) and different methods of data analysis (i.e., availability vs. accessibility scores) might be an important research strategy to counter artefacts and confusions in the universality versus specificity problem related to the SCM. Theoretical and practical implications are discussed.

Philosophical aesthetics is the branch of philosophy which explores issues having to do with art, beauty, and related phenomena. Philosophers have often been skeptical about the place of empirical investigation in aesthetics. However, in recent years many philosophical aestheticians have turned to cognitive science to enrich their understanding of their subject matter. Cognitive scientists have, in turn, been inspired by work in philosophical aesthetics. This essay focuses on a representative subset of the areas in which there has been fruitful dialog between philosophical aestheticians and cognitive scientists. We start with some general topics in philosophical aesthetics-the definition of art and the epistemic status of aesthetic judgments. We then move on to discussing research concerning the roles that imagination and perception play in our aesthetic engagement. We conclude with a discussion of the emerging field of experimental philosophical aesthetics. WIREs Cogn Sci 2018, 9:e1445. doi: 10.1002/wcs.1445 This article is categorized under: Philosophy > Value., (© 2017 Wiley Periodicals, Inc.)

Written symbols such as letters have been used extensively in cognitive psychology, whether to understand their contributions to written word recognition or to examine the processes involved in other mental functions. Sometimes, however, researchers want to manipulate letters while removing their associated characteristics. A powerful solution to do so is to use new characters, devised to be highly similar to letters, but without the associated sound or name. Given the growing use of artificial characters in experimental paradigms, the aim of the present study was to make available the Brussels Artificial Character Sets (BACS): two full, strictly controlled, and portable sets of artificial characters for a broad range of experimental situations.

The game of chess has often been used for psychological investigations, particularly in cognitive science. The clear-cut rules and well-defined environment of chess provide a model for investigations of basic cognitive processes, such as perception, memory, and problem solving, while the precise rating system for the measurement of skill has enabled investigations of individual differences and expertise-related effects. In the present study, we focus on another appealing feature of chess-namely, the large archive databases associated with the game. The German national chess database presented in this study represents a fruitful ground for the investigation of multiple longitudinal research questions, since it collects the data of over 130,000 players and spans over 25 years. The German chess database collects the data of all players, including hobby players, and all tournaments played. This results in a rich and complete collection of the skill, age, and activity of the whole population of chess players in Germany. The database therefore complements the commonly used expertise approach in cognitive science by opening up new possibilities for the investigation of multiple factors that underlie expertise and skill acquisition. Since large datasets are not common in psychology, their introduction also raises the question of optimal and efficient statistical analysis. We offer the database for download and illustrate how it can be used by providing concrete examples and a step-by-step tutorial using different statistical analyses on a range of topics, including skill development over the lifetime, birth cohort effects, effects of activity and inactivity on skill, and gender differences.

Eye movement analysis is effective for investigating visual perception and cognition. The cost of conducting eye movement studies has decreased as a result of the recent release of low-cost commercial and open-source eye trackers. However, synchronizing visual stimulus presentation with eye movement recording is still difficult, particularly if the eye tracker does not come with a practical application programming interface. This paper introduces a Matlab/Octave toolbox named Sgttoolbox, which works in conjunction with the widely used experiment control library Psychtoolbox to control a cross-platform open-source eye tracker named SimpleGazeTracker, which is an eye-tracking application of GazeParser software. Hardware and software requirements for Sgttoolbox and its main functions are described. A test of temporal accuracy showed that eye movement sampling frequency was stable when stimulus presentation and recording were performed on a single PC, although better performance was obtained when presentation and recording were performed on separate PCs. Transferring the latest eye position from SimpleGazeTracker to Psychtoolbox script takes 2 to 4 ms on average, which causes a delay in drawing multiple visual stimuli when recording and stimulus presentation were performed on a single PC. When such a transfer delay is not importnat, Sgttoolbox would be a good choice for Psychtoolbox users who wish to conduct eye-tracking studies.

BACKGROUND The rostral anterior cingulate cortex (rACC) is important in pain expectation. Previous studies demonstrated that mechanical stimulus-induced withdrawal behaviors are spinally-mediated nocifensive reflexes in rats, but it is not known whether pain expectation is influenced by withdrawal behaviors. MATERIAL AND METHODS We reanalyzed previous mechanosensitivity measurements of 244 rats measured 5 times in succession. To study neural oscillation in the rACC, 1 recording microwire array was surgically implanted. Then, we simultaneously recorded the local field potential (LFP) of the rACC over the course of multiple withdrawal behaviors in unanesthetized rats. RESULTS From our previous withdrawal behavioral data in 244 rats, we observed that the distributions of paw withdrawal thresholds (PWTs) were denser and more concentrated after the first withdrawal behavior. Compared to the first mechanical stimulus, increased neuronal synchrony and a stronger delta band component existed in each pre-stimulus LFP in the rACC during subsequent stimuli. CONCLUSIONS Pain expectation could be involved in withdrawal behaviors, which is related to increased total power and delta band power of the subsequent pre-stimulus LFPs in the rACC.

This article is the second part of a study on the legacy of Jens Rasmussen. The first article, subtitled 'A Strong Program for a Hard Problem', looks back on his 30 years of scientific contribution, from 1969 to 2000. This second article explores and investigates some of the intellectual roots which influenced his thinking, using them as a basis to understand some limits and move forward. Indeed, historically oriented studies such as this one are not only tributes to researchers, but a way to differentiate and contrast our present situation with the past in order to integrate contemporary trends, be they theoretical or empirical, or oriented towards research and new models. In the first section of this article, I offer a synthesis of the background covered in the previous article, but I use a tree here as a graphical complement. Branches of the tree show the many fruitful directions opened by Jens Rasmussen, directions which inspired many researchers. In the second part, I address what I believe to be behind this wealth of engineering legacy: cybernetics. I contend that cybernetics has had a profound influence on his thinking and provided him key principles for his inspiring and successful models. To develop the tree image, one might say that cybernetics is the trunk of the tree. Finally, in the third part, I take the opportunity to explore the relevance of extending and sensitising his program to constructivist discourses. After an introduction to this discourse, identifying four types of constructivisms (cognitive, social, epistemological and anthropological), I characterise this move as a 'constructivist turn'., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Jens Rasmussen's multifaceted legacy includes cognitive work analysis (CWA), a framework for the analysis, design, and evaluation of complex sociotechnical systems. After considering the framework's origins, this paper reviews its progress, predictably covering experimental research on ecological interface design, case studies of the application of CWA to human factors and engineering problems in industry, and methods and modelling tools for CWA. Emphasis is placed, however, on studying the nexus between some of the recent results obtained with CWA and the original field studies of human problem-solving that motivated the framework's development. Of particular interest is a case study of the use of CWA for military doctrine development, a problem commonly regarded as lying outside the fields of human factors and engineering. It is concluded that the value of CWA, even for such diverse problems, is likely to result from its conceptual grounding in empirical observations of patterns of human reasoning in complex systems., (Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.)

This article describes challenges encountered in applying Jens Rasmussen's Cognitive Work Analysis (CWA) framework to the practice of energy efficiency Monitoring & Targeting (M&T). Eight theoretic issues encountered in the analysis are described with respect to Rasmussen's work and the modeling solutions we adopted. We grappled with how to usefully apply Work Domain Analysis (WDA) to analyze categories of domains with secondary purposes and no ideal grain of decomposition. This difficulty encouraged us to pursue Control Task (ConTA) and Strategies (StrA) analysis, which are under-explored as bases for interface design. In ConTA we found M&T was best represented by two interlinked work functions; one controlling energy, the other maintaining knowledge representations. From StrA, we identified a popular representation-dependent strategy and inferred information required to diagnose faults in system performance and knowledge representation. This article presents and discusses excerpts from our analysis, and outlines their application to diagnosis support tools., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Within the cognitive sciences, most researchers assume that it is the job of linguists to investigate how language is represented, and that they do so largely by building theories based on explicit judgments about patterns of acceptability - whereas it is the task of psychologists to determine how language is processed, and that in doing so, they do not typically question the linguists' representational assumptions. We challenge this division of labor by arguing that structural priming provides an implicit method of investigating linguistic representations that should end the current reliance on acceptability judgments. Moreover, structural priming has now reached sufficient methodological maturity to provide substantial evidence about such representations. We argue that evidence from speakers' tendency to repeat their own and others' structural choices supports a linguistic architecture involving a single shallow level of syntax connected to a semantic level containing information about quantification, thematic relations, and information structure, as well as to a phonological level. Many of the linguistic distinctions often used to support complex (or multilevel) syntactic structure are instead captured by semantics; however, the syntactic level includes some specification of "missing" elements that are not realized at the phonological level. We also show that structural priming provides evidence about the consistency of representations across languages and about language development. In sum, we propose that structural priming provides a new basis for understanding the nature of language.

We explore how preferences for attributes are constructed when people choose between multiattribute options. As found in prior research, we observed that while people make decisions, their preferences for the attributes in question shift to support the emerging choice, thus enabling confident decisions. The novelty of the studies reported here is that participants repeated the same task 6 to 8 weeks later. We found that between tasks, preferences returned to near their original levels, only to shift again to support the second choice, regardless of which choice participants made. Similar patterns were observed in a free-choice task (Study 1) and when the favorableness of options was manipulated (Study 2). It follows that preferences behave in an elastic manner: In the absence of situational pressures, they rest at baseline levels, but during the process of reaching a decision, they morph to support the chosen options. This elasticity appears to facilitate confident decision making in the face of decisional conflict.

An organizing model of 'the self' emerges from applying various kinds of brain injury to recent cognitive science and philosophical work on 'the self'. This model unifies various contents and mechanisms central to current notions of the self. The article then highlights several criteria and aspects of this notion of self. Qualities of the right type and level of psychological significance delineate 'the self' as an organizing concept useful for recent philosophical work and cognitive science research., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.

Both cognitive and educational psychology literature strive to investigate human category and concept learning. However, both literatures focus on different phenomena and often use different methodologies. We identify and discuss commonalities and differences between the literatures. This literature comparison reveals that research on relational category learning offers a promising avenue to integration. We suggest that this integration would be especially beneficial to advance our understanding of conceptual change essentially, how complex scientific concepts and categories are acquired and developed in educational contexts elaborating or correcting students' prior conceptions. Furthermore, the focus on relational categories allows us to provide an integrative discussion on how recent lines of research on analogy, memory and category learning, and knowledge restructuring relate to and can inform education. In general, this article advocates the complementary nature of cognitive and educational psychology and identifies viable, and potentially synergistic paths for future research. (PsycINFO Database Record, ((c) 2016 APA, all rights reserved).)

We present a computational model of multiple-object tracking that makes trial-level predictions about the allocation of visual attention and the effect of this allocation on observers' ability to track multiple objects simultaneously. This model follows the intuition that increased attention to a location increases the spatial resolution of its internal representation. Using a combination of empirical and computational experiments, we demonstrate the existence of a tight coupling between cognitive and perceptual resources in this task: Low-level tracking of objects generates bottom-up predictions of error likelihood, and high-level attention allocation selectively reduces error probabilities in attended locations while increasing it at non-attended locations. Whereas earlier models of multiple-object tracking have predicted the big picture relationship between stimulus complexity and response accuracy, our approach makes accurate predictions of both the macro-scale effect of target number and velocity on tracking difficulty and micro-scale variations in difficulty across individual trials and targets arising from the idiosyncratic within-trial interactions of targets and distractors., (Copyright © 2016 Cognitive Science Society, Inc.)

Education is the fundamental process used to develop and maintain the professional skills of physicians. Medical students, residents, and fellows are expected to learn considerable amounts of information as they progress toward board certification. Established practitioners must continue to learn in an effort to remain up-to-date in their clinical realm. Those responsible for educating these populations endeavor to teach in a manner that is effective, efficient, and durable. The study of learning and performance is a subdivision of the field of cognitive science that focuses on how people interpret and process information and how they eventually develop mastery. A deeper understanding of how individuals learn can empower both educators and learners to be more effective in their endeavors. In this article, we review a number of concepts found in the literature on learning and performance. We address both the theoretical principles and the practical applications of each concept. Cognitive load theory, constructivism, and analogical transfer are concepts particularly beneficial to educators. An understanding of goal orientation, metacognition, retrieval, spaced learning, and deliberate practice will primarily benefit the learner. When these concepts are understood and incorporated into education and study, the effectiveness of learning is significantly improved.

The domain of numbers provides a paradigmatic case for investigating interactions of culture, language, and cognition: Numerical competencies are considered a core domain of knowledge, and yet the development of specifically human abilities presupposes cultural and linguistic input by way of counting sequences. These sequences constitute systems with distinct structural properties, the cross-linguistic variability of which has implications for number representation and processing. Such representational effects are scrutinized for two types of verbal numeration systems-general and object-specific ones-that were in parallel use in several Oceanic languages (English with its general system is included for comparison). The analysis indicates that the object-specific systems outperform the general systems with respect to counting and mental arithmetic, largely due to their regular and more compact representation. What these findings reveal on cognitive diversity, how the conjectures involved speak to more general issues in cognitive science, and how the approach taken here might help to bridge the gap between anthropology and other cognitive sciences is discussed in the conclusion., (Copyright © 2015 Cognitive Science Society, Inc.)

We begin our commentary by summarizing the commonalities and differences in cognitive phenomena across cultures, as found by the seven papers of this topic. We then assess the commonalities and differences in how our various authors have approached the study of cognitive diversity, and speculate on the need for, and potential of, cross-disciplinary collaboration., (Copyright © 2015 Cognitive Science Society, Inc.)

Media outlets are reporting that cognitive enhancement is reaching epidemic levels, but evidence is lacking and ethical questions remain. The US Presidential Commission for the Study of Bioethical Issues (Bioethics Commission) has examined the issue, and we lay out the commission's findings and their relevance for the scientific community., (Published by Elsevier Ltd.)

Natural and supernatural explanations are used to interpret the same events in a number of predictable and universal ways. Yet little is known about how variation in diverse cultural ecologies influences how people integrate natural and supernatural explanations. Here, we examine explanatory coexistence in three existentially arousing domains of human thought: illness, death, and human origins using qualitative data from interviews conducted in Tanna, Vanuatu. Vanuatu, a Melanesian archipelago, provides a cultural context ideal for examining variation in explanatory coexistence due to the lack of industrialization and the relatively recent introduction of Christianity and Western education. We argue for the integration of interdisciplinary methodologies from cognitive science and anthropology to inform research on explanatory coexistence., (Copyright © 2015 Cognitive Science Society, Inc.)