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Cognitive economics is an emerging interdisciplinary field that uses the tools of cognitive science to study economic and social decision-making. Although most strains of cognitive economics share commitments to bridging levels of analysis (cognitive, behavioral, and systems) and embracing interdisciplinary approaches, we review a newer strand of cognitive economic thinking with a further commitment: conceptualizing minds and markets each as complex adaptive systems. We describe three ongoing research programs that strive toward these goals: (i) studying narratives as a cognitive and social representation used to guide decision-making; (ii) building cognitively informed agent-based models; and (iii) understanding markets as an extended mind - the Market Mind Hypothesis - analyzed using the concepts, methods, and tools of Coordination Dynamics., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This theme issue brings together researchers from diverse fields to assess the current status and future prospects of embodied cognition in the age of generative artificial intelligence. In this introduction, we first clarify our view of embodiment as a potentially unifying concept in the study of cognition, characterizing this as a perspective that questions mind-body dualism and recognizes a profound continuity between sensorimotor action in the world and more abstract forms of cognition. We then consider how this unifying concept is developed and elaborated by the other contributions to this issue, identifying the following two key themes: (i) the role of language in cognition and its entanglement with the body and (ii) bodily mechanisms of interpersonal perception and alignment across the domains of social affiliation, teaching and learning. On balance, we consider that embodied approaches to the study of cognition, culture and evolution remain promising, but will require greater integration across disciplines to fully realize their potential. We conclude by suggesting that researchers will need to be ready and able to meet the various methodological, theoretical and practical challenges this will entail and remain open to encountering markedly different viewpoints about how and why embodiment matters. This article is the part of this theme issue 'Minds in movement: embodied cognition in the age of artificial intelligence'.

In our 2023 paper, entitled "Modeling interactions between the embodied and the narrative self: Dynamics of the self-pattern within LIDA," Kugele, Newen, Franklin, and I propose a functional description and implementation of a central element of Gallagher & Newen's pattern theory of self, which identifies an agent's self with a dynamic pattern of so-called cognitive aspects which govern their thought and behavior (Gallagher, 2013; Newen, 2018; Gallagher & Daly, 2018). The pattern theory explicitly rejects the traditional conceptualization of the self as a unitary entity with certain properties that resides within agents, with the idea of a pattern of aspects being central to its ability to account for the dynamic, yet relatively stable development of most natural agents' selves. Implementing the pattern theory within Learning Intelligent Distribution Agent revealed that, in order for a cognitive architecture to account for both the dynamic and stable nature of an agent's self-pattern, aspects of that pattern had to be realized by dispositions of the agent to either think or act in a certain way. In this commentary, I argue that this fundamental role of dispositions extends to cognitive processes in general and that cognitive systems should be understood in terms of the dynamical interactions of dispositions over time. In order to facilitate such an understanding, dispositions will have to be identified with topologies of cognitive (sub)systems. I provide an example of such a topology by reference to informational topologies in neuronal systems., Competing Interests: Declaration of conflicting interestsThe author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Elections, jury deliberations, lawmaking, high-stakes negotiations and related activities are human attempts to answer the question "How should we live?" Collectively, we know these activities as politics. Politics are how societies attempt to reconcile diverse individual needs with potential benefits of social coordination. People's beliefs about what others will do ainfluence many political strategies and outcomes. This article reviews how properties of cognition affect these political phenomena. Contrary to the common belief that many citizens are too ignorant to make competent political decisions, we focus on a central finding of social science-how societies can design contexts and environments to overcome individual cognitive limitations. These adaptations expand societal capacities to provide essential goods, services, and protections. In addition to explaining these adaptations, we also show how greater collaborations between cognitive science and the social sciences can help societies do even better., (© 2023 The Authors. Topics in Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society.)

To introduce our special issue How Minds Work: The Collective in the Individual, we propose "radical CI," a form of collective intelligence, as a new paradigm for cognitive science. Radical CI posits that the representations and processes necessary to perform the cognitive functions that humans perform are collective entities, not encapsulated by any individual. To explain cognitive performance, it appeals to the distribution of cognitive labor on the assumption that the human project runs on countless interactions between locally acting individuals with specialized skills that each retain a small part of the relevant information. Some of the papers in the special issue appeal to radical CI to account for a variety of cognitive phenomena including memory performance, metacognition, belief updating, reasoning, and problem-solving. Other papers focus on the cultural and institutional practices that make radical CI possible., (© 2024 Cognitive Science Society LLC.)

We explore systems of spatial deictic words (such as 'here' and 'there') from the perspective of communicative efficiency using typological data from over 200 languages Nintemann et al. (2020). We argue from an information-theoretic perspective that spatial deictic systems balance informativity and complexity in the sense of the Information Bottleneck (Zaslavsky et al., (2018). We find that under an appropriate choice of cost function and need probability over meanings, among all the 21,146 theoretically possible spatial deictic systems, those adopted by real languages lie near an efficient frontier of informativity and complexity. Moreover, we find that the conditions that the need probability and the cost function need to satisfy for this result are consistent with the cognitive science literature on spatial cognition, especially regarding the source-goal asymmetry. We further show that the typological data are better explained by introducing a notion of consistency into the Information Bottleneck framework, which is jointly optimized along with informativity and complexity., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Quilty-Dunn et al. defended the reemergence of language-of-thought hypothesis (LoTH). My commentary builds up implications for the study of the development of our logical capacities. Empirical support for logically augmented LoT systems calls for the investigation of their logical primitives and developmental origin. Furthermore, Quilty-Dunn et al.'s characterization of LoT helps the quest for the foundation of logic by dissociating logical cognition from natural language.

There are two versions of the language-of-thought hypothesis (LOT): Representational LOT (roughly, structured representation), introduced by Ockham, and computational LOT (roughly, symbolic computation) introduced by Fodor. Like many others, I oppose the latter but not the former. Quilty-Dunn et al. defend representational LOT, but they do not defend the strong computational LOT thesis central to the classical-connectionist debate.

Despite its many twists and turns, the arc of cognitive science generally bends toward progress, thanks to its interdisciplinary nature. By glancing at the last few decades of experimental and computational advances, it can be argued that-far from failing to converge on a shared set of conceptual assumptions-the field is indeed making steady consensual progress toward what can broadly be referred to as interactive frameworks. This inclination is apparent in the subfields of psycholinguistics, visual perception, embodied cognition, extended cognition, neural networks, dynamical systems theory, and more. This pictorial essay briefly documents this steady progress both from a bird's eye view and from the trenches. The conclusion is one of optimism that cognitive science is getting there, albeit slowly and arduously, like any good science should., (© 2023 The Authors. Topics in Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society.)

Mental representations remain the central posits of psychology after many decades of scrutiny. However, there is no consensus about the representational format(s) of biological cognition. This paper provides a survey of evidence from computational cognitive psychology, perceptual psychology, developmental psychology, comparative psychology, and social psychology, and concludes that one type of format that routinely crops up is the language-of-thought (LoT). We outline six core properties of LoTs: (i) discrete constituents; (ii) role-filler independence; (iii) predicate-argument structure; (iv) logical operators; (v) inferential promiscuity; and (vi) abstract content. These properties cluster together throughout cognitive science. Bayesian computational modeling, compositional features of object perception, complex infant and animal reasoning, and automatic, intuitive cognition in adults all implicate LoT-like structures. Instead of regarding LoT as a relic of the previous century, researchers in cognitive science and philosophy-of-mind must take seriously the explanatory breadth of LoT-based architectures. We grant that the mind may harbor many formats and architectures, including iconic and associative structures as well as deep-neural-network-like architectures. However, as computational/representational approaches to the mind continue to advance, classical compositional symbolic structures - that is, LoTs - only prove more flexible and well-supported over time.

Cognitive science has been traditionally organized around the individual as the basic unit of cognition. Despite developments in areas such as communication, human-machine interaction, group behavior, and community organization, the individual-centric approach heavily dominates both cognitive research and its application. A promising direction for cognitive science is the study of augmented intelligence, or the way social and technological systems interact with and extend individual cognition. The cognitive science of augmented intelligence holds promise in helping society tackle major real-world challenges that can only be discovered and solved by teams made of individuals and machines with complementary skills who can productively collaborate with each other., (© 2022 Cognitive Science Society LLC.)

How does human cognition adapt to idiosyncratic features of our real-world experiences across our lifetimes? The dynamic interaction between individuals and their natural environments is rarely the focus of study within cognitive science, but I argue that a more ecological approach will be critical for advancing developmental science and revealing the adaptive nature of cognition., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

How can we study unobservable cognitive processes that cannot be measured directly? This has been an enduring challenge for cognitive scientists. In this essay we discuss advances in neurotechnology that could allow cognitive processes to be decoded in real-time and the implications that this may have for cognitive science and the treatment of neuropsychiatric disease., Competing Interests: Declaration of interests The authors declare no conflicts of interest., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The study of human cognition and the study of artificial intelligence (AI) have a symbiotic relationship, with advancements in one field often informing or creating new work in the other. Human cognition has many capabilities modern AI systems cannot compete with. One such capability is the detection, identification, and resolution of knowledge gaps (KGs). Using these capabilities as inspiration, we examine how to incorporate detection, identification, and resolution of KGs in artificial agents. We present a paradigm that enables research on the understanding of KGs for visual-linguistic communication. We leverage and enhance and existing KG taxonomy to identify possible KGs that can occur for visual question answer (VQA) tasks and use these findings to develop a classifier to identify questions that could be engineered to contain specific KG types for other VQA datasets. Additionally, we examine the performance of different VQA models through the lens of KGs., (© 2021 Cognitive Science Society LLC.)

An efficient integration of sensory and motor processes is crucial to goal-directed behavior. Despite this high relevance, and although cognitive theories provide clear conceptual frameworks, the neurobiological basis of these processes remains insufficiently understood. In a double-blind, randomized placebo-controlled pharmacological study, we examine the relevance of catecholamines for perception-motor integration processes. Using EEG data, we perform an in-depth analysis of the underlying neurophysiological mechanisms, focusing on sensorimotor integration processes during response inhibition. We show that the catecholaminergic system affects sensorimotor integration during response inhibition by modulating the stability of the representational content. Importantly, catecholamine levels do not affect the stability of all aspects of information processing during sensorimotor integration, but rather-as suggested by cognitive theory-of specific codes in the neurophysiological signal. Particularly fronto-parietal cortical regions are associated with the identified mechanisms. The study shows how cognitive science theory-driven pharmacology can shed light on the neurobiological basis of perception-motor integration and how catecholamines affect specific information codes relevant to cognitive control., (© 2022. The Author(s).)

Many scientists routinely generalize from study samples to larger populations. It is commonly assumed that this cognitive process of scientific induction is a voluntary inference in which researchers assess the generalizability of their data and then draw conclusions accordingly. We challenge this view and argue for a novel account. The account describes scientific induction as involving by default a generalization bias that operates automatically and frequently leads researchers to unintentionally generalize their findings without sufficient evidence. The result is unwarranted, overgeneralized conclusions. We support this account of scientific induction by integrating a range of disparate findings from across the cognitive sciences that have until now not been connected to research on the nature of scientific induction. The view that scientific induction involves by default a generalization bias calls for a revision of the current thinking about scientific induction and highlights an overlooked cause of the replication crisis in the sciences. Commonly proposed interventions to tackle scientific overgeneralizations that may feed into this crisis need to be supplemented with cognitive debiasing strategies against generalization bias to most effectively improve science., (© 2022 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)

Conviction Narrative Theory (CNT) is a theory of choice under radical uncertainty - situations where outcomes cannot be enumerated and probabilities cannot be assigned. Whereas most theories of choice assume that people rely on (potentially biased) probabilistic judgments, such theories cannot account for adaptive decision-making when probabilities cannot be assigned. CNT proposes that people use narratives - structured representations of causal, temporal, analogical, and valence relationships - rather than probabilities, as the currency of thought that unifies our sense-making and decision-making faculties. According to CNT, narratives arise from the interplay between individual cognition and the social environment, with reasoners adopting a narrative that feels "right" to explain the available data; using that narrative to imagine plausible futures; and affectively evaluating those imagined futures to make a choice. Evidence from many areas of the cognitive, behavioral, and social sciences supports this basic model, including lab experiments, interview studies, and econometric analyses. We identify 12 propositions to explain how the mental representations (narratives) interact with four inter-related processes (explanation, simulation, affective evaluation, and communication), examining the theoretical and empirical basis for each. We conclude by discussing how CNT can provide a common vocabulary for researchers studying everyday choices across areas of the decision sciences.

Unlike animal behavior, behavior in plants is traditionally assumed to be completely determined either genetically or environmentally. Under this assumption, plants are usually considered to be noncognitive organisms. This view nonetheless clashes with a growing body of empirical research that shows that many sophisticated cognitive capabilities traditionally assumed to be exclusive to animals are exhibited by plants too. Yet, if plants can be considered cognitive, even in a minimal sense, can they also be considered conscious? Some authors defend that the quest for plant consciousness is worth pursuing, under the premise that sentience can play a role in facilitating plant's sophisticated behavior. The goal of this article is not to provide a positive argument for plant cognition and consciousness, but to invite a constructive, empirically informed debate about it. After reviewing the empirical literature concerning plant cognition, we introduce the reader to the emerging field of plant neurobiology. Research on plant electrical and chemical signaling can help shed light into the biological bases for plant sentience. To conclude, we shall present a series of approaches to scientifically investigate plant consciousness. In sum, we invite the reader to consider the idea that if consciousness boils down to some form of biological adaptation, we should not exclude a priori the possibility that plants have evolved their own phenomenal experience of the world. This article is categorized under: Cognitive Biology > Evolutionary Roots of Cognition Philosophy > Consciousness Neuroscience > Cognition., (© 2021 The Authors. WIREs Cognitive Science published by Wiley Periodicals LLC.)

Cognitive researchers often carve cognition up into structures and processes. Cognitive processes operate on structures, like vehicles driving over a map. Language alongside semantic and episodic memory are proposed to have structure, as are perceptual systems. Over these structures, processes operate to construct memory and solve problems by retrieving and manipulating information. Network science offers an approach to representing cognitive structures and has made tremendous inroads into understanding the nature of cognitive structure and process. But is the mind a network? If so, what kind? In this article, we briefly review the main metaphors, assumptions, and pitfalls prevalent in cognitive network science (maps and vehicles; one network/process to rule them all), highlight the need for new metaphors that elaborate on the map-and-vehicle framework (wormholes, skyhooks, and generators), and present open questions in studying the mind as a network (the challenge of capturing network change, what should the edges of cognitive networks be made of, and aggregated vs. individual-based networks). One critical lesson of this exercise is that the richness of the mind as network approach makes it a powerful tool in its own right; it has helped to make our assumptions more visible, generating new and fascinating questions, and enriching the prospects for future research. A second lesson is that the mind as a network-though useful-is incomplete. The mind is not a network, but it may contain them., (© 2021 Cognitive Science Society LLC.)

A central goal for cognitive science and philosophy of mind is to distinguish between perception and cognition. The representational approach has emerged as a prominent candidate to draw such a distinction. The idea is that perception and cognition differ in the content and the format in which the information is represented -just as perceptual representations are nonconceptual in content and iconic in format, cognitive representations are conceptual in content and discursive in format. This paper argues against this view. I argue that both perception and cognition can use conceptual and nonconceptual contents and be vehiculated in iconic and discursive formats. If correct, the representational strategy to distinguish perception from cognition fails., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Science regularly experiences periods in which simply describing the world is prioritised over attempting to explain it. Cognition, this journal, came into being some 45 years ago as an attempt to lay one such period to rest; without doubt, it has helped create the current cognitive science climate in which theory is decidedly welcome. Here we summarise the reasons why a theoretical approach is imperative in our field, and call attention to some potentially counter-productive trends in which cognitive models are concerned too exclusively with how processes work at the expense of why the processes exist in the first place and thus what the goal of modelling them must be., (Crown Copyright © 2021. Published by Elsevier B.V. All rights reserved.)

Jacques Mehler and I started Cognition, to break the grip of empiricist associationist behaviorism and stultifying style requirements on scientific discourse, and to liberate Cognitive Psychology's contributions to social issues. The journal provided opportunities for upcoming generations to expand Cognitive Psychology, publishing new concepts unhindered by established topics and standard formats. As the journal matured, Jacques kept. it fresh for 4 decades, seeking young scientists, novel ideas, and elegant writing, as it midwifed the emergence from Reductionist Behaviorism through Cognitive Psychology to rationalist Cognitive Science. The journal now has opportunities to nurture further progress in the future of Cognitive Science. I speculate that the field will keep associationist processes but integrate them with a new kind of non-reductionist theory that eschews detailed predictions, and which which interprets the brain as an enactor of thought, but not its structural cause. Ideally it will provide a set of constraints on the action of brain and mind that subsume and explain behavioral regularities, the role of frequency, how the brain externalizes those constraints and how the externalization processes emerge developmentally as a function of innate factors, structures unique to the mind and brain, experience and natural law., (Published by Elsevier B.V.)

Objectives: Determine intra-individual changes in CogSport performance in elite cricket players diagnosed with concussion, and differentiate this from changes which may be attributed to post-match with no head impact., Design: Retrospective observational study of elite Australian male and female cricket players with diagnosed concussion and prospective cohort study of cricket players with no head impact post-match., Methods: CogSport performance relative to an individual's baseline was compared between 46 cricket players diagnosed with concussion following a head impact sustained during a match, and 84 cricket players who played a match during which they had no head impact., Results: CogSport performance post-match for players diagnosed with concussion was slower for detection speed (p < 0.001), identification speed (p = 0.007), and one back speed (p = 0.011). No changes in one card learning speed or any accuracy measures were observed. CogSport performance post-match with no head impact was faster but less accurate for one card learning (both p < 0.001). No changes in the other three test components were observed., Conclusions: Slower performance in three of four CogSport tasks (detection, identification, one back) may be indicative of concussion, as these intra-individual changes were not observed in players post-match with no head impact. The fourth task, one card learning, may not be a useful indicator of concussion as it was not observed to change with concussion yet was susceptible to change post-match with no head impact. CogSport may have clinical utility in assisting the clinical diagnosis of concussion in elite male and female cricket players., (Copyright © 2020 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.)

Nervous systems' computational abilities are an evolutionary innovation, specializing and speed-optimizing ancient biophysical dynamics. Bioelectric signalling originated in cells' communication with the outside world and with each other, enabling cooperation towards adaptive construction and repair of multicellular bodies. Here, we review the emerging field of developmental bioelectricity, which links the field of basal cognition to state-of-the-art questions in regenerative medicine, synthetic bioengineering and even artificial intelligence. One of the predictions of this view is that regeneration and regulative development can restore correct large-scale anatomies from diverse starting states because, like the brain, they exploit bioelectric encoding of distributed goal states-in this case, pattern memories. We propose a new interpretation of recent stochastic regenerative phenotypes in planaria, by appealing to computational models of memory representation and processing in the brain. Moreover, we discuss novel findings showing that bioelectric changes induced in planaria can be stored in tissue for over a week, thus revealing that somatic bioelectric circuits in vivo can implement a long-term, re-writable memory medium. A consideration of the mechanisms, evolution and functionality of basal cognition makes novel predictions and provides an integrative perspective on the evolution, physiology and biomedicine of information processing in vivo . This article is part of the theme issue 'Basal cognition: multicellularity, neurons and the cognitive lens'.

The premise of this two-part theme issue is simple: the cognitive sciences should join the rest of the life sciences in how they approach the quarry within their research domain. Specifically, understanding how organisms on the lower branches of the phylogenetic tree become familiar with, value and exploit elements of an ecological niche while avoiding harm can be expected to aid understanding of how organisms that evolved later (including Homo sapiens ) do the same or similar things. We call this approach basal cognition. In this introductory essay, we explain what the approach involves. Because no definition of cognition exists that reflects its biological basis, we advance a working definition that can be operationalized; introduce a behaviour-generating toolkit of capacities that comprise the function (e.g. sensing/perception, memory, valence, learning, decision making, communication), each element of which can be studied relatively independently; and identify a (necessarily incomplete) suite of common biophysical mechanisms found throughout the domains of life involved in implementing the toolkit. The articles in this collection illuminate different aspects of basal cognition across different forms of biological organization, from prokaryotes and single-celled eukaryotes-the focus of Part 1-to plants and finally to animals, without and with nervous systems, the focus of Part 2. By showcasing work in diverse, currently disconnected fields, we hope to sketch the outline of a new multidisciplinary approach for comprehending cognition, arguably the most fascinating and hard-to-fathom evolved function on this planet. Doing so has the potential to shed light on problems in a wide variety of research domains, including microbiology, immunology, zoology, biophysics, botany, developmental biology, neurobiology/science, regenerative medicine, computational biology, artificial life and synthetic bioengineering. This article is part of the theme issue 'Basal cognition: conceptual tools and the view from the single cell'.

I argue that an enactivist framework has more explanatory power than traditional philosophical theories of cognition when it comes to understanding the mechanisms underlying human-animal relationships. In both intraspecies and interspecies exchanges, what we often find are novel forms of cognition emerging from such transactions, but these "co-cognitive" processes cannot be understood apart from the interaction itself. I focus on a specific form of human-animal interaction-play, as it occurs between humans and domestic dogs-and argue that the best theory suited to the task of explaining how these two species create unique thought processes is a "sympoietic enactivism." Rather than the more common "autopoietic" arguments defended by many enactivists, I argue that what is more accurately occurring during bouts of human-dog play is sympoietic, or "collectively producing." Drawing on several different disciplines that converge on similar conclusions about creativity and collaboration, I show that human-dog play is a quintessential case of cognition that cannot be readily understood by appealing to the inner workings of either individual among the dyad. Thinking, on this view, is a form of play, and in playful interaction what gets created are wholly intersubjective modes of thought.

Systems Factorial Technology (SFT) is a popular framework for that has been used to investigate processing capacity across many psychological domains over the past 25+ years. To date, it had been assumed that no processing resources are used for sources in which no signal has been presented (i.e., in a location that can contain a signal but does not on a given trial). Hence, response times are purely driven by the signal-containing location or locations. This assumption is critical to the underlying mathematics of the capacity coefficient measure of SFT. In this article, we show that stimulus locations influence response times even when they contain no signal, and that this influence has repercussions for the interpretation of processing capacity under the SFT framework, particularly in conjunctive (AND) tasks-where positive responses require detection of signals in multiple locations. We propose a modification to the AND task requiring participants to fully identify both target locations on all trials. This modification allows a new coefficient to be derived. We apply the new coefficient to novel experimental data and resolve a previously reported empirical paradox, where observed capacity was limited in an OR detection task but super capacity in an AND detection task. Hence, previously reported differences in processing capacity between OR and AND task designs are likely to have been spurious. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Mobility is integral to mankind, but current cognitive research on migrants is almost nonexistent. Most of the existing knowledge on human cognition is based on data collected from (and by) the wealthiest and least mobile citizens of the world. In turn, most of the migration literature relies on superficial, and at times erroneous, assumptions regarding the cognitive processes underlying migratory phenomenon. However, research conducted to date in reveals striking convergences between core issues relevant to scholars in cognitive science on the one hand, and in migration studies on the other. This current lack on cross-disciplinary dialog has no scientific grounds for two fields, which are inherently interdisciplinary, and yet it has concerning sociopolitical implications. Mapping out a novel research agenda at the crossroads of the cognitive and social sciences, this article stands as an invitation for researchers to engage in further collaborative work involving joint data collections and joint data analyses. This paper argues that researching migrant cognition would give more breadth to cognitive science and more depth to migration studies, which has the potential to better inform the design of public policies. Though the examples of (a) visual perception, (b) future-oriented cognition, and (c) language acquisition, this article shows that pairing the discoveries of migration scholars and cognitive scientists can move forward our understanding on the human mind, in an ever-moving world. This article is categorized under: Economics > Individual Decision-Making Psychology > Theory and Methods Psychology > Comparative Psychology Psychology > Language., (© 2020 Wiley Periodicals LLC.)

An important aspect of intelligence is the ability to adapt to a novel task without any direct experience (zero shot), based on its relationship to previous tasks. Humans can exhibit this cognitive flexibility. By contrast, models that achieve superhuman performance in specific tasks often fail to adapt to even slight task alterations. To address this, we propose a general computational framework for adapting to novel tasks based on their relationship to prior tasks. We begin by learning vector representations of tasks. To adapt to new tasks, we propose metamappings, higher-order tasks that transform basic task representations. We demonstrate the effectiveness of this framework across a wide variety of tasks and computational paradigms, ranging from regression to image classification and reinforcement learning. We compare to both human adaptability and language-based approaches to zero-shot learning. Across these domains, metamapping is successful, often achieving 80 to 90% performance, without any data, on a novel task, even when the new task directly contradicts prior experience. We further show that metamapping can not only generalize to new tasks via learned relationships, but can also generalize using novel relationships unseen during training. Finally, using metamapping as a starting point can dramatically accelerate later learning on a new task and reduce learning time and cumulative error substantially. Our results provide insight into a possible computational basis of intelligent adaptability and offer a possible framework for modeling cognitive flexibility and building more flexible artificial intelligence systems., Competing Interests: The authors declare no competing interest.

Background: Researchers often misinterpret and misrepresent statistical outputs. This abuse has led to a large literature on modification or replacement of testing thresholds and P-values with confidence intervals, Bayes factors, and other devices. Because the core problems appear cognitive rather than statistical, we review some simple methods to aid researchers in interpreting statistical outputs. These methods emphasize logical and information concepts over probability, and thus may be more robust to common misinterpretations than are traditional descriptions., Methods: We use the Shannon transform of the P-value p, also known as the binary surprisal or S-value s = -log 2 (p), to provide a measure of the information supplied by the testing procedure, and to help calibrate intuitions against simple physical experiments like coin tossing. We also use tables or graphs of test statistics for alternative hypotheses, and interval estimates for different percentile levels, to thwart fallacies arising from arbitrary dichotomies. Finally, we reinterpret P-values and interval estimates in unconditional terms, which describe compatibility of data with the entire set of analysis assumptions. We illustrate these methods with a reanalysis of data from an existing record-based cohort study., Conclusions: In line with other recent recommendations, we advise that teaching materials and research reports discuss P-values as measures of compatibility rather than significance, compute P-values for alternative hypotheses whenever they are computed for null hypotheses, and interpret interval estimates as showing values of high compatibility with data, rather than regions of confidence. Our recommendations emphasize cognitive devices for displaying the compatibility of the observed data with various hypotheses of interest, rather than focusing on single hypothesis tests or interval estimates. We believe these simple reforms are well worth the minor effort they require.

Religious conversion involves changes in the convert's way of thinking and behaving. This paper focuses on the unique form that this transformative process took within the Christian monastic movement in late antiquity. Treating monastic conversion as a gradual process in which the convert is an active participant, it examines the ways in which monastic converts were able to intentionally promote such a change and influence its direction. This study draws on research in cognitive psychology and neuroscience on the cognitive underpinnings of self-transformation in order to reconstruct from the literary sources of Near Eastern monasticism the strategies and training methods that late antique monks employed in order to facilitate and sustain the transformation implicated in conversion.

Leider and Griffiths clarify the basis for unification between mechanism-driven and solution-driven disciplines and methodologies in cognitive science. But, two outstanding issues arise for their model of resource-rationality: human brains co-process information with their environments, rather than merely adapt to them; and this is expressed in methodological differences between disciplines that complicate Leider and Griffiths' proposed structural unification.

Cognitive engineering is focused on how humans can cope and master the complexity of processes and technological environments. In cardiothoracic surgery, the goal is to support safe and effective human performance by preventing medical errors. Strategies derived from cognitive engineering research could be introduced in cardiothoracic surgery practice in the near future to enhance patient safety and outcomes., (Copyright © 2019 Elsevier Inc. All rights reserved.)

First, I argue that there is no agreement within non-classical cognitive science as to whether one should eliminate representations, hence, it is not clear that Brette's appeal to it is going to solve the problems with coding. Second, I argue that Brette's criticism of predictive coding as being intellectualistic is not justified, as predictive coding is compatible with embodied cognition.

Although cognitive science started in the 1970s as a multidisciplinary field with the goal of becoming an interdisciplinary one over time, it is now dominated by cognitive psychology. The question becomes whether this matters, and if it does, what should cognitive scientists do about it? I propose that the multidisciplinarity and interdisciplinarity of cognitive science does matter because it leads to potential generation of new ideas, models, and methods. I offer a few recommendations for reforming cognitive science based, in part, on the recent 41st annual meeting of the Cognitive Science Society that sought to reopen cognitive science to minority disciplines comprising cognitive science., (© 2019 Cognitive Science Society, Inc.)

Polarization is one of the biggest societal challenges of our time, yet its drivers are poorly understood. Here we propose a novel approach - computational political psychology - which uses behavioral tasks in combination with formal computational models to identify candidate cognitive processes underpinning susceptibility to polarized beliefs about political and societal issues., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

In his enormously influential The Modularity of Mind, Jerry Fodor (1983) proposed that the mind was divided into input modules and central processes. Much subsequent research focused on the modules and whether processes like speech perception or spatial vision are truly modular. Much less attention has been given to Fodor's writing on the central processes, what would today be called higher-level cognition. In "Fodor's First Law of the Nonexistence of Cognitive Science," he argued that central processes are "bad candidates for scientific study" and would resist attempts at empirical analysis. This essay evaluates his argument for this remarkable claim, concluding that although central processes may well be "messier" than input modules, this does not mean that they cannot be studied and understood. The article briefly reviews the scientific progress made in understanding central processes in the 35 years since the book was published, showing that Fodor's prediction is clearly falsified by massive advances in topics like decision making and analogy. The essay concludes that Fodor's Law was not based on a clear argument for why the complexities of central systems could not be studied but was likely based on intuitions and preferences that were common in psychology at the time., (© 2019 Cognitive Science Society, Inc.)

The capacity for abstract thought is one of the hallmarks of human cognition. However, the mechanisms underlying the ability to form and use abstract concepts like 'fantasy' and 'grace' have not been elucidated yet. This theme issue brings together developmental, social and cognitive psychologists, linguists, anthropologists, cognitive scientists, neuroscientists, philosophers and computer scientists to present theoretical insights and novel evidence on how abstract concepts are acquired, used and represented in the brain. Many of the contributions conceive concepts as grounded in sensorimotor systems and constrained by bodily mechanisms and structures. The theme issue develops along two main axes, related to the most promising research directions on abstract concepts. The axes focus on (i) the different kinds of abstract concepts (numbers, emotions, evaluative concepts like moral and aesthetic ones, social concepts); (ii) the role played by perception and action, language and sociality, and inner processes (emotions, interoception, metacognition) in grounding abstract concepts. Most papers adopt a cognitive science/neuroscience approach, but the theme issue also includes studies on development, on social cognition, and on how linguistic diversity shapes abstract concepts. Overall, the theme issue provides an integrated theoretical account that highlights the importance of language, sociality and inner processes for abstract concepts, and that offers new methodological tools to investigate them.This article is part of the theme issue 'Varieties of abstract concepts: development, use and representation in the brain'., (© 2018 The Author(s).)