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In this article, with the help of Heidegger and Foucault's conceptual tools, as well as the achievements of the cognitive science, we try to examine the transition from paper reading to digital reading. This discussion can be a preparation for a philosophical understanding of the digital age. We show that Heidegger's analysis of the ready-to-hand beings and technology can help to understand the reading behaviors of paper and digital readers. We have also use Heidegger's analytical framework for text ontology. On the other hand, Foucault's reflections on the embodied technologies can explain the power-knowledge relationships that is constructed around the reader. In addition, the cognitive science has provided detailed empirical findings on the effects of reading behaviors on the human cognitive biases and skills by examining the various modes of reading. Embodied and skillful cognitive science, by going beyond the computational understanding of human beings, has noticed the various behaviors and states of the body in reading processes and highlighted their effects. To integrate these areas of research, we try to place the findings of the cognitive science within the framework of Heidegger and Foucault's technological understanding of the modern power-knowledge relationships. [ABSTRACT FROM AUTHOR]

Abstract concepts are relevant to a wide range of disciplines, including cognitive science, linguistics, psychology, cognitive, social, and affective neuroscience, and philosophy. This consensus paper synthesizes the work and views of researchers in the field, discussing current perspectives on theoretical and methodological issues, and recommendations for future research. In this paper, we urge researchers to go beyond the traditional abstract-concrete dichotomy and consider the multiple dimensions that characterize concepts (e.g., sensorimotor experience, social interaction, conceptual metaphor), as well as the mediating influence of linguistic and cultural context on conceptual representations. We also promote the use of interactive methods to investigate both the comprehension and production of abstract concepts, while also focusing on individual differences in conceptual representations. Overall, we argue that abstract concepts should be studied in a more nuanced way that takes into account their complexity and diversity, which should permit us a fuller, more holistic understanding of abstract cognition. [ABSTRACT FROM AUTHOR]

Reading primary research literature is an essential skill for all scientists and students on science degree programmes, however little is known about how researchers at different career stages interact with and interpret scientific papers. To explore this, we conducted a survey of 260 undergraduate students and researchers in Biological Sciences at a research intensive UK university. Responses to Likert scale questions demonstrated increases in confidence and skill with reading the literature between individuals at each career stage, including between postdoctoral researchers and faculty academics. The survey indicated that individuals at different career stages valued different sections of scientific papers, and skill in reading the results section develops slowly over the course of an academic career. Inexperienced readers found the methods and results sections of research papers the most difficult to read, and undervalued the importance of the results section and critical interpretation of data. These data highlight a need for structured support with reading scientific literature at multiple career stages, and for senior academics to be aware that junior colleagues may prioritise their reading differently. We propose a model for the development of literature processing skills, and consider the need for training strategies to help inexperienced readers engage with primary literature, and therefore develop important skills that underpin scientific careers. We also encourage researchers to be mindful of language used when writing papers, and to be more inclusive of diverse audiences when disseminating their work. [ABSTRACT FROM AUTHOR]

Is cognitive science interdisciplinary or multidisciplinary? We contribute to this debate by examining the authorship structure and topic similarity of contributions to the Cognitive Science Society from 2000 to 2019. Our analysis focuses on graph theoretic features of the co‐authorship network—edge density, transitivity, and maximum subgraph size—as well as clustering within the space of scientific topics. We also combine structural and semantic information with an analysis of how authors choose their collaborators based on their interests and prior collaborations. We compare findings from CogSci to abstracts from the Vision Science Society over the same time frame and validate our approach by predicting new collaborations in the 2020 CogSci proceedings. Our results suggest that collaboration across authors and topics within cognitive science has become increasingly integrated in the last 19 years. More broadly, we argue that a formal quantitative approach which combines structural co‐authorship information and semantic topic analysis provides inroads to questions about the level of interdisciplinary collaboration in a scientific community. DeStefano, Oey, Brockbank, and Vul explore interdisciplinary collaboration using data‐driven measures of research topics and co‐authorship, constructed from a rich dataset of over 11,000 Cogsci conference papers. Findings suggest the cognitive science research community has become increasingly integrated in the last 19 years. [ABSTRACT FROM AUTHOR]

Artificial neural network models are able to achieve great performance at numerous computationally challenging tasks like face recognition. It is of significant importance to explore the difference between neural network models and human brains in terms of computational mechanism. This issue has become an experimental focus for some researchers in recent studies, and it is believed that using human behavior to understand neural network models can address this issue. This paper compares the neural network model performance with human performance on a classic yet important task: judging the ethnicity of a given face. This study uses Caucasian and East Asian faces to train 4 neural networks including AlexNet, VGG11, VGG13, and VGG16. Then, the ethnicity judgments of the neural networks are compared with human data using classical psychophysical methods by fitting psychometric curves. The results suggest that VGG11, followed by VGG16, shows a similar response pattern as humans, while simpler AlexNet and more complex VGG13 do not resemble human performance. Thus, this paper explores a new paradigm to compare neural networks and human brains. • Neural networks are able to provide cognitive approaches from face perception. • Human perception is used as a benchmark to evaluate the performance of neural networks. • Neural networks utilizing eye regions are confirmed to be better to perceive faces. • Attentional region analysis would unveil the processing details of a neural network. [ABSTRACT FROM AUTHOR]

This paper proposes epistemic environmentalism as a novel framework for accounting for the contribution of the environment – broadly construed – to epistemic standings and which can be used to improve or protect epistemic environments. The contribution of the environment to epistemic standings is explained through recent developments in epistemology and cognitive science, including embodied cognition, embedded cognition, extended cognition and distributed cognition. The paper examines how these developments support epistemic environmentalism, as well as contributes theoretical resources to make epistemic assessments of dynamic environments. The epistemic environmentalist procedure from the assessment of an individual environment to changes made to that environment based on promoting the attainment of epistemic goods is also discussed. [ABSTRACT FROM AUTHOR]

While research evidence has the potential to improve classroom practice, research–practice gaps continue to persist not least owing to the limited relevance of research findings for practice. A common approach in healthcare to address the research–practice gap is to form research priority setting partnerships (PSPs) in which stakeholders identify questions they would like research to answer. This paper presents the results from such a PSP in education with a focus on cognitive science research, which has received increased attention in the past few years owing to its potential to explain memory and learning processes and inform classroom practice. Over 400 questions from teachers were collected using an online survey. The final 15 research priorities highlight the need for research on a wider range of subjects, settings and phases as well as research designs that take the complexity of classrooms into consideration and aim to answer how different teaching strategies interact with each other as well as student motivation and agency at the micro‐ and macro‐level. The role of teacher expertise vs. fidelity to original research designs should also be investigated further. Overall, this paper highlights the importance of taking teacher voice into account to ensure that new research in the field is both academically rigorous and practically relevant. [ABSTRACT FROM AUTHOR]

The Semantic Link Network is a general semantic model for modeling the structure and the evolution of complex systems. Various semantic links play different roles in rendering the semantics of complex system. One of the basic semantic links represents cause-effect relation, which plays an important role in representation and understanding. This paper verifies the role of the Semantic Link Network in representing the core of text by investigating the contribution of cause-effect link to representing the core of scientific papers. Research carries out with the following steps: (1) Two propositions on the contribution of cause-effect link in rendering the core of paper are proposed and verified through a statistical survey, which shows that the sentences on cause-effect links cover about 65% of key words within each paper on average. (2) An algorithm based on syntactic patterns is designed for automatically extracting cause-effect link from scientific papers, which recalls about 70% of manually annotated cause-effect links on average, indicating that the result adapts to the scale of data sets. (3) The effects of cause-effect link on four schemes of incorporating cause-effect link into the existing instances of the Semantic Link Network for enhancing the summarization of scientific papers are investigated. The experiments show that the quality of the summaries is significantly improved, which verifies the role of semantic links. The significance of this research lies in two aspects: (1) it verifies that the Semantic Link Network connects the important concepts to render the core of text; and, (2) it provides an evidence for realizing content services such as summarization, recommendation and question answering based on the Semantic Link Network, and it can inspire relevant research on content computing. [ABSTRACT FROM AUTHOR]

The need to complete multiple tasks concurrently is a common occurrence both daily life and in occupational activities, which can often include simultaneous cognitive and physical demands. As one example, there is increasing availability of head-worn display technologies that can be employed when a user is mobile (e.g., while walking). This new method of information presentation may, however, introduce risks of adverse outcomes such as a decrement to gait performance. The goal of this study was thus to quantify the effects of a head-worn display (i.e., smart glasses) on motor variability during gait and to compare these effects with those of other common information displays (i.e., smartphone and paper-based system). Twenty participants completed four walking conditions, as a single task and in three dual-task conditions (three information displays). In the dual-task conditions, the information display was used to present several cognitive tasks. Three different measures were used to quantify variability in gait parameters for each walking condition (using the cycle-to-cycle standard deviation, sample entropy, and the “goal-equivalent manifold” approach). Our results indicated that participants used less adaptable gait strategies in dual-task walking using the paper-based system and smartphone conditions compared with single-task walking. Gait performance, however, was less affected during dual-task walking with the smart glasses. We conclude that the risk of an adverse gait event (e.g., a fall) in head-down walking conditions (i.e., the paper-based system and smartphone conditions) were higher than in single-task walking, and that head-worn displays might help reduce the risk of such events during dual-task gait conditions. [ABSTRACT FROM AUTHOR]

This paper aims to show that properties of cognitive/conceptual representations and formal‐logical structures of linguistic meaning can be inter‐translated, recast, transformed into one another, and so united together, even though cognitive/conceptual representations and formal‐logical structures of linguistic meaning are apparently distinct in ontology and divergent in their form or character. While cognitive/conceptual representations are ultimately rooted in sensory‐motor systems, formal‐logical structures of linguistic meaning are abstractions detached from and independent of the actualized world. This paper sketches out the foundations of how representations of linguistic meaning in terms of cognitive/conceptual structures in Cognitive/Conceptual Semantics can be unified with those in terms of formal‐logical structures in Formal Semantics. This is done by recasting cognitive/conceptual representations in terms of formal‐logical structures of linguistic meaning and re‐encoding formal‐logical structures of linguistic meaning in terms of cognitive/conceptual representations. Then, these two types of semantic representations, thus shown representationally equivalent, will be related to a series of derivations across levels in neuronal networks and dynamics. The general discussion on unifying cognitive/conceptual representations of linguistic meaning with formal‐logical structures is contextualized within the broader context of theorizing in cognitive science. [ABSTRACT FROM AUTHOR]

Historically, the dispute between empiricists and nativists in philosophy and cognitive science has concerned human and animal minds (Margolis and Laurence in Philos Stud: An Int J Philos Anal Tradit 165(2): 693-718, 2013, Ritchie in Synthese 199(Suppl 1): 159–176, 2021, Colombo in Synthese 195: 4817–4838, 2018). But recent progress has highlighted how empiricist and nativist concerns arise in the construction of artificial systems (Buckner in From deep learning to rational machines: What the history of philosophy can teach us about the future of artificial intelligence. Oxford University Press.). This paper uses nativism and empiricism to address questions about the nature of artificial intelligence and its trajectory. It begins by defining the nativism/empiricism debate in terms of the generality of a system. Nativist systems have initial states with domain-specific features; empiricist systems have initial states with only domain-general features. With the debate framed in this way, it then explores a variety of arguments for nativism and empiricism in AI. These arguments revolve around two different questions which must be distinguished: whether nativism the only possible approach to developing human-level AI (HLAI); and whether nativism is the most practical approach to developing HLAI. On the first question, it argues that nativism is quite clearly not the only possible approach to developing HLAI, as is sometimes suggested. It argues that existing arguments for the necessity of nativism are unconvincing, because they analogize from poverty of the stimulus arguments about humans, while AIs often have access to much more data than humans. Then it argues that the case of evolution gives us a compelling argument against nativism. On the second, practical question, the paper argues that there is a tradeoff between the advantages of encoding innate machinery directly, and the advantages of evolving or learning it. However, as the past decade has shown, empiricism is a much more viable path to greater capability levels, given the 'bitter lesson' (Sutton in Reinforcement Learning: An Introduction. MIT press.) that encoding the 'correct' knowledge in AI systems is perennially outperformed by more empiricist methods that leverage large-scale data and computation. [ABSTRACT FROM AUTHOR]

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. The notion that cognition is collective has a long pedigree but is enjoying considerable attention in the cognitive sciences as multiple fields of study deliver evidence for the central role of community and culture in cognition. To introduce the special issue of topiCS surveying this groundswell, we propose the concept of "radical collective intelligence," the view that some of the key representations and processes necessary to perform the cognitive functions that humans perform are collective entities, not encapsulated by any individual. This concept clarifies how the volume's contributions either rethink long‐studied cognitive processes (memory, metacognition, reasoning) or contemplate how radical CI can arise. [ABSTRACT FROM AUTHOR]

Do highly productive researchers have significantly higher probability to produce top cited papers? Or do high productive researchers mainly produce a sea of irrelevant papers—in other words do we find a diminishing marginal result from productivity? The answer on these questions is important, as it may help to answer the question of whether the increased competition and increased use of indicators for research evaluation and accountability focus has perverse effects or not. We use a Swedish author disambiguated dataset consisting of 48.000 researchers and their WoS-publications during the period of 2008–2011 with citations until 2014 to investigate the relation between productivity and production of highly cited papers. As the analysis shows, quantity does make a difference. [ABSTRACT FROM AUTHOR]

The growing integration of renewable energy sources into grid-connected microgrids has created new challenges in power generation forecasting and energy management. This paper explores the use of advanced machine learning algorithms, specifically Support Vector Regression (SVR), to enhance the efficiency and reliability of these systems. The proposed SVR algorithm leverages comprehensive historical energy production data, detailed weather patterns, and dynamic grid conditions to accurately forecast power generation. Our model demonstrated significantly lower error metrics compared to traditional linear regression models, achieving a Mean Squared Error of 2.002 for solar PV and 3.059 for wind power forecasting. The Mean Absolute Error was reduced to 0.547 for solar PV and 0.825 for wind scenarios, and the Root Mean Squared Error (RMSE) was 1.415 for solar PV and 1.749 for wind power, showcasing the model's superior accuracy. Enhanced predictive accuracy directly contributes to optimized resource allocation, enabling more precise control of energy generation schedules and reducing the reliance on external power sources. The application of our SVR model resulted in an 8.4% reduction in overall operating costs, highlighting its effectiveness in improving energy management efficiency. Furthermore, the system's ability to predict fluctuations in energy output allowed for adaptive real-time energy management, reducing grid stress and enhancing system stability. This approach led to a 10% improvement in the balance between supply and demand, a 15% reduction in peak load demand, and a 12% increase in the utilization of renewable energy sources. Our approach enhances grid stability by better balancing supply and demand, mitigating the variability and intermittency of renewable energy sources. These advancements promote a more sustainable integration of renewable energy into the microgrid, contributing to a cleaner, more resilient, and efficient energy infrastructure. The findings of this research provide valuable insights into the development of intelligent energy systems capable of adapting to changing conditions, paving the way for future innovations in energy management. Additionally, this work underscores the potential of machine learning to revolutionize energy management practices by providing more accurate, reliable, and cost-effective solutions for integrating renewable energy into existing grid infrastructures. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) policy, innovation, and practice are moving ahead in rapid fashion. There is a growing mismatch between technological innovations in AI, which are advancing at a rapid rate, and normative and regulatory frameworks, which are lagging, particularly when it comes to protecting democratic values and human rights principles. National governments and multilateral institutions are attempting to catch up. At least 175 countries, firms and other organizations have produced documents listing ethical principles for AI. These efforts have proceeded in a somewhat fragmented manner, yet there are emerging signs of consolidation as the United States, Europe, and other countries begin to coalesce around shared principles. Europe, in particular, has raced ahead to draft comprehensive legislation, the Artificial Intelligence Act (AIA), to oversee these technologies and systems. What has motivated the European Union to pursue this approach? And how will this effort influence AI norms globally? This paper describes how Europe's AI norm-building process represents an effort to ensure EU priorities are reflected in the AI governance landscape. Europe's approach faces uncertainty. While it is likely that the AIA will meaningfully influence global AI norms, several factors may hinder its global diffusion and adoption. [ABSTRACT FROM AUTHOR]

Marek Pokropski's "Mechanisms and Consciousness Integrating Phenomenology with Cognitive Science" reopens the question about the possibility of naturalization of phenomenology. The author adopts the position of nonreductive mechanistic integration, which, he claims, has offered new methodological perspectives for studying complex mental phenomena such as consciousness. In this paper, I outline the context of the discussions on the relationship between phenomenology and cognitive sciences, and (§2) discuss the approach proposed by Pokropski, pointing out the main arguments and the most important research achievements. Then I focus on some difficulties of this position. The first of these I associate with a procedure which I call a dismemberment of phenomenology (§3). The second (§4) concerns the concept of constraint, which is key to Pokropski's analyzes, and some consequences of its application and alternative reading. Finally, in §5 I draw attention to two difficulties. The first is whether it is possible to read phenomenology in terms of functional analysis; the second is related to the doubt whether psychological or phenomenological functional explanations can be treated as mechanistic (which is a strong premise of Pokropski's argument). In Conclusion I make an overall assessment of the presented approach. [ABSTRACT FROM AUTHOR]

Ignorance, or the lack of knowledge, appears to be steadily spreading, despite the increasing availability of information. The notion of informed ignorance herein proposed to describe the widespread position of being exposed to an abundance of information yet lacking relevant knowledge, which is tied to the exponential growth in misinformation driven by technological developments and social media. Linked to many of societies' most looming catastrophes, from political polarization to the climate crisis, practices related to knowledge and information are deemed some of the most imminent and daunting modern threats, evidenced by the latest report of the World Economic Forum, which has named misinformation the most severe short-term global risk. This paper's epistemic perspective links the properties of today's information culture and the ways in which it interacts with individual capacities and limitations in current technological and socio-political contexts. Such a position is analyzed through the lens of epistemic principles as a contemporary epistemic phenotype that emerges from an environment of ill-adapted and excessive information inputs and leads to a distinctive type of social injustice that is primarily epistemic in nature. While equity and accessibility are widely discussed as important contributing factors to epistemic discrepancies, other overlooked but fundamental issues underlying epistemic injustices are considered, such as information manipulation, cognitive limitations, and epistemic degradation. To effectively face this elusive threat, we propose an inclusive viewpoint that harnesses knowledge from cognitive science, science and technology studies, and social epistemology to inform a unifying theory of its main impacts and driving forces. By adjusting a modern epistemic framework to the described phenomena, we intend to contextually outline its trajectory and possible means of containment based on a shared responsibility to maintain ethical epistemic standards. In a time of international unrest and mounting civil acts of violence, it is pertinent to emphasize the ethical principles of knowledge systems and authorities and suggest policy adaptations to maintain a social contract based on the shared values of truth and freedom. [ABSTRACT FROM AUTHOR]

In this paper, we demonstrate the advantages of combining the detailed military history of actual battles with contemporary decision-making cognitive theories. Specifically, we analyse two battle decisions made in Israeli-Arab wars, and interpret, through a cognitive lens, some of the decisions that were subsequently deemed "incomprehensible" in the civilian and military literature. This perspective permits analysis of multiple processes – such as risk evaluation, mental completion of unknown information, and estimation of enemy response. Moreover, it predicts that even highly experienced commanders are prone to the effect of cognitive biases, and may therefore make bad decisions with disastrous consequences. [ABSTRACT FROM AUTHOR]

It is important to implement detection and assessment of plant diseases based on remotely sensed data for disease monitoring and control. Hyperspectral data of healthy leaves, leaves in incubation period and leaves in diseased period of wheat stripe rust and wheat leaf rust were collected under in-field conditions using a black-paper-based measuring method developed in this study. After data preprocessing, the models to identify the diseases were built using distinguished partial least squares (DPLS) and support vector machine (SVM), and the disease severity inversion models of stripe rust and the disease severity inversion models of leaf rust were built using quantitative partial least squares (QPLS) and support vector regression (SVR). All the models were validated by using leave-one-out cross validation and external validation. The diseases could be discriminated using both distinguished partial least squares and support vector machine with the accuracies of more than 99%. For each wheat rust, disease severity levels were accurately retrieved using both the optimal QPLS models and the optimal SVR models with the coefficients of determination (R2) of more than 0.90 and the root mean square errors (RMSE) of less than 0.15. The results demonstrated that identification and severity evaluation of stripe rust and leaf rust at the leaf level could be implemented based on the hyperspectral data acquired using the developed method. A scientific basis was provided for implementing disease monitoring by using aerial and space remote sensing technologies. [ABSTRACT FROM AUTHOR]

Cognitive science-informed approaches have gained considerable influence in education in the UK and internationally, but not much is known about how teachers perceive cognitive science-informed strategies or enact them within the contexts of their everyday classrooms. In this paper, we discuss the perceptions and experiences of cognitive science-informed strategies of 13 teachers in England. The paper critically explores how the teachers understood and used cognitive science-informed strategies in their teaching, their views of the benefits and challenges for different subjects and groups of learners, and their reflections on supporting factors and barriers for adopting the strategies in their schools. The teachers' accounts illustrate some of the many complexities of adopting cognitive science-informed approaches in real-life educational settings. Drawing on their narratives, the paper emphasises the importance of acknowledging different contextual dimensions and the dynamic interactions between them to understand when and how teachers enact cognitive science-informed approaches in their classrooms. [ABSTRACT FROM AUTHOR]

Cognitive communication research with Chinese characteristics is both the theoretical innovation and practical exploration in the interdisciplinary fields of communication and cognitive science. In recent years, under the context of interdisciplinary research, cognitive communication research in China is no longer limited to the discussion of its disciplinary boundary and its legitimacy. According to the former literature, researchers have discussed the three main topics of cognitive communication: the knowledge system of cognitive communication, the framework of cognitive neurocommunication and the applied research of cognitive communication. However, the discipline construction of cognitive communication in China is still in the stage of exploration. Both how to form an independent and original cognitive communication knowledge system and how to put the theoretical vision in the local context and respond to the social problems need to be explained and to be closely integrated with Chinese characteristics in the cognitive communication research. In order to systematically illustrate the Chinese characteristics of cognitive communication research, this paper focuses on four basic questions: what to construct, why to construct, how to construct and what to do. Then, this paper constructs a four-dimensional framework which includes the value system, the dynamic system, the knowledge production system and the application system. This paper (1) discusses the theoretical construction with Chinese characteristics in the value system. (2) integrates the background of disciplinary development and the trend of technological development into the dynamic system of cognitive communication research. (3) focuses on the theoretical innovation based on practice in the knowledge production system. (4) then explores the implement of cognitive communication with Chinese characteristics in overall strategic needs of the country. This study suggests that, under the construction of philosophy and social sciences with Chinese characteristics, cognitive communication with Chinese characteristics needs to ascertain the value orientation, characteristic and research objective. Under the impetus of practice power, discipline development power and tool power, cognitive communication continues to have Chinese characteristics. Cognitive communication with Chinese characteristics needs to be completed in terms of establishing the guiding position of Marxism, integrating multi-theory and solving important problems, which can reflect Chinese characteristics in academic research, theoretical construction and problem-orientation. Finally, in the insight of cognitive pattern, exploration of cognitive mechanism and innovation of cognitive tools, the research result of cognitive communication can be used in practical applications. Compared to previous research, this paper has made extensions in the following aspects: Firstly, this paper has constructed the interactive and complex four-dimensional framework for the study of cognitive communication with Chinese characteristics, which suggests the essential requirements of Chinese characteristics in cognitive communication. At the same time, it explores the approach to the local study of cognitive communication, hoping to establish a subject status in constructing original theories, to keep up with local practice and respond to real problems. Secondly, this paper, closely related to the practice of socialist construction with Chinese characteristics, explores the possible practical aspects of cognitive communication, aiming at exploring and solving real problems. The four-dimensional framework helps to explicit the essence, the development motivation, the implementation approach and the application of the study of cognitive communication with Chinese characteristics, which helps to form the Chinese style of cognitive communication, to expand the Chinese research team of cognitive communication, and to infuse Chinese style into the international academic exchange of cognitive communication, which makes the future cognitive communication research move towards the construction direction of "Chinese characteristics" and finally, the cognitive communication discipline with Chinese characteristics will be constructed. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses articles in the issue on the topics including demonstrates exciting results based on self-imitation learning within a cross-modal setting; and providing advances in controllable generation and interpolation across attributes.

An editorial is presented which discusses the collaborative writing with multiple authors which has additional challenges including varied levels of engagement of coauthors, provision of fair credit through authorship or acknowledgements and acceptance of diversity of work styles. Also discussed are the 10 simple rules for collaboratively writing a multi-authored paper which include to build a writing team wisely; to create a data management plan and to jointly decide on authorship guidelines.

The victories of the Go-playing artificial intelligence (AI) "AlphaGo" against professional player Lee Sedol in 2016 had a profound impact on public and academic perceptions of AI. This event shocked observers, as the ability of a machine to defeat a world champion human in a highly complex game seemed to indicate that a machine had achieved human-like—or more than human—intelligence. But why was AlphaGo so readily anthropomorphized by academic and non-academic audiences alike? Drawing from existing analyses of reactions to and arguments concerning AlphaGo and AI generally, this paper argues that "generative" cognitive science—a school of thought exemplified by the linguistic work of Noam Chomsky—offers two novel contributions to this subject. First, generativism sheds light on an irrational double standard in the study of the human mind in contrast to the study of non-cognitive systems—"methodological dualism"—which, I argue, has been transferred to evaluations of AlphaGo and other AI. Second, by exposing this irrational double standard in perceptions of AI, I employ generativism's more well-known arguments concerning the nature of human intelligence and its scientific study to the evaluation of AI, exposing deficient interpretations widely used in the case of AlphaGo and AI generally. [ABSTRACT FROM AUTHOR]

Researchers in cognitive science have long been interested in modeling human perception using statistical methods. This requires maneuvers because these multiple dimensional data are always intertwined with complex inner structures. The previous studies in cognitive sciences commonly applied principal component analysis (PCA) to truncate data dimensions when dealing with data with multiple dimensions. This is not necessarily because of its merit in terms of mathematical algorithm, but partly because it is easy to conduct with commonly accessible statistical software. On the other hand, dimension reduction might not be the best analysis when modeling data with no more than 20 dimensions. Using state-of-the-art techniques, researchers in various research disciplines (e.g., computer vision) classified data with more than hundreds of dimensions with neural networks and revealed the inner structure of the data. Therefore, it might be more sophisticated to process human perception data directly with neural networks. In this paper, we introduce the multi-dimensional data analysis platform (MuDAP), a powerful toolbox for data analysis in cognitive science. It utilizes artificial intelligence as well as network analysis, an analysis method that takes advantage of data symmetry. With the graphic user interface, a researcher, with or without previous experience, could analyze multiple dimensional data with great ease. [ABSTRACT FROM AUTHOR]

In his article in Science, Nicolas Gisin claimed that quantum correlations emerge from outside space–time. We explainthat they are due to space-time symmetries. This paper is a critical review of metaphysical conclusions found in many recent articles. It advocates the importance of contextuality, Einstein -causality and global symmetries. Bell tests allow only rejecting probabilistic coupling provided by a local hidden variable model, but they do not justify metaphysical speculations about quantum nonlocality and objects which know about each other's state, even when separated by large distances. The violation of Bell inequalities in physics and in cognitive science can be explained using the notion of Bohr- contextuality. If contextual variables, describing varying experimental contexts, are correctly incorporated into a probabilistic model, then the Bell–CHSH inequalities cannot be proven and nonlocal correlations may be explained in an intuitive way. We also elucidate the meaning of statistical independence assumption incorrectly called free choice, measurement independence or no- conspiracy. Since correlation does not imply causation, the violation of statistical independence should be called contextuality; it does not restrict the experimenter's freedom of choice. Therefore, contrary to what is believed, closing the freedom-of choice loophole does not close the contextuality loophole. [ABSTRACT FROM AUTHOR]

Caregivers, i.e., parents, grandparents, and anyone caring for children, make up the majority of users in many urban centers around the world, including in China. Yet urban design and planning rarely consider specific needs of caregivers. This can result in a negative perception among people that cities are unfriendly places to raise children. Such negative perception is among the major contributors to the aging population problem, as parents and parents-to-be feel reluctant to give birth and raise more than one or even any children. Using an interdisciplinary approach, i.e., cognitive science, psychology, behavioral economics, and urban studies, this paper examines a new city model of "parent-friendly city," where urban design serves the needs of caregivers, effectively creating a perception that cities are friendly places for raising children. First, we identify that caregivers' needs are characterized by two major factors: (1) provision: parents want to provide for their children, such as providing places for play and learning, and (2) restoration: parents want to restore things that they lack due to childcare responsibilities, such as lack of rest and interaction with other adults. Second, we offer cognitive-based design principles that can work powerfully and effectively to fill both needs. Third, using real case studies from cities in China and around the world, we illustrate how these design principles work, even reversing caregivers' perception from negative to positive. Ultimately, thoughtful urban design can support parents in raising children, making cities into partners in parenthood. [ABSTRACT FROM AUTHOR]

Bounded rationality gets a bad rap in epistemology. It is argued that theories of bounded rationality are overly context‐sensitive; conventionalist; or dependent on ordinary language (Carr, 2022; Pasnau, 2013). In this paper, I have three aims. The first is to set out and motivate an approach to bounded rationality in epistemology inspired by traditional theories of bounded rationality in cognitive science. My second aim is to show how this approach can answer recent challenges raised for theories of bounded rationality. My third aim is to clarify the role of rational ideals in bounded rationality. [ABSTRACT FROM AUTHOR]

The Free Energy Principle (FEP) and Integrated Information Theory (IIT) are two ambitious theoretical approaches. The first aims to make a formal framework for describing self-organizing and life-like systems in general, and the second attempts a mathematical theory of conscious experience based on the intrinsic properties of a system. They are each concerned with complementary aspects of the properties of systems, one with life and behavior, the other with meaning and experience, so combining them has potential for scientific value. In this paper, we take a first step towards such a synthesis by expanding on the results of an earlier published evolutionary simulation study, which show a relationship between IIT-measures and fitness in differing complexities of tasks. We relate a basic information theoretic measure from the FEP, surprisal, to this result, finding that the surprisal of simulated agents' observations is inversely related to the general increase in fitness and integration over evolutionary time. Moreover, surprisal fluctuates together with IIT-based consciousness measures in within-trial time. This suggests that the consciousness measures used in IIT indirectly depend on the relation between the agent and the external world, and that it should therefore be possible to relate them to the theoretical concepts used in the FEP. Lastly, we suggest a future approach for investigating this relationship empirically. Author summary: Two influential theoretical frameworks in cognitive science, neuroscience and computational biology, are the Free Energy Principle and Integrated Information Theory. The first is a formal approach to self-organization and adaptive behavior ‐ in short, life ‐ based on first principles from statistical physics. The second is an attempt at formally describing the intrinsic experience of a given system, that is, how it feels to be that system. In this way, these two theories provide tools for understanding two complementary aspects of a given organism; namely, how it acts in a goal-directed manner based on statistical beliefs about the world, and how it feels to be that system in that process. In this paper, we provide an initial numerical investigation of the potential relation of these theoretical frameworks. We simulate agents that undergo evolution, and show that as their level of integration (Φ, a measure from Integrated Information Theory) increases, information theoretic surprisal (a quantity used in the Free Energy Principle) decreases. We also see that Φ and surprisal fluctuate together, and that these fluctuations depend on sensory input. Finally we provide considerations for future simulation work, and how to bring these two theoretical frameworks closer together. [ABSTRACT FROM AUTHOR]

Right now one of remarkable features of clashes between countries is frequent cognitive warfare. In order to control emotions of the public, US and Western countries use a lot of theories on cognitive dissonance and psychodynamics to develop information and publicity in grey zone when facing enemy countries. But related researches always rely on traditional frames of strategic communication to understand the new kind of warfare, neglecting the beginning of cognitive turn of strategic communication or the important effects of cognitive sciences on the core logic of traditional strategic communication. This paper uses paradigms of cognitive sciences, securitization, semiotics and narratives to analyze critical topic field of cognitive strategic communication and indicates the research propositions of public opinion and group communication in cyber space, which are divided into two strategies of cultivating KOL to lead good opinions and constructing commonwealth or fighting enemies in bias of emotions. The ultimate pursuit of cognitive strategic communication is general national security, which includes three approaches of breaking information lockout, carrying out strategic deception and defending non-material territories. In realities, cognitive strategic communication always focuses on practices of new public diplomacy that demonstrate in manipulating narratives and spreading strong symbols for reconstructing“brain frontier”of the public of rivals. This paper concludes that national narrative ability and symbol spreading ability should be promoted unceasingly, the basic constructions, theoretical schema, system mechanism of cognitive strategic communication must be improved in the future. Compared with related documents, this paper hopes to make innovations as followings: (1) start a new academic sphere by integrating paradigms of politics, communication studies, military science, national security science, psychology, narratives, semiotics and break the stereotype of detecting strategic communication or national security under one perspective; (2) put forward an important concept of cognitive strategic communication under the grand frame of national security, upgrade the traditional system of strategic communication and meet theoretical requirements of cognitive warfare in practice; (3) the raising of cognitive strategic communication is expected to take the lead of western academic research in the related fields and complete discourse transformation; (4) link the science of journalism and communication with national security for the first time and illustrate the importance and urgency of breaking information monopoly and defending non-material territories. This paper penetrates self-speech and industry regulation of information single discipline of science, marches on complex dimension of multi-disciplinary cross connection; Based on the connecting historic context and global background, this paper emphasizes the combination of world vision and Chinese text, Chinese expression, Chinese ideas, which is an important research on theories of international communication with Chinese characteristics. [ABSTRACT FROM AUTHOR]

The prosperity of Chinese philosophy and social sciences necessitates knowledge independence and theoretical innovation, which in turn guides the mission and direction of academic maturity and development. Chinese cognitive communication research originated from the trend of our epoch of cognitive turn responding to the development needs of the breakthrough of the communication discipline. As a result, the cross-boundary dialogue and convergence of multiple knowledge were stimulated, benefiting its interdisciplinary characteristics. This discipline gradually completed the transformation of the "Chinese style" discipline and became a fresh experience of the construction of the New Liberal Arts Initiative (NLAI) after more than ten years of path exploration. However, Chinese cognitive communication research is still in a dilemma of interdisciplinary research which emphasizes the importance of facing the suspicion and pain of discipline legitimacy by forming self-awareness of a fully-fledged academic subject through articulating the position, establishing the independent scientific principle, clearing a self-consistent value of the academic and forming a deep consciousness of Chinese discipline construction. This paper systematically examined 979 articles sourced from CSSCI using the formalism approach. The goal is to inspect the disciplinary practice and characteristics of Chinese cognitive communication research, predict its transformation into a fully-fledged academic subject, and illuminate its way of promoting disciplinary consciousness. The results show that the "disciplinary exploration" of Chinese cognitive communication research was executed from the aspects of "positioning", "practice" and "organization". Nevertheless, this discipline is trapped in the path of dependence induced by inflexible means of interdisciplinary research and its outlook is overshadowed by the contradictory properties of disciplinary, which forces it to pursue innovative structural thinking, firmly anchored in a bedrock of shared values, while simultaneously embracing the dynamism inherent in distinctive creation in order to tackle these hurdles. So it’s imperative to undertake a meticulous examination of the field of this discipline involving scrutinizing the logical framework of knowledge, which is established through the development of a well-defined conceptual system, and making dedicated efforts toward advancing theoretical innovation. The impediments that hinder this emerging discipline may be overcome by confronting the challenges brought about by cutting-edge technology, engaging in inter-civilizational learning to assimilate cognitive knowledge from various cultures around the world, leveraging the enriching discourse resources of classical Chinese philosophy, and re-evaluating the humanistic implications of Chinese cognitive communication research, based on which it can reconstruct the domain of research via the consistent and coherent logical connotation of the methods and discourse. In this way, Chinese cognitive communication research will be transformed into a comprehensive insight into the live world and take the main responsibility of governance decisions and scientific prosperity. Compared with previous studies, this paper tries to integrate the academic frontier and Chinese context, combining the latest achievements of cognitive science and ancient Chinese cognitive wisdom. The thinking model was constructed on the basis of the systematic literature review, with the help of diversified knowledge paradigms to lead this discipline to the path of knowledge independence and broad domain. According to this idea, Chinese cognitive communication research will incorporate literature and function, promoting mutual learning and coexistence of civilizations, advancing human digital civilization, and Chinese modernization. [ABSTRACT FROM AUTHOR]

Computational models of memory presented in this issue reflect varied empirical data and levels of representation. From mathematical models to neural and cognitive architectures, all aim to converge on a unified theory of the mind. [ABSTRACT FROM AUTHOR]

All papers will be fully peer reviewed with publication of the full issue scheduled for later in the same year. Belief in conspiracy theories has become widespread, from COVID-19 and vaccinations to climate change and QAnon. [Extracted from the article]

Knauff and Gazzo Castañeda (2022) object to using the term "new paradigm" to describe recent developments in the psychology of reasoning. This paper concedes that the Kuhnian term "paradigm" may be queried. What cannot is that the work subsumed under this heading is part of a new, progressive movement that spans the brain and cognitive sciences: Bayesian cognitive science. Sampling algorithms and Bayes nets used to explain biases in JDM can implement the Bayesian new paradigm approach belying any advantages of mental models theory (MMT) at the algorithmic level. Moreover, this paper argues that new versions of MMT lack a computational level theory and questions the grounds for MMTs much-vaunted generality. The paper then examines common ground on the importance of small-scale models/simulations of the world and the importance of argumentation in the social domain rather than individual reasoning. Finally, the paper concludes that although there may be prospects for moving reasoning research forward in a more collective, collaborative manner, many disagreements remain to be resolved. [ABSTRACT FROM AUTHOR]

This essay takes up the framework of Semiotic Cultural Psychology, which in last decade was very productive in analyzing societal phenomena. Digging into complex sensemaking mechanisms, underlying the interaction between individual and his surrounding environment, has consolidated a base of empirical data gathered from different societies. Aiming to better understand the role of culture in this interaction, the current paper proposes to bridge these findings of observable macro-processes with the ones from the Active inference theory and cognitive science. Similarities between the two frameworks, as well as possible benefits of employing them for one goal, are discussed in this paper. [ABSTRACT FROM AUTHOR]

How to account for the power that art holds over us? Why do artworks touch us deeply, consoling, transforming or invigorating us in the process? In this paper, we argue that an answer to this question might emerge from a fecund framework in cognitive science known as predictive processing (a.k.a. active inference). We unpack how this approach connects sense-making and aesthetic experiences through the idea of an 'epistemic arc', consisting of three parts (curiosity, epistemic action and aha experiences), which we cast as aspects of active inference. We then show how epistemic arcs are built and sustained by artworks to provide us with those satisfying experiences that we tend to call 'aesthetic'. Next, we defuse two key objections to this approach; namely, that it places undue emphasis on the cognitive component of our aesthetic encounters—at the expense of affective aspects—and on closure and uncertainty minimization (order)—at the expense of openness and lingering uncertainty (change). We show that the approach offers crucial resources to account for the open-ended, free and playful behaviour inherent in aesthetic experiences. The upshot is a promising but deflationary approach, both philosophically informed and psychologically sound, that opens new empirical avenues for understanding our aesthetic encounters. This article is part of the theme issue 'Art, aesthetics and predictive processing: theoretical and empirical perspectives'. [ABSTRACT FROM AUTHOR]

In this paper, I discuss the emerging field of conceptual engineering from the perspective of the philosophy of mind and cognitive science. I explore the role the latter disciplines can and do play by specifically focusing on how different notions of what a concept is affects the general conceptual engineering framework, both positively and negatively, before considering a particular account that eschews talk of concepts altogether. I call this project 'Cappelen's challenge' as it draws from suggestive remarks in his work (Cappelen, H. 2018. Fixing Language: Conceptual Engineering and the Limits of Revision. Oxford: Oxford University Press). I argue that by appreciating the range of options that each theory of concepts brings with it, the field as a whole can come to better grips with its foundations. [ABSTRACT FROM AUTHOR]

This paper aims at integrating insights from ecological psychology, pragmatism, and embodied cognitive science to shed light on the aesthetic dimension underlying daily activities. For this purpose, we discuss conceptions of the aesthetic developed by authors from diverse traditions, including Dewey's pragmatism, Carroll's cognitivism, and Saito's everyday aesthetics. We focus on the activity of reading, which has traditionally been conceived as involving the establishment of letter-sound correspondences and the rule-based deduction of information. However, an embodied framework opens up a more ecological understanding of this activity encompassing dynamic, multimodal perceptual engagement which is dependent on: (i) who the reader is (ii) the task or purpose, and (iii) what the person-environment-system affords. This form of engagement, even in mundane everyday-reading, we argue, brings forth an aesthetic dimension to it. Specifically, we explore how bodily engagement such as olfactory, tactile, and prosodic processes, saturate even logical judgements and reasoning. This integration of embodied and aesthetic processes in a particular context, we claim, can effectively emphasise and cultivate an aesthetic attitude. This, in turn, will provide insight into how the aesthetic dimension of reading can be cultivated intelligently, enriching the overall experience and will also illuminate why we read at all. [ABSTRACT FROM AUTHOR]

The role of artificial intelligence (AI) in the education sector has received considerable attention from scholars; however, its potency and application among tourism learners are yet to be discerned. Accordingly, this research note articulates the potential impact and limitations of the AI chatbot, ChatGPT, in tourism education practices. In particular, the paper aims to raise awareness among tourism educators regarding the disruptive potential of ChatGPT and its impact on academic integrity and ethics. This paper contributes to tourism education practices on AI and robotics by critically discussing ChatGPT from a cognitive science perspective and providing recommendations on how to minimise AI plagiarism in tourism education. This research argues for adapting novel pedagogies as technology evolves and raises the need for AI ethical use guidelines in tourism education. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue including the development of cognitive models, the use of the models in cognitive simulation and the prediction of human cognitive process.

The Nibbānasukha-sutta contains Sāriputta's statement that the pleasure (sukha) of nibbāna lies in the fact that nothing is experienced (vedayita). This statement may be seen as complementary to the proclamation in the Kaḷāra-sutta that all that is experienced is unpleasant (dukkha). In this paper, I attempt to reconstruct the ideas serving as a philosophical backdrop to these radical and seemingly counterintuitive claims. I use a comparative and interdisciplinary approach, re-examining several key Nikāya passages, as well as drawing on modern cognitive science and philosophy of mind. I suggest that vedayita and the closely related concept of the five khandhas (and in particular viññāṇa) refer to various aspects of the type of consciousness whose content is phenomenal, introspectable, reportable and may be integrated into memory. I suggest that such consciousness is not a constant feature of our being engaged in the world and that its absence does not entail insentience or being incognizant. I hypothesize that a relatively low frequency of occurrences of such consciousness in the states known as absorption or flow contributes to their pleasurable nature and the altered sense of the passage of time and selfhood. I attempt to explain how the presence or absence of such consciousness is related to the states of dukkha or sukha, with particular focus on the role played by saṅkhāra. I also discuss the limits of introspection as a means of understanding what exactly makes experiences pleasurable or painful, and consider the possibility of non-introspectable forms of pleasure. In conclusion, I suggest that psychological transformation in early Buddhism is connected with a radical change of perspective, which involves no longer identifying with one's own consciousness. [ABSTRACT FROM AUTHOR]

We propose the "runtime learning" hypothesis which states that people quickly learn to perform unfamiliar tasks as the tasks arise by using task-relevant instances of concepts stored in memory during mental training. To make learning rapid, the hypothesis claims that only a few class instances are used, but these instances are especially valuable for training. The paper motivates the hypothesis by describing related ideas from the cognitive science and machine learning literatures. Using computer simulation, we show that deep neural networks (DNNs) can learn effectively from small, curated training sets, and that valuable training items tend to lie toward the centers of data item clusters in an abstract feature space. In a series of three behavioral experiments, we show that people can also learn effectively from small, curated training sets. Critically, we find that participant reaction times and fitted drift rates are best accounted for by the confidences of DNNs trained on small datasets of highly valuable items. We conclude that the runtime learning hypothesis is a novel conjecture about the relationship between learning and memory with the potential for explaining a wide variety of cognitive phenomena. Author summary: Human cognition is remarkably flexible, with the ability to reliably perform a wide variety of tasks, including idiosyncratic and unfamiliar ones, in a wide variety of contexts. However, despite impressive advances in machine learning, leading to artificial intelligences capable of outperforming humans on select individual tasks, this flexibility has yet to be replicated by computational models. Doing so is essential to both creating general artificial intelligence and to achieving a deeper understanding of the human brain and mind. To account for this vital property of human cognition, we introduce the "runtime learning hypothesis", in which the brain rapidly constructs task-specific models in response to the needs of the moment using an internal training process based on valuable exemplars of the relevant concepts. We examine the plausibility of this hypothesis using human behavioral experiments and machine-learning-based computational modeling. The results are consistent with the human brain using runtime learning to flexibly perform tasks. [ABSTRACT FROM AUTHOR]

Vision and Language Navigation (VLN) is a task in which an agent needs to understand natural language instructions to reach the target location in a real-scene environment. To improve the model ability of long-horizon planning, emerging research focuses on extending the models with different types of memory structures, mainly including topological maps or a hidden state vector. However, the fixed-length hidden state vector is often insufficient to capture long-term temporal context. In comparison, topological maps have been shown to be beneficial for many robotic navigation tasks. Therefore, we focus on building a feasible and effective topological map representation and using it to improve the navigation performance and the generalization across seen and unseen environments. This paper presents a S elf-organizing Memory based on Adaptive Resonance Theory (SMART) module for incremental topological mapping and a framework for utilizing the SMART module to guide navigation. Based on fusion adaptive resonance theory networks, the SMART module can extract salient scenes from historical observations and build a topological map of the environmental layout. It provides a compact spatial representation and supports the discovery of novel shortcuts through inferences while being explainable in terms of cognitive science. Furthermore, given a language instruction and on top of the topological map, we propose a vision–language alignment framework for navigational decision-making. Notably, the framework utilizes three off-the-shelf pre-trained models to perform landmark extraction, node–landmark matching, and low-level controlling, without any fine-tuning on human-annotated datasets. We validate our approach using the Habitat simulator on VLN-CE tasks, which provides a photo-realistic environment for the embodied agent in continuous action space. The experimental results demonstrate that our approach achieves comparable performance to the supervised baseline. [ABSTRACT FROM AUTHOR]

Resilience is a basic trait of cognitive systems and fundamentally connected to their autopoietic organization. It plays a vital role in maintaining the identity of cognitive systems in the face of external threats and perturbances. However, when examining resilience in the context of autopoiesis, an overlooked issue arises: the autopoietic theory formulated by Maturana and Varela (1980) renders traditional Shannon information obsolete, highlighting that information should not be ascribed a role in cognitive systems in a general sense. This paper examines the current situation and suggests a possible way forward by exploring an affordance-based view on information, derived from radical cognitive science, which is exempted from Maturana and Varela's critique. Specifically, it argues that the impact of social influence on affordance use is crucial when considering how resilience can manifest in informational relations pertaining to the human cognitive ecology. [ABSTRACT FROM AUTHOR]

Over the past few decades, cognitive science has identified several forms of reasoning that make essential use of conceptual knowledge. Despite significant theoretical and empirical progress, there is still no unified framework for understanding how concepts are used in reasoning. This paper argues that the theory of conceptual spaces is capable of filling this gap. Our strategy is to demonstrate how various inference mechanisms which clearly rely on conceptual information—including similarity, typicality, and diagnosticity-based reasoning—can be modeled using principles derived from conceptual spaces. Our first topic analyzes the role of expectations in inductive reasoning and their relation to the structure of our concepts. We examine the relationship between using generic expressions in natural language and common-sense reasoning as a second topic. We propose that the strength of a generic can be described by distances between properties and prototypes in conceptual spaces. Our third topic is category-based induction. We demonstrate that the theory of conceptual spaces can serve as a comprehensive model for this type of reasoning. The final topic is analogy. We review some proposals in this area, present a taxonomy of analogical relations, and show how to model them in terms of distances in conceptual spaces. We also briefly discuss the implications of the model for reasoning with concepts in artificial systems. [ABSTRACT FROM AUTHOR]

The search for the engram—the neural mechanism of memory—has been a guiding research project for neuroscience since its emergence as a distinct scientific field. Recent developments in the tools and techniques available for investigating the mechanisms of memory have allowed researchers to proclaimed the search is over. While there is ongoing debate about the justification for that claim, renewed interest in the engram is clear. This attention highlights the impoverished status of the engram concept. As research accelerates, the simple characterization of the engram as an enduring physical change is stretched thin. Now that the engram commitment has been made more explicit, it must also be made more precise. If the project of 20th century neurobiology was finding the engram, the project of the 21st must be supplying a richer account of what's been found. This paper sketches a history of the engram, and a way forward. This article is categorized under: Philosophy > Foundations of Cognitive Science [ABSTRACT FROM AUTHOR]

Causal inference is a key step in many research endeavors in cognitive science and neuroscience, and particularly cognitive neuroscience. Statistical knowledge is sufficient for prediction and diagnosis, but causal knowledge is required for action and intervention. Most statistics courses and textbooks emphasize the difficulty of causal inference, focusing on the maxim that "correlation does not mean causation": there can be multiple causal possibilities, often many of them, consistent with given observed statistics. This paper focuses instead on the conceptual issues and assumptions that confront causal and other kinds of inference, primarily focusing on cognitive neuroscience. We connect inference methods with goals and challenges, and provide concrete guidance about how to select appropriate tools for the scientific task. This article is categorized under: Psychology > Theory and MethodsPhilosophy > Foundations of Cognitive Science [ABSTRACT FROM AUTHOR]