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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]

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]

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]

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]

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]

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]

Cognition is crucial to brain function, and accurately classifying cognitive load is essential for understanding the psychological processes across tasks. This paper innovatively combines functional near-infrared spectroscopy (fNIRS) with eye tracking technology to delve into the classification of cognitive load at the neurocognitive level. This integration overcomes the limitations of a single modality, addressing challenges such as feature selection, high dimensionality, and insufficient sample capacity. We employ fNIRS-eye tracking technology to collect neural activity and eye tracking data during various cognitive tasks, followed by preprocessing. Using the maximum relevance minimum redundancy algorithm, we extract the most relevant features and evaluate their impact on the classification task. We evaluate the classification performance by building models (naive Bayes, support vector machine, K-nearest neighbors, and random forest) and employing cross-validation. The results demonstrate the effectiveness of fNIRS-eye tracking, the maximum relevance minimum redundancy algorithm, and machine learning techniques in discriminating cognitive load levels. This study emphasizes the impact of the number of features on performance, highlighting the need for an optimal feature set to improve accuracy. These findings advance our understanding of neuroscientific features related to cognitive load, propelling neural psychology research to deeper levels and holding significant implications for future cognitive science.Graphical Abstract: Cognition is crucial to brain function, and accurately classifying cognitive load is essential for understanding the psychological processes across tasks. This paper innovatively combines functional near-infrared spectroscopy (fNIRS) with eye tracking technology to delve into the classification of cognitive load at the neurocognitive level. This integration overcomes the limitations of a single modality, addressing challenges such as feature selection, high dimensionality, and insufficient sample capacity. We employ fNIRS-eye tracking technology to collect neural activity and eye tracking data during various cognitive tasks, followed by preprocessing. Using the maximum relevance minimum redundancy algorithm, we extract the most relevant features and evaluate their impact on the classification task. We evaluate the classification performance by building models (naive Bayes, support vector machine, K-nearest neighbors, and random forest) and employing cross-validation. The results demonstrate the effectiveness of fNIRS-eye tracking, the maximum relevance minimum redundancy algorithm, and machine learning techniques in discriminating cognitive load levels. This study emphasizes the impact of the number of features on performance, highlighting the need for an optimal feature set to improve accuracy. These findings advance our understanding of neuroscientific features related to cognitive load, propelling neural psychology research to deeper levels and holding significant implications for future cognitive science. [ABSTRACT FROM AUTHOR]

The article introduces the latest issue of Topics in Cognitive Science, which is dedicated to excellent and award-winning research. The first topic focuses on the Fellows of the Cognitive Science Society, featuring articles by various researchers. Barbara Malt from Lehigh University has joined this exclusive group and provides an overview of her research on the relationship between language, thought, and representation. The second topic includes revised papers from the Annual Meeting of the Cognitive Science Society, and the final topic showcases the best papers from the International Conference on Cognitive Modeling. The article encourages letters, commentaries, and proposals for new topics. [Extracted from the article]

The terms "extended cognition" and the "extended mind" identify two strands of philosophical argument that are commonly subsumed under the general heading of active externalism. The present paper describes an integrated approach to understanding extended cognition and the extended mind—one that papers over the differences between these two, ostensibly distinct, forms of cognitive extension. As an added bonus, the paper describes how active externalism might be applied to the realm of non-cognitive phenomena, thereby yielding an expansion in the theoretical and empirical scope of the active externalist enterprise. Both these points of progress stem from what is called the dispositional hypothesis. According to the dispositional hypothesis, extended cognition occurs when the mechanisms responsible for the manifestation of dispositional properties include components that lie beyond the borders of the thing to which the dispositional properties are ascribed. • A clearer explication of active externalist theses is required. • According to the dispositional hypothesis, cognitive extension occurs when the mechanisms responsible for the manifestation of dispositional properties extend beyond the borders of the entity to which dispositional properties are ascribed. • A consideration of dispositional properties provides the basis for a unified approach to understanding extended cognition and the extended mind. • Active externalism can be applied to phenomena that do not fall within the empirical orbit of cognitive science. [ABSTRACT FROM AUTHOR]

The article discusses the evolving perspective in cognitive science towards understanding how individual cognition is connected to collective efforts and cultural evolution. The editors of the journal issue, Steven A. Sloman and Nathaniel Rabb, have compiled a collection of papers that explore how cognitive processes and functions, such as memory and problem-solving, are influenced by and shape group coordination. The article emphasizes the importance of cumulative culture and language in human uniqueness and highlights the shift in cognitive science towards studying the organization and distribution of knowledge. The introduction to the journal issue is described as thrilling, captivating, and thought-provoking. [Extracted from the article]

This paper examines the interplay between integrative explanatory pluralism and the quest for unified theories. We argue that when grounded in virtues associated with satisfactory explanations, integrative pluralism exhibits an inherent instability stemming from the conflict between the demand for unity and the commitment to preserving a patchwork of disparate partial explanations. A case study in cognitive science illuminates the challenges of maintaining both systematicity and depth in explanations within this framework. While this instability does not render integrative pluralism fundamentally flawed, it stresses the importance of a diachronic analysis of scientific dynamics and norms. The conclusion highlights the continued value of integrative pluralism in interdisciplinary research programs, while emphasizing its role as a temporary rather than permanent approach. [ABSTRACT FROM AUTHOR]

We offer a framework for the design and use of Ambient Smart Environments (ASEs) for preventive mental health care support. Drawing from Complex Systems Theory (CST) and 'E' Cognitive Science (ECS), we claim that ASEs have the potential to act in a preventive capacity in support of good mental health, i.e. supporting dynamics that avoid so-called "struck states" (which are, according to CST, thought generally to underpin forms of psychopathology). Here, we frame our discussion with what has recently been termed the "mind-technology problem". We define and characterise ASE systems, present some examples, and briefly survey some existing theoretical work. After introducing the essential CST terminology, the paper goes on to apply CST to explain developmental adaptation to continuously changing (smart) environments. Understanding the ASE's navigation in terms of a dynamic geometry between attracting and repelling points (or local minima/local maxima), allows us to develop neurotechnology that can augment clinical interventions by predicting upcoming shifts for good symptomatic outcomes, i.e. when a preventive intervention (i.e. destabilisation) should take place. We further offer clear directions for the development and design of such neurotechnology. [ABSTRACT FROM AUTHOR]