The foundations of biology have been a topic of debate for the past few decades. The traditional perspective of the Modern Synthesis, which portrays organisms as passive entities with limited role in evolutionary theory, is giving way to a new paradigm where organisms are recognized as active agents, actively shaping their own phenotypic traits for adaptive purposes. Within this context, this article raises the question of whether contemporary biological theory is undergoing a cognitive revolution. This inquiry can be approached in (...) two ways: from a theoretical standpoint, exploring the centrality of the cognitive sciences in current theoretical biology; and from a historical perspective, examining the resemblance between the current state of theoretical biology and the Cognitive Revolution of the mid-20th century. Both inquiries yield affirmative answers, though important nuances will be emphasized. The cognitive sciences' explanatory framework is employed to elucidate the agentic characteristics of organisms, establishing a clear parallelism between the Cognitive Revolution and the present state of theoretical biology. (shrink)

The prominence of Bayesian modeling of cognition has increased recently largely because of mathematical advances in specifying and deriving predictions from complex probabilistic models. Much of this research aims to demonstrate that cognitive behavior can be explained from rational principles alone, without recourse to psychological or neurological processes and representations. We note commonalities between this rational approach and other movements in psychology – namely, Behaviorism and evolutionary psychology – that set aside mechanistic explanations or make use of optimality assumptions. Through (...) these comparisons, we identify a number of challenges that limit the rational program's potential contribution to psychological theory. Specifically, rational Bayesian models are significantly unconstrained, both because they are uninformed by a wide range of process-level data and because their assumptions about the environment are generally not grounded in empirical measurement. The psychological implications of most Bayesian models are also unclear. Bayesian inference itself is conceptually trivial, but strong assumptions are often embedded in the hypothesis sets and the approximation algorithms used to derive model predictions, without a clear delineation between psychological commitments and implementational details. Comparing multiple Bayesian models of the same task is rare, as is the realization that many Bayesian models recapitulate existing (mechanistic level) theories. Despite the expressive power of current Bayesian models, we argue they must be developed in conjunction with mechanistic considerations to offer substantive explanations of cognition. We lay out several means for such an integration, which take into account the representations on which Bayesian inference operates, as well as the algorithms and heuristics that carry it out. We argue this unification will better facilitate lasting contributions to psychological theory, avoiding the pitfalls that have plagued previous theoretical movements. (shrink)

The paper adopts an inter-theoretical socio-cultural and -material perspective on the relationship between human + machine learning to propose a new way to investigate the human + machine assistive assemblages emerging in professional work (e.g. medicine, architecture, design and engineering). Its starting point is Hutchins’s (1995a) concept of ‘distributed cognition’ and his argument that his concept of ‘cultural ecosystems’ constitutes a unit of analysis to investigate collective human + machine working and learning (Hutchins, Philos Psychol 27:39–49, 2013). It argues that: (...) (i) the former offers a way to reveal the cultural constitution of and enactment of human + machine cognition and, in the process, the limitations of the computational and connectionist assumptions about learning that underpin, respectively, good old-fashioned AI and deep learning; and (2) the latter offers a way to identify, when amplified with insights from Socio-Materialism and Cultural-Historical Activity Theory, how ML is further rearranging and reorganising the distributed basis of cognition in assistive assemblages. The paper concludes by outlining a set of conjectures researchers that could use to guide their investigations into the ongoing design and deployment of HL + ML assemblages and challenges associated with the interaction between HL + ML. (shrink)

This chapter describes the conceptual foundations of cognitive science during its establishment as a science in the 20th century. It is organized around the core ideas of individual agency as its basic explanans and information-processing as its basic explanandum. The latter consists of a package of ideas that provide a mathematico-engineering framework for the philosophical theory of materialism.

The information age can be dated to the work of Norbert Wiener and Claude Shannon in the 1940s. Their work on cybernetics and information theory, and many subsequent developments, had a profound influence on reshaping the field of psychology from what it was prior to the 1950s. Contemporaneously, advances also occurred in experimental design and inferential statistical testing stemming from the work of Ronald Fisher, Jerzy Neyman, and Egon Pearson. These interdisciplinary advances from outside of psychology provided the conceptual and (...) methodological tools for what is often called the cognitive revolution but is more accurately described as the information-processing revolution. Cybernetics set the stage with the idea that everything ranging from neurophysiological mechanisms to societal activities can be modeled as structured control systems with feedforward and feedback loops. Information theory offered a way to quantify entropy and information, and promoted theorizing in terms of information flow. Statistical theory provided means for making scientific inferences from the results of controlled experiments and for conceptualizing human decision making. With those three pillars, a cognitive psychology adapted to the information age evolved. The growth of technology in the information age has resulted in human lives being increasingly interweaved with the cyber environment, making cognitive psychology an essential part of interdisciplinary research on such interweaving. Continued engagement in interdisciplinary research at the forefront of technology development provides a chance for psychologists not only to refine their theories but also to play a major role in the advent of a new age of science. (shrink)

Cognitive ecology as a research tradition in cognitive science: The article presents cognitive ecology as a research tradition in cognitive science, under which studies on embodied cognition and various forms of situated cognition are conducted. At the same time, the basic heuristic of cognitive ecology and its relationship to methodological individualism are identified. The paper includes the history of the concept of “cognitive ecology”, historical approaches preceding this research tradition, as well as an outline of contemporary research related to it. (...) At the end of the article, the role of the ecological heuristic is summarized. (shrink)

Academic procrastination – habitually delaying work with academic tasks to the extent that the delays become detrimental to performance, wellbeing, and health – represents a substantial personal, systemic, and societal problem. Still, efforts to prevent and reduce it are surprisingly scarce and often offered as treatment regimens rather than preventive efforts. Based on the principles of functional analysis and a broad examination of factors that are important for academic procrastinatory behaviors, this paper aims to describe a strategy for analyzing individual (...) controlling conditions for procrastination and give parallel advice on how to change those controlling conditions. Both are ideographic, allowing for individual and dynamic analyses of factors responsible for instigating and maintaining procrastination, as well as tailor-made remedies that address controlling conditions in preventive and curative efforts to reduce procrastination. Although functional analysis integrates well with important research findings in the procrastination field, this approach suggests new criteria for identifying procrastinatory behaviors and an alternative model for analyzing their control conditions. We conclude that a functional approach may supplement procrastination research and efforts to prevent and alleviate this detrimental habit. (shrink)

Experiences of art involve exercise of ordinary cognitive and perceptual capacities but in unique ways. These two features of experiences of art imply the mutual importance of aesthetics and cognitive science. Cognitive science provides empirical and theoretical analysis of the relevant cognitive capacities. Aesthetics thus does well to incorporate cognitive scientific research. Aesthetics also offers philosophical analysis of the uniqueness of the experience of art. Thus, cognitive science does well to incorporate the explanations of aesthetics. This paper explores this general (...) framework of expansionism : a research strategy that suggests that the explanatory goals and resources of both aesthetics and cognitive science should expand to include those of the other. Two relations are considered. First, what is the relation between aesthetics and more traditional cognitive science? Second, what is the relation between aesthetics and new developments in cognitive science that de-emphasize mental representation and emphasize body and action? (shrink)

Radical views on cognition are generally defined by a cluster of features including non-representationalism and vehicle-externalism. In this paper, I concentrate on the way radical views on cognition define themselves as revolutionary theories in cognitive science. These theories often use the Kuhnian concepts of “paradigm” and “paradigm shift” for describing their ambitions and the current situation in cognitive science. I examine whether the use of Kuhn’s theory of science is appropriate here. There might be good reasons to think that cognitive (...) science is in a situation of foundational crisis, but that does not entail that the classical paradigm is currently displaced to the benefit of a new paradigm. Larry Laudan’s theory of research traditions is more enlightening than Kuhn’s theory for describing the scope and ambitions of radical views on cognition, and their relations with an anti-intellectualist tradition in philosophy. (shrink)

In contrast to the fruitful relationship between psychoanalysis/psychoanalysts and the humanities, institutionalized psychoanalysis has been largely resistant to the integration of psychoanalysis with other empirical branches of knowledge, as well as clinical ones [primarily cognitive-behavioral therapy ]. Drawing from two decades of theoretical and empirical work on psychopathology, psychotherapy, and psychoanalysis, the author aims to show how a reformulation of object relations theory using psychological science may enhance a clinical-psychoanalytic understanding and treatment of suicidal depression, which constitutes one of the (...) most formidable health challenges of our time. Specifically, he rewrote the notion of Melanie Klein positions—primarily the depressive position—using extant knowledge of structure of emotions, the centrality of mental representations of the future and the toxic nature of criticism-based emotions. This reformulation enables a dialog between clinical psychoanalysis and other therapeutic schools of thought and sheds light on the understanding and treatment of suicidal depression. (shrink)

Cognitive Science is a promising field of research that deals with one of the most fundamental questions ever: how do beings know? However, despite the long and extensive tradition of the field it has not yet become an area of knowledge with scientific identity. This is primarily due to three reasons: the lack of boundaries in defining the object of study, i.e. cognition, the lack of a precise, robust and consistent scientific methodology and results, and the inner problems derived from (...) its interdisciplinary nature. This paper presents a background review, a theoretical frame and a humble reflection on these topics in order to arouse the internal debate among readers once more. (shrink)

Despite the continuous emphasis on globalization, we witness increasing divisions and divisiveness in all domains of human activities. One of the reasons, if not the main one, is the intellectual fragmentation of humanity, compared in the title to the failed attempt at building the Biblical Tower of Babel. The attempts to reintegrate worldview, fragmented by the specialization of education and expected to be achieved through reforms in curricula at all levels of education, were based on the assumption that the design (...) of a curriculum should focus on the wide distribution of subjects of study, as if the distribution was the goal. The key point is not the distribution of themes, but the development of skills in the integration of knowledge. The quantitative assessment of the width of knowledge by the number of disciplines is of secondary importance. We cannot expect the miracle that students without any intellectual tools developed for this purpose would perform the job of integration, which their teachers do not promote or demonstrate, and which they cannot achieve for themselves. There are many other reasons for the increasing interest in making inquiries interdisciplinary, but there is little progress in the methodology of the integration of knowledge. This paper is a study of the transition from multidisciplinarity to interdisciplinarity, and further, to transdisciplinarity, with some suggestions regarding the use of methodological tools of structuralism and the choice of a conceptual framework. (shrink)

An intuitive view is that creativity involves bringing together what is already known and familiar in a way that produces something new. In cognitive science, this intuition is typically formalized in terms of computational processes that combine or associate internally represented information. From this computationalist perspective, it is hard to imagine how non-representational approaches in embodied cognitive science could shed light on creativity, especially when it comes to abstract conceptual reasoning of the kind scientists so often engage in. The present (...) article offers an entry point to addressing this challenge. The scientific project of embodied cognitive science is a continuation of work in the functionalist tradition in psychology developed over a century ago by William James and John Dewey, among others. The focus here is on how functionalist views on the nature of mind, thought, and experience offer an alternative starting point for cognitive science in general, and for the cognitive science of scientific creativity in particular. The result may seem paradoxical. On the one hand, the article claims that the functionalist conceptual framework motivates rejecting mainstream cognitive views of creativity as the combination or association of ideas. On the other hand, however, the strategy adopted here—namely, revisiting ideas from functionalist psychology to inform current scientific theorizing—can itself be described as a process of arriving at new, creative ideas from combinations of old ones. As is shown here, a proper understanding of cognition in light of the functionalist tradition resolves the seeming tension between these two claims. (shrink)

Fechner remains virtually unknown for his psychological research on the unconscious. However, he was one of the most prominent theorists of unconscious cognition of the 19th century, in the context of the rise of scientific investigations on the unconscious in German psychology. In line with the models previously developed by Leibniz and Herbart, Fechner proposes an explanative system of unconscious phenomena based on a modular conception of the mind and on the idea of a functional dissociation between representational and attentional (...) activity. For Fechner, the unconscious is a state of consciousness resulting from the isolation of representational activity from the rest of psychical life. Unconscious mental phenomena are unattended mental states that behave autonomously while remaining able to act on consciousness. This paper aims to revisit Fechner’s contribution to the history of the unconscious, but also the theoretical significance of the Fechnerian unconscious vis-à-vis current research on the cognitive unconscious. (shrink)

ABSTRACTThe seminal work of David Marr, popularized in his classic work Vision, continues to exert a major influence on both cognitive science and philosophy. The interpretation of his work also co...

Швидкий технологічний прогрес спричинив зрушення інтересів науковців з усього світу в бік когнітивної науки та інформатики, що, безперечно, вплинуло на формування нового типу мислення. Логіка, як наука про специфічний логічний тип людського мислення, не може залишитися осторонь. У статі проаналізовано методологічні засади когнітивістики та дуальність самої науки логіки, які відкривають перспективи їх співпраці. Для цього автор робить історико-методологічний розгляд обох дисциплін. Доводиться, що, з одного боку, формальна логіка багато вкладає в розвиток штучних формалізованих мов, які активно застосовуються для програмування Штучного (...) Інтелекту, а з іншого – неформальна логіка, як і когнітивістика, займається вивченням природньої мови, що дає їй можливість наблизитися до реального людського мислення. Показано, в який спосіб логіка, застосувавши для вивчення реального процесу мислення людей методологічну базу когнітивістики, може розширити межі своїх досліджень з теоретичного поля до практично-експериментального. (shrink)

A familiar story about mid-twentieth-century American psychology tells of the replacement of behaviorism by cognitive science. Between these two, however, lay a borderland, muddy and much trespassed-upon. This paper relocates the origins of the Chomskyan program in linguistics there. Following his introduction of transformational generative grammar, Chomsky mounted a highly publicized attack on behaviorist psychology. Yet when he first developed that approach to grammar, he was a defender of behaviorism. His anti-behaviorism emerged only in the course of what became a (...) systematic repudiation of the work of the Cornell linguist C. F. Hockett. In the name of the positivist Unity-of-Science movement, Hockett had synthesized an approach to grammar based on statistical communication theory; a behaviorist view of language acquisition in children as a process of association and analogy; and an interest in uncovering the Darwinian origins of language. In criticizing Hockett on grammar, Chomsky came to engage gradually and critically with the whole Hockettian synthesis. Situating Chomsky thus within his own disciplinary matrix suggests lessons for students of disciplinary politics generally and – famously with Chomsky – the place of political discipline within a scientific life. (shrink)

Following in a psychological and musicological tradition beginning with Leonard Meyer, and continuing through David Huron, we present a functional, cognitive account of the phenomenon of expectation in music, grounded in computational, probabilistic modeling. We summarize a range of evidence for this approach, from psychology, neuroscience, musicology, linguistics, and creativity studies, and argue that simulating expectation is an important part of understanding a broad range of human faculties, in music and beyond.

This paper discusses the resources for deconstruction offered by cognitive science, drawing inspiration from David Gunkel’s work on the topic (Deconstruction, MIT Press 2021). The gesture of deconstruction is seen as having a positive impact on the development of this interdisciplinary field by challenging misleading dichotomies and examining its underlying assumptions, such as the symmetry of integration.

As we rapidly approach the 50th year of the much‐celebrated ‘cognitive revolution’, it is worth reflecting on its widespread impact on individual disciplines and areas of multidisciplinary endeavour. Of specific concern in this paper is the example of the influence of cognitivism's equation of mind and computer in education. Within education, this paper focuses on a particular area of concern to which both mind and computer are simultaneously central: educational technology. It examines the profound and lasting effect of cognitive science (...) on our understandings of the educational potential of information and communication technologies, and further argues that recent and multiple ‘signs of discontent’, ‘crises’ and even ‘failures’ in cognitive science and psychology should result in changes in these understandings. It concludes by suggesting new directions that educational technology research might take in the light of this crisis of cognitivsm. (shrink)

A recent issue of Topics in Cognitive Science featured 11 thoughtful commentaries responding to our article “What happened to cognitive science?” (Núñez et al., 2019). Here, we identify several themes that arose in those commentaries and respond to each. Crucial to understanding our original article is the fundamental distinction between multidisciplinary and interdisciplinary endeavors: Cognitive science began (and has stayed) as multidisciplinary but has failed to move on to form a cohesive interdisciplinary field. We clarify and elaborate our original argument (...) and reiterate the importance of a data‐driven evaluation of the current status of the field, which exhibits a marked disciplinary imbalance, a lack of a coherent conceptual core, and a striking absence of a consistent curriculum in the institutions that grant degrees in this domain. Half a century after the creation of cognitive science, it may now be a good time to revisit goals and visions for how to best approach the ever‐fascinating scientific study of the mind(s). (shrink)

The question “What are cognitive processes?” can be understood variously as meaning “What is the nature of cognitive processes?”, “Can we distinguish epistemically cognitive processes from physical and biochemical processes on the one hand, and from mental or conscious processes on the other?”, and “Can we establish a fruitful notion of cognitive process?” The present aim is to deliver a positive answer to the last question by developing criteria for what would count as a paradigmatic exemplar of a cognitive process, (...) and then to offer the comparator mechanism as a convincing paradigmatic example. Thus, the paper argues, given the current state of science, we can indeed establish a fruitful scientific notion of a cognitive process. Nevertheless, it is left open whether the example-based characterization ends up as merely highlighting a fruitful convention within the early-twentyfirst century interdisciplinary investigation of intelligent behaviour in humans, animals, and robots, or whether the examples determine a natural kind or a property cluster. (shrink)

Linguistics as a science has rapidly changed during the course of a relatively short period. The mathematical foundations of the science, however, present a different story below the surface. In this paper, I argue that due to the former, the seismic shifts in theory over the past 80 years opens linguistics up to the problem of pessimistic meta-induction or radical theory change. I further argue that, due to the latter, one current solution to this problem in the philosophy of science, (...) namely structural realism :403–424, 1998; French in Proc Aristot Soc 106:167–185, 2006), should be viewed as especially enticing for linguists, as their field is a largely structural enterprise. I discuss particular historical instances of theory change in generative syntax before investigating two views on the nature of structural properties and eventually proposing an approach in terms of invariance :162–186, 2015) as a grounding for structural realism in the history and philosophy of linguistics. (shrink)

This article surveys the philosophical literature on theoretical linguistics. The focus of the paper is centred around the major debates in the philosophy of linguistics, past and present, with specific relation to how they connect to the philosophy of science. Specific issues such as scientific realism in linguistics, the scientific status of grammars, the methodological underpinnings of formal semantics, and the integration of linguistics into the larger cognitive sciences form the crux of the discussion.

In their recent book, Ladyman and Wiesner (What is a complex system?, Yale University Press, 2020) delineate the bounds of the exciting interdisciplinary field of complexity science. In this work, they provide examples of generally accepted complex systems and common features which these possess to varying degrees. In this paper, I plan to extend their list to include the formal study of natural language, i.e. linguistics. In fact, I will argue that language exhibits many of the hallmarks of a complex (...) system, specifically a complex biological system. Thus, my aim is to advocate contra the the ‘Minimalist Program’ (Chomsky, The minimalist program, MIT Press, Cambridge, 1995), which motivates simple underlying mechanisms (i.e. Merge) in their idealisations, that biolinguistics should embrace a ‘Maximalist Program’ in which multiple subfields contribute component explanations to an emerging whole. (shrink)

Choice architecture describes the environment in which choices are presented to decision-makers. In recent years, public and private actors have looked at choice architecture with great interest as they seek to influence human behaviour. These actors are typically called choice architects. Increasingly, however, this role of architecting choice is not performed by a human choice architect, but an algorithm or artificial intelligence, powered by a stream of Big Data and infused with an objective it has been programmed to maximise. We (...) call this entity the autonomous choice architect. In this paper, we present an account of why artificial intelligence can fulfil the role of a choice architect and why this creates problems of transparency, responsibility and accountability for nudges. We argue that choice architects, be them autonomous computational systems or human-beings, at a most basic level select, from a range of designs, the design which is most likely to maximise a pre-determined objective. We then proceed to argue that, given the growing demand for targeted, personalised choice architecture and for faster, dynamic reconfigurations of choice architecture, as well as the ever-expanding pool of data from which feedback can be drawn, the role of the human choice architect is increasingly obscured behind algorithmic, artificially intelligent systems. We provide a discussion of the implications of autonomous choice architects, focusing on the importance of the humans who programme these systems, ultimately arguing that despite technological advances, the responsibility of choice architecture and influence remains firmly one human beings must bear. (shrink)

The past decade has seen an explosion of work on the history of the human sciences during the Cold War. This work, however, does not engage with one of the leading human sciences of the period: linguistics. This article begins to rectify this knowledge gap by investigating the influence of linguistics and its concept of study, language, on American public, political and intellectual life during the postwar and early Cold War years. I show that language emerged in three frameworks in (...) this period: language as tool, language as weapon, and language as knowledge. As America stepped onto the international stage, language and linguistics were at the forefront: the military poured millions of dollars into machine translation, American diplomats were required to master scores of foreign languages, and schoolchildren were exposed to language-learning on a scale never before seen in the United States. Together, I argue, language and linguistics formed a critical part of the rise of American leadership in the new world order — one that provided communities as dispersed as the military, the diplomatic corps, scientists and language teachers with a powerful way of tackling the problems they faced. To date, linguistics has not been integrated into the broader framework of Cold War human sciences. In this article, I aim to bring both language, as concept, and linguistics, as discipline, into this framework. In doing so, I pave the way for future work on the history of linguistics as a human science. (shrink)

It has been just over 100 years since the birth of Alan Turing and more than 65 years since he published in Mind his seminal paper, Computing Machinery and Intelligence. In the Mind paper, Turing asked a number of questions, including whether computers could ever be said to have the power of “thinking”. Turing also set up a number of criteria—including his imitation game—under which a human could judge whether a computer could be said to be “intelligent”. Turing’s paper, as (...) well as his important mathematical and computational insights of the 1930s and 1940s led to his popular acclaim as the “Father of Artificial Intelligence”. In the years since his paper was published, however, no computational system has fully satisfied Turing’s challenge. In this paper we focus on a different question, ignored in, but inspired by Turing’s work: How might the Artificial Intelligence practitioner implement “intelligence” on a computational device? Over the past 60 years, although the AI community has not produced a general-purpose computational intelligence, it has constructed a large number of important artifacts, as well as taken several philosophical stances able to shed light on the nature and implementation of intelligence. This paper contends that the construction of any human artifact includes an implicit epistemic stance. In AI this stance is found in commitments to particular knowledge representations and search strategies that lead to a product’s successes as well as its limitations. Finally, we suggest that computational and human intelligence are two different natural kinds, in the philosophical sense, and elaborate on this point in the conclusion. (shrink)

Whether computational algorithms such as latent semantic analysis (LSA) can both extract meaning from language and advance theories of human cognition has become a topic of debate in cognitive science, whereby accounts of symbolic cognition and embodied cognition are often contrasted. Albeit for different reasons, in both accounts the importance of statistical regularities in linguistic surface structure tends to be underestimated. The current article gives an overview of the symbolic and embodied cognition accounts and shows how meaning induction attributed to (...) a specific statistical process or to activation of embodied representations should be attributed to language itself. Specifically, the performance of LSA can be attributed to the linguistic surface structure, more than special characteristics of the algorithm, and embodiment findings attributed to perceptual simulations can be explained by distributional linguistic information. (shrink)

LONI & Co: About the Epistemic Specificity of Digital Spaces of Knowledge in Cognitive Neuroscience. In the neurosciences digital databases more and more are becoming important tools of data rendering and distributing. This development is due to the growing impact of imaging based trial design in cognitive neuroscience, including morphological as much as functional imaging technologies. As the case of the ‘Laboratory of Neuro Imaging’ (LONI) is showing, databases are attributed a specific epistemological power: Since the 1990s databasing is seen (...) to foster the integration of neuroscientific data, although local regimes of data production, ‐manipulation and ‐interpretation are also challenging this development. Databasing in the neurosciences goes along with the introduction of new structures of integrating local data, hence establishing digital spaces of knowledge (epistemic spaces): At this stage, inherent norms of digital databases are affecting regimes of imaging‐based trial design, for example clinical research into Alzheimer's disease. (shrink)

Most research on transmission biases in cultural evolution has treated different biases as distinct strategies. Here I present a model that combines both frequency dependent bias (including conformist bias) and payoff bias in a single decision-making calculus and show that such an integrated learning strategy may be superior to relying on either bias alone. Natural selection may operate on humans’ relative dependence on frequency and payoff information, but both are likely to contribute to the spread of variants with high payoffs. (...) Importantly, the magnitude of conformist bias affects the evolutionary dynamics, and I show that an intermediate level of conformity may be most adaptive and may spontaneously evolve as it resists the invasion of low-payoff variants yet enables the fixation of high-payoff variants in the population. (shrink)

This paper proposes an account of neurocognitive activity without leveraging the notion of neural representation. Neural representation is a concept that results from assuming that the properties of the models used in computational cognitive neuroscience must literally exist the system being modelled. Computational models are important tools to test a theory about how the collected data has been generated. While the usefulness of computational models is unquestionable, it does not follow that neurocognitive activity should literally entail the properties construed in (...) the model. While this is an assumption present in computationalist accounts, it is not held across the board in neuroscience. In the last section, the paper offers a dynamical account of neurocognitive activity with Dynamical Causal Modelling that combines dynamical systems theory mathematical formalisms with the theoretical contextualisation provided by Embodied and Enactive Cognitive Science. (shrink)

The article presents an epistemological and partially methodological analysis of cognitive science as a scientific discipline, created as a result of the transformations that took place in the philosophical and psychological concepts of the mind and cognition, which were carried out with the aid of tools and methods of modelling as well as through simulating human cognitive processes and consciousness. In order to describe this interdisciplinary science, and its positions, as well as the stages and directions of its development, it (...) makes use of the epistemological model formulated by Michel Foucault, in which he draws attention to social, ideological and technological conditions of scientific knowledge. The opinions of the leading creators and critics of cognitive science, such as George A. Miller, Howard Gardner, Margaret Boden and José Luis Bermúdez are referenced to and analyzed with the use of this model. The article shows the epistemologically and methodologically divergent status of cognitive science, as well as its cognitive and institutional conditions and challenges, which stand before it after half a century of intensive development. (shrink)

In keeping with recent views of consciousness of self as represented in the body in action, empirical studies are reviewed that demonstrate a bottlenose dolphin’s conscious awareness of its own body and body parts, implying a representational “body image” system. Additional work reviewed demonstrates an advanced capability of dolphins for motor imitation of self-produced behaviors and of behaviors of others, including imitation of human actions, supporting hypotheses that dolphins have a sense of agency and ownership of their actions and may (...) implicitly attribute those levels of self-awareness to others. Possibly, a mirror-neuron system, or its functional equivalent to that described in monkeys and humans, may mediate both self-awareness and awareness of others. (shrink)

The cognition and information theoretic sciences have now been in existence for the better part of a century. In that time, their varied disciplines have undergone extensive maturation, honing their methods, constitutions, and evaluation techniques in the pursuit of academic rigor, while not losing sight of the practical influences that have served as their almost universal cornerstone. Meanwhile, this period has also been marked by increasing disparity and gradual distancing of the philosophical underpinnings upon which each field is founded, adding (...) strain to interdisciplinary collaborative efforts. This article presents an overview of select information-science-related cognition disciplines, and shows how the nascent Philosophy of Information can be adopted as a means of unifying these philosophical foundations in an empirically sound manner, without sacrificing general applicability. In addition, it demonstrates how PI is already rooted in the philosophies or epistemological views of several of the cognition disciplines, implicitly or otherwise. (shrink)

Among those living systems, which are cognizers? Among the behaviours of, and causes of behaviour in, living systems, which are cognitive? Such questions sit at the heart of a sophisticated, ongoing debate, of which the recent papers by Corcoran et al. ( 2020 ) and Sims and Kiverstein ( 2021 ) serve as excellent examples. I argue that despite their virtues, both papers suffer from flawed conceptions of the point of the debate. This leaves their proposals ill-motivated—good answers to the (...) wrong question. Additionally, their proposals are unfit to serve the legitimate roles for characterizations of cognition. (shrink)

Cognitive Science, Volume 46, Issue 9, September 2022.

Structure–activity relationship and quantitative SAR are modeling methods largely used in assessing biological properties of chemical substances. QSAR is based on the hypothesis that the chemical structure is responsible for the activity; it follows that similar molecules are expected to have similar properties. Similarity plays an important role in read across, which categorizes molecules primarily on the basis of similarity. Similarity, and chemical similarity too, is a property differently perceived by humans. The various proposed metrics often disagree with human judgment, (...) and no a unique metric for chemical similarity is universally adopted. Researchers argued that categorization is not only explained by similarity but depends as well on abstract knowledge and the task to accomplish. Moreover, similarity cannot be the unique explanation of a categorization, as different perceptual processes take place in category formation. Assuming that similarity judgments are deeply rooted in human knowledge and perception, cognitive sciences contributions are as important as the mathematical considerations of the classical theories. After an excursus in the many views of similarity in philosophy, mathematics, and cognitive science, the paper explores how connectionist systems, which loosely mimic the human cognitive system, could improve similarity-based choices. A case study on building SARs using connectionism and deep neural networks shows the role of similarity in building and explaining those models. A discussion about deep learning for QSAR and as a modeling tool for science concludes the presentation. (shrink)

Núñez et al (2019) argue (1) that the field of Cognitive Science has failed, in that it has not arrived at a cohesive theory, and (2) that this is contrary to the intentions of the founders. Their survey of publication and citation patterns bears out the lack of a cohesive theory and also provides corroboration for (3) the concern that the field is becoming unbalanced, with psychology overweighted (Gentner, 2010). I will argue against points (1) and (2), but agree with (...) point (3). My central claim is that cognitive science was never meant to have one unified theoretical framework, nor should it have. (shrink)