Classical Cognitive Science Research Articles

What Are We Talking About When We Talk About Cognition? Human, Cybernetic, and Phylogenetic Conceptual Schemes

In this paper I will outline three conceptual schemes for thinking about cognition. One is the anthropocentric scheme that dominated our thinking for thousands of years: human cognition. Another is the approach founded in classical cognitive science and artificial intelligence: cybernetic cognition. The third is the framework of evolutionary biology that encompasses all traits of evolved organisms: phylogenetic cognition. I will explain all three and sketch their current relationships. Each scheme forms the conceptual ground of a valid research programme, but how these programmes and schemes will end up in relation to each other is an open question.

Knowing Groundlessness: An Enactive Approach to a Shift From Cognition to Non-Dual Awareness.

The enactive approach has become an influential paradigm in cognitive science. One of its most important claims is that cognition is sense-making: to cognize is to enact a world of meaning. Thus, a world is not pregiven but enacted through sense-making. Most importantly, sense-making is not a fixed process or thing. It does not have substantial existence. Instead, it is groundless: it springs from a dynamic of relations, without substantial ground. Thereby, as all cognition is groundless, this groundlessness is considered the central underlying principle of cognition. This article takes that key concept of the enactive approach and argues that it is not only a theoretical statement. Rather, groundlessness is directly accessible in lived experience. The two guiding questions of this article concern that lived experience of groundlessness: (1) What is it to know groundlessness? (2) How can one know groundlessness? Accordingly, it elaborates (1) how this knowing of groundlessness fits into the theoretical framework of the enactive approach. Also, it describes (2) how it can be directly experienced when certain requirements are met. In an additional reflexive analysis, the context-dependency and observer-relativity of those statements themselves is highlighted. Through those steps, this article exhibits the importance of knowing groundlessness for a cognitive science discourse: this underlying groundlessness is not only the “ground” of cognition, but it also can be investigated empirically through lived experience. However, it requires a methodology that is radically different from classical cognitive science. This article ends with envisioning a future praxis of cognitive science which enables researchers to investigate not only theoretically but empirically the “foundationless foundation” of cognition: groundlessness.

The Development of Cognitive Science and Philosophy of Information—From Anthropocentrism to Naturalism

The emergence of Floridi’s philosophy of information has been directly pushed by the emergence of classical cognitive science and it attempts to provide us with a computational and representational epistemology and ontology. They share some common points: 1. anthropocentrism on cognition; 2. Cartesianism on knowledge; 3. nativism on semantics; 4. methodology on computationalism–representationalism. However, the development of cognitive science is deviating from Floridi’s philosophy of information, as the core concept of representation has been gradually abandoned in more and more cognitive studies, corresponding to the movement of situated, embodied, embedded and dynamic study in cognitive science. Thus, a new philosophy of information should emerge to accommodate the new development in cognitive science. Moreover, Wu’s PI satisfies the demand of this trend, which I will defend in this article.

Computational Knowledge Representation in Cognitive Science

Cognitive research can contribute to the formal epistemological study of knowledge representation inasmuch as, firstly, it may be regarded as a descriptive science of the very same subject as that, of which formal epistemology is a normative one. And, secondly, the notion of representation plays a constitutive role in both disciplines, though differing therein in shades of its meaning. Representation, in my view, makes sense only being paired with computation. A process may be viewed as computational if it adheres to some algorithm and is substrate-independent. Traditionally, psychology is not directly determined by neuroscience, sticking to functional or dynamical analyses in the what-level and skipping mechanistic explanations in the how-level. Therefore, any version of computational approach in psychology is a very promising move in connecting the two scientific realms. On the other hand, the digital and linear computational approach of the classical cognitive science is of little help in this way, as it is not biologically realistic. Thus, what is needed there on the methodological level, is a shift from classical Turing-style computationalism to a generic computational theory that would comprehend the complicated architecture of neuronal computations. To this end, the cutting-edge cognitive neuroscience is in need of а satisfactory mathematical theory applicable to natural, particularly neuronal, computations. Computational systems may be construed as natural or artificial devices that use some physical processes on their lower levels as atomic operations for algorithmic processes on their higher levels. A cognitive system is a multi-level mechanism, in which linguistic, visual and other processors are built on numerous levels of more elementary operations, which ultimately boil down to atomic neural spikes. The hypothesis defended in this paper is that knowledge derives not only from an individual computational device, such as a brain, but also from the social communication system that, in its turn, may be presented as a kind of supercomputer of the parallel network architecture. Therefore, a plausible account of knowledge production and exchange must base on some mathematical theory of social computations, along with that of natural, particularly neuronal, ones.

Contribuciones desde la experiencia musical al debate sobre la naturaleza de la mente

Se presentan aportes al debate sobre la naturaleza abstracta o corporeizada de la mente. En particular se presenta el problema desde el punto de vista epistemológico, en torno a la determinación de la unidad de cómputo. Se muestra cómo la ciencia cognitiva clásica de la música exhibe un sesgo etnocéntrico en la selección de tal unidad al partir de la experiencia del sujeto eurocentrado. A tal fin se discuten aspectos de la relevancia de la unidad seleccionada en cuanto a su escala y perspectiva. Mediante ejemplos del campo de la psicología de la perfomance musical se argumenta que los enfoques corporeizados tienen más chances de evitar esos sesgos pues resuelven mejor el problema de la situacionalidad de los procesos cognitivos. Se concluye que la atención a la situacionalidad de los procesos cognitivos favorece la pluralidad epistémica en psicología de la música y por ende constituye un resguardo de justicia cognitiva.

Autopsy of an airplane crash: a transactional approach to forensic cognitive science

In considerations of cognition in complex, technologically enhanced work environments, the question often concerns the boundaries of the phenomena to be researched. In classical cognitive science, the boundary of cognition is the brain case. More recent approaches, including distributed cognition and joint cognitive systems, draw the boundaries so that human operators and aspects of their environment are included; and the foci of the inquiries are interactions and representations that are passed around between players. This study makes a case for a transactional approach, which acknowledges a unity/identity of agent and environment. To understand the effect of agent characteristics in performance requires knowing the environment characteristics; and to understand the effect of the environment characteristics on performance requires knowing the agent characteristics. The approach is exemplified in the analysis of key instants of the spectacular and widely publicized crash of TransAsia Flight GE235 in which 43 lives were lost. The transactional analysis exhibits the internal cognitive dynamic in the cockpit that actually explains why agents acted as they did (rather than what they did not do because situation awareness lacked). It is better suited as a foundation of forensic cognitive science than the classical view on human error.

The paradox of the universal triangle: Concepts, language, and prototypes.

For over 300 years, the humble triangle has served as the paradigmatic example of the problem of abstraction. How can we have the idea of a general triangle even though every experience with triangles is with specific ones? Classical cognitive science seemed to provide an answer in symbolic representation. With its easily enumerated necessary and sufficient conditions, the triangle would appear to be an ideal candidate for being represented in a symbolic form. I show that it is not. Across a variety of tasks-drawing, speeded recognition, unspeeded visual judgments, and inference-representations of triangles appear to be graded and context dependent. I show that using the category name "triangle" activates a more prototypical representation than using an arguably coextensive cue, "three-sided polygon". For example, when asked to draw "triangles" people draw more typical triangles than when asked to draw "three-sided polygons". Altogether, the results support the view that (even formal) concepts have a graded and flexible structure, which takes on a more prototypical and stable form when activated by category labels.

The Demise of the Synapse As the Locus of Memory: A Looming Paradigm Shift?

Synaptic plasticity is widely considered to be the neurobiological basis of learning and memory by neuroscientists and researchers in adjacent fields, though diverging opinions are increasingly being recognized. From the perspective of what we might call “classical cognitive science” it has always been understood that the mind/brain is to be considered a computational-representational system. Proponents of the information-processing approach to cognitive science have long been critical of connectionist or network approaches to (neuro-)cognitive architecture, pointing to the shortcomings of the associative psychology that underlies Hebbian learning as well as to the fact that synapses are practically unfit to implement symbols. Recent work on memory has been adding fuel to the fire and current findings in neuroscience now provide first tentative neurobiological evidence for the cognitive scientists' doubts about the synapse as the (sole) locus of memory in the brain. This paper briefly considers the history and appeal of synaptic plasticity as a memory mechanism, followed by a summary of the cognitive scientists' objections regarding these assertions. Next, a variety of tentative neuroscientific evidence that appears to substantiate questioning the idea of the synapse as the locus of memory is presented. On this basis, a novel way of thinking about the role of synaptic plasticity in learning and memory is proposed.

Theoretical Analysis of the Meaning of Embodiment

The topic of embodiment has received a great deal of attention and aroused much enthusiasm within cognitive science in general and psychology in particular. The connotation of embodiment refers essentially to the dependency of cognition on agent's own body. The classical cognitive science committed to the view of disembodied mind. That is, cognition involves algorithmic processes upon symbolic representations. These theories posit no role for body in cognitive processes. They claimed that Mental processes such as perception, memory and thinking et al are independent of bodily structure and functioning. The view of "weak embodiment"argues against disembodiment, and claims that the body should be understood as playing a role in implementing the function of computation and representation that underpins our cognitive capacities. In contrast, the view of "strong embodiment"entirely eschews the computational theory of cognition. It assigns embodiment a degree of significance in the shaping of the character of cognition. From the point of view of strong embodiment, cognitive processes are profoundly reflect the body's interactions with the world. In contemporary embodied cognitive science, there is a radically different stance that also has roots in diverse branches of cognitive science. It resulted in a great deal of diversity in how to understand the meaning of embodiment. We distinguished the following four views:(i) embodiment is understood as a kind of somatic learning. From this point of view, embodiment and somatic learning are used interchangeably. Both are associated with a kind of bodily experiences from body's interaction with outside world.(ii) embodiment involves lived experiences coming from a body with a special neurophysiological structure, which means embodiment is a kind of experience from which cognition is made. Different body intends to make different experience, and different experience make, in turn, different cognition.(iii) embodiment is a way of knowing. We need a brain and a body to make sense of the world around us, and to understand the meaning of "chair"or "cat", then significant differences in forms of embodiment will translate into distinct conceptual metaphors and image schemas which structure our systems of everyday thought.(iv) embodiment means that cognitive processes can not located in a brain alone. The boundary between a cognitive agent and his or her environment should be broken down. Cognition is hybrid processes, it straddle both internal and external operations. In author's opinion, cognition's embodiment means that:(i) cognizing agent's body is a constituent of cognitive processes, and bodily structure and functioning are imprinted on mental processes, which influence our mental processes such as thinking, categorization, attitude, learning and emotion et al.(ii) perception is not the internal reconstruction of the external world. Perception of the environment is the result of the agent's bodily actions. This kind of actions shape the perception of the agent.(iii) body is the source of meaning. It is the body that makes us into a meaningful world. Therefore, abstract meaning is based on bodily sensor-motor systems.(iv) different bodies intend to dictate different thought. If people use their physical perceptions and bodily experiences to construct cognitive processes, then the differences from our interactions with the environment should in fact make people along different way of thinking. Viewed all together, embodiment is about the consequences on cognition of existing as a human body. We are not "having a body", we are "existing as a body". The answers to the meaning of embodiment will have considerable theoretical and practical significance for the community of psychology.

Communication as Navigation: A New Role for Consciousness in Language

Classical cognitive science has been characterized by an association with the computational theory of mind. Although this association has produced highly significant results, it has also limited the scope of scientific psychology. In this paper, we analyse the limits of the specific kind of computational model represented by the Chomskian-Fodorian tradition in the study of mind and language. In our opinion, the adhesion to the principle of formality imposed by this specific computational model has motivated the exclusion of consciousness in the reflection on language and, consequently, has led to the inability to account for some aspects of language functioning at the processing level of discourse. The aim of this article is to restore the role of consciousness in discourse comprehension and production processes. Specifically, we argue that the ability to produce and understand discourses is based on individuals’ capacity for navigation in space and time. We will show that the space–time orientation is guaranteed by the projection of the self, which involves a special kind of consciousness.

Non-representationalist cognitive science and realism

Embodied and extended cognition is a relatively new paradigm within cognitive science that challenges the basic tenet of classical cognitive science, viz. cognition consists in building and manipulating internal representations. Some of the pioneers of embodied cognitive science have claimed that this new way of conceptualizing cognition puts pressure on epistemological and ontological realism. In this paper I will argue that such anti-realist conclusions do not follow from the basic assumptions of radical embodied cognitive science. Furthermore I will show that one can develop a form of realism that reflects rather than just accommodates the core principles of non-representationalist embodied cognitive science.

The Original Sin of Cognitive Science

Classical cognitive science was launched on the premise that the architecture of human cognition is uniform and universal across the species. This premise is biologically impossible and is being actively undermined by, for example, imaging genomics. Anthropology (including archaeology, biological anthropology, linguistics, and cultural anthropology) is, in contrast, largely concerned with the diversification of human culture, language, and biology across time and space-it belongs fundamentally to the evolutionary sciences. The new cognitive sciences that will emerge from the interactions with the biological sciences will focus on variation and diversity, opening the door for rapprochement with anthropology.

Language as a Cognitive Tool

The standard view of classical cognitive science stated that cognition consists in the manipulation of language-like structures according to formal rules. Since cognition is ‘linguistic’ in itself, according to this view language is just a complex communication system and does not influence cognitive processes in any substantial way. This view has been criticized from several perspectives and a new framework (Embodied Cognition) has emerged that considers cognitive processes as non-symbolic and heavily dependent on the dynamical interactions between the cognitive system and its environment. But notwithstanding the successes of the embodied cognitive science in explaining low-level cognitive behaviors, it is still not clear whether and how it can scale up for explaining high-level cognition. In this paper we argue that this can be done by considering the role of language as a cognitive tool: i.e. how language transforms basic cognitive functions in the high-level functions that are characteristic of human cognition. In order to do that, we review some computational models that substantiate this view with respect to categorization and memory. Since these models are based on a very rudimentary form of non-syntactic ‘language’ we argue that the use of language as a cognitive tool might have been an early discovery in hominid evolution, and might have played a substantial role in the evolution of language itself.

Where is Cognitive Science Heading?

According to Ramsey (Representation reconsidered, Cambridge University Press, New York, 2007), only classical cognitive science, with the related notions of input---output and structural representations, meets the job description challenge (the challenge to show that a certain structure or process serves a representational role at the subpersonal level). By contrast, connectionism and other nonclassical models, insofar as they exploit receptor and tacit notions of representation, are not genuinely representational. As a result, Ramsey submits, cognitive science is taking a U-turn from representationalism back to behaviourism, thus presupposing that (1) the emergence of cognitivism capitalized on the concept of representation, and that (2) the materialization of nonclassical cognitive science involves a return to some form of pre-cognitivist behaviourism. We argue against both (1) and (2), by questioning Ramsey's divide between classical and representational, versus nonclassical and nonrepresentational, cognitive models. For, firstly, connectionist and other nonclassical accounts have the resources to exploit the notion of a structural isomorphism, like classical accounts (the beefing-up strategy); and, secondly, insofar as input---output and structural representations refer to a cognitive agent, classical explanations fail to meet the job description challenge (the deflationary strategy). Both strategies work independently of each other: if the deflationary strategy succeeds, contra (1), cognitivism has failed to capitalize on the relevant concept of representation; if the beefing-up strategy is sound, contra (2), the return to a pre-cognitivist era cancels out.

Neuroscience in Context: The New Flagship of the Cognitive Sciences

Cognitive neuroscience has come to be viewed as the flagship of the cognitive sciences and is transforming our understanding of the nature of mind. In this paper we survey several research fields in cognitive neuroscience (lateralization, neuroeconomics, and cognitive control) and note that they are making rapid progress on fundamental issues. Lateralization research is developing a comparative framework for evolutionary analysis, and is identifying individual- and population-level factors that favor brain asymmetries. Neuroeconomics is creating a research framework for studying valuation mechanisms in the brain that allows investigation of more complex phenomena than traditional reward paradigms. And cognitive control research has cast light on the mechanisms of task learning and top-down control that enable fluid goal-directed behavior in complex situations. Reasons for the success of cognitive neuroscience are varied: technical advances (e.g., in molecular genetics and imaging) are part of the story, but the more important factors have to do with the power of integrating a bottom-up mechanistic approach with larger functional and evolutionary perspectives. The incorporation of a bottom-up component differentiates cognitive neuroscience from the multidisciplinary ambitions of classical cognitive science, which suffered from having limited access to mechanisms.

Blending out of the background: Play, props and staging in the material world

The focus in blending theory on the dynamics of meaning construction makes it a productive tool for analysing psychological processes in a developmental perspective. However, blending theory has largely preserved the traditionally mentalist and individualist assumptions of classical cognitive science. This article argues for an extension of the range of both theory and data, to encompass the socially collaborative, culturally and materially grounded nature of the human mind. An approach to young children's symbolic play in terms of conceptual blending is presented, together with an analysis of an episode of sociodramatic play which highlights the role of cultural material objects as crucial meaning-bearing elements in the blend. From a developmental perspective, conceptual blending can be viewed as a microgenetic process, in which not only cognitive strategies, but social roles, relationships and identities are negotiated by participants in social and communicative interactions.

Modularity reconsidered

An orthodoxy in classical cognitive science is that representation is symbolic and that functional architecture is modular. That modular theory is the cornerstone of Cognitive Neuropsychology (CN), which identifies functionally discrete neurocomputational entities by observing psychological disorder. While the symbolic theory of representation is optional for CN, the modular hypothesis is essential to it and depends on a distinction between modular and central processing. Jerry Fodor has refined that distinction with the concept of Informational Encapsulation. This paper defends the encapsulation hypothesis against arguments that the interaction between modules and central systems requires its abandonment.

A Defense of Cartesian Materialism

One of the principal tasks Dennett sets himself in Consciousness Explained is to demolish the Cartesian theatre model of phenomenal consciousness, which in its contemporary garb takes the form of Cartesian materialism: the idea that conscious experience is a process of presentation realized in the physical materials of the brain. The now standard response to Dennett is that, in focusing on Cartesian materialism, he attacks an impossibly naive account of consciousness held by no one currently working in cognitive science or the philosophy of mind. Our response is quite different. We believe that, once properly formulated, Cartesian materialism is no straw man. Rather, it is an attractive hypothesis about the relationship between the computational architecture of the brain and phenomenal consciousness, and hence one that is worthy of further exploration. Consequently, our primary aim in this paper is to defend Cartesian materialism from Dennett's assault. We do this by showing that Dennett's argument against this position is founded on an implicit assumption (about the relationship between phenomenal experience and information coding in the brain), which while valid in the context of classical cognitive science, is not forced on connectionism.

Connectionism, Systematicity, and the Frame Problem

This paper investigates connectionism‘s potential to solve the frame problem. The frame problem arises in the context of modelling the human ability to see the relevant consequences of events in a situation. It has been claimed to be unsolvable for classical cognitive science, but easily manageable for connectionism. We will focus on a representational approach to the frame problem which advocates the use of intrinsic representations. We argue that although connectionism‘s distributed representations may look promising from this perspective, doubts can be raised about the potential of distributed representations to allow large amounts of complexly structured information to be adequately encoded and processed. It is questionable whether connectionist models that are claimed to effectively represent structured information can be scaled up to a realistic extent. We conclude that the frame problem provides a difficulty to connectionism that is no less serious than the obstacle it constitutes for classical cognitive science.

A nonclassical framework for cognitive science

David Marr provided a useful framework for theorizing about cognition within classical, AI-style cognitive science, in terms of three levels of description: the levels of (i) cognitive function, (ii) algorithm and (iii) physical implementation. We generalize this framework: (i) cognitive state transitions, (ii) mathematical/functional design and (iii) physical implementation or realization. Specifying the middle, design level to be the theory of dynamical systems yields a nonclassical, alternative framework that suits (but is not committed to) connectionism. We consider how a brain's (or a network's) being a dynamical system might be the key both to its realizing various essential features of cognition — productivity, systematicity, structure-sensitive processing, syntax — and also to a non-classical solution of (frame-type) problems plaguing classical cognitive science.