If imagination is subject to the will, in the sense that people choose the content of their own imaginings, how is it that one nevertheless can learn from what one imagines? This chapter argues for a way forward in addressing this perennial puzzle, both with respect to propositional imagination and sensory imagination. Making progress requires looking carefully at the interplay between one’s intentions and various kinds of constraints that may be operative in the generation of imaginings. Lessons are drawn from (...) the existing literature on propositional imagination and from the control theory literature concerning the prediction and comparison mechanisms (or “forward models”) involved in ordinary perception. A more general conclusion is reached that, once we have the tools to understand how some imaginings are both under willful control and helpfully guide action and inference, we will have what we need to understand the cognitive basis of imagination in general. (shrink)

Do perceiving subjects represent kind properties in the content of their conscious visual experience when they see and recognize instances of those natural kinds? In Part 1 of my thesis I clarify this question, in Part 2 I answer it, and in Part 3 I raise a problem for previous answers. Part 1 conceives of conscious experience in an internalist way, and the unified conscious episode does not exclude having beliefs about what one sees. Following Siegel and Bayne, Part 2 (...) formulates two arguments in support of representing kind properties in the content of experience. In Part 3, I argue that attempts to distinguish visual experiences from visual beliefs might fail to account for the interplay of sensory and cognitive elements in visual object recognition. I conclude by suggesting it has not been established that visual experiences can be distinguished from visual beliefs. (shrink)

Mental fictionalism holds that folk psychology should be regarded as a kind of fiction. The present version gives a Lewisian prefix semantics for mentalistic discourse, where roughly, a mentalistic sentence “p” is true iff “p” is deducible from the folk psychological fiction. An eliminativist version of the view can seem self-refuting, but this charge is neutralized. Yet a different kind of “self-effacing” emerges: Mental fictionalism appears to be a mere “parasite” on a future science of cognition, without contributing anything substantial. (...) The paper then rebuts the objection, illustrating that prefix semantics resolves a lingering problem for eliminativism from Boghossian. The problem is that eliminativists seem unable to adopt realism about neuroscience, for such realism implies that neuroscientific statements *represent* reality accurately. However, a deflationary version of prefix semantics allows the eliminativist to draw an ontologically relevant distinction (roughly) between truths that have a story-telling prefix and those that do not. (Deflationism means there is no implication that the unprefixed sentences robustly represent reality.) The overarching lesson is that eliminativists need to approach to ontology carefully so to avoid self-refutation; however, prefix semantical mental fictionalism provides the resources for them to do so. (shrink)

Currie’s (2010) argument that “i-desires” must be posited to explain our responses to fiction is critically discussed. It is argued that beliefs and desires featuring ‘in the fiction’ operators—and not sui generis imaginings (or "i-beliefs" or "i-desires")—are the crucial states involved in generating fiction-directed affect. A defense of the “Operator Claim” is mounted, according to which ‘in the fiction’ operators would be also be required within fiction-directed sui generis imaginings (or "i-beliefs" and "i-desires"), were there such. Once we appreciate that (...) even fiction-directed sui generis imaginings would need to incorporate ‘in the fiction’ operators, the main appeal of the idea that sui generis imaginings (or "i-beliefs" or "i-desires") are at work in fiction-appreciation dissipates. [This is Chapter 10 of Explaining Imagination (OUP, 2020)]. (shrink)

Comparatively easy questions we might ask about creativity are distinguished from the hard question of explaining transformative creativity. Many have focused on the easy questions, offering no reason to think that the imagining relied upon in creative cognition cannot be reduced to more basic folk psychological states. The relevance of associative thought processes to songwriting is then explored as a means for understanding the nature of transformative creativity. Productive artificial neural networks—known as generative antagonistic networks (GANs)—are a recent example of (...) how a system’s ability to generate novel products can both be finely tuned by prior experience and grounded in strategies that cannot be articulated by the system itself. Further, the kinds of processes exploited by GANs need not be seen as incorporating something akin to sui generis imaginative states. The chapter concludes with reflection on the added relevance of personal character to explanations of creativity. [This is Chapter 12 of the book Explaining Imagination.]. (shrink)

Neuroclassicism is the view that cognition is explained by “classical” computing mechanisms in the nervous system that exhibit a clear demarcation between processing machinery and read–write memory. The psychologist C. R. Gallistel has mounted a sophisticated defense of neuroclassicism by drawing from ethology and computability theory to argue that animal brains necessarily contain read–write memory mechanisms. This argument threatens to undermine the “connectionist” orthodoxy in contemporary neuroscience, which does not seem to recognize any such mechanisms. In this paper I argue (...) that the neuroclassicist critique rests on a misunderstanding of how computability theory constrains theorizing about natural computing mechanisms. (shrink)

This paper aims to offer a new view of the role of connectionist models in the study of human cognition through the conceptualization of the history of connectionism – from the simplest perceptrons to convolutional neural nets based on deep learning techniques, as well as through the interpretation of criticism coming from symbolic cognitive science. Namely, the connectionist approach in cognitive science was the target of sharp criticism from the symbolists, which on several occasions caused its marginalization and almost complete (...) abandonment of its assumptions in the study of cognition. Criticisms have mostly pointed to its explanatory inadequacy as a theory of cognition or to its biological implausibility as a theory of implementation, and critics often focused on specific shortcomings of some connectionist models and argued that they apply to connectionism in general. In this paper, we want to show that both types of critique are based on the assumption that the only valid explanations in cognitive science are instances of homuncular functionalism and that by removing this assumption and by adopting an alternative methodology – exploratory mechanistic strategy, we can reject most objections to connectionism as irrelevant, explain the progress of connectionist models despite their shortcomings and sketch the trajectory of their future development. By adopting mechanistic explanations and by criticizing functionalism, we will reject the objections of explanatory inadequacy, by characterizing connectionist models as generic rather than concrete mechanisms, we will reject the objections of biological implausibility, and by attributing the exploratory character to connectionist models we will show that practice of generalizing current to general failures of connectionism is unjustified. (shrink)

​Imagination will remain a mystery—we will not be able to explain imagination—until we can break it into parts we already understand. Explaining Imagination is a guidebook for doing just that, where the parts are other ordinary mental states like beliefs, desires, judgments, and decisions. In different combinations and contexts, these states constitute cases of imagining. This reductive approach to imagination is at direct odds with the current orthodoxy, according to which imagination is a sui generis mental state or process—one with (...) its own inscrutable principles of operation. Explaining Imagination upends that view, showing how, on closer inspection, the imaginings at work in hypothetical reasoning, pretense, the enjoyment of fiction, and creativity are reducible to other familiar mental states—judgments, beliefs, desires, and decisions among them. Crisscrossing contemporary philosophy of mind, cognitive science, and aesthetics, Explaining Imagination argues that a clearer understanding of imagination is already well within reach. (shrink)

The purpose of this article is to start a dialogue between the so-called autopoietic enactivism and the semiotic pragmatism of C. S. Peirce, in order to re-examine both action and representation under a Peircean light. The focus lays on autopoietic enactivism because this approach offers a wider theoretical scope to cognition based on the continuity of life and mind, embodiment, dynamic and non-linear interaction between a system and its environment which are compatible ideas with Peirce’s semiotic pragmatism. The term ‘pragmatic’ (...) has been introduced in cognitive science to reinforce the idea that cognition is a form of practice and to help action-oriented viewpoints to escape representationalism. In this paper, I shall try to demonstrate that Peirce’s semiotic pragmatism can be a meaningful methodological path to guide a reconciliation between not only anti-Cartesianism and representation but also representation and action. In order to accomplish this purpose, Peirce’s account to action, habit, thought and mind will be addressed through some of the guiding principles of his semiotic—sign and sign action. What follows is the re-examining of the problem of representation—as refuted by autopoietic enactivism—under the light of Peirce’s semiotic pragmatism. (shrink)

There is a vast literature within philosophy of mind that focuses on artificial intelligence, but hardly mentions methodological questions. There is also a growing body of work in philosophy of science about modeling methodology that hardly mentions examples from cognitive science. Here these discussions are connected. Insights developed in the philosophy of science literature about the importance of idealization provide a way of understanding the neural implausibility of connectionist networks. Insights from neurocognitive science illuminate how relevant similarities between models and (...) targets are picked out, how modeling inferences are justified, and the metaphysical status of models. (shrink)

Explanations of how psychological capacities are carried out often invoke functional brain areas. I argue that such explanations cannot succeed. Psychological capacities are carried out by identifiable entities and their activities in the brain, but functional brain areas are not the relevant entities. I proceed by assuming that if functional brain areas did carry out psychological capacities, then these brain areas could be included in descriptions of mechanisms. And if functional brain areas participate in mechanisms, then they must engage in (...) activities. A number of ways in which we might understand the claim that functional brain areas engage in activities are examined. None are successful, and so one conclusion is that functional brain areas do not participate in mechanisms. Consequently, they are not the entities that carry out psychological capacities. (shrink)

Some contemporary philosophers suggest that we know just by introspection that folk psychological states exist. However, such an "armchair refutation" of eliminativism seems too easy. I first attack two strategems, inspired by Descartes, on how such a refutation might proceed. However, I concede that the Cartesian intuition that we have direct knowledge of representational states is very powerful. The rest of this paper then offers an error theory of how that intuition might really be mistaken. The idea is that introspection (...) does not detect any folk psychological states, but rather detects neural states that dispose us to certain sorts of linguistic behavior. Briefly, rather than detecting a mental appearance of the state-of-affairs that I am sitting near the fire, introspection detects a state disposing me to assert "It appears to me that I am sitting by the fire." The nature of this linguistic-dispositional state is then given a connectionist underpinning, where inputs from introspection lead to such assertive behavior. The Cartesian certainty we feel in self-ascribing such appearances is also explained. Even though I do not endorse such an error theory outright, I suggest that its tenability is enough to undercut introspection arguments against eliminativism. (shrink)

Localizing content in neural networks provides a bridge to understanding the way in which the brain stores and processes information. In this paper, I propose the existence of polytopes in the state space of the hidden layer of feedforward neural networks as vehicles of content. I analyze these geometrical structures from an information-theoretic point of view, invoking mutual information to help define the content stored within them. I establish how this proposal addresses the problem of misclassification and provide a novel (...) solution to the disjunction problem, which hinges on the precise nature of the causal-informational framework for content advocated herein. (shrink)

I argue that intentional psychology does not stand in need of vindication by a lower-level implementation theory from cognitive science, in particular the representational theory of mind (RTM), as most famously Jerry Fodor has argued. The stance of the paper is novel in that I claim this holds even if one, in line with Fodor, views intentional psychology as an empirical theory, and its theoretical posits as as real as those of other sciences. I consider four metaphysical arguments for the (...) idea that intentional psychological states, such as beliefs, must be seen as requiring in-the-head mental representations for us to be able to understand their characteristic causal powers and argue that none of them validly generate their desired conclusions. I go on to argue that RTM, or some computational version thereof, is not motivated by appeal to the nature of cognitive science research either. I conclude that intentional psychology, though an empirical theory, is autonomous from details of lower level mechanism in a way that renders RTM unwarranted. (shrink)

Martin Heidegger is a towering figure in the history of continental philosophy, but his work has recently been brought into productive engagement with analytic philosophy. This paper introduces and explores two channels along which such engagement has been taking place. The first is in metaphysics, where Heideggerian thought has been interpreted either as making the metaphysical concept of being literally senseless or as mandating a revision to classical logic. The second is in philosophy of mind, and more particularly in philosophy (...) of cognitive science, where Heideggerian thought has been used to mount a challenge to representational theories of mind. (shrink)

Recent work in the methodology of connectionist explanation has I'ocrrsccl on the notion of levels of explanation. Specific issucs in conncctionisrn hcrc intersect with rvider areas of debate in the philosophy of psychology and thc philosophy of science generally. The issues I raise in this chapter, then, are not unique to cognitive science; but they arise in new and important contexts when connectionism is taken seriously as a model of cognition. The general questions are the relation between levels and the (...) status of levels which have no obvious relation to others. In speaking of levels, what is the connection, if there is one, between explanation and ontology? Which, if any, conccpt of reduction is applicable to connectionist systems? What kind of legitinrtcy can the constructs of common sense psychology, or of that vclsion ol intentional realism represented by classical symbol-systems n I, hirvc irr ir full-scale connectionist theory of mind? (shrink)

Neuroethological investigations of mammalian and avian auditory systems have documented species-specific specializations for processing complex acoustic signals that could, if viewed in abstract terms, have an intriguing and striking relevance for human speech sound categorization and representation. Each species forms biologically relevant categories based on combinatorial analysis of information-bearing parameters within the complex input signal. This target article uses known neural models from the mustached bat and barn owl to develop, by analogy, a conceptualization of human processing of consonant plus (...) vowel sequences that offers a partial solution to the noninvariance dilemma the locus equations orderly output constraint”) is hypothesized based on the notion of an evolutionarily conserved auditory-processing strategy. High correlation and linearity between critical parameters in the speech signal that help to cue place of articulation categories might have evolved to satisfy a preadaptation by mammalian auditory systems for representing tightly correlated, linearly related components of acoustic signals. (shrink)

The Churchlands are notorious for their theory of eliminative materialism (EM). This theory has become associated with scientism and a possible death of philosophy. In this article, I will closely examine the most common accusations made against EM and try to give an overall assessment of them. The conclusion is that EM survives most of the criticisms levelled against it. For sure, there are many things to do to improve on the current form of the theory, but none of them (...) seems to be unsurpassable. The charges of blind enthusiasm, reductionism, neuroscience exceptionalism and scientism originate from widespread misconceptions about the nature of actual science. Furthermore, the objection that EM is self-defeating is answered. (shrink)

The article provides an analysis of Paul and Patricia Churchland’s eliminative materialism. I will distinguish two lines of argument in their eliminativism: one seeking to eliminate folk psychology and the second criticising Jerry Fodor’s language of thought hypothesis. Then I will closely examine the second line of argument, and show that it represents the main motive of Churchland’s work since the end of 1980s and demonstrate why the success of the argument against the language of thought hypothesis does not constitute (...) a reason for the elimination of folk psychology. Finally, I will examine the consequences of this approach for the role of folk psychology in the study of mind and show that the weakened eliminativist position still fulfils the original aim of Churchland’s program. (shrink)

There is currently a debate over whether cognitive architecture is classical or connectionist in nature. One finds the following three comparisons between classical architecture and connectionist architecture made in the pro-connectionist literature in this debate: (1) connectionist architecture is neurally plausible and classical architecture is not; (2) connectionist architecture is far better suited to model pattern recognition capacities than is classical architecture; and (3) connectionist architecture is far better suited to model the acquisition of pattern recognition capacities by learning than (...) is classical architecture. If true, (1)-(3) would yield a compelling case against the view that cognitive architecture is classical, and would offer some reason to think that cognitive architecture may be connectionist. We first present the case for (1)-(3) in the very words of connectionist enthusiasts. We then argue that the currently available evidence fails to support any of (1)-(3). (shrink)

This paper examines whether a classical model could be translated into a PDP network using a standard connectionist training technique called extra output learning. In Study 1, standard machine learning techniques were used to create a decision tree that could be used to classify 8124 different mushrooms as being edible or poisonous on the basis of 21 different Features (Schlimmer, 1987). In Study 2, extra output learning was used to insert this decision tree into a PDP network being trained on (...) the identical problem. An interpretation of the trained network revealed a perfect mapping from its internal structure to the decision tree, representing a precise translation of the classical theory to the connectionist model. In Study 3, a second network was trained on the mushroom problem without using extra output learning. An interpretation of this second network revealed a different algorithm for solving the mushroom problem, demonstrating that the Study 2 network was indeed a proper theory translation. (shrink)

There is currently a debate over whether cognitive architecture is classical or connectionist in nature. One finds the following three comparisons between classical architecture and connectionist architecture made in the pro-connectionist literature in this debate: (1) connectionist architecture is neurally plausible and classical architecture is not; (2) connectionist architecture is far better suited to model pattern recognition capacities than is classical architecture; and (3) connectionist architecture is far better suited to model the acquisition of pattern recognition capacities by learning than (...) is classical architecture. If true, (1)–(3) would yield a compelling case against the view that cognitive architecture is classical, and would offer some reason to think that cognitive architecture may be connectionist. We first present the case for (1)–(3) in the very words of connectionist enthusiasts. We then argue that the currently available evidence fails to support any of (1)–(3). (shrink)

In various essays, Paul Churchland explores the relevance of studies in cognitive science to issues in ethics. What emerges is a kind of ethical naturalism that has two components. The first component is a descriptive‐genealogical one whose purpose is to explain how people come to have their ethical beliefs. The second component is a normative one whose purpose is to explain why some values are better than other values. Given this distinction, the problem of integrating ethics with beliefs about the (...) world is a consequence of the traditional view that it is possible to naturalize descriptive‐genealogical ethics but not normative ethics. With this distinction as background, I critically examine Churchland's exploration of cognitive science's contribution to our understanding of the values and purposes that should direct our lives. The conclusion is twofold. First, using concepts from the American pragmatists, I argue that, pace Churchland, it is possible to bridge the descriptive‐normative gap in order to articulate an ethical naturalism that addresses the so‐called naturalistic fallacy but is not committed to an unpalatable relativism. Second, I argue that the sort of ethical naturalism that emerges has affinities to the postmodern ethics of Jean‐François Lyotard. (shrink)

In this paper we defend structural representations, more specifically neural structural representation. We are not alone in this, many are currently engaged in this endeavor. The direction we take, however, diverges from the main road, a road paved by the mathematical theory of measure that, in the 1970s, established homomorphism as the way to map empirical domains of things in the world to the codomain of numbers. By adopting the mind as codomain, this mapping became a boon for all those (...) convinced that a representation system should bear similarities with what was being represented, but struggled to find a precise account of what such similarities mean. The euforia was brief, however, and soon homomorphism revealed itself to be affected by serious weaknesses, the primary one being that it included systems embarrassingly alien to representations. We find that the defense attempts that have followed, adopt strategies that share a common format: valid structural representations come as “homomorphism plus X”, with various “X”, provided in descriptive format only. Our alternative direction stems from the observation of the overlooked departure from homomorphism as used in the theory of measure and its later use in mental representations. In the former case, the codomain or the realm of numbers, is the most suited for developing theorems detailing the existence and uniqueness of homomorphism for a wide range of empirical domains. In the latter case, the codomain is the realm of the mind, possibly more vague and more ill-defined than the empirical domain itself. The time is ripe for articulating the mapping between represented domains and the mind in formal terms, by exploiting what is currently known about coding mechanisms in the brain. We provide a sketch of a possible development in this direction, one that adopts the theory of neural population coding as codomain. We will show that our framework is not only not in disagreement with the “plus X” proposals, but can lead to natural derivation of several of the “X”. (shrink)

The paper is an examination of the ways and extent to which neuroscience places constraints on cognitive science. In Part I, I clarify the issue, as well as the notion of levels in cognitive inquiry. I then present and address, in Part II, two arguments designed to show that facts from neuroscience are at a level too low to constrain cognitive theory in any important sense. I argue, to the contrary, that there are several respects in which facts from neurophysiology (...) will constrain cognitive theory. Part III then turns to an examination of Connectionism and Classical Cognitivism to determine which, if either, is in a better position to accomodate neural constraints in the ways suggested in Part II. (shrink)

Connectionist research first emerged in the 1940s. The first phase of connectionism attracted a certain amount of media attention, but scant philosophical interest. The phase came to an abrupt halt, due to the efforts of Minsky and Papert (1969), when they argued for the intrinsic limitations of the approach. In the mid-1980s connectionism saw a resurgence. This marked the beginning of the second phase of connectionist research. This phase did attract considerable philosophical attention. It was of philosophical interest, as it (...) offered a way of counteracting the conceptual ties to the philosophical traditions of atomism, rationalism, logic, nativism, rule realism and a concern with the role symbols play in human cognitive functioning, which was prevalent as a consequence of artificial intelligence research. The surge in philosophical interest waned, possibly in part due to the efforts of some traditionalists and the so-called black box problem. Most recently, what may be thought of as a third phase of connectionist research, based on so-called deep learning methods, is beginning to show some signs of again exciting philosophical interest. (shrink)

This work is an investigation into philosophical method and rational argument in moral philosophy. It makes an original contribution to human understanding, by taking some of the tools and techniques that Gordon Baker identifies in the later work of Wittgenstein, and using them as a way of fending for oneself in an area of philosophy that neither Baker, nor Wittgenstein, wrote on. More specifically, a discussion of some different aspects of the contemporary literature on Dancy’s moral particularism is used as (...) a vehicle for illustrating how Baker’s therapeutic conception of philosophy offers alternative possibilities for how we can do philosophy, and what counts as rational argument in moral philosophy. I maintain that, by considering some indicative ways in which Baker’s therapeutic approach to philosophy can dissolve, rather than solve, the kinds of perplexities found in the existing literature on Dancy’s moral particularism, we can liberate ourselves from the traditional/theoretical view of how we ought to do philosophy, and an understanding of rational argument in moral philosophy, to which we need not be committed. (shrink)

We propose a non-representationalist framework for deep learning relying on a novel method computational phenomenology, a dialogue between the first-person perspective (relying on phenomenology) and the mechanisms of computational models. We thereby propose an alternative to the modern cognitivist interpretation of deep learning, according to which artificial neural networks encode representations of external entities. This interpretation mainly relies on neuro-representationalism, a position that combines a strong ontological commitment towards scientific theoretical entities and the idea that the brain operates on symbolic (...) representations of these entities. We proceed as follows: after offering a review of cognitivism and neuro-representationalism in the field of deep learning, we first elaborate a phenomenological critique of these positions; we then sketch out computational phenomenology and distinguish it from existing alternatives; finally we apply this new method to deep learning models trained on specific tasks, in order to formulate a conceptual framework of deep-learning, that allows one to think of artificial neural networks’ mechanisms in terms of lived experience. (shrink)

Remarks on the Relations between Neurophysiology and Psychology. In the last decades of Analytical Philosophy, contributions to the so-called mind-body-problem have been suffering by several serious methodological misunderstandings: they have failed, for instance, to distinguish between explanations of particular and strictly general ("necessary") properties and between two important senses of existential statements; and they have overlooked the role conceptual explanations play in the development of science. Changing our methodological premisses, we should be able to put questions like that of the (...) relation between (neuro)physiological and psychological phenomena in a new way - and we should be able to see that such newly understood questions allow answers which evade the pitfalls of both reductionist and holistic positions. The paper tries to illustrate and to defend these contentions by reference to a very elementary example: the rational re-building of our concepts to identify behaviour by which a subject controls the position of his body in space. (shrink)

Background: Interdisciplinarity is one of the current trends in the scientific world today, that began with the uneasiness about the loss of the unity of science. This trend also opens possibilities for explaining complex phenomena more comprehensively and creating more advanced applications and implementations of scientific theories. One of the biggest challenges to conducting interdisciplinary research is theoretical integration, how can we combine theories from various disciplines such that the combination is fruitful? Method: This dissertation attempts to answer this challenge (...) by analyzing the intertheoretical connections of some theories from various disciplines for some real interdisciplinary research. The structuralist metatheory of science is applied as the basic theory to model the intertheoretical connections formally. This research begins with modeling the scientific theories in question before modeling the intertheoretical connections and some modifications needed. This research focuses on some researches in cognitive science that involve psychology, neuroscience, and artificial intelligence. The first research is the research conducted by van Veen et al., who research the activity of neurons in a brain's field called dorsal Anterior Cingulate Cortex during a phase of dissonance between cognitions. This research serves as a context for the analysis of intertheoretical reduction between the Festinger theory of cognitive dissonance and the Hawkins-Kandel computational neuroscientific theory. The other research is the consonance model of simulation built by Shultz and Lepper, which implements the Hopfield network to build a simulation of the cognitive dissonance. The third research is the connectionist model of simulation built by van Overwalle and Jordens, which implements the two-layers feed-forward perceptron and the delta rule as its learning rule to build a simulation of forced compliance dissonance. Result: Through this research, the author concludes that the structuralist metatheory of science can be applied for modeling and analyzing intertheoretical connections in the same discipline and between disciplines in real scientific research. The structuralist metatheory of science enables us to model and analyze the structure of the theories and their intertheoretical connections with great detail and brings very fruitful results. This research delivers some results not only for the structuralist theory science itself but also for the philosophy of science in general and interdisciplinary researches, especially cognitive science. First, by analyzing the models, a revision of the definition of intertheoretical specialization, and specialization of the concept of theory-holon according to the structuralist theory of science, called the V-pattern and strategy for combining scientific theories, are proposed. These V-pattern and strategy can serve as a tool for combining scientific theories. Second, unlike other approaches on intertheoretical reduction such as the GNS model, the structuralist metatheory of science does not intend to formulate a generalized model of reduction nor focus only on intertheoretical reduction. It provides us powerful tools for modeling various intertheoretical relations, including intertheoretical reduction, case by case. Although the intertheoretical reduction in the structuralist model is more epistemological than ontological, the structuralist models show how the reduction has empirical claims and intended applications by applying the r* function that maps the T-theoretical level to T-non-theoretical level. Third, related to the notion of the unity of science, this dissertation still sees that the unity of science is still a plausible and essential agenda for the philosophy of science and the scientific world in general. This dissertation's idea of the unity of science proposed does not assume essentialism, reductionism, and epistemological monism. This dissertation sees that the unity of science is closely related to scientific practice. Fourth, for interdisciplinary research, primarily cognitive science, this dissertation proposes an approach to model and analyze intertheoretical connections for any scientific research or any philosophical school in philosophy of science related to the idea of intertheoretical relation. This dissertation is the first example of such modeling and analysis. (shrink)

Remarks on the Relations between Neurophysiology and Psychology. In the last decades of Analytical Philosophy, contributions to the so-called mind-body-problem have been suffering by several serious methodological misunderstandings: they have failed, for instance, to distinguish between explanations of particular and strictly general properties and between two important senses of existential statements; and they have overlooked the role conceptual explanations play in the development of science. Changing our methodological premisses, we should be able to put questions like that of the relation (...) between physiological and psychological phenomena in a new way - and we should be able to see that such newly understood questions allow answers which evade the pitfalls of both reductionist and holistic positions. The paper tries to illustrate and to defend these contentions by reference to a very elementary example: the rational re-building of our concepts to identify behaviour by which a subject controls the position of his body in space. (shrink)

In this paper we defend structural representations, more specifically neural structural representation. We are not alone in this, many are currently engaged in this endeavor. The direction we take, however, diverges from the main road, a road paved by the mathematical theory of measure that, in the 1970s, established homomorphism as the way to map empirical domains of things in the world to the codomain of numbers. By adopting the mind as codomain, this mapping became a boon for all those (...) convinced that a representation system should bear similarities with what was being represented, but struggled to find a precise account of what such similarities mean. The euforia was brief, however, and soon homomorphism revealed itself to be affected by serious weaknesses, the primary one being that it included systems embarrassingly alien to representations. We find that the defense attempts that have followed, adopt strategies that share a common format: valid structural representations come as “homomorphism plus X”, with various “X”, provided in descriptive format only. Our alternative direction stems from the observation of the overlooked departure from homomorphism as used in the theory of measure and its later use in mental representations. In the former case, the codomain or the realm of numbers, is the most suited for developing theorems detailing the existence and uniqueness of homomorphism for a wide range of empirical domains. In the latter case, the codomain is the realm of the mind, possibly more vague and more ill-defined than the empirical domain itself. The time is ripe for articulating the mapping between represented domains and the mind in formal terms, by exploiting what is currently known about coding mechanisms in the brain. We provide a sketch of a possible development in this direction, one that adopts the theory of neural population coding as codomain. We will show that our framework is not only not in disagreement with the “plus X” proposals, but can lead to natural derivation of several of the “X”. (shrink)