All of the chapters have been written especially for the book by the leading scholars in the field.Michael I. Posner is Professor of Psychology at the ...

PREFACE PART I METAPHYSICS Review of John McDowell’s Mind and World Special Sciences: Still Autonomous after All These Years Conclusion Acknowledgment Notes PART II CONCEPTS Review of Christopher Peacocke’s A Study of Concepts Notes There Are No Recognitional Concepts--Not Even RED Introduction Compositionality Why Premise P is Plausible Objections Conclusion Afterword Acknowledgment Notes There Are No Recognitional Concepts--Not Even RED, Part 2: The Plot Thickens Introduction: The Story ’til Now Compositonality and Learnability Notes Do We Think in Mentalese? Remarks on (...) Some Arguments of Peter Carruthers Appendix: Higher-Order Thoughts Notes Review of A. W. Moore’s Points of View PART III COGNITIVE ARCHITECTURE Review of Paul Churchland’s The Engine of Reason, The Seat of the Soul Connectionism and the Problem of Systematicity: Why Smolensky’s Solution Doesn’t Work Introduction I The Systematicity Problem and Its Classical Solution II Weak Compositionality III Strong Compositional Structure Conclusion Notes Connectionism and the Problem of Systematicity : Why Smolensky’s Solution Still Doesn’t Work Stage 1: Classical Theories The Connection with The Connection with Stage 2: Smolenksy Architectures Stage 3: Why Smolensky’s Solution Still Doesn’t Work Digression on singing and sailing Acknowledgment Notes There and Back Again: A Review of Annette Karmiloff-Smith’s Beyond Modularity 1. Encapsulation 2. Inaccessibility 3. Domain specificity 4. Innateness Conclusion Notes Review of Jeff Elman et al., Rethinking Innateness Brainlikeness Interactions Representational Nativism Empiricism Review of Steven Mithen’s The Prehistory of the Mind PART IV PHILOSOPHICAL DARWINISM Review of Richard Dawkins’s Climbing Mount Improbable Deconstructing Dennett’s Darwin Introduction Adaptation Adaptation and Teleology Deconstruction Notes Is Science Biologically Possible? Comments on Some Arguments of Patricia Churchland and of Alvin Plantinga Acknowledgment Notes Review of Steven Pinker’s How the Mind Works and Henry Plotkin’s Evolution in Mind Computation Massive modularity Innateness Psychological Darwinism. (shrink)

Two widely accepted assumptions within cognitive science are that (1) the goal is to understand the mechanisms responsible for cognitive performances and (2) computational modeling is a major tool for understanding these mechanisms. The particular approaches to computational modeling adopted in cognitive science, moreover, have significantly affected the way in which cognitive mechanisms are understood. Unable to employ some of the more common methods for conducting research on mechanisms, cognitive scientists’ guiding ideas about mechanism have (...) developed in conjunction with their styles of modeling. In particular, mental operations often are conceptualized as comparable to the processes employed in classical symbolic AI or neural network models. These models, in turn, have been interpreted by some as themselves intelligent systems since they employ the same type of operations as does the mind. For this paper, what is significant about these approaches to modeling is that they are constructed specifically to account for behavior and are evaluated by how well they do so—not by independent evidence that they describe actual operations in mental mechanisms. (shrink)

This book is a major contribution to the interdisciplinary project of investigating the true nature of color vision.

Stanley and Williamson have defended the intellectualist thesis that knowing-how is a subspecies of knowing-that by appeal to the syntax and semantics of ascriptions of knowing-how. Critics have objected that this way of defending intellectualism places undue weight on linguistic considerations and fails to give sufficient attention to empirical considerations from the scientific study of the mind. In this paper, I examine and reject Stanley's recent attempt to answer the critics.

(1) This is Part 2 of the semantic theory I call TM. In Part 1, I developed TM as a theory in the analytic philosophy of language, in lexical semantics, and in the sociology of relating occasions of statement production and comprehension to formal and informal lexicographic conclusions about statements and lexical items – roughly, as showing how synchronic semantics is a sociological derivative of diachronic, person-relative acts of linguistic behavior. I included descriptions of new cognitive psychology experimental paradigms (...) which would allow us to precisely measure the two constituents of semantics – meaning and reference – both at the level of individual speech acts and at the level of societal convergences, i.e. at both the token and type levels. -/- (2) In the Introduction, I recapitulate the arguments of Part 1. The Introduction also develops some analytic philosophical and lexical semantics themes not discussed in Part 1. -/- (3) After the Introduction, I present neural TM (nTM) as a theory of the neural mechanisms and processes which give rise to these person/occasion-relative acts of linguistic behavior. I develop nTM at three levels, the first two of which describe linguistic/semantic functions independently of their cortical locations. At the first level, I describe individual word-to-word and word-to-object connections. At the second level, I describe the corresponding structuralist networks of which they are the individual components. At this level, I introduce some key linguistic concepts of TM – its graded meaning, reference, and generalization sets, and the types of statements which express various levels of word-to-word and word-to-object relationships among lexical items which, because of the constraints they impose on the use of those lexical items in statements we produce and comprehend, are concepts. This constitutes the second structural level of nTM. -/- (4) At the third level, I associate the non-localized structures of the previous levels with cortically located neural structures and with the fasciculi that connect them. I distinguish neural areas in which primary (phonetic) and secondary (orthographic) lexicons are stored in long-term memory. I also describe the embodied concepts which co-exist in the anterior temporal lobes with the images they lexicalize. These concepts are often said to name physical objects and their features, although what they in fact name are kinds of physical objects and features. I describe how conceptual constraints and referential constraints interact to channel our intentions to say how things are into statements which are semantically well-formed, and which consequently successfully communicate information. -/- (5) Following this presentation of nTM, I examine five prominent neural semantic theories. I point out what is wrong with each of them as far as their explanations of semantics are concerned, and I also indicate how nTM can replace the “semantic cores” of those theories. -/- (6) The two basic mistakes made by neuroscience semantic theories, as I will explain, are (i) that all but one of them regard semantics as a matter of the association of words with perceptual images, and of generalizations from those associations; and (ii) that they all rely on an unspecified set of neural structures which purportedly encode the meaning of concepts in abstraction from their phonological and orthographic forms. nTM maintains, in contrast, that there are no abstract neural representations of semantic content. Neural constraints on our linguistic behavior, especially on our ascriptive and co-ascriptive use of words, express the semantic constraints on those words which make them concepts. That is the semantic content of words. -/- (7) I next consider several results from neuroscience experimental data which have been given one interpretation by one or another of the standard neurosemantic theories, but to which nTM gives a different interpretation. I include several predictions which I have found neither confirmed nor disconfirmed in the experimental neuroscience literature. -/- (8) After a concluding section in which I summarize the major changes to neurosemantic theory introduced by TM, and the analytic philosophy of language and lexical semantics contexts within which TM is situated, there follows an appendix in which I discuss neural net AI, and make some recommendations for implementing nTM in silicon. (shrink)

Philosophy of science is positioned to make distinctive contributions to cognitive science by providing perspective on its conceptual foundations and by advancing normative recommendations. The philosophy of science I embrace is naturalistic in that it is grounded in the study of actual science. Focusing on explanation, I describe the recent development of a mechanistic philosophy of science from which I draw three normative consequences for cognitive science. First, insofar as cognitive mechanisms are information-processing mechanisms, cognitive science (...) needs an account of how the representations invoked in cognitive mechanisms carry information about contents, and I suggest that control theory offers the needed perspective on the relation of representations to contents. Second, I argue that cognitive science requires, but is still in search of, a catalog of cognitive operations that researchers can draw upon in explaining cognitive mechanisms. Last, I provide a new perspective on the relation of cognitive science to brain sciences, one which embraces both reductive research on neural components that figure in cognitive mechanisms and a concern with recomposing higher-level mechanisms from their components and situating them in their environments. (shrink)

According to proper functionalist theories of warrant, a belief is warranted only if it is formed by cognitive faculties that are properly functioning according to a good, truth-aimed design plan, one that is often thought to be specified either by intentional design or by natural selection. A formidable challenge to proper functionalist theories is the Swampman objection, according to which there are scenarios involving creatures who have warranted beliefs but whose cognitive faculties are not properly functioning, or are (...) poorly designed, or are not aimed at truth. In this paper, we draw lessons from cognitive science in order to develop a novel argument for the conclusion that the Swampman objection fails against proper functionalist theories of warrant. Our argument not only shows that the underlying, central intuition motivating Swampman-like scenarios is false but also motivates proper function as a necessary condition for warrant, thereby lending support to the claim that any theory of knowledge that lacks a proper function requirement is false. (shrink)

_Minds, Brains, Computers_ serves as both an historical and interdisciplinary introduction to the foundations of cognitive science.

This volume features the complete text of all regular papers, posters, and summaries of symposia presented at the 16th annual meeting of the Cognitive Science ...

I identify three lessons from Kenneth Craik’s landmark book “The Nature of Explanation” for contemporary debates surrounding the existence, extent, and nature of mental representation: first, an account of mental representations as neural structures that function analogously to public models; second, an appreciation of prediction as the central component of intelligence in demand of such models; and third, a metaphor for understanding the brain as an engineer, not a scientist. I then relate these insights to discussions surrounding the representational status (...) of predictive processing – which, I argue, provides a contemporary vindication of Craik’s extremely prescient “hypothesis on the nature of thought.”. (shrink)

Credences are similar to levels of confidence, represented as a value on the [0,1] interval. This chapter sheds light on questions about credence, including its relationship to full belief, with an eye toward the empirical relevance of credence. First, I’ll provide a brief epistemological history of credence and lay out some of the main theories of the nature of credence. Then, I’ll provide an overview of the main views on how credences relate to full beliefs. Finally, I’ll turn to the (...) empirical, and suggest some ways that cognitive science does and could answer questions about credence, such as what credences one has, how credences relate to beliefs, and the extent to which we can control our credences. (shrink)

This paper is aimed at identifying how a model’s explanatory power is constructed and identified, particularly in the practice of template-based modeling (Humphreys, Philos Sci 69:1–11, 2002; Extending ourselves: computational science, empiricism, and scientific method, 2004), and what kinds of explanations models constructed in this way can provide. In particular, this paper offers an account of non-causal structural explanation that forms an alternative to causal–mechanical accounts of model explanation that are currently popular in philosophy of biology and cognitive science. (...) Clearly, defences of non-causal explanation are far from new (e.g. Batterman, Br J Philos Sci 53:21–38, 2002a; The devil in the details: asymptotic reasoning in explanation, reduction, and emergence, 2002b; Pincock, Noûs 41:253–275, 2007; Mathematics and scientific representation 2012; Rice, Noûs. doi:10.1111/nous.12042, 2013; Biol Philos 27:685–703, 2012), so the targets here are focused on a particular type of robust phenomenon and how strong invariance to interventions can block a range of causal explanations. By focusing on a common form of model construction, the paper also ties functional or computational style explanations found in cognitive science and biology more firmly with explanatory practices across model-based science in general. (shrink)

How can we think about things in the outside world? There is still no widely accepted theory of how mental representations get their meaning. In light of pioneering research, Nicholas Shea develops a naturalistic account of the nature of mental representation with a firm focus on the subpersonal representations that pervade the cognitive sciences.

The essays in this anthology deal with the growing interconnections developmental psychology and evolutionary biology. This cross-disciplinary interchange coincides, not accidentally, with the renewed interest in ethical naturalism.

In this paper I evaluate the soundness of the prototype paradigm, in particular its basic assumption that there are pan-human psychological essences or core meanings that refer to basic-level natural kinds, explaining why, on the whole, human communication and learning are successful. Instead I argue that there are no particular pan-human basic elements for thought, meaning and cognition, neither prototypes, nor otherwise. To illuminate my view I draw on examples from anthropology. More generally I argue that the prototype paradigm exemplifies (...) two assumptions that dominate cognitive science: (1) If human beings use words they mean something particular and what they mean can be discovered by scientific methods. (2) There is a fixed number of domains of categorization, each made up of a fixed number of basic categories. I suggest that these two assumptions lead to Brave New World. (shrink)

The programme of work -- Towards a theory of jokes -- The process of joke comprehension -- Text comprehension -- Processing and prediction -- Logic in jokes -- Incongruity and resolution -- Surprise -- The role of language -- Impropriety -- Superiority and aggression -- What's in a joke? -- Applying the framework -- The way forward.

Zuidema et al. illustrate how empirical AGL studies can benefit from computational models and techniques. Computational models can help clarifying theories, and thus in delineating research questions, but also in facilitating experimental design, stimulus generation, and data analysis. The authors show, with a series of examples, how computational modeling can be integrated with empirical AGL approaches, and how model selection techniques can indicate the most likely model to explain experimental outcomes.

This article examines the notions of “intuitive” and “counterintuitive” beliefs and concepts in cognitive science of religion. “Intuitive” states are contrasted with those that are products of explicit, conscious reasoning. In many cases the intuitions are grounded in the implicit rules of mental models, frames, or schemas. I argue that the pathway from intuitive to high theological concepts and beliefs may be distinct from that from intuitions to “folk religion,” and discuss how Christian theology might best interpret the results (...) of studies in cognitive psychology of religion. (shrink)

This article explores the limits of social constructionism and criticizes the `demiurgic conception of society' associated with it. It contemplates the possibility of sociological realism by investigating the intrinsic and objective properties of action, cognition and morality. The incorporation of intrinsic meanings and intentions in social actions, the objective information supporting cognitive processes and human sensitivity to pleasure and pain as well as the normative rejection of undue suffering, delineate the objective core of social facts, which can be interpreted (...) or influenced, but not arbitrarily or capriciously constructed or manipulated. This general argument is supported by various illustrations drawn from the semantics of social actions and classical puzzles of interpretative sociology such as the meaning of suicide or the morality of social sanctions. (shrink)

This book demonstrates for the first time how the work of Ludwig Wittgenstein can transform 4E Cognitive Science. In particular, it shows how insights from Wittgenstein can empower those within 4E to reject the long held view that our minds must involve representations inside our heads. The book begins by showing how proponents of 4E are divided amongst themselves. Proponents of Extended Mind insist that internal representations are always needed to explain the human mind. However, proponents of Enacted Mind (...) reject this claim. Using insights from Ludwig Wittgenstein, the book introduces and defends a new theoretical framework called Structural Enacted or Extended Mins (STEEM). (shrink)

Some of the methods for data collection in experimental psychology, as well as many of the inferences from observed behavior or image scanning, are based on the implicit premise that language use can be linked, via the meaning of words, to specific subjective states. Wittgenstein’s well known private language argument (PLA), however, calls into question the legitimacy of such inferences. According to a strong interpretation of PLA, all of the elements of a language must be publicly available. Thus the meaning (...) of words is not fixed by reference to our private experiences, and so data from subjective state claims indicates nothing about our subjective experiences. Application of PLA to psychological studies based on descriptions of the experience of orgasm offers support for the strong version of the conclusion of PLA. We show that PLA has deep implications for data collection methods and inferences in experimental psychology. In particular we critique two contemporary research projects in neuroscience: one studying the ability to remember emotionally loaded words and the other studying experience of attraction. Both of these projects attempt to link subjective experiences and thought processes to particular observable brain states. The research methods appeal to (implicit) inferences from linguistic usage to subjective states. Application of PLA will show that such inferences cannot be made because the meaning of a word is not determined by any subjective state of the speaker. (shrink)

Hume said that to have a memory image of some individual, x, is to perceive a ‘faint copy’ of some prior perception of x. This classical view of memory images includes three distinct claims: Images and percepts are mental entities which serve as objects for a ‘direct’ or ‘non-inferential’ perception. A memory image of some individual, x, shares numerous properties with some prior perception of x.

The volumes are self contained and can be used individually in upper-level undergraduate and graduate courses ranging from introductory psychology, linguistics, ...

Media reporting of science has consequences for public debates on the ethics of research. Accordingly, it is crucial to understand how the sciences of the brain and the mind are covered in the media, and how coverage is received and negotiated. The authors report here their sociological findings from a case study of media coverage and associated reader comments of an article from Annals of Neurology. The media attention attracted by the article was high for cognitive science; further, as (...) associates/members of the Centre where it was produced, the authors of the research reported here had rare insight into how the scientists responsible for the Annals of Neurology article interacted with the media. The data corpus included 37 news items and 228 readers’ comments, examined via qualitative thematic analysis. Media coverage of the article was largely accurate, without merely copying the press release. Analysis of reader comments showed these to be an important resource for considering issues of import to neuroethics scholars, as well as to scientists themselves. In particular, the findings demonstrate how personal experiences were vital in shaping readers’ accounts of their agreements with the scientific article. Furthermore, the data show how scientific research can catalyse political discussions in ways likely unanticipated by scientists. The analysis indicates the importance of dialogue between journalists, laboratory scientists and social scientists in order to support the communication of the messages researchers intend. (shrink)

There is a growing chorus of voices in the scientific community calling for greater openness in the sharing of raw data that lead to a publication. In this commentary, we discuss the merits of sharing, common concerns that are raised, and practical issues that arise in developing a sharing policy. We suggest that the cognitive science community discuss the topic and establish a data-sharing policy.