Non-sensory experiences represent almost all context information in consciousness. They condition most aspects of conscious cognition including voluntary retrieval, perception, monitoring, problem solving, emotion, evaluation, meaning recognition. Many peculiar aspects of non-sensory qualia (e.g., they resist being 'grasped' by an act of attention) are explained as adaptations shaped by the cognitive functions they serve. The most important nonsensory experience is coherence or "rightness." Rightness represents degrees of context fit among contents in consciousness, and between conscious and non-conscious processes. Rightness (not (...) familiarity) is the feeling-of-knowing in implicit cognition. The experience of rightness suggests that neural mechanisms "compute" signals indicating the global dynamics of network integration. (shrink)

Baars (1988, 1997) has proposed a psychological theory of consciousness, called global workspace theory. The present study describes a software agent implementation of that theory, called ''Conscious'' Mattie (CMattie). CMattie operates in a clerical domain from within a UNIX operating system, sending messages and interpreting messages in natural language that organize seminars at a university. CMattie fleshes out global workspace theory with a detailed computational model that integrates contemporary architectures in cognitive science and artificial intelligence. Baars (1997) lists the psychological (...) ''facts that any complete theory of consciousness must explain'' in his appendix to In the Theater of Consciousness; global workspace theory was designed to explain these ''facts.'' The present article discusses how the design of CMattie accounts for these facts and thereby the extent to which it implements global workspace theory. (shrink)

Conscious experience is one of the most difficult and thorny problems in psychological science. Its study has been neglected for many years, either because it was thought to be too difficult, or because the relevant evidence was thought to be poor. Bernard Baars suggests a way to specify empirical constraints on a theory of consciousness by contrasting well-established conscious phenomena - such as stimulus representations known to be attended, perceptual, and informative - with closely comparable unconscious ones - such as (...) stimulus representations known to be preperceptual, unattended, or habituated. Adducing data to show that consciousness is associated with a kind of global workplace in the nervous system, and that several brain structures are known to behave in accordance with his theory, Baars helps to clarify many difficult problems. (shrink)

Can we make progress exploring consciousness? Or is it forever beyond human reach? In science we never know the ultimate outcome of the journey. We can only take whatever steps our current knowledge affords. This paper explores today's evidence from the viewpoint of Global Workspace theory. First, we ask what kind of evidence has the most direct bearing on the question. The answer given here is ‘contrastive analysis’ -- a set of paired comparisons between similar conscious and unconscious processes. This (...) body of evidence is already quite large, and constrains any possible theory . Because it involves both conscious and unconscious events, it deals directly with our own subjective experience, as anyone can tell by trying the demonstrations in this article. (shrink)

First published in 1995, The Visual Brain in Action remains a seminal publication in the cognitive sciences. It presents a model for understanding the visual processing underlying perception and action, proposing a broad distinction within the brain between two kinds of vision: conscious perception and unconscious 'online' vision. It argues that each kind of vision can occur quasi-independently of the other, and is separately handled by a quite different processing system. In the 11 years since publication, the book has provoked (...) considerable interest and debate - throughout both cognitive neuroscience and philosophy, while the field has continued to flourish and develop. -/- For this new edition, the text from the original edition has been left untouched, standing as a coherent statement of the authors' position. However, a very substantial epilogue has been added to the book in which Milner and Goodale review some of the key developments that support or challenge the views that were put forward in the first edition. The new chapter summarizes developments in various relevant areas of psychology, neuroscience and behaviour. It notably supplements the main text by updating the reader on the contributions that have emerged from the use of functional neuroimaging, which was in its infancy when the first edition was written. Neuroimaging, and functional MRI in particular, has revolutionized the field over the past 11 years by allowing investigators to plot in detail the patterns of activity within the visual brains of behaving and perceiving humans. The authors show how its use now allows scientists to test and confirm their proposals, based as they then were largely on evidence accrued from primate neuroscience in conjunction with studies of neurological patients. (shrink)

Voluntary acts are preceded by electrophysiological (RPs). With spontaneous acts involving no preplanning, the main negative RP shift begins at about200 ms. Control experiments, in which a skin stimulus was timed (S), helped evaluate each subject's error in reporting the clock times for awareness of any perceived event.

Having laid the groundwork in his critically acclaimed books Neural Darwinism (Basic Books, 1987) and Topobiology (Basic Books, 1988), Nobel laureate Gerald M. Edelman now proposes a comprehensive theory of consciousness in The Remembered ...

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

This paper explores a variety of different versions of the thesis that natural language is involved in human thinking. It distinguishes amongst strong and weak forms of this thesis, dismissing some as implausibly strong and others as uninterestingly weak. Strong forms dismissed include the view that language is conceptually necessary for thought (endorsed by many philosophers) and the view that language is _de facto_ the medium of all human conceptual thinking (endorsed by many philosophers and social scientists). Weak forms include (...) the view that language is necessary for the acquisition of many human concepts, and the view that language can serve to scaffold human thought processes. The paper also discusses the thesis that language may be the medium of _conscious_ propositional thinking, but argues that this cannot be its most fundamental cognitive role. The idea is then proposed that natural language is the medium for non-domain-specific thinking, serving to integrate the outputs of a variety of domain-specific conceptual faculties (or central-cognitive ‘quasi-modules’). Recent experimental evidence in support of this idea is reviewed, and the implications of the idea are discussed, especially for our conception of the architecture of human cognition. Finally, some further kinds of evidence which might serve to corroborate or refute the hypothesis are mentioned. The overall goal of the paper is to review a wide variety of accounts of the cognitive function of natural language, integrating a number of different kinds of evidence and theoretical consideration in order to propose and elaborate the most plausible candidate. (shrink)

Much of traditional AI exemplifies the explicit representation paradigm, and during the late 1980''s a heated debate arose between the classical and connectionist camps as to whether beliefs and rules receive an explicit or implicit representation in human cognition. In a recent paper, Kirsh (1990) questions the coherence of the fundamental distinction underlying this debate. He argues that our basic intuitions concerning explicit and implicit representations are not only confused but inconsistent. Ultimately, Kirsh proposes a new formulation of the distinction, (...) based upon the criterion ofconstant time processing.The present paper examines Kirsh''s claims. It is argued that Kirsh fails to demonstrate that our usage of explicit and implicit is seriously confused or inconsistent. Furthermore, it is argued that Kirsh''s new formulation of the explicit-implicit distinction is excessively stringent, in that it banishes virtually all sentences of natural language from the realm of explicit representation. By contrast, the present paper proposes definitions for explicit and implicit which preserve most of our strong intuitions concerning straightforward uses of these terms. It is also argued that the distinction delineated here sustains the meaningfulness of the abovementioned debate between classicists and connectionists. (shrink)

What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...) But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to. (shrink)

Presenting a look at the human mind's capacity while criticizing artificial intelligence, the author makes suggestions about classical and quantum physics and ..

The philosophy of mind and cognition has been transformed by recent advances in what is loosely called cognitive science. This book is a thoroughly up-to-date introduction to and account of that transformation, in which the many strands in contemporary cognitive science are brought together into a coherent philosophical picture of the mind. The book begins with discussions of the pre-history of contemporary philosophy of mind - dualism, behaviourism, and early versions of the identity theory of mind - and moves through (...) discussions of functionalism in autonomy of psychology, to topics such as eliminative materialism, individualism and the problems of content and representation. The synoptic nature of the discussion makes it ideal as the foundation of an undergraduate course in the philosophy of mind. (shrink)

Linking the process of rational decision making to emotions, an award-winning scientist who has done extensive research with brain-damaged patients notes the dependence of thought processes on feelings and the body's survival-oriented regulators. 50,000 first printing.

Jaegwon Kim is one of the most preeminent and most influential contributors to the philosophy of mind and metaphysics. This collection of essays presents the core of his work on supervenience and mind with two sets of postscripts especially written for the book. The essays focus on such issues as the nature of causation and events, what dependency relations other than causal relations connect facts and events, the analysis of supervenience, and the mind-body problem. A central problem in the philosophy (...) of mind is the problem of explaining how the mind can causally influence bodily processes. Professor Kim explores this problem in detail, criticizes the nonreductionist solution of it, and offers a modified reductionist solution of his own. Both professional philosophers and their graduate students will find this an invaluable collection. (shrink)

Consciousness is a mongrel concept: there are a number of very different "consciousnesses." Phenomenal consciousness is experience; the phenomenally conscious aspect of a state is what it is like to be in that state. The mark of access-consciousness, by contrast, is availability for use in reasoning and rationally guiding speech and action. These concepts are often partly or totally conflated, with bad results. This target article uses as an example a form of reasoning about a function of "consciousness" based on (...) the phenomenon of blindsight. Some information about stimuli in the blind field is represented in the brains of blindsight patients, as shown by their correct "guesses," but they cannot harness this information in the service of action, and this is said to show that a function of phenomenal consciousness is somehow to enable information represented in the brain to guide action. But stimuli in the blind field are BOTH access-unconscious and phenomenally unconscious. The fallacy is: an obvious function of the machinery of access-consciousness is illicitly transferred to phenomenal consciousness. (shrink)

Little, Brown, 1992 Review by Glenn Branch on Jul 5th 1999 Volume: 3, Number: 27.

To make progress on the problem of consciousness, we have to confront it directly. In this paper, I first isolate the truly hard part of the problem, separating it from more tractable parts and giving an account of why it is so difficult to explain. I critique some recent work that uses reductive methods to address consciousness, and argue that such methods inevitably fail to come to grips with the hardest part of the problem. Once this failure is recognized, the (...) door to further progress is opened. In the second half of the paper, I argue that if we move to a new kind of nonreductive explanation, a naturalistic account of consciousness can be given. I put forward my own candidate for such an account: a nonreductive theory based on principles of structural coherence and organizational invariance, and a double-aspect theory of information. (shrink)

I examine the phenomenon of implicit learning, the process by which knowledge about the rule-governed complexities of the stimulus environment is acquired independently of conscious attempts to do so. Our research with the two seemingly disparate experimental paradigms of synthetic grammar learning and probability learning, is reviewed and integrated with other approaches to the general problem of unconscious cognition. The conclusions reached are as follows: Implicit learning produces a tacit knowledge base that is abstract and representative of the structure of (...) the environment; such knowledge is optimally acquired independently of conscious efforts to learn; and it can be used implicitly to solve problems and make accurate decisions about novel stimulus circumstances. Various epistemological issues and related problems such as intuition, neuroclinical disorders of learning and memory, and the relationship of evolutionary processes to cognitive science are also discussed. (shrink)

An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent (...) explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993. (shrink)

When cognitive scientists apply computational theory to the problem of phenomenal consciousness, as many of them have been doing recently, there are two fundamentally distinct approaches available. Either consciousness is to be explained in terms of the nature of the representational vehicles the brain deploys; or it is to be explained in terms of the computational processes defined over these vehicles. We call versions of these two approaches _vehicle_ and _process_ theories of consciousness, respectively. However, while there may be space (...) for vehicle theories of consciousness in cognitive science, they are relatively rare. This is because of the influence exerted, on the one hand, by a large body of research which purports to show that the explicit representation of information in the brain and conscious experience are _dissociable_, and on the other, by the _classical_ computational theory of mind – the theory that takes human cognition to be a species of symbol manipulation. But two recent developments in cognitive science combine to suggest that a reappraisal of this situation is in order. First, a number of theorists have recently been highly critical of the experimental methodologies employed in the dissociation studies – so critical, in fact, it’s no longer reasonable to assume that the dissociability of conscious experience and explicit representation has been adequately demonstrated. Second, classicism, as a theory of human cognition, is no longer as dominant in cognitive science as it once was. It now has a lively competitor in the form of _connectionism; _and connectionism, unlike classicism, does have the computational resources to support a robust vehicle theory of consciousness. In this paper we develop and defend this connectionist vehicle theory of consciousness. It takes the form of the following simple empirical hypothesis: _phenomenal experience consists in the explicit_ _representation of information in neurally realized PDP networks_.. (shrink)

Theorists are converging from quite different quarters on a version of the global neuronal workspace model of consciousness, but there are residual confusions to be dissolved. In particular, theorists must resist the temptation to see global accessibility as the cause of consciousness (as if consciousness were some other, further condition); rather, it is consciousness. A useful metaphor for keeping this elusive idea in focus is that consciousness is rather like fame in the brain. It is not a privileged medium of (...) representation, or an added property some states have; it is the very mutual accessibility that gives some informational states the powers that come with a subject's consciousness of that information. Like fame, consciousness is not a momentary condition, or a purely dispositional state, but rather a matter of actual influence over time. Theorists who take on the task of accounting for the aftermath that is critical for consciousness often appear to be leaving out the Subject of consciousness, when in fact they are providing an analysis of the Subject, a necessary component in any serious theory of consciousness. (shrink)

Examining one of the fundamental issues in cognitive psychology: How does our conscious experience come to be the way it is?

This paper addresses weighting and partitioning in complex reinforcement learning tasks, with the aim of facilitating learning. The paper presents some ideas regarding weighting of multiple agents and extends them into partitioning an input/state space into multiple regions with di erential weighting in these regions, to exploit di erential characteristics of regions and di erential characteristics of agents to reduce the learning complexity of agents (and their function approximators) and thus to facilitate the learning overall. It analyzes, in reinforcement learning (...) tasks, di erent ways of partitioning a task and using agents selectively based on partitioning. Based on the analysis, some heuristic methods are described and experimentally tested. We nd that some o -line heuristic methods performed the best, signi cantly better than single-agent models. (shrink)

First published in 1995, The Visual Brain in Action remains a seminal publication in the cognitive sciences. For this new edition, a very substantial and illustrated epilogue has been added to the book in which Milner and Goodale review the key developments that support or challenge the views that were put forward in the first edition.

Connectionism and phenomenology can mutually inform and mutually constrain each other. In this manifesto I outline an approach to consciousness based on distinctions developed by connectionists. Two core identities are central to a connectionist theory of consciouness: conscious states of mind are identical to occurrent activation patterns of processing units; and the variable dispositional strengths on connections between units store latent and unconscious information. Within this broad framework, a connectionist model of consciousness succeeds according to the degree of correspondence between (...) the content of human consciousness (the world as it is experienced) and the interpreted content of the network. Constitutive self-awareness and reflective self-awareness can be captured in a model through its ability to respond to self-reflexive information, identify self-referential categories, and process information in the absence of simultaneous input. The qualitative feel of sensation appears in a model as states of activation that are not fully discriminated by later processing. Connectionism also uniquely explains several specific features of experience. The most important of these is the superposition of information in consciousness — our ability to perceive more than meets the eye, and to apprehend complex categorical and temporal information in a single highly-cognized glance. This superposition in experience matches a superposition of representational content in distributed representations. (shrink)

This paper argues for an explanation of the mechanistic (computational) basis of consciousness that is based on the distinction between localist (symbolic) representation and distributed representation, the ideas of which have been put forth in the connectionist literature. A model is developed to substantiate and test this approach. The paper also explores the issue of the functional roles of consciousness, in relation to the proposed mechanistic explanation of consciousness. The model, embodying the representational difference, is able to account for the (...) functional role of consciousness, in the form of the synergy between the conscious and the unconscious. The fit between the model and various cognitive phenomena and data (documented in the psychological literatures) is discussed to accentuate the plausibility of the model and its explanation of consciousness. Comparisons with existing models of consciousness are made in the end. (shrink)

Research on expert‐novice differences has mainly focused on how experts solve familiar problems. We know far less about the skills and knowledge used by experts when they are confronted with novel problems within their area of expertise. This article discusses a study in which verbal protocols were taken from subjects of various expertise designing an experiment in an area with which they were unfamiliar. The results showed that even when domain knowledge is lacking, experts solve a novel problem within their (...) area of expertise by dividing the problem into a number of subproblems that are solved in a specified order. The lack of domain knowledge is compensated for by using abstract knowledge structures and domain‐specific heuristic strategies. However, the quality of their solutions is considerably lower than the quality attained by experts who were familiar with the type of problem to be solved. The results suggest that when experts are confronted with novel problems as compared with familiar problems, their form of reasoning remains intact, but the content of their reasoning suffers due to lack of domain knowledge. (shrink)