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)

Computation is a process of making explicit, information that was implicit. In computing 5 as the solution to ∛125, for example, we move from a description that is not explicitly about 5 to one that is. We are drawing out numerical consequences to the description ∛125. We are extracting information implicit in the problem statement. Can we precisely state the difference between information thati s implicit in a state, structure or process and information that is explicit?

Although the mechanics of how the eye works are well understood, debate still exists as to how the complex machinery of the brain interprets neural impulses...

To my father, who got me thinking, and to Tricia, who provided the love, support, and encouragement that enabled me to see this through.

An essential work for anyone interested in the creativity of the human mind, "The Creative Mind" has been updated to include recent developments in artificial ...

This book relates work in neuroscience, psychology and psychiatry to questions about what a person is and the nature of a persons unity across a lifetime. The neuropsychiatry is now dated. The philosophy has three themes still perhaps of interest. The first is a response to Derek Parfits powerful and influential work on personal identity, which, like many other people, I discussed with him as he worked it out. I accept his view that there is no ego that owns the (...) stream of our experiences, and the unity of a person over time is constructed out of continuities in our mental life. But I argue against Parfits view that personal unity thereby becomes less deep or less morally important. The second theme is an emphasis on the importance of self-creation and an attempt to work out how far it is possible. The third theme is about the way self-creation is linked to recognition by other people, and the importance of this for understanding the role of tribalism in human life. "This book is about what it is to be a person, to think of oneself as an "I". It is about the ways people think of themselves, and how they use these ideas in shaping their own distinctive characteristics. It is about how far we create ourslves." "When a way of life does not fit with what you think you are really like, you can feel like a plant away from the light, distorted by having to twist and grope towards the sun. This analogy suggests that we might have a genetic programme to unfold, in the way plants do. But no doubt it is too simple to think that "the real me" is genetically laid down. These strong affinities we have for some kinds of life, and the sense of drowning that others give us, are likely to have been created by the interaction of our genetic make-up with thigs we have come across and responded to... We care a bit like trees would be, if they were conscious and could partly choose their direction of growth. Perhaps oaks could not become beeches, and stunted trees could not become giants, but they could influence the angle and direction of their branches. Trees thinking about determinism and free will might find it impossible to assess their own contribution to their final shape.". (shrink)

Looks at accounts by Locke, Fodor, Dretske, and Millikan concerning the nature of mental representation, and discusses connectionism and representation.

When it comes to applying computational theory to the problem of phenomenal consciousness, cognitive scientists appear to face a dilemma. The only strategy that seems to be available is one that explains consciousness in terms of special kinds of computational processes. But such theories, while they dominate the field, have counter-intuitive consequences; in particular, they force one to accept that phenomenal experience is composed of information processing effects. For cognitive scientists, therefore, it seems to come down to a choice between (...) a counter-intuitive theory or no theory at all. We offer a way out of this dilemma. We argue that the computational theory of mind doesn't force cognitive scientists to explain consciousness in terms of computational processes, as there is an alternative strategy available: one that focuses on the representational vehicles that encode information in the brain. This alternative approach to consciousness allows us to do justice to the standard intuitions about phenomenal experience, yet remain within the confines of cognitive science. (shrink)

One of the principal tasks Dennett sets himself in Consciousness Explained is to demolish the Cartesian theater 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. (shrink)

In this new volume in the Oxford Psychology Series, the author presents a highly readable account of the cognitive unconscious, focusing in particular on the problem of implicit learning. Implicit learning is defined as the acquisition of knowledge that takes place independently of the conscious attempts to learn and largely in the absence of explicit knowledge about what was acquired. One of the core assumptions of this argument is that implicit learning is a fundamental, "root" process, one that lies at (...) the very heart of the adaptive behavioral repertoire of every complex organism. The author's goals are to outline the essential features of implicit learning that have emerged from the many studies that have been carried out in a variety of experimental laboratories over the past several decades; to present the various alternative perspectives on this issue that have been proposed by other researchers and to try to accommodate these views with his own; to structure the literature so that it can be seen in the context of standard heuristics of evolutionary biology; to present the material within a functionalist approach and to try to show why the experimental data should be seen as entailing particular epistemological perspectives; and to present implicit processing as encompassing a general and ubiquitous set of operations that have wide currency and several possible applications. Chapter 1 begins with the core problem under consideration in this book, a characterization of "implicit learning" as it has come to be used in the literature. Reber puts this seemingly specialized topic into a general framework and suggests a theoretical model based on standard heuristics of evolutionary biology. In his account, Reber weaves a capsule history of interest in and work on the cognitive unconscious. Chapter 2 turns to a detailed overview of the experimental work on the acquisition of implicit knowledge, which currently is of great interest. Chapter 3 develops the evolutionary model within which one can see learning and cognition as richly intertwining issues and not as two distinct fields with one dominating the other. Finally, Chapter 4 explores a variety of entailments and speculations concerning implicit cognitive processes and their general role in the larger scope of human performance. (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)

When are psychologists entitled to call a certain theoretical construct "consciousness?" Over the past few decades cognitive psychologists have reintroduced almost the entire conceptual vocabulary of common sense psychology, but now in a way that is tied explicitly to reliable empirical observations, and to compelling and increasingly adequate theoretical models. Nevertheless, until the past few years most cognitive psychologists and neuroscientists avoided dealing with consciousness. Today there is an increasing willingness to do so. But is "consciousness" different from other theoretical (...) entities like "working memory" or "mental imagery"? Some argue that under no circumstances can empirical science speak of consciousness as such, while others claim that the scientific goal is "knowing what it is like to be a bat" --- to share an organism's conscious experience . The Bat Criterion is ominously reminiscent of the protracted debate on the consciousness of ants and amoebas that caused so much uneasiness in psychology around 1900. It seems to demand that we first solve the mind-body problem as a condition of doing sensible science, and thereby creates the risk of endless, fruitless controversy. The endless philosophical debate about consciousness helped trigger the Behaviorist revolution about 1913, which threw out the baby of consciousness with the bathwater of perennial, circular debate. We've been that way; let's not go back to it. This paper maintains that the position of behavioristic denial is far too restrictive, but that the Bat Criterion is far too demanding --- that in fact, we only need to specify comparable pairs of psychological phenomena that differ only in the fact that one member of any pair is conscious, while the other is not. This "method of contrastive analysis" is a generalization of the experimental method, with consciousness as a variable whose interaction with other psychological and biological phenomena can be assessed in standard ways. As usual in science, this strategy is pragmatic: If it appears to yield sensible results, it can be a stepping-stone toward further understanding . This paper describes five sets of well-established pairs of phenomena that meet these criteria. Others are presented elsewhere, with more of a theoretical interpretation . Here I simply want to show that any adequate theory of conscious experience must satisfy these demanding but achievable empirical constraints. (shrink)

The evidence of blindsight is occasionally used to argue that we can see things, and thus have perceptual belief, without the distinctive visual awareness accompanying normal sight; thereby displacing phenomenality as a component of the concept of vision. I maintain that arguments to this end typically rely on misconceptions about blindsight and almost always ignore associated visual (or visuomotor) pathologies relevant to the lessons of such cases. More specifically, I conclude, first, that the phenomena very likely do not result from (...) dissociations within a single system, but from the interaction of evolutionarily distinct, if interacting, systems; second, that a closer study of spared motor abilities indicates that verbal responses of patients result not from degraded vision but from proprioception; and, finally, above chance verbal responses, being forced guesses, are not tentative beliefs and cannot become beliefs just by training patients to have more confidence in their responses. (shrink)

Complete URL to this document: http://srsc.ulb.ac.be/axcWWW/93-Principles.html.

In Connectionism and the Philosophy of Psychology, Horgan and Tienson (1996) argue that cognitive processes, pace classicism, are not governed by exceptionless, “representation-level” rules; they are instead the work of defeasible cognitive tendencies subserved by the non-linear dynamics of the brain’s neural networks. Many theorists are sympathetic with the dynamical characterisation of connectionism and the general (re)conception of cognition that it affords. But in all the excitement surrounding the connectionist revolution in cognitive science, it has largely gone unnoticed that connectionism (...) adds to the traditional focus on computational processes, a new focus – one on the vehicles of mental representation, on the entities that carry content through the mind. Indeed, if Horgan and Tienson’s dynamical characterisation of connectionism is on the right track, then so intimate is the relationship between computational processes and representational vehicles, that connectionist cognitive science is committed to a resemblance theory of mental content. (shrink)

It is commonplace for both philosophers and cognitive scientists to express their allegiance to the "unity of consciousness". This is the claim that a subject’s phenomenal consciousness, at any one moment in time, is a single thing. This view has had a major influence on computational theories of consciousness. In particular, what we call single-track theories dominate the literature, theories which contend that our conscious experience is the result of a single consciousness-making process or mechanism in the brain. We argue (...) that the orthodox view is quite wrong: phenomenal experience is not a unity, in the sense of being a single thing at each instant. It is a multiplicity, an aggregate of phenomenal elements, each of which is the product of a distinct consciousness-making mechanism in the brain. Consequently, cognitive science is in need of a multi-track theory of consciousness; a computational model that acknowledges both the manifold nature of experience, and its distributed neural basis. (shrink)