Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on processing rather than explicitly (as in a spatial representation). The current report develops a proposal along these lines first described by Jordan (1986) which involves the use of recurrent links in order to provide networks with a dynamic memory. In this approach, hidden unit patterns are fed back to themselves: (...) the internal representations which develop thus reflect task demands in the context of prior internal states. A set of simulations is reported which range from relatively simple problems (temporal version of XOR) to discovering syntactic/semantic features for words. The networks are able to learn interesting internal representations which incorporate task demands with memory demands: indeed, in this approach the notion of memory is inextricably bound up with task processing. These representations reveal a rich structure, which allows them to be highly context‐dependent, while also expressing generalizations across classes of items. These representations suggest a method for representing lexical categories and the type/token distinction. (shrink)

Stephen Cole Kleene was one of the greatest logicians of the twentieth century and this book is the influential textbook he wrote to teach the subject to the next generation. It was first published in 1952, some twenty years after the publication of Godel's paper on the incompleteness of arithmetic, which marked, if not the beginning of modern logic. The 1930s was a time of creativity and ferment in the subject, when the notion of computable moved from the realm of (...) philosophical speculation to the realm of science. This was accomplished by the work of Kurt Gode1, Alan Turing, and Alonzo Church, who gave three apparently different precise definitions of computable. When they all turned out to be equivalent, there was a collective realization that this was indeed the right notion. Kleene played a key role in this process. One could say that he was there at the beginning of modern logic. He showed the equivalence of lambda calculus with Turing machines and with Godel's recursion equations, and developed the modern machinery of partial recursive functions. This textbook played an invaluable part in educating the logicians of the present. It played an important role in their own logical education.". (shrink)

Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial ...

Most ?theories of consciousness? are based on vague speculations about the properties of conscious experience. We aim to provide a more solid basis for a science of consciousness. We argue that a theory of consciousness should provide an account of the very processes that allow us to acquire and use information about our own mental states ? the processes underlying introspection. This can be achieved through the construction of information processing models that can account for ?Type-C? processes. Type-C processes can (...) be specified experimentally by identifying paradigms in which awareness of the stimulus is necessary for an intentional action. The Shallice (1988b) framework is put forward as providing an initial account of Type-C processes, which can relate perceptual consciousness to consciously performed actions. Further, we suggest that this framework may be refined through the investigation of the functions of prefrontal cortex. The formulation of our approach requires us to consider fundamental conceptual and methodological issues associated with consciousness. The most significant of these issues concerns the scientific use of introspective evidence. We outline and justify a conservative methodological approach to the use of introspective evidence, with attention to the difficulties historically associated with its use in psychology. (shrink)

Amidst the many brain events evoked by a visual stimulus, which are specifically associated with conscious perception, and which merely reflect non-conscious processing? Several recent neuroimaging studies have contrasted conscious and non-conscious visual processing, but their results appear inconsistent. Some support a correlation of conscious perception with early occipital events, others with late parieto-frontal activity. Here we attempt to make sense of those dissenting results. On the basis of a minimal neuro-computational model, the global neuronal workspace hypothesis, we propose a (...) taxonomy which distinguishes between vigilance and access to conscious report, as well as between subliminal, preconscious and conscious processing. We suggest that these distinctions map onto different neural mechanisms, and that conscious perception is systematically associated with a sudden surge of parieto-frontal activity causing top-down amplification. (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)

This introductory chapter attempts to clarify the philosophical, empirical, and theoretical bases on which a cognitive neuroscience approach to consciousness can be founded. We isolate three major empirical observations that any theory of consciousness should incorporate, namely (1) a considerable amount of processing is possible without consciousness, (2) attention is a prerequisite of consciousness, and (3) consciousness is required for some specific cognitive tasks, including those that require durable information maintenance, novel combinations of operations, or the spontaneous generation of intentional (...) behavior. We then propose a theoretical framework that synthesizes those facts: the hypothesis of a global neuronal workspace. This framework postulates that, at any given time, many modular cerebral networks are active in parallel and process information in an unconscious manner. An information becomes conscious, however, if the neural population that represents it is mobilized by top-down attentional amplification into a brain-scale state of coherent activity that involves many neurons distributed throughout the brain. The long-distance connectivity of these `workspace neurons' can, when they are active for a minimal duration, make the information available to a variety of processes including perceptual categorization, long-term memorization, evaluation, and intentional action. We postulate that this global availability of information through the workspace is what we subjectively experience as a conscious state. A complete theory of consciousness should explain why some cognitive and cerebral representations can be permanently or temporarily inaccessible to consciousness, what is the range of possible conscious contents, how they map onto specific cerebral circuits, and whether a generic neuronal mechanism underlies all of them. We confront the workspace model with those issues and identify novel experimental predictions. Neurophysiological, anatomical, and brain-imaging data strongly argue for a major role of prefrontal cortex, anterior cingulate, and the areas that connect to them, in creating the postulated brain-scale workspace. (shrink)

This book discusses principles and theories regarding perception and communication. Relevant research data is presented which support these theories. 2004 APA, all rights reserved).

On the occasion of a first conference on Cognitive Science, it seems appropriate to review the basis of common understanding between the various disciplines. In my estimate, the most fundamental contribution so far of artificial intelligence and computer science to the joint enterprise of cognitive science has been the notion of a physical symbol system, i.e., the concept of a broad class of systems capable of having and manipulating symbols, yet realizable in the physical universe. The notion of symbol so (...) defined is internal to this concept, so it becomes a hypothesis that this notion of symbols includes the symbols that we humans use every day of our lives. In this paper we attempt systematically, but plainly, to lay out the nature of physical symbol systems. Such a review is in ways familiar, but not thereby useless. Restatement of fundamentals is an important exercise. (shrink)

Subjects classified visible 2-digit numbers as larger or smaller than 55. Target numbers were preceded by masked 2-digit primes that were either congruent (same relation to 55) or incongruent. Experiments 1 and 2 showed prime congruency effects for stimuli never included in the set of classified visible targets, indicating subliminal priming based on long-term semantic memory. Experiments 2 and 3 went further to demonstrate paradoxical unconscious priming effects resulting from task context. For example, after repeated practice classifying 73 as larger (...) than 55, the novel masked prime 37 paradoxically facilitated the “larger” response. In these experiments task context could induce subjects to unconsciously process only the leftmost masked prime digit, only the rightmost digit, or both independently. Across 3 experiments, subliminal priming was governed by both task context and long-term semantic memory. (shrink)

This book represents the views of one of the greatest mathematicians of the twentieth century on the analogies between computing machines and the living human brain.

This article describes the Adaptive Control of Thought–Rational (ACT–R) cognitive architecture (Anderson et al., 2004; Anderson & Lebiere, 1998) and its detailed application to the learning of algebraic symbol manipulation. The theory is applied to modeling the data from a study by Qin, Anderson, Silk, Stenger, & Carter (2004) in which children learn to solve linear equations and perfect their skills over a 6‐day period. Functional MRI data show that: (a) a motor region tracks the output of equation solutions, (b) (...) a prefrontal region tracks the retrieval of declarative information, (c) a parietal region tracks the transformation of mental representations of the equation, (d) an anterior cingulate region tracks the setting of goal information to control the information flow, and (e) a caudate region tracks the firing of productions in the ACT–R model. The article concludes with an architectural comparison of the competence children display in this task and the competence that monkeys have shown in tasks that require manipulations of sequences of elements. (shrink)