What do people learn when they do not know that they are learning? Until recently, all of the work in the area of implicit learning focused on empirical questions and methods. In this book, Axel Cleeremans explores unintentional learning from an information-processing perspective. He introduces a theoretical framework that unifies existing data and models on implicit learning, along with a detailed computational model of human performance in sequence-learning situations.

As linguistic competence so clearly illustrates, processing sequences of events is a fundamental aspect of human cognition. For this reason perhaps, sequence learning behavior currently attracts considerable attention in both cognitive psychology and computational theory. In typical sequence learning situations, participants are asked to react to each element of sequentially structured visual sequences of events. An important issue in this context is to determine whether essentially associative processes are sufficient to understand human performance, or whether more powerful learning mechanisms are (...) necessary. To address this issue, we explore how well human participants and connectionist models are capable of learning sequential material that involves complex, disjoint, longdistance contingencies. We show that the popular Simple Recurrent Network model (Elman, 1990), which has otherwise been shown to account for a variety of empirical findings (Cleeremans, 1993), fails to account for human performance in several experimental situations meant to test the model’s specific predictions. In previous research (Cleeremans, 1993) briefly described in this paper, the structure of center-embedded sequential structures was manipulated to be strictly identical or probabilistically different as a function of the elements surrounding the embedding. While the SRN could only learn in the second case, human subjects were found to be insensitive to the manipulation. In the new experiment described in this paper, we tested the idea that performance benefits from “starting small effects” (Elman, 1993) by contrasting two conditions in which the training regimen was either incremental or not. Again, while the SRN is only capable of learning in the first case, human subjects were able to learn in both. We suggest an alternative model based on Maskara & Noetzel’s (1991) Auto-Associative Recurrent Network as a way to overcome the SRN model’s failure to account for the empirical findings.. (shrink)

69 Thompson-Schill, S.L. _et al. _(1997) Role of left inferior prefrontal cortex 59 Buckner, R.L. _et al. _(1996) Functional anatomic studies of memory in retrieval of semantic knowledge: a re-evaluation _Proc. Natl. Acad._ retrieval for auditory words and pictures _J. Neurosci. _16, 6219–6235 _Sci. U. S. A. _94, 14792–14797 60 Buckner, R.L. _et al. _(1995) Functional anatomical studies of explicit and 70 Baddeley, A. (1992) Working memory: the interface between memory implicit memory retrieval tasks _J. Neurosci. _15, 12–29 and cognition (...) _J. Cogn. Neurosci. _4, 281–288 61 Bäckman, L. _et al. _(1997) Brain activation in young and older adults 71 Petrides, M. (1994) Frontal lobes and behavior _Curr. Opin. Neurobiol._ during implicit and explicit retrieval _J. Cogn. Neurosci. _9, 378–391. (shrink)

In Proceedings of the 17th Annual Conference of the Cognitive Science Society, Hillsdale, NJ: Erlbaum, 1995.

According to unconscious thought theory, complex decisions are best made after a period of distraction assumed to elicit ‘‘unconscious thought.’’ Here, the authors suggest instead that the superiority of decisions made after distraction results from the fact that conscious deliberation can deteriorate impressions formed on-line during information acquisition. The authors found that participants instructed to form an impression made better decisions after distraction than after deliberation, thereby replicating earlier findings. However, decisions made immediately were just as good as decisions made (...) after distraction, which suggests (a) that people had already made their decision during information acquisition, (b) that deliberation without attention does not occur during distraction, and (c) that ruminating about one’s first impression can deteriorate decision quality. Strikingly, in another condition that should have favored unconscious thought even more, deliberated decisions were better than immediate or distracted decisions. These findings were replicated in a field study. (shrink)

The ability to process events in their temporal and sequential context is a fundamental skill made mandatory by constant interaction with a dynamic environment. Sequence learning studies have demonstrated that subjects exhibit detailed — and often implicit — sensitivity to the sequential structure of streams of stimuli. Current connectionist models of performance in the so-called Serial Reaction Time Task (SRT), however, fail to capture the fact that sequence learning can be based not only on sensitivity to the sequential associations between (...) successive stimuli, but also on sensitivity to the associations between successive responses, and on the predictive relationships that exist between these sequences of responses and their effects in the environment. In this paper, we offer an initial exploration of an alternative architecture for sequence learning, based on the principles of Forward Models. (shrink)

Electronic Mail: [email protected] Abstract Stability of activation, while it may be necessary for information to become available to consciousness, is not sufficient to produce phenomenal experience. We suggest that consciousness involves access to information and that access makes information symbolic. From this perspective, implicit representations exist, and are best thought of as sub-symbolic. Crucially, such representations can be causally efficacious in the absence of consciousness.

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

While the study of implicit learning is nothing new, the field as a whole has come to embody — over the last decade or so — ongoing questioning about three of the most fundamental debates in the cognitive sciences: The nature of consciousness, the nature of mental representation (in particular the difficult issue of abstraction), and the role of experience in shaping the cognitive system. Our main goal in this chapter is to offer a framework that attempts to integrate current (...) thinking about these three issues in a way that specifically links consciousness with adaptation and learning. Our assumptions about this relationship are rooted in further assumptions about the nature of processing and of representation in cognitive systems. When considered together, we believe that these assumptions offer a new perspective on the relationships between conscious and unconscious processing and on the function of consciousness in cognitive systems. (shrink)

Consciousness has many elements, from sensory experiences such as vision and bodily sensation, to nonsensory aspects such as memory and thought. All are presented as experiences of a single subject, and all seem to be contained within a unified field of experience. This unity raises many questions: How do diverse systems in the brain co-operate to produce a unified experience? Are there conditions under which this unity breaks down? Is conscious experience really unified at all? Such questions are addressed in (...) this thought-provoking book. (shrink)

A significant part of everyday learning occurs incidentally — a process typically described as implicit learning. A central issue in this domain and others, such as language acquisition, is the extent to which performance depends on the acquisition and deployment of abstract rules. Shanks and colleagues [22], [11] have suggested (1) that discrimination between grammatical and ungrammatical instances of a biconditional grammar requires the acquisition and use of abstract rules, and (2) that training conditions — in particular whether instructions orient (...) participants to identify the relevant rules or not — strongly influence the extent to which such rules will be learned. In this paper, we show (1) that a Simple Recurrent Network can in fact, under some conditions, learn a biconditional grammar, (2) that training conditions indeed influence learning in simple auto-associators networks and (3) that such networks can likewise learn about biconditional grammars, albeit to a lesser extent than human participants. These findings suggest that mastering biconditional grammars does not require the acquisition of abstract rules to the extent implied by Shanks and colleagues, and that performance on such material may in fact be based, at least in part, on simple associative learning mechanisms. (shrink)

Consider Susan Hurley's depiction of mainstream views of the mind: "The mind is a kind of sandwich, and cognition is the filling" (p. 401). This particular sandwich (with perception as the bottom loaf and action as the top loaf) tastes foul to Hurley, who devotes most of "Consciousness in Action" to a systematic and sometimes extraordinarily detailed critique of what has otherwise been dubbed "classical" models of the mind. This critique then provides the basis for her alternative proposal, in which (...) perception, action and environment are deeply intertwined. (shrink)

We explore a network architecture introduced by Elman (1988) for predicting successive elements of a sequence. The network uses the pattern of activation over a set of hidden units from time-step 25-1, together with element t, to predict element t + 1. When the network is trained with strings from a particular finite-state grammar, it can learn to be a perfect finite-state recognizer for the grammar. When the network has a minimal number of hidden units, patterns on the hidden units (...) come to correspond to the nodes of the grammar, although this correspondence is not necessary for the network to act as a perfect finite-state recognizer. We explore the conditions under which the network can carry information about distant sequential contingencies across intervening elements. Such information is maintained with relative ease if it is.. (shrink)

Using positron emission tomography (PET) and regional cerebral blood flow (rCBF) measurements, we investigated the cerebral correlates of consciousness in a sequence learning task through a novel application of the Process Dissociation Procedure, a behavioral paradigm that makes it possible to separately assess conscious and unconscious contributions to performance. Results show that the metabolic response in the anterior cingulate / mesial prefrontal cortex (ACC / MPFC) is exclusively and specifically correlated with the explicit component of performance during recollection of a (...) learned sequence. This suggests a significant role for the ACC / MPFC in the explicit processing of sequential material.  2003 Elsevier Science B.V. All rights reserved. (shrink)

Over the past few years numerous proposals have appeared that attempt to characterize consciousness in terms of what could be called its computational correlates: Principles of information processing with which to characterize the differences between conscious and unconscious processing. Proposed computational correlates include architectural specialization (such as the involvement of specific regions of the brain in conscious processing), properties of representations (such as their stability in time or their strength), and properties of specific processes (such as resonance, synchrony, interactivity, or (...) information integration). In exactly the same way as one can engage in a search for the neural correlates of consciousness, one can thus search for the computational correlates of consciousness. The most direct way of doing is to contrast models of conscious versus unconscious information processing. In this paper, I review these developments and illustrate how computational modeling of specific cognitive processes can be useful in exploring and in formulating putative computational principles through which to capture the differences between conscious and unconscious cognition. What can be gained from such approaches to the problem of consciousness is an understanding of the function it plays in information processing and of the mechanisms that subtend it. Here, I suggest that the central function of consciousness is to make it possible for cognitive agents to exert ?exible, adaptive control over behavior. From this perspective, consciousness is best characterized as involving (1) a graded continuum de?ned over quality of representation, such that availability to consciousness and to cognitive control correlates with properties of representation, and (2) the implication of systems of meta-representations. (shrink)

Consciousness remains a mystery—“a phenomenon that people do not know how to think about—yet” (Dennett, , p. 21). Here, I consider how the connectionist perspective on information processing may help us progress toward the goal of understanding the computational principles through which conscious and unconscious processing differ. I begin by delineating the conceptual challenges associated with classical approaches to cognition insofar as understanding unconscious information processing is concerned, and to highlight several contrasting computational principles that are constitutive of the connectionist (...) approach. This leads me to suggest that conscious and unconscious processing are fundamentally connected, that is, rooted in the very same computational principles. I further develop a perspective according to which the brain continuously and unconsciously learns to redescribe its own activity itself based on constant interaction with itself, with the world, and with other minds. The outcome of such interactions is the emergence of internal models that are metacognitive in nature and that function so as to make it possible for an agent to develop a (limited, implicit, practical) understanding of itself. In this light, plasticity and learning are constitutive of what makes us conscious, for it is in virtue of our own experiences with ourselves and with other people that our mental life acquires its subjective character. The connectionist framework continues to be uniquely positioned in the Cognitive Sciences to address the challenge of identifying what one could call the “computational correlates of consciousness” (Mathis & Mozer, ) because it makes it possible to focus on the mechanisms through which information processing takes place. (shrink)

Consider the following three situations: learning to perform a complex skill such as gymastics (a stunning demonstration of which participants to ICP 2004 experienced during the opening ceremony), learning a complex game such as the ancient Chinese game of Weichi (more widely known as Go), or learning natural language. What these situations have in common, beyond the sheer complexity of the required skills, is the fact that most of what we learn about each appears to proceed in a manner that (...) does not depend so much on the acquisition of explicit, declarative information or on the deployment of intentional strategies, but instead critically depends on repeated practice: Developing the skills needed to execute complex movements in gymnastics, to. (shrink)

Comparing the relative sensitivity of direct and indirect measures of learning is proposed as the best way to provide evidence for unconscious learning when both conceptual and operative definitions of awareness are lacking. This approach was first proposed by Reingold & Merikle (1988) in the context of subliminal perception. In this paper, we apply it to a choice reaction time task in which the material is generated based on a probabilistic finite-state grammar (Cleeremans, 1993). We show (1) that participants (...) progressively learn about the statistical structure of the stimulus material over training with the choice reaction time task, and (2) that they can use some of this knowledge to predict the location of the next stimulus in a subsequent “generation” task. However, detailed partial correlational analyses of the correspondence between performance during the reaction time task and the statistical structure of the training material showed that large effects remained even when controlling for explicit knowledge as assessed by the generation task. Hence we conclude (1) that at least some of the knowledge expressed through reaction time performance can not be characterized as conscious, and (2) that even when associations are found at a global level of analysis, dissociations can still be obtained when more detailed analyses are conducted. Finally, we also show that participants are limited in the depth of the contingencies they can learn about, and that these limitations are shared by the Simple Recurrent Network model of Cleeremans & McClelland (1991). (shrink)

In this chapter, I sketch a conceptual framework which takes it as a starting point that conscious and unconscious cognition are rooted in the same set of interacting learning mechanisms and representational systems. On this view, the extent to which a representation is conscious depends in a graded manner on properties such as its stability in time or its strength. Crucially, these properties are accrued as a result of learning, which is in turn viewed as a mandatory process that always (...) accompanies information processing. From this perspective, consciousness is best characterized as involving (1) a graded continuum defined over “quality of representation”, such that availability to consciousness and to cognitive control correlates with quality , and (2) the implication of systems of metarepresentations. A first implication of these ideas is that the main function of consciousness is to make flexible, adaptive control over behavior possible. A second, much more speculative implication, is that we learn to be conscious. This I call the “radical plasticity thesis” — the hypothesis that consciousness emerges in systems capable not only of learning about their environment, but also about their own internal representations of it. (shrink)

referred to as implicit learning (Reber, 1989). Implicit learning contrasts with explicit learning (exhibited for.

Over the past decade, sequence learning has gradually become a central paradigm through which to study implicit learning. In this chapter, we start by briefly summarizing the results obtained with different variants of the sequence learning paradigm. We distinguish three subparadigms in terms of whether the stimulus material is generated either by following a fixed and repeating sequence (e.g., Nissen & Bullemer, 1987), by relying on a complex set of rules from which one can produce several alternative deterministic sequences (e.g., (...) Lewicki, Hill & Bizot, 1988; Stadler, 1989), or by following the output of a probabilistic set of rules such as instantiated by noisy finite-state grammars (Cleeremans & McClelland, 1991; Jiménez, Mendéz & Cleeremans, 1996). Next, we focus on the processes involved in sequence representation and acquisition. We suggest that the sensitivity to the sequential structure observed in the probabilistic subparadigm can only be a result of the acquisition of a representation of the statistical constraints of the material, and that this sensitivity emerges through the operation of mechanisms that are well instantiated by connectionist models such as the Simple Recurrent Network (Elman, 1990; Cleeremans, 1993b). We present new simulation work meant to explore to what extent the model can also account for specific data obtained in a paradigmatic instance of deterministic, rule-based sequence learning task: Lewicki et al. (1988)'s situation. Finally, we report on the results of an experiment that compares learning on otherwise similar deterministic and probabilistic structures, and we show that learning of both types of structures is equivalent only under conditions that maximally hinder explicit acquisition. Taken together, these simulation and experimental data lend support to the claim that implicit learning in all three sequence learning subparadigms can amount to a form of statistical sequence learning. They also suggest that distinguishing among several theories of sequence representation and acquisition may require us to analize the data in great detail. Hopefully, however, some truth can be found in such details.. (shrink)

Time plays a central role in consciousness, at different levels and in different aspects of information processing. Subliminal perception experiments demonstrate that stimuli presented too briefly to enter conscious awareness are nevertheless processed to some extent. Implicit learning, implicit memory, and conditioning studies suggest that the extent to which memory traces are available for verbal report and for cognitive control is likewise dependent on the time available for processing during acquisition. Differences in the time available for processing also determine not (...) only the extent to which one becomes conscious of action, but also provides the basis for making attributions of authorship to experienced acts. In this paper, we offer a brief overview of these different findings and suggest that they can all be understood based on the fact that consciousness takes time. From this perspective, the availability of representations to conscious awareness depends on the quality of these representations — the extent to which they are strong, stable in time, and distinctive. High-quality representations occur when processes of global competition have had sufficient time to operate so as to make the system settle into the best possible interpretation of the input. Such processes implement global constraint satisfaction and critically depend on reentrant processing, through which representations can be further enriched by high-level constraints. We discuss these ideas in light of current theories of consciousness, emphasizing the fact that consciousness should be viewed as a process rather than as a static property associated with some states and not with others. (shrink)

We have previously shown that several brain areas are activated both during sequence learning at wake and during subsequent rapid-eye-movements (REM) sleep (Nat. Neurosci. 3 (2000) 831– 836), suggesting that REM sleep participates in the reprocessing of recent memory traces in humans. However, the nature of the reprocessed information remains open. Here, we show that regional cerebral reactivation during posttraining REM sleep is not merely related to the acquisition of basic visuomotor skills during prior practice of the serial reaction time (...) task, but rather to the implicit acquisition of the probabilistic rules that defined stimulus sequences. Moreover, functional connections between the reactivated cuneus and the striatum—the latter being critical for implicit sequence learning—are reinforced during REM sleep after practice on a probabilistic rather than on a random sequence of stimuli. Our results therefore support the hypothesis that REM sleep is deeply involved in the reprocessing and optimization of the high-order information contained in the material to be learned. In addition, we show that the level of acquisition of probabilistic rules attained prior to sleep is correlated to the increase in regional cerebral blood flow during subsequent REM sleep. This suggests that posttraining cerebral reactivation is modulated by the strength of the memory traces developed during the learning episode. Our data provide the first experimental evidence for a link between behavioral performance and cerebral reactivation during REM sleep. © 2003 Elsevier Inc. All rights reserved. (shrink)

59 words Main Text: 1108 words References: 114 words Total Text: 1281 words.

Change blindness—our inability to detect changes in a stimulus—occurs even when the change takes place gradually, without any disruption [Simons, D. J., Franconeri, S. L., & Reimer, R. L. . Change blindness in the absence of a visual disruption. Perception, 29, 1143–1154]. Such gradual changes are more difficult to detect than changes that involve a disruption. Using this method, David et al. [David, E., Laloyaux, C., Devue, C., & Cleeremans, A. . Change blindness to gradual changes in facial expressions. (...) Psychologica Belgica] recently showed substantial blindness to changes that involve facial expressions of emotion. In this experiment, we show that people who failed to detect any change in the displays were nevertheless influenced by the changing information in subsequent recognition decisions about which facial expression they had seen, and that their confidence in their decisions was lower after exposure to changing vs. static displays. The findings therefore support the notion that undetected changes that occur in highly salient stimuli may be causally efficacious and influence subsequent behavior. Implications concerning the nature of the representations associated with undetected changes are discussed. (shrink)

Through the use of double task conditions, the sequence learning (SL) paradigm offers unique opportunities to study the relationships between learning and attention. In their original study, Nissen & Bullemer (1987) argued that a secondary tone-counting task prevents SL because it exhausts participants’ attentional resources. Other authors have instead suggested that the detrimental effects of tone-counting are due to scheduling conflicts between performing the main and secondary tasks rather than to attentional load. Frensch & Miner (1994), for instance, suggested that (...) the secondary task impairs sequence learning because it lengthens the response-to-stimulus interval (RSI) and hence makes it less likely for relevant contingencies to be represented together in short-term memory, — a condition for learning. Stadler (1995), on the other hand, argued that the secondary task introduces variability in the RSI and disrupts the organization of the sequence into chunks. Further, according to Willingham, Greenberg & Cannon Thomas (1997) manipulation of the RSI influences performance but not sequence learning.. (shrink)

According to Unconscious Thought Theory (Dijksterhuis & Nordgren, 2006), complex decisions are best made after a period of distraction assumed to elicit “unconscious thought”. Here, we suggest instead that the superiority of decisions made after distraction results from the fact that conscious deliberation can deteriorate impressions formed online during information acquisition. We found that participants instructed to form an impression made better decisions after distraction than after deliberation, thereby replicating earlier findings. However, decisions made immediately were just as good as (...) decisions made after distraction, which suggests (1) that people had already made their decision during information acquisition, (2) that deliberation-without-attention does not occur during distraction, and (3) that ruminating about one's first impression can deteriorate decision quality. Strikingly, in another condition that should have favored unconscious thought even more, deliberated decisions were better than immediate or distracted decisions. These findings were replicated in a field study. (shrink)

While the study of implicit learning is nothing new, the field as a whole has come to embody — over the last decade or so — ongoing questioning about three of the most fundamental debates in the cognitive sciences: The nature of consciousness, the nature of mental representation (in particular the difficult issue of abstraction), and the role of experience in shaping the cognitive system. Our main goal in this chapter is to offer a framework that attempts to integrate current (...) thinking about these three issues in a way that specifically links consciousness with adaptation and learning. Our assumptions about this relationship are rooted in further assumptions about the nature of processing and of representation in cognitive systems. When considered together, we believe that these assumptions offer a new perspective on the relationships between conscious and unconscious processing and on the function of consciousness in cognitive systems. (shrink)

❚ EN DEUX MOTS ❚ Elles ont des noms impro- remettent en cause la vision unifiée du monde insu. À l’extrême, nos intentions d’agir seraient la nonçables – hémianopsie, akinétopsie... Elles se que nous offre notre conscience. Du reste, plu- conséquence de nos actions ! Mais attention : manifestent par des symptômes étonnants – voir sieurs expériences suggèrent que cette dernière pas question, pour autant, de considérer que pro- bien qu’étant aveugle, percevoir le monde sous serait fragmentée, et que de (...) nombreux aspects cessus conscients et inconscients relèvent de forme d’images fixes... Autant de pathologies qui du traitement de l’information se feraient à son deux systèmes distincts. (shrink)

The goal of computational cognitive neuroscience is to understand how the brain embodies the mind by using biologically based computational models comprised of networks of neuronlike units. This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the field. The neural units in the simulations use equations based directly on the ion channels that govern the behavior of real neurons and the neural networks (...) incorporate anatomical and physiological properties of the neocortex. Thus the text provides the student with knowledge of the basic biology of the brain as well as the computational skills needed to simulate large-scale cognitive phenomena. (shrink)

Over the past decade, many findings in cognitive about the contents of consciousness: we will not address neuroscience have resulted in the view that selective what might be called the ‘enabling factors’ for conscious- attention, working memory and cognitive control ness (e.g. appropriate neuromodulation from the brain- stem, etc.). involve competition between widely distributed rep-.

Research on consciousness is currently enjoying a spectacular revival of interest in the cognitive sciences. From an empirical point of view, the NCC program — the search for the “Neural Correlates of Consciousness” — holds the promise of establishing correlations between physiological and phenomenal states in a way that directly resembles G. T. Fechner´s (1860) so-called “inner psychophysics”. Should the NCC program be entirely successful, we would thus be able to predict phenomenal states based on physiological states. we would be (...) able to predict phenomenal states based on physiological states. In this paper, we explore some of the conceptual and methodological difficulties of this approach. In both neurobiology and psychology, there are serious measurement problems that stand in the way of correlation research, even after the “hard problem” has been set aside. Thus, even if one had identified certain internal functional states as indicators of phenomenal states, the empirical psychologist would still be confronted with fundamental problems, such as determining the absence or presence of these functional states. In this respect, philosophy of science may help and provide a metatheoretical framework for the current interdisciplinary project. (shrink)

68 words Main Text: 1256 words References: 192 words Total Text: 1516 words.

Challenges conventional wisdom and presents the most up-to-date studies to define, quantify and test the predictions of the main models of implicit learning.

Change blindness—our inability to detect changes in a stimulus—occurs even when the change takes place gradually, without disruption (Simons et al., 2000). Such gradual changes are more difficult to detect than changes that involve a disruption. In this experiment, we extend previous findings to the domain of facial expressions of emotions occurring in the context of a realistic scene. Even with changes occurring in central, highly relevant stimuli such as faces, gradual changes still produced high levels of change blindness: Detection (...) rates were three times lower for gradual changes than for displays involving disruption, with only 15% of the observers perceiving the gradual change within a single trial. However, despite this high rate of change blindness, changes on faces were significantly better detected than color changes occurring on non facial objects in the same scene. (shrink)

Axel Cleeremans Research Associate of the National Fund for Scientific Research (Belgium) Laboratoire de Psychologie Industrielle et Commerciale Université Libre de Bruxelles CP 122 Avenue F.-D. Roosevelt, 50 1050 Bruxelles..

In this paper we explore the extent to which implicit learning is subtended by somatic markers, as evidenced by skin conductance measures. On each trial subjects were asked to decide which ‘word’ from a pair of ‘words’ was the ‘correct’ word. Unknown to subjects, each ‘word’ of a pair was constructed using a different set of rules (grammar ‘A’ and grammar ‘B’). A (monetary) reward was given if the subject choose the ‘word’ from grammar ‘A’. Choosing the grammar ‘B’ word (...) resulted in (monetary) punishment. Skin conductance was measured during each of 100 trials. After each set of 10 trials subjects were asked how they selected the ‘correct word’. Task performance increased long before the subjects could even formulate a single relevant rule. In this ‘pre-conceptual’ phase of the experiment, skin conductance was larger before incorrect than before correct choices. Thus it was shown that artificial grammar learning is accompagnied by a somatic marker, possibly ‘warning’ the subject for the incorrect decision. (shrink)

The constructivist notion that features are purely functional is incompatible with the classical computational metaphor of mind. I suggest that the discontent expressed by Schyns, Goldstone and Thibaut about fixed-features theories of categorization reflects the growing impact of connectionism, and show how their perspective is similar to recent research on implicit learning, consciousness, and development. A hard problem remains, however: How to bridge the gap between subsymbolic and symbolic cognition.

Consider Susan Hurley's depiction of mainstream views of the mind: "The mind is a kind of sandwich, and cognition is the filling" (p. 401). This particular sandwich (with perception as the bottom loaf and action as the top loaf) tastes foul to Hurley, who devotes most of "Consciousness in Action" to a systematic and sometimes extraordinarily detailed critique of what has otherwise been dubbed "classical" models of the mind. This critique then provides the basis for her alternative proposal, in which (...) perception, action and environment are deeply intertwined. (shrink)

Characterizing the relationships between conscious and unconscious processes is one of the most important and long-standing goals of cognitive psychology. Renewed interest in the nature of consciousness — long considered not to be scientifically explorable —, as well as the increasingly widespread availability of functional brain imaging techniques, now offer the possibility of detailed exploration of the neural, behavioral, and computational correlates of conscious and unconscious cognition. This entry reviews some of the relevant experimental work, highlights the methodological challenges involved (...) in establishing the extent to which cognition can occur unconsciously, and situates ongoing debates in the theoretical context provided by current thinking about consciousness. (shrink)