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Implicit learning

Trends in Cognitive Sciences 2 (10):406-416 (1998)

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  1. A new look at habits and the habit-goal interface.Wendy Wood & David T. Neal - 2007 - Psychological Review 114 (4):843-863.
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  • Mindfulness reduces habitual responding based on implicit knowledge: Evidence from artificial grammar learning.Stephen Whitmarsh, Julia Uddén, Henk Barendregt & Karl Magnus Petersson - 2013 - Consciousness and Cognition 22 (3):833-845.
    Participants were unknowingly exposed to complex regularities in a working memory task. The existence of implicit knowledge was subsequently inferred from a preference for stimuli with similar grammatical regularities. Several affective traits have been shown to influence AGL performance positively, many of which are related to a tendency for automatic responding. We therefore tested whether the mindfulness trait predicted a reduction of grammatically congruent preferences, and used emotional primes to explore the influence of affect. Mindfulness was shown to correlate negatively (...)
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  • Implicit learning: A way to improve visual search in spatial neglect?Murielle Wansard, Marie Geurten, Catherine Colson & Thierry Meulemans - 2016 - Consciousness and Cognition 43:102-112.
  • Testing the implicit processing hypothesis of precognitive dream experience.Milan Valášek, Caroline Watt, Jenny Hutton, Rebecca Neill, Rachel Nuttall & Grace Renwick - 2014 - Consciousness and Cognition 28:113-125.
  • Studying Different Tasks of Implicit Learning across Multiple Test Sessions Conducted on the Web.Werner Sævland & Elisabeth Norman - 2016 - Frontiers in Psychology 7.
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  • The Interaction of the Explicit and the Implicit in Skill Learning: A Dual-Process Approach.Ron Sun - 2005 - Psychological Review 112 (1):159-192.
    This article explicates the interaction between implicit and explicit processes in skill learning, in contrast to the tendency of researchers to study each type in isolation. It highlights various effects of the interaction on learning (including synergy effects). The authors argue for an integrated model of skill learning that takes into account both implicit and explicit processes. Moreover, they argue for a bottom-up approach (first learning implicit knowledge and then explicit knowledge) in the integrated model. A variety of qualitative data (...)
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  • Incubation, insight, and creative problem solving: A unified theory and a connectionist model.Ron Sun - 2010 - Psychological Review 117 (3):994-1024.
    This article proposes a unified framework for understanding creative problem solving, namely, the explicit–implicit interaction theory. This new theory of creative problem solving constitutes an attempt at providing a more unified explanation of relevant phenomena (in part by reinterpreting/integrating various fragmentary existing theories of incubation and insight). The explicit–implicit interaction theory relies mainly on 5 basic principles, namely, (a) the coexistence of and the difference between explicit and implicit knowledge, (b) the simultaneous involvement of implicit and explicit processes in most (...)
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  • Representation and knowledge are not the same thing.Leslie Smith - 1999 - Behavioral and Brain Sciences 22 (5):784-785.
    Two standard epistemological accounts are conflated in Dienes & Perner's account of knowledge, and this conflation requires the rejection of their four conditions of knowledge. Because their four metarepresentations applied to the explicit-implicit distinction are paired with these conditions, it follows by modus tollens that if the latter are inadequate, then so are the former. Quite simply, their account misses the link between true reasoning and knowledge.
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  • Does complexity matter? Meta-analysis of learner performance in artificial grammar tasks.Rachel Schiff & Pesia Katan - 2014 - Frontiers in Psychology 5.
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  • How Transcranial Direct Current Stimulation Can Modulate Implicit Motor Sequence Learning and Consolidation: A Brief Review.Branislav Savic & Beat Meier - 2016 - Frontiers in Human Neuroscience 10.
  • A New Argument for Nonconceptual Content.Adina L. Roskies - 2008 - Philosophy and Phenomenological Research 76 (3):633-659.
    This paper provides a novel argument against conceptualism, the claim that the content of human experience, including perceptual experience, is entirely conceptual. Conceptualism entails that the content of experience is limited by the concepts that we possess and deploy. I present an argument to show that such a view is exceedingly costly—if the nature of our experience is entirely conceptual, then we cannot account for concept learning: all perceptual concepts must be innate. The version of nativism that results is incompatible (...)
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  • Incidental Learning of Melodic Structure of North Indian Music.Martin Rohrmeier & Richard Widdess - 2017 - Cognitive Science 41 (5):1299-1327.
    Musical knowledge is largely implicit. It is acquired without awareness of its complex rules, through interaction with a large number of samples during musical enculturation. Whereas several studies explored implicit learning of mostly abstract and less ecologically valid features of Western music, very little work has been done with respect to ecologically valid stimuli as well as non-Western music. The present study investigated implicit learning of modal melodic features in North Indian classical music in a realistic and ecologically valid way. (...)
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  • The reinterpretation of dreams: An evolutionary hypothesis of the function of dreaming.Antti Revonsuo - 2000 - Behavioral and Brain Sciences 23 (6):877-901.
    Several theories claim that dreaming is a random by-product of REM sleep physiology and that it does not serve any natural function. Phenomenal dream content, however, is not as disorganized as such views imply. The form and content of dreams is not random but organized and selective: during dreaming, the brain constructs a complex model of the world in which certain types of elements, when compared to waking life, are underrepresented whereas others are over represented. Furthermore, dream content is consistently (...)
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  • Context influences conscious appraisal of cross situational statistical learning.Timothy J. Poepsel & Daniel J. Weiss - 2014 - Frontiers in Psychology 5.
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  • Learning and Memory Processes Following Cochlear Implantation: The Missing Piece of the Puzzle.David B. Pisoni, William G. Kronenberger, Suyog H. Chandramouli & Christopher M. Conway - 2016 - Frontiers in Psychology 7.
  • Implicit learning and statistical learning: One phenomenon, two approaches.Pierre Perruchet & Sebastien Pacton - 2006 - Trends in Cognitive Sciences 10 (5):233-238.
  • Learning non-local dependencies.Gustav Kuhn & Zoltán Dienes - 2008 - Cognition 106 (1):184-206.
  • Neuropsychological dissociations between priming and recognition: A single-system connectionist account.Annette Kinder & David R. Shanks - 2003 - Psychological Review 110 (4):728-744.
  • On the automaticity of pure perceptual sequence learning.Daphné Coomans, Natacha Deroost, Peter Zeischka & Eric Soetens - 2011 - Consciousness and Cognition 20 (4):1460-1472.
    We investigated the automaticity of implicit sequence learning by varying perceptual load in a pure perceptual sequence learning paradigm. Participants responded to the randomly changing identity of a target, while the irrelevant target location was structured. In Experiment 1, the target was presented under low or high perceptual load during training, whereas testing occurred without load. Unexpectedly, no sequence learning was observed. In Experiment 2, perceptual load was introduced during the test phase to determine whether load is required to express (...)
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  • Connecting Conscious and Unconscious Processing.Axel Cleeremans - 2014 - Cognitive Science 38 (6):1286-1315.
    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 (...)
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  • Varieties of consciousness.Paolo Bartolomeo & Gianfranco Dalla Barba - 2002 - Behavioral and Brain Sciences 25 (3):331-332.
    In agreement with some of the ideas expressed by Perruchet & Vinter (P&V), we believe that some phenomena hitherto attributed to processing may in fact reflect a fundamental distinction between direct and reflexive forms of consciousness. This dichotomy, developed by the phenomenological tradition, is substantiated by examples coming from experimental psychology and lesion neuropsychology.
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  • Thomas S. kuhn e Michael Polanyi: uno studio sulle "abilità preverbali".Alfio Allò - 2014 - Epistemologia 37 (2):302-323.
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  • Thomas S. kuhn e Michael Polanyi: uno studio sulle "abilità preverbali".Alfio Allò - 2015 - Epistemologia 2:302-323.
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  • Cognitive architectures and multi-agent social simulation.Ron Sun - unknown
    As we know, a cognitive architecture is a domain-generic computational cognitive model that may be used for a broad analysis of cognition and behavior. Cognitive architectures embody theories of cognition in computer algorithms and programs. Social simulation with multi-agent systems can benefit from incorporating cognitive architectures, as they provide a realistic basis for modeling individual agents (as argued in Sun 2001). In this survey, an example cognitive architecture will be given, and its application to social simulation will be sketched.
     
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  • Modeling meta-cognition in a cognitive architecture.Ron Sun, Xi Zhang & Robert Mathews - unknown
    This paper describes how meta-cognitive processes (i.e., the self monitoring and regulating of cognitive processes) may be captured within a cognitive architecture Clarion. Some currently popular cognitive architectures lack sufficiently complex built-in meta-cognitive mechanisms. However, a sufficiently complex meta-cognitive mechanism is important, in that it is an essential part of cognition and without it, human cognition may not function properly. We contend that such a meta-cognitive mechanism should be an integral part of a cognitive architecture. Thus such a mechanism has (...)
     
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  • Computational models of implicit learning.Axel Cleeremans & Zoltán Dienes - 2008 - In Ron Sun (ed.), The Cambridge Handbook of Computational Psychology. Cambridge University Press. pp. 396--421.
  • Consciousness and sensation: Philosophical aspects.David Rosenthal - 2001 - In N. J. Smelser & B. Baltes (eds.), International Encyclopedia of the Social and Behavioral Sciences. Pergamon/Elsevier.
    consciousness. Such unconscious processing always " Cambridge, UK " tends to re?ect habitual or strong responses. From this.
     
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  • Implicit Learning and Consciousness: A Graded, Dynamic Perspective.Axel Cleeremans & Luis Jimenez - 2002 - In Robert M. French & Axel Cleeremans (eds.), Implicit Learning and Consciousness: An Empirical. Psychology Press.
    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 (...)
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  • Correlating consciousness: A view from empirical science.Axel Cleeremans & John-Dylan Haynes - 1999 - Revue Internationale de Philosophie 53 (209):387-420.
     
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  • An integrative pluralistic approach to phenomenal consciousness.Rick Dale, Deborah P. Tollefsen & Christopher T. Kello - 2012 - In Shimon Edelman, Tomer Fekete & Neta Zach (eds.), Being in Time: Dynamical Models of Phenomenal Experience. John Benjamins. pp. 88--231.
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  • The importance of cognitive architectures: An analysis based on CLARION.Ron Sun - unknown
    Research in computational cognitive modeling investigates the nature of cognition through developing process-based understanding by specifying computational models of mechanisms (including representations) and processes. In this enterprise, a cognitive architecture is a domaingeneric computational cognitive model that may be used for a broad, multiple-level, multipledomain analysis of behavior. It embodies generic descriptions of cognition in computer algorithms and programs. Developing cognitive architectures is a difficult but important task. In this article, discussions of issues and challenges in developing cognitive architectures will (...)
     
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  • Differential contributions of global, local and background contexts in contextual-guided visual search.Xuelian Zang - unknown
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