Attention and Implicit Learning

Editor
| University of Santiago de Compostella, Spain
HardboundAvailable
ISBN 9789027251756 (Eur) | EUR 110.00
ISBN 9781588113351 (USA) | USD 165.00
PaperbackAvailable
ISBN 9789027251763 (Eur) | EUR 72.00
ISBN 9781588113368 (USA) | USD 108.00
e-Book
ISBN 9789027296405 | EUR 110.00/72.00*
| USD 165.00/108.00*
 
Attention and Implicit Learning provides a comprehensive overview of the research conducted in this area. The book is conceived as a multidisciplinary forum of discussion on the question of whether implicit learning may be depicted as a process that runs independently of attention. The volume also deals with the complementary question of whether implicit learning affects the dynamics of attention, and it addresses these questions from perspectives that range from functional to neuroscientific and computational approaches. The view of implicit learning that arises from these pages is not that of a mysterious faculty, but rather that of an elementary ability of the cognitive systems to extract the structure of their environment as it appears directly through experience, and regardless of any intention to do so. Implicit learning, thus, is taken to be a process that may shape not only our behavior, but also our representations of the world, our attentional functions, and even our conscious experience. (Series B)
[Advances in Consciousness Research, 48]  2003.  x, 385 pp.
Publishing status: Available
Table of Contents
Acknowledgement
vii
Contributors
ix–x
Introduction: Attention to implicit learning
Luis Jiménez
1–7
Part 1. The cognitive debate
9
Attention and awareness in “implicit” sequence learning
David R. Shanks
11–42
Intention, attention, and consciousness in probabilistic sequence learning
Luis Jiménez
43–68
Part 2. Neuroscientific and computational approaches
69
Neural structures that support implicit sequence learning
Eliot Hazeltine and Richard B. Ivry
71–107
The cognitive neuroscience of implicit category learning
F. Gregory Ashby and Michael B. Casale
109–141
Structure and function in sequence learning: Evidence from experimental, neuropsychological and simulation studies
Peter Ford Dominey
143–180
Temporal effects in sequence learning
Arnaud Destrebecqz and Axel Cleeremans
181–213
Implicit and explicit learning in a unified architecture of cognition
Dieter Wallach and Christian Lebiere
215–250
Part 3. Reciprocal influences: Implicit learning, attention, and beyond
251
Visual orienting, learning and conscious awareness
Tony Lambert
253–275
Contextual cueing: Reciprocal influences between attention and implicit learning
Yuhong Jiang and Marvin M. Chun
277–296
Attention and implicit memory
Neil W. Mulligan and Alan S. Brown
297–334
The route from implicit learning to verbal expression of what has been learned: Verbal report of incidentally experienced environmental regularity
Peter A. Frensch, Hilde Haider, Dennis Rünger, Uwe Neugebauer, Sabine Voigt and Jana Werg
335–366
Author index
367–377
Subject index
379–383
“In summary, Attention and Implicit Learning discusses a broad array of implicit learning tasks and methodologies, including behavioral experiments, computational models, and neuroimaging and neuropsychological studies. It is a worthwhile contribution that emphasizes theories of implicit learning over theories of attention.”
Subjects

Consciousness Research

Consciousness research
BIC Subject: JMT – States of consciousness
BISAC Subject: PSY008000 – PSYCHOLOGY / Cognitive Psychology & Cognition
U.S. Library of Congress Control Number:  2002034215
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Beck, Melissa R., S. Lee Hong, Amanda E. van Lamsweerde, Justin M. Ericson & Suliann Ben Hamed
2014. The Effects of Incidentally Learned Temporal and Spatial Predictability on Response Times and Visual Fixations during Target Detection and Discrimination. PLoS ONE 9:4  pp. e94539 ff. https://doi.org/10.1371/journal.pone.0094539
Colas, Jaron T. & Joy Lu
2017. Learning Where to Look for High Value Improves Decision Making Asymmetrically. Frontiers in Psychology 8 https://doi.org/10.3389/fpsyg.2017.02000
de Oliveira, Rita F., Markus Raab, Mathias Hegele & Jörg Schorer
2017. Task Integration Facilitates Multitasking. Frontiers in Psychology 8 https://doi.org/10.3389/fpsyg.2017.00398
Dienes, Zoltán
2007.  In Models of Brain and Mind - Physical, Computational and Psychological Approaches [Progress in Brain Research, 168],  pp. 49 ff. https://doi.org/10.1016/S0079-6123(07)68005-4
Foti, F., F. De Crescenzo, G. Vivanti, D. Menghini & S. Vicari
2015. Implicit learning in individuals with autism spectrum disorders: a meta-analysis. Psychological Medicine 45:05  pp. 897 ff. https://doi.org/10.1017/S0033291714001950
Kuppuraj, Sengottuvel, Prema Rao & Dorothy VM Bishop
2016. Declarative capacity does not trade-off with procedural capacity in children with specific language impairment. Autism & Developmental Language Impairments 1  pp. 239694151667441 ff. https://doi.org/10.1177/2396941516674416
Miyawaki, Kaori
2006. The influence of the response–stimulus interval on implicit and explicit learning of stimulus sequence. Psychological Research Psychologische Forschung 70:4  pp. 262 ff. https://doi.org/10.1007/s00426-005-0216-y
Rausei, Valeria, Tal Makovski & Yuhong V. Jiang
2007. Attention Dependency in Implicit Learning of Repeated Search Context. Quarterly Journal of Experimental Psychology 60:10  pp. 1321 ff. https://doi.org/10.1080/17470210701515744
Ziori, Eleni & Zoltán Dienes
2008. How does Prior Knowledge Affect Implicit and Explicit Concept Learning?. Quarterly Journal of Experimental Psychology 61:4  pp. 601 ff. https://doi.org/10.1080/17470210701255374
Ziori, Eleni & Emmanuel Pothos
2015.  In Implicit and Explicit Learning of Languages [Studies in Bilingualism, 48],  pp. 247 ff. https://doi.org/10.1075/sibil.48.11zio

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