Learning and Memory: A Comprehensive Reference is the most authoritative set of volumes ever produced on learning and memory and represents the state of the science in the early 21st century. The study of learning (the process of acquiring new information) and memory (retention of that information for future use) has intrigued philosophers and writers for centuries because our memories and plans for the future consolidate who we are, and disruption of these processes dramatically interferes with our daily lives. The fascination with learning and memory is not limited to the humanities, but has been the subject of intense scientific research. Psychologists are concerned with elucidating the features of learning and memory processes and systems, neurobiologists seek to determine the neuronal mechanisms of learning and memory, and neurologists and psychiatrists focus on research and treatment of failures or disruptions in learning and memory.

Explicit and Implicit Memory.
Explicit memory refers to cases of conscious recollection. When we remember our trip to Paris or recognize that some words occurred in a recent list, these arc instances of explicit memory. In eases of explicit retention, people respond to a direct request for information about their past, and such tests arc called explicit memory tests. On the other hand, on tests of implicit memory, people arc asked to perform some task, and the measure of interest is how some prior experience affects the task. For example, take the simple ease of the word elephant appearing in a long list of words. If subjects are given a recognition test in which they arc instructed to identify words studied in the list (and to reject nonstudied words), then their choice of elephant as a studied word would represent an instance of explicit retention. However, if a different group of subjects were given the same set of words to study and then were given a word stem completion test (with instructions to say the first word that comes to mind to the word stem ele), then this would constitute a test of implicit memory.
The relevant measure on this test is priming, the greater probability of completing the stem with elephant rather than other plausible words (element, elegant, electricity, etc.) when the word has been studied than when it has not been studied. For example, the probability of producing elephant to the word stem might be 10% if the word had not been studied in the list and 40% when it had been studied, which would constitute a 30% priming effect One reason for believing that these two measures represent different forms of memory is that they can be dissociated by many experimental (and subject) variables.
Contents.
Contributors to Volume 1.
Contents List of All Volumes.
Foreword.
Preface.
Learning Theory and Behaviour.
1.01 Introduction and Overview R. Menzel, Freie Universitat Berlin, Berlin, Germany.
1.02 A Typology of Mentory Terms H. L. Roediger, III, F. M. Zaromb, and M. K. Goode, Washington University in St. Louis, St. Louis, MO, USA.
1.03 History of Behavioral Learning Theories E. J. Capaldi and A. Martins, Purdue University, West Lafayette, IN, USA.
1.04 Multiple Memory Systems: A New View L. Nadel, University of Arizona, Tuscan, AZ, USA.
1.05 Retrieval from Mentory G. P. Urcelay and R. R. Miller, State University of New York at Binghamton, Binghamton, NY, USA.
1.06 Operant Behavior J. Jozefowiez and J. E. R. Staddon, Duke University, Durham, NC, USA.
1.07 Perceptual Learning G. Hall, University of York, York, UK.
1.08 Discrimination and Generalization E. J. Kehoe, University of New South Wales, Sydney, NSW, Australia.
1.09 Extinction: Behavioral Mechanisms and Their Implications M. E. Bouton and A. M. Woods, University of Vermont, Burlington, VT, USA.
1.10 Cognitive Dimension of Operant Learning A. P. Blaisdell, University of California at Los Angeles, Los Angeles, CA, USA.
1.11 Categories and Concepts in Animals O. F. Lazareva and E. A. Wasserman, University of Iowa, Iowa City, IA, USA.
1.12 Learning and Representation C. R. Gallistel, Rutgers University, Piscataway, NJ, USA.
1.13 Attention and Memory in Mammals and Primates P. Dalton, Royal Holloway University of London, Egbam, Surrey, UK C. Spence, University of Oxford, Oxford, UK.
1.14 Amnesia: Point and Counterpoint E. A. Kensinger, Boston College, Chestnut Hill, MA, USA S. Corkin, Massachusetts Institute of Technology, Cambridge, MA, USA, and Massachusetts General Hospital, Boston, MA, USA.
1.15 The Nature of Infantile Amnesia M. L. Howe, Lancaster University, Lancaster, UK.
1.16 Transmission of Acquired Information in Nonhuman Primates J. Fischer, German Primate Center, Gottingen, Germany.
1.17 Bird Song Learning P. Marler, University of California at Davis, Davis, CA, USA.
1.18 Adaptive Specializations and Generality of the Laws of Classical and Instrumental Conditioning M. Domjan, University of Texas at Austin, Austin, TX, USA.
1.19 Learning to Time Intervals K. Cheng, Macquarie University, Sydney, NSW, Australia J. D. Crystal, University of Georgia, Athens, Georgia, USA.
1.20 Foraging D. W. Stephens and A. S. Dunlap, University of Minnesota, St. Paul, MN, USA.
1.21 Navigation and Episodic-Like Memory in Mammals N. Fortin, Boston University, Boston, MA, USA.
1.22 Memory in Food Caching Animals A. C. Kamil, University of Nebraska-Lincoln, Lincoln, NE, USA K. L. Gould, Luther College, Decor ah, I A, USA.
1.23 What Do Animals Remember about Their Past? L. H. Salwiczek, A. Dickinson, and N. S. Clayton, Cambridge University, Cambridge, UK.
1.24 Reconsolidation: Historical Perspective and Theoretical Aspects S. J. Sara, College de France, Paris, France.
1.25 Learning and Memory in Communication and Navigation in Insects R. J. De Marco and R. Menzel, Freie Universitat Berlin, Berlin, Germany.
1.26 Spatial Learning in Fish C. Salas, C. Broglio, E. Duran, A. Gomez, and F. Rodriguez, Universidad de Sevilla, Sevilla, Spain.
1.27 Reconsolidation in Invertebrates D. Eisenhardt and N. Stollhoff, Freie Universitat Berlin, Berlin, Germany.
1.28 Behavioral Analysis of Learning and Memory in Drosophila M. Heisenberg and B. Gerber, Universitat Wurzburg Wurzburg Germany.
1.29 Behavioral and Neural Analysis of Associate Learning in the Honeybee M. Giurfa, CNRS, Universite Paul Sabatier, Toulouse, France.
1.30 Behavioral and Circuit Analysis of Learning and Memory in Mollusks P. R. Benjamin and G. Kemenes, University of Sussex, East Sussex, UK.
1.31 Behavioral Analysis of Learning and Memory in Cephalopods L. Borrelli and G. Fiorito, Stazione Zoologica A. Dohrn, Naples, Italy.
1.32 Behavioral Analysis of Learning and Memory in C. elegans A. C. Giles and С. H. Rankin, University of British Columbia, Vancouver, BC, Canada.
1.33 Computational Models of Hippocampal Functions E. T. Rolls, University of Oxford, Oxford, UK.
1.34 Neural Computation Theories of Learning S. B. Moldakarimov, Salk Institute for Biological Studies, La folia, CA, USA T. J. Sejnowski, Salk Institute for Biological Studies and University of California at San Diego, La folia, CA, USA.
1.35 Connectionist Memory Models of Hippocampal Function R. A. Koene and M. E. Hasselmo, Boston University, Boston, ALA, USA.
1.36 Theory of Reward Systems S. B. Ostlund, N. E. Winterbauer and B. W. Balleine, University of California, Los Angeles, CA, USA.
1.37 Synchronous Oscillations and Memory Formation W. Singer, Max Planck Institute for Brain Research, Frankfurt am Main, Germany.
1.38 The Neuronal Workspace Model: Conscious Processing and Learning J.-P. Changeux, URACNRS 2182, College de France and Institut Pasteur, Paris, France S. Dehaene, College de France, Paris, France; and INSERM-CEA Cognitive Neuroimaging Unit, Neurospin Center, Gif-sur-Yvette, France.
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