Behavioral and Brain Sciences

Volume 20 : Issue 1

Table of Contents

• What memory is for 
  Arthur M. Glenberg
  Page 1-19
• Functional memory versus reproductive memory 
  Norman H. Anderson
  Page 19-20
• Problematic aspects of embodied memory 
  Aaron S. Benjamin and Robert A. Bjork
  Page 20-20
• Meshing Glenberg with Piaget, Gibson, and the ecological self 
  Richard A. Carlson
  Page 21-21
• Embodiment in language-based memory: Some qualifications 
  Manuel de Vega
  Page 22-23
• Action patterns, conceptualization, and artificial intelligence 
  Stan Franklin
  Page 23-24
• The role of memory in planning and pretense 
  Peter G;auml;rdenfors
  Page 24-25
• Where is the body in the mental model for a story? 
  Arthur C. Graesser
  Page 25-25
• Has Glenberg forgotten his nurse? 
  Arthur M. Jacobs and Johannes C. Ziegler
  Page 26-27
• Embodied representations are part of a grouping of representations 
  Christopher Habel, Barbara Kaup and Stephanie Kelter
  Page 26-26
• The myriad functions and metaphors of memory 
  Asher Koriat and Morris Goldsmith
  Page 27-28
• What working memory is for 
  Robert H. Logie
  Page 28-29
• Memory must also mesh affect 
  Carl F. MacDorman
  Page 29-30
• Is memory caught in the mesh? 
  Colin M. MacLeod
  Page 30-30
• Semantic memory 
  Timothy P. McNamara
  Page 30-31
• Is memory like understanding? 
  Gail Musen
  Page 31-32
• Functional memory: A developmental perspective 
  Katherine Nelson
  Page 32-33
• Against suppression and clamping: A commentary on Glenberg 
  Jason T. Ramsay and Bruce Homer
  Page 33-34
• What memory is for action: The gap between percepts and concepts 
  Yves Rossetti and Emmanuel Procyk
  Page 34-36
• What is modeling for? 
  Terry Regier
  Page 34-34
• Suppression, attention, and effort: A proposed enhancement for a promising theory 
  David A. Schwartz, J. Eric Ivancich and Stephen Kaplan
  Page 36-37
• Conceptualizing a sunset ; using a sunset as a discriminative stimulus 
  Carol Slater
  Page 37-38
• Productivity and propositional construal as the meshing of embodied representations 
  Karen O. Solomon and Lawrence W. Barsalou
  Page 38-39
• Towards a dynamic connectionist model of memory 
  Douglas Vickers and Michael D. Lee
  Page 40-41
• What memory is for: Creating meaning in the service of action 
  Arthur M. Glenberg
  Page 41-50
• Trading spaces: Computation, representation, and the limits of uninformed learning 
  Andy Clark and Chris Thornton
  Page 57-66
• Taming type-2 tigers: A nonmonotonic strategy 
  Istv;aacute;n S. N. Berkeley
  Page 66-67
• Constraining solution space to improve generalization 
  John A. Bullinaria
  Page 67-68
• What is the type-1/type-2 distinction? 
  Nick Chater
  Page 68-69
• Parity is not a generalisation problem 
  R. I. Damper
  Page 69-70
• Epistemological missing links 
  Terry Dartnall
  Page 70-71
• Reducing problem complexity by analogical transfer 
  Peter F. Dominey
  Page 71-72
• Cognitive success and exam preparation 
  Matthew Elton
  Page 72-73
• Model-based learning problem taxonomies 
  Richard M. Golden
  Page 73-74
• Type-2 problems are difficult to learn, but generalize well (in general) 
  M. Gareth Gaskell
  Page 73-73
• Trading spaces: A promissory note to solve relational mapping problems 
  Karl Haberlandt
  Page 74-74
• Recoding can lead to inaccessible structures, but avoids capacity limitations 
  Graeme S. Halford
  Page 75-75
• The dynamics of cumulative knowledge 
  David Leiser
  Page 76-77
• Data coding takes place within a context 
  Daniel Memmi
  Page 77-78
• Extracting higher-level relationships in connectionist models 
  Gary F. Marcus
  Page 77-77
• Of ants and academics: The computational power of external representation 
  Jon Oberlander
  Page 78-79
• Old ideas, new mistakes: All learning is relational 
  Stellan Ohlsson
  Page 79-80
• Neural computation, architecture, and evolution 
  Paul Skokowski
  Page 80-80
• Why computation need not be traded only for internal representation 
  Robert S. Stufflebeam
  Page 80-81
• Prospects for automatic recoding of inputs in connectionist learning 
  Nicolas Szilas and Thomas R. Shultz
  Page 81-82
• Relational problems are not fully solved by a temporal sequence of statistical learning episodes 
  A. Vinter and P. Perruchet
  Page 82-82
• Relational learning re-examined 
  Chris Thornton and Andy Clark
  Page 83-83
• Real self-deception 
  Alfred R. Mele
  Page 91-102
• If belief is a behavior, what controls it? 
  George Ainslie
  Page 103-104
• Self-deception vs. self-caused deception: A comment on Professor Mele 
  Robert Audi
  Page 104-104
• Thinking and believing in self-deception 
  Kent Bach
  Page 105-105
• Deceived by metaphor 
  John A. Barnden
  Page 105-106
• Biased steps toward reasonable conclusions: How self-deception remains hidden 
  Roy F. Baumeister and Karen Pezza Leith
  Page 106-107
• Defending intentionalist accounts of self-deception 
  Jose Luis Bermudez
  Page 107-108
• Varieties of self-deception 
  Robert F. Bornstein
  Page 108-109
• Paradoxical self-deception: Maybe not so paradoxical after all 
  Stephanie L. Brown and Douglas T. Kenrick
  Page 109-110
• Once more with feeling: The role of emotion in self-deception 
  Tim Dalgleish
  Page 110-111
• It may require another person to deceive oneself 
  Jean-Pierre Dupuy
  Page 111-111
• How many beliefs can dance in the head of the self-deceived? 
  Jeffrey E. Foss
  Page 111-112
• Self, awareness of self, and the illusion of control 
  Walter J. Freeman
  Page 112-113
• Is real self-deception really all that biased? 
  James Friedrich
  Page 113-114
• Detecting deception 
  Kenneth J. Gergen
  Page 114-115
• Partial belief as a solution to the logical problem of holding simultaneous, contrary beliefs in self-deception research 
  Keith Gibbins
  Page 115-116
• Self-deceived about self-deception: An evolutionary analysis 
  Mario Heilmann
  Page 116-117
• Intentional self-deception can and does occur 
  Donald R. Gorassini
  Page 116-116
• Real ascriptions of self-deception are fallible moral judgments 
  Edward A. Johnson
  Page 117-118
• Hypnotic responding and self-deception 
  Irving Kirsch
  Page 118-119
• Self-deception and the desire to believe 
  Ariela Lazar
  Page 119-120
• The many faces of self-deception 
  Dennis Krebs and Tim Racine
  Page 119-119
• Self-deceiving intentions 
  Mike W. Martin
  Page 122-123
• Direct, fully intentional self-deception is also real 
  Christian Perring
  Page 123-124
• The uses of self-deception 
  Howard Rachlin and Marvin Frankel
  Page 124-125
• Flavors of self-deception: Ontology and epidemiology 
  Harold A. Sackeim and Ruben C. Gur
  Page 125-126
• Pragmatically pristine, the dialogical cause of self-deception 
  Colin T. Schmidt
  Page 126-126
• Understanding and explaining real self-deception 
  Alfred R. Mele
  Page 127-134
• Does self-deception involve intentional biasing? 
  W. J. Talbott
  Page 127-127
• Individual differences in age preferences in mates: Taking a closer look 
  Dorothy Einon
  Page 137-138
• Differences between men and women in age preferences for a same-sex partner 
  Ray Over and Gabriel Phillips
  Page 138-140
• Age preferences in mates: An even closer look, without the distorting lenses 
  Douglas T. Kenrick and Richard C. Keefe
  Page 140-143
• An example of access-consciousness without phenomenal consciousness? 
  Joseph E. Bogen
  Page 144-144
• Consciousness by the lights of logic and commonsense 
  Selmer Bringsjord
  Page 144-146
• Two conceptions of access-consciousness 
  Derek Browne
  Page 147-147
• Availability: The cognitive basis of experience 
  David J. Chalmers
  Page 148-149
• P-Consciousness presentation/A-Consciousness representation 
  Denise Gamble
  Page 149-150
• Consciousness and mental representation 
  Daniel Gilman
  Page 150-151
• On the relation between phenomenal and representational properties 
  
  Page 151-153
• Perception and content 
  Alva No;euml;
  Page 154-155
• Consciousness versus states of being conscious 
  Ernst P;ouml;ppel
  Page 155-156
• On widening the explanatory gap 
  A. H. C. van der Heijden, P. T. W. Hudson and A. G. Kurvink
  Page 157-158
• Biology versus computation in the study of consciousness 
  Ned Block
  Page 159-165