Behavioral and Brain Sciences

Volume 29 : Issue 1

Table of Contents

• Prcis of Principles of Brain Evolution 
  Georg F. Striedter
  Page 1
• Brain evolution: Part I 
  Elizabeth Adkins-Regan
  Page 12
• Neuroscientists need to be evolutionarily challenged 
  Robert A. Barton
  Page 13
• Practical use of evolutionary neuroscience principles 
  Barbara Clancy
  Page 14
• Putting humans in their proper place 
  R. I. M. Dunbar
  Page 15
• Scaling patterns of interhemispheric connectivity in eutherian mammals 
  Emmanuel Gilissen
  Page 16
• The evolution of computation in brain circuitry 
  Richard Granger
  Page 17
• Principles of brain connectivity organization 
  Claus C. Hilgetag
  Page 18
• Mental attention, not language, may explain evolutionary growth of human intelligence and brain size 
  Juan Pascual-Leone
  Page 19
• Velocity and direction in neurobehavioral evolution: The centripetal prospective 
  Robert R. Provine
  Page 21
• The key role of prefrontal cortex structure and function 
  Antonino Raffone and Gary L. Brase
  Page 22
• An evolutionary niche for quantitative theoretical analyses? 
  Yasser Roudi and Alessandro Treves
  Page 23
• Brain design: The evolution of brains 
  James E. Swain
  Page 24
• Evolutionary neuroscience: Limitations and prospects 
  Georg F. Striedter
  Page 25
• Neural blackboard architectures of combinatorial structures in cognition 
  Frank van der Velde and Marc de Kamps
  Page 37
• Conscious cognition and blackboard architectures 
  Bernard J. Baars
  Page 70
• On the structural ambiguity in natural language that the neural architecture cannot deal with 
  Rens Bod, Hartmut Fitz and Willem Zuidema
  Page 71
• How neural is the neural blackboard architecture? 
  Yoonsuck Choe
  Page 72
• How anchors allow reusing categories in neural composition of sentences 
  William J. Clancey
  Page 73
• The problem with using associations to carry binding information 
  Leonidas A. A. Doumas, Keith J. Holyoak and John E. Hummel
  Page 74
• Has the brain evolved to answer binding questions or to generate likely hypotheses about complex and continuously changing environments? 
  Birgitta Dresp and Jean Charles Barthaud
  Page 75
• Engineering the brain 
  Daniel Durstewitz
  Page 76
• Will the neural blackboard architecture scale up to semantics? 
  Michael G. Dyer
  Page 77
• Vector symbolic architectures are a viable alternative for Jackendoffs challenges 
  Ross W. Gayler
  Page 78
• Distributed neural blackboards could be more attractive 
  Andr Grning and Alessandro Treves
  Page 79
• Neural circuits, matrices, and conjunctive binding 
  Robert F. Hadley
  Page 80
• Blackboards in the brain 
  Ralph-Axel Mller
  Page 81
• On the unproductiveness of language and linguistics 
  David M. W. Powers
  Page 82
• Comparing the neural blackboard and the temporal synchrony-based SHRUTI architectures 
  Lokendra Shastri
  Page 84
• Can neural models of cognition benefit from the advantages of connectionism? 
  Friedrich T. Sommer and Pentti Kanerva
  Page 86
• An alternative model of sentence parsing explains complexity phenomena more comprehensively without problems of localist encoding 
  Carol Whitney
  Page 87
• From neural dynamics to true combinatorial structures 
  Frank van der Velde and Marc de Kamps
  Page 88