This volume provides an overview of a relatively neglected branch of connectionism known as localist connectionism. The singling out of localist connectionism is motivated by the fact that some critical modeling strategies have been more readily applied in the development and testing of localist as opposed to distributed connectionist models (models using distributed hidden-unit representations and trained with a particular learning algorithm, typically back-propagation). One major theme emerging from this book is that localist connectionism currently provides an interesting means of evolving from verbal-boxological models of human cognition to computer-implemented algorithmic models. The other central messages conveyed are that the highly delicate issue of model testing, evaluation, and selection must be taken seriously, and that model-builders of the localist connectionist family have already shown exemplary steps in this direction.
Table of Contents
Contents: Preface. J. Grainger, A.M. Jacobs, On Localist Connectionism and Psychological Science. G. Houghton, S.P. Tipper, A Model of Selective Attention as a Mechanism of Cognitive Control. A.M. Burton, A Model of Human Face Recognition. U.H. Frauenfelder, G. Peeters, Simulating the Time Course of Spoken Word Recognition: An Analysis of Lexical Competition in TRACE. A.M. Jacobs, A. Rey, J.C. Ziegler, J. Grainger, MROM-p: An Interactive Activation, Multiple Readout Model of Orthographic and Phonological Processes in Visual Word Recognition. T. Dijkstra, W.J.B. van Heuven, The BIA Model and Bilingual Word Recognition. M. Page, D. Norris, Modeling Immediate Serial Recall With a Localist Implementation of the Primacy Model. U. Schade, H-J. Eikmeyer, Modeling the Production of Object Specifications. R.L. Goldstone, Hanging Together: A Connectionist Model of Similarity. I.J. Myung, M.A. Pitt, Issues in Selecting Mathematical Models of Cognition.
"..the book contains many excellent papers."
—Journal of Mathematical Psychology
"The editors have done a commendable job of laying out a general approach to psychological theory building and testing. Importantly, they have also done much to show how connectionist modeling can be linked to information processing approaches in psychological science."