Journal
PSYCHOLOGICAL REVIEW
Volume 114, Issue 2, Pages 273-315Publisher
AMER PSYCHOLOGICAL ASSOC
DOI: 10.1037/0033-295X.114.2.273
Keywords
reading; naming; word recognition; dual-route cascaded model; connectionist models
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At least 3 different types of computational model have been shown to account for various facets of both normal and impaired single word reading: (a) the connectionist triangle model, (b) the dual-route cascaded model, and (c) the connectionist dual process model. Major strengths and weaknesses of these models are identified. In the spirit of nested incremental modeling, a new connectionist dual process model (the CDP+ model) is presented. This model builds on the strengths of 2 of the previous models while eliminating their weaknesses. Contrary to the dual-route cascaded model, CDP+ is able to learn and produce graded consistency effects. Contrary to the triangle and the connectionist dual process models, CDP+ accounts for serial effects and has more accurate nonword reading performance. CDP+ also beats all previous models by an order of magnitude when predicting individual item-level variance on large databases. Thus, the authors show that building on existing theories by combining the best features of previous models-a nested modeling strategy that is commonly used in other areas of science but often neglected in psychology-results in better and more powerful computational models.
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