Computational models offer tools for exploring the nature of human cognitive processes. In connectionist, neural network, or parallel distributed processing models, information processing takes the form of cooperative and competitive interactions among many simple, neuron-like processing units. These models provide new ways of thinking about the neural basis of cognitive processes, and how disorders of brain function lead to disorders of cognition. This monograph is an expanded version of a recent issue of the journal Cognitive Neuropsychology. It presents the most comprehensive existing "case study" of how the effects of damage in connectionist models can replicate the detailed and diverse patterns of cognitive impairments that can arise in humans as a result of brain damage. It begins with a review of the basic methodology of cognitive neuropsychology and of other attempts at modeling neuropsychological phenomena. It then focuses on a particular form of acquired reading disorder, "deep dyslexia," in which previously literate adults with brain damage exhibit a wide range of symptoms in pronouncing written words, the most striking of which is the production of semantic errors (e.g. reading RIVER as "ocean").
