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Connectionist Modelling in Cognitive Neuropsychology: A Case Study - A Special Issue of Cognitive Neuropsychology (Paperback)
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Connectionist Modelling in Cognitive Neuropsychology: A Case Study - A Special Issue of Cognitive Neuropsychology (Paperback)
Series: Essays in Cognitive Psychology
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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"). A
series of simulations investigate the effects of damage in
connectionist models that pronounce written words via their
meaning. The work systematically explores each main aspect of the
design of the models, identifying the basic computational
properties that are responsible for the occurrence of deep dyslexia
when the models are damaged. Although the investigation concerns a
specific form of reading impairment, the computational principles
that emerge as critical are very general ones: representation of
concepts as distributed patterns of activity, encoding of knowledge
in terms of weights on connections between units, interactivity
between units to form stable attractors for familiar activity
patterns, and greater richness of concrete vs. abstract semantics.
The fact that damage to models embodying these principles and
damage to the brain can produce strikingly similar behaviour
supports the view that the human cognitive system operates
according to similar principles.
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