Simulating Event-Related Potential Reading Data in a Neurally Plausible Parallel Distributed Processing Model

Parallel Distributed Processing (PDP) models have always been considered a particularly likely framework for achieving neural-like simulations of cognitive function. To date, however, minimal contact has been made between PDP models and physiological data from the brain performing cognitive tasks. We present an implemented PDP model of Event-Related Potential (ERP) data on visual word recognition. Simulations demonstrate that a novel architecture with improved neural plausibility is critical for successfully reproducing key findings in the ERP data.

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