A DISTRIBUTED-MEMORY MODEL OF SEMANTIC PRIMING

An alternative to semantic network models of lexical knowledge represe ntation and access is described, in which knowledge about a word is re presented as a pattern of activation across a collection of processing units. In this distributed memory model, semantic priming effects ari se naturally from the similarity of the patterns of activation that re present a related prime and target. Priming effects can be reduced by an intervening stimulus that modifies the pattern of activation before the target appears. This process is demonstrated empirically with a w ord naming task. An implemented version of the distributed memory mode l is used to simulate these results, and results from previous researc h in which participants overtly responded to the item that intervened between a prime and target are also simulated. Comparisons with semant ic network and compound cue models of priming are discussed.