title: Long-term semantic priming: a computational account and empirical evidence.
abstract: Semantic priming is traditionally viewed as an effect that rapidly decays. A new view of long-term word priming in attractor neural networks is proposed. The model predicts long-term semantic priming under certain conditions. That is, the task must engage semantic-level processing to a sufficient degree. The predictions were confirmed in computer simulations and in 3 experiments. Experiment 1 showed that when target words are each preceded by multiple semantically related primes, there is long-lag priming on a semantic-decision task but not on a lexical-decision task. Experiment 2 replicated the long-term semantic priming effect for semantic decisions with only one prime per target. Experiment 3 demonstrated semantic priming with much longer word lists at lags of 0, 4, and 8 items. These are the first experiments to demonstrate a semantic priming effect spanning many intervening items and lasting much longer than a few seconds.
authors.affiliation: Department of Psychology, McMaster University, Hamilton, Ontario, Canada. becker@mcmaster.ca
authors.forename: S
authors.initials: S
authors.lastname: Becker
authors.forename: M
authors.initials: M
authors.lastname: Moscovitch
authors.forename: M
authors.initials: M
authors.lastname: Behrmann
authors.forename: S
authors.initials: S
authors.lastname: Joordens
mesh_terms: D000328:Adult; D001288:Attention; D003657:Decision Making; D005260:Female; D006801:Humans; D008297:Male; D016571:Neural Networks, Computer; D010153:Paired-Associate Learning; D011930:Reaction Time; D012153:Retention, Psychology; D012660:Semantics