Long-Term Semantic Priming: A Computational Account and Empirical Evidence

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 …