A Computational Swinging Lexical Network: Cohort Concentration Predicts Semantic Interference in a Large-Scale Picture–Word Interference Dataset
The Swinging Lexical Network (SLN) model explains semantic context effects in word production through the lexical cohort that a target and distractor co-activate: whether naming is facilitated or slowed depends on the balance between semantic priming and lexical competition within this cohort. As a verbal theory the SL...