Attractor Dynamics and Semantic Neighborhood Density: Processing Is Slowed by Near Neighbors and Speeded by Distant Neighbors

摘要

The authors investigated semantic neighborhood density effects on visual word processing to examine the dynamics of activation and competition among semantic representations. Experiment 1 validated feature-based semantic representations as a basis for computing semantic neighborhood density and suggested that near and distant neighbors have opposite effects on word processing. Experiment 2 confirmed these results: Word processing was slower for dense near neighborhoods and faster for dense distant neighborhoods. Analysis of a computational model showed that attractor dynamics can produce this pattern of neighborhood effects. The authors argue for reconsideration of traditional models of neighborhood effects in terms of attractor dynamics, which allow both inhibitory and facilitative effects to emerge.