A Parallel Grains Model for Simple Reaction Time
A race-like model is developed to account for various phenomena arising in simple reaction time (RT) tasks. Within the model, each stimulus is represented by a number of grains of information or activation processed in parallel. The stimulus is detected when a criterion number of activated grains reaches a decision center. Using the concept of statistical facilitation, the model accounts for many classical effects on mean simple RT, including those of stimulus area, stimulus intensity, stimulus duration, criterion manipulations, redundant stimuli, and the dissociation between intensity effects on simple RTs and temporal order judgments. The model is also consistent with distributional properties of simple RTs.