Dissociable Perceptual Learning Mechanisms Revealed by Diffusion-Model Analysis

Petrov, A., Van Horn, N., & Ratcliff, R. (2011)
Dissociable perceptual learning mechanisms revealed by diffusion-model analysis. Psychonomic Bulletin & Review, 18 (3), 490-497.
Preprint (pdf) Supplement (pdf) Matlab report (html) Companion paper

Abstract:

Performance on perceptual tasks improves with practice. Most theories address only accuracy data and tacitly assume that perceptual learning is a monolithic phenomenon. The current study pioneers the use of response-time distributions in perceptual learning research. The 27 observers practiced a visual motion-direction discrimination task with filtered-noise textures for 4 sessions with feedback. Session 5 tested whether the learning effects transferred to the orthogonal direction. The diffusion model (Ratcliff, Psychological Review, 85, 59-108, 1978) achieved good fits to the individual response-time distributions from each session and identified two distinct learning mechanisms with markedly different specificities. A stimulus-specific increase in the drift-rate parameter indicates improved sensory input to the decision process. A stimulus-general decrease in the nondecision time variability suggests improved timing of the decision-process onset relative to stimulus onset (which was preceded by a beep). The traditional d' analysis misses the latter effect but the diffusion-model analysis identifies it in the response-time data.

Preprint (pdf) Supplement (pdf) Matlab report (html) Companion paper
Perceptual Learning Project

Matlab Report

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