Please use this identifier to cite or link to this item:
Title: Perceptual learning through optimization of attentional weighting: Human versus optimal Bayesian learner
Authors: Eckstein, M. P.
Abbey, C. K.
Pham, B. T.
Shimozaki, S. S.
First Published: 7-Dec-2004
Citation: Journal of Vision, 2004, 4 (12), pp. 1006-1019
Abstract: Human performance in visual detection, discrimination, identification, and search tasks typically improves with practice. Psychophysical studies suggest that perceptual learning is mediated by an enhancement in the coding of the signal, and physiological studies suggest that it might be related to the plasticity in the weighting or selection of sensory units coding task relevant information (learning through attention optimization). We propose an experimental paradigm (optimal perceptual learning paradigm) to systematically study the dynamics of perceptual learning in humans by allowing comparisons to that of an optimal Bayesian algorithm and a number of suboptimal learning models. We measured improvement in human localization (eight-alternative forced-choice with feedback) performance of a target randomly sampled from four elongated Gaussian targets with different orientations and polarities and kept as a target for a block of four trials. The results suggest that the human perceptual learning can occur within a lapse of four trials (<1 min) but that human learning is slower and incomplete with respect to the optimal algorithm (23.3% reduction in human efficiency from the 1st-to-4th learning trials). The greatest improvement in human performance, occurring from the 1st-to-2nd learning trial, was also present in the optimal observer, and, thus reflects a property inherent to the visual task and not a property particular to the human perceptual learning mechanism. One notable source of human inefficiency is that, unlike the ideal observer, human learning relies more heavily on previous decisions than on the provided feedback, resulting in no human learning on trials following a previous incorrect localization decision. Finally, the proposed theory and paradigm provide a flexible framework for future studies to evaluate the optimality of human learning of other visual cues and/or sensory modalities.
DOI Link: 10.1167/4.12.3
ISSN: 1534-7362
eISSN: 1534-7362
Type: Journal Article
Rights: Copyright © 2004 ARVO
Appears in Collections:Published Articles, School of Psychology

Files in This Item:
There are no files associated with this item.

Items in LRA are protected by copyright, with all rights reserved, unless otherwise indicated.