期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2007
卷号：104
期号：9
页码：3532-3537
DOI：10.1073/pnas.0611288104
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：Physiological studies suggest that decision networks read from the neural representation in the middle temporal area to determine the perceived direction of visual motion, whereas psychophysical studies tend to characterize motion perception in terms of the statistical properties of stimuli. To reconcile these different approaches, we examined whether estimating the central tendency of the physical direction of global motion was a better indicator of perceived direction than algorithms (e.g., maximum likelihood) that read from directionally tuned mechanisms near the end of the motion pathway. The task of human observers was to discriminate the global direction of random dot kinematograms composed of asymmetrical distributions of local directions with distinct measures of central tendency. None of the statistical measures of image direction central tendency provided consistently accurate predictions of perceived global motion direction. However, regardless of the local composition of motion directions, a maximum-likelihood decoder produced global motion estimates commensurate with the psychophysical data. Our results suggest that mechanism-based, read-out algorithms offer a more accurate and robust guide to human motion perception than any stimulus-based, statistical estimate of central tendency.
