Hierarchical Bayesian measurement models for continuous reproduction of visual features from working memory

Journal of vision

Colin Stoneking¹  Dominik Wabersich²  Hsuan-Yu Lin³  Klaus Oberauer³ 

[1] Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA;University of Tübingen, Tübingen, Germany;University of Zurich, Zurich, Switzerland

关键词: memory, short-term;    recovery of function;    reproductive physiological process;    memory;    precision;    visual working memory;   

DOI  :  10.1167/17.5.11

学科分类：眼科学

来源: Association for Research in Vision and Ophthalmology

【 摘 要 】

The article presents Bayesian hierarchical modeling frameworks for two measurement models for visual working memory. The models can be applied to the distributions of responses on a circular feature dimension, as obtained with the continuous reproduction (a.k.a. delayed estimation) task. The first measurement model is a mixture model that describes the response distributions as a mixture of one (Zhang & Luck, 2008) or several (Bays, Catalao, & Husain, 2009) von-Mises distribution(s) and a uniform distribution. The second model is a novel, interference-based measurement model. We present parameter recovery simulations for both models, demonstrating that the hierarchical framework enables precise parameter estimates when a small number of trials are compensated by a large number of subjects. Simulations with the mixture model show that the Bayesian hierarchical framework minimizes the previously observed estimation bias for memory precision in conditions of low performance. Unbiased and reasonably precise parameter estimates can also be obtained from the interference measurement model, though some parameters of this model demand a relatively large amount of data for precise measurement. Both models are applied to two experimental data sets. Experiment 1 measures the effect of memory set size on the model parameters. Experiment 2 provides evidence for the assumption in the interference model that the target feature tends to be confused with features of those nontargets that are close to the target on the dimension used as retrieval cue.

【 授权许可】

CC BY