Psychology Department, University of New South Wales, Kensington.
Psychol Rev. 2013 Oct;120(4):873-902. doi: 10.1037/a0034247. Epub 2013 Sep 9.
Much recent research has aimed to establish whether visual working memory (WM) is better characterized by a limited number of discrete all-or-none slots or by a continuous sharing of memory resources. To date, however, researchers have not considered the response-time (RT) predictions of discrete-slots versus shared-resources models. To complement the past research in this field, we formalize a family of mixed-state, discrete-slots models for explaining choice and RTs in tasks of visual WM change detection. In the tasks under investigation, a small set of visual items is presented, followed by a test item in 1 of the studied positions for which a change judgment must be made. According to the models, if the studied item in that position is retained in 1 of the discrete slots, then a memory-based evidence-accumulation process determines the choice and the RT; if the studied item in that position is missing, then a guessing-based accumulation process operates. Observed RT distributions are therefore theorized to arise as probabilistic mixtures of the memory-based and guessing distributions. We formalize an analogous set of continuous shared-resources models. The model classes are tested on individual subjects with both qualitative contrasts and quantitative fits to RT-distribution data. The discrete-slots models provide much better qualitative and quantitative accounts of the RT and choice data than do the shared-resources models, although there is some evidence for "slots plus resources" when memory set size is very small.
最近的许多研究旨在确定视觉工作记忆 (WM) 是否更适合用有限数量的离散全有或全无插槽来描述,或者是否更适合用连续共享的记忆资源来描述。然而,到目前为止,研究人员还没有考虑离散插槽与共享资源模型的反应时间 (RT) 预测。为了补充该领域过去的研究,我们形式化了一组混合状态的离散插槽模型,用于解释视觉 WM 变化检测任务中的选择和 RT。在研究的任务中,首先呈现一小部分视觉项目,然后在研究的位置之一呈现一个测试项目,必须对该位置的变化进行判断。根据模型,如果在该位置保留了离散插槽之一中的研究项目,则基于记忆的证据积累过程决定选择和 RT;如果在该位置的研究项目丢失,则基于猜测的积累过程起作用。因此,观察到的 RT 分布被理论化为基于记忆和猜测分布的概率混合。我们形式化了一组类似的连续共享资源模型。使用定性对比和对 RT 分布数据的定量拟合,对个体受试者的模型类进行了测试。离散插槽模型比共享资源模型提供了更好的定性和定量解释,尽管当记忆集非常小时,有一些证据表明存在“插槽加资源”。