Suppr超能文献

视觉短期记忆中特征精度和项目负荷的可分离效应。

The separable effects of feature precision and item load in visual short-term memory.

作者信息

Lilburn Simon D, Smith Philip L, Sewell David K

机构信息

Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Australia.

School of Psychology, The University of Queensland, St Lucia, Australia.

出版信息

J Vis. 2019 Jan 2;19(1):2. doi: 10.1167/19.1.2.

Abstract

Visual short-term memory (VSTM) has been described as being limited by the number of discrete visual objects, the aggregate quantity of information across multiple visual objects, or some combination of the two. Many recent studies examining these capacity limitations have shown that increasing the number of items in VSTM increases the frequency and magnitude of errors in a participant's recall of the stimulus. This increase in response dispersion has been interpreted as a loss of precision in an item's representation as the number of items in memory increases, possibly due to a change in the tuning of the underlying representation. However, increased response dispersion can also be caused by a reduction in the total memory strength available for decision making as a consequence of a reduction in the total amount of a fixed resource representing a stimulus. We investigated the effects of load on the precision of memory representations in a fine orientation discrimination task. Accuracy was well captured by extending a simple sample-size model of VSTM, using a tuning function to account for the effect of orientation precision on performance. The best model of the data was one in which the item strength decreased progressively with memory load at all stimulus exposure durations but in which tuning bandwidth was invariant. Our results imply that memory strength and feature precision are experimentally dissociable attributes of VSTM.

摘要

视觉短期记忆(VSTM)被认为受到离散视觉对象数量、多个视觉对象的信息总量或两者某种组合的限制。最近许多研究这些容量限制的研究表明,增加VSTM中的项目数量会增加参与者对刺激回忆的错误频率和幅度。随着记忆中项目数量的增加,这种反应分散性的增加被解释为项目表征精度的丧失,这可能是由于底层表征的调谐变化所致。然而,反应分散性的增加也可能是由于代表刺激的固定资源总量减少导致可用于决策的总记忆强度降低所致。我们在精细方向辨别任务中研究了负载对记忆表征精度的影响。通过扩展一个简单的VSTM样本大小模型,并使用一个调谐函数来解释方向精度对性能的影响,能够很好地捕捉到准确性。数据的最佳模型是这样一种模型:在所有刺激暴露持续时间下,项目强度随记忆负载逐渐降低,但调谐带宽不变。我们的结果表明,记忆强度和特征精度是VSTM在实验中可分离的属性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验