Baumann Oliver, Vromen Joyce M G, Boddy Adam C, Crawshaw Eloise, Humphreys Michael S
Queensland Brain Institute, University of Queensland, St Lucia, Queensland, 4072, Australia.
School of Psychology and Interdisciplinary Centre for the Artificial Mind (iCAM), Bond University, Robina, Queensland, 4226, Australia.
Mem Cognit. 2018 Nov;46(8):1234-1247. doi: 10.3758/s13421-018-0833-5.
Global matching models have provided an important theoretical framework for recognition memory. Key predictions of this class of models are that (1) increasing the number of occurrences in a study list of some items affects the performance on other items (list-strength effect) and that (2) adding new items results in a deterioration of performance on the other items (list-length effect). Experimental confirmation of these predictions has been difficult, and the results have been inconsistent. A review of the existing literature, however, suggests that robust length and strength effects do occur when sufficiently similar hard-to-label items are used. In an effort to investigate this further, we had participants study lists containing one or more members of visual scene categories (bathrooms, beaches, etc.). Experiments 1 and 2 replicated and extended previous findings showing that the study of additional category members decreased accuracy, providing confirmation of the category-length effect. Experiment 3 showed that repeating some category members decreased the accuracy of nonrepeated members, providing evidence for a category-strength effect. Experiment 4 eliminated a potential challenge to these results. Taken together, these findings provide robust support for global matching models of recognition memory. The overall list lengths, the category sizes, and the number of repetitions used demonstrated that scene categories are well-suited to testing the fundamental assumptions of global matching models. These include (A) interference from memories for similar items and contexts, (B) nondestructive interference, and (C) that conjunctive information is made available through a matching operation.
全局匹配模型为识别记忆提供了一个重要的理论框架。这类模型的关键预测是:(1)增加学习列表中某些项目的出现次数会影响其他项目的表现(列表强度效应);(2)添加新项目会导致其他项目的表现变差(列表长度效应)。对这些预测的实验验证一直很困难,结果也不一致。然而,对现有文献的回顾表明,当使用足够相似的难以标记的项目时,确实会出现稳健的长度和强度效应。为了进一步研究这一点,我们让参与者学习包含视觉场景类别(浴室、海滩等)中一个或多个成员的列表。实验1和实验2重复并扩展了先前的研究结果,即学习额外的类别成员会降低准确性,从而证实了类别长度效应。实验3表明,重复某些类别成员会降低非重复成员的准确性,为类别强度效应提供了证据。实验4消除了对这些结果的一个潜在挑战。综上所述,这些发现为识别记忆的全局匹配模型提供了有力支持。所使用的总体列表长度、类别大小和重复次数表明,场景类别非常适合测试全局匹配模型的基本假设。这些假设包括:(A)来自相似项目和情境记忆的干扰;(B)非破坏性干扰;以及(C)通过匹配操作可获得联合信息。