Brainerd C J, Wang Zheng, Reyna Valerie F, Nakamura K
Department of Human Development, Cornell University.
School of Communication and Center for Cognitive and Brain Sciences, The Ohio State University.
J Mem Lang. 2015 Oct 1;84:224-245. doi: 10.1016/j.jml.2015.06.006.
Fuzzy-trace theory's assumptions about memory representation are cognitive examples of the familiar superposition property of physical quantum systems. When those assumptions are implemented in a formal quantum model (QEMc), they predict that episodic memory will violate the additive law of probability: If memory is tested for a partition of an item's possible episodic states, the individual probabilities of remembering the item as belonging to each state must sum to more than 1. We detected this phenomenon using two standard designs, item false memory and source false memory. The quantum implementation of fuzzy-trace theory also predicts that violations of the additive law will vary in strength as a function of reliance on gist memory. That prediction, too, was confirmed via a series of manipulations (e.g., semantic relatedness, testing delay) that are thought to increase gist reliance. Surprisingly, an analysis of the underlying structure of violations of the additive law revealed that as a general rule, increases in remembering correct episodic states do not produce commensurate reductions in remembering incorrect states.
模糊痕迹理论关于记忆表征的假设是物理量子系统中常见叠加特性的认知示例。当这些假设在形式量子模型(QEMc)中得以实现时,它们预测情景记忆将违反概率加法法则:如果对一个项目可能的情景状态进行划分并测试记忆,记住该项目属于每个状态的个体概率之和必然大于1。我们使用两种标准设计,即项目错误记忆和来源错误记忆,检测到了这一现象。模糊痕迹理论的量子实现还预测,违反加法法则的程度将作为依赖要点记忆的函数而有所不同。这一预测也通过一系列被认为会增加对要点依赖的操作(例如语义关联性、测试延迟)得到了证实。令人惊讶的是,对违反加法法则的潜在结构的分析表明,一般来说,记住正确情景状态的增加并不会相应地减少记住错误状态的情况。