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The formation of specific and gist associative episodic memory representations during encoding: Effects of rate of presentation.

主旨 心理学 编码(内存) 结合属性 认知心理学 情景记忆 跟踪(心理语言学) 任务(项目管理) 计算机科学 认知 数学 神经科学 病理 纯数学 管理 经济 哲学 医学 语言学 间质细胞
作者
Nathaniel R. Greene,Moshe Naveh-Benjamin
出处
期刊:Journal of Experimental Psychology: Learning, Memory and Cognition [American Psychological Association]
卷期号:49 (7): 1099-1118 被引量:3
标识
DOI:10.1037/xlm0001173
摘要

Assessing the time course under which underlying memory representations can be formed is an important question for understanding memory. Several studies assessing item memory have shown that gist representations of items are laid out more rapidly than verbatim representations. However, for associations among items/components, which form the core of episodic memory, it is unclear whether gist representations form more quickly than, or at least in parallel with, verbatim representations, as fuzzy-trace theory predicts, or whether gist is extracted more slowly from inferring the meaning of verbatim representations, as in gist macroprocessor theories. To test these contrasting possibilities, we used a novel associative recognition task in which participants studied face-scene pairs for .75, 1.5, or 4 seconds each, and were later tested on their ability to discriminate intact pairs from foils which varied in how similar they were to originally studied pairs. Across 2 experiments, we found that verbatim memory for associations, measured using a multinomial-processing-tree model, improved from .75 to 1.5 to 4 seconds of presentation time. Paralleling these effects of encoding time on verbatim memory, for gist memory, there were improvements from .75 seconds to 1.5 seconds in both experiment 1 and 2, while improvements from 1.5 seconds to 4 seconds were only evident when the retention interval between study and test was increased (experiment 2). These results provide strong support for the parallel processing framework of fuzzy-trace theory over the slow gist extraction framework of an alternative gist macroprocessor theory. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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