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从无意义音节到小说的记忆:一项关于记忆保持的调查。

Memory from nonsense syllables to novels: A survey of retention.

作者信息

Radvansky Gabriel A, Parra Dani, Doolen Abigail C

机构信息

Department of Psychology, University of Notre Dame, 390 Corbett Hall, Notre Dame, IN, 46556, USA.

出版信息

Psychon Bull Rev. 2024 Dec;31(6):2437-2464. doi: 10.3758/s13423-024-02514-3. Epub 2024 May 7.

Abstract

Memory has been the subject of scientific study for nearly 150 years. Because a broad range of studies have been done, we can now assess how effective memory is for a range of materials, from simple nonsense syllables to complex materials such as novels. Moreover, we can assess memory effectiveness for a variety of durations, anywhere from a few seconds up to decades later. Our aim here is to assess a range of factors that contribute to the patterns of retention and forgetting under various circumstances. This was done by taking a meta-analytic approach that assesses performance across a broad assortment of studies. Specifically, we assessed memory across 256 papers, involving 916 data sets (e.g., experiments and conditions). The results revealed that exponential-power, logarithmic, and linear functions best captured the widest range of data compared with power and hyperbolic-power functions. Given previous research on this topic, it was surprising that the power function was not the best-fitting function most often. Contrary to what would be expected, a substantial amount of data also revealed either stable memory over time or improvement. These findings can be used to improve our ability to model and predict the amount of information retained in memory. In addition, this analysis of a large set of memory data provides a foundation for expanding behavioral and neuroimaging research to better target areas of study that can inform the effectiveness of memory.

摘要

近150年来,记忆一直是科学研究的主题。由于已经开展了广泛的研究,我们现在可以评估记忆对于一系列材料的有效性,从简单的无意义音节到诸如小说之类的复杂材料。此外,我们可以评估记忆在从几秒钟到几十年后的各种时长下的有效性。我们在此的目的是评估一系列因素,这些因素在各种情况下对记忆保持和遗忘模式有所贡献。这是通过采用一种元分析方法来完成的,该方法评估了广泛各类研究中的表现。具体而言,我们评估了256篇论文中的记忆情况,涉及916个数据集(例如实验和条件)。结果显示,与幂函数和双曲幂函数相比,指数幂函数、对数函数和线性函数最能涵盖最广泛的数据范围。鉴于此前关于该主题的研究,幂函数并非最常拟合的函数这一点令人惊讶。与预期相反,大量数据还显示随着时间推移记忆要么稳定要么有所改善。这些发现可用于提高我们对记忆中保留信息量进行建模和预测的能力。此外,对大量记忆数据的这一分析为扩展行为和神经成像研究提供了基础,以便更好地确定能够为记忆有效性提供信息的研究领域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ab9/11680664/b1453106473b/13423_2024_2514_Fig1_HTML.jpg

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