Institute of Psychology and Sports Science, University of Münster, Münster, Germany.
Otto Creutzfeld Center for Cognitive and Behavioral NeuroscienceUniversity of Münster, Münster, Germany.
Mem Cognit. 2021 Jul;49(5):998-1018. doi: 10.3758/s13421-020-01105-6. Epub 2020 Nov 23.
Many photographs of real-life scenes are very consistently remembered or forgotten by most people, making these images intrinsically memorable or forgettable. Although machine vision algorithms can predict a given image's memorability very well, nothing is known about the subjective quality of these memories: are memorable images recognized based on strong feelings of familiarity or on recollection of episodic details? We tested people's recognition memory for memorable and forgettable scenes selected from image memorability databases, which contain memorability scores for each image, based on large-scale recognition memory experiments. Specifically, we tested the effect of intrinsic memorability on recollection and familiarity using cognitive computational models based on receiver operating characteristics (ROCs; Experiment 1 and 2) and on remember/know (R/K) judgments (Experiment 2). The ROC data of Experiment 2 indicated that image memorability boosted memory strength, but did not find a specific effect on recollection or familiarity. By contrast, ROC data from Experiment 2, which was designed to facilitate encoding and, in turn, recollection, found evidence for a specific effect of image memorability on recollection. Moreover, R/K judgments showed that, on average, memorability boosts recollection rather than familiarity. However, we also found a large degree of variability in these judgments across individual images: some images actually achieved high recognition rates by exclusively boosting familiarity rather than recollection. Together, these results show that current machine vision algorithms that can predict an image's intrinsic memorability in terms of hit rates fall short of describing the subjective quality of human memories.
许多现实场景的照片都被大多数人非常一致地记住或遗忘,这使得这些图像具有内在的可记忆性或可遗忘性。尽管机器视觉算法可以很好地预测给定图像的可记忆性,但对于这些记忆的主观质量却一无所知:可记忆的图像是基于强烈的熟悉感还是基于对情节细节的回忆来识别的?我们测试了人们对从图像可记忆性数据库中选择的可记忆和易忘场景的识别记忆,这些数据库包含每个图像的可记忆性得分,这是基于大规模的识别记忆实验。具体来说,我们使用基于接收者操作特征(ROC)的认知计算模型(实验 1 和 2)和记住/知道(R/K)判断(实验 2)来测试内在可记忆性对回忆和熟悉度的影响。实验 2 的 ROC 数据表明,图像可记忆性增强了记忆强度,但没有发现对回忆或熟悉度的特定影响。相比之下,实验 2 的 ROC 数据旨在促进编码,从而促进回忆,发现图像可记忆性对回忆有特定影响的证据。此外,R/K 判断表明,平均而言,可记忆性增强了回忆,而不是熟悉度。然而,我们也发现这些判断在个体图像之间存在很大的可变性:一些图像实际上通过仅增强熟悉度而不是回忆来实现高识别率。总之,这些结果表明,当前能够根据命中率预测图像内在可记忆性的机器视觉算法,无法描述人类记忆的主观质量。