The study of music-evoked autobiographical memories (MEAMs) has grown substantially in recent years. Prior work has used various methods to compare MEAMs to memories evoked by other cues (e.g., images, words). Here, we sought to identify which methods could distinguish between MEAMs and picture-evoked memories. Participants (N = 18) listened to popular music and viewed pictures of famous persons, and described any autobiographical memories evoked by the stimuli. Memories were scored using the Autobiographical Interview (AI; Levine, Svoboda, Hay, Winocur, & Moscovitch, 2002), Linguistic Inquiry and Word Count (LIWC; Pennebaker et al., 2015), and Evaluative Lexicon (EL; Rocklage & Fazio, 2018). We trained three logistic regression models (one for each scoring method) to differentiate between memories evoked by music and faces. Models trained on LIWC and AI data exhibited significantly above chance accuracy when classifying whether a memory was evoked by a face or a song. The EL, which focuses on the affective nature of a text, failed to predict whether memories were evoked by music or faces. This demonstrates that various memory scoring techniques provide complementary information about cued autobiographical memories, and suggests that MEAMs differ from memories evoked by pictures in some aspects (e.g., perceptual and episodic content) but not others (e.g., emotional content).

中文翻译：

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比较分析音乐诱发的自传记忆的方法

近年来，对音乐诱发的自传体记忆 (MEAM) 的研究有了长足的发展。先前的工作使用各种方法将 MEAM 与其他线索（例如，图像、文字）唤起的记忆进行比较。在这里，我们试图确定哪些方法可以区分 MEAM 和图片诱发的记忆。参与者（N = 18）听流行音乐并观看名人的照片，并描述由刺激引起的任何自传记忆。使用自传式访谈 (AI;​​ Levine, Svoboda, Hay, Winocur, & Moscovitch, 2002)、语言查询和字数统计 (LIWC; Pennebaker et al., 2015) 和评估词典 (EL; Rocklage & Fazio, 2018）。我们训练了三个逻辑回归模型（每种评分方法一个）来区分音乐和面部唤起的记忆。在分类记忆是由一张脸还是一首歌唤起时，在 LIWC 和 AI 数据上训练的模型表现出明显高于偶然性的准确性。关注文本情感本质的 EL 无法预测记忆是由音乐还是面孔唤起的。这表明各种记忆评分技术提供了关于线索自传记忆的补充信息，并表明 MEAM 在某些方面（例如，感知和情节内容）与图片唤起的记忆不同（例如，情感内容）。