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在编码过程中瞳孔放大,但听觉刺激的类型并不能预测面孔记忆的识别成功。

Pupil dilation during encoding, but not type of auditory stimulation, predicts recognition success in face memory.

机构信息

School of Population Health, Discipline of Psychology, Curtin University, Perth, Western Australia, Australia.

School of Psychology and Counselling, Queensland University of Technology, Brisbane, Queensland, Australia.

出版信息

Biol Psychol. 2023 Mar;178:108547. doi: 10.1016/j.biopsycho.2023.108547. Epub 2023 Mar 25.

Abstract

We encounter and process information from multiple sensory modalities in our daily lives, and research suggests that learning can be more efficient when contexts are multisensory. In this study, we were interested in whether face identity recognition memory might be improved in multisensory learning conditions, and to explore associated changes in pupil dilation during encoding and recognition. In two studies participants completed old/new face recognition tasks wherein visual face stimuli were presented in the context of sounds. Faces were learnt alongside no sound, low arousal sounds (Experiment 1), high arousal non-face relevant, or high arousal face relevant (Experiment 2) sounds. We predicted that the presence of sounds during encoding would improve later recognition accuracy, however, the results did not support this with no effect of sound condition on memory. Pupil dilation, however, was found to predict later successful recognition both at encoding and during recognition. While these results do not provide support to the notion that face learning is improved under multisensory conditions relative to unisensory conditions, they do suggest that pupillometry may be a useful tool to further explore face identity learning and recognition.

摘要

在日常生活中,我们会从多种感觉模式中获取和处理信息,研究表明,当学习环境是多感觉的时,学习会更加高效。在这项研究中,我们感兴趣的是,在多感觉学习条件下,面孔身份识别记忆是否可以得到改善,以及探索在编码和识别过程中瞳孔扩张的相关变化。在两项研究中,参与者完成了旧/新面孔识别任务,其中视觉面孔刺激在声音的背景下呈现。在编码过程中同时呈现声音和没有声音、低唤醒声音(实验 1)或高唤醒非面孔相关或高唤醒面孔相关声音(实验 2)。我们预测,在编码过程中出现声音会提高之后的识别准确性,但结果并没有支持这种说法,即声音条件对记忆没有影响。然而,瞳孔扩张在编码和识别过程中都被发现可以预测之后的成功识别。虽然这些结果并没有提供支持,即与单感觉条件相比,面孔学习在多感觉条件下得到改善,但它们确实表明瞳孔测量可能是一个有用的工具,可以进一步探索面孔身份学习和识别。

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