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失眠个体在错过眼睛的情况下,将愤怒的面孔错误识别为恐惧的面孔:一项眼动追踪研究。

Individuals with insomnia misrecognize angry faces as fearful faces while missing the eyes: an eye-tracking study.

机构信息

Department of Psychology, The University of Hong Kong, Pok Fu Lam, Hong Kong.

Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong.

出版信息

Sleep. 2019 Feb 1;42(2). doi: 10.1093/sleep/zsy220.

Abstract

Individuals with insomnia have been found to have disturbed perception of facial expressions. Through eye movement examinations, here we test the hypothesis that this effect is due to impaired visual attention functions for retrieving diagnostic features in facial expression judgments. Twenty-three individuals with insomnia symptoms and 23 controls without insomnia completed a task to categorize happy, sad, fearful, and angry facial expressions. The participants with insomnia were less accurate in recognizing angry faces and misidentified them as fearful faces more often than the controls. A hidden Markov modeling approach for eye movement data analysis revealed that when viewing facial expressions, more individuals with insomnia adopted a nose-mouth eye movement pattern focusing on the vertical face midline while more controls adopted an eyes-mouth pattern preferentially attending to lateral features, particularly the two eyes. As previous studies found that the primary diagnostic feature for recognizing angry faces is the eyes while the diagnostic features for other facial expressions involve the mouth region, missing the eye region may contribute to specific difficulties in recognizing angry facial expressions, consistent with our behavioral finding in participants with insomnia symptoms. Taken together, the findings suggest that impaired information selection through visual attention control may be related to the compromised emotion perception in individuals with insomnia.

摘要

研究发现,失眠个体对面部表情的感知存在障碍。通过眼动检查,我们在这里测试了这样一种假设,即这种效应是由于在进行面部表情判断时,检索诊断特征的视觉注意力功能受损所致。23 名有失眠症状的个体和 23 名没有失眠的对照者完成了一项任务,即对快乐、悲伤、恐惧和愤怒的面部表情进行分类。有失眠症状的参与者在识别愤怒表情时准确性较低,并且比对照组更频繁地将愤怒表情误认作恐惧表情。眼动数据的隐藏 Markov 建模分析方法显示,在观看面部表情时,更多的失眠个体采用了一种关注垂直面部中线的口鼻眼动模式,而更多的对照组则采用了一种优先关注侧面特征的眼睛-嘴模式,特别是眼睛。正如之前的研究发现,识别愤怒表情的主要诊断特征是眼睛,而其他面部表情的诊断特征则涉及嘴部区域,因此,错过眼部区域可能会导致对愤怒面部表情的识别出现特定困难,这与我们在有失眠症状的参与者中发现的行为结果一致。总之,这些发现表明,通过视觉注意力控制进行的信息选择受损可能与失眠个体的情绪感知受损有关。

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