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重度抑郁症患者对情绪面孔进行分类的积极分类优势

Positive Classification Advantage of Categorizing Emotional Faces in Patients With Major Depressive Disorder.

作者信息

Zhao Lun, Wang Xiaoyu, Sun Gang

机构信息

School of Education Science, Liaocheng University, Liaocheng, China.

The Department of Medical Imaging, The 960th Hospital of Joint Logistics Support Force of PLA, Jinan, China.

出版信息

Front Psychol. 2022 Jul 1;13:734405. doi: 10.3389/fpsyg.2022.734405. eCollection 2022.

DOI:10.3389/fpsyg.2022.734405
PMID:35846609
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9284029/
Abstract

This study investigated whether patients with MDD (major depressive disorder) have deficits in emotional face classification as well as the perceptual mechanism. We found that, compared with the control group, MDD patients exhibited slower speed and lower accuracy in emotional face classification. In normal controls, happy faces were classified faster than sad faces, i.e., positive classification advantage (PCA), which disappeared under the inverted condition. MDD patients showed PCA similar to the control group, although the inversion effects of happy and sad faces were more evident. These data suggest that the dysfunction of categorizing emotional faces in MDD patients could be due to general impairment in decoding facial expressions, reflecting the more common perceptual motion defects in face expression classification.

摘要

本研究调查了重度抑郁症(MDD)患者在情绪面孔分类以及感知机制方面是否存在缺陷。我们发现,与对照组相比,MDD患者在情绪面孔分类中表现出速度较慢和准确性较低的情况。在正常对照组中,快乐面孔的分类速度比悲伤面孔快,即存在正性分类优势(PCA),而在面孔倒置条件下这种优势消失。MDD患者表现出与对照组相似的PCA,尽管快乐和悲伤面孔的倒置效应更为明显。这些数据表明,MDD患者在情绪面孔分类方面的功能障碍可能是由于解码面部表情的一般损伤所致,这反映了面部表情分类中更常见的感知运动缺陷。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e48/9284029/5a7a2a2458d9/fpsyg-13-734405-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e48/9284029/5a7a2a2458d9/fpsyg-13-734405-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e48/9284029/5a7a2a2458d9/fpsyg-13-734405-g0001.jpg

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本文引用的文献

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Biases of Happy Faces in Face Classification Processing of Depression in Chinese Patients.中文患者面部表情分类处理中快乐面孔的偏差对抑郁症的影响。
Neural Plast. 2020 Aug 17;2020:7235734. doi: 10.1155/2020/7235734. eCollection 2020.
2
Categorization of Emotional Faces in Insomnia Disorder.失眠障碍中情绪面孔的分类
Front Neurol. 2020 Jun 19;11:569. doi: 10.3389/fneur.2020.00569. eCollection 2020.
3
Memory bias for emotional facial expressions in major depression.重度抑郁症患者对情绪性面部表情的记忆偏差。
Cogn Emot. 2003 Jan;17(1):101-122. doi: 10.1080/02699930302272.
4
Positive Classification Advantage: Tracing the Time Course Based on Brain Oscillation.阳性分类优势:基于脑振荡追踪时间进程
Front Hum Neurosci. 2018 Jan 11;11:659. doi: 10.3389/fnhum.2017.00659. eCollection 2017.
5
Classification of Emotional Expressions Is Affected by Inversion: Behavioral and Electrophysiological Evidence.情绪表情的分类受倒置影响:行为学和电生理学证据
Front Behav Neurosci. 2017 Feb 9;11:21. doi: 10.3389/fnbeh.2017.00021. eCollection 2017.
6
Non-Conscious Perception of Emotions in Psychiatric Disorders: The Unsolved Puzzle of Psychopathology.精神疾病中情绪的无意识感知:精神病理学的未解之谜。
Psychiatry Investig. 2016 Mar;13(2):165-73. doi: 10.4306/pi.2016.13.2.165. Epub 2016 Mar 23.
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Attention bias modification for major depressive disorder: Effects on attention bias, resting state connectivity, and symptom change.重度抑郁症的注意偏向矫正:对注意偏向、静息态连接性及症状变化的影响
J Abnorm Psychol. 2015 Aug;124(3):463-75. doi: 10.1037/abn0000049.
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Higher levels of depression are associated with reduced global bias in visual processing.抑郁程度越高,与视觉处理的全局偏差减少有关。
Cogn Emot. 2014 Apr;28(3):541-9. doi: 10.1080/02699931.2013.839939. Epub 2013 Sep 25.
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Mapping the time course of the positive classification advantage: an ERP study.正分类优势时间进程的映射:一项 ERP 研究。
Cogn Affect Behav Neurosci. 2013 Sep;13(3):491-500. doi: 10.3758/s13415-013-0158-6.
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Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.使用 G*Power 3.1 进行统计功效分析:相关和回归分析的检验。
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