心理学报, 2018, 50(10): 1120-1130 doi: 10.3724/SP.J.1041.2018.01120

研究报告

自我积极表情加工优势效应:来自ERPs的证据

谭群1, 尹月阳1,2, 刘燊,1,3, 韩尚锋1, 徐强1, 张林,1

1宁波大学心理学系暨研究所, 宁波 315211

2吉林大学哲学社会学院, 长春 130000

3中国科学技术大学人文与社会科学学院, 合肥 230022

The processing advantage of self-positive expression: Evidence from an ERPs study

TAN Qun1, YIN Yueyang1,2, LIU Shen,1,3, HAN Shangfeng1, XU Qiang1, ZHANG Lin,1

1 Department and Institute of Psychology, Ningbo University, Ningbo 315211, China

2 School of Philosophy and Sociology, Jilin University, Changchun 130000, China

3 School of Humanities and Social Science, University of Science and Technology of China, Hefei 230022, China

通讯作者: 张林, E-mail:zhanglin1@nbu.edu.cn 刘燊, E-mail:liushenpsy@ustc.edu.cn

收稿日期: 2017-09-26   网络出版日期: 2018-10-15

基金资助: * 国家社会科学基金.  12BSH055
国家自然科学基金.  31540024
宁波大学研究生科研创新基金资助.  G18044

Received: 2017-09-26   Online: 2018-10-15

摘要

基于自我加工优势和内隐积极联想理论, 采用视觉搜索范式结合ERPs技术考察个体自我表情加工的特点, 并进一步探讨情绪效价和身份信息对面孔加工的直接影响。结果发现:(1)搜索自我快乐表情比自我愤怒表情及两类他人表情速度更快、正确率也更高; (2)自我快乐表情对N1、N2、LPP成分的激活显著大于自我愤怒表情及两类他人表情。自我表情加工存在积极加工偏向, 且这种加工优势在面孔加工早期视觉编码阶段就已出现。

关键词: 自我表情 ; 他人表情 ; 视觉搜索范式 ; 内隐积极联想理论 ; 自我积极偏见

Abstract

It is well established in a number of studies that there is a cognitive advantage for self-related information, which is called “self-reference effect”. Some researchers have found that the processing of self-related information and the processing of emotional valence information are not only independent, but also interactive. However, these previous studies lacked the investigation of how individuals processed self-related information with different emotional valence. It is difficult to reveal the interaction between self-attribute and emotional valence of stimuli. Moreover, the influence of emotional valence of self-related information on “self-processing advantage” and the cognitive processing of self-expression performs are unclear. So, we used self-expression as stimulus to investigate the processing of self-related information with different emotional valence, and to explore the interaction between self and emotion in the self-face perception process.

In the present study, we adopted the visual search paradigm and the event related potential technology to investigate the processing of self-expression. We designed a 2 (emotion type: happy VS angry) ×2 (identity type: self VS other) within groups design. A total of 25 college students (11 males, 14 females) participated in the experiment, and 6 of the participants were eliminated because of too much artifacts in EEG. We gathered the happy and angry faces of each participant in advance, and selected other people's emotional faces from the Chinese Facial Affective Picture System. All photos were processed in a unified manner, and only the main features of the face were retained. In the visual search task, participants were asked to search the target expression and to ignore other faces in the 6 faces (1 target expression face with 5 neutral faces or 6 neutral faces). When they see the target expression, they should press the "F" as soon as possible; and if all are neutral faces, then press the "J". We record their reaction and corresponding EEG signals.

Behavioral results showed that, (1) the search of self-expression is significantly faster and better than the others, and it is not influenced by the emotional valence; (2) the search of self-happy expression is significantly faster and better than the self-angry expression, that is, the processing advantage of self-positive expression exist. And the results of ERP showed that the N1, N2 and LPP amplitudes of self-happy expressions were greater than those of self-anger and other people’s expressions. The results reflected that the processing advantage of self-positive expression began in visual coding phase of N1 composition, and there is also displayed in expression decoding stage and behavioral decision stage. It showed that the early attention to self-positive expression is faster, and the middle and later period get more attention resources.

Overall, these results consistently showed that, there was a processing advantage effect of self-positive expression. According to implicit positive association theory, the self-expression with different emotional valences might have different meanings to individuals. To be detailed, the self-positive expression was related to positive attribute in self-concept, and it could promote individual cognitive processing of such stimuli. The self-negative expression was related to negative property of self-concept and it might weaken the advantages of self-processing, thereby causing individuals to slow down the processing of such stimuli.

Keywords: self-expression ; other-expression ; visual search paradigm ; implicit positive association theory ; self-positivity bias

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本文引用格式

谭群, 尹月阳, 刘燊, 韩尚锋, 徐强, 张林. (2018). 自我积极表情加工优势效应:来自ERPs的证据 . 心理学报, 50(10), 1120-1130

TAN Qun, YIN Yueyang, LIU Shen, HAN Shangfeng, XU Qiang, ZHANG Lin. (2018). The processing advantage of self-positive expression: Evidence from an ERPs study. Acta Psychologica Sinica, 50(10), 1120-1130

1 引言

自我作为一种特殊的心理建构, 其独特性主要表现为当某一刺激与自我相关时, 会被个体进行更快速的加工, 研究者将这种加工优势称为自我参照效应(self-reference effect; Kim, 2012)。而个体的自我参照加工会受刺激材料情绪效价的影响, 例如个体在自我参照情境下对不同情绪效价的刺激存在积极加工偏向(Hoefler, Athenstaedt, Corcoran, Ebner, & Ischebeck, 2015; 钟毅平, 陈芸, 周路平, 周海波, 2010); 在不同情绪启动条件下, 个体的自我参照加工也会发生变化(周一琳, 胡少军, 蔡佳烨, 胡治国, 刘宏艳, 2016)。特别是, 研究者已经在电生理层面证实了自我相关信息与情绪效价的加工并非独立而是存在相互影响(Watson, Dritschel, Obonsawin, & Jentzsch, 2007; 陈芸, 钟毅平, 周海波, 周路平, 王小艳, 2012; 钟毅平等, 2010)。然而, 以往研究并未直接探讨具有不同情绪效价的自我相关信息加工过程, 而是将自我信息与情绪材料分开操作, 难以揭示自我和情绪效价对个体认知加工的共同作用。本研究以不同效价的自我表情面孔为刺激材料, 考察个体对自我表情的加工特点, 探讨具有不同情绪效价的自我表情加工模式, 以揭示在面孔加工过程中自我信息与情绪效价的作用机制。

个体对自我表情的加工不仅是一种自我参照加工, 更是一种凸显自我与他人区别的特殊的自我面孔加工过程(韩世辉, 张逸凡, 2012)。在自我面孔加工领域, 研究者发现个体对自我面孔的加工存在优势效应, 表现为识别自我面孔快于识别他人面孔(Tong & Nakayama, 1999; Yun et al., 2014; 王凌云, 张明, 隋洁, 2011)。而且个体在知觉自我面孔时能优先得到更多的注意资源, 会激活更大的额中区N2负波以及更大的晚期正成分(Guan, Qi, Zhang, & Yang, 2014; Yun et al., 2014; 钟毅平, 李琎, 占友龙, 范伟, 杨子鹿, 2016)。针对自我面孔加工优势效应, 有研究者提出采用内隐积极联想理论(implicit positive association, IPA)进行解释(Ma & Han, 2010)。根据该理论, 个体进行自我面孔识别的同时会伴随自我意识活动, 更容易激活其自我概念的积极属性, 从而促进个体对自我面孔的加工, 由此导致自我面孔具有加工优势。根据自我面孔的内隐积极联想理论, 自我面孔的加工优势反映了自我面孔对个体积极自我概念的激活, 那么不同情绪效价的自我面孔是否都能激活个体积极的自我概念?对于消极的自我面孔或自我消极表情面孔, 是否还能通过激活其自我概念而表现出加工的优势?这是本研究要探讨的第一个问题。有研究者提出, 自我面孔识别优势是基于积极自我概念的激活而产生, 当自我概念的积极属性受到破坏时, 其自我面孔的识别优势就会被削弱, 并进一步采用自我概念威胁范式证实了这一观点(关丽丽, 张庆林, 齐铭铭, 侯燕, 杨娟, 2012)。也有研究发现, 消极的自我威胁刺激(如自我扭曲面孔)会激活自我概念的消极属性, 进而削弱自我面孔的识别优势(徐欣颖, 高湘萍, 2017)。另外, 以往研究还发现个体对与自我相关的信息加工存在积极偏向, 他们会更倾向于将积极信息与自我相联系, 即自我积极偏向(self-positivity bias; 钟毅平等, 2010)。Verosky和Todorov (2010)发现人们更倾向于将具有积极属性的面孔(如更值得信任的面孔)判断为自己的面孔; Hoefler等人(2015)也发现在自我参照条件下, 人们对积极特质词比消极特质词反应更快。基于内隐积极联想理论和自我积极偏向, 本研究提出假设1:积极的自我表情更容易激活个体积极的自我概念, 从而增强其自我表情的加工优势; 而消极自我表情作为一种自我概念威胁刺激, 会阻碍积极自我概念的激活, 进而削弱自我表情的加工优势。相比于自我消极表情, 个体对自我积极表情的识别反应更快, 即存在自我积极表情的加工优势。

个体对自我表情加工同时涉及面孔的身份信息加工和情绪效价加工两个方面。最初, Bruce和Yong (1986)提出的面孔识别功能模型(functional model for face recognition)将面孔身份信息和情绪信息加工作为两个并行而又独立的加工路径。但近年来, 有研究者对这一观点提出质疑, 认为面孔的身份加工与表情加工之间可能存在相互影响, 尤其是面孔的身份对表情加工的影响较为常见(吴彬星, 张智君, 孙雨生, 2015)。另外, 有一些研究也发现面孔的表情加工也会影响其对面孔身份的加工, 如目击者实验中目标人物的表情会影响目击者身份的识别(Pavel & Iordãnescu, 2012)。但这些研究在考察面孔表情加工与身份加工关系时, 缺乏对“自我”这一特殊身份的深入探讨。以往研究发现, 表情与身份的区分度水平是影响两者交互的重要因素(汪亚珉, 傅小兰, 2007), 而自我面孔的身份区分度明显高于他人面孔(韩世辉, 张逸凡, 2012)。因此, 本研究要探讨的第二个问题是个体进行自我表情加工时, 面孔的身份信息和情绪效价如何影响其加工过程, 即身份信息和情绪效价在面孔的不同加工阶段会如何发生作用?

回顾以往研究可以发现, 在面孔知觉加工过程中, 面孔的身份信息和情绪效价分别在不同的加工阶段产生不同的作用。在早期视觉编码阶段, 面孔表情的加工会受情绪效价的影响。例如, N1成分与情绪信息的注意选择密切相关, 反映了个体对信息最初的感觉编码和注意定向, 而情绪刺激的效价对出现在中央顶区的N1成分(130 ms左右)具有调节作用(Foti, Hajcak, & Dien, 2009)。另外, 还有研究发现不同情绪效价的面孔激活颞枕区N170成分存在显著的差异(Rellecke, Sommer, Schacht, 2012)。而Sui, Zhu和Han等人(2006)则认为, 自我面孔加工优势与早期加工阶段无关, 取决于后期的注意与评价阶段(220~700 ms)。由此可以推测, 在早期视觉编码阶段, 面孔的表情加工主要受情绪效价的影响, 而不受自我身份信息的影响。但在中期阶段, 面孔的加工不仅会受情绪效价的影响, 也会受面孔身份信息的影响, 表现为额中区的N2成分(200~300 ms左右)不仅会受表情效价的影响(Feldmann-Wüstefeld, Schmidt-Daffy, & Schubö, 2011), 同时也与自我面孔的加工高度相关, 反映出个体对刺激的选择性注意(Guan et al., 2014; Yun et al., 2014)。此外, 面孔加工的晚期阶段同样也会受到身份和情绪效价的影响。有研究发现, 自我面孔能比他人面孔的识别诱发出更大的LPP波幅, 反映了个体对自我相关信息的特异性加工(Yun et al., 2014)。LPP是一种晚期正向慢波, 在刺激呈现大约300~400 ms后开始出现, 持续几百毫秒, 并常常能在中央顶叶区域达到最大(侠牧, 李雪榴, 叶春, 李红, 2014)。同时, Calvo和Beltrán (2013)发现相比于消极的表情, 积极表情能诱发更大的LPP, 表明个体会对积极表情进行更加精细的高级认知加工。根据以上分析, 本研究认为个体进行自我表情加工时, 其加工过程会受到自我信息和情绪效价的共同影响, 但在不同的加工阶段二者的作用可能存在差异。基于此, 本研究以N1、N170、N2、LPP成分为指标, 考察具有不同情绪效价的自我和他人表情加工过程, 以及自我信息和情绪效价在面孔加工过程中的作用, 并提出假设2:在早期视觉编码阶段, 面孔表情加工只受情绪效价影响; 在后续加工过程中, 面孔的情绪效价和身份信息则存在交互影响。

在传统的面孔加工研究中, 表情的识别判断任务范式不利于表情刺激自身属性的凸显, 且任务的生态效度较低。而视觉搜索范式要求被试从干扰刺激中搜索出目标刺激, 考察何种表情的面孔刺激更容易在干扰刺激中凸显出来并获得个体的早期注意定向(Tong & Nakayama, 1999)。基于此, 本研究采用视觉搜索范式, 结合具有高时间分辨率特性的ERP技术, 以正确搜索的反应时、正确率以及N1、N170、N2、LPP脑电成分为指标考察个体进行自我表情加工的过程和特点, 探讨个体对自我表情与他人表情的加工过程是否存在差异, 验证面孔识别加工中是否存在自我表情的加工优势, 并进一步探讨不同情绪效价的自我和他人面孔表情加工过程, 以揭示面孔身份信息和情绪效价在面孔加工过程中的影响作用。

2 方法

2.1 被试

招募在校大学生25名参加实验, 其中男生11名, 女生14名; 平均年龄为19.85岁(SD = 1.16)。所有被试视力、听力正常, 均为右利手, 无类似实验经历, 无精神病史和脑部损伤史, 可正常匹配表情图片和情绪标签词, 可熟练操作计算机。所有被试均自愿参加实验, 实验后获得一定报酬。

2.2 实验材料和仪器

自我表情图片参考中国情绪面孔系统(Chinese Facial Affective Picture System, CAFPS) (龚栩, 黄宇霞, 王妍, 罗跃嘉, 2011)的制作方法, 采用同一数码相机(Nikon S8200)在同样的光线条件和拍摄环境下对所有被试进行拍照采集, 分别得到每个被试的快乐表情和愤怒表情图片各一张, 共50张, 均为彩色图片(RGB)。他人表情图片选自中国情绪面孔系统, 其中快乐表情、愤怒表情各6张, 中性表情30张, 男女各半(龚栩 等, 2011)。图片统一采用PhotoShop CS 6软件进行黑白处理, 尺寸为472× 545像素, 位图为24位, 匹配明暗度和对比度。所有面孔材料去除其头发、耳朵等特征, 仅保留面孔内特征(如眼鼻口、脸颊等), 示例材料见图1

图1

图1   自我(左一、左二)和他人(右一、右二)表情示例图


另选不参加本实验的45名大学生(男女各半)对自我表情图片的效价、强度、唤醒度进行9点评分, 并对其认同度进行评定, 本次评定的统计检验效能Power (1-β err prob)为0.9。结果发现, 自我快乐表情的平均效价是6.05 (SD = 0.93)、平均强度是6.44 (SD = 1.09)、平均唤醒度是6.06 (SD = 1.33), 自我愤怒表情的平均效价是3.54 (SD = 0.96)、平均强度是6.37 (SD = 0.99)、平均唤醒度是6.13 (SD = 1.36)。每张自我表情图片的认同度均在80%以上。自我快乐表情与愤怒表情在效价上差异显著(t(44) = 55.16, p < 0.001, d = 2.69), 而在强度(t(44) = 1.58, p = 0.122)和唤醒度(t(44) = -0.90, p = 0.372)上差异不显著。他人快乐表情(5.95 ± 0.46)与愤怒表情(3.62 ± 0.12)在效价上差异显著(t(10) = 11.87, p < 0.001, d = 7.59), 在强度(6.38 ± 0.06, 6.41 ± 0.10; t(10) = -0.76, p = 0.464)和唤醒度(5.86 ± 0.82, 6.07 ± 0.50; t(10) = -0.54, p = 0.598)上差异不显著。自我快乐表情与他人快乐表情在效价(t(29) = 0.94, p = 0.356)、强度(t(29) = 0.93, p = 0.358)和唤醒度(t(29) = 1.32, p = 0.197)上差异均不显著。自我愤怒表情与他人愤怒表情在效价(t(29) = -1.49, p = 0.147)、强度(t(29) = -0.85, p = 0.403)和唤醒度(t(29) = 0.55, p = 0.590)上差异均不显著。另外, 每张自我快乐表情材料的效价、强度、唤醒度均分别与他人快乐表情的效价、强度、唤醒度差异不显著(all ps > 0.05), 每张自我愤怒表情材料也都与他人愤怒表情的效价、强度、唤醒度差异不显著(all ps > 0.05)。自我表情(83.06 ± 3.31)与他人表情(81.48 ± 5.20)的认同度也无显著差异, t(90) = 1.79, p = 0.077。

2.3 实验设计

实验采用2 (表情类型: 快乐表情/愤怒表情)×2 (身份类型: 自我/他人)的被试内设计, 因变量为表情判断的反应时、正确率和ERP数据(N1、N170、N2、LPP各成分的平均波幅或峰值)。

2.4 实验程序

采用E-Prime 2.0软件呈现实验刺激并记录行为数据。采用视觉搜索范式, 向被试呈现一种按照圆形分布的搜索序列, 要求被试快速判断序列中是否存在目标表情刺激。首先在屏幕中央呈现500 ms的注视点“+”, 接着呈现300 ms的空屏, 随后在屏幕的6个位置上呈现6张不同身份的面孔(1张目标表情面孔和5张中性面孔; 或6张中性面孔), 要求被试判断屏幕上是否出现目标表情。若出现了目标表情, 则按“F”键; 若未出现目标表情(即6张都是中性面孔), 则按“J”键。被试按键后随机间隔600~ 800 ms进入下一个trial, 超过3000 ms未反应则自动进入下一个trial (见图2)。计算机屏幕距离被试双眼65 cm, 面孔图片的呈现视角为14.47°×10.55°。

图2

图2   实验程序的单次试验流程图


整个实验共464个trials, 其中包括32个练习trials, 216个填充trials (6张都是中性面孔)以及每种实验条件下的54个trials。正式实验分为两个block, 分别为快乐表情搜索block和愤怒表情搜索block, 呈现顺序在被试间平衡。每张目标表情面孔在六个位置上随机出现, 每张自我表情面孔在每个位置出现6次, 每张他人面孔(同性别)在每个位置出现3次。

2.5 脑电数据记录与分析

使用NeuroScan Synamps2脑电记录与分析系统采集和分析脑电(Electroencephalogram, EEG)数据。按国际10-20系统扩展的64导电极帽记录头皮位置的EEG以及水平眼电(HEOG)和垂直眼电(VEOG)。水平眼电记录电极安置在双眼角外侧10 mm处, 垂直眼电记录电极安置在左眼上下10 mm处。以鼻尖作为参考电极, 前额接地。采样频率为1000 Hz/导, 滤波带通为0.01~100 Hz, 电极与头皮的阻抗维持在5 kΩ以下。

采用NeuroScan 4.3软件对EEG数据进行离线分析(off-line)。行为数据融合以及脑电预览后, 剔除脑电伪迹过多的6名被试, 有效被试19名(8名男生、11名女生)。之后剔除由于眼动或者眨眼引起的眼电伪迹(Gratton, Coles, & Donchin, 1983)。EEG分析时程为1200 ms, 即面孔刺激呈现前200 ms和后1000 ms, 基线为刺激呈现前200 ms。波幅大于± 100 μV者被视为伪迹自动剔除, 然后分别叠加平均每个被试在4种实验条件下正确反应的EEG, 有效叠加次数在45次以上, 超过总trial数的80%。最后对得到的ERP数据采用FIR数字滤波器进行30 Hz (24 dB/octave)的无相移低通数字滤波。

根据本研究目的、以往研究结果以及本研究总平均波形图和地形图的波性特征, 选取需进行考察的ERP成分和电极位置, 最终选取了25个电极点。具体包括:N1 (50~150 ms, 左半球F1/FC1/C1/CP1, 中线Fz/FCz/Cz/CPz, 右半球F2/FC2/C2/CP2)成分的峰值和潜伏期、N170 (120~200 ms, 左半球P7/ PO7/CB1, 右半球P8/PO8/CB2)成分的峰值和潜伏期、N2 (230~330 ms, 左半球F1/FC1/C1/CP1, 中线Fz/FCz/Cz/CPz, 右半球F2/FC2/C2/CP2)成分的峰值和潜伏期以及LPP (400~800 ms, 左半球F1/FC1/ C1/CP1/P1, 中线Fz/FCz/Cz/CPz/Pz, 右半球F2/FC2/ C2/CP2/P2)成分的平均波幅。

将上述选取的各脑电成分的数据分别进行多因素重复测量方差分析, 表情类型(快乐表情/愤怒表情)、身份类型(自我/他人)以及脑区均为被试内变量。所有方差分析的p值均采用Greenhouse-Geisser法进行校正。

3 数据分析与结果

3.1 行为结果

删除错误反应和反应时小于100 ms或大于3000 ms的反应(Tong & Nakayama, 1999), 删除数据占总数据9.47%。各实验条件下被试判断表情的反应时和正确率描述统计结果见表1

表1   各实验条件下表情判断的反应时(ms)和正确率(%) (M ± SD)

身份类型 表情类型 反应时 正确率
自我 快乐 713 ± 218 97 ± 2
愤怒 899 ± 336 97 ± 5
他人 快乐 765 ± 257 94 ± 4
愤怒 1060 ± 377 91 ± 9

新窗口打开| 下载CSV


对于正确率:身份类型的主效应显著, F(1, 24) = 16.48, p < 0.001, η2p = 0.41。搜索自我表情的正确率 (M = 96.94, SD = 3.78)显著大于搜索他人表情的正确率(M = 92.72, SD = 7.19), t(24) = 4.24, p < 0.001, d = 0.75。表情类型的主效应(F(1, 24) = 3.78, p = 0.064)和两者的交互作用(F(1, 24) = 1.81, p = 0.191)均不显著。

对于反应时:身份类型的主效应显著, F(1, 24) = 178.89, p < 0.001, η2p = 0.14。搜索自我表情(M = 805.81, SD = 299.51)显著快于搜索他人表情(M = 912.95, SD = 355.11), t(24) = 10.81, p < 0.001, d = 0.33。表情类型的主效应显著, F(1, 24) = 691.67, p < 0.001, η2p = 0.39。搜索快乐表情的速度(M = 739.09, SD = 240.98)显著快于搜索愤怒表情(M = 979.66, SD = 368.16), t(24) = 28.56, p < 0.001, d = 0.79。两者的交互作用显著, F(1, 24) = 47.10, p < 0.001, η2p = 0.04。进一步简单效应分析发现, 无论是快乐表情(F(1, 24) = 40.63, p < 0.001, η2p = 0.04)还是愤怒表情(F(1, 24) = 140.64, p < 0.001, η2p = 0.12), 自我表情搜索均显著快于他人表情搜索。同时, 无论是对于自我表情(F(1, 24) = 264.42, p < 0.001, η2p = 0.20)还是他人表情(F(1, 24) = 537.28, p < 0.001, η2p = 0.33), 快乐表情的搜索均显著快于愤怒表情的搜索。这表明, 个体在进行面孔表情加工时存在自我表情的优势效应和积极表情的优势效应, 即存在自我积极表情的加工优势效应。

3.2 ERPs结果

搜索4种目标表情刺激在额中区、顶叶、颞枕区等电极各自诱发的脑波形图, 见图3

图3

图3   自我表情加工与他人表情加工的ERP总平均波形图和地形图


3.2.1 N1 (50~150 ms)

对N1的波峰幅值和潜伏期进行2 (表情类型: 快乐, 愤怒)×2 (身份类型: 自我, 他人)×3 (脑区: 左半球F1/FC1/C1/CP1, 中线Fz/FCz/Cz/CPz, 右半球F2/FC2/C2/CP2)的重复测量方差分析。结果表明, 在波幅上, 身份类型的主效应显著, F(1, 18) = 27.44, p < 0.001, η2p = 0.60。自我表情诱发的波幅(-3.14 ± 0.92 μV)显著大于他人表情诱发的波幅(-1.87 ± 1.13 μV), t(18) = 5.24, p < 0.001, d = 1.27。表情类型的主效应显著, F(1, 18) = 44.42, p < 0.001, η2p = 0.71。快乐表情诱发的波幅(-3.20 ± 0.83 μV)显著大于愤怒表情诱发的波幅(-1.83 ± 1.12 μV), t(18) = 6.67, p < 0.001, d = 1.43。身份类型和表情类型的交互作用显著, F(1, 18) = 4.53, p < 0.05, η2p = 0.20。简单效应分析发现, 无论是对于快乐表情还是愤怒表情, 自我表情刺激诱发的N1波幅显著大于他人表情刺激诱发的N1波幅(p < 0.05); 同时, 对于自我表情刺激, 快乐表情诱发的波幅显著大于愤怒表情诱发的波幅(p < 0.001), 但是对于他人表情刺激, 快乐表情诱发的波幅与愤怒表情诱发的波幅差异并不显著(p = 0.108)。其余主效应与交互作用均不显著(all ps > 0.05)。

在潜伏期上, 身份类型和表情类型的交互作用显著, F(1, 18) = 4.39, p < 0.05, η2p = 0.06。简单效应分析发现, 自我快乐表情刺激诱发的N1潜伏期显著短于自我愤怒表情(p < 0.01), 但是他人快乐表情刺激诱发的N1潜伏期与他人愤怒表情差异并不显著(p = 0.893); 并且无论快乐表情还是愤怒表情, 自我与他人表情刺激诱发的N1潜伏期差异均不显著(all ps > 0.05)。其余的主效应与交互作用均不显著(all ps > 0.05)。

3.2.2 N170 (120~200 ms)

对N170的波峰幅值和潜伏期进行2 (表情类型: 快乐, 愤怒)×2 (身份类型: 自我, 他人)×2 (脑区: 左半球P7/PO7/CB1, 右半球P8/PO8/CB2)的重复测量方差分析。结果表明, 在波幅上, 表情类型的主效应显著, F(1, 18) = 10.53, p < 0.01, η2p = 0.16。快乐表情诱发的波幅(-5.21 ± 5.36 μV)显著大于愤怒表情诱发的波幅(-3.68 ± 5.67 μV), t(18) = 3.25, p < 0.01, d = 0.28。其余的主效应与交互作用均不显著(all ps > 0.05)。

在潜伏期上, 表情类型的主效应显著, F(1, 18) = 6.27, p < 0.05, η2p = 0.10。快乐表情诱发的N170潜伏期显著短于愤怒表情。其余的主效应与交互作用均不显著(all ps > 0.05)。

3.2.3 N2 (230~330 ms)

对N2的波峰幅值和潜伏期进行2 (表情类型: 快乐, 愤怒)×2 (身份类型: 自我, 他人)×3 (脑区: 左半球F1/FC1/C1/CP1, 中线Fz/FCz/Cz/CPz, 右半球F2/FC2/C2/CP2)的重复测量方差分析。结果表明, 在波幅上, 身份类型的主效应显著, F(1, 18) = 21.74, p < 0.001, η2p = 0.19)。自我表情诱发的波幅(-6.17 ± 4.61 μV)显著大于他人表情诱发的波幅(-5.41 ± 4.66 μV), t(18) = 4.66, p < 0.001, d = 0.17。表情类型的主效应显著, F(1, 18) = 42.37, p < 0.001, η2p = 0.31。快乐表情诱发的波幅(-6.92 ± 4.27 μV)显著大于愤怒表情诱发的波幅(-4.65 ± 4.74 μV), t(18) = 6.51, p < 0.001, d = 0.52。进一步比较4种表情刺激发现, 自我快乐表情诱发的波幅(-7.33 ± 4.20 μV)显著大于自我愤怒表情(-5.00 ± 4.66 μV)、他人快乐表情(-6.51 ± 4.24 μV)和他人愤怒表情(-4.31 ± 4.76 μV)诱发的波幅(all ps < 0.001)。脑区的主效应显著, F(2, 36) = 34.80, p < 0.001, η2p = 0.18。进一步多重比较发现, 表情刺激在中线脑区诱发的波幅(-6.10 ± 4.73 μV)显著大于在左半球(-5.61 ± 4.50 μV)和右半球(-5.65 ± 4.70 μV)诱发的波幅(all ps < 0.001); 但在左半球和右半球诱发的波幅差异并不显著(p = 0.664)。此外, 身份类型和脑区的交互作用显著, F(2, 36) = 9.70, p < 0.001, η2p = 0.09。进一步的简单效应分析发现, 在所有脑区自我表情诱发的波幅均显著大于他人表情诱发的波幅(all ps < 0.001); 无论自我表情还是他人表情, 表情刺激在中线脑区诱发波幅均显著大于在左半球和右半球诱发的波幅(all ps < 0.001)。其余交互作用均不显著(all ps > 0.05)。

在潜伏期上, 表情类型的主效应显著, F(1, 18) = 25.72, p < 0.001, η2p = 0.26。愤怒表情诱发的N2潜伏期显著短于快乐表情。其余的交互作用均不显著(all ps > 0.05)。

3.2.4 LPP (400~800 ms)

对LPP的平均波幅进行2 (表情类型: 快乐, 愤怒)×2 (身份类型: 自我, 他人)×3 (脑区: 左半球F1/FC1/C1/CP1/P1, 中线Fz/FCz/Cz/CPz/Pz, 右半球F2/FC2/C2/CP2/P2)的重复测量方差分析。结果表明, 身份类型的主效应显著, F(1, 18) = 80.75, p < 0.001, η2p = 0.46。自我表情诱发的波幅(1.38 ± 2.73 μV)显著大于他人表情诱发的波幅(0.49 ± 2.42 μV), t(18) = 8.99, p < 0.001, d = 0.35。表情类型的主效应显著, F(1, 18) = 68.62, p < 0.001, η2p = 0.42。快乐表情诱发的波幅(1.48 ± 2.78 μV)显著大于愤怒表情诱发的波幅(0.39 ± 2.33 μV), t(18) = 8.28, p < 0.001, d = 0.44。身份类型和表情类型的交互作用显著, F(1, 18) = 27.21, p < 0.001, η2p = 0.22。简单效应分析发现, 无论是加工快乐表情还是愤怒表情, 自我表情刺激诱发的波幅均显著大于他人表情刺激诱发的波幅(all ps < 0.001); 同时, 无论对于自我表情还是他人表情刺激, 快乐表情诱发的波幅均显著大于愤怒表情诱发的波幅(p < 0.001)。其余的主效应与交互作用均不显著(all ps > 0.05)。

4 讨论

4.1 自我积极表情的加工优势

本研究采用视觉搜索范式结合ERP技术考察了自我表情的加工特点。行为数据结果表明, 无论是快乐表情还是愤怒表情, 自我表情的搜索都显著快于他人表情, 表现出自我表情的加工优势; 无论是自我表情还是他人表情, 快乐表情的搜索都显著快于愤怒表情, 表现出积极表情的加工优势。在所有表情中, 自我快乐表情的搜索最快、搜索正确率最高, 即在行为指标上表现出自我积极表情具有加工的优势。另外, ERP数据结果发现, 自我积极表情相比于其他的表情能诱发更大的N1、N2、LPP成分, 亦表现出自我积极表情的加工优势。综上, 本研究的结果表明, 个体对具有不同身份信息和不同情绪效价的面孔表情在加工上存在差异, 表现出对自我表情尤其是自我积极表情存在加工优势。这验证了本研究自我积极表情的加工优势效应的假设, 也与以往相关领域的研究结果相一致, 表现出自我相关信息的加工优势和自我的积极加工偏见(Kim, 2012)。另外, 本研究的结果也进一步证实了内隐积极联想理论, 自我积极表情相比于自我消极表情更能激活自我概念的积极属性, 从而提高了个体对自我面孔的认知加工和行为反应, 表现出对自我积极表情的识别优势。对于个体而言, 自我表情加工不仅是了解其自我情绪表征的途径之一, 也包含了自我评价和情绪体验, 而自我积极表情的加工优势既反映了个体对自我信息的积极加工偏好, 也反映了个体对自我相关信息的普遍加工特点(钟毅平等, 2010)。

4.2 自我表情的知觉加工过程

ERP数据结果表明, 自我表情比他人表情诱发更大的N1、N2、LPP成分, 且快乐表情比愤怒表情诱发更大的N1、N2、N170、LPP波幅和更短的N170潜伏期, 自我快乐表情激活的N1、N2、LPP波幅均显著大于自我愤怒表情和他人表情。

早期N1成分反映了对信息最初的感觉编码和注意定向, 与视觉空间注意有关。本研究发现, 相比于其他表情, 自我积极表情能诱发更大的额中区N1成分。以往研究认为自我面孔的加工优势只发生在220~700 ms的注意与评价阶段, 会在额中央区诱发更大的正波, 与早期编码加工无关(Sui et al., 2006)。而本研究将自我信息与面孔情绪效价整合, 在面孔早期编码加工阶段发现了自我积极表情的加工优势。根据IPA理论, 这可能是由于自我积极表情激活了个体的积极自我概念, 从而加速了个体对自我积极信息的注意定向, 而自我身份和积极情绪的结合可能加强了个体对该类刺激的优先认知加工。另外, 本研究发现自我积极表情诱发的N1 潜伏期比自我消极表情更短, 而这种早期的加速定向在他人积极表情中并未发现, 这也反映出个体在加工自我情绪信息时的独特性。另外, 本研究采用的视觉搜索范式要求被试在6张中性面孔中快速搜索出目标表情面孔, 而Sui等人(2006)研究中使用单张面孔不需要搜索定向, 这可能也是本研究与以往研究结果出现差异的另一原因。同时, N170成分作为反映表情结构编码的另一早期成分, 本研究并未发现自我表情与他人表情在颞枕区诱发的N170成分上存在显著差异。有研究者认为面孔识别的早期成分N170是面孔结构编码和特征处理等的混合产物, 不受面孔熟悉性的影响(Gosling, & Eimer, 2011); 无论是内隐还是外显加工, 情绪面孔均能比中性面孔诱发出更大的N170波幅(Rellecke et al., 2012), 但对于何种表情诱发的波幅更大, 目前暂无一致性结论(侠牧等, 2014)。另外, 本研究发现快乐表情比愤怒表情诱发出更大的N170波幅和更短的N170潜伏期, 这可能与识别区域有关, 愤怒表情信息主要来自于眼睛, 而快乐表情的信息主要来自于嘴巴。Calvo和Beltrán (2014)发现快乐表情的嘴巴在刺激呈现后的150 ms就开始突出, 其在150~180 ms的颞枕区诱发更大的脑波, 这表明嘴巴似乎是识别快乐面孔的捷径。总之, 在早期成分上, 只有自我积极表情诱发的N1成分表现出与其他表情的显著差异, 这表明早期阶段的自我积极表情加工优势更多体现为个体对自我积极表情的优先注意定向, 而非表情结构编码上的优势。

在自我面孔加工领域, N2成分被认为与自我面孔加工高度相关(Guan et al., 2014; Yun et al., 2014); 同时它还通常被认为与注意的转换机制相联系, 易受刺激强度和唤醒度的影响(Feldmann- Wüstefeld et al., 2011)。本研究匹配了表情强度和唤醒度, 仍发现自我表情比他人表情激活了更大的N2波幅, 快乐表情比愤怒表情激活了更大的N2波幅, 并且愤怒表情比快乐表情激活更短的N2潜伏期, 这说明自我表情和快乐表情对于个体具有心理突出性, 能够使个体对其投入更多的注意资源。虽然相比于愤怒表情, 快乐表情在该阶段的加工相对滞后, 但更为精细和深入, 占据了更多的注意资源。另外在N2成分上, 本研究未发现面孔身份信息与表情信息的交互作用, 可能是由于在该阶段大脑对这两种信息的加工仍是粗糙的, 只进行了快速区分, 而将两种信息相结合进行更精细的认知加工可能会发生在更晚的阶段(钟毅平等, 2016)。相比于其他表情刺激, 自我快乐表情会诱发更大的N2波幅, 这表明自我积极表情的加工优势在面孔加工的中期阶段依然存在。

在情绪研究中, LPP成分反映了大脑皮层对情绪刺激的的持续注意、意识评价、精细加工等高级加工过程(侠牧等, 2014)。自我研究领域的ERPs研究也发现自我面孔刺激会诱发更大的LPP波幅, 反映了大脑对自我相关信息的特异性加工(Yun et al., 2014)。本研究发现, 自我积极表情相比其他表情诱发更大的LPP。这表明, 自我积极表情占用了个体更多的注意资源, 个体的自我卷入程度更高, 得到了更精细的加工。这不仅证实了个体会对与自我概念相关信息进行快速的精细加工(Kim, 2012), 还进一步支持了IPA理论, 即积极自我概念的激活使得自我积极表情表现出加工的优势效应。

本研究的ERP结果表明, 自我积极表情在面孔表情加工过程中一直处于优势地位, 而且这种优势在早期视觉编码阶段已然存在, 表现为个体对自我积极表情的快速注意定向, 并且相比于其他表情, 自我积极表情更具心理突出性, 能够优先占用更多的注意资源完成后续的精细加工活动。

4.3 总结与展望

总的来说, 本研究采用ERP技术探索自我表情的认知加工过程, 同时结合自我积极偏见提出了自我积极表情优势效应, 这不仅延伸了关于自我面孔加工的研究, 更进一步拓展和完善了自我面孔优势效应理论, 也展现了自我表情加工作为自我加工独特性的重要体现。与以往自我面孔加工的研究结果不同, 本研究发现自我积极表情优势效应开始于面孔加工的早期阶段, 说明个体对自我情绪信息的加工独特性不仅表现在后期的认知评价, 也表现在早期的注意定向。另外, 个体对自我表情与他人表情的加工意义是不同的, 自我表情的加工与自我概念相联系, 反映了个体对自我情绪表征的认知和评价。因此, 本研究对自我表情加工特点的探讨也在一定程度上有助于加深人们对自我认知加工机制的认识与理解。但本研究也存在一些不足之处:首先, 正式实验中自我表情材料的重复次数高于他人表情材料, 虽然补充实验的结果证明了被试的行为反应未受表情材料重复次数的影响, 但仍无直接证据表明表情材料重复次数是否影响相关的ERPs结果; 其次, 在本研究中未对面孔的熟悉度进行控制, 无法完全排除熟悉度对研究结果的干扰。在未来的研究中, 可以加入对重要或熟悉他人表情的探讨, 控制熟悉度以及其他无关因素对实验结果的影响。另外, 本研究使用不同身份的表情刺激, 探讨面孔身份信息和表情信息两者的关系。结果不仅发现相比于他人表情, 自我表情的加工速度更快、正确率更高; 同时还发现, 不同身份的表情受情绪效价的影响, 不同效价的自我表情的加工速度具有显著差异, 自我快乐表情的加工速度显著快于自我愤怒表情, 表现出自我积极表情加工优势效应, 这支持了IPA观点。但自我愤怒表情的加工速度变慢, 是否仅仅由于其对自我概念的积极属性威胁削弱了自我加工优势, 这还需要进一步的探讨。未来的研究可以通过操纵自我概念威胁启动, 以削弱自我概念与积极属性的联结来探讨自我概念威胁情况下自我表情的加工优势是否仍然存在, 以此来进一步探究其内在加工机制(Ma & Han, 2010)。另外, 由于表情识别和身份识别会受面孔物理属性(如高低空间频率、面孔倒置或旋转等)的影响, 未来研究也可以深入探讨自我积极表情加工优势的稳定性问题。

5 结论

本研究得到如下主要结论:

(1)个体对表情的加工存在自我积极表情加工优势, 表现为搜索自我快乐表情比搜索自我愤怒表情和两类他人表情的速度更快、正确率更高。

(2)这种优势开始于早期视觉编码阶段, 在之后的加工阶段也有所表现, 主要表现为自我快乐表情激活的N1、N2、LPP波幅均显著大于自我愤怒表情和两类他人表情。

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Why we respond faster to the self than to others? An implicit positive association theory of self-advantage during implicit face recognition

Journal of Experimental Psychology: Human Perception and Performance, 36( 3), 619-633.

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Pavel F.A., &Iordănescu E . ( 2012).

The influence of facial expressions on recognition performance in facial identity

Procedia-Social and Behavioral Sciences, 33, 548-552.

URL     [本文引用: 1]

The process of encoding the facial information, the interest topic for witness psychology, is accomplished dependently on several factors, like: the context of the event in which the witness it taking part(Megreya & Burton, 2008); the type of the facial expressions that the targeted person displays (D rgembeau & Van der Linden, 2011), the level of the witnesses empathy (Bate, Parris, Haslam, Kay, 2009), etc. The present study analyses the performance of recognition by eyewitnesses of faces, which display different facial expressions. The results show that the binomial happy / anger displayed by the subjects, influence significantly the performance of recognition the targeted person's face.

Rellecke J., Sommer W., & Schacht A . ( 2012).

Does processing of emotional facial expressions depend on intention? Time-resolved evidence from event-related brain potentials

Biological Psychology, 90( 1), 23-32.

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Sui J., Zhu Y., & Han S. H . ( 2006).

Self-face recognition in attended and unattended conditions: An event-related brain potential study

Neuroreport, 17( 4), 423-427.

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Tong F., & Nakayama K . ( 1999).

Robust representations for faces: Evidence from visual search

Journal of Experimental Psychology Human Perception and Performance, 25( 4), 1016-1035.

URL     PMID:10464943      [本文引用: 3]

We report evidence from visual search that people can develop robust representations for highly overlearned faces. When observers searched for their own face versus the face of an unfamiliar observer, search slopes and intercepts revealed consistently faster processing of self than stranger. These processing advantages persisted even after hundreds of presentations of the unfamiliar face and even for atypical profile and upside-down views. Observers not only showed rapid asymptotic recognition of their own face as the target, but could reject their own face more quickly as the distractor. These findings suggest that robust representations for a highly overlearned face may (a) mediate rapid asymptotic visual processing, (b) require extensive experience to develop, (c) contain abstract or view-invariant information, (d) facilitate a variety of processes such as target recognition and distractor rejection, and (e) demand less attentional resources.

Verosky S.C., & Todorov A .( 2010).

Differential neural responses to faces physically similar to the self as a function of their valence

Neuroimage, 49( 2), 1690-1698.

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Wang L. Y., Zhang M., & Sui J . ( 2011).

Self-face advantage benefits from a visual self-reference frame

Acta Psychologica Sinica, 43( 5), 494-499.

[本文引用: 1]

[ 王凌云, 张明, 隋洁 . ( 2011).

自我参照框架决定了自我面孔优势效应的出现

心理学报,43( 5), 494-499.]

[本文引用: 1]

Wang Y.M., &Fu X.L .( 2007).

Effect of discriminability on interference between facial expression and facial identity recognition

Acta Psychologica Sinica, 39( 2), 191-200.

[本文引用: 1]

[ 汪亚珉, 傅小兰 . ( 2007).

区分度在面部表情与面孔身份识别交互中的作用

心理学报, 39( 2), 191-200.]

[本文引用: 1]

Watson L. A., Dritschel B., Obonsawin M. C., & Jentzsch I . ( 2007).

Seeing yourself in a positive light: Brain correlates of the self-positivity bias

Brain Research, 1152, 106-110.

URL     PMID:17462610      [本文引用: 1]

Abstract Individuals are found to have better recall for self-referent information than other types of information. However, attribution research has shown that self-reference is highly correlated with emotional valence. The present study attempted to identify and separate the processing of self-reference and emotional valence using ERPs. Participants performed a two-choice task, judging the self-referential content of positive and negative words. Reaction times revealed an interaction between self-reference and emotional valence. Faster responses occurred after self-positive and non-self negative words as compared to self-negative and non-self-positive words. A similar interaction was identified in ERP waveforms in the time range of the N400 component at fronto-central electrode sites, with larger N400 amplitudes for words outwith the self-positivity bias. Thus, the size of the N400 may indicate the extent to which information is discrepant with the individual's self-concept.

Wu B. X., Zhang Z. J., & Sun Y. S . ( 2015).

Facial Familiarity Modulates the Interaction between Facial Gender and Emotional Expression

Acta Psychologica Sinica,47( 10), 1201-1212.

[本文引用: 1]

[ 吴彬星, 张智君, 孙雨生 . ( 2015).

面孔熟悉度对面孔性别与表情相互作用的调节

心理学报,47( 10), 1201-1212.]

[本文引用: 1]

Xia M., Li X. L., Ye C., & Li H . ( 2014).

The ERPs for the facial expression processing

Advances in Psychological Science, 22( 10), 1556-1563.

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[ 侠牧, 李雪榴, 叶春, 李红 . ( 2014).

面部表情加工的ERP成分

心理科学进展, 22( 10), 1556-1563.]

[本文引用: 3]

Xu X.Y., &Gao X.P . ( 2017).

Self-threat Stimuli Capture Attention: Evidence from Inhibition of Return

Journal of Psychological Science, 40( 2), 296-302.

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[ 徐欣颖, 高湘萍 . ( 2017).

自我威胁刺激对返回抑制的影响

心理科学, 40( 2), 296-302.]

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Yun J. Y., Hur J. W., Jung W. H., Jang J. H., Youn T., Kang D.-H., … Kwon J. S . ( 2014).

Dysfunctional role of parietal lobe during self-face recognition in schizophrenia

Schizophrenia Research, 152( 1), 81-88.

URL     PMID:23916187      [本文引用: 6]

These findings support a conceptual model that posits a causal relationship between disrupted self–other discrimination and attenuated effective connectivity among the right supramarginal gyrus, cuneus, and prefronto-temporal brain areas involved in the SF recognition network of SZ.

Zhong Y. P., Chen Y., Zhou L. P., & Zhou H. B . ( 2010).

An ERP study on self-positivity bias

Journal of Psychological Science, 33( 3), 560-563.

[本文引用: 4]

[ 钟毅平, 陈芸, 周路平, 周海波 . ( 2010).

自我正面偏见的ERP研究

心理科学, 33( 3), 560-563.]

[本文引用: 4]

Zhong Y. P., Li J., Zhan Y. L., Fan W., & Yang Z. L . ( 2016).

Rotated self-face recognition: Evidence from ERPs

Acta Psychologica Sinica, 48( 11), 1379-1389.

URL     [本文引用: 2]

[ 钟毅平, 李琎, 占友龙, 范伟, 杨子鹿 . ( 2016).

自我旋转面孔识别的ERPs研究

心理学报, 48( 11), 1379-1389.]

URL     [本文引用: 2]

Zhou Y. L., Hu S. J., Cai J. Y., Hu Z. G., & Liu H. Y . ( 2016).

Modulation effect of emotional state on self-positivity bias

Chinese Journal of Clinical Psychology, 24( 2), 196-199.

[本文引用: 1]

[ 周一琳, 胡少军, 蔡佳烨, 胡治国, 刘宏艳 . ( 2016).

情绪状态对积极自我偏向的调节

中国临床心理学杂志, 24( 2), 196-199.]

[本文引用: 1]

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