第三方惩罚的神经机制：来自经颅直流电刺激的证据

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殷西乐¹^,², 李建标³^,⁴(

), 陈思宇¹, 刘晓丽⁴, 郝洁⁵(

)

1 浙江工商大学工商管理学院
2 浙江工商大学浙商研究院
3 浙江工商大学MBA学院, 杭州 310018
4 南开大学泽尔滕实验室, 南开大学滨海学院, 天津 300071
5 浙江工商大学财务与会计学院, 杭州 310018

收稿日期:2018-08-10出版日期:2019-05-25发布日期:2019-03-20
通讯作者:李建标,郝洁E-mail:biaojl@126.com;haojie@mail.zjgsu.edu.cn

基金资助:浙江省高校人文社会科学重点研究基地(浙江工商大学工商管理学科)(JYTgs20181107);国家自然科学基金(71673152)

Neural mechanisms of third-party punishment: Evidence from transcranial direct current stimulation

YIN Xile¹^,², LI Jianbiao³^,⁴(

), CHEN Siyu¹, LIU Xiaoli⁴, HAO Jie⁵(

)

1 School of Business Administration, Zhejiang Gongshang University, Hangzhou 310018, China
2 Zheshang Research Institute, Zhejiang Gongshang University, Hangzhou 310018, China
3 MBA School, Zhejiang Gongshang University, Hangzhou 310018, China
4 Selten Laboratory, Binhai College, Nankai University, Tianjin 300071, China
5 School of Accounting, Zhejiang Gongshang University, Hangzhou 310018, China

Received:2018-08-10Online:2019-05-25Published:2019-03-20
Contact:LI Jianbiao,HAO Jie E-mail:biaojl@126.com;haojie@mail.zjgsu.edu.cn

摘要/Abstract

摘要： 第三方惩罚既是社会规范在群体得以维系的基石, 也是个体维护社会规范的体现。当前关注社会规范的神经研究大多基于第二方惩罚的独裁者或最后通牒实验框架, 缺乏对第三方维护社会规范过程中相关脑区活动的探索, 对这一过程的内在神经机制也不清楚。本文基于第三方惩罚的独裁者博弈框架, 对右侧背外侧前额叶区域(DLPFC)进行不同极性的经颅直流电刺激(tDCS), 同时依据第三方是否需要为其惩罚付出成本设计了零成本和有成本两个实验任务。结果发现, 第三方在零成本任务的情绪反应和惩罚显著受到tDCS设置的影响, 且阴极刺激显著提升了第三方的惩罚值, 这表明情绪机制对第三方惩罚有着重要影响。另外, 第三方在零成本和有成本任务中的惩罚差异在不同tDCS设置之间也存在显著差异, 这与第三方惩罚还受到自利机制影响的观点相符。本文率先为右侧DLPFC活动影响第三方惩罚提供了神经层面的证据, 且支持了第三方对社会规范的遵从与其负性情绪反应和自利加工密切相关的机制解释。

图/表 6

图1HD-Explore软件绘制的电流模式展示(左图为阳极刺激, 右图为阴极刺激)

图2独裁者A的决策界面

图3不同分配方案下第三方的情绪及其惩罚值(误差线为标准误)

图3不同分配方案下第三方的情绪及其惩罚值(误差线为标准误)

表1独裁者博弈中第三方情绪反应的描述性统计

方案公平性	tDCS	n	M	SD	ANOVA
不公平	阴极	29	-1.38	0.78	F(2, 86) = 12.07, p < 0.001, η² = 0.219
	虚拟	30	-0.97	0.72
	阳极	30	-0.33	0.96
	总体	89	-0.89	0.92
中等	阴极	29	0.00	0.80	F(2, 86) = 0.83, p = 0.438
	虚拟	30	0.23	0.77
	阳极	30	0.20	0.66
	总体	89	0.15	0.75
公平	阴极	29	1.52	0.57	F(2, 86) = 1.43, p = 0.245
	虚拟	30	1.30	0.70
	阳极	30	1.23	0.73
	总体	89	1.35	0.68

表1独裁者博弈中第三方情绪反应的描述性统计

方案公平性	tDCS	n	M	SD	ANOVA
不公平	阴极	29	-1.38	0.78	F(2, 86) = 12.07, p < 0.001, η² = 0.219
	虚拟	30	-0.97	0.72
	阳极	30	-0.33	0.96
	总体	89	-0.89	0.92
中等	阴极	29	0.00	0.80	F(2, 86) = 0.83, p = 0.438
	虚拟	30	0.23	0.77
	阳极	30	0.20	0.66
	总体	89	0.15	0.75
公平	阴极	29	1.52	0.57	F(2, 86) = 1.43, p = 0.245
	虚拟	30	1.30	0.70
	阳极	30	1.23	0.73
	总体	89	1.35	0.68

表2独裁者博弈中第三方惩罚值的描述性统计(零成本设置)

方案公平性	tDCS	n	M	SD	ANOVA
不公平	阴极	29	29.59	9.88	F(2, 86) = 9.29, p < 0.001, η² = 0.178
	虚拟	30	19.37	13.74
	阳极	30	16.23	13.19
	总体	89	21.64	13.54
中等	阴极	29	9.69	8.61	F(2, 86) = 1.43, p = 0.246
	虚拟	30	6.53	6.75
	阳极	30	6.50	9.35
	总体	89	7.55	8.35
公平	阴极	29	1.76	9.28	F(2, 86) = 0.07, p = 0.935
	虚拟	30	1.83	9.14
	阳极	30	1.17	3.13
	总体	89	1.58	7.63

表2独裁者博弈中第三方惩罚值的描述性统计(零成本设置)

方案公平性	tDCS	n	M	SD	ANOVA
不公平	阴极	29	29.59	9.88	F(2, 86) = 9.29, p < 0.001, η² = 0.178
	虚拟	30	19.37	13.74
	阳极	30	16.23	13.19
	总体	89	21.64	13.54
中等	阴极	29	9.69	8.61	F(2, 86) = 1.43, p = 0.246
	虚拟	30	6.53	6.75
	阳极	30	6.50	9.35
	总体	89	7.55	8.35
公平	阴极	29	1.76	9.28	F(2, 86) = 0.07, p = 0.935
	虚拟	30	1.83	9.14
	阳极	30	1.17	3.13
	总体	89	1.58	7.63

表3独裁者博弈中第三方惩罚差异的描述性统计

方案公平性	tDCS	n	M	SD	ANOVA
不公平	阴极	29	21.90	13.10	F(2, 86) = 6.62, p = 0.002, η² = 0.133
	虚拟	30	12.67	12.92
	阳极	30	10.10	13.17
	总体	89	14.81	13.87
中等	阴极	29	7.48	9.48	F(2, 86) = 1.7, p = 0.188
	虚拟	30	4.00	6.68
	阳极	30	3.07	12.07
	总体	89	4.82	9.74
公平	阴极	29	1.76	9.28	F(2, 86) = 0.08, p = 0.925
	虚拟	30	1.33	9.28
	阳极	30	0.97	2.65
	总体	89	1.35	7.63

表3独裁者博弈中第三方惩罚差异的描述性统计

方案公平性	tDCS	n	M	SD	ANOVA
不公平	阴极	29	21.90	13.10	F(2, 86) = 6.62, p = 0.002, η² = 0.133
	虚拟	30	12.67	12.92
	阳极	30	10.10	13.17
	总体	89	14.81	13.87
中等	阴极	29	7.48	9.48	F(2, 86) = 1.7, p = 0.188
	虚拟	30	4.00	6.68
	阳极	30	3.07	12.07
	总体	89	4.82	9.74
公平	阴极	29	1.76	9.28	F(2, 86) = 0.08, p = 0.925
	虚拟	30	1.33	9.28
	阳极	30	0.97	2.65
	总体	89	1.35	7.63

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