连续反馈影响主导感的心理与脑电机制

doi:10.3724/SP.J.1041.2025.0380

摘要/Abstract

摘要： 通过简单赌博任务和主导感的外显测量, 操纵连续反馈次数(1~8次), 首次考察了主导感在连续反馈下的变化模式及其脑电机制。结果发现：主导感在连续反馈的作用下随着连续反馈的累积而持续变化, 且累积结果在效价间的变化趋势不同。收益条件下, 主导感变化趋势符合二次多项式, 先上升后趋于稳定; 损失条件下, 主导感变化趋势符合一元线性模型, 随连续损失反馈而降低。脑电上, 与不连续损失相比, 连续损失期间会诱发更负的右侧SPN波幅; 而FRN波幅对收益的连续性敏感, 与不连续收益相比, 连续收益下FRN波幅更负, 且与随后更高的行为选择重复率有关; 与连续收益相比, 连续损失会诱发更大的Fb-P3波幅。综上, 收益和损失下主导感的变化模式在行为和脑电层面均呈现差异化。研究为主导感的“动态假说”提供了来自连续反馈下心理及其脑电特征的证据。

关键词: 主导感, 连续反馈, 事件相关电位, SPN, FRN, Fb-P3

Abstract:

This study aimed to investigate the impact of multiple sequential feedback on sense of agency (SoA) and its underlying cognitive mechanisms, bridging a gap in previous research that primarily focused on the influence of outcome feedback valences on SoA. Employing a simple gambling task (door task), the study manipulated the number of successive feedbacks and utilized explicit measure of SoA.

A within-subject design of 2 (outcome valence: gain, loss) × 8 (sequential feedback times: 1~8) was implemented. The study included forty college students (38 in the final analysis, with 20 females, aged 20.79 ± 1.70), who voluntarily participated. During the experiment, participants guessed which of two doors contained a reward and selected the corresponding door by pressing a button. Feedback resulted in a gain of 10 for a correct guess and a loss of 10 for an incorrect one, with outcome feedback predetermined before the experiment, leading to one to eight different gain or loss sequences. Subsequently, participants rated their SoA after receiving feedback. Event-related potential responses to outcome feedback, focusing on stimulus-preceding negativity (SPN) in the outcome anticipation phase, and feedback-related negativity (FRN) and feedback-P3 (fb-P3) in the outcome processing phase, were recorded and analyzed.

Behavioral results revealed a significantly lower SoA under loss conditions compared to gain conditions, aligning with previous findings. Sequential feedback demonstrated a cumulative effect on SoA, with continuous changes observed based on feedback results. Under gain conditions, the cumulative effect followed a quadratic polynomial model, with SoA increasing to a "change" point (the seventh gain feedback) and then stabilizing. Conversely, under loss conditions, SoA gradually diminished with continuous loss feedback, following a unitary linear model. Combining ERP and behavioral results, it was found that SoA under continuous loss was related to the amplitude of right frontal lobe SPN before outcome feedback. FRN amplitude was sensitive to the continuity of loss, being more negative under continuous loss compared to discontinuous loss and associated with a higher repetition rate of subsequent behavior selection. Moreover, continuous losses induced a significantly greater Fb-P3 amplitude compared to continuous gains.

In conclusion, this study provides empirical evidence supporting the dynamic account of SoA, revealing differentiated developmental mechanisms in both behavior and ERPs under sequential gain and loss conditions. These findings shed light on how sequential feedback influences SoA and the characteristics of processing time.

Key words: sense of agency, sequential feedback, event-related potentials (ERPs), stimulus-preceding negativity (SPN), feedback-related negativity (FRN), feedback-P3 (Fb-P3)

中图分类号:

B842.1

谢晓玲, 潘文谊, 张纯纯, 林静远, 李红. (2025). 连续反馈影响主导感的心理与脑电机制. 心理学报, 57(3), 380-397.

XIE XiaoLing, PAN WenYi, ZHANG ChunChun, LIN JingYuan, LI Hong. (2025). Sequential feedback influences the psychological and event-related potentials mechanism of sense of agency. Acta Psychologica Sinica, 57(3), 380-397.

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连续反馈次数	1	2	3	4	5	6	7
2	−0.67 (0.11)
2	p < 0.001
3	−1.15 (0.17)	−0.48 (0.08)
3	p < 0.001	p < 0.001
4	−1.57 (0.24)	−0.90 (0.15)	−0.42 (0.10)
4	p < 0.001	p < 0.001	p = 0.005
5	−1.87 (0.28)	−1.20 (0.21)	−0.722 (0.15)	−0.30 (0.07)
5	p < 0.001	p < 0.001	p < 0.001	p = 0.002
6	−2.13 (0.30)	−1.46 (0.23)	−0.99 (0.18)	−0.56 (0.11)	−0.26 (0.06)
6	p < 0.001	p < 0.001	p < 0.001	p < 0.001	p = 0.003
7	−2.04 (0.31)	−1.37 (0.24)	−0.90 (0.18)	−0.47 (0.13)	−0.17 (0.09)	0.09 (0.06)
7	p < 0.001	p < 0.001	p < 0.001	p = 0.016	p = 1.000	p = 1.000
8	−2.13 (0.32)	−1.46 (0.26)	−0.98 (0.20)	−0.56 (0.14)	−0.26 (0.10)	0.00 (0.06)	−0.09 (0.06)
8	p < 0.001	p < 0.001	p < 0.001	p = 0.010	p = 0.499	p = 1.000	p = 1.000

连续反馈次数	1	2	3	4	5	6	7
2	−0.67 (0.11)
2	p < 0.001
3	−1.15 (0.17)	−0.48 (0.08)
3	p < 0.001	p < 0.001
4	−1.57 (0.24)	−0.90 (0.15)	−0.42 (0.10)
4	p < 0.001	p < 0.001	p = 0.005
5	−1.87 (0.28)	−1.20 (0.21)	−0.722 (0.15)	−0.30 (0.07)
5	p < 0.001	p < 0.001	p < 0.001	p = 0.002
6	−2.13 (0.30)	−1.46 (0.23)	−0.99 (0.18)	−0.56 (0.11)	−0.26 (0.06)
6	p < 0.001	p < 0.001	p < 0.001	p < 0.001	p = 0.003
7	−2.04 (0.31)	−1.37 (0.24)	−0.90 (0.18)	−0.47 (0.13)	−0.17 (0.09)	0.09 (0.06)
7	p < 0.001	p < 0.001	p < 0.001	p = 0.016	p = 1.000	p = 1.000
8	−2.13 (0.32)	−1.46 (0.26)	−0.98 (0.20)	−0.56 (0.14)	−0.26 (0.10)	0.00 (0.06)	−0.09 (0.06)
8	p < 0.001	p < 0.001	p < 0.001	p = 0.010	p = 0.499	p = 1.000	p = 1.000

连续反馈次数	1	2	3	4	5	6	7
2	0.06 (0.09)
2	p = 1.000
3	0.19 (0.12)	0.14 (0.07)
3	p = 1.000	p = 1.000
4	0.29 (0.15)	0.23 (0.09)	0.10 (0.08)
4	p = 1.000	p = 0.376	p = 1.000
5	0.24 (0.15)	0.18 (0.10)	0.05 (0.08)	−0.05 (0.08)
5	p = 1.000	p = 1.000	p = 1.000	p = 1.000
6	0.45 (0.14)	0.40 (0.09)	0.26 (0.09)	0.17 (0.07)	0.21 (0.10)
6	p = 0.061	p = 0.003	p = 0.172	p = 0.758	p = 1.000
7	0.49 (0.16)	0.43 (0.11)	0.30 (0.08)	0.20 (0.08)	0.25 (0.07)	0.04 (0.07)
7	p = 0.100	p = 0.008	p = 0.027	p = 0.278	p = 0.036	p = 1.000
8	0.54 (0.18)	0.49 (0.14)	0.35 (0.12)	0.26 (0.10)	0.30 (0.10)	0.09 (0.10)	0.05 (0.07)
8	p = 0.154	p = 0.030	p = 0.157	p = 0.385	p = 0.162	p = 1.000	p = 1.000

连续反馈次数	1	2	3	4	5	6	7
2	0.06 (0.09)
2	p = 1.000
3	0.19 (0.12)	0.14 (0.07)
3	p = 1.000	p = 1.000
4	0.29 (0.15)	0.23 (0.09)	0.10 (0.08)
4	p = 1.000	p = 0.376	p = 1.000
5	0.24 (0.15)	0.18 (0.10)	0.05 (0.08)	−0.05 (0.08)
5	p = 1.000	p = 1.000	p = 1.000	p = 1.000
6	0.45 (0.14)	0.40 (0.09)	0.26 (0.09)	0.17 (0.07)	0.21 (0.10)
6	p = 0.061	p = 0.003	p = 0.172	p = 0.758	p = 1.000
7	0.49 (0.16)	0.43 (0.11)	0.30 (0.08)	0.20 (0.08)	0.25 (0.07)	0.04 (0.07)
7	p = 0.100	p = 0.008	p = 0.027	p = 0.278	p = 0.036	p = 1.000
8	0.54 (0.18)	0.49 (0.14)	0.35 (0.12)	0.26 (0.10)	0.30 (0.10)	0.09 (0.10)	0.05 (0.07)
8	p = 0.154	p = 0.030	p = 0.157	p = 0.385	p = 0.162	p = 1.000	p = 1.000

连续反馈次数	N	M	SD	t	p	Cohen's d
1	38	4.35	1.97	−2.03	0.049	1.97
2	38	5.02	1.95	0.06	0.951	1.95
3	38	5.50	1.98	1.55	0.131	1.98
4	38	5.92	2.01	2.83	0.008	2.01
5	38	6.22	2.08	3.61***	< 0.001	2.08
6	38	6.48	2.04	4.47***	< 0.001	2.04
7	38	6.39	2.11	4.07***	< 0.001	2.11
8	38	6.48	2.10	4.34***	< 0.001	2.10