工作记忆负荷对反馈加工过程的影响: 来自脑电研究的证据

doi:10.3724/SP.J.1041.2022.00248

摘要/Abstract

摘要：

个体对行为后反馈结果的加工在学习和环境适应方面有重要意义, 工作记忆负荷(working memory load, WM load)如何影响反馈加工过程尚不清楚。采用双任务范式, 设置基线、低WM load、高WM load三种条件, 结合ERP技术对这一问题进行探究。发现RewP (reward positivity, 奖赏正波)对效价敏感, 而不受WM load条件影响; Theta震荡的正、负反馈差异波在高WM load条件下比在低WM load条件下小。结果支持等级强化学习-前扣带回理论(HRL-ACC, hierarchical reinforcement learning theory of anterior cingulate cortex)对于RewP和theta震荡的观点: RewP反映了反馈效价评估功能, theta震荡反映了认知控制功能, 并且WM load选择性影响了ACC的认知控制功能而不是反馈效价评估功能。

关键词: 工作记忆负荷(WM load), 反馈, 奖赏正波(RewP), theta震荡, 前扣带回

Abstract:

Feedback processing plays an important role in behavior modification and knowledge acquisition. Previous research has explored the neurophysiological basis and psychological functions of feedback processing and proposed corresponding theoretical models, but little is known about how working memory (WM) load affects feedback processing. Studies have reported electrophysiological indicators, such as the reward positivity (RewP) and the related theta and delta oscillations, the P3 and the late positive potential (LPP), during brain processing feedback. This study will further examine how WM load modulates these electrophysiological components and their corresponding cognitive functions.
In the present study, we used a dual-task paradigm to investigate feedback processing under different WM load conditions. This study included 25 healthy college students and used a 3 (WM load: baseline vs. low WM load vs. high WM load) by 2 (feedback valence: positive vs. negative) within-participant factorial design. During the experiment, participants were asked to perform a simple gambling task and a spatial memory task simultaneously, and the magnitude of the WM load included three conditions: baseline, low WM load and high WM load. The RewP generated in the early stage of feedback processing and the LPP generated in the late stage of feedback processing, as well as the delta and theta oscillations related to feedback evaluation, were analyzed.
The behavioral results showed that the accuracy of the low WM load condition was significantly higher than that of the high WM load condition. The electrophysiological results showed that the amplitudes of the RewP were sensitive to feedback valence, with positive feedback evoking larger RewP than negative feedback, but the RewP was not affected by the WM load. There was no difference in the P3 amplitude under the different WM load conditions. For the LPP, there was a significant interaction between the WM load and feedback valence. Further analysis revealed that, in the high WM load condition, the LPP amplitude was larger for positive feedback than for negative feedback. The theta power differences between negative feedback and positive feedback were larger in the low WM load condition than in the high WM load condition. For delta oscillation, the power was increased after positive feedback compared to after negative feedback, but there was no difference at different WM load levels.
The RewP results indicate that the participants process feedback valence information well under all three WM load conditions in the experiment. The LPP results suggest that the participants assigned additional emotional motivation to the feedback outcome as a result of their cognitive efforts under high WM load conditions. The ERP results for the time domain dimension showed that the effect of the WM load on feedback processing was most noticeable in the later stages of feedback processing. Moreover, these observations support the argument that the RewP and theta power reflect distinct cognitive phenomena; namely, the RewP reflects the processing of feedback valence in the anterior cingulate cortex (ACC), whereas theta oscillations reflect the role of the ACC in cognitive control. The WM load selectively modulates the cognitive control process in the ACC.

Key words: WM load, feedback, reward positivity (RewP), theta oscillation, anterior cingulate cortex

中图分类号:

B842

贾世伟, 齐丛丛, 陈乐乐, 任衍具. (2022). 工作记忆负荷对反馈加工过程的影响: 来自脑电研究的证据. 心理学报, 54(3), 248-258.

JIA Shiwei, QI Congcong, CHEN Lele, REN Yanju. (2022). The effect of working memory load on feedback processing: Evidence from an event-related potentials (ERP) study. Acta Psychologica Sinica, 54(3), 248-258.

图/表 6

图1 高WM load和低WM load条件的记忆材料举例(1a), 以及实验流程图(1b)。如1b所示, 实验为双任务范式, 简单赌博任务嵌在工作记忆任务中。

图2 各条件下RewP原始波和差异波波形图(Fz, FCz和Cz点), 以及RewP差异波地形图

图3 各条件下P3波形图(Pz和POz点), 以及P3地形图

图4 各条件下LPP波形图(Cz、CPz、Pz和POz点), 以及LPP地形图

图5 各条件下theta活动时频分析图(Fz和FCz点)

图6 各条件下delta活动时频分析图(Cz和CPz点)

参考文献 44

[1]	Alexander, W. H., & Brown, J. W. (2010). Computational models of performance monitoring and cognitive control. Topics in Cognitive Science, 2(4), 658-677. pmid: 21359126
[2]	Alexander, W. H., & Brown, J. W. (2011). Medial prefrontal cortex as an action-outcome predictor. Nature Neuroscience, 14(10), 1338-1344. doi: 10.1038/nn.2921 pmid: 21926982
[3]	Baker, T. E., & Holroyd, C. B. (2011). Dissociated roles of the anterior cingulate cortex in reward and conflict processing as revealed by the feedback error-related negativity and N200. Biological Psychology, 87, 25-34. doi: 10.1016/j.biopsycho.2011.01.010 URL
[4]	Bernat, E. M., Nelson, L. D., Steele, V. R., Gehring, W. J., & Patrick, C. J. (2011). Externalizing psychopathology and gain-loss feedback in a simulated gambling task: Dissociable components of brain response revealed by time-frequency analysis. Journal of Abnormal Psychology, 120, 352-364. doi: 10.1037/a0022124 URL
[5]	Broyd, S. J., Richards, H. J., Helps, S. K., Chronaki, G., Bamford, S., & Sonuga-Barke, E. J. S. (2012). An electrophysiological monetary incentive delay (e-MID) task: A way to decompose the different components of neural response to positive and negative monetary reinforcement. Journal of Neuroscience Methods, 209(1), 40-49. doi: 10.1016/j.jneumeth.2012.05.015 URL
[6]	Cheng, J. P., Luo, Y. J., & Cui, F. (2017). Empathy for pain influenced by cognitive load: Evidence from an ERP study. Acta Psychologica Sinica, 49(5), 622-630. doi: 10.3724/SP.J.1041.2017.00622 URL
	[程家萍, 罗跃嘉, 崔芳. (2017). 认知负荷对疼痛共情的影响: 来自ERP研究的证据. 心理学报, 49(5), 622-630.]
[7]	Cohen, M. X., Elger, C. E., & Ranganath, C. (2007). Reward expectation modulates feedback-related negativity and EEG spectra. NeuroImage, 35(2), 968-978. doi: 10.1016/j.neuroimage.2006.11.056 URL
[8]	Donaldson, K. R., Ait Oumeziane, B., Hélie, S., & Foti, D. (2016). The temporal dynamics of reversal learning: P3 amplitude predicts valence-specific behavioral adjustment. Physiology & Behavior, 161, 24-32. doi: 10.1016/j.physbeh.2016.03.034 URL
[9]	Donchin, E., & Coles, M. G. H. (1988). Is the P300 component a manifestation of context updating? Behavioral & Brain Sciences, 11(03), 357-374.
[10]	Ferdinand, N. K. (2019). The influence of task complexity and information value on feedback processing in younger and older adults: No evidence for a positivity bias during feedback- induced learning in older adults. Brain Research, 1717, 74-85. doi: S0006-8993(19)30204-5 pmid: 30991040
[11]	Foti, D., Weinberg, A., Bernat, E. M., & Proudfit, G. H. (2015). Anterior cingulate activity to monetary loss and basal ganglia activity to monetary gain uniquely contribute to the feedback negativity. Clinical Neurophysiology, 126(7), 1338-1347. doi: 10.1016/j.clinph.2014.08.025 pmid: 25454338
[12]	Foti, D., Weinberg, A., Dien, J., & Hajcak, G. (2011). Event- related potential activity in the basal ganglia differentiates rewards from nonrewards: Temporospatial principal components analysis and source localization of the feedback negativity. Human Brain Mapping, 32, 2207-2216. doi: 10.1002/hbm.21182 pmid: 21305664
[13]	Gehring, W. J., & Willoughby, A. R. (2002). The medial frontal cortex and the rapid processing of monetary gains and losses. Science, 295(5563), 2279-2282. doi: 10.1126/science.1066893 URL
[14]	Glazer, J. E., Kelley, N. J., Pornpattananangkul, N., Mittal, V. A., & Nusslock, R. (2018). Beyond the FRN: Broadening the time-course of EEG and ERP components implicated in reward processing. International Journal of Psychophysiology, 132, 184-202. doi: S0167-8760(17)30473-7 pmid: 29454641
[15]	Hajcak, G., Dunning, J. P., & Foti, D. (2009). Motivated and controlled attention to emotion: Time-course of the late positive potential. Clinical Neurophysiology, 120(3), 505-510. doi: 10.1016/j.clinph.2008.11.028 pmid: 19157974
[16]	Hajcak, G., Moser, J. S., Holroyd, C. B., & Simons, R. F. (2006). The feedback-related negativity reflects the binary evaluation of good versus bad outcomes. Biological Psychology, 71(2), 148-154. pmid: 16005561
[17]	Han, M., Shi, L., & Jia, S. (2017). Attentional resources modulate error processing-related brain electrical activity: Evidence from a dual-task design. Brain Research, 1670, 68-75. doi: 10.1016/j.brainres.2017.05.029 URL
[18]	Hernandez Lallement, J., Kuss, K., Trautner, P., Weber, B., Falk, A., & Fliessbach, K. (2014). Effort increases sensitivity to reward and loss magnitude in the human brain. Social Cognitive and Affective Neuroscience, 9(3), 342-349. doi: 10.1093/scan/nss147 pmid: 23202663
[19]	Holroyd, C. B., & Coles, M. G. H. (2002). The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review, 109(4), 679-709. doi: 10.1037/0033-295X.109.4.679 pmid: 12374324
[20]	Holroyd, C. B., & Umemoto, A. (2016). The research domain criteria framework: The case for anterior cingulate cortex. Neuroscience & Biobehavioral Reviews, 71, 418-443. doi: 10.1016/j.neubiorev.2016.09.021 URL
[21]	Holroyd, C. B., & Yeung, N. (2011). An integrative theory of anterior cingulate cortex function: Option selection in hierarchical reinforcement learning. In: Mars, R.B., Sallet, J., Rushworth, M.F.S., Yeung, N. (Eds.), Neural Basis of Motivational and Cognitive Control (pp. 333-349). MIT Press, Cambridge, MA.
[22]	Hsieh, L. T., & Ranganath, C. (2014). Frontal midline theta oscillations during working memory maintenance and episodic encoding and retrieval. Neuroimage. 85, 721-729. doi: 10.1016/j.neuroimage.2013.08.003 URL
[23]	Huang, C., & Yu, R. (2018). Making mistakes in public: Being observed magnifies physiological responses to errors. Neuropsychologia, 119, 214-222. doi: 10.1016/j.neuropsychologia.2018.08.015 URL
[24]	Krigolson, O. E., Hassall, C. D., Satel, J., & Klein, R. M. (2015). The impact of cognitive load on reward evaluation. Brain Research, 1627, 225-232. doi: 10.1016/j.brainres.2015.09.028 pmid: 26431993
[25]	Krigolson, O. E., Heinekey, H., Kent, C. M., & Handy, T. C. (2012). Cognitive load impacts error evaluation within medial-frontal cortex. Brain Research, 1430, 62-67. doi: 10.1016/j.brainres.2011.10.028 pmid: 22099261
[26]	Langeslag, S. J. E., & van Strien, J. W. (2013). Up-regulation of emotional responses to reward-predicting stimuli: An ERP study. Biological Psychology, 94(1), 228-233. doi: 10.1016/j.biopsycho.2013.05.021 pmid: 23770414
[27]	Li, P., Peng, W., Li, H., & Holroyd, C. B. (2018). Electrophysiological measures reveal the role of anterior cingulate cortex in learning from unreliable feedback. Cognitive, Affective, & Behavioral Neuroscience, 18(5), 949-963.
[28]	Luft, C. D. B. (2014). Learning from feedback: The neural mechanisms of feedback processing facilitating better performance. Behavioural Brain Research, 261, 356-368. doi: 10.1016/j.bbr.2013.12.043 URL
[29]	Meadows, C. C., Gable, P. A., Lohse, K. R., & Miller, M. W. (2016). The effects of reward magnitude on reward processing: An averaged and single trial event-related potential study. Biological Psychology, 118, 154-160. doi: 10.1016/j.biopsycho.2016.06.002 URL
[30]	Miltner, W. H. R., Braun, C. H., & Coles, M. G. H. (1997). Event-related brain potentials following incorrect feedback in a time-estimation task: Evidence for a "generic" neural system for error detection. Journal of Cognitive Neuroscience, 9(6), 788-798. doi: 10.1162/jocn.1997.9.6.788 pmid: 23964600
[31]	Mitchell, D. J., McNaughton, N., Flanagan, D., & Kirk, I. J. (2008). Frontal-midline theta from the perspective of hippocampal theta. Progress In Neurobiology, 86, 156-185. doi: 10.1016/j.pneurobio.2008.09.005 pmid: 18824212
[32]	Nieuwenhuis, S., Aston-Jones, G., & Cohen, J. D. (2005). Decision making, the P3, and the locus coeruleus-- norepinephrine system. Psychological Bulletin, 131(4), 510-532. pmid: 16060800
[33]	Oliveira, F. T., Mcdonald, J. J., & Goodman, D. (2007). Performance monitoring in the anterior cingulate is not all error related: Expectancy deviation and the representation of action-outcome associations. Journal of Cognitive Neuroscience, 19(12), 1994-2004. pmid: 17892382
[34]	Polich, J. (2007). Updating P300: An integrative theory of P3a and P3b. Clinical Neurophysiology, 118(10), 2128-2148. pmid: 17573239
[35]	Proudfit, G. H. (2015). The reward positivity: From basic research on reward to a biomarker for depression. Psychophysiology, 52(4), 449-459. doi: 10.1111/psyp.12370 pmid: 25327938
[36]	Rodriguez Buritica, J. M., Heekeren, H. R., Li, S.-C., & Eppinger, B. (2018). Developmental differences in the neural dynamics of observational learning. Neuropsychologia, 119, 12-23. doi: S0028-3932(18)30373-7 pmid: 30036542
[37]	Sambrook, T. D., & Goslin, J. (2015). A neural reward prediction error revealed by a meta-analysis of ERPs using great grand averages. Psychological Bulletin, 141(1), 213-235. doi: 10.1037/bul0000006 pmid: 25495239
[38]	Shahnazian, D., Shulver, K., & Holroyd, C. B. (2018). Electrophysiological responses of medial prefrontal cortex to feedback at different levels of hierarchy. NeuroImage, 183, 121-131. doi: S1053-8119(18)30680-3 pmid: 30081194
[39]	Stewart, J. G., Singleton, P., Benau, E. M., Foti, D., Allchurch, H.,... Kaplan, C. S., Auerbach, R. P. (2019). Neurophysiological activity following rewards and losses among female adolescents and young adults with borderline personality disorder. Journal of Abnormal Psychology, 128(6), 610-621. doi: 10.1037/abn0000439 pmid: 31318241
[40]	Webb, C. A., Auerbach, R. P., Bondy, E., Stanton, C. H., Foti, D., & Pizzagalli, D. A. (2017). Abnormal neural responses to feedback in depressed adolescents. Journal of Abnormal Psychology, 126(1), 19-31. doi: 10.1037/abn0000228 URL
[41]	White, E. J., & Grant, D. M. (2017). Electrocortical consequences of image processing: The influence of working memory load and worry. Psychiatry Research: Neuroimaging, 261, 1-8. doi: 10.1016/j.pscychresns.2017.01.003 URL
[42]	Yang, Q., Zhao, D., Wu, Y., Tang, P., Gu, R., & Luo, Y.-j. (2018). Differentiating the influence of incidental anger and fear on risk decision-making. Physiology & Behavior, 184, 179-188. doi: 10.1016/j.physbeh.2017.11.028 URL
[43]	Yeung, N., & Sanfey, A. G. (2004). Independent coding of reward magnitude and valence in the human brain. Journal of Neuroscience, 24(28), 6258-6264. pmid: 15254080
[44]	Zhou, Z., Yu, R., & Zhou, X. (2010). To do or not to do? Action enlarges the FRN and P300 effects in outcome evaluation. Neuropsychologia, 48(12), 3606-3613. doi: 10.1016/j.neuropsychologia.2010.08.010 URL