连续风险决策中先前结果反馈的作用机制
Mechanisms of Previous Outcome Feedback in Sequential Risky Decision-Making
摘要: 连续风险决策是一种决策者在不确定和有风险的情况下做出的连续决策，先前决策的结果反馈是连续决策过程中一个非常重要的影响因素，这类根据反馈信息进行的连续动态决策更贴近现实情境，了解连续风险决策行为中的黑箱机制有助于个体理性决策。本研究从参照点适应模型、强化学习模型、注意力模型、多维情绪模型等方面综述了连续风险决策中先前结果反馈的作用机制，试图进一步理解连续风险行为背后的心理机制，厘清多种机制模型在连续的风险决策过程中如何变化发展。未来研究可以深入考察几种机制模型的竞争与结合，探究决策领域发生转换时结果反馈的作用途径，同时重视时间因素在连续风险决策中的影响以及其内在神经机制。
Abstract: Sequential risky decision-making (SRDM) is a kind of continuous decision-making in which the individuals make decisions under uncertain and risky situations. Outcome feedback of previous decisions is a significant influencing factor in the sequential risky decision-making process, and this type of continuous dynamic decision-making is more relevant to real-world authentic situations. This study reviewed the multiple mechanism of the role of previous outcome feedback in sequential risky decision-making in terms of the reference point adaptation model, the reinforcement learning model, the attentional model, and the multidimensional emotion model. The objective of the present work is to understand completely the psychological mechanisms behind sequential risk behaviors and help individuals make rational decisions. Future researches may be able to focus on the competition and combination of multiple mechanism models, explore the role of outcome feedback when switching decision domains, emphasize the impact of the temporal factor, and validate integrated models through the neural mechanisms behind sequential risk decisions.
文章引用：张静芝 (2024). 连续风险决策中先前结果反馈的作用机制. 心理学进展, 14(3), 316-327. https://doi.org/10.12677/ap.2024.143163

参考文献

[1] 潘禄, 钱秀莹(2014). 动态重复决策中先前结果对风险偏好的影响. 心理学报, 46(12), 1860-1870.
[2] 张颖, 冯廷勇(2014). 青少年风险决策的发展认知神经机制. 心理科学进展, 22(7), 1139-1148.
[3] Ariely, D., & Norton, M. I. (2011). From Thinking Too Little to Thinking Too Much: A Continuum of Decision Making. Wiley Interdisciplinary Reviews: Cognitive Science, 2, 39-46.[CrossRef] [PubMed]
[4] Arkes, H. R., Hirshleifer, D., Jiang, D., & Lim, S. (2008). Reference Point Adaptation: Tests in the Domain of Security Trading. Organizational Behavior and Human Decision Processes, 105, 67-81.[CrossRef] 
[5] Barron, G., Leider, S., & Stack, J. (2008). The Effect of Safe Experience on a Warnings’ Impact: Sex, Drugs, and Rock-N-Roll. Organizational Behavior and Human Decision Processes, 106, 125-142.[CrossRef] 
[6] Bennett, D., Davidson, G., & Niv, Y. (2022). A Model of Mood as Integrated Advantage. Psychological Review, 129, 513-541.[CrossRef] [PubMed]
[7] Brand, M., Labudda, K., & Markowitsch, H. J. (2006). Neuropsychological Correlates of Decision-Making in Ambiguous and Risky Situations. Neural Networks, 19, 1266-1276.[CrossRef] [PubMed]
[8] Brassen, S., Gamer, M., Peters, J., Gluth, S., & Buchel, C. (2012). Don’t Look Back in Anger! Responsiveness to Missed Chances in Successful and Nonsuccessful Aging. Science, 336, 612-614.[CrossRef] [PubMed]
[9] Buckenmaier, J., & Dimant, E. (2021). The Experience Is (Not) Everything: Sequential Outcomes and Social Decision-Making. Economics Letters, 205, Article 109916.[CrossRef] 
[10] Busemeyer, J. R., & Townsend, J. T. (1993). Decision Field Theory: A Dynamic-Cognitive Approach to Decision Making in an Uncertain Environment. Psychological Review, 100, 432-459.[CrossRef] 
[11] Calabro, F. J., Montez, D. F., Larsen, B., Laymon, C. M., Foran, W., Hallquist, M. N., Price, J. C., & Luna, B. (2023). Striatal Dopamine Supports Reward Expectation and Learning: A Simultaneous PET/FMRI Study. NeuroImage, 267, Article 119831.[CrossRef] [PubMed]
[12] Chen, H., & Rao, A. R. (2002). Close Encounters of Two Kinds: False Alarms and Dashed Hopes. Marketing Science, 21, 178-196.[CrossRef] 
[13] Colasante, A., Marini, M., & Russo, A. (2017). Incidental Emotions and Risk-Taking: An Experimental Analysis. SSRN Electronic Journal.[CrossRef] 
[14] Del Giacco, A. C., Jones, S. A., Morales, A. M., Kliamovich, D., & Nagel, B. J. (2022). Adolescent Novelty Seeking Is Associated with Greater Ventral Striatal and Prefrontal Brain Response during Evaluation of Risk and Reward. Cognitive, Affective & Behavioral Neuroscience, 22, 123-133.[CrossRef] [PubMed]
[15] Domenech, P., Redouté, J., Koechlin, E., & Dreher, J. C. (2018). The Neuro-Computational Architecture of Value-Based Selection in the Human Brain. Cerebral Cortex, 28, 585-601.[CrossRef] [PubMed]
[16] Feng, L., & Seasholes, M. S. (2005). Do Investor Sophistication and Trading Experience Eliminate Behavioral Biases in Financial Markets? Review of Finance, 9, 305-351.[CrossRef] 
[17] Figner, B., Mackinlay, R. J., Wilkening, F., & Weber, E. U. (2009). Affective and Deliberative Processes in Risky Choice: Age Differences in Risk Taking in the Columbia Card Task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35, 709-730.[CrossRef] [PubMed]
[18] Franken, I., Georgieva, I., Muris, P., & Dijksterhuis, A. (2006). The Rich Get Richer and the Poor Get Poorer. Judgment & Decision Making, 1, 153-158.[CrossRef] 
[19] Gabillon, E. (2020). When Choosing Is Painful: Anticipated Regret and Psychological Opportunity Cost. Journal of Economic Behavior & Organization, 178, 644-659.[CrossRef] 
[20] Gerrard, M., Gibbons, F. X., Houlihan, A. E., Stock, M. L., & Pomery, E. A. (2008). A Dual-Process Approach to Health Risk Decision Making: The Prototype Willingness Model. Developmental Review, 28, 29-61.[CrossRef] 
[21] Gianfranchi, E., Tagliabue, M., Megías-Robles, A., & Maldonado, A. (2021). The Role of Feedback in Shaping Responses to Risky Road Scenarios: Evidence from Electrodermal Activity. Transportation Research: Part F, 83, 130-147.[CrossRef] 
[22] Gu, R., Zhang, D., Luo, Y., Wang, H., & Broster, L. S. (2018). Predicting Risk Decisions in a Modified Balloon Analogue Risk Task: Conventional and Single-Trial ERP Analyses. Cognitive, Affective & Behavioral Neuroscience, 18, 99-116.[CrossRef] [PubMed]
[23] Haffke, P., & Hübner, R. (2015). Effects of Different Feedback Types on Information Integration in Repeated Monetary Gambles. Frontiers in Psychology, 5, Article 1597.[CrossRef] [PubMed]
[24] Haffke, P., & Hübner, R. (2020). Are Choices Based on Conditional or Conjunctive Probabilities in a Sequential Risk-Taking Task? Journal of Behavioral Decision Making, 33, 333-347.[CrossRef] 
[25] Herweg, F., & Müller, D. (2021). A Comparison of Regret Theory and Salience Theory for Decisions under Risk. Journal of Economic Theory, 193, Article 105226.[CrossRef] 
[26] Jessup, R. K. (2008). Neural Correlates of the Behavioral Differences between Descriptive and Experiential Choice: An Examination Combining Computational Modeling with FMRI. Doctoral Dissertation, Indiana University.[CrossRef] 
[27] Kahneman, D. (1973). Attention and Effort. Prentice Hall.
[28] Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47, 263-291.[CrossRef] 
[29] Kelly, S. P., Corbett, E. A., & O’Connell, R. G. (2021). Neurocomputational Mechanisms of Prior-Informed Perceptual Decision-Making in Humans. Nature Human Behaviour, 5, 467-481.[CrossRef] [PubMed]
[30] Koop, G. J., & Johnson, J. G. (2010). The Use of Multiple Reference Points in Risky Decision Making. Journal of Behavioral Decision Making, 25, 49-62.[CrossRef] 
[31] Krajbich, I. (2019). Accounting for Attention in Sequential Sampling Models of Decision Making. Current Opinion in Psychology, 29, 6-11.[CrossRef] [PubMed]
[32] Kumano, S., Hamilton, A., & Bahrami, B. (2021). The Role of Anticipated Regret in Choosing for Others. Scientific Reports, 11, Article No. 12557.[CrossRef] [PubMed]
[33] Ledgerwood, A., & Boydstun, A. E. (2014). Sticky Prospects: Loss Frames Are Cognitively Stickier Than Gain Frames. Journal of Experimental Psychology: General, 143, 376-385.[CrossRef] [PubMed]
[34] Lin, H., Liang, J., Yang, J., & Wu, F. (2021). Effects of Experienced Regret on Risky Decision Making Are Dependent on Risky Degree. Scandinavian Journal of Psychology, 62, 339-347.[CrossRef] [PubMed]
[35] Liu, Z., Cheng, X., Liu, S., Zhang, Z., & Guo, X. (2020). Attentional Deployment Training Impacts Neural Responses to Subsequent Regret. International Journal of Psychophysiology: Official Journal of the International Organization of Psychophysiology, 157, 23-31.[CrossRef] [PubMed]
[36] Liu, Z., Liu, S., Li, S., Li, L., Zheng, L., Weng, X., Guo, X., Lu, Y., Men, W., Gao, J., & You, X. (2022). Dissociating Value-Based Neurocomputation from Subsequent Selection-Related Activations in Human Decision-Making. Cerebral Cortex, 32, 4141-4155.[CrossRef] [PubMed]
[37] Liu, Z., Zheng, L., Li, L., Xu, J., Cheng, X., Guo, X. et al. (2018). Social Comparison Modulates the Neural Responses to Regret and Subsequent Risk-Taking Behavior. Social Cognitive and Affective Neuroscience, 13, 1059-1070.[CrossRef] [PubMed]
[38] Ludvig, E. A., Madan, C. R., & Spetch, M. L. (2014). Extreme Outcomes Sway Risky Decisions from Experience. Journal of Behavioral Decision Making, 27, 146-156.[CrossRef] 
[39] Mailliez, M., Bollon, T., Graton, A., & Hot, P. (2020). Can the Induction of Incidental Positive Emotions Lead to Different Performances in Sequential Decision-Making? Cognition & Emotion, 34, 1509-1516.[CrossRef] [PubMed]
[40] Marini, M. M. (2022). 20 Years of Emotions and Risky Choices in the Lab: A Meta-Analysis. Working Papers 2022/03, Economics Department, Universitat Jaume I.
[41] Marshall, A. T., & Kirkpatrick, K. (2017). Reinforcement Learning Models of Risky Choice and the Promotion of Risk-Taking by Losses Disguised as Wins in Rats. Journal of Experimental Psychology: Animal Learning and Cognition, 43, 262-279.[CrossRef] [PubMed]
[42] Merkle, C., Müller-Dethard, J., & Weber, M. (2020). Closing a Mental Account: the Realization Effect for Gains and Losses. Experimental Economics, 24, 303-329.[CrossRef] 
[43] Mishra, S., Lalumière, M. L., & Williams, R. J. (2010). Gambling as a Form of Risk Taking: Individual Differences in Personality, Risk-Accepting Attitudes, and Behavioural Preferences for Risk. Personality and Individual Differences, 49, 616-621.[CrossRef] 
[44] Mrkva, K., Johnson, E. J., Gächter, S., & Herrmann, A. (2019). Moderating Loss Aversion: Loss Aversion Has Moderators, but Reports of Its Death Are Greatly Exaggerated. Journal of Consumer Psychology, 30, 407-428.[CrossRef] 
[45] Pachur, T., Schulte-Mecklenbeck, M., Murphy, R. O., & Hertwig, R. (2018). Prospect Theory Reflects Selective Allocation of Attention. Journal of Experimental Psychology: General, 147, 147-169.[CrossRef] [PubMed]
[46] Paiva, M. L., Rzezak, P., Santos, B., Lima, E. M., Moschetta, S. P., Vincentiis, S. et al. (2019). Dissociation between Decision Making under Ambiguity and Risk in Patients with Juvenile Myoclonic Epilepsy. Epilepsy & Behavior, 101, Article 106548.[CrossRef] [PubMed]
[47] Panno, A., Lauriola, M., & Pierro, A. (2015). Regulatory Mode and Risk-Taking: the Mediating Role of Anticipated Regret. PLOS ONE, 10, e0143147.[CrossRef] [PubMed]
[48] Pine, A., Seymour, B., Roiser, J. P., Bossaerts, P., Friston, K. J., & Curran, H. V. (2009). Encoding of Marginal Utility across Time in the Human Brain. Journal of Neuroscience, 29, 9575-9581.[CrossRef] 
[49] Pleskac, T. J., & Wershbale, A. (2014). Making Assessments While Taking Repeated Risks: A Pattern of Multiple Response Pathways. Journal of Experimental Psychology: General, 143, 142-162.[CrossRef] [PubMed]
[50] Polich, J. (2007). Updating P300: An Integrative Theory of P3a and P3b. Clinical Neurophysiology, 118, 2128-2148.[CrossRef] [PubMed]
[51] Poudel, R., Riedel, M. C., Salo, T., Flannery, J. S., Hill-Bowen, L. D., Eickhoff, S. B. et al. (2020). Common and Distinct Brain Activity Associated with Risky and Ambiguous Decision-Making. Drug and Alcohol Dependence, 209, Article 107884.[CrossRef] [PubMed]
[52] Rangel, A., Camerer, C., & Montague, P. R. (2008). A Framework for Studying the Neurobiology of Value-Based Decision Making. Nature Reviews Neuroscience, 9, 545-556.[CrossRef] [PubMed]
[53] Schwerter, F., & Zimmermann, F. (2020). Determinants of Trust: the Role of Personal Experiences. Games and Economic Behavior, 122, 413-425.[CrossRef] 
[54] Sekścińska, K., Rudzinska-Wojciechowska, J., & Maison, D. (2018). Individual Differences in Time Perspectives and Risky Financial Choices. Personality and Individual Differences, 120, 118-126.[CrossRef] 
[55] Shapiro, M. S., Price, P. C., Mitchell, E., & Baron, J. (2020). Carryover of Domain-Dependent Risk Preferences in a Novel Decision-Making Task. Judgment and Decision Making, 15, 1009-1023.[CrossRef] 
[56] Skagerlund, K., Forsblad, M., Slovic, P., & Västfjäll, D. (2020). The Affect Heuristic and Risk Perception-Stability across Elicitation Methods and Individual Cognitive Abilities. Frontiers in Psychology, 11, Article 970.[CrossRef] [PubMed]
[57] Somasundaram, J., & Diecidue, E. (2017). Regret Theory and Risk Attitudes. Journal of Risk and Uncertainty, 55, 147-175.[CrossRef] 
[58] Sui, Y., Tan, H., & Li, D. (2019). Individual and Dyadic Continuous Risk-Based Decision Making: Changes and Differences. Social Behavior and Personality: An International Journal, 47, 1-10.[CrossRef] 
[59] Tannou, T., Magnin, E., Comte, A., Aubry, R., & Joubert, S. (2021). Neural Activation in Risky Decision-Making Tasks in Healthy Older Adults: A Meta-Analysis of FMRI Data. Brain Sciences, 11, Article 1043.[CrossRef] [PubMed]
[60] Taswell, C. A., Janssen, M., Murray, E. A., & Averbeck, B. B. (2023). The Motivational Role of the Ventral Striatum and Amygdala in Learning from Gains and Losses. Behavioral Neuroscience, 137, 268-280.[CrossRef] [PubMed]
[61] Xiong, W., Wang, C., & Ma, L. (2023). Partner or Subordinate? Sequential Risky Decision-Making Behaviors under Human-Machine Collaboration Contexts. Computers in Human Behavior, 139, Article 107556.[CrossRef] 
[62] Yang, J., Liu, Z., Liu, S., Li, L., Zheng, L., & Guo, X. (2019). The Emotional Stability of Elders with Tai Chi Experience in the Sequential Risk-Taking Task. PsyCh Journal, 8, 491-502.[CrossRef] [PubMed]
[63] Yechiam, E., & Hochman, G. (2013). Losses as Modulators of Attention: Review and Analysis of the Unique Effects of Losses over Gains. Psychological Bulletin, 139, 497-518.[CrossRef] [PubMed]
[64] Yechiam, E., Ashby, N. J., & Pachur, T. (2017). Who’s Biased? A Meta-Analysis of Buyer-Seller Differences in the Pricing of Lotteries. Psychological Bulletin, 143, 543-563.[CrossRef] [PubMed]
[65] Zhai, Y., Lv, Z., Zhao, J., Wang, W., & Leung, H. (2022). Associative Reasoning-Based Interpretable Continuous Decision Making in Industrial Production Process. Expert Systems with Applications, 204, Article 117585.[CrossRef] 
[66] Zhang, B., & Shou, Y. (2022). Immediate Emotions and Subjective Stakes in Risky Decision-Making under Uncertainty. Anxiety, Stress & Coping, 35, 649-661.[CrossRef] [PubMed]
[67] Zhou, F., Zimmermann, K., Xin, F., Scheele, D., Dau, W., Banger, M., Weber, B., Hurlemann, R., Kendrick, K. M., & Becker, B. (2018). Shifted Balance of Dorsal Versus Ventral Striatal Communication with Frontal Reward and Regulatory Regions in Cannabis-Dependent Males. Human Brain Mapping, 39, 5062-5073.[CrossRef] [PubMed]