价值计算决定何时与如何努力

优化努力的分配, 最小化努力成本和最大化收益是各个领域的关键问题。本文梳理了基于努力的决策(effort-based decision-making)的理论与实证研究, 讨论了努力的两面性：固有成本和潜在价值。通过拓展控制期望价值理论(Expected Value of Control, EVC), 本研究探讨了影响努力的非社会与社会因素。探索人们何时以及如何付出努力的计算神经机制, 有利于理解与促进社会互动中的努力行为, 以及为干预精神疾病中动机缺失症状提供参考。

Value Analysis determines when and how to strive

The optimization of effort investment, which minimizes the cost of effort and maximizes benefits, is a core issue in every field. “What factors influence how much effort we invest?” is gaining more and more attention. This study aims to review previous theoretical and empirical studies on effort. Based on the Paradox of Effort theory, this study expounds on the two sides of effort: inherent cost and potential value. Even though there are intrinsic costs associated with effort, the concept of effort solely in terms of costs is inadequate. The Paradox of Effort theory indicates that analyzing the value of effort at different time stages is more in line with daily activities. The key to effort-based decision-making is weighing the rewards and effort required to accomplish a goal. On this basis, we discussed the non-social and social factors and the neural mechanisms involved in effort investment according to the Expected Value of Control (EVC) theory. EVC theory discusses models of effort optimization in terms of conflict monitoring, cost-benefit integration of cognitive control, and implementation of control, emphasizing the role of integrating the expected value in the dorsal anterior cingulate cortex. Both social and non-social factors have impacts on the adaptive control allocation during the integration, but few empirical studies have explored the two-level interaction. Therefore, we developed the topic of cost-benefit analysis in EVC theory and highlighted its application to motivational behavior in social circumstances, which is conducive to exploring the plasticity of social behavior. The cognitive and neural mechanisms of effort play an essential role in understanding the adaptive allocation of effort in social life and provide references for treating motivational disorders, shaping learned industriousness and prosocial behavior. Future research needs to explore the adaptive changes in the expected value of control during the dynamic process using methods of neurophysiology and combine computational modeling to complement and validate the EVC theory in social contexts.