人际视角下的建议互动:决策、社会认知过程与计算神经机制

Interpersonal advice interaction:Decision-making,social cognition processes,and neurocomputational mechanisms

建议互动是信息和影响力在社会传播的重要基石之一.近年来,越来越多的研究开始关注决策者与建议者之间的相互影响,但这种影响的内在过程尚不清晰.从人际互动的角度出发,我们尝试构建了一个整合建议双方行为与社会认知过程的人际影响模型:建议者和决策者分别通过提供建议信息和对建议进行反馈相互影响.这种影响通过社会认知过程被各自内化、更新了决策者对建议者可靠性的信念和建议者对自身的社会影响力的信念,以及对彼此的社会态度.这些社会认知结果进一步指导了决策者后续的建议采纳倾向和决策优化结果,以及建议者随后的建议策略与建议准确性.同时,受影响的决策、建议行为又产生新的建议反馈和建议信息影响对方.在这些过程中,奖赏加工、心理理论加工和自我监控发挥了关键作用.具体来说,建议采纳过程和建议者对自身影响力的信念更新主要涉及奖赏相关的认知计算和神经表征;决策者对建议者可靠性的信念更新和建议提出过程涉及与社会学习相关的计算过程,并伴随着心理理论相关脑区的激活;此外,自我监控加工也参与了建议者的建议策略的使用过程.总之,本文为揭示建议互动中双方的行为以及认知加工(如信念更新、决策权衡)的内在机理提供了启示.未来研究还需进一步通过人际神经科学、计算建模等手段探索建议互动双方复杂的社会信念和互动动机如何整合,进而影响社会行为.

The dynamic processes of giving and taking advice(so-called“advice interaction”)is one of the fundamental cornerstones of how information and social influence are spread in society.During advice interaction,advisors(i.e.,those giving advice)not only exert unilateral influence over advisees(i.e.,those seeking advice),but the response of advisees towards the advice also have a counteractive effect on shaping subsequent advice-giving behavior.While recent studies have started investigating the relationships between the behaviors of advisors and advisees,there is still a lack of comprehensive understanding regarding the mechanical processes that drive these interactions.This review aims to develop an interpersonal influence model that elucidates the dynamic relationship between advisees and advisors,highlighting the prevalent link between their behavioral outcomes and cognitive processes.To this end,we undertake a simultaneous review of two sub-processes inherent in both advice-taking and advice-giving:(1)Decisionmaking and(2)social cognition.During the advice-taking process,advisees primarily rely on and benefit from advice based on their perception of the advisor’s reliability.Consequently,advisees update their beliefs about the advisor’s reliability through social learning,considering the advisor’s expertise and intentions.In the advice-giving process,advisors offer cautious or overconfident,beneficial or misleading advice depending on their perception of their own influence and the level of respect they receive from advisees.Moreover,by monitoring the feedback(i.e.,acceptance or rejection)of their advice from advisees,advisors consistently revise their perception of influence and adjust their attitudes and evaluations of advisees accordingly.Furthermore,we review the computational and neural mechanisms involved in the sub-processes of advice taking and giving,shedding light on the cognitive processes underlying interpersonal advice interactions.Empirical studies indicate that during advice taking,advisees dynamically consider both advice and their own opinions,while monitoring the outcomes of implementing the advice.The rewarding neural system plays a crucial role in guiding advisees towards achieving favorable decision outcomes.Additionally,advisees track advisors’expertise and intentions following reinforcement-learning and Bayesian-learning rules,activating neural regions associated with Theory of Mind.This enables individuals to decipher social information and make more accurate decisions.On the other hand,advisors provide advice based on their beliefs about their current influence,requiring social inference from advisees’feedback.Therefore,Theory of Mind and self-monitoring neural mechanisms are significantly activated when advisors give advice.Advisors receive feedback on their advice,which they use to infer the level of their influence,making it a reward learning process that evokes neural representations related to reward processing.In summary,our theoretical model framework proposes a reciprocal influence between advisors and advisees during advice interactions.This influence is manifested through the exchange of advice and the subsequent feedback.These reciprocal influences are internalized and lead to updates in social cognition,specifically in terms of beliefs about the advisor’s reliability and their impact on the advisee.These updated beliefs,in turn,shape future behaviors in giving and taking advice,as well as the overall relationship between the advisee and advisor.Crucial roles in these processes are played by reward processing,Theory of Mind,and self-monitoring.To gain a deeper understanding of how individuals integrate social beliefs and motivations to generate social behavior during advice interactions,future research should explore the use of interdisciplinary approaches such as interpersonal neuroscience and computational modeling.