Integration of individual and social information for decision-making in groups of different sizes

When making judgments in a group, individuals often revise their initial beliefs about the best judgment to make given what others believe. Despite the ubiquity of this phenomenon, we know little about how the brain updates beliefs when integrating personal judgments (individual information) with those of others (social information). Here, we investigated the neurocomputational mechanisms of how we adapt our judgments to those made by groups of different sizes, in the context of jury decisions for a criminal. By testing different theoretical models, we showed that a social Bayesian inference model captured changes in judgments better than 2 other models. Our results showed that participants updated their beliefs by appropriately weighting individual and social sources of information according to their respective credibility. When investigating 2 fundamental computations of Bayesian inference, belief updates and credibility estimates of social information, we found that the dorsal anterior cingulate cortex (dACC) computed the level of belief updates, while the bilateral frontopolar cortex (FPC) was more engaged in individuals who assigned a greater credibility to the judgments of a larger group. Moreover, increased functional connectivity between these 2 brain regions reflected a greater influence of group size on the relative credibility of social information. These results provide a mechanistic understanding of the computational roles of the FPC-dACC network in steering judgment adaptation to a group’s opinion. Taken together, these findings provide a computational account of how the human brain integrates individual and social information for decision-making in groups.

当在群体中开展判断决策时，个体往往会根据他人所持信念，修正自身原本认定的最优判断的初始想法。尽管这一现象极为普遍，但我们对大脑在整合个人判断（个体信息）与他人判断（社会信息）的过程中如何更新信念，仍所知有限。本研究以刑事案件的陪审团决策为研究情境，探究了我们如何调整自身判断以适配不同规模群体所做判断的神经计算机制。通过检验不同理论模型，我们发现社会贝叶斯推理模型（social Bayesian inference model）相较于其余两种模型，更能精准捕捉判断的变化过程。研究结果显示，参与者会依据个体与社会信息来源各自的可信度，对二者施以恰当的权重分配，以此更新自身信念。在探究贝叶斯推理的两项核心计算——信念更新与社会信息可信度评估时，我们发现背侧前扣带回皮层（dorsal anterior cingulate cortex, dACC）负责计算信念更新的程度，而双侧额极皮层（bilateral frontopolar cortex, FPC）在那些更倾向于赋予大规模群体判断更高可信度的个体中，激活程度更为显著。此外，这两个脑区间的功能连接强度增强，反映出群体规模对社会信息相对可信度的影响程度更大。上述结果为阐释额极皮层-前扣带回网络（FPC-dACC network）在引导个体根据群体观点调整判断时所承担的计算角色，提供了机制层面的见解。总而言之，这些发现为人脑在群体决策中整合个体与社会信息的过程，提供了计算层面的理论阐释。