Laboratory for Integrated Theoretical Neuroscience, RIKEN Center for Brain Science, Wako 351-0198, Japan.
Research Center for Life Sciences Computing, Zhejiang Laboratory, Hangzhou 311100, China.
J Neurosci. 2024 Sep 11;44(37):e2236232024. doi: 10.1523/JNEUROSCI.2236-23.2024.
For better decisions in social interactions, humans often must understand the thinking of others and predict their actions. Since such predictions are uncertain, multiple predictions may be necessary for better decision-making. However, the neural processes and computations underlying such social decision-making remain unclear. We investigated this issue by developing a behavioral paradigm and performing functional magnetic resonance imaging and computational modeling. In our task, female and male participants were required to predict others' choices in order to make their own value-based decisions, as the outcome depended on others' choices. Results showed, to make choices, the participants mostly relied on a value difference (primary) generated from the case where others would make a likely choice, but sometimes they additionally used another value difference (secondary) from the opposite case where others make an unlikely choice. We found that the activations in the posterior cingulate cortex (PCC) correlated with the primary difference while the activations in the right dorsolateral prefrontal cortex (rdlPFC) correlated with the secondary difference. Analysis of neural coupling and temporal dynamics suggested a three-step processing network, beginning with the left amygdala signals for predictions of others' choices. Modulated by these signals, the PCC and rdlPFC reflect the respective value differences for self-decisions. Finally, the medial prefrontal cortex integrated these decision signals for a final decision. Our findings elucidate the neural process of constructing value-based decisions by predicting others and illuminate their key variables with social modulations, providing insight into the differential functional roles of these brain regions in this process.
为了在社交互动中做出更好的决策,人类通常必须理解他人的思维并预测他们的行为。由于这种预测具有不确定性,因此可能需要多次预测才能做出更好的决策。然而,支持这种社会决策的神经过程和计算仍然不清楚。我们通过开发行为范式并进行功能磁共振成像和计算建模来研究这个问题。在我们的任务中,女性和男性参与者需要预测他人的选择,以便做出自己基于价值的决策,因为结果取决于他人的选择。结果表明,为了做出选择,参与者主要依赖于从他人可能做出选择的情况下产生的价值差异(主要差异),但有时他们还会从他人做出不太可能选择的相反情况下使用另一个价值差异(次要差异)。我们发现,后扣带皮层(PCC)的激活与主要差异相关,而右侧背外侧前额叶皮层(rdlPFC)的激活与次要差异相关。神经耦合和时间动态分析表明,存在一个三步骤处理网络,从左杏仁核信号预测他人的选择开始。这些信号的调制作用下,PCC 和 rdlPFC 反映了自我决策的相应价值差异。最后,内侧前额叶皮层整合了这些决策信号以做出最终决策。我们的研究结果阐明了通过预测他人来构建基于价值的决策的神经过程,并阐明了他们具有社会调节作用的关键变量,为这些大脑区域在这个过程中的差异功能作用提供了深入了解。