State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing 100875, China.
Cereb Cortex. 2023 Apr 4;33(8):4612-4625. doi: 10.1093/cercor/bhac365.
Cooperation is fundamental for survival and a functioning society. With substantial individual variability in cooperativeness, we must learn whom to cooperate with, and often make these decisions on behalf of others. Understanding how people learn about the cooperativeness of others, and the neurocomputational mechanisms supporting this learning, is therefore essential. During functional magnetic resonance imaging scanning, participants completed a novel cooperation-partner-choice task where they learned to choose between cooperative and uncooperative partners through trial-and-error both for themselves and vicariously for another person. Interestingly, when choosing for themselves, participants made faster and more exploitative choices than when choosing for another person. Activity in the ventral striatum preferentially responded to prediction errors (PEs) during self-learning, whereas activity in the perigenual anterior cingulate cortex (ACC) signaled both personal and vicarious PEs. Multivariate pattern analyses showed distinct coding of personal and vicarious choice-making and outcome processing in the temporoparietal junction (TPJ), dorsal ACC, and striatum. Moreover, in right TPJ the activity pattern that differentiated self and other outcomes was associated with individual differences in exploitation tendency. We reveal neurocomputational mechanisms supporting cooperative learning and show that this learning is reflected in trial-by-trial univariate signals and multivariate patterns that can distinguish personal and vicarious choices.
合作是生存和社会运转的基础。由于合作意愿存在个体差异，我们必须学会与谁合作，并且经常要代表他人做出这些决定。因此，了解人们如何了解他人的合作意愿以及支持这种学习的神经计算机制至关重要。在功能磁共振成像扫描过程中，参与者完成了一项新颖的合作伙伴选择任务，他们通过试错学习为自己和他人选择合作和不合作的伙伴。有趣的是，当为自己选择时，参与者比为他人选择时做出更快、更具剥削性的选择。腹侧纹状体在自我学习时优先对预测误差（PE）做出反应，而前扣带皮层（ACC）的旁正中区（peri-genual ACC）则对个人和他人的 PE 均有信号反应。多元模式分析显示，颞顶联合区（TPJ）、背侧 ACC 和纹状体中存在个人和他人决策以及结果处理的独特编码。此外，右侧 TPJ 中区分自我和他人结果的活动模式与个体差异的剥削倾向有关。我们揭示了支持合作学习的神经计算机制，并表明这种学习反映在逐次的单变量信号和多元模式中，可以区分个人和他人的选择。
