The neural basis of following advice.
The neural basis of following advice.
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DOI：
10.1371/journal.pbio.1001089
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发表时间：
2011-06
期刊：
影响因子：
9.8
通讯作者：
Heekeren HR
中科院分区：
文献类型：
--
作者：
Biele G;Rieskamp J;Krugel LK;Heekeren HR
通过遵循明确的建议来学习是人类文化进化的基础，但适应性社会学习的神经生物学在很大程度上是未知的。在这里，我们使用模拟来分析社会学习机制的适应性价值，行为数据的计算建模来描述社会学习中涉及的认知机制，以及基于模型的功能性磁共振成像（fMRI）来识别遵循建议的神经生物学基础。在学习前接受一次性建议对人们的学习过程有持续的影响。这一点最好的解释是，社会学习机制对推荐选项的结果进行了更积极的评估。计算机模拟表明，这种“结果奖金”积累了更多的奖励比替代机制实施更高的初始奖励期望的推荐选项。功能磁共振成像结果显示，在隔区和左侧尾状核的神经结果奖金信号。在没有建议的情况下，这种神经信号会对奖励进行编码，而且至关重要的是，它在推荐后而不是在非推荐选择后，对积极和消极的反馈发出了更大的积极奖励。因此，我们的研究结果表明，遵循建议本质上是有益的。正反馈后，模型的结果奖金参数与杏仁核活动之间的正相关性直接将计算模型与大脑活动联系起来。这些结果通过为从建议中进行适应性学习提供神经生物学解释，推进了对社会学习的理解。通过遵循建议来学习是人类文化进化的基础。然而，大脑是如何执行建议以获得最大回报的，这在很大程度上是未知的。在这里，我们使用功能性磁共振成像（fMRI）和行为实验来研究人们如何使用一次性建议。我们发现，建议有一个持续的影响选择和调制学习在两个方面。首先，与会者最初认为建议的备选办法最有益。第二，也是更重要的是，在遵循建议后获得的收益和损失获得了“成果奖金”，其中对它们的评价比不遵循建议后更积极。换句话说，听从建议通常是有益的。计算机模拟表明，结果奖金是自适应的，因为它受益于好的建议，限制了坏建议的影响。功能性磁共振成像分析显示，在隔区和左尾状核中存在一个神经结果奖励信号，这些结构以前与基于信任和奖励的学习有关。结果奖金更高的参与者在遵循杏仁核的建议后表现出更大的增益信号增加，杏仁核是一种与处理情绪和社会信息有关的结构。总之，这些结果表明，决策者自适应地结合联合收割机的建议和个人学习的社会学习机制，其中建议调节神经奖励反应。
Learning by following explicit advice is fundamental for human cultural evolution, yet the neurobiology of adaptive social learning is largely unknown. Here, we used simulations to analyze the adaptive value of social learning mechanisms, computational modeling of behavioral data to describe cognitive mechanisms involved in social learning, and model-based functional magnetic resonance imaging (fMRI) to identify the neurobiological basis of following advice. One-time advice received before learning had a sustained influence on people's learning processes. This was best explained by social learning mechanisms implementing a more positive evaluation of the outcomes from recommended options. Computer simulations showed that this “outcome-bonus” accumulates more rewards than an alternative mechanism implementing higher initial reward expectation for recommended options. fMRI results revealed a neural outcome-bonus signal in the septal area and the left caudate. This neural signal coded rewards in the absence of advice, and crucially, it signaled greater positive rewards for positive and negative feedback after recommended rather than after non-recommended choices. Hence, our results indicate that following advice is intrinsically rewarding. A positive correlation between the model's outcome-bonus parameter and amygdala activity after positive feedback directly relates the computational model to brain activity. These results advance the understanding of social learning by providing a neurobiological account for adaptive learning from advice. Learning by following advice is fundamental for human cultural evolution. Yet it is largely unknown how the brain implements advice-taking in order to maximize rewards. Here, we used functional magnetic resonance imaging (fMRI) and behavioral experiments to study how people use one-off advice. We find that advice had a sustained effect on choices and modulated learning in two ways. First, participants initially assumed that the recommended option was most beneficial. Second, and more importantly, gains and losses obtained after following advice received an “outcome-bonus,” in which they were evaluated more positively than after not following advice. In other words, following advice was in general intrinsically rewarding. Computer simulations showed that the outcome-bonus is adaptive, because it benefits from good advice and limits the effect of bad advice. The fMRI analysis revealed a neural outcome-bonus signal in the septal area and left caudate head, structures previously implicated in trust and reward based learning. Participants with greater outcome-bonuses showed a greater gain-signal increase after following advice in the amygdala, a structure implicated in processing emotions and social information. In sum, these results suggest that decision makers adaptively combine advice and individual learning with a social learning mechanism in which advice modulates the neural reward response.
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