PDF(Pubmed)
Abstract：
It remains a pressing concern to understand how neural computations relate to risky decisions. However, most observations of brain-behavior relationships in the risk-taking domain lack a rigorous computational basis or fail to emulate of the dynamic, sequential nature of real-life risky decision-making. Recent advances emphasize the role of neural prediction error (PE) signals. We modeled, according to prospect theory, the choices of n = 43 human participants (33 females, 10 males) performing an EEG version of the hot Columbia Card Task, featuring rounds of sequential decisions between stopping (safe option) and continuing with increasing odds of a high loss (risky option). Single-trial regression EEG analyses yielded a subjective value signal at centroparietal (300-700 ms) and frontocentral (>800 ms) electrodes and in the delta band, as well as PE signals tied to the feedback-related negativity, P3a, and P3b, and in the theta band. Higher risk preference (total number of risky choices) was linked to attenuated subjective value signals but increased PE signals. Higher P3-like activity associated with the most positive PE in each round predicted stopping in the present round but not risk-taking in the subsequent round. Our findings indicate that decreased representation of decision values and increased sensitivity to winning despite low odds (positive PE) facilitate risky choices at the subject level. Strong neural responses when gains are least expected (the most positive PE on each round) adaptively contribute to safer choices at the trial-by-trial level but do not affect risky choice at the round-by-round level.
摘要：
了解神经计算与风险决策的关系仍然是一个紧迫的问题。然而,在冒险领域中，大多数对大脑行为关系的观察缺乏严格的计算基础或无法模拟动态，现实生活中风险决策的顺序性质。最近的进展强调了神经预测误差(PE)信号的作用。我们建模，根据前景理论，n=43名人类参与者的选择(33名女性，十名男性）执行脑电图版本的热门哥伦比亚卡片任务，具有在停止（安全选项）和继续增加高损失（风险选项）的几率之间的连续决策回合。单试验回归EEG分析在中心顶叶（300-700ms）和额中央（>800ms）电极以及δ波段产生了主观值信号，以及与反馈相关的负性相关的PE信号，P3a,P3b,在θ带。较高的风险偏好（风险选择的总数）与主观价值信号减弱但PE信号增加有关。与每一轮中最积极的PE相关的更高的P3样活性预测在本轮中停止,但在下一轮中不冒险。我们的发现表明，尽管赔率较低（积极的PE），但决策值的代表性降低和对获胜的敏感性增加，有助于在受试者水平上进行风险选择。当预期收益最少（每轮上最积极的PE）时，强烈的神经反应自适应地有助于在逐个试验水平上进行更安全的选择，但在逐次水平上不影响风险选择显著性陈述仍然是一个悬而未决的问题，在心理健康方面最紧迫的是，神经计算如何促进现实生活中的危险行为(例如饮酒，犯罪活动)。这一努力需要严格的计算基础以及模拟动态的范式，现实生活中冒险的顺序性质。我们应用前景理论对顺序相关的风险选择和主观决策值和意外收益（预测误差）的孤立神经关联进行建模。这使我们能够证明总体风险承担与过度活跃的预测误差和减少的决策值信号有关。此外，受试者在对最低预期增益的较高神经反应后反应更加谨慎.这些发现表明多层，预测误差处理的独立角色，在试验层面调解更安全的选择，但在受试者层面调解风险倾向。
