Neural differentiation of expected reward and risk in human subcortical structures
Neural differentiation of expected reward and risk in human subcortical structures
复制标题
DOI：
10.1016/j.neuron.2006.06.024
复制
发表时间：
2006-08-03
期刊：
影响因子：
16.2
通讯作者：
Quartz, Steven R.
中科院分区：
文献类型：
--
作者：
Preuschoff, Kerstin;Bossaerts, Peter;Quartz, Steven R.
在不确定条件下的决策中，经济学研究除了强调预期回报外，还强调风险的重要性。神经科学研究关注的是预期回报和学习，而不是风险。我们将功能成像与一个简单的赌博任务结合起来，以不相关的方式同时改变预期的回报和风险。利用财务决策理论，我们将期望报酬建模为数学上的报酬期望，将风险建模为报酬方差。多巴胺感觉结构的激活与这两个数学参数相关。这些激活在空间和时间上存在差异。在时间上，与预期奖励相关的激活是即时的，而与风险相关的激活是延迟的。分析证实，我们的范式最大限度地减少了学习、动机和突出性带来的混淆。这些结果表明，多巴胺能系统的主要任务是传递即将到来的随机奖励的信号，如预期的奖励和风险，而不是它在学习、动机和突出性方面的作用。
In decision-making under uncertainty, economic studies emphasize the importance of risk in addition to expected reward. Studies in neuroscience focus on expected reward and learning rather than risk. We combined functional imaging with a simple gambling task to vary expected reward and risk simultaneously and in an uncorrelated manner. Drawing on financial decision theory, we modeled expected reward as mathematical expectation of reward, and risk as reward variance. Activations in dopaminoceptive structures correlated with both mathematical parameters. These activations differentiated spatially and temporally. Temporally, the activation related to expected reward was immediate, while the activation related to risk was delayed. Analyses confirmed that our paradigm minimized confounds from learning, motivation, and salience. These results suggest that the primary task of the dopaminergic system is to convey signals of upcoming stochastic rewards, such as expected reward and risk, beyond its role in learning, motivation, and salience.