Vanni-Mercier Giovanna, Mauguière François, Isnard Jean, Dreher Jean-Claude
Center for Cognitive Neuroscience, Reward and Decision Making Group, CNRS, UMR 5229, Université Lyon 1, 69675 Bron Cedex, France.
J Neurosci. 2009 Apr 22;29(16):5287-94. doi: 10.1523/JNEUROSCI.5298-08.2009.
Learning to predict upcoming outcomes based on environmental cues is essential for adaptative behavior. In monkeys, midbrain dopaminergic neurons code two statistical properties of reward: a prediction error at the outcome and uncertainty during the delay period between cues and outcomes. Although the hippocampus is sensitive to reward processing, and hippocampal-midbrain functional interactions are well documented, it is unknown whether it also codes the statistical properties of reward information. To address this question, we recorded local field potentials from intracranial electrodes in human hippocampus while subjects learned to associate cues of slot machines with various monetary reward probabilities (P). We found that the amplitudes of negative event-related potentials covaried with uncertainty at the outcome, being maximal for P = 0.5 and minimal for P = 0 and P = 1, regardless of winning or not. These results show that the hippocampus computes an uncertainty signal that may constitute a fundamental mechanism underlying the role of this brain region in a number of functions, including attention-based learning, associative learning, probabilistic classification, and binding of stimulus elements.
学会根据环境线索预测即将到来的结果对于适应性行为至关重要。在猴子中,中脑多巴胺能神经元编码奖励的两种统计特性:结果时的预测误差以及线索与结果之间延迟期的不确定性。尽管海马体对奖励处理敏感,并且海马体与中脑的功能相互作用已有充分记录,但尚不清楚它是否也编码奖励信息的统计特性。为了解决这个问题,我们在人类海马体中通过颅内电极记录局部场电位,同时让受试者学习将老虎机的线索与各种货币奖励概率(P)相关联。我们发现,负性事件相关电位的振幅与结果时的不确定性共变,无论输赢,在P = 0.5时最大,在P = 0和P = 1时最小。这些结果表明,海马体计算出一种不确定性信号,这可能构成该脑区在许多功能中发挥作用的基本机制,这些功能包括基于注意力的学习、联想学习、概率分类以及刺激元素的绑定。