Aberg Kristoffer C, Müller Julia, Schwartz Sophie
Department of Neuroscience, Faculty of Medicine, University of GenevaGeneva, Switzerland; Swiss Center for Affective Sciences, University of GenevaGeneva, Switzerland; Geneva Neuroscience Center, University of GenevaGeneva, Switzerland.
Front Hum Neurosci. 2017 Feb 15;11:56. doi: 10.3389/fnhum.2017.00056. eCollection 2017.
Anticipation and delivery of rewards improves memory formation, but little effort has been made to disentangle their respective contributions to memory enhancement. Moreover, it has been suggested that the effects of reward on memory are mediated by dopaminergic influences on hippocampal plasticity. Yet, evidence linking memory improvements to actual reward computations reflected in the activity of the dopaminergic system, i.e., prediction errors and expected values, is scarce and inconclusive. For example, different previous studies reported that the magnitude of prediction errors during a reinforcement learning task was a positive, negative, or non-significant predictor of successfully encoding simultaneously presented images. Individual sensitivities to reward and punishment have been found to influence the activation of the dopaminergic reward system and could therefore help explain these seemingly discrepant results. Here, we used a novel associative memory task combined with computational modeling and showed independent effects of reward-delivery and reward-anticipation on memory. Strikingly, the computational approach revealed positive influences from both reward delivery, as mediated by prediction error magnitude, and reward anticipation, as mediated by magnitude of expected value, even in the absence of behavioral effects when analyzed using standard methods, i.e., by collapsing memory performance across trials within conditions. We additionally measured trait estimates of reward and punishment sensitivity and found that individuals with increased reward (vs. punishment) sensitivity had better memory for associations encoded during positive (vs. negative) prediction errors when tested after 20 min, but a negative trend when tested after 24 h. In conclusion, modeling trial-by-trial fluctuations in the magnitude of reward, as we did here for prediction errors and expected value computations, provides a comprehensive and biologically plausible description of the dynamic interplay between reward, dopamine, and associative memory formation. Our results also underline the importance of considering individual traits when assessing reward-related influences on memory.
奖励的预期与给予可改善记忆形成，但在区分它们对记忆增强的各自贡献方面所做的努力甚少。此外，有观点认为奖励对记忆的影响是通过多巴胺能对海马可塑性的影响来介导的。然而，将记忆改善与多巴胺能系统活动中反映的实际奖励计算（即预测误差和期望值）联系起来的证据却很稀少且尚无定论。例如，先前不同的研究报告称，强化学习任务期间预测误差的大小是成功编码同时呈现图像的正向、负向或无显著意义的预测指标。已发现个体对奖励和惩罚的敏感度会影响多巴胺能奖励系统的激活，因此有助于解释这些看似矛盾的结果。在此，我们使用了一种新颖的联想记忆任务并结合计算建模，展示了奖励给予和奖励预期对记忆的独立影响。引人注目的是，计算方法揭示了由预测误差大小介导的奖励给予以及由期望值大小介导的奖励预期均产生了积极影响，即使在使用标准方法（即在各条件下将跨试验的记忆表现合并分析）进行分析时没有行为效应。我们还测量了奖励和惩罚敏感度的特质估计值，发现奖励（相对于惩罚）敏感度增加的个体在20分钟后进行测试时，对在正向（相对于负向）预测误差期间编码的联想记忆更好，但在24小时后进行测试时呈负向趋势。总之，正如我们在此针对预测误差和期望值计算所做的那样，对奖励大小的逐次试验波动进行建模，提供了对奖励、多巴胺和联想记忆形成之间动态相互作用的全面且具有生物学合理性的描述。我们的结果还强调了在评估奖励对记忆的相关影响时考虑个体特质的重要性。
