In search of reward: Are prediction errors metabolically scaled in women and men?

寻找奖励：预测误差在女性和男性中是否存在代谢差异？

• 批准号: 468068857
• 负责人: Professorin Dr. Birgit Derntl
• 金额: --
• 依托单位: Abteilung Allgemeine Psychiatrie und Psychotherapie mit Poliklinik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/468068857?language=en
• 关键词: search; reward; prediction; errors; metabolically

Discovering novel sources of food is one of the key challenges for any foraging animal. Although it is well-established that metabolic states shape motivation as hungry animals are more eager to attain rewards, the role of hunger in human reward learning is largely elusive. Likewise, despite emerging evidence on altered reward learning in obesity, the putative mechanisms are still largely unknown, and striking inconsistencies in the literature hamper progress towards a unified theory. Here, we propose to address this gap by conducting an extensive assessment of dopamine-dependent reward learning as a function of metabolic states (“deep phenotyping”) in women and men. To this end, using a newly developed smartphone game, we will repeatedly assess reinforcement learning for food and monetary rewards in 80 participants over one month (i.e. one menstrual cycle in women). Concurrently, we will record glucose levels via continuous glucose monitoring to capture modulations by glycemic states. We will complement these detailed recordings by two neuroimaging sessions, where we manipulate metabolic states and assess changes in reward prediction error signals using fMRI. Based on preliminary evidence and preclinical research, we predict that a hungry state is associated with higher learning rates and quicker decreases of prediction errors for new action contingencies. Moreover, we predict that this “hunger edge” in learning is blunted in overweight/obesity (Metabolic State × BMI interaction). Critically, we will capitalize on amplified hormonal and metabolic fluctuations in women by examining to what extent reward signals are metabolically scaled across the menstrual cycle. We expect that if changes in energy metabolism are linked to changes in reward learning, then greater fluctuations in estradiol and progesterone would be echoed in reward learning as well. Collectively, the proposed project would shed new light on a key mechanism linking learning and motivation with metabolic demands via dopamine transmission. Further insights into vital differences in reward learning due to changes in energy metabolism may help improve the treatment of women and men suffering from disorders characterized by altered reward function such as obesity. By detailing potential sex and cycle effects on the metabolic scaling of reward signals, the proposed project may also provide novel insights into the etiology of eating or mood disorders.

寻找新的食物来源是任何觅食动物面临的关键挑战之一。虽然新陈代谢状态塑造动机是众所周知的，因为饥饿的动物更渴望获得奖励，但饥饿在人类奖励学习中的作用在很大程度上是难以捉摸的。同样，尽管出现了肥胖症奖赏学习改变的证据，但推测的机制仍然很大程度上是未知的，文献中惊人的不一致阻碍了朝着统一理论的进展。在这里，我们建议通过对女性和男性的代谢状态(“深层表型”)对多巴胺依赖的奖赏学习进行广泛的评估来解决这一差距。为此，使用一款新开发的智能手机游戏，我们将在一个月内反复评估80名参与者在食物和金钱奖励方面的强化学习(即女性的一个月经周期)。同时，我们将通过持续的血糖监测记录血糖水平，以捕捉血糖状态的调节。我们将通过两个神经成像会议来补充这些详细的记录，在这两个会议中，我们操纵新陈代谢状态，并使用功能磁共振成像评估奖励预测误差信号的变化。基于初步证据和临床前研究，我们预测饥饿状态与更高的学习率和更快地减少新动作偶发事件的预测误差有关。此外，我们预测，学习中的这种“饥饿边缘”在超重/肥胖(新陈代谢状态×体重指数交互作用)中变得迟钝。关键的是，我们将通过检查奖励信号在月经周期中代谢变化的程度来利用女性荷尔蒙和代谢的放大波动。我们预计，如果能量代谢的变化与奖赏学习的变化有关，那么雌二醇和黄体酮的更大波动也将在奖赏学习中得到回应。总的来说，拟议的项目将为通过多巴胺传递将学习和动机与新陈代谢需求联系起来的关键机制提供新的线索。进一步深入了解能量代谢变化导致的奖赏学习的重要差异，可能有助于改善以肥胖等奖赏功能改变为特征的女性和男性的治疗。通过详细说明性别和周期对奖励信号代谢比例的潜在影响，拟议的项目还可能为饮食或情绪障碍的病因提供新的见解。