The neurocomputational basis of mood-reward dynamics

情绪奖励动力学的神经计算基础

• 批准号: 526147109
• 负责人: Dr. Jochen Michely
• 金额: --
• 依托单位: Klinik für Psychiatrie und Psychotherapie (CCM)
• 依托单位国家: 德国
• 项目类别: Independent Junior Research Groups
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/526147109?language=en
• 关键词: neurocomputational; basis; mood; reward; dynamics

Most, if not all of us, go through periods of feeling happy or blue. Mood swings are a core feature of everyday life and not tantamount to the existence of mental illness. However, excessive or prolonged moodiness can lead to a serious mood disorder, above all depression, which is one of modern society’s most challenging and costly health burdens. Mood may be shaped by experience, such as reward or punishment. For instance, a smile from a stranger on the bus may brighten our day, whilst losing a tennis match may make us feel low. Our mood, however, may also influence how we perceive an experience. For example, imagine getting ticked off by your boss when beaming with joy, e.g., right after winning the lottery, or alternatively, in the middle of a bad day, e.g., after a grant rejection. In other words, outcomes, such as reward and punishment, impact on mood, and mood, in turn, shapes sensitivity to future outcomes. Yet, despite the importance of bidirectional feedback dynamics between mood and reward sensitivity, we know little about their neurobiological underpinnings and their role in the treatment of mental illness. The overarching goal of this project is to provide a mechanistic account of the neurobiology of such mood-reward dynamics in humans – with a focus on the treatment of mood disorders, such as depression. Applying state-of-the-art methods in cognitive computational neuroscience, I will answer the following research questions: (1) How, and where, are bidirectional influences between mood and reward sensitivity represented in the healthy brain? (2) Are these neurobiological processes altered in mood disorders, and does this relate to symptoms of depression? (3) How can we modulate these processes with different types of drugs, and can we use this knowledge to improve depression therapy? To address these questions, I will use a multimodal approach of cognitive experiments, functional neuroimaging, psychopharmacology, and computational modelling. This project will provide a neurocomputational framework for understanding mood swings in health and psychiatric illness. Further, it promises to provide neurocognitive markers for identifying individuals at-risk for depression, and antidepressant treatment response, that can be tested in large-scale clinical trials in the future. Ultimately, by bridging a gap between basic neuroscience research and clinical psychiatry, this project has the potential to transform how we diagnose, and treat, the most common form of mental illness.

大多数人，如果不是所有人，都会经历快乐或忧郁的时期。情绪波动是日常生活的核心特征，并不等同于精神疾病的存在。然而，过度或长期的喜怒无常会导致严重的情绪紊乱，尤其是抑郁症，这是现代社会最具挑战性和代价最高的健康负担之一。情绪可能是由经验塑造的，比如奖励或惩罚。例如，在公交车上一个陌生人的微笑可能会让我们的一天变得光明，而输掉一场网球比赛可能会让我们感到情绪低落。然而，我们的情绪也可能会影响我们对一种体验的看法。例如，想象一下，当你和喜悦一起微笑时，比如刚刚中了彩票，或者在糟糕的一天中，比如拨款被拒绝之后，被老板责备。换句话说，结果，如奖励和惩罚，对情绪的影响，以及情绪，反过来又塑造了对未来结果的敏感性。然而，尽管情绪和奖励敏感性之间的双向反馈动力学很重要，但我们对它们的神经生物学基础以及它们在精神疾病治疗中的作用知之甚少。该项目的总体目标是为人类这种情绪奖赏动态的神经生物学提供一个机械性的描述，重点是情绪障碍的治疗，如抑郁症。应用认知计算神经科学中最先进的方法，我将回答以下研究问题：(1)在健康的大脑中，情绪和奖励敏感性之间的双向影响是如何以及在哪里表现出来的？(2)这些神经生物学过程在情绪障碍中是否发生了变化，这与抑郁症的症状有关吗？(3)我们如何用不同类型的药物来调节这些过程，我们能否利用这些知识来改进抑郁症的治疗？为了解决这些问题，我将使用认知实验、功能神经成像、精神药理学和计算模型的多模式方法。该项目将提供一个神经计算框架，用于理解健康和精神疾病中的情绪波动。此外，它还承诺提供神经认知标记物，用于识别有抑郁风险的个人，以及抗抑郁药物治疗反应，这些可以在未来的大规模临床试验中进行测试。最终，通过弥合基础神经科学研究和临床精神病学之间的差距，这个项目有可能改变我们诊断和治疗最常见的精神疾病的方式。