Differentiating reward seeking and loss avoidance with reference-dependent learning models

项目摘要 正价和负价之间的区别是精神病学的核心。一个看似绝对的 对许多人来说，追求奖励与避免惩罚的努力之间的区别似乎是核心 精神障碍的症状，在诊断类别的划分和 RDoC中交叉诊断构造的定义。然而，尽管在这方面取得了重大进展， 了解奖励如何驱动学习和行动，以及潜在的神经机制，已经有 在理解损失和惩罚影响行为的机制方面，进展要少得多。的确， 关于奖赏和损失的神经机制是否是 完全不合群。关于寻求回报和避免损失的神经基础的研究结果喜忧参半。 结果，表现在关于共享和分离神经回路的不一致发现，以及令人惊讶的 在精神病人群中的结果，例如，在精神病患者中显示奖励处理异常 表面上看来是由回避引起的情况(如强迫症和焦虑)。这件事已经做到了 几乎不可能解决为寻求回报与损失定义有效衡量标准的关键问题 单独回避，更不用说理解它们之间的平衡以及它们与他人的关系了 次元结构和精神病理学。在这里，我们应对这一挑战。我们建立在计算的基础上 通过规范避免亏损的方式来解决现有结果中的不一致问题的框架 在某些情况下，在某些人中--被重新定义为奖励。在这里，我们提出这样一个假设 使用计算方法来量化和分离这种主观重构将使我们能够更好地 理清寻求回报与避免损失的相对的、隐蔽的贡献，并澄清它们的神经 支撑点。我们建议通过严格评估结果的有效性来检验这一假设 跨任务、测量和损失行为的测量(与公开奖励和损失行为的简单测量相比) 测试-重新测试复制。特别是，我们解决了两个具体目标。首先，我们试图比较神经性和 跨任务和参与者的奖赏寻求和损失避免的行为测量 在大样本参与者中进行模型和功能磁共振检查。第二，我们试图审视个人 奖赏寻求和损失回避学习的差异及其与精神病学维度的关系 使用大量在线样本的症状学。这两个目标都利用了两个平行和互补的 实验任务分别测试奖励寻求、损失回避和平衡的程度 两者之间的差异受到基线预期回报或损失的差异的影响。总而言之，这些研究 提供了一个综合的计算框架来测试奖赏寻求和奖励测量的结构效度 损失避免，它们之间的关系，它们相对重组的新结构，以及如何 这些结构的个体差异在整个人群的大脑和行为中都很明显。

Project Summary The differentiation between positive and negative valence is central to psychiatry. A seemingly categorical distinction between the drive toward rewards vs. the effort to avoid punishment appears central to many symptoms of psychiatric dysfunction and is evident in both how diagnostic categories are delineated and in the definition of cross-diagnostic constructs in RDoC. However, while there has been major progress in understanding how reward drives learning and actions and the underlying neural mechanisms, there has been much less progress in understanding the mechanisms by which loss and punishment affect behavior. Indeed, there has been continued controversy about whether the neural mechanisms of reward and loss are dissociable at all. Studies of the neural bases of reward seeking vs. loss avoidance have yielded mixed results, manifested both in inconsistent findings about shared vs. separate neural circuitry, and in surprising results in psychiatric populations, for instance showing reward processing abnormalities in psychiatric conditions that appear at face value to be driven by avoidance (e.g. OCD and anxiety). This has made it virtually impossible to address the critical question of defining valid measurements for reward seeking vs. loss avoidance separately, let alone for understanding the balance between them and their relation to other dimensional constructs and psychopathology. Here we address this challenge. We build on a computational framework that resolves the inconsistency in existing results by formalizing how avoiding a loss can – in certain circumstances and in some people – be reframed as a reward. Here we advance the hypothesis that using computational methods for quantifying and isolating this subjective reframing will allow us better to disentangle the relative, covert contributions of reward seeking vs. loss avoidance, and clarify their neural underpinnings. We propose to test this hypothesis by rigorously assessing the validity of the resulting measures (compared to simpler measures of overt reward and loss behavior) across tasks, measures, and test-retest replications. In particular, we address two specific aims. First, we seek to compare neural and behavioral measures of reward seeking and loss avoidance across tasks and participants using computational models and functional MRI in a large sample of participants. Second, we seek to examine individual differences in reward seeking and loss avoidance learning and their relationship to dimensions of psychiatric symptomatology using a large online sample. Both aims make use of two parallel and complementary experimental tasks which each test reward seeking, loss avoidance, and the extent to which the balance between the two is affected by differences in baseline expectations of reward or loss. Together, these studies offer an integrative computational framework to test the construct validity of measures of reward seeking and loss avoidance, the relationship between them, the new construct of their relative reframing, and how individual differences in these constructs are manifest across the population in brain and behavior.