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

通过参考依赖学习模型区分奖励寻求和损失避免

基本信息

批准号：
10219070
负责人：
Nathaniel Douglass Daw
金额：
$ 52.66万
依托单位：
COLUMBIA UNIV NEW YORK MORNINGSIDE
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-10 至 2023-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10219070
关键词：
Accounting Address Affect Anorexia Nervosa Anterior Anxiety Appetite Disorder Avoidance Learning Behavior Behavior Disorders Behavioral Binge Eating Brain Case-Control Studies Categories Choice Behavior Cognitive Complex Computer Models Computing Methodologies Decision Making Desire for food Diagnostic Dimensions Disease Equilibrium Evaluation Expectancy Exposure to Factor Analysis Functional Magnetic Resonance Imaging Functional disorder General Population Goals Health Heterogeneity Individual Individual Differences Insula of Reil Learning Measurement Measures Mental Health Mental disorders Modeling Moods Negative Valence Obsessive-Compulsive Disorder Outcome Participant Patient Self-Report Pattern Performance Population Positive Valence Process Psychiatry Psychopathology Punishment Reaction Time Research Research Domain Criteria Rewards Role Sampling Site Symptoms System Testing Time Training Validity of Results Variant Ventral Striatum base behavior measurement brain behavior cognitive neuroscience comorbidity computational neuroscience computer framework expectation improved insight neural circuit neuromechanism psychiatric symptom relating to nervous system response reward processing symptomatology virtual

项目摘要

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.

项目概要正价和负价之间的区分是精神病学的核心。对许多人来说，追求奖励的动力与避免惩罚的努力之间的区别似乎很重要精神功能障碍的症状，在诊断类别的划分和诊断中都很明显然而，尽管 RDoC 中交叉诊断结构的定义已经取得了重大进展。了解奖励如何驱动学习和行动以及潜在的神经机制事实上，在理解损失和惩罚影响行为的机制方面进展更甚。关于奖励和损失的神经机制是否有效一直存在争议。对寻求奖励与避免损失的神经基础的研究产生了不同的结果。结果，既表现在关于共享神经回路与分离神经回路的不一致的发现，也表现在令人惊讶的在精神病人群中的结果，例如在精神病人群中显示奖励处理异常从表面上看，这些情况是由回避引起的（例如强迫症和焦虑）。实际上不可能解决定义有效衡量奖励寻求与损失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其他人的关系在这里，我们以计算为基础来解决这一挑战。该框架通过正式确定如何避免损失来解决现有结果的不一致问题在某些情况下和在某些人身上——被重新定义为奖励。在这里，我们提出这样的假设：使用计算方法来量化和隔离这种主观重构将使我们能够更好地理清寻求奖励与避免损失的相对的、隐蔽的贡献，并阐明它们的神经网络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、测量和特别是，我们解决了两个具体目标：首先，我们寻求比较神经网络和网络。跨任务并使用计算来寻求奖励和避免损失的行为测量其次，我们试图对个体进行检查。寻求奖励和避免损失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进行症状学研究这两个目标都利用了两个平行且互补的方法。实验任务，每个任务测试奖励寻求、损失避免以及平衡的程度两者之间的差异受到奖励或损失的基线预期差异的影响。提供一个综合的计算框架来测试奖励寻求和衡量的结构有效性损失避免、它们之间的关系、它们相对重构的新构造，以及如何这些结构的个体差异在人群的大脑和行为中表现得很明显。