Investigating the effects of aversive interoceptive states on computations underlying avoidance behavior and their neural basis

研究厌恶内感受状态对回避行为背后的计算及其神经基础的影响

• 批准号: 10399800
• 负责人: Ryan S Smith
• 金额: $ 30.09万
• 依托单位: LAUREATE INSTITUTE FOR BRAIN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10399800
• 关键词: Investigating; effects; aversive; interoceptive; states

Anxiety disorders are the most ubiquitous form of mental illness, affecting roughly 34% of the population. One major factor that maintains anxiety symptoms is the continued avoidance of feared situations that are in fact tolerable and would often improve quality of life. However, it is unknown how the aversive interoceptive states associated with high anxiety influence maladaptive avoidance behavior – or what the neural underpinnings of such influences are. To answer these questions, we propose to employ a previously validated inspiratory breathing load paradigm capable of reliably inducing aversive visceral states while individuals complete two decision-making tasks. We will use computational modeling to identify dissociable parameters underlying learning and decision-making on an individual basis. Some important individual differences that can be estimated within these models are values of parameters reflecting: (1) how much decisions are driven by seeking information vs. reward, and (2) how far into the future an individual considers when making decisions (planning horizon). Abnormal values for these parameters could drive maladaptive avoidance behavior in anxious populations, because learning to approach uncomfortable situations requires both information-seeking (to test expectations) and a sufficient planning horizon to anticipate that short-term discomfort can lead to long-term benefit. Here we hypothesize that aversive visceral states reduce information-seeking and shorten planning horizon. We further hypothesize that these effects are magnified in anxious populations. In this project will recruit 50 low- and 50 high-anxiety participants (Overall Anxiety Severity and Impairment Scale [OASIS] scores > 8) to test the above-stated hypotheses. Participants will complete two decision-making tasks widely used with computational modelling – the aversive pruning (AP) task 6,7 and the horizon task 8. They will complete each task twice, once with and once without the unpleasant breathing load. The AP task assesses aversive decision true ‘pruning’ – the tendency to not evaluate distal outcomes of a possible course of action if a proximal negative outcome is expected (i.e. effectively reducing planning horizon for policies that may have positive distal outcomes). The horizon task assesses goal-directed information-seeking – the tendency to strategically seek out observations to reduce uncertainty before becoming confident in the best course of action. The AP task will be completed during fMRI. We will compare information-seeking and pruning parameter values with vs. without breathing loads and correlate these parameters with state and trait anxiety levels. We will also test the hypothesis that aversive states during breathing load will amplify the known neural correlates of pruning, by increasing neural responses in subgenual cingulate, insula, and amygdala and reducing dorsal frontoparietal activity associated with future planning. Identifying the mechanisms by which aversive states promote avoidance will be an important first step toward designing new interventions to target these mechanisms and improve symptoms.

焦虑症是最普遍的精神疾病形式，影响大约34%的人口。一 保持焦虑症状的主要因素是持续避免恐惧的情况， 可以忍受，往往会提高生活质量。然而，目前还不清楚厌恶的内感受状态是如何 与高度焦虑相关的影响适应不良的回避行为-或者说， 这种影响是。为了回答这些问题，我们建议采用先前验证的吸气 呼吸负荷范式能够可靠地诱导厌恶的内脏状态，而个人完成两个 决策任务。我们将使用计算建模来识别潜在的可分离参数， 个人的学习和决策。可以估计的一些重要的个体差异 在这些模型中，参数值反映了：（1）有多少决策是由寻求驱动的 信息与奖励，以及（2）个人在做出决策（规划）时考虑的未来有多远 地平线）。这些参数的异常值可能会导致焦虑症患者的适应不良回避行为。 人群，因为学习接近不舒服的情况需要信息寻求（测试）， 预期）和足够的规划范围，以预期短期不适可能导致长期 效益在这里，我们假设厌恶的内脏状态会减少信息寻求并缩短计划 地平线我们进一步假设，这些影响在焦虑人群中被放大。在这个项目中将招募 50名低焦虑和50名高焦虑参与者（总体焦虑严重程度和损害量表[OASIS]评分> 8）， 测试上述假设。参与者将完成两个广泛使用的决策任务， 计算建模-厌恶修剪（AP）任务6、7和水平任务8。他们将完成每一个 任务两次，一次有，一次没有令人不快的呼吸负荷。AP任务评估令人厌恶的决策 真正的“修剪”-如果近端阴性，则倾向于不评估可能的行动过程的远端结果 预期的结果（即有效地减少可能具有积极影响的政策的规划范围） 成果）。地平线任务评估目标导向的信息寻求-战略寻求的倾向 在对最佳行动方案充满信心之前，我们需要进行观察，以减少不确定性。AP任务将 在fMRI中完成。我们将比较信息搜索和修剪参数值与没有 呼吸负荷，并将这些参数与状态和特质焦虑水平相关联。我们还将检验假设 呼吸负荷期间的厌恶状态将通过增加已知的神经相关的修剪来放大， 膝下扣带回、杏仁核和杏仁核的神经反应，减少背侧额顶叶活动 与未来规划有关。确定厌恶国家促进回避的机制将是 这是设计新干预措施以针对这些机制并改善症状的重要第一步。