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: 10403483
• 负责人: Ryan S Smith
• 金额: $ 30.87万
• 依托单位: LAUREATE INSTITUTE FOR BRAIN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-15 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10403483
• 关键词: Affect; Amygdaloid structure; Anxiety; Anxiety Disorders; Breathing; Computer Models; Decision Making; Distal; Distant; Dorsal; Foundations; Fright; Functional Magnetic Resonance Imaging; Future; Goals; Impairment; Individual; Individual Differences; Insula of Reil; Intervention; Lead; Learning; Maintenance; Mental Health; Mental disorders; Methods; Modeling; Neurosciences; Outcome; Participant; Policies; Population; Quality of life; Rewards; Severities; Symptoms; Testing; Uncertainty; Visceral; Work; anxiety symptoms; anxious; avoidance behavior; base; behavior influence; design; expectation; health assessment; improved; neural correlate; recruit; relating to nervous system; response; symptomatic improvement; trait

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.

焦虑症是精神疾病中最普遍的形式，影响了大约34％的人群。一 保持动画症状的主要因素是持续避免实际上是 可以容忍的，通常会改善生活质量。但是，尚不清楚厌恶性的互感状态 与高焦虑相关的影响适应不良的回避行为 - 或神经的基础 这种影响是。要回答这些问题，我们建议采用先前验证的查询 呼吸负荷范式能够可靠地引起厌恶性内脏状态，而个体完成两个 决策任务。我们将使用计算建模来识别可分离的参数 个人学习和决策。可以估计的一些重要的个体差异 在这些模型中，是反映参数的值：（1）寻求多​​少决策是驱动的 信息与奖励，以及（2）个人在做出决定时要考虑的未来多远（计划 地平线）。这些参数的异常值可能会导致焦虑的适应不良的回避行为 人群，因为学会处理不舒服的情况需要寻求信息（测试 期望）和足够的计划范围，以期预测短期不适会导致长期 益处。在这里，我们假设厌恶性内脏状态减少了信息寻求信息和缩短计划 地平线。我们进一步假设这些影响在焦虑的人群中被放大。在这个项目中将招募 50个低和50个高焦虑参与者（总体焦虑严重性和障碍量表[OASIS]得分> 8） 测试上述假设。参与者将完成两项广泛使用的决策任务 计算建模 - 厌恶修剪（AP）任务6,7和Horizo​​n Task 8。他们将完成每个任务 任务两次，一次没有不愉快的呼吸负荷。 AP任务评估反对性决定 真实的“修剪” - 如果近端负面的倾向 预期结果（即有效地减少可能具有不同不同的政策的计划范围 结果）。地平线任务评估目标指导的信息寻求信息 - 战略性寻求的趋势 在对最佳行动方案充满信心之前，要进行观察以减少不确定性。 AP任务将 在fMRI期间完成。我们将用与没有 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 在呼吸负荷期间的厌恶状态将通过增加来扩大修剪的已知神经相关性 亚属扣带，岛状和杏仁核的神经反应，并减少背侧额叶活动 与未来的计划相关。确定厌恶状态促进避免的机制将是 设计新干预措施以针对这些机制并改善符号的重要第一步。