A translational determination of the mechanisms of maladaptive choice in cocaine use disorder

摘要 可卡因使用障碍(CUD)的特点是决定以牺牲其他活动为代价使用可卡因。 因此，解决这一问题的实验室努力包括可卡因选择自我给药程序。 其中包含了非药物替代品来模拟这一定义特征。使用这些程序的研究已经 通常计划竞争的增强剂，以便概率是确定的。然而，这种决定论 结果并不代表真实世界的情景，在现实世界中，毒品相关决定的后果 通常是不可预测的。重要的是，在动态、不确定的环境中进行决策会显著改变 选择期权的价值，并需要不断更新期权价值，这需要进行学习过程 以及可能在CUD中功能异常的相关皮质纹状体网络。动态决策 使用概率强化学习选择(PRLC)任务成功地对环境进行了建模。 这些任务与强化学习(RL)建模的集成已被用于捕获时刻到 动态选择机制的瞬间变化，以及神经科学技术的应用 开始确定潜在的神经生物学。这种方法揭示了以生物学为基础的决策 多发性脑疾病中的异常，但尚未系统地应用于脑损伤的实验研究 CUD，将RL和神经科学的结合方法翻译到CUD是合乎逻辑的，考虑到 典型的适应不良选择行为，可卡因吸毒者的强化概率不同 自然环境，以及学习障碍和神经适应，已在 患有CUD的个体。因此，我们对动态背后的机制的理解存在严重差距 可卡因使用决定，以及应用RL框架填补这些空白的强有力的科学前提。这 该项目提出了严格的PRLC任务、RL建模、神经调节/功能磁共振神经成像技术和 在大鼠和人类中进行的互补性、转换性研究设计，以研究CUD的动态选择。第一套 跨物种实验将展示有问题的可卡因使用对动态决策的影响 并揭示了这种异常任务表现背后的神经行为和神经生物学过程。这个 第二组实验将使用PRLC任务，其中静脉注射可卡因作为替代 非药物增强剂，用于确定与使用决定相关的行为和神经“概况” 可卡因和治疗期间可卡因选择的减少。苯丙胺维持与非药物替代 强化治疗减少了可卡因的选择，这里将利用这一点来揭示行为和神经 可作为未来治疗发展目标的机制。这个项目将产生重大影响 在现场通过建立强化学习理论在研究中的实验应用 CUD中的非适应性动态决策。

ABSTRACT Cocaine use disorder (CUD) is characterized by the decision to use cocaine at the expense of other activities. Lab-based efforts to address this problem have therefore included cocaine choice self-administration procedures that incorporate a non-drug alternative to model this defining feature. Studies using these procedures have typically scheduled competing reinforcers so that the probabilities are certain. However, such deterministic outcomes are not representative of real-world scenarios in which the consequences from drug-related decisions are often unpredictable. Importantly, decision-making in a dynamic, uncertain context significantly alters the value of choice options and requires continuous updating of option values, which engages learning processes and related corticostriatal networks that might be functioning abnormally in CUD. Decision-making in dynamic environments has been successfully modeled using probabilistic reinforcement-learning choice (PRLC) tasks. The integration of these tasks with reinforcement-learning (RL) modeling has been used to capture moment-to- moment changes in the mechanisms of dynamic choice, and the application of neuroscience techniques has begun to identify the underlying neurobiology. This approach has uncovered biologically-based decision-making abnormalities in multiple brain disorders, but has yet to be systematically applied to the experimental study of CUD, The translation of combined RL and neuroscience approaches to CUD is logical considering the maladaptive choice behavior that typifies the disorder, the varying reinforcement probabilities in cocaine users’ natural environments, and the learning impairments and neuroadaptations that have been documented in individuals with CUD. Thus, there are critical gaps in our understanding of the mechanisms underlying dynamic cocaine use decisions, and a strong scientific premise for applying an RL framework to fill these gaps. This project proposes rigorous PRLC tasks, RL modeling, neuromodulation/fMRI neuroimaging techniques and complementary, translational study designs in rats and humans to study dynamic choice in CUD. The first set of cross-species experiments will demonstrate the impact of problematic cocaine use on dynamic decision-making and reveal the neurobehavioral and neurobiological processes underlying this abnormal task performance. The second set of experiments will use a PRLC task in which intravenous cocaine is available as an alternative to the non-drug reinforcer to determine the behavioral and neural “profile” associated with the decision to use cocaine and reduced cocaine choice during treatment. Amphetamine maintenance and non-drug alternative reinforcer treatments reduce cocaine choice, which will be leveraged here to uncover behavioral and neural mechanisms that can be targeted for future treatment development. This project will have a significant impact on the field by establishing the experimental application of reinforcement-learning theory to the study of maladaptive dynamic decision-making in CUD.