CRCNS Research Proposal: Cortico-amygdalar substrates of adaptive learning

CRCNS 研究提案：适应性学习的皮质杏仁核基质

• 批准号: 10162266
• 负责人: Alicia Izquierdo
• 金额: $ 6.23万
• 依托单位: DARTMOUTH COLLEGE
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10162266
• 关键词: Adaptive Behaviors; Amygdaloid structure; Anterior; Area; Behavioral; Brain; Calcium; Clinical; Computer Models; Data; Environment; Exhibits; Failure; Future; Human; Image; Individual; Learning; Measurement; Modeling; Neurons; Outcome; Pathway interactions; Prefrontal Cortex; Psychiatry; Research Proposals; Resolution; Reversal Learning; Rewards; Rodent; Role; Stimulus; Substance Use Disorder; System; Testing; Treatment Efficacy; Uncertainty; Work; adaptive learning; base; behavior change; cingulate cortex; flexibility; improved; network models; neuromechanism; neuropsychiatry; nonhuman primate; preference; response; therapeutic target

PROJECT SUMMARY Individuals with Substance Use Disorders (SUD) often exhibit preferences for risky, uncertain outcomes and demonstrate inflexible learning. The neural mechanisms of adaptive learning under uncertainty, however, have been predominantly investigated in human and nonhuman primates with limited capacity for microcircuit measurements and/or systems-level causal manipulations. Guided by mechanistic computational models, here we propose precise systems-level manipulation of interactions between multiple brain areas and imaging of stable neuronal ensembles in rodents, to reveal circuit- level mechanisms underlying adaptive learning. Previous studies point to the role of basolateral amygdala (BLA) and several interconnected subregions of the prefrontal cortex (PFC), including orbitofrontal (OFC) and anterior cingulate cortex (ACC), in adaptive behavior. Based on our recent modeling and experimental work, we hypothesize that OFC and ACC provide stable representations of stimulus-outcome (state values) and action-outcome associations (action values), respectively. BLA uses input from OFC and ACC to estimate volatility in both state and action values to destabilize these representations, which in turn enables faster adjustments in response to real changes in the environment. To test this hypothesis we will chemogenetically inhibit projection neurons between these regions during probabilistic reversal learning of state and action values, and record neuronal ensemble activity via calcium imaging in each cortical region during learning. The results from manipulating different pathways and high temporal- and spatial- resolution of calcium imaging data will be used to identify the relative strength and types of projections, and the representations of reward value in order to refine our models and subsequently develop circuit-level, spiking network models for adaptive learning under uncertainty. Given that SUDs are characterized by uncertain, rapidly-changing, and often extreme reward environments, our proposed aims are pertinent to clinical observations in SUDs and especially deficits in behavioral adjustments. Altogether, using a combination of detailed computational modeling and a sophisticated experimental approach, we will reveal the contributions of cortico- amygdalar circuits to adaptive behavior under uncertainty.

项目概要 患有药物滥用障碍 (SUD) 的个体通常表现出对风险、不确定结果的偏好 并表现出不灵活的学习。不确定性下自适应学习的神经机制， 然而，主要在人类和非人类灵长类动物中进行了研究，但效果有限 微电路测量和/或系统级因果操作的能力。指导者 机械计算模型，在这里我们提出了交互的精确系统级操纵 在啮齿类动物的多个大脑区域和稳定神经元群的成像之间进行研究，以揭示回路 适应性学习的水平机制。先前的研究指出了基底外侧的作用 杏仁核 (BLA) 和前额皮质 (PFC) 的几个相互关联的子区域，包括 眶额皮质（OFC）和前扣带皮层（ACC）在适应性行为中的作用。根据我们最近 通过建模和实验工作，我们假设 OFC 和 ACC 提供了稳定的表示 分别是刺激-结果（状态值）和行动-结果关联（行动值）。 BLA用途 OFC 和 ACC 的输入来估计状态和行动值的波动性，从而破坏这些值的稳定性 表示，这反过来又可以更快地调整以响应实际变化 环境。为了检验这个假设，我们将通过化学遗传学方法抑制这些神经元之间的投射神经元。 状态和动作值的概率逆转学习过程中的区域，并记录神经元集合 通过学习过程中每个皮质区域的钙成像活动。操纵的结果 不同的途径以及钙成像数据的高时间和空间分辨率将用于 确定预测的相对强度和类型，以及奖励值的表示顺序 完善我们的模型并随后开发电路级尖峰网络模型以实现自适应 不确定性下的学习。鉴于 SUD 的特点是不确定、快速变化且经常 在极端奖励环境中，我们提出的目标与 SUD 的临床观察相关，并且 尤其是行为调整方面的缺陷。总而言之，结合使用详细的计算 建模和复杂的实验方法，我们将揭示皮质的贡献 杏仁核回路在不确定性下适应行为。