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: 10598322
• 负责人: Alicia Izquierdo
• 金额: $ 31.42万
• 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 2024-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10598322
• 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; Uncertainty; Work; adaptive learning; base; behavior change; cingulate cortex; flexibility; improved; network models; neuromechanism; neuropsychiatry; nonhuman primate; preference; response; therapeutic target; therapeutically effective

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.

项目总结 物质使用障碍(SUD)患者通常表现出对高风险、不确定结果的偏好 并表现出僵化的学习方式。不确定条件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， 微电路测量和/或系统级因果操作的能力。指导原则 机械性计算模型，在这里我们提出了精确的系统级交互操作 在啮齿动物的多个脑区和稳定的神经元群的成像之间，以揭示电路- 自适应学习背后的层次机制。以前的研究指出了基底外侧的作用。 杏仁核(BLA)和前额叶皮质(PFC)的几个相互关联的亚区，包括 眼眶前额叶(OFC)和前扣带回(ACC)，在适应行为中。根据我们最近的调查 建模和实验工作中，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(动作值)。BLA使用 来自OFC和ACC的输入，以估计状态和动作值的波动性，从而破坏这些 表示，这进而实现了更快的调整，以响应 环境。为了验证这一假设，我们将从化学上抑制这些神经元之间的投射神经元。 状态和动作值的概率反转学习过程中的区域，并记录神经元集合 在学习过程中，通过钙成像在每个皮质区域进行活动。操纵的结果是 不同的路径和高时间和空间分辨率的钙成像数据将用于 确定预测的相对强度和类型，并按顺序确定奖励值的表示 改进我们的模型并随后开发电路级、尖峰网络模型以自适应 在不确定的情况下学习。鉴于肥皂水的特征是不确定的、快速变化的，并且通常 极端的奖励环境，我们建议的目标与肥胖症的临床观察和 尤其是行为调整方面的缺陷。总之，使用了详细计算的组合 模型和复杂的实验方法，我们将揭示皮质的贡献。 杏仁核神经元在不确定条件下的适应行为。