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.

项目摘要 患有药物使用障碍（SUD）的个体通常会表现出对风险，不确定结果的偏好 并表现出僵化的学习。在不确定性下自适应学习的神经机制， 然而，在人类和非人类灵长类动物中主要研究了 微电路测量和/或系统级别因果关系的能力。指导 机械计算模型，我们在这里提出了精确的系统级交互操作 在多个大脑区域和啮齿动物中稳定的神经元集合成像之间，以揭示电路 - 自适应学习的基础机制。先前的研究指出基底外侧的作用 杏仁核（BLA）和前额叶皮层（PFC）的几个相互连接的子区域，包括 轨道额（OFC）和前扣带回皮层（ACC），以适应性行为。根据我们最近的 建模和实验工作，我们假设OFC和ACC提供了稳定的表示 刺激结果（状态值）和行动结果关联（动作值）。 BLA使用 OFC和ACC的输入以估计状态和行动价值的波动，以使这些稳定性不稳定 表示，这反过来可以响应于实际更改 环境。为了检验这一假设，我们将在化学上抑制这些假设 概率逆转对状态和行动价值的逆转学习中的区域，并记录神经元集合 学习过程中每个皮质区域中通过钙成像的活性。操纵的结果 钙成像数据的不同途径以及高时间和空间分辨率将用于 确定预测的相对强度和类型，以及奖励价值的表示形式 为了完善我们的模型，并随后开发电路级，尖峰网络模型以进行自适应 在不确定性下学习。鉴于泡沫的特征是不确定，迅速变化且经常 极端的奖励环境，我们提出的目标与SUD和 特别是行为调整的缺陷。总共结合了详细的计算 建模和复杂的实验方法，我们将揭示皮质的贡献 杏仁核电路在不确定性下适应适应性行为。