Locus coeruelus-prefrontal interactions for flexible decision-making

项目概要/摘要 高级大脑功能包括学习对世界的期望、更新这些期望的能力 当给予新的感官信息时，适当地使用这些不断更新的期望来指导 行为。神经回路如何实现这些灵活的信息处理动态尚不清楚。我们 提出一个新颖的研究项目，该项目与 BRAIN 计划的目标一致，使用创新的、 方法论上的综合方法，以了解灵长类动物特定回路中的活动模式 大脑支持灵活更新用于行为相关决策。该电路主要包括两个 具有与我们提议的研究相关的已知特性的组件。第一个组成部分是背外侧 前额皮质 (dlPFC)，其中包括编码持续处理期望和感觉的神经元 工作记忆中的证据。第二个成分是蓝斑（LC）-去甲肾上腺素（NE） 神经调节系统，可以影响 dlPFC 中的工作记忆表征。然而，它并不是 已知 dlPFC 中工作记忆表征的 LC-NE 调制是否以及如何有助于灵活 决策。基于我们之前关于 LC-NE 系统的灵活决策和效果的工作 在神经信息处理方面，我们提出并检验了 dlPFC 中 LC 介导的 NE 释放的假设 控制 dlPFC 神经群体如何灵活地将工作记忆中的学习期望与 传入的感官信息形成指导行为的决策。我们通过训练来检验这个假设 猴子执行一项新任务，使我们能够量化习得的期望和新的感官信息的情况 以灵活的、依赖于上下文的方式组合起来做出扫视决策。然后我们阐明 底层电路机制，通过三个目标，每个目标都利用一套创新的方法。目标 1 是 测量单神经元分辨率下的 LC 和 dlPFC 活动与灵活决策的关系。目标2 使用多种技术，包括用于时间特异性的电微刺激和用于 通路特异性，以测试 LC->dlPFC 投影的时间特异性放电模式的因果作用 灵活决策。目标 3 使用计算模型来关联 LC-dlPFC 电路特性（包括 NE 介导的神经元增益变化）到支持灵活决策的计算原理。每个 仅目标就提供了对 LC-dlPFC 的相关性、因果性和计算贡献的新见解 电路灵活决策。总而言之，这些研究为 LC 如何 PFC 电路执行关键计算，灵活地将期望与证据结合起来，为决策提供信息。

PROJECT SUMMARY/ABSTRACT Higher brain functions include the ability to learn expectations about the world, update those expectations appropriately when given new sensory information, and use those continually updating expectations to guide behavior. How neural circuits implement these flexible information-processing dynamics is not known. We propose a novel research project that, consistent with the goals of the BRAIN initiative, uses innovative, methodologically integrated approaches to understand how activity pattens in a specific circuit in the primate brain support flexible updating used for behaviorally relevant decisions. The circuit includes two main components with known properties relevant to our proposed studies. The first component is the dorsolateral prefrontal cortex (dlPFC), which includes neurons that encode ongoing processing of expectations and sensory evidence in working memory. The second component is the locus coeruleus (LC)-norepinephrine (NE) neuromodulatory system, which can affect working-memory representations in the dlPFC. However, it is not known whether and how LC-NE modulations of working-memory representations in dlPFC contribute to flexible decision-making. Building on our previous work on flexible decision-making and effects of the LC-NE system on neural information processing, we propose and test the hypothesis that LC-mediated NE release in dlPFC governs how dlPFC neural populations flexibly combine learned expectations held in working memory with incoming sensory information to form decisions that guide behavior. We test this hypothesis by training monkeys on a novel task that allows us to quantify how learned expectations and new sensory information are combined in a flexible, context-dependent manner to make saccadic decisions. We then elucidate the underlying circuit mechanisms, via three Aims that each leverage an innovative set of approaches. Aim 1 is to measure how LC and dlPFC activity at a single-neuron resolution relates to flexible decision-making. Aim 2 uses multiple techniques, including electrical microstimulation for temporal specificity and chemogenetics for pathway specificity, to test for causal roles of temporally specific firing patterns of LC->dlPFC projections on flexible decision-making. Aim 3 uses computational modeling to relate LC-dlPFC circuit properties (including NE-mediated changes in neuronal gain) to computational principles that support flexible decision-making. Each Aim alone provides new insights into correlative, causal, and computational contributions of the LC-dlPFC circuit to flexible decision-making. Taken together, these studies provide a novel, unified view of how the LC- PFC circuit performs critical computations that flexibly combine expectations with evidence to inform decisions.