LC-ACC interactions supporting adaptive, feedback-driven decisions

LC-ACC 交互支持自适应、反馈驱动的决策

• 批准号: 10688111
• 负责人: JOSHUA I GOLD
• 金额: $ 56.08万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-23 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10688111
• 关键词: Anterior; Arousal; Basic Science; Behavior; Behavioral; Brain; Brain Stem; Cell Nucleus; Cerebral hemisphere; Cognition; Cognitive; Complex; Data; Data Set; Decision Making; Diagnosis; Diameter; Electroencephalography; Etiology; Event; Feedback; Foundations; Functional disorder; Goals; Individual; Link; Measurement; Measures; Medial; Mediating; Mental disorders; Modeling; Monitor; Monkeys; Motor; Motor Neurons; National Institute of Mental Health; Nervous System; Neuromodulator; Neurons; Norepinephrine; Output; Pathway interactions; Pattern; Performance; Play; Population; Population Process; Process; Public Health; Pupil; Research Domain Criteria; Resolution; Rest; Rewards; Role; Sensory; Signal Transduction; Source; Specificity; Structure; Surface; System; Task Performances; Testing; Time; Training; Uncertainty; Work; awake; cingulate cortex; design; experience; flexibility; information processing; innovation; insight; interest; locus ceruleus structure; neural; neuroregulation; novel; pharmacologic; theories

PROJECT SUMMARY/ABSTRACT Our long-term goal is to understand how the brain processes information in a flexible, context-dependent manner to support effective decision-making. Many previous studies of decision-making focused on how the brain accumulates evidence used to select a particular action, which was shown to involve modulations of persistent activity of individual sensory-motor neurons that prepare the appropriate action. However, the brain must also often accumulate evidence in a flexible manner across actions, about which little is known. We propose that decisions requiring the flexible accumulation of feedback-related evidence across actions depends on interactions between the Anterior Cingulate Cortex (ACC), a cortical structure on the medial surface of each cerebral hemisphere that has widespread connectivity with other parts of the brain, and the brainstem nucleus locus coeruleus (LC), which is the primary source of the neuromodulator norepinephrine (NE) to the rest of the brain. The ACC and LC have strong, reciprocal connections and are thought to interact in ways that support key features of cognition, including adaptive information processing, but the details of these interactions are not well understood. Our primary hypothesis is that these interactions modulate activity patterns of populations of ACC neurons that implement a process of across-trial evidence accumulation that uses reward and error feedback to govern decisions to switch behavioral choices. We are particularly interested in understanding how these modulations relate to changes in coordinated variability in ACC that can have major effects on how neural populations process information. To test this hypothesis, we use simultaneous, complementary measurements of neuronal activity from single and populations of neurons from the two brain areasin the context of two tasks that require different forms of across-trial accumulation of feedback information to guide saccadic decisions. We have three Specific Aims. Aim 1 is to understand how activity patterns of individual neurons in the LC relate to performance on these tasks. Aim 2 is to understand how relationships between neuronal activity patterns in the LC and ACC relate to performance on these tasks. Aim 3 is to use a combination of manipulations to identify causal contributions of temporally precise, pathway specific activity patterns from LC to ACC on task performance. Together these Aims will provide new mechanistic and computational insights into how LC-related modulations of ACC population activity support ACC's role in flexibly linking performance monitoring and control across multiple trials. Our findings will have direct relevance to numerous constructs in the Research Domain Criteria (RDoC) framework and thus have broad significance to fields that aim to understand the neural substrates of complex behaviors and their dysfunction in certain mental disorders.

项目摘要/摘要 我们的长期目标是了解大脑如何以灵活的上下文依赖性处理信息 支持有效决策的方式。许多先前关于决策的研究集中在 大脑积累用于选择特定动作的证据，该证据涉及调制 准备适当作用的单个感觉运动神经元的持续活动。但是，大脑 还必须经常以灵活的方式在各种行动中积累证据，这一点鲜为人知。我们 提出，要求跨动作的决策需要灵活地积累与反馈相关的证据 取决于前扣带回皮质（ACC）之间的相互作用，这是内侧的皮质结构 每个脑半球的表面，与大脑其他部位具有广泛的连通性， 脑干核基因座（LC），这是神经调节剂去甲肾上腺素的主要来源 （NE）到其他大脑。 ACC和LC具有牢固的相互连接，被认为可以相互作用 以支持认知关键特征的方式，包括自适应信息处理，但 这些相互作用尚不清楚。我们的主要假设是这些相互作用调节活动 ACC神经元种群的模式，这些群体实施了跨审判证据积累的过程 使用奖励和错误反馈来管理决定行为选择的决策。我们特别是 有兴趣了解这些调制与ACC协调可变性变化的关系 对神经种群的处理信息有重大影响。为了检验这一假设，我们使用 同时对来自单个神经元和神经元种群神经元活性的互补测量 这两个大脑区域在两个任务的背景下，需要不同形式的跨审判积累 反馈信息指导律师决策。我们有三个具体的目标。目标1是了解如何 LC中单个神经元的活动模式与这些任务的性能有关。目标2是了解 LC中的神经元活动模式与ACC之间的关系与这些任务的性能有关。 AIM 3是使用操纵的组合来确定时间精确的途径的因果关系 从LC到ACC的特定活动模式。这些目标将共同提供新的 机械和计算洞察与LC相关的ACC种群活动如何支持 ACC在跨多个试验中灵活地链接性能监控和控制方面的作用。我们的发现将有 与研究领域标准（RDOC）框架中的众多结构的直接相关性，因此具有 对旨在了解复杂行为及其其神经基质的领域的广泛意义 某些精神障碍的功能障碍。