Locus coeruleus ensembles in active avoidance and reward seeking

蓝斑集合了主动回避和寻求奖励

基本信息

批准号：
10678364
负责人：
Ellen Marie Rodberg
金额：
$ 4.77万
依托单位：
UNIVERSITY OF MASSACHUSETTS AMHERST
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-03-16 至 2025-03-15
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10678364
关键词：
Adaptive Behaviors Amygdaloid structure Anxiety Auditory Auditory area Behavior Behavioral Brain Brain Stem Brain region Calcium Cell Nucleus Characteristics Complex Computational Technique Cues Data Data Analyses Detection Disease Dissociation Electrophysiology (science)Environment Evaluation Extinction Food Freezing Fright Genetic Goals Heterogeneity Histology Individual Injury Intervention Label Learning Light Maps Mental Depression Mental disorders Mentorship Motor Cortex Negative Reinforcements Neurons Norepinephrine Outcome Population Positive Reinforcements Post-Traumatic Stress Disorders Process Property Rattus Research Research Personnel Rewards Rodent Role Schizophrenia Shock Testing Training Ventral Tegmental Area Viral Work addiction autism spectrum disorder behavioral response cognitive process density extracellular large scale data locus ceruleus structure maladaptive behavior neural neural network neurochemistry neuropsychiatric disorder noradrenergic novel novel therapeutic intervention optogenetics oral communication recruit response

项目摘要

PROJECT SUMMARY Knowing how to act in response to cues in our environment is a critical behavior. Making optimal choices involves engaging the necessary neural networks to seek rewards (e.g., food etc.), avoid negative outcomes (e.g., injury etc.), and ignore irrelevant information. Aberrant network activity in response to cues leads to maladaptive behavioral responses, something characteristic in many psychiatric disorders including PTSD, addiction, autism spectrum disorder, and schizophrenia. The brainstem nucleus locus coeruleus (LC) and brain-wide levels of norepinephrine (NE), a majority of which originates from LC, are vital for engaging appropriate behaviors in response to cues. Recent discoveries emphasize the unexplored complexity in the organization of LC and its role in responding to cues that elicit behavior. Distinct ensembles of LC neurons encode different cognitive processes and behaviors. Furthermore, discrete LC subcircuits are required to parse various LC functions. My long-term goal is to dissociate the complex role of LC and NE in regulating adaptive and maladaptive behaviors. The specific objective of this proposed research is to identify the functional LC neural ensembles and projection targets necessary to appropriately respond to positive and negative reinforcement cues. To achieve this goal, I will (1) characterize LC neural activity acquired from high density electrophysiology probes and (2) identify and modulate LC projections with an activity dependent viral labelling strategy during an active avoidance and reward seeking task. My central hypothesis is that opposing cue-outcome associations recruit separate LC neuron ensembles and circuits necessary for appropriate behavioral responses, even when outcome-associated behaviors are similar. In Aim 1 I will analyze large scale electrophysiology data obtained from high-density Neuropixel probes to characterize LC neuronal activity during active avoidance and reward cue presentation. I hypothesize that there will be separate and distinct ensembles of neurons that respond to cues prompting similar actions to either receive a positive outcome vs avoid a negative outcome. In Aim 2 I will use calcium-dependent genetic tagging, Cal-Light, to identify and inhibit discrete LC projections driven by behavior-evoking cues. I hypothesize that LC ensembles for active avoidance and reward seeking cues preferentially target different brain regions forming functional subcircuits. Furthermore, I will test my hypothesis that activity in these LC subcircuits is necessary for appropriate behavior. The proposed research will identify LC ensembles and projections underlying optimal behavior, highlight circuits that may contribute to maladaptive behavior, and inform circuit- based treatment targets for PTSD and other psychiatric disorders.

项目概要知道如何根据环境中的提示采取行动是一项至关重要的行为。做出最佳选择涉及参与必要的神经网络来寻求奖励（例如食物等），避免负面结果（例如受伤等），并忽略不相关的信息。对提示做出反应的异常网络活动会导致适应不良行为反应，这是许多精神疾病的特征，包括创伤后应激障碍、成瘾、自闭症谱系障碍和精神分裂症。脑干蓝斑核 (LC) 和全脑水平去甲肾上腺素 (NE)，其中大部分源自 LC，对于参与适当的行为至关重要对提示的反应。最近的发现强调了 LC 组织及其未探索的复杂性在响应引发行为的线索中发挥作用。不同的 LC 神经元群编码不同的认知流程和行为。此外，需要离散的 LC 子电路来解析各种 LC 函数。我的长期目标是分离 LC 和 NE 在调节适应和适应不良行为中的复杂作用。这项研究的具体目标是确定功能性 LC 神经元集成和投影对积极和消极强化线索做出适当反应所必需的目标。为了实现这个目标，我将 (1) 表征从高密度电生理学探针获得的 LC 神经活动，以及 (2) 识别和在主动回避和奖励期间通过活动依赖的病毒标记策略调节 LC 预测寻求任务。我的中心假设是相反的线索结果关联招募单独的 LC 神经元适当的行为反应所必需的整体和电路，即使与结果相关行为相似。在目标 1 中，我将分析从高密度数据中获得的大规模电生理学数据 Neuropixel 探针可表征主动回避和奖励提示呈现期间 LC 神经元的活动。我假设存在独立且不同的神经元集合，它们对提示类似的线索做出反应获得积极结果与避免消极结果的行动。在目标 2 中，我将使用钙依赖性药物基因标记 Cal-Light，用于识别和抑制由行为诱发线索驱动的离散 LC 投影。我假设主动回避和奖励寻求线索的 LC 集合优先针对不同的大脑形成功能子电路的区域。此外，我将检验我的假设，即这些 LC 子电路中的活动对于适当的行为是必要的。拟议的研究将确定 LC 系综和预测潜在的最佳行为，突出显示可能导致适应不良行为的回路，并告知回路 PTSD 和其他精神疾病的治疗目标。