Brainstem-forebrain networks and threat computation

脑干前脑网络和威胁计算

• 批准号: 10736117
• 负责人: MICHAEL A MCDANNALD
• 金额: $ 65.05万
• 依托单位: BOSTON COLLEGE
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2028-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10736117
• 关键词: Amygdaloid structure; Anxiety Disorders; Area; Behavior; Behavioral; Brain; Brain Stem; Clinical; Cues; Data; Dependence; Discrimination; Disease; Dorsal; Equation; Female; Foundations; Freezing; Fright; Functional disorder; Implant; Infusion procedures; Injections; Interruption; Knowledge; Laboratories; Learning; Link; Locomotion; Mus; Neurons; Outcome; Output; Phase; Play; Probability; Procedures; Prosencephalon; Rattus; Role; Shapes; Shock; Signal Transduction; Source; Testing; Update; Virus; conditioned fear; density; designer receptors exclusively activated by designer drugs; effective therapy; fluorophore; genetic manipulation; innovation; learning network; male; midbrain central gray substance; neural; neural circuit; optogenetics; treatment of anxiety disorders

Project Summary A cardinal feature of anxiety disorders is exaggerated fear to cues signaling threat. The prevailing view of the neural circuit for fear learning is a division of labor in which the amygdala and associated forebrain regions signal threat probability, and brainstem regions organize fear output. This view is the intellectual foundation for proposals that forebrain threat dysfunction drives exaggerated fear in anxiety disorders. Much more than organizing fear output, my laboratory is showing brainstem networks compute prediction error – a learning signal to drive fear learning. Further, brainstem networks signal threat – a function purported to be specific to the forebrain. This proposal will reveal brainstem networks that signal threat probability, compute prediction error, and organize fear output. Aim 1 will detail the emergence of brainstem threat and behavior signaling dynamics. Female and male rats will receive Neuropixels implant through a complete dorsal-ventral brainstem axis. Thousands of single units will be recorded from 20+ brainstem regions during a fear discrimination procedure that produces selective learning to a threat cue. Firing analyses during the cue period will reveal the emergence of brainstem network threat signaling and tracking of diverse behaviors over fear learning. Aim 2 will establish a framework for brainstem prediction error dynamics. Firing analyses during the outcome period will link brainstem network firing dynamics for prediction error that precede the emergence of fear learning. Aim 3 will reveal forebrain inputs shaping brainstem firing dynamics and fear learning. Rats will receive brainstem Neuropixels implant. AAV2-retro in a brainstem region and cre-casp3 in a forebrain region will be used to delete specific inputs to the brainstem (e.g. prelimibic cortex neurons projecting to the periaqueductal gray). Firing analyses comparing casp3 and control rats will reveal the dependence of brainstem firing dynamics (threat, behavior, and prediction error) on forebrain inputs. Aim 4 will chemogenetically manipulate brainstem firing to diminish prediction error computation and fear learning. Rats will receive brainstem Neuropixels implant. Half will then receive excitatory DREADD infusions in regions flanking the periaqueductal gray – sources of a tonic prediction error organized by firing inhibition. Actuator injections (JH60), but not saline injection, will excite brainstem firing – blocking the tonic prediction error network. Firing analyses will reveal the effects of network interruption on brainstem firing dynamics for threat, behavior, and prediction error. This proposal will extend scientific knowledge by uncovering core threat functions of brainstem networks. The proposal will further reveal how forebrain inputs shape brainstem firing dynamics that signal threat, compute prediction error and organize specific fear behaviors. This knowledge is essential to developing effective anxiety disorder treatments aimed to reduce fear.

项目概要 焦虑症的一个主要特征是夸大对威胁信号的恐惧。 恐惧学习的神经回路是一种分工，其中杏仁核和相关的前脑区域 信号区域威胁概率，以及脑干组织恐惧输出，这一观点是这一观点的智力基础。 有人提出，前脑威胁功能障碍不仅仅会导致焦虑症患者过度恐惧。 组织恐惧输出，我的实验室正在展示脑干网络计算预测误差——一种学习 此外，脑干网络发出威胁信号——据称是针对恐惧学习的特定功能。 该提案将揭示发出威胁概率、计算预测的脑干网络。 错误，并组织恐惧输出 目标1将详细说明脑干威胁的出现和行为信号。 雌性和雄性大鼠将通过完整的背腹脑干接受 Neuropixels 植入。 在恐惧辨别过程中，来自 20 多个脑干区域的数千个单个单元将被记录下来。 在提示期间对威胁线索进行选择性学习的过程将揭示威胁线索。 目标 2：脑干网络威胁信号的出现和对恐惧学习的不同行为的跟踪。 将建立结果期间脑干预测误差动态分析的框架。 将脑干网络放电动力学与恐惧学习出现之前的预测错误联系起来。 3 将揭示前脑输入塑造脑干放电动力学和恐惧学习。 脑干区域的 AAV2-retro 植入物和前脑区域的 cre-casp3 植入物将用于 删除脑干的特定输入（例如投射到导水管周围灰色的前边缘皮质神经元）。 比较 casp3 和对照大鼠的放电分析将揭示脑干放电动力学的依赖性 前脑输入（威胁、行为和预测错误）将通过化学遗传学方式操纵脑干。 发射以减少预测误差计算和恐惧学习大鼠将接收脑干神经像素。 然后一半将在导水管周围灰质两侧的区域接受兴奋性 DREADD 输注—— 强直预测误差的来源是由执行器注射（JH60）组织的，但不是盐水。 注射，会激发脑干放电——阻断强直预测误差网络，放电分析将揭示。 网络中断对威胁、行为和预测错误的脑干放电动力学的影响。 该提案将通过揭示脑干网络的核心威胁功能来扩展科学知识。 该提案将进一步揭示前脑输入如何塑造脑干放电动力学，从而发出威胁信号、计算 预测错误并组织特定的恐惧行为对于发展有效的恐惧行为至关重要。 焦虑症治疗旨在减少恐惧。