Dissecting motor cortex modulation of nociception during chronic pain

剖析慢性疼痛期间运动皮层对伤害感受的调节

• 批准号: 10589724
• 负责人: Nicole Mercer Lindsay
• 金额: $ 15.19万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-06 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10589724
• 关键词: Absence of pain sensation; Affect; Agonist; American; Analgesics; Area; Behavior; Behavioral Paradigm; Body Regions; Body part; Calcium; Clinical; Clinical Protocols; Complement; Environment; Face; Facial Pain; Fluorescent in Situ Hybridization; Goals; Hyperalgesia; Image; Imaging Techniques; Individual; Jaw; Knockout Mice; Knowledge; Machine Learning; Magnetism; Maps; Mentorship; Methods; Modeling; Motor; Motor Cortex; Mus; Naloxone; Neprilysin; Nerve; Neurobiology; Neurons; Neuropathy; Neurosciences; Nociception; Opioid; Opioid Antagonist; Opioid Peptide; Opioid Receptor; Output; Pain; Pathway interactions; Pattern; Peptides; Persistent pain; Pharmacology; Physicians; Positioning Attribute; Property; Reporting; Research; Research Personnel; Research Project Grants; Rodent; Rodent Model; Running; Scientist; Signal Pathway; Signal Transduction; Silicones; Site; Structure of trigeminal nerve spinal tract nucleus; Techniques; Technology; Testing; Training; Trigeminal Nuclei; Trigeminal System; Trigeminal nerve structure; Viral; Work; allodynia; antagonist; behavioral response; cell type; chronic pain; clinical efficacy; clinical implementation; clinical pain; clinical practice; constriction; endogenous opioids; experimental study; human subject; improved; inferior alveolar nerve; inhibitor; innovation; machine learning algorithm; mouse genetics; neurobiological mechanism; novel; off-target site; opioid epidemic; pain model; pain relief; pain signal; painful neuropathy; programs; recruit; relating to nervous system; two-photon; Absence of pain sensation; Affect; Agonist; American; Analgesics; Area; Behavior; Behavioral Paradigm; Body Regions; Body part; Calcium; Clinical; Clinical Protocols; Complement; Environment; Face; Facial Pain; Fluorescent in Situ Hybridization; Goals; Hyperalgesia; Image; Imaging Techniques; Individual; Jaw; Knockout Mice; Knowledge; Machine Learning; Magnetism; Maps; Mentorship; Methods; Modeling; Motor; Motor Cortex; Mus; Naloxone; Neprilysin; Nerve; Neurobiology; Neurons; Neuropathy; Neurosciences; Nociception; Opioid; Opioid Antagonist; Opioid Peptide; Opioid Receptor; Output; Pain; Pathway interactions; Pattern; Peptides; Persistent pain; Pharmacology; Physicians; Positioning Attribute; Property; Reporting; Research; Research Personnel; Research Project Grants; Rodent; Rodent Model; Running; Scientist; Signal Pathway; Signal Transduction; Silicones; Site; Structure of trigeminal nerve spinal tract nucleus; Techniques; Technology; Testing; Training; Trigeminal Nuclei; Trigeminal System; Trigeminal nerve structure; Viral; Work; allodynia; antagonist; behavioral response; cell type; chronic pain; clinical efficacy; clinical implementation; clinical pain; clinical practice; constriction; endogenous opioids; experimental study; human subject; improved; inferior alveolar nerve; inhibitor; innovation; machine learning algorithm; mouse genetics; neurobiological mechanism; novel; off-target site; opioid epidemic; pain model; pain relief; pain signal; painful neuropathy; programs; recruit; relating to nervous system; two-photon

Abstract The heavy burden of chronic pain and the Opioid Epidemic has prompted an urgent, worldwide search for alternative, non-addictive methods of analgesia. One promising alternative is non-invasive electrical or magnetic stimulation of the motor cortex (MC). While MC stimulation (MCS) has repeatedly been found to reduce chronic pain in human subjects and to decrease nocifensive behaviors in rodent pain models, major questions remain about the MCS analgesic mechanisms of action, how MC influences activity in nociceptive circuits, and how to improve MCS clinical efficacy. Evidence suggests that MCS antinociceptive efficacy increases when the stimulation targets the region in motor cortex that corresponds to the body part from which nociception originates (somatotopically matched) and that MCS analgesia requires endogenous opioid activity. Here, I propose to use a rodent model of trigeminal neuropathic pain to elucidate the underlying mechanisms of MCS antinociception and to define key MCS features that pain clinicians can use to improve MCS efficacy. To characterize MCS mechanisms, I will 1) quantify the efficacy of somatotopically matched MCS (ssMCS), 2) determine what opioid receptor subtypes are required for MCS antinociception, and 3) identify how endogenous opioids modulate an opioid-sensitive MC descending circuit to the spinal trigeminal nucleus pars caudalis (SpVC) during ssMCS. To ascertain MCS efficacy between matched and off-target MCS in two different nerve constriction models, I will use classic pain behavioral paradigms along with cutting-edge machine learning algorithms to analyze mouse behavioral responses. To interrogate the combined impact of MC somatotopy and endogenous opioid signaling in MCS analgesia, I will focus on the descending projection from MC to SpVC. I will determine where opioid receptor types and endogenous opioid peptides are positioned along this circuit and then assess the impact of ssMCS +/- opioid signaling on MC and SpVC neural activity using cutting-edge calcium imaging techniques in behaving mice. Altogether, this project will determine how MCS modulates nociception through endogenous opioid signaling in somatotopically aligned circuits to guide the optimization of MCS clinical protocols. The results will also provide the first report of neural activity during and after ssMCS at both the target and in an MC output. This project will take place in the lab of Prof. Mark Schnitzer’s (sponsor) lab at Stanford, an ideal environment for innovative neuroscience. Together with the mentorship of leading pain neuroscientists, Profs. Greg Scherrer and Sean Mackey (co-sponsors), the proposed training plan provides an excellent opportunity for me to become an expert in pain and opioid neurobiology while interrogating novel scientific concepts with cutting-edge technology. Further, I will gain valuable clinical knowledge by interacting with Prof. Mackey and his team of clinical pain researchers and physicians. Finally, this project will help me develop into an independent scientist and ideally position me to start my own lab program studying pain circuitry and its intersection with motor circuits.

抽象的 慢性疼痛和阿片类药物流行的严重燃烧引起了全世界的紧急寻找 替代性的非添加性镇痛方法。一个承诺的替代方案是无创的电气或磁性 刺激运动皮层（MC）。虽然已反复发现MC刺激（MC）减少了慢性 人类受试者的疼痛并减轻啮齿动物疼痛模型中的单位行为，仍然存在主要问题 关于动作的MCS镇痛机制，MC如何影响伤害性圆圈的活动以及如何影响 提高MCS临床效率。有证据表明，当 刺激针对运动皮层中的区域，与伤害感受起来的身体部分相对应 （与体型相匹配）并且MCS镇痛需要内源性阿片类药物活性。在这里，我建议使用 三叉神经性疼痛的啮齿动物模型，以阐明MCS抗伤害感受的潜在机制 并定义疼痛临床医生可以用来提高MCS效率的关键MCS功能。为了表征MC 机制，我将1）量化体形匹配的MC（SSMC）的有效性，2）确定哪种阿片类药物 MC抗伤害感受需要受体亚型，3）确定内源性阿片类药物如何调节 在SSMC中，阿片类药物敏感的MC降低电路降低了脊柱三叉神经核的caudalis（SPVC）。 为了在两个不同的神经收缩模型中确定匹配和脱靶MC之间的MC效率，我将 使用经典的疼痛行为范式以及尖端的机器学习算法来分析鼠标 行为反应。询问MC大型体育和内源性阿片类药物信号的综合影响 在MCS镇痛中，我将重点关注从MC到SPVC的下降投影。我将确定阿片类药物在哪里 受体类型和内源性阿片类肽位于该电路，然后评估 SSMC +/-在MC和SPVC神经活动上使用尖端钙成像技术上的阿片类药物信号传导 行为小鼠。总共，该项目将决定MC如何通过内生调节伤害感受 在体位对齐的电路中，静脉信号传导指导MCS临床方案的优化。结果 还将在目标和MC输出中的SSMC期间和之后提供第一份关于神经活动的报告。 该项目将在斯坦福大学马克·施尼策（Mark Schnitzer）（赞助商）实验室的实验室举行，这是一个理想的环境 用于创新的神经科学。加上领先的疼痛神经科学家的精神制，教授。格雷格·施雷尔（Greg Scherrer） 和肖恩·麦基（Sean Mackey）（共同赞助人），拟议的培训计划为我提供了一个绝佳的机会 疼痛和阿片类神经生物学专家，同时用尖端询问新颖的科学概念 技术。此外，我将通过与麦基教授及其团队互动来获得宝贵的临床知识 临床疼痛研究人员和医生。最后，这个项目将帮助我发展成为独立科学家 理想情况下，我将自己的实验室计划启动，研究止痛电路及其与电机电路的交集。