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

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.

摘要 慢性疼痛和阿片类药物流行的沉重负担促使世界范围内紧急寻找 替代的非成瘾性镇痛方法一个有希望的替代方法是非侵入性的电或磁 运动皮层（MC）的刺激。虽然多次发现MC刺激（MCS）可以减少慢性 为了减轻人类受试者的疼痛并减少啮齿动物疼痛模型中的伤害反应行为，主要问题仍然存在 关于MCS的镇痛作用机制，MC如何影响伤害性回路的活动，以及如何 提高MCS临床疗效。有证据表明，MCS抗伤害效果增加时， 刺激的目标是运动皮层中对应于伤害感受起源的身体部位的区域 （躯体位置匹配）和MCS镇痛需要内源性阿片活性。在这里，我建议使用 三叉神经病理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用于提高MCS疗效的关键MCS功能。表征MCS 机制，我将1）量化躯体位置匹配MCS（ssMCS）的疗效，2）确定阿片类药物 受体亚型是MCS抗伤害感受所必需的，以及3）确定内源性阿片样物质如何调节 在ssMCS期间，阿片样物质敏感的MC下行回路至三叉神经脊束核尾侧部（SpVC）。 为了确定两种不同神经收缩模型中匹配和脱靶MCS之间的MCS疗效，我将 使用经典的疼痛行为范例沿着尖端的机器学习算法来分析小鼠 行为反应探讨MC躯体特征和内源性阿片信号传导的联合影响 在MCS镇痛中，我将重点关注MC到SpVC的下行投射。我会确定阿片类药物 受体类型和内源性阿片肽被定位沿着这个回路，然后评估 使用尖端钙成像技术研究ssMCS +/-阿片样物质信号对MC和SpVC神经活动的影响 行为老鼠总之，这个项目将确定MCS如何通过内源性调节伤害性感受， 阿片样物质信号在躯体定位对齐电路，以指导MCS临床方案的优化。结果 还将在目标和MC输出中提供ssMCS期间和之后的神经活动的第一个报告。 该项目将在斯坦福大学Mark Schnitzer教授（赞助商）的实验室进行， 创新的神经科学。与领先的疼痛神经科学家的指导，教授。格雷格·谢勒 和肖恩麦基（共同赞助商），拟议的培训计划提供了一个很好的机会，我成为 疼痛和阿片类药物神经生物学专家，同时用尖端的 技术.此外，我将通过与Mackey教授及其团队的互动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一个独立的科学家 理想情况下，我可以开始我自己的实验室项目，研究疼痛回路及其与运动回路的交叉。