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.

抽象的 慢性疼痛和阿片类药物流行的沉重负担促使全球范围内紧急寻找药物 替代性、非成瘾性镇痛方法。一种有前途的替代方案是非侵入性电或磁 刺激运动皮层（MC）。虽然 MC 刺激 (MCS) 已多次被发现可以减少慢性 为了减少人类受试者的疼痛并减少啮齿动物疼痛模型中的伤害行为，主要问题仍然存在 关于 MCS 镇痛作用机制、MC 如何影响伤害感受回路的活动以及如何 提高MCS临床疗效。有证据表明，当 MCS 的镇痛功效增加时， 刺激的目标是运动皮层中与伤害感受起源的身体部位相对应的区域 （体位匹配）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 啮齿动物三叉神经病理性疼痛模型阐明 MCS 镇痛的潜在机制 并定义疼痛临床医生可以用来提高 MCS 疗效的关键 MCS 特征。表征 MCS 机制，我将 1) 量化体位匹配 MCS (ssMCS) 的功效，2) 确定哪种阿片类药物 MCS 抗伤害需要受体亚型，并且 3) 确定内源性阿片类药物如何调节 ssMCS 期间阿片敏感 MC 下行回路至三叉神经尾部脊髓核 (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 功效，我将 使用经典的疼痛行为范例以及尖端的机器学习算法来分析小鼠 行为反应。探讨 MC 体型和内源性阿片类药物信号传导的综合影响 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肽沿着该回路定位，然后评估 使用尖端钙成像技术对 MC 和 SpVC 神经活动进行 ssMCS +/- 阿片类信号传导 行为老鼠。总而言之，该项目将确定 MCS 如何通过内源性调节伤害感受 体细胞排列回路中的阿片类信号传导，指导 MCS 临床方案的优化。结果 还将在 ssMCS 期间和之后在目标和 MC 输出中提供神经活动的第一份报告。 该项目将在斯坦福大学 Mark Schnitzer 教授（赞助者）的实验室进行，环境理想 创新神经科学。在顶尖疼痛神经科学家的指导下，教授们。格雷格谢勒 和肖恩·麦基（共同发起人），拟议的培训计划为我提供了一个极好的机会，使我能够成为 疼痛和阿片类神经生物学专家，同时用尖端技术质疑新颖的科学概念 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名独立科学家 并让我能够开始自己的实验室项目，研究疼痛电路及其与运动电路的交叉点。