Identifying neuromodulation targets for pain in the human brain

识别人脑疼痛的神经调节目标

• 批准号: 10589120
• 负责人: MICHAEL D FOX
• 金额: $ 22.38万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-15 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10589120
• 关键词: Adverse effects; Analgesics; Atlases; Brain; Brain Mapping; Brain hemorrhage; Brain region; Clinical Trials; Compensation; Data; Data Set; Databases; Dedications; Dependence; Development; Dystonia; Enrollment; Future; Human; Ischemic Stroke; Lesion; Link; Location; Magnetic Resonance Imaging; Maps; Mental Depression; Mental disorders; Metabolism; Methods; Motor Cortex; Neuroanatomy; Neurologic; Neurologic Symptoms; Pain; Pain Map; Pain management; Parkinson Disease; Patients; Quality of life; Questionnaires; Reporting; Rest; Symptoms; Testing; Thalamic structure; Transcranial magnetic stimulation; Tremor; addiction; brain based; central pain; clinically significant; cohort; fluorodeoxyglucose positron emission tomography; improved; metabolic imaging; nervous system disorder; neuroimaging; neuropsychiatric symptom; neuroregulation; novel strategies; pain relief; painful neuropathy; pharmacologic; post stroke; post stroke pain; prospective; psychiatric symptom; side effect; stroke outcome; text searching; thalamic pain; therapeutic target; Adverse effects; Analgesics; Atlases; Brain; Brain Mapping; Brain hemorrhage; Brain region; Clinical Trials; Compensation; Data; Data Set; Databases; Dedications; Dependence; Development; Dystonia; Enrollment; Future; Human; Ischemic Stroke; Lesion; Link; Location; Magnetic Resonance Imaging; Maps; Mental Depression; Mental disorders; Metabolism; Methods; Motor Cortex; Neuroanatomy; Neurologic; Neurologic Symptoms; Pain; Pain Map; Pain management; Parkinson Disease; Patients; Quality of life; Questionnaires; Reporting; Rest; Symptoms; Testing; Thalamic structure; Transcranial magnetic stimulation; Tremor; addiction; brain based; central pain; clinically significant; cohort; fluorodeoxyglucose positron emission tomography; improved; metabolic imaging; nervous system disorder; neuroimaging; neuropsychiatric symptom; neuroregulation; novel strategies; pain relief; painful neuropathy; pharmacologic; post stroke; post stroke pain; prospective; psychiatric symptom; side effect; stroke outcome; text searching; thalamic pain; therapeutic target

Identifying neuromodulation targets for pain in the human brain Neuropathic pain is prevalent across many different neurological and psychiatric disorders and has one of the largest adverse effects on quality of life. Pharmacological pain treatments often have limited efficacy and undesirable side effects, including dependence and addiction. Neuromodulation treatments such as transcranial magnetic stimulation show promise for pain while avoiding the side effects associated with pain medications. An obstacle to improving neuromodulation treatment is identifying the human brain regions responsible for pain. Traditional functional neuroimaging studies only identify correlates of pain which could be causing symptoms, compensating for symptoms, or simply serving as a marker of symptoms. This ambiguity is a problem when seeking to identify therapeutic targets. Unlike functional neuroimaging, lesion studies allow for casual links between symptoms and human neuroanatomy. The PI has developed and validated a new method to identify neuromodulation targets in the human brain based on brain lesions and a map of human brain connectivity. Called lesion network mapping, this approach has been used to map numerous neurological and psychiatric symptoms to brain networks (Fox 2018, NEJM). Brain networks identified using this approach have proven to be effective neuromodulation targets for symptoms such as tremor, Parkinson’s disease, dystonia, and depression. Our preliminary data suggests this method is equally valuable for mapping pain, including identification of therapeutic targets. Here, we will use this approach to map pain to a human brain circuit based on lesion locations previously reported to cause pain (Aim 1), a dedicated dataset focused on thalamic lesions causing or not causing pain (Aim 2), and a prospective dataset of patients longitudinally assessed for development of post-stroke pain (Aim 3). We hypothesize that; (1) lesions causing pain will map to a common brain network; (2) this network will show abnormal metabolism in patients with post stroke pain, (3) this network will predict who will develop post-stroke pain; and (4) this pain network will include primary motor cortex, our best validated neuromodulation target for pain. Completion of these aims will identify a candidate human brain network causally linked to pain. Once identified, this network can be validated in future trials with more detailed characterization of post stroke pain and used as an improved target for neuromodulation that can be tested in clinical trials.

确定人脑疼痛的神经调节靶 神经性疼痛在许多不同的神经系统和精神疾病中普遍存在，并且具有其中之一 对生活质量的最大不利影响。药理学疼痛治疗通常的有效性有限， 神经调节治疗，例如经颅 磁刺激显示出疼痛的希望，同时避免了与止痛药有关的副作用。一个 改善神经调节治疗的障碍是确定负责疼痛的人脑区域。 传统的功能性神经影像学研究仅确定可能导致症状的疼痛的相关性， 补偿症状，或者简单地用作症状的标志。这种歧义是一个问题 寻求识别治疗靶标。与功能性神经成像不同，病变研究允许休闲联系 症状和人类神经解剖学之间。 PI已开发并验证了一种新方法来识别 基于脑部病变和人脑连接图的人脑中的神经调节靶标。 称为病变网络映射，该方法已用于绘制众多神经和精神病学 大脑网络的症状（FOX 2018，NEJM）。使用这种方法确定的大脑网络已证明 有效的神经调节目标，例如震颤，帕金森氏病，肌张力障碍和 沮丧。我们的初步数据表明，此方法对于映射疼痛同样有价值，包括 鉴定治疗靶标。在这里，我们将使用这种方法将疼痛映射到基于人脑电路的 在先前报道引起疼痛的病变位置（AIM 1），这是一个专门针对丘脑病变的数据集 引起或不引起疼痛（AIM 2），并纵向评估患者的前瞻性数据集 冲程后疼痛的发展（AIM 3）。我们假设这一点； （1）导致疼痛的病变将映射到常见 大脑网络； （2）该网络将显示中风后疼痛患者的异常代谢，（3）该网络 将预测谁将患上势后疼痛； （4）这个疼痛网络将包括主电机皮层，我们的 疼痛的最佳验证神经调节靶标。这些目标的完成将确定候选人的大脑 网络意外与疼痛有关。一旦确定，该网络就可以在以后的试验中得到更详细的验证 卒中后疼痛的表征，并用作改进的神经调节目标，可以在 临床试验。