Using human brain connectivity to identify the causal neuroanatomical substrate of depression symptoms

利用人脑连接来识别抑郁症状的因果神经解剖学基础

• 批准号: 9766881
• 负责人: MICHAEL D FOX
• 金额: $ 51.73万
• 依托单位: BETH ISRAEL DEACONESS MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-19 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9766881
• 关键词: Age; Animal Model; Antidepressive Agents; Area; Biological Markers; Blood Vessels; Brain; Brain region; Data; Data Set; Databases; Deep Brain Stimulation; Diffusion; Distant; Dorsal; Future; Gender; Goals; Grant; Human; Knowledge; Lateral; Lead; Left; Lesion; Link; Localized Lesion; Location; Magnetic Resonance Imaging; Maps; Measures; Mediating; Mental Depression; Modality; Neuroanatomy; Patient imaging; Patients; Penetrating Head Injuries; Pharmaceutical Preparations; Physically Handicapped; Play; Prefrontal Cortex; Refractory; Rest; Role; Severities; Site; Source; Stroke; Symptoms; Techniques; Testing; Therapeutic Trials; Time; Transcranial magnetic stimulation; United States National Institutes of Health; base; biomarker identification; connectome; depressive symptoms; disability; insight; neuroimaging; neuropsychiatric symptom; post stroke; prospective; response; symptomatic improvement; therapeutic target; tractography

PROJECT SUMMARY: Using human brain connectivity to identify the causal neuroanatomical substrate of depression symptoms Depression is the leading cause of disability worldwide and new treatments are needed. Identifying the brain regions causing depression symptoms can lead to treatment targets and better therapies. However, identifying these regions has been difficult. Neuroimaging of patients identifies brain areas where activity correlates with depression symptoms, but can’t determine whether these regions actual cause symptoms. Animal models allow for causal manipulations, but only approximate human symptoms. The goal of this grant is to link depression symptoms to human neuroanatomy in a causal way. Here I focus on two sources of information that can provide theses causal neuroanatomical links. The first is patients with focal brain lesions causing depression symptoms. The second is patients with depression who have received focal brain stimulation for symptomatic relief. In both cases, there is a causal link between symptoms and the site of the lesion or stimulation. However, this causal link can be indirect. Lesion-induced symptoms can come from brain regions connected to the lesion location rather than the lesion location itself. Similarly, benefits of brain stimulation can come from modulation of distant regions connected to the site of stimulation. As such, utilizing these causal sources of information requires a map of human brain connectivity. Due to NIH initiatives like the human connectome project and high powered MRI scanners, such maps are now available. I’ve recently developed a technique that uses these brain connectivity maps to better localize lesion-induced symptoms and identify regions mediating response to focal brain stimulation. Because this technique utilizes existing connectivity data, it does not require connectivity imaging of the patients themselves. As such, the technique can be applied to any lesion or stimulation dataset and has already lent insight into a variety of neuropsychiatric symptoms. Here, I leverage this technique to identify brain regions causing depression symptoms (Aim 1) and brain regions mediating anti-depressant response to focal brain stimulation (Aim 2). Successful completion of these aims will lend insight into the causal neuroanatomical substrate of depression symptoms. Such knowledge will facilitate identification of biomarkers for evaluating future therapies, optimal therapeutic targets for invasive and noninvasive brain stimulation, and individualized targets based on patient-specific symptom profiles. These treatment targets can then be empirically tested in future therapeutic trials.

项目摘要：使用人脑连接来识别因果神经解剖学 抑郁符号的基板 抑郁症是全球残疾的主要原因，需要新的治疗方法。识别大脑 导致抑郁症状的区域会导致治疗靶标和更好的疗法。但是，识别 这些地区很困难。患者的神经影像学识别活动与活动相关的大脑区域 抑郁症状，但无法确定这些区域是否实际引起症状。动物模型 允许因果关系，但仅近似人类症状。这笔赠款的目的是链接 人类神经解剖学的抑郁症状以因果关系。在这里，我专注于两个信息来源 这可以提供有关因果神经解剖学联系的论文。首先是引起局灶性脑损伤的患者 抑郁症状。第二个是抑郁症患者接受了局灶性脑刺激的患者 有症状的缓解。在这两种情况下，症状与病变部位之间都有因果关系或 刺激。但是，这种因果关系可以间接。病变引起的症状可能来自大脑区域 连接到病变位置，而不是病变位置本身。同样，大脑刺激的益处可以 来自与刺激部位相关的远处的调节。因此，使用这些催化 信息源需要人脑连通性的地图。由于NIH像人类这样的倡议 Connectome项目和高功率MRI扫描仪，现在可以使用此类地图。我最近开发了一个 使用这些大脑连接图来更好地定位病变引起的符号并识别的技术 区域介导对局灶性大脑刺激的反应。因为该技术利用了现有的连接性 数据，它不需要患者本身的连通性成像。因此，该技术可以是 应用于任何病变或刺激数据集，并且已经借鉴了各种神经精神病学的洞察力 症状。在这里，我利用这种技术来识别引起抑郁症状的大脑区域（AIM 1）和 大脑区域介导对局灶性脑刺激的抗抑郁反应（AIM 2）。成功完成 这些目标将深入了解抑郁症状的因果神经解剖学底物。这样的 知识将有助于识别生物标志物，以评估未来疗法，最佳治疗靶标 用于侵入性和无创脑刺激以及基于患者特异性症状的个性化靶标 概况。然后可以在将来的治疗试验中对这些治疗靶标进行经验测试。