The integration of laboratory data with computational 3-D modeling to analyze the role of the central amygdala in neuropathic pain

项目摘要/摘要 神经性疼痛影响着全世界数百万人的生活。了解以下机制 推动神经病理性疼痛的发展和维持对下一代的进步至关重要 治疗策略。在神经损伤的情况下，可能导致疼痛的一个大脑区域是中央 杏仁核(CEA)。来自人类患者和动物模型的证据表明，短期和长期 杏仁核的变化可能会导致整体的病理状态。细胞类型特异性的爆炸性增长 光遗传学、化学遗传学和生理学方法提供了前所未有的细胞途径 在受伤的情况下的CEA。该领域面临的一个主要挑战是确定如何集成不同来源的数据 了解杏仁核对伤害和疼痛的贡献的方法和实验室。我们最近 开发了第一个使用真实世界细胞类型数据在疼痛背景下计算CEA的模型。这 用生理数据建立的模型，并与体内结果进行了验证，为研究提供了一个可靠的框架 不同细胞类型之间的相互作用及其对疼痛发展的集体贡献。我们的 CEA模型标志着神经病理性疼痛的研究向前迈进了一大步，但同时该模型 它的假设仍然是原始的。该模型在2维空间中表示CEA，并且不能 准确捕捉CEA及其亚核的复杂三维(3-D)结构特性 可能会驱动CEA产生的前伤害性和抗伤害性感觉输出。这项提议的目的是利用 现有和新的湿实验室数据，以建立CEA中疼痛相关神经元的概念验证3D模型 考虑到空间和像元类型的异质性，并确定模型可以预测的程度 活体结果。我们的中心假设是CEA中两种特定细胞类型的三维分布影响 在神经性损伤的背景下的适当的行为反应，并且这种分布可以是 建模以产生对CEA在慢性伤害性感觉发展中的作用的新见解。我们将使用 基于智能体的描述个体生理形态特征的计算模型 CEA中的神经元以及它们之间的相互作用。这种方法将使我们能够捕获复杂性 在CEA系统内，同时保持对本科生的访问权限，包括那些 编程。计算模型将公开提供并开放源代码，它将包括一个 图形用户界面，任何研究人员都可以访问，以便在电子计算机实验之前完成 把时间和资源花在昂贵的体内实验上。计算和湿法实验室实验都是 纳入了这项提案，重点是让本科生参与进来，以支持他们的 发展成为严谨、跨学科、有思想的生物医学研究人员。

PROJECT SUMMARY/ABSTRACT Neuropathic pain impacts the lives of millions of individuals worldwide. Understanding the mechanisms that drive the development and maintenance of neuropathic pain is critical to the advancement of next generation therapeutic strategies. In the context of nerve injury, one brain area that may contribute to pain is the central nucleus of the amygdala (CeA). Evidence from human patients and animal models shows short and long-term changes in the amygdala may contribute to the overall pathologic state. An explosion of cell-type specific optogenetic, chemogenetic, and physiological approaches has provided unprecedented cellular access to the CeA in the context of injury. A major challenge for the field is determining how to integrate data from different approaches and laboratories to understand the amygdala’s contribution to nociception and pain. We recently developed the first computational model of the CeA in the context of pain using real-world cell-type data. This model, built with physiological data and validated against in vivo results, provides a robust framework to study the interactions between different cell types and their collective contributions to the development of pain. Our model of the CeA marks a major step forward in the study of neuropathic pain, but at the same time the model is still primitive in its assumptions. The model represents the CeA in 2-dimensional space and fails to accurately capture the complex 3-dimensional (3-D) structural properties of the CeA and its subnuclei that likely drive pronociceptive and antinociceptive outputs from the CeA. The objective of this proposal is to utilize existing and new wet-lab data to build a proof-of-concept 3-D model of pain-related neurons in the CeA that accounts for spatial and cell-type heterogeneity and determine the extent to which the model can predict in vivo results. Our central hypothesis is that the 3-D distribution of two specific cell types in the CeA influences the appropriate behavioral responses in the context of neuropathic injury and that this distribution can be modeled to produce novel insights into the CeA’s role in the development of chronic nociception. We will use an agent-based computational model to describe the physiological and morphological properties of individual neurons in the CeA and their interactions with one another. This approach will allow us to capture complexity within the CeA system while remaining accessible to undergraduate students, including those new to programming. The computational model, which will be publicly available and open source, will include a graphical user interface that can be accessed by any researcher to complete in silico experiments prior to devoting the time and resources to costly in vivo experiments. Both computational and wet-lab experiments are incorporated in this proposal with a focus on involvement of undergraduate students to bolster their development as rigorous, interdisciplinary, and thoughtful biomedical researchers.