CRCNS: Modeling Impact of Receptor Arrangement on Spike Initiation in Touch

描述（由申请人提供）：这项研究的长期目标是确定哺乳动物的触觉感受器如何将力转化为神经信号，并告知大脑动态环境中的物体。从避免身体伤害到养育孩子等重要的社会互动，触觉对各种行为都是必不可少的。支配皮肤的触觉感受器在其外周形态和生理输出上也同样不同。先前的研究表明，不同种类的触觉感受器产生不同的放电模式，编码物体的空间和时间特征。尽管过去取得了进展，但控制哺乳动物触觉感受器神经输出的原理尚未明确。本应用程序的目的是阐明在小鼠默克尔细胞-神经突复合体中产生神经信号的细胞和系统水平机制，我们将其用作分子，生理和计算研究的模型。这些复合体调节缓慢适应I型（SAI）触摸反应，其分辨精细的空间细节，如盲文模式。我们以高速和保真度提取边缘和物体曲率的能力可能与SAI传入的独特的双相发射模式直接相关。SAI传入神经的形态在触觉感受器中也是独一无二的，因为它与感觉感受器细胞突触耦合。每个SAI传入有一个分支乔木，连接约10-40个默克尔细胞。进化的格言“形式遵循功能”导致了我们的中心假设，即SAI传入的独特结构是其独特的发射特性的基础。这个新的合作项目将通过结合计算模型、显微镜和神经生理学来验证这一假设。我们将使用固体力学、微分方程和统计学来建立新的计算模型，以定义决定双相SAI发射模式的关键原理。为了建立模型，我们将阐明小鼠SAI事件的三维结构，包括默克尔细胞和动作电位起始区的数量和排列。由此产生的模型将对哺乳动物触摸诱发反应的生物学机制做出具体预测。这些预测随后将通过转基因小鼠的神经生理学记录进行实验测试，这些记录可以直接看到默克尔细胞在感受区的情况。这项拟议研究的智力价值在于我们将计算和实验技术结合起来，以确定触摸受体解剖学如何支配生理学。计算的力量使我们能够评估成千上万的可能性，而这些可能性实际上是不可能逐一进行经验检验的。实验观察的力量使我们能够通过可视化特定的解剖结构和分子，以及通过测量神经元输出来构建逼真的模型。这一策略符合一种新兴的生物探索范式——即建立预测模型，首先在建模空间中探索问题，然后在经验空间中测试预测。这个项目是系统工程和神经生物学研究人员之间的一个新项目，他们的职业是致力于理解触摸。该研究计划描述了一个新的合作项目，该项目将受益于我们最近通过皮肤力学研究开发的基础设施，该研究产生了同行评审手稿和会议论文[1,2,3,4]。所提出的研究产生的更广泛的影响将促进对生物系统中力转导机制的理解。该项目将支持系统工程、神经科学和生理学的教学和研究生培训。在这项工作中阐明的生物学原理可能会进一步理解神经信号在其他感觉模式，包括疼痛。我们期望这些模型对工程人工触摸传感器至关重要，这些传感器可以与人类神经系统接口，以恢复触摸灵敏度（例如，烧伤患者和截肢者），以及在医学上的人机操作应用。我们希望实验结果能够影响传感器设计、组织建模、神经生物学、心理物理学、触觉学和皮肤病学等领域的研究人员。结果将在适当的同行评议期刊和会议报告中传播。

DESCRIPTION (provided by applicant): The long-term goal of this research is to determine how mammalian touch receptors transduce forces into neural signals that inform the brain about objects in our dynamic environment. The sense of touch is essential for behaviors that range from avoiding bodily harm to vital social interactions such as child rearing. The touch receptors that innervate the skin are likewise diverse in their peripheral morphologies and physiological outputs. Previous studies demonstrate that different classes of touch receptors produce distinctive firing patterns that encode spatial and temporal features of objects. Despite past progress, the principles that govern neural output in mammalian touch receptors have not been defined. The objective of this application is to elucidate cellular and systems-level mechanisms that generate neural signals in mouse Merkel cell-neurite complexes, which we use as a model for molecular, physiological and computational studies. These complexes mediate slowly adapting type I (SAI) touch responses, which resolve fine spatial details, such as Braille patterns. Our ability to extract edges and object curvature with high speed and fidelity may relate directly to the SAI afferent's distinctive biphasic firing pattern. The SAI afferent's morphology is also unique among touch receptors because it is synaptically coupled to sensory receptor cells. Each SAI afferent has a branching arbor that contacts ~10-40 Merkel cells. The evolutionary maxim 'form follows function' leads to our central hypothesis that the SAI afferent's unique architecture is fundamental to its distinctive firing properties. This new collaborative project will test this hypothesis by combining computational models, microscopy and neurophysiology. We will build novel computational models using solid mechanics, differential equations and statistics to define the key principles that dictate biphasic SAI firing patterns. To inform the modeling, we will elucidate the three dimensional architecture of mouse SAI afferents, including the quantity and arrangement of Merkel cells and action potential initiation zones. The resulting models will make specific predictions about biological mechanisms that underlie touch-evoked responses in mammals. These predictions will then be experimentally tested with neurophysiological recordings from transgenic mice that allow direct visualization of Merkel cells in receptive fields. The intellectual merit of the proposed research lies in our means of joining computational and experimental techniques to determine how touch-receptor anatomy governs physiology. The power of computation allows us to evaluate thousands of possibilities that would be virtually impossible to empirically test one by one. The power of experimental observation allows us to construct realistic models by visualizing specific anatomical structures and molecules, as well as by measuring neuronal outputs. This strategy fits into an emerging paradigm of biological exploration - that of building predictive models to first explore questions in a modeling space and to subsequently test predictions in empirical space. This project is a new venture between researchers in systems engineering and neurobiology whose careers are dedicated to understanding touch. This research proposal describes a new collaborative project that will benefit from infrastructure developed through our recent study of skin mechanics, which resulted in peer-review manuscripts and conference papers [1, 2, 3, 4]. The broader impacts resulting from the proposed research will be to advance the understanding of force transduction mechanisms in biological systems. This project will support teaching and graduate student training in systems engineering, neuroscience and physiology. The biological principles elucidated in this work may further the understanding of neural signaling in other sensory modalities including pain. We expect the models to be critical for engineering artificial touch sensors that can interface with the human nervous system to restore touch sensitivity (e.g., in burn victims and amputees), as well as for applications in human-robotic manipulation in medicine. We expect the experimental results to impact researchers in fields of sensor design, tissue modeling, neurobiology, psychophysics, haptics, and dermatology. Results will be disseminated in appropriate peer-reviewed journals and conference presentations.