Activity-dependent homeostatic regulation in neural networks

描述(由申请人提供)：神经元网络必须在一生中可靠地发挥作用，尽管分子周转以及发育和环境变化。这在呼吸等重要行为背后的模式生成神经回路中最为明显。网络特性的活动依赖的稳态调节(ADHR)通过回路的电活动与潜在的细胞和突触特性之间的反馈环来支持稳定的网络功能。细胞内钙水平在这个反馈环路中扮演着重要的角色，因为它们是电活动的传感器，并参与细胞内的信号传递，但ADHR背后的通路尚不清楚。这项拨款将使用计算蛮力来检查数百万种不同的ADHR模型，目的是识别支持稳定网络功能并能够在扰动后恢复的调控途径结构。分析成功的调控模型的共同属性将确定ADHR通路的关键特征，并揭示神经元网络如何维持稳定的功能。拟议的研究将使用龙虾幽门模式产生电路作为已建立的模型系统，其中ADHR已在细胞和网络水平上进行了演示。模拟将分三个步骤进行：1)识别区分功能和非功能网络活动的基于钙的活动传感器，2)确定这些传感器如何反馈到神经元属性以实现细胞水平的动态平衡，以及3)测试在细胞水平上成功的调节机制，以确定它们在网络水平支持动态平衡的能力。由于对模式产生回路中突触特性的ADHR知之甚少，实验将确定幽门回路中的突触是否以及如何受到稳态调节，这些实验的结果将为最终的网络水平模拟提供信息。相关性：保持稳定的神经网络功能，特别是在模式产生电路中，对包括人类在内的任何动物都是至关重要的。动态平衡调节失灵可导致网络输出功能障碍，包括沉默或癫痫样活动，并与癫痫和其他癫痫发作障碍以及脑组织对创伤或缺氧的反应有关。这笔赠款将有助于更好地了解神经回路中的体内平衡调节过程，从而为这些疾病的潜在治疗奠定基础。

DESCRIPTION (provided by applicant): Neuronal networks must function reliably throughout life in spite of molecular turnover and developmental and environmental changes. This is most evident for pattern-generating neural circuits underlying vital behaviors such as breathing. Activity-dependent homeostatic regulation (ADHR) of network properties supports stable network function through a feedback loop between a circuit's electrical activity and the underlying cellular and synaptic properties. Intracellular calcium levels play an important role in this feedback loop because they act as sensors of electrical activity and are involved in intracellular signaling, but the pathways underlying ADHR are not understood. This grant will use computational brute force to examine millions of different models of ADHR, with the aim of identifying regulatory pathway structures that support stable network function and can restore it after perturbations. Analyzing the common properties of successful regulation models will identify key features of ADHR pathways and reveal how neuronal networks can maintain stable function. The proposed research will use the lobster pyloric pattern-generating circuit as an established model system in which ADHR has been demonstrated at the cellular and network levels. Simulations will proceed in three steps: 1) identifying calcium-based activity sensors that distinguish functional from non-functional network activity, 2) determining how these sensors feed back onto neuronal properties to achieve homeostasis at the cellular level, and 3) testing regulation mechanisms that are successful at the cellular level for their ability to support homeostasis at the network level. Because little is know about ADHR of synaptic properties in pattern-generating circuits, experiments will determine whether and how synapses in the pyloric circuit are homeostatically regulated, and results from these experiments will inform the final network level simulations. RELEVANCE: Maintaining stable neural network function, especially in pattern-generating circuits, is of vital importance for any animal, including humans. Homeostatic regulation failure can lead to dysfunctional network outputs including silence or seizure-like activity, and has been implicated in epilepsy and other seizure disorders and in the response of brain tissue to trauma or hypoxia. This grant will contribute to a better understanding of homeostatic regulation processes in neural circuits and will thus lay the groundwork for potential treatments of these disorders.