Activity-dependent homeostatic regulation in neural networks

神经元网络必须在整个生命过程中可靠地发挥作用，尽管分子转向- 以及发展和环境的变化。这对于模式生成神经网络来说是最明显的。 呼吸等重要行为背后的回路。活动依赖性稳态调节（ADHR） 网络属性通过电路的电气之间的反馈回路支持稳定的网络功能 活动和潜在的细胞和突触特性。细胞内钙离子水平起着重要的作用 在这个反馈回路中，因为它们作为电活动的传感器， 信号转导，但ADHR的潜在途径尚不清楚。这项补助金将使用计算蛮力 研究数百万种不同的ADHR模型，目的是确定调节途径 支持稳定网络功能并在扰动后恢复的结构。分析常见的 成功的调节模型的特性将确定ADHR途径的关键特征，并揭示如何 神经元网络可以保持稳定的功能。这项研究将使用龙虾幽门模式- 生成电路作为已建立的模型系统，其中ADHR已在细胞和 网络层次。模拟将分三个步骤进行：1）识别基于钙的活动传感器， 区分功能性和非功能性网络活动，2）确定这些传感器如何反馈到 在细胞水平上实现体内平衡的神经元特性，以及3）测试调节机制， 在细胞水平上是成功的，因为它们能够在网络水平上支持稳态。因为小 是关于ADHR的突触特性的图案生成电路，实验将确定是否 以及幽门回路中的突触是如何被稳态调节的，以及这些实验的结果。 将通知最终的网络级模拟。相关性：维持稳定的神经网络功能， 特别是在模式生成电路中，对任何动物都至关重要，包括人类。自我平衡 监管失败可能导致功能失调的网络输出，包括沉默或类似于沉默的活动， 涉及癫痫和其他癫痫发作障碍以及脑组织对创伤的反应，或 缺氧这项资助将有助于更好地了解神经系统中的稳态调节过程。 电路，从而为这些疾病的潜在治疗奠定基础。

PROJECT SUMMARY: Neuronal networks must function reliably throughout life in spite of molecular turn- over 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 researchwill 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 disfunctional 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.