Activity-dependent homeostatic regulation in neural networks

描述（由申请人提供）：神经网络必须在整个生命中可靠地运行，尽管分子更新，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表现得最为明显。网络特性的活动依赖的稳态调节（ADHR）通过电路的电活动和潜在的细胞和突触特性之间的反馈回路支持稳定的网络功能。细胞内钙水平在这种反馈回路中起着重要作用，因为它们充当电活动的传感器，并参与细胞内信号传导，但ADHR的潜在途径尚不清楚。这笔拨款将使用计算蛮力来检查数百万种不同的ADHR模型，目的是确定支持稳定网络功能的调节途径结构，并在扰动后恢复它。分析成功调节模型的共同特性将确定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得到证明。模拟将分三步进行：1)识别区分功能性和非功能性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特性以实现细胞水平的内稳态，以及3)测试在细胞水平上成功的调节机制，因为它们有能力支持网络水平的内稳态。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：维持稳定的神经网络功能，特别是在模式生成电路中，对包括人类在内的任何动物都至关重要。体内平衡调节失败可导致功能失调的网络输出，包括沉默或癫痫样活动，并且与癫痫和其他癫痫性疾病以及脑组织对创伤或缺氧的反应有关。这项资助将有助于更好地理解神经回路中的稳态调节过程，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.