Ionic conductance correlations tune neuronal network activity to natural inputs

描述（由申请人提供）：已识别的神经元群体表达高度可变的离子电流（或电导）水平。然而，有时发现这些电导的子集是共变的。这表明存在一种神经元活动稳态控制机制，即控制特定活动特征的离子电流相互补偿以保持或稳定神经元活动特征。这主要是由理论研究证实的。然而，电导相关性在神经元网络中所起的实际作用却鲜为人知。本研究的目的是验证神经元使用内在和突触离子通道的相关表达来维持其活动在或多或少狭窄的范围内的假设。这确保了离子电导发生变化时活性的稳定性（如在生长过程中发生的变化，或由神经调节作用和活性依赖性电导改变引起的变化）。我们进一步提出，这种离子电流相关性有助于调节单个细胞，使其对网络内神经元之间的自然输入（例如突触）做出最佳反应，而网络本身可能因动物而异。我们认为这两种现象都与共变电导的性质有关。我们将主要使用电压钳（测量形成螃蟹产生节奏的幽门网络核心的已确定目标神经元中的可变电流水平）和动态钳技术来操纵这些电流（为了检查神经元和网络活动的稳定性）以及神经元和网络的计算建模来测试这些假设。我们将使用定量的方法来评估活性的稳定性，并将实验数据与理论数据进行比较。振荡系统是研究这些问题的理想选择，因为它们的循环动力学提供了良好定义的活动属性，可以量化系统的行为。此外，振荡系统是至关重要的基础

DESCRIPTION (provided by applicant): Populations of identified neurons express highly variable ionic current (or conductance) levels. However, subsets of these conductances are sometimes found to co-vary. This suggests the existence of a mechanism for the homeostatic control of neuronal activity whereby ionic currents controlling specific features of activity compensate for each other to preserve or stabilize that neuronal activity trait. This has been confirmed mostly by theoretical studies. However, the actual roles that conductance correlations play in neuronal networks are poorly understood. The goal of this proposal is to test the hypothesis that Neurons use the correlated expression of intrinsic and synaptic ion channels to maintain their activity bounded within more or less narrow limits. This ensures stability of activiy as ionic conductance changes occur (such as those that take place during growth, or result from neuromodulatory effects, and activity-dependent conductance modifications). We further propose that such Ionic current correlations contribute to tuning individual cells to optimally respond to natural inputs (synaptic for example) between neurons within a network that may themselves vary from animal to animal. We suggest that both of these phenomena are related by the property of co-varying conductances. We will test these hypotheses using, primarily, voltage clamp (to measure -the variable- current levels in identified target neurons that form the core of the rhythm- generating pyloric network of crabs), and dynamic clamp techniques to manipulate these currents (in order to examine the stability of neuronal and network activity), as well as computational modeling of neurons and networks. We will use quantitative measures to evaluate stability of activity and to compare experimental with theoretical data. Oscillatory systems are ideal to study these questions because their recurrent dynamics offers well defined activity attributes to quantify the system's behavior. Moreover, oscillatory systems underlie vital functions in most animals, such as respiration, heartbeat, locomotion, digestion, etc. Thus, understanding the mechanisms that generate rhythmic behaviors and that regulate their stability is essential to develop strategies and therapies to maximize our ability to prevent dysfunction or recovery from neurological disease and injury. The model system we study is ideally suited for this work because its component neurons are very few (reduced to 3 in this case), because all the ionic currents are known and can be measured in individual cells, and because there are distinct activity features that the system naturally maintains constant across individuals, providing a clear and convenient assay for our hypotheses. Success to uncover how robustness of network- wide properties is achieved is expected to provide a new framework to understand homeostasis in the nervous system and to guide future research in the field.