Ionic conductance correlations tune neuronal network activity to natural inputs

描述（由申请人提供）：鉴定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的稳态控制机制，由此控制活动的特定特征的离子电流相互补偿以保持或稳定该神经元活动特征。这主要是通过理论研究得到证实的。然而，电导相关性在神经元网络中的实际作用却知之甚少。该提议的目的是检验神经元使用内在和突触离子通道的相关表达来维持其在或多或少狭窄的范围内的活动的假设。这确保了当离子电导发生变化时活性的稳定性（例如在生长期间发生的那些，或由神经调节作用和活性依赖性电导修饰引起的那些）。我们进一步提出，这种离子电流的相关性有助于调整单个细胞，以最佳地响应网络内神经元之间的自然输入（例如突触），这些神经元本身可能因动物而异。我们认为，这两种现象是相关的属性的共变电导。我们将测试这些假设，主要使用，电压钳（测量-可变-电流水平，在确定的目标神经元，形成核心的节奏产生幽门网络的螃蟹），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。我们将使用定量测量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定义良好的活动属性来量化系统的行为。此外，振荡系统是重要的 因此，了解产生节律行为并调节其稳定性的机制对于开发策略和疗法以最大限度地提高我们预防功能障碍或从神经疾病和损伤中恢复的能力至关重要。我们研究的模型系统非常适合这项工作，因为它的组成神经元非常少（在这种情况下减少到3个），因为所有的离子电流都是已知的，并且可以在单个细胞中测量，并且因为有不同的活动特征，系统自然地在个体之间保持恒定，为我们的假设提供了清晰和方便的分析。成功揭示如何实现网络范围特性的鲁棒性有望为理解神经系统中的稳态提供新的框架，并指导该领域的未来研究。

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.