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Ionic conductance correlations tune neuronal network activity to natural inputs

离子电导相关性将神经元网络活动调整为自然输入

基本信息

批准号：
8928696
负责人：
JORGE P GOLOWASCH
金额：
$ 38.27万
依托单位：
NEW JERSEY INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-30 至 2016-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8928696
关键词：
Accounting Address Affect Animals Basal Ganglia Behavior Biological Assay Biological Models Biophysical Process Brain Cells Complex Computer Simulation Corpus striatum structure Crabs Data Digestion Disease Ensure Epilepsy Failure Functional disorder Generations Gilles de la Tourette syndrome Goals Growth Health Homeostasis Huntington Disease Individual Informal Social Control Ion Channel Lead Learning Leeches Locomotion Maps Measures Modeling Modification Nervous System Trauma Nervous system structure Neurons Output Parkinson Disease Pattern Phase Play Population Property Recovery Recurrence Relative (related person)Respiration Restless Legs Syndrome Role Synapses System Techniques Testing Theoretical Studies Time Variant Voltage-Clamp Technics Work basal forebrain base biological systems cholinergic member motor disorder nervous system disorder neuron component novel prevent relating to nervous system success trait vector voltage voltage clamp

项目摘要

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.

描述(由申请人提供)：已鉴定的神经元群体表现出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。这表明存在一种控制神经元活动的动态平衡的机制，通过这种机制，控制特定活动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。这在很大程度上得到了理论研究的证实。然而，电导关联在神经网络中扮演的实际角色还知之甚少。这一提议的目的是检验这样一种假设，即神经元使用内在离子通道和突触离子通道的相关表达来将其活动维持在或多或少狭窄的范围内。这确保了在离子电导发生变化时(例如在生长过程中发生的变化，或由神经调节效应引起的变化，以及活动依赖的电导修饰)的活性稳定性。我们进一步提出，这种离子电流相关性有助于调整单个细胞，使其对网络中神经元之间的自然输入(例如突触)做出最佳反应，该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(用于测量形成螃蟹幽门节律网络核心的已识别目标神经元中的可变电流水平)和动态钳制技术来操作这些电流(以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模型来验证这些假设。我们将使用定量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系统，因为它们的循环动力学提供了明确定义的活动属性来量化系统的行为。此外，振荡系统是至关重要的基础。大多数动物的功能，如呼吸、心跳、运动、消化等。因此，了解产生节律性行为并调节其稳定性的机制对于制定策略和治疗方案至关重要，以最大限度地提高我们预防功能障碍或从神经系统疾病和损伤中恢复的能力。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，可以在单个细胞中测量，而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一个清晰和方便的分析。成功揭示全网络特性的稳健性是如何实现的，有望为理解神经系统的动态平衡提供一个新的框架，并指导该领域的未来研究。