Neuromodulation of Ionic Currents and Neuronal Network Activity

离子电流和神经元网络活动的神经调节

• 批准号: 8434281
• 负责人: JORGE P GOLOWASCH
• 金额: $ 25.45万
• 依托单位: NEW JERSEY INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-12-01 至 2015-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8434281
• 关键词: Affect; Animals; Attention; Awareness; Back; Behavior; Behavioral; Biological Models; Biological Rhythm; Cells; Cognitive; Computer Simulation; Computing Methodologies; Crustacea; Dependence; Digestion; Disease; Ensure; Experimental Models; Funding; Ganglia; Generations; Health; Hormones; Individual; Ion Channel; Knowledge; Locomotion; Long-Term Effects; Mediating; Memory; Memory Disorders; Modeling; Molecular; Nature; Nervous System Physiology; Nervous system structure; Neuromodulator; Neurons; Neurotransmitters; Output; Pattern; Perception; Play; Process; Production; Property; Recovery; Recovery of Function; Regulation; Respiration; Role; Shapes; Sleep Disorders; Sleep Wake Cycle; Stomach; Synapses; System; Techniques; Testing; Time; Trauma; Work; base; cognitive function; design; driving behavior; effective therapy; heart function; neuroregulation; novel; pressure; response; restoration; voltage

DESCRIPTION (provided by applicant): It is well known that neuronal network activity is shaped by extrinsic neuromodulation, synaptic interactions and by the intrinsic properties of each neuron within the network. Intrinsic properties in turn are determined chiefly by the ionic currents expressed by each cell. The changes and regulation of each one of these processes results in a diverse repertoire of network outputs. Neurons and networks have been shown to generate stable electric activity despite wide variability in ionic current levels. Such stability could, however, be compromised if variability is allowed to go unchecked. The global ionic current variability in a neuron could be reduced, and output stability enhanced, if the conductance variance of multiple ionic currents depended on each other and were coordinately regulated. Regulation of ionic current levels can in principle be controlled by two classes of mechanisms: 1) mechanisms that sense a departure of activity from a given set point or range that trigger compensatory changes leading to activity restoration, 2) mechanisms that stabilize activity in an activity-independent manner. The crustacean pyloric and gastric mill networks of the stomatogastric ganglion have been used as model systems to study the role of neuromodulation, synaptic properties and intrinsic neuronal properties on the generation of rhythmic activity. These networks generate rhythmic activity patterns that drive digestive behaviors. Other rhythmic pattern generating networks drive behaviors that are also essential for survival (e.g. respiration, locomotion) or are thought to be key in cognitive functions (attention, memory, etc). Because of their basic nature, it could be argued that these rhythms need to be stable and able to recover from disruptive perturbations to maximize survival. The pyloric network has this kind of robust behavior and will be used to examine biophysical mechanisms that stabilize network output. The guiding hypothesis of this proposal is that neuronal and network activities are regulated by two distinct mechanisms at two different time scales: 1) via slow-acting neuromodulatory effects that control the levels and the correlated expression of multiple ionic currents that are not acutely modulated by them, 2) via fast-acting activity-dependent mechanisms that regulate ionic currents levels. I propose to examine the mechanisms of action of these two regulatory processes, characterize their effects in individual neurons, and examine their role on rhythmic activity generation and stability. We will focus especially on the novel, slow, neuromodulator-mediated process. We will use electrophysiological, molecular and computational methods. The capacity to generate stable neuronal output and to recover such output following disease or trauma is crucial to ensure behavioral stability and, ultimately, survival. The mechanisms underlying such stabilization and recovery of function are not well known, and their understanding may be of enormous therapeutical relevance.

描述（由申请人提供）：众所周知，神经元网络活动是由外在神经调节、突触相互作用和网络内每个神经元的内在性质形成的。内在的性质又主要由每个细胞表达的离子电流决定。这些过程中的每一个的变化和调节导致网络输出的多样化。尽管离子电流水平存在很大差异，但神经元和网络已被证明会产生稳定的电活动。然而，如果允许不加检查地变化，这种稳定性可能会受到损害。如果多个离子电流的电导方差相互依赖并协调调节，则可以降低神经元中离子电流的全局变异性，提高输出稳定性。离子电流水平的调节原则上可以通过两类机制来控制：1）感测活性偏离给定的设定点或范围的机制，其触发导致活性恢复的补偿变化，2）以活性独立的方式稳定活性的机制。甲壳动物幽门和胃磨网络的口胃神经节已被用作模型系统，以研究神经调制，突触特性和内在神经元特性的作用，对产生的节律活动。这些网络产生有节奏的活动模式，驱动消化行为。其他节律模式生成网络驱动的行为也是生存所必需的（例如呼吸，运动）或被认为是认知功能（注意力，记忆力等）的关键。由于它们的基本性质，可以认为这些节律需要稳定，能够从破坏性扰动中恢复，以最大限度地提高生存率。幽门网络具有这种鲁棒的行为，并将用于检查稳定网络输出的生物物理机制。该提议的指导假设是，神经元和网络活动在两个不同的时间尺度上由两种不同的机制调节：1）通过控制不受其急性调节的多个离子电流的水平和相关表达的慢作用神经调节效应，2）通过调节离子电流水平的快作用活动依赖性机制。我建议研究这两个监管过程的作用机制，表征其在单个神经元的影响，并研究其对节律活动的产生和稳定性的作用。我们将特别关注新的，缓慢的，神经调节剂介导的过程。我们将使用电生理学，分子和计算方法。产生稳定的神经元输出和在疾病或创伤后恢复这种输出的能力对于确保行为稳定性和最终生存至关重要。这种稳定和恢复功能的机制尚不清楚，对它们的理解可能具有巨大的治疗意义。

项目成果

Ionic Current Variability and Functional Stability in the Nervous System.

• DOI: 10.1093/biosci/biu070
• 发表时间: 2014-07
• 期刊: Bioscience
• 影响因子: 10.1
• 作者: Golowasch J

Recovery of rhythmic activity in a central pattern generator: analysis of the role of neuromodulator and activity-dependent mechanisms.

• DOI: 10.1007/s10827-011-0338-8
• 发表时间: 2011-11
• 期刊: Journal of computational neuroscience
• 影响因子: 1.2
• 作者: Zhang Y;Golowasch J
• 通讯作者: Golowasch J

Ionic current correlations underlie the global tuning of large numbers of neuronal activity attributes.

• DOI: 10.1523/jneurosci.6500-11.2012
• 发表时间: 2012-09-26
• 期刊: The Journal of neuroscience : the official journal of the Society for Neuroscience
• 作者: Zhao S;Golowasch J
• 通讯作者: Golowasch J

Voltage Dependence of a Neuromodulator-Activated Ionic Current.

• DOI: 10.1523/eneuro.0038-16.2016
• 发表时间: 2016-03
• 期刊: eNeuro
• 影响因子: 3.4
• 作者: Gray M;Golowasch J
• 通讯作者: Golowasch J

Modeling Recovery of Rhythmic Activity: Hypothesis for the role of a calcium pump.

节律活动恢复建模：钙泵作用的假设。

• DOI: 10.1016/j.neucom.2006.10.051
• 发表时间: 2007
• 期刊: Neurocomputing
• 影响因子: 6
• 作者: Zhang,Yili;Golowasch,Jorge
• 通讯作者: Golowasch,Jorge