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Detection of Fractal Behavior in Temporal Series of Synaptic Quantal Release Events: A Feasibility Study

机译:突触量子释放事件的时间序列中的分形行为的检测:可行性研究。

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摘要

Since the pioneering work of Fatt and Katz at the neuromuscular junction (NMJ), spontaneous synaptic release (minis), that is, the quantal discharge of neurotransmitter molecules which occurs in the absence of action potentials, has been unanimously considered a memoryless random Poisson process where each quantum is discharged with a very low release probability independently from other quanta. When this model was thoroughly tested, for both population and single-synapse recordings, some clear evidence in favor of a more complex scenario emerged. This included short- and long-range correlation in mini occurrences and divergence from mono-exponential inter-mini-interval distributions, both unexpected for a homogeneous Poisson process, that is, with a rate parameter that does not change over time. Since we are interested in accurately quantifying the fractal exponent α of the spontaneous neurotransmitter release process at central synaptic sites, this work was aimed at evaluating the sensitivity of the most established methods available, such as the periodogram, the Allan, factor and the detrended fluctuation analysis. For this analysis we matched spontaneous release series recorded at individual hippocampal synapses (single-synapse recordings) to generate large collections of simulated quantal events by means of a custom algorithm combining Monte Carlo sampling methods with spectral methods for the generation of 1/f series. These tests were performed by varying separately: (i) the fractal exponent α of the rate driving the release process; (ii) the distribution of intervals between successive releases, mimicking those encountered in single-synapse experimental series; (iii) the number of samples. The aims were to provide a methodological framework for approaching the fractal analysis of single-unit spontaneous release series recorded at central synapses.
机译:自Fatt和Katz在神经肌肉接头(NMJ)的开创性工作以来,一致认为自发突触释放(minis),即在没有动作电位的情况下发生的神经递质分子的定量放电,被一致认为是无记忆的随机Poisson过程其中每个量子独立于其他量子以极低的释放概​​率放电。当对该模型进行全面测试时,无论是针对种群还是单突触录音,都出现了一些支持更复杂场景的明确证据。这包括小型事件的短时和长期相关性以及与单指数间的小型时间间隔分布的差异,这对于均质Poisson过程都是意料之外的,即速率参数不会随时间变化。由于我们对准确量化突触中心自发性神经递质释放过程的分形指数α感兴趣,因此这项工作旨在评估可用的最成熟方法的敏感性,例如周期图,艾伦(Allan),因子和去趋势波动分析。对于此分析,我们通过结合蒙特卡罗采样方法和频谱方法的自定义算法,将在单个海马突触处记录的自发释放序列(单突触记录)进行匹配,以生成大量的模拟定量事件,以生成1 / f系列。这些测试是通过分别改变来进行的:(i)驱动释放过程的速率的分形指数α; (ii)连续释放之间的间隔分布,模仿在单突触实验系列中遇到的间隔; (iii)样本数量。目的是提供一种方法框架,用于进行在中央突触处记录的单单位自发释放序列的分形分析。

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