神经元的发放阈值及能量效率研究

发布时间：2018-01-04 11:05

本文关键词：神经元的发放阈值及能量效率研究　出处：《兰州大学》2016年博士论文　论文类型：学位论文

【摘要】：神经元是神经系统实现其功能的基本单元。理解神经元的功能是理解大脑智能来源的基础。神经元的功能简单来说就是整合接收到的大量信息,然后决定是否产生输出信号。神经元的输出信号称为动作电位,又称发放。一般认为,神经元细胞膜两侧电势差超过一个阈值就会产生动作电位。所以神经元发放的阈值在神经元的信息整合中起着关键作用。实验广泛发现,动作电位的阈值是可变的,而且这种可变性对神经元处理信息有重要影响。目前,关于可变阈值的来源并没有统一的意见,甚至引起不小的争议。神经元的发放要消耗大量的能量。发放耗能在神经系统的总耗能中占据了很大的比例。神经系统处理信息是极其耗能的过程,然而对于动物的生存至关重要,所以其发放的能量效率可能在漫长的进化过程中已经得到了优化。神经元发放的阈值决定着神经元如何编码信息,而发放的能量效率则关系着编码信息的效率。本文第一章介绍本文课题的研究背景;第二章中总结阐述神经元及动作电位的生物学基础知识;第三章给出常见的神经元模型及后面分析中需要用到的动力学基础知识。第四章详细讨论神经元发放的阈值问题。我们提出阈值现象可以按机制不同分为“参数阈值”和“状态阈值”,通常所说的阈值是一种状态阈值,是由状态空间中的“广义分界线”(简称分界线)决定的。我们认为分界线普遍地存在于神经元模型的状态空间中,通过构建一个一般性的可激神经元模型,我们得到了普适的分界线表达式,进而得到普遍的阈值随时间演化的方程。阈值演化方程在相应条件下可以很自然地约化得出与前人的工作一致的结果,而在前人工作中一般是直接假设或者做了一些不太自然的简化才能得到。在此基础上,我们的神经元动力学研究还揭示,阈值电压在不同刺激下的变化是由于系统在状态空间中跨越分界线上的不同点造成的,神经元的分界线和刺激条件决定了阈值电压变化的范围。状态空间中的分界线跨越机制是电压阈值和刺激后的参数阈值的普遍的内在动力学机制。我们还系统地在从一维到四维的多个模型中检验了我们的结果,其中二维和三维的模型中解析的分界线,将对以后的阈值研究有重要意义,而对有着现实对应的四维的经典Hodgkin-Huxley模型的研究也发现了一些有意思的新现象。分界线跨越理论为阈值可变性提供了一个普适的机制,是阈值可变性的一个重要来源。在第五章中,我们研究神经元发放的能量效率,也就是一个神经元在处理信息时消耗单位能量能够传递的信息量。我们计算了Hodgkin-Huxley神经元在有噪声的环境中不同温度不同刺激强度下的信息率和能量效率。我们发现在特定的温度下,信息率或能量效率最大。尽管信息率和能量效率不能同时达到最大化,但是我们也发现神经元在最优能量效率的温度下保持了较高的信息处理能力。我们认为处理信息的能量效率可能对神经系统进化起到更重要的作用。最后,我们对目前的工作做了总结,并展望未来相关的可能的研究方向。
[Abstract]:Neuron is the basic unit of the nervous system to realize its function. Understanding of neuronal function is the base of understanding the brain intelligence sources. A large amount of information the function of neurons is simply the integration of the received, and then decide whether to generate an output signal. The output signal of neurons called potential, also called release. Generally, the neuronal membrane on both sides the potential difference exceeds a threshold will produce action potentials. So neuron threshold neurons in the integration of information plays a key role in the experiment. Widely found that action potential threshold is variable, and the variability of neuronal processing has an important influence on the source of information. At present, the variable threshold and no unified opinion, even caused no small controversy. The neuron spikes to consume large amounts of energy. Energy consumption in the total energy release of the nervous system occupies a large The proportion of the nervous system. Information processing is extremely energy, however, is vital for the survival of the animal, so the energy efficiency issue may have been optimized in the long evolutionary process. Neuron threshold determines how neurons encoding information, and put the energy efficiency affects the efficiency of the first encoding information. This chapter introduces the background of the research topic; the second chapter summarizes basic knowledge of biology and neuronal action potential; need to use the basic knowledge of mechanical neuron model and the third chapter gives the analysis of the common behind. The fourth chapter discusses neuron threshold problem. We propose a threshold phenomenon can be divided into "according to the mechanism of different parameter threshold" and "state threshold", usually said threshold is a state of the threshold is determined by the state space in the "general line" ( Referred to as the dividing line) decision. We believe that state space boundaries generally exist in the neuron model, through the construction of a generic excitable neuron model, we obtain the general boundary expression of pain, and the time evolution equation is obtained. The universal threshold threshold evolution equation can naturally get reduced with previous work consistent results in the corresponding conditions, while in the previous work in general is a direct assumption or do some of the less natural can be simplified. On this basis, we also study on neuron dynamics reveals the change of threshold voltage in different stimuli are due to different points in the state space system across the dividing line between the neuron boundaries and stimulation conditions determine the range of threshold voltage change. The dividing line in the state space is across the threshold and stimulating mechanism After the threshold parameter universal intrinsic dynamic mechanism. We also systematically in multiple models from one-dimensional to four-dimensional in our test results, the analytical model of 2D and 3D in line, the threshold for future research has important significance, but also found some new interesting phenomenon of study on a classical Hodgkin-Huxley model corresponding to the four-dimensional reality. The dividing line across the theory provides a universal mechanism for threshold variability is an important source of threshold variability. In the fifth chapter, we study the energy efficiency of neuron is a neuron, when processing the information consumption information unit energy transfer. We can calculate the temperature under different stimulus intensities in the noisy environment of the information rate and energy efficiency of Hodgkin-Huxley neurons. We found that at a specific temperature Under the maximum information rate or energy efficiency. Although the information rate and energy efficiency can reach the maximum at the same time, but we also found that neurons maintain information processing ability of higher energy efficiency in the optimal temperature. We believe that the energy efficiency of processing information may be more important to the evolution of the nervous system. Finally, we a summary of the present work and look forward to the future possible research direction.

【学位授予单位】：兰州大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：Q42

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