基于抑制性突触可塑性的神经元放电率自稳态机制

神经元放电率自稳态是指大脑神经网络的放电率维持在相对稳定的状态.大量实验研究发现神经元放电率自稳态是神经电活动的重要特征,并且放电率自稳态是实现神经信息处理及维持正常脑功能的基础,因此放电率自稳态的研究是神经科学领域的重要科学问题.脑神经网络是一个高度复杂的动态系统,存在大量输入扰动信号及由于动态链接导致的参数摄动,因此如何建立并维持神经元放电率自稳态及其鲁棒性仍有待深入研究.反馈神经回路是皮层神经网络的典型连接模式,抑制性突触可塑性对神经元放电率自稳态具有重要的调控作用.本文通过构建包含抑制性突触可塑性的反馈神经回路模型对神经元放电率自稳态及其鲁棒性进行计算研究.结果表明:在抑制性突触可塑性的作用下,神经元放电率可自适应地跟踪目标放电率,从而取得放电率自稳态;在有外部输入干扰和参数摄动的情况下,神经元放电率具有良好的抗扰动性能,表明放电率自稳态具有很强的鲁棒性;理论分析揭示了抑制性突触可塑性学习规则是神经元放电率自稳态的神经机制;仿真分析进一步揭示了学习率及目标放电率对放电率自稳态建立过程具有重要影响.     

兴奋性自突触引起神经簇放电频率降低或增加的非线性机制

兴奋和抑制性作用分别会增强和压制神经电活动,这是神经调控的通常观念,在神经信息处理中起重要作用.本文选取了放电簇和阈下振荡相交替、放电簇谷值小于阈下振荡谷值的Homoclinic/Homoclinic型簇放电,研究发现时滞和强度合适的兴奋性自突触电流作用在放电簇的谷值附近时,能引起簇内放电个数降低,并进而导致平均放电频率降低,这是不同于通常观念的新现象.进一步,用快慢变量分离获得的分岔和相轨迹,揭示了阈下振荡和放电簇分别对应快子系统的阈下和阈上极限环,兴奋性自突触电流引起阈上极限环向阈下极限环的转迁导致放电提前结束是频率降低原因.并与近期在Fold/Homoclinic簇放电报道的兴奋性自突触诱发的簇内放电个数降低但放电频率增加的现象和机制进行了比较.研究结果丰富了神经电活动的反常现象并揭示了背后的非线性机制,给出了调控簇放电的新手段,揭示了兴奋性自突触的潜在功能.     

兴奋性作用诱发神经簇放电个数不增反降的分岔机制

非线性动力学在识别神经放电的复杂现象、机制和功能方面发挥了重要作用.不同于传统观念,本文提出了兴奋性作用可以降低而不是增加簇内放电个数的新观点.在簇放电模式休止期的适合相位施加强度合适的脉冲或自突触电流,能诱发簇内放电个数降低;电流的施加相位越早,所需的强度阈值越大,簇内放电个数越少.进一步,利用快慢变量分离获得的簇放电的动力学性质进行了理论解释.簇放电模式表现出低电位的休止期和高电位的放电的交替,存在于快子系统的鞍结分岔点和同宿轨分岔点之间;放电起始于鞍结分岔、结束于同宿轨分岔;越靠近同宿轨分岔从休止期跨越到放电所需的电流强度越大.因此,电流在休止期上的作用相位越早,就越靠近同宿轨分岔,因而从休止期跨越到放电需要的电流强度阈值越大,放电起始相位到同宿轨分岔之间的区间变小导致放电个数变少.研究结果丰富了非线性现象及机制,对兴奋性作用提出了新看法,给出了调控簇放电模式的新途径.     

具有自适应反馈突触的神经元模型中的混沌:电路设计

近期文献中报道了在具有自适应反馈突触的神经元模型中,随着参数的变化,存在从两个共存吸引子到一个相连吸引子再到两个共存吸引子的混沌转化现象.本文对此模型进行了电路设计,同时对具有非单调激活函数功能的电路设计进行了细致的研究,并利用Electronic Workbench (EWB)软件对所设计的电路进行了仿真实验,研究了电路中的混沌现象,验证了所设计电路的动力学行为与通过数值模拟结果十分相似. 关键词： 自适应反馈突触 神经元模型 混沌 电路设计     

动态突触、神经耦合与时间延迟对神经元发放的影响

神经元膜电位的受激发放在神经系统的信息传递中起着重要作用.基于一个受动态突触刺激的突触后神经元发放模型,采用数值模拟和傅里叶变换分析的方法研究了动态突触、神经耦合与时间延迟对突触后神经元发放的影响.结果发现:突触前神经元发放频率与Hodgkin-Huxley神经元的固有频率发生共振决定了突触后神经元发放的难易,特定频率范围内的电流刺激有利于神经元激发,动态突触输出的随机突触电流中这些电流刺激所占的比率在很大程度上影响了突触后神经元的发放次数;将突触后神经元换成神经网络后,网络中神经元之间的耦合可以促进神经元的发放,耦合中的时间延迟可以增强这种促进作用,但是不会改变神经耦合对神经元发放的促进模式.     

忆阻突触耦合环形Hopfield神经网络动力学分析及其电路实现

提出一种新型忆阻器模型, 利用标准非线性理论分析三个忆阻特性, 并设计模拟电路。基于忆阻突触, 构建一个忆阻突触耦合环形Hopfield神经网络模型。采用分岔图、李雅普诺夫指数谱、时序图等方法, 揭示与忆阻突触密切相关的特殊动力学行为。数值仿真表明: 在忆阻突触权重的影响下, 它能够产生多种对称簇发放电模式和复杂的混沌行为。实现了该忆阻环形神经网络的模拟等效电路, 并由PSIM电路仿真验证MATLAB数值仿真的正确性。     

Hindmarsh-Rose神经元的随机自共振和噪声影响下的同步

研究了噪声对Hindmarsh-Rose(HR)神经元随机自共振和同步的影响。将高斯白噪声加入HR神经元模型的膜电位上，把外界直流电作为分岔参数，分别考虑参数处于Hopf分岔前、Hopf分岔附近和Hopf分岔后时，噪声影响下的随机自共振现象。两个未经耦合的全同HR神经元，如果接受相同的噪声激励，只要噪声强度高于某临界值，就能达到完全同步。进一步，噪声能够增强弱耦合神经元的完全同步。数值结果表明簇放电的神经元比峰放电的神经元更容易被噪声诱导而达到完全同步，耦合也增强了神经元对噪声激励的灵敏度。     

化学自突触的电导扰动诱导相干或随机双共振现象

神经元的自突触结构具有自反馈的作用,神经递质量子形式的释放使得自突触的自反馈作用容易受到扰动,本文重点研究了化学自突触的电导扰动对FHN神经元电生理活动的影响.首先,恰当的化学自突触参数能够产生动力学行为的分岔现象,诱导不同周期峰放电模式之间的转迁.特别地,自突触的自反馈功能会引起从混沌放电状态到周期的峰放电或准周期的簇放电状态的转迁.其次,基于神经递质释放的量子特征,借助放电频率和变异系数两个指标定量地研究自突触电导的随机扰动对神经元放电活动的影响.数值结果表明自突触电导的扰动在自反馈的作用下能够改变离子通道的活性,不仅提高FHN神经元对外加激励信号的编码效率,而且改变神经元放电活动的规则性,诱导显著的相干或随机双共振现象,其内在机制是电导扰动所引起的神经元系统不稳定的动力学分岔.本文的研究进一步揭示了自突触结构对神经元放电活动自我调节的作用,有待为生理操控自突触结构提供理论参考.     

延迟自反馈控制Hindmarsh-Rose神经元的混沌运动

利用线性时间延迟自反馈方法,研究单个Hindmarsh-Rose（H-R）神经元模型混沌动力学模式的控制问题.分别将增益因子和时间延迟作为控制参数,通过数值模拟分析,发现在增益因子和时间延迟两个参数组合的一些范围内,混沌动力学模式的H-R神经元运动可自动被控制成时间间隔意义上的单峰、2峰、3峰及4峰的周期或多倍周期模式.延迟时间的选取并无特别要求,不必和嵌入在混沌吸引子内的某不稳周期轨道的周期相同,延迟控制自适应地引导混沌轨到相应的放电峰峰间隔的周期模式上. 关键词： H-R神经元 延迟反馈控制 混沌放电模式 峰峰间隔周期     

“Hopf/homoclinic”簇放电和“SubHopf/homoclinic"簇放电之间的同步

以修正过的Morris-Lecar神经元模型为例,讨论了“Hopf/homoclinic”簇放电和“SubHopf/homoclinic"簇放电之间的同步行为.首先,分别考察了同一拓扑类型的两个耦合簇放电神经元的同步行为,发现“Hopf/homoclinic”簇放电比“SubHopf/homoclinic”簇放电达到膜电位完全同步所需要的耦合强度小,即前者比后者更容易达到膜电位完全同步.其次,对这两个不同拓扑类型的簇放电神经元的耦合同步行为进行了讨论.通过数值分析发现随着耦合强度的增加,两种不同类型的簇放电首先达到簇放电同步,然后当耦合强度足够大时甚至可以达到膜电位完全同步,并且同步后的放电类型更接近容易同步的簇放电类型,即“Hopf/homoclinic”簇放电.然而令人奇怪的是此时慢变量并没有达到完全同步,而是相位同步;慢变量之间呈现为一种线性关系.这一点和现有文献的结果截然不同.     

Control of firing activities in thermosensitive neuron by activating excitatory autapse

Temperature has distinct influence on the activation of ion channels and the excitability of neurons, and careful change in temperature can induce possible mode transition in the neural activities. The formation and development of autapse connection to neuron can enhance its self-adaption to external stimulus, and thus the firing patterns in neuron can be controlled effectively. The autapse is activated to drive a thermosensitive neuron, which is developed from the FitzHugh–Nagumo neural circuit by incorporating a thermistor, and the dynamics in the neural activities is explored to find mode dependence on the temperature and autaptic current. It is found that the firing modes can be controlled by temperature, and the neuron is wakened from resting state to periodic oscillation with the increase of temperature. Furthermore, the intensity and the intrinsic time delay in the autapse are respectively adjusted to control the neural activities, and it is confirmed that appropriate setting for autaptic current can balance and enhance the temperature effect on the neural activities.     

Spiking sychronization regulated by noise in three types of Hodgkin—Huxley neuronal networks

In this paper,we study spiking synchronization in three different types of Hodgkin-Huxley neuronal networks,which are the small-world,regular,and random neuronal networks.All the neurons are subjected to subthreshold stimulus and external noise.It is found that in each of all the neuronal networks there is an optimal strength of noise to induce the maximal spiking synchronization.We further demonstrate that in each of the neuronal networks there is a range of synaptic conductance to induce the effect that an optimal strength of noise maximizes the spiking synchronization.Only when the magnitude of the synaptic conductance is moderate,will the effect be considerable.However,if the synaptic conductance is small or large,the effect vanishes.As the connections between neurons increase,the synaptic conductance to maximize the effect decreases.Therefore,we show quantitatively that the noise-induced maximal synchronization in the Hodgkin-Huxley neuronal network is a general effect,regardless of the specific type of neuronal network.     

Effects of fractal gating of potassium channels on neuronal behaviours

The classical model of voltage-gated ion channels assumes that according to a Markov process ion channels switch among a small number of states without memory, but a bunch of experimental papers show that some ion channels exhibit significant memory effects, and this memory effects can take the form of kinetic rate constant that is fractal. Obviously the gating character of ion channels will affect generation and propagation of action potentials, furthermore, affect generation, coding and propagation of neural information. However, there is little previous research on this series of interesting issues. This paper investigates effects of fractal gating of potassium channel subunits switching from closed state to open state on neuronal behaviours. The obtained results show that fractal gating of potassium channel subunits switching from closed state to open state has important effects on neuronal behaviours, increases excitability, rest potential and spiking frequency of the neuronal membrane, and decreases threshold voltage and threshold injected current of the neuronal membrane. So fractal gating of potassium channel subunits switching from closed state to open state can improve the sensitivity of the neuronal membrane, and enlarge the encoded strength of neural information.     

Different types of bursting in Chay neuronal model

Based on actual neuronal firing activities, bursting in the Chay neuronal model is considered, in which V _K, reversal potentials for K⁺, V _C, reversal potentials for Ca²⁺, time kinetic constant λ _n and an additional depolarized current I are considered as dynamical parameters. According to the number of the Hopf bifurcation points on the upper branch of the bifurcation curve of fast subsystem, which is associated with the stable limit cycle corresponding to spiking states, different types of bursting and their respective dynamical behavior are surveyed by means of fast-slow dynamical bifurcation analysis. Supported by the National Natural Science Foundation of China (Grant Nos. 10432010, 10526002 and 10702002)     

Non-smooth bifurcations in a double-scroll circuit with periodic excitation

The fast-slow effect can be observed in a typical non-smooth electric circuit with order gap between the natural frequency and the excitation frequency. Numerical simulations are employed to show complicated behaviours, especially different types of busting phenomena. The bifurcation mechanism for the bursting solutions is analysed by assuming the forms of the solutions and introducing the generalized Jacobian matrix at the non-smooth boundaries, which can also be used to account for the evolution of the complicated structures of the phase portraits with the variation of the parameter. Period-adding bifurcation has been explored through the computation of the eigenvalues related to the solutions. At the non-smooth boundaries the so-called `single crossing bifurcation' can occur, corresponding to the case where the eigenvalues jump only once across the imaginary axis, which leads the periodic burster to have a quasi-periodic oscillation.     

高维广义蔡氏电路中的快慢动力学行为及其分岔分析

讨论了四阶广义蔡氏电路在两时间尺度下的动力学行为. 由数值模拟得到了系统在不同参数条件下的周期簇发解和混沌吸引子. 通过引入快慢分析法,从分岔的角度,以周期解为例, 对系统动力学行为产生的机理及其演化规律进行了理论分析和解释, 其结论与数值计算的结果基本符合.     

交流源作用下介观RLC电路系统量子态随时间的演化

根据量子不变量理论，同时考虑介观电容器极板间电子波函数的耦合作用和电路的耗散,研究介观RLC电路系统在交流电流源作用下动力学的演化过程，并且得到描述系统量子态随时间的演化算符.进一步的分析结果表明，介观RLC电路系统的波函数将由任意的初态演化到一般的压缩态. 关键词： 介观RLC电路 交变电源 不变量理论 时间演化算符     

Realization of fractional-order Liu chaotic system by a new circuit unit

A new circuit unit for the analysis and the synthesis of the chaotic behaviours in a fractional-order Liu system is proposed in this paper. Based on the approximation theory of fractional-order operator, an electronic circuit is designed to describe the dynamic behaviours of the fractional-order Liu system with α = 0.9. The results between simulation and experiment are in good agreement with each other, thereby proving that the chaos exists indeed in the fractional-order Liu system.