随机中毒对神经元网络时空动力学行为的影响

神经元细胞膜上的离子通道能够被一些有毒的化学物质阻断. 离子通道阻断会降低离子通道的电导率和激活通道数, 影响神经元的放电活动, 进而影响神经网络时空模式的动力学行为. 本文采用具有周期边界的近邻耦合Hodgkin-Huxley神经元网络, 数值研究了钠离子和钾离子通道随机中毒时神经网络时空模式的演化过程. 发现钠离子和钾离子通道随机中毒可以导致螺旋波破裂. 通过分析网络的放电概率, 发现钠离子通道随机中毒降低了神经网络的兴奋性, 且其对中毒的敏感程度与噪声强度有关; 钾离子通道随机中毒增强了神经网络的兴奋性. 与均匀的通道中毒相比, 随机通道中毒的神经网络具有更丰富的动力学行为. 最后, 采用无流边界条件对神经网络进行数值仿真, 得到了类似的结果. 该研究更真实地反映神经系统中毒时整体兴奋性的变化, 从另一个方面揭示离子通道中毒对网络时空行为的影响, 有利于更进一步理解离子通道在网络整体行为中的作用. 关键词： 神经网络 离子通道 随机中毒 时空动力学     

随机边界诱导Izhikevich神经元网络的时空模式转换

在随机边界条件下构建由200×200个Izhikevich神经元组成的方形网络，并利用计算机模拟计算方形网络的时空特性和同步因子，对神经元的放电模式、分岔现象以及方形网络的时空模式和同步性质进行研究。研究结果表明：在相同电流刺激和耦合强度下，由不同放电模式Izhikevich神经元构建的方形网络中，仅当神经元处于Regular Spiking放电模式下才能在网络中观察到螺旋波种子的出现和消失；对于其他放电模式(Fast Spiking, Chattering和Intrinsically Bursting)的Izhikevich神经元构建的方形网络，则无法观察到螺旋波种子的出现。当外界电流刺激恒定时，只有当神经元之间的耦合强度为中等大小时才可在方形网络中观察到螺旋波种子的出现和消亡，相对较小或较大的耦合强度不能诱导神经元网络出现螺旋波种子。对方形神经网络中的同步因子研究发现同步因子随耦合强度的变化存在类似“反共振”的形式。     

白噪声诱发Morris-Lecar模型构成的Ⅱ型兴奋网络产生多次空间相干共振

为研究噪声在网络中的作用及对时空行为的影响, 通过电耦合、近邻连接的Morris-Lecar模型构建了同质可兴奋细胞网络. 单元振子的确定性行为表现为Ⅱ型兴奋性的静息. 在高斯白噪声的作用下, 网络会在较大的噪声强度范围产生螺旋波, 以及在某些较小的噪声强度范围产生杂乱的空间结构. 随着噪声强度的增加, 螺旋波的结构会在简单和复杂之间转换, 或与杂乱的空间结构交替出现. 通过空间结构函数及其信噪比的计算, 发现简单螺旋波的信噪比较大, 复杂螺旋波以及杂乱的时空结构的信噪比较小. 信噪比随着噪声强度的增加会出现多次极大值, 说明白噪声可以在可兴奋细胞网络中诱导多次空间相干共振. 研究结果提示现实的可兴奋系统能有多次机会选择不同强度的噪声加以合理利用.     

螺旋波等离子体放电三维直接数值模拟

在详细考虑电化学反应和粒子碰撞关系的基础上,建立了螺旋波放电三维直接数值计算模型,舍弃以往模型小扰动假设,对Maxwell方程组直接求解以计算电磁场能量沉积份额,扩展了螺旋波等离子体计算模型的精度和适用范围.以Ar为工质气体的仿真结果显示:密度跃升效应和电子温度与放电压力的关系与Toki等和Chen的实验结果符合较好;与经典鞘层理论对比,在粒子数密度、德拜长度、电势以及电子温度的分布上取得高度一致,验证了模型的有效性和精度.利用本文模型研究了低场螺旋波放电过程中的磁场峰值现象,验证了放电室端面的波干涉机理,并发现波干涉的本质是螺旋波分量与其端面回波叠加形成的驻波.     

热敏神经元网络中螺旋波死亡和破裂的数值模拟

实验发现大脑皮层内出现螺旋波且螺旋波对神经元电信号传递有积极作用.利用细胞网络方法从对大脑皮层观察到的螺旋波进行数值模拟.以包含温度因子的热敏神经元模型在二维空间构造规则网络,研究了神经元膜片温度参数对神经元网络中螺旋波演化影响;定义了一类统计同步因子来刻画温度因子引起螺旋波相变(破裂和死亡)的临界条件.发现在规则网络下,当温度超过一定值后螺旋波会死亡和消失而导致整个网络达到均匀同步;在考虑了弱通道噪声情况下,螺旋波温度超越一定临界值则引起螺旋波的破裂.进一步分析了暂时性发烧昏迷的可能机制在于神经系统某些功能区螺旋波传播电信号的中断.     

神经元网络螺旋波诱发机理研究

实验研究发现大脑皮层电活动和信号传播有类似螺旋波的特征.本文利用包含离子通道效应的Hodgkin-Huxley神经元构造规则网络来研究螺旋波的形成机理,利用缺陷阻挡行波的方法在神经元网络中诱导到不同周期的螺旋波,分析了螺旋波产生条件和耦合强度对螺旋波的影响.同时,对脑皮层中螺旋波形成的机理进行了讨论.     

短管螺旋波放电中等离子体参数测量和模式转化研究

对长度为45 cm的短放电管螺旋波放电等离子体进行了Langmuir探针、原子发射光谱以及集成电荷耦合检测器(ICCD)检测诊断,研究螺旋波等离子体的放电特性.Langmuir探针数据显示电子密度在射频功率增加过程中出现两次大幅增长,由此确认了放电模式的转换及螺旋波放电模式的出现.发射光谱测量结果与Langmuir探针测量的电子密度数据一致,发现Ar原子和Ar离子的谱线强度与放电模式变化有着密切相关性.而通过对不同放电模式的ICCD测量,获得射频功率吸收因放电模式转变而变化的方式,认为放电模式转换时电子行为和能量传递方式也发生着变化.     

在具有排斥耦合的神经元网络中有序斑图的熵测量

脑神经网络在一定条件下可以自发出现行波、驻波、螺旋波,这些有序时空斑图的出现往往与某种神经疾病有关,但是其产生的机制尚未完全清楚,如何定量描述这些时空斑图的性质仍需要探索,为了解决这些问题,本文采用Hindmarsh-Rose神经元模型研究了具有排斥耦合的二维双耦合层神经元网络从混沌初相位开始演化的动力学行为,并用改进的集团熵来描述神经元网络的时空斑图.数值模拟结果表明:排斥耦合既可以促进有序斑图的形成,也可以抑制有序斑图的形成.适当选择排斥和兴奋性耦合强度,排斥耦合可导致单螺旋波、多螺旋波、行波、螺旋波和靶波与其他态共存、行波与驻波共存等有序斑图出现,螺旋波、行波出现概率分别达到0.4555和0.1667.靶波与其他态共存和行波与驻波共存出现概率分别达到0.0389和0.1056,我们提出的集团熵可以较好区分这些有序斑图和混沌态.当排斥耦合强度足够大时,网络一般处于混沌态.当网络处于弱耦合状态时,通过计算集团熵发现网络可以出现很大集团,这些结果有助于理解在实验中观察到的现象,从而能为神经疾病治疗提供帮助.     

钾扩散耦合引起的心脏中螺旋波的变化

在某些情况下, 心肌细胞外的钾离子浓度是变化的, 钾离子的横向扩散会导致细胞外钾离子的聚集和产生钾扩散耦合, 用考虑钾扩散耦合的Luo-Rudy相I心脏模型研究了钾扩散耦合对螺旋波动力学的影响. 数值模拟结果表明: 当钾扩散耦合比较强时, 钾扩散耦合使细胞外钾离子浓度先升高, 然后做规则振荡, 导致螺旋波做无规则漫游; 观察到螺旋波的波臂宽度和频率随钾扩散耦合的强度增大而减小, 这样, 当钾扩散耦合足够强时, 钾扩散耦合可以消除螺旋波和时空混沌. 关键词： 钾扩散耦合 螺旋波 时空混沌     

单向耦合神经元网络中螺旋波的自发形成机制

构造一个具有单向耦合的二维神经元网络,引入信息传输熵来描述定向信息传输,采用Hindmarsh-Rose神经元模型研究网络中螺旋波等有序波自发产生的机制.数值模拟表明：适当选取耦合的强度和单向耦合的距离,网络可自发出现螺旋波、行波、靶波和平面波.各种有序波的产生与网络中出现信息间歇定向传输有关,网络出现单或多螺旋波时发生熵共振现象.噪声、抑制性耦合和排斥性耦合诱发螺旋波时网络中也存在信息间歇定向传输.首次发现自维持长平面波,其存在是由于网络存在持续的强信息定向传输.     

Effects of channel noise on firing coherence of small-world Hodgkin-Huxley neuronal networks

We investigate the effects of channel noise on firing coherence of Watts-Strogatz small-world networks consisting of biophysically realistic HH neurons having a fraction of blocked voltage-gated sodium and potassium ion channels embedded in their neuronal membranes. The intensity of channel noise is determined by the number of non-blocked ion channels, which depends on the fraction of working ion channels and the membrane patch size with the assumption of homogeneous ion channel density. We find that firing coherence of the neuronal network can be either enhanced or reduced depending on the source of channel noise. As shown in this paper, sodium channel noise reduces firing coherence of neuronal networks; in contrast, potassium channel noise enhances it. Furthermore, compared with potassium channel noise, sodium channel noise plays a dominant role in affecting firing coherence of the neuronal network. Moreover, we declare that the observed phenomena are independent of the rewiring probability.     

Robustness,Death of Spiral Wave in the Network of Neurons under Partial Ion Channel Block

The development of spiral wave in a two-dimensional square array due to partial ion channel block (Potas- sium, Sodium) is investigated, the dynamics of the node is described by Hodgkin-Huxley neuron and these neurons are coupled with nearest neighbor connection. The parameter ratio x Na (and xK ), which defines the ratio of working ion channel number of sodium (potassium) to the total ion channel number of sodium (and potassium), is used to measure the shift conductance induced by channel block. The distribution of statistical variable R in the two-parameter phase space (parameter ratio vs. poisoning area) is extensively calculated to mark the parameter region for transition of spiral wave induced by partial ion channel block, the area with smaller factors of synchronization R is associated the parameter region that spiral wave keeps alive and robust to the channel poisoning. Spiral wave keeps alive when the poisoned area (potassium or sodium) and degree of intoxication are small, distinct transition (death, several spiral waves coexist or multi-arm spiral wave emergence) occurs under moderate ratio x Na (and xK ) when the size of blocked area exceeds certain thresholds. Breakup of spiral wave occurs and multi-arm of spiral waves are observed when the channel noise is considered.     

Spatial patterns in a network composed of neurons with different excitabilities induced by autapse

It has been identified that autapse can modulate dynamics of single neurons and spatial patterns of neuronal networks. In the present paper, based on the results that autapse can induce type II excitability changed to type I excitability, spatial pattern transitions are simulated in a two-dimensional neuronal network composed of excitatory coupled neurons with autapse which can induce excitability transition. Different spatial patterns including random-like pattern, irregular wave, regular wave, and nearly synchronous behavior are simulated with increasing the percentage (σ) of neurons with type I excitability. When noise is introduced, spiral waves are induced. By calculating signal-to-noise ratio from the spatial structure function and the mean firing probability of neurons, regular waves and spiral waves exhibit optimal spatial correlation, implying the occurrence of spatial coherence resonance phenomenon. The changes of mean firing probability of neurons show that different firing frequency between type I excitability and type II excitability may be an important factor to modulate the spatial patterns. The results are helpful to understand the spatial patterns including spiral waves observed in the biological experiment on the rat cortex perfused with drugs which can induce single neurons changed from type II excitability to type I excitability and block the inhibitory couplings between neurons. The excitability transition, absence of inhibitory coupling, noise as well as the autapse are important factors to modulate the spatial patterns including spiral waves.     

Parameter Diversity Induced Multiple Spatial Coherence Resonances and Spiral Waves in Neuronal Network with and Without Noise

Diversity in the neurons and noise are inevitable in the real neuronal network. In this paper, parameter diversity induced spiral waves and multiple spatial coherence resonances in a two-dimensional neuronal network without or with noise are simulated. The relationship between the multiple resonances and the multiple transitions between patterns of spiral waves are identified. The coherence degrees induced by the diversity are suppressed when noise is introduced and noise density is increased. The results suggest that natural nervous system might profit from both parameter diversity and noise, provided a possible approach to control formation and transition of spiral wave by the cooperation between the diversity and noise.     

Multiple Spatial Coherence Resonances and Spatial Patterns in a Noise-Driven Heterogeneous Neuronal Network

Heterogeneity of the neurons and noise are inevitable in the real neuronal network. In this paper, Gaussian white noise induced spatial patterns including spiral waves and multiple spatial coherence resonances are studied in a network composed of Morris-Lecar neurons with heterogeneity characterized by parameter diversity. The relationship between the resonances and the transitions between ordered spiral waves and disordered spatial patterns are achieved. When parameter diversity is introduced, the maxima of multiple resonances increases first, and then decreases as diversity strength increases, which implies that the coherence degrees induced by noise are enhanced at an intermediate diversity strength. The synchronization degree of spatial patterns including ordered spiral waves and disordered patterns is identified to be a very low level. The results suggest that the nervous system can profit from both heterogeneity and noise, and the multiple spatial coherence resonances are achieved via the emergency of spiral waves instead of synchronization patterns.     

Spiral Waves and Multiple Spatial Coherence Resonances Induced by Colored Noise in Neuronal Network

Gaussian colored noise induced spatial patterns and spatial coherence resonances in a square lattice neuronal network composed of Morris-Lecar neurons are studied.Each neuron is at resting state near a saddle-node bifurcation on invariant circle,coupled to its nearest neighbors by electronic coupling.Spiral waves with different structures and disordered spatial structures can be alternately induced within a large range of noise intensity.By calculating spatial structure function and signal-to-noise ratio(SNR),it is found that SNR values are higher when the spiral structures are simple and are lower when the spatial patterns are complex or disordered,respectively.SNR manifest multiple local maximal peaks,indicating that the colored noise can induce multiple spatial coherence resonances.The maximal SNR values decrease as the correlation time of the noise increases.These results not only provide an example of multiple resonances,but also show that Gaussian colored noise play constructive roles in neuronal network.     

梯度耦合下神经元网络中靶波和螺旋波的诱发研究

神经系统内数量众多的神经元电活动的群体行为呈现一定的节律性和自组织性. 当网络局部区域存在异质性或者受到持续周期性刺激, 则在网络内诱发靶波, 且这些靶波如'节拍器'可调制介质中行波的诱发和传播. 基于Hindmarsh-Rose 神经元模型构造了最近邻连接下的二维神经元网络, 研究在非均匀耦合下神经元网络内有序波的诱发问题. 在研究中, 选定网络中心区域的耦合强度最大, 从中心向边界的神经元之间的耦合强度则按照阶梯式下降. 研究结果表明, 在恰当的耦合梯度下, 神经元网络内诱发的靶波或螺旋波可以占据整个网络, 并有效调制神经元网络的群体电活动, 使得整个网络呈现有序性. 特别地, 当初始值为随机值时, 梯度耦合也可以诱发稳定的有序态. 这种梯度耦合对网络群体行为调制的研究结果有助于理解神经元网络的自组织行为.     

Development and transition of spiral wave in the coupled Hindmarsh--Rose neurons in two-dimensional space

The dynamics and the transition of spiral waves in the coupled Hindmarsh--Rose (H--R) neurons in two-dimensional space are investigated in the paper. It is found that the spiral wave can be induced and developed in the coupled HR neurons in two-dimensional space, with appropriate initial values and a parameter region given. However, the spiral wave could encounter instability when the intensity of the external current reaches a threshold value of 1.945. The transition of spiral wave is found to be affected by coupling intensity D and bifurcation parameter r. The spiral wave becomes sparse as the coupling intensity increases, while the spiral wave is eliminated and the whole neuronal system becomes homogeneous as the bifurcation parameter increases to a certain threshold value. Then the coupling action of the four sub-adjacent neurons, which is described by coupling coefficient D’, is also considered, and it is found that the spiral wave begins to breakup due to the introduced coupling action from the sub-adjacent neurons (or sites) and together with the coupling action of the nearest-neighbour neurons, which is described by the coupling intensity D.