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.     

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.     

Hindmarsh-Rose神经元阵列自发产生螺旋波的研究

采用Hindmarsh-Rose(HR)神经元模型,研究了二维神经元阵列系统从一个具有随机相位分布的初态演化最终是否能自发产生螺旋波的问题.数值结果表明:系统是否出现螺旋波与单个HR神经元的状态、系统的初态和耦合强度有关,其中单个HR神经元的振荡状态起主要作用.当单个HR神经元处于一周期振荡态时,在一定的耦合强度范围内系统都会自发出现多个螺旋波和螺旋波对,出现螺旋波与系统初态无关,只要适当选择耦合强度,在系统中可以出现单个螺旋波.当耦合强度超过某一阈值后,继续增加耦合强度,系统会呈现三种不同的动力学行为,分别与三类初态有关.系统从第一类初态演化将偶尔出现单个螺旋波,系统从第二类和第三类初态演化将分别出现间歇性全局同步振荡和振荡死亡.当单个神经元处于二周期态时,只有当系统神经元的初相位比较均匀分布时,系统才能自发出现螺旋波,而且出现螺旋波的耦合强度范围大为减少.当神经元处于更高的周期态时,系统一般不容易自发出现螺旋波.这些结果有助于人们了解大脑皮层自发产生螺旋波的机制.     

非对称耦合两层可激发介质中的螺旋波动力学

本文采用Bär-Eiswirth模型研究了两层可激发介质中螺旋波的动力学, 两层介质采用抑制和兴奋性非对称耦合. 数值模拟结果表明: 兴奋性非对称耦合可以促进两个不同频率的螺旋波锁频, 即使初始频率相差大, 两螺旋波也能实现锁频, 这种耦合使两个螺旋波具有最强的锁频能力; 当两层介质采用抑制性非对称耦合时, 只有当两个初始螺旋波的频率差比较小才能实现锁频, 而且比一般扩散耦合的锁频范围窄, 两螺旋波锁频能力达到最低水平; 当耦合强度和控制参数适当选取时, 抑制性和兴奋性非对称耦合既可以使其中一层介质维持螺旋波态, 使另一层介质中的螺旋波演化到静息态或低频靶波态, 也可以使两层介质中的螺旋波都漫游, 或都转变成靶波, 最后这两个靶波要么消失, 要么转变成平面波状的振荡斑图, 而且两层介质振荡是反相的, 此外在模拟中还观察到两螺旋波局部间歇锁频现象, 这些结果有助于人们理解在心脏系统中出现的复杂现象.     

神经元网络中局部同步引发的各种效应

在大脑皮层中,神经元大范围的同步放电可以引发癫痫,而癫痫发作期间可以自发出现螺旋波,大量神经元的同步放电与螺旋波自发产生之间的关系目前仍不清楚.本文通过增加水平长程连接构造了具有局域长程耦合区的二维神经元网络,采用Morris-Lecar神经元模型研究了具有多个长方形长程耦合区的神经元网络中波的传播,数值模拟结果表明:传播方向与长程耦合朝向平行的平面波和靶波经过长程耦合区会导致长程耦合区内的神经元同步激发,这种同步激发伴随一部分神经元延迟激发,而另一部分提前激发;当长程耦合区宽度超过临界宽度时,长程耦合区所有神经元延迟激发;当长程耦合区宽度超过最大导通宽度时,波将不能通过长程耦合区.当适当选择长方形长程耦合区的尺寸时,神经元同步激发可使网络出现波回传效应和具有波传播方向的选择性,而且这种波传播方向的选择性对神经元是否处于定态和耦合强度变化很敏感,以致高频平面波列可以部分通过宽度超过最大导通宽度的长程耦合区,因此可以通过对长程耦合区内的神经元施加微扰来控制低频波是否可以通过一定宽度的长程耦合区.对于适当选取的神经元网络结构,当平面波或靶波经过长程耦合区时,网络可自发出现自维持平面波、螺旋波和靶波等现象.本文对产生这些现象的物理机制作了分析.     

通过被动介质耦合的两螺旋波的同步

采用Br模型研究了通过被动介质耦合的两二维可激发系统中螺旋波的同步,被动介质由可激发元素组成,这些元素之间不存在耦合.数值模拟结果表明,被动介质对螺旋波的同步有很大影响,当两系统中的初态螺旋波相同时,被动介质可导致稳定螺旋波发生漫游,螺旋波转变为螺旋波对或反靶波;当两系统中的初态螺旋波不同步时,在适当的参数下,两螺旋波可以实现同步、相同步,此外还观察到两螺旋波波头相互排斥、多螺旋波共存、同步的时空周期斑图、系统演化到静息态等现象.在被动介质中,一般可观察到波斑图,但是在某些情况下,被动介质会出现同步振荡现象.这些结果有助于人们理解心脏系统中出现的时空斑图.     

两层耦合可激发介质中螺旋波转变为平面波

采用Br-Eiswirth模型研究了两层耦合可激发介质中螺旋波的动力学,两层介质通过网络连接,即在每一层介质上,每一列选一个可激发单元作为中心点,在一层介质上同一列的可激发单元只与另一层介质上对应的中心点及其8个邻居有耦合.数值模拟结果表明:通过这种局部耦合,在适当小的耦合强度下两耦合螺旋波可实现同步,增大耦合强度会导致螺旋波漫游和漂移,造成螺旋波不同步,观察到螺旋波与静息态、低频平面波和不规则斑图共存现象.在适当强的耦合强度下,还观察到两螺旋波转变成同步的平面波消失现象.对产生这些现象的物理机理做了讨论.     

两个延迟耦合FitzHugh-Nagumo系统的动力学行为

考虑了两个延迟耦合FitzHugh-Nagumo系统，首先分析两点延迟耦合的动力学行为，给出静息态的局部稳定和不稳定的参数区. 螺旋波同步、共同的静息态以及两个系统不同的状态出现在静息态稳定参数区内，在这些态的过渡耦合强度参数区内会出现很多演化图样，它们反映了螺旋波波头、波体和波尾的不同，也反映空间尺度对螺旋波的影响.讨论了静息态局部不稳定参数区内，两点延迟耦合的动力学行为和相应参数下两个延迟耦合反应-扩散系统的斑图动力学行为. 关键词： FitzHugh-Nagumo系统 螺旋波 同步     

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.     

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。     

Exploring the role of inhibitory coupling in duplex networks

The electrical coupling of myocytes and fibroblasts can play a role in inhibiting electrical impluse propagation in cardiac muscle. To understand the function of fibroblast–myocyte coupling in the aging heart, the spiral-wave dynamics in the duplex networks with inhibitory coupling is numerically investigated by the Br–Eiswirth model. The numerical results show that the inhibitory coupling can change the wave amplitude, excited phase duration and excitability of the system. When the related parameters are properly chosen, the inhibitory coupling can induce local abnormal oscillation in the system and the Eckhaus instability of the spiral wave. For the dense inhibitory network, the maximal decrement(maximal increment) in the excited phase duration can reach 24.3%(13.4%), whereas the maximal decrement in wave amplitude approaches 28.1%. Upon increasing the inhibitory coupling strength, the system excitability is reduced and even completely suppressed when the interval between grid points in the inhibitory network is small enough. Moreover, the inhibitory coupling can lead to richer phase transition scenarios of the system, such as the transition from a stable spiral wave to turbulence and the transition from a meandering spiral wave to a planar wave. In addition, the self-sustaining planar wave, the unique meandering of spiral wave and inward spiral wave are observed. The physical mechanisms behind the phenomena are analyzed.     

Autapse-induced target wave,spiral wave in regular network of neurons

Autapse is a type of synapse that connects axon and dendrites of the same neuron, and the effect is often detected by close-loop feedback in axonal action potentials to the owned dendritic tree. An artificial autapse was introduced into the Hindmarsh-Rose neuron model, and a regular network was designed to detect the regular pattern formation induced by autapse. It was found that target wave emerged in the network even when only a single autapse was considered. By increasing the(autapse density) number of neurons with autapse, for example, a regular area(2×2, 3×3, 4×4, 5×5 neurons) under autapse induced target wave by selecting the feedback gain and time-delay in autapse. Spiral waves were also observed under optimized feedback gain and time delay in autapses because of coherence-like resonance in the network induced by some electric autapses connected to some neurons. This confirmed that the electric autapse has a critical role in exciting and regulating the collective behaviors of neurons by generating stable regular waves(target waves, spiral waves) in the network. The wave length of the induced travelling wave(target wave, spiral wave), because of local effect of autapse, was also calculated to understand the waveprofile in the network of neurons.     

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.     

Dislocation Coupling-Induced Transition of Synchronization in Two-Layer Neuronal Networks

The mutual coupling between neurons in a realistic neuronal system is much complex, and a two-layer neuronal network is designed to investigate the transition of electric activities of neurons. The Hindmarsh-Rose neuron model is used to describe the local dynamics of each neuron, and neurons in the two-layer networks are coupled in dislocated type. The coupling intensity between two-layer networks, and the coupling ratio (Pro), which defines the percentage involved in the coupling in each layer, are changed to observe the synchronization transition of collective behaviors in the two-layer networks. It is found that the two-layer networks of neurons becomes synchronized with increasing the coupling intensity and coupling ratio (Pro) beyond certain thresholds. An ordered wave in the first layer is useful to wake up the rest state in the second layer, or suppress the spatiotemporal state in the second layer under coupling by generating target wave or spiral waves. And the scheme of dislocation coupling can be used to suppress spatiotemporal chaos and excite quiescent neurons.     

Meandering Spiral Waves Induced by Time-Periodic Coupling Strength

Effects of time-periodic coupling strength (TPCS) on spiral waves dynamics are studied by numerical computations and mathematical analyses. We find that meandering or drifting spirals waves, which are not observed for the case of constant coupling strength, can be induced by TPCS. In particular, a transition between outward petal and inward petal meandering spirals is observed when the period of TPCS is varied. These two types of meandering spirals are separated by a drifting spiral, which can be induced by TPCS when the period of TPCS is very close to that of rigidly rotating spiral. Similar results can be obtained if the coupling strength is modulated by a rectangle wave. Furthermore, a kinetic model for spiral movement suggested by Di et al., [Phys. Rev. E 85 (2012) 046216] is applied for explaining the above findings. The theoretical results are in good qualitative agreement with numerical simulations.