兴奋性和抑制性自反馈压制靠近Hopf分岔的神经电活动比较

突触输入刺激神经元产生的电活动,在神经编码中发挥着重要作用.通常认为,兴奋性输入增强电活动,抑制性输入压制电活动.本文选取可调节电流衰减速度的突触模型,研究了兴奋性自突触在亚临界Hopf分岔附近压制神经元电活动的反常作用,与抑制性自突触的压制作用进行了比较,并采用相位响应曲线和相平面分析解释了压制作用的机制.对于单稳的峰放电,快速和中速衰减的兴奋性自突触分别可以诱发频率降低的峰放电和混合振荡(峰放电与阈下振荡的交替),而中速和慢速衰减的抑制性自突触也可以分别诱发频率降低的峰放电和混合振荡.对于与静息共存的峰放电,除上述两种行为外,中速衰减的兴奋性和慢速衰减的抑制性自突触还可以诱发静息.兴奋性和抑制性自突触电流在不同的衰减速度下,分别作用在峰放电的不同相位,才能诱发同类压制行为.结果丰富了兴奋性突触压制电活动反常作用的实例,获得了兴奋性和抑制性自突触压制作用机制的不同,给出了调控神经放电的新手段.     

快自突触反馈诱发混合簇放电的反常变化及分岔机制

簇放电是神经系统复杂的、多时间尺度的非线性现象,具有多样性,在兴奋性或抑制性作用下实现生理功能.近期较多研究发现了与通常概念(抑制性作用引起电活动降低、兴奋性作用引起放电增强)相反的现象,丰富了非线性科学的内涵.本文关注于抑制性和兴奋性自突触反馈都会诱发的一类复杂的混合簇放电产生的反常现象及其分岔机制.利用快慢变量分离,确认了放电的复杂之处:簇结束于极限环的鞍结分岔之后要先经过去极化阻滞才到休止期.进一步,揭示了该鞍结分岔在反常现象的产生中起到了关键作用.抑制性自反馈引起了该分岔的左移导致簇的参数范围变宽,引起簇内峰个数增多和平均放电频率增加;而兴奋性自突触则引起该分岔右移导致电活动降低.与其他类簇放电只在抑制性自反馈下产生反常现象和慢突触诱发的反常现象不同,该结果给出了簇放电的反常现象的新示例及调控机制,展示了反常现象的多样性,有助于认识脑神经元簇放电和自反馈调控的潜在功能.     

基于分岔理论的突触可塑性对神经群动力学特性调控规律研究

神经群模型是典型的非线性系统,具有丰富而复杂的动力学行为模式.神经群兴奋性和抑制性突触具有可塑性,并对神经群动力学特性具有重要调控作用,研究突触可塑性对神经群动力学特性的调控规律具有重要意义.本文基于分岔理论,通过神经群模型兴奋性和抑制性突触增益的余维一分岔分析,分别给出了神经群运行于单稳、双稳、正常和异常极限环振荡状态的兴奋性和抑制性突触增益的单参数区间;进而通过兴奋性和抑制性突触增益的余维二分岔分析给出了神经群运行于上述多种状态的双参数区域.上述结果定量剖析了兴奋性与抑制性突触可塑性及二者的相互作用对神经群动力学特性的调控规律,揭示了兴奋性与抑制性的动态平衡在神经电活动调控中所扮演的关键角色,仿真结果验证了分岔分析的正确性.本文的研究对理解突触可塑性在脑功能的维持及各种神经疾病的诱发机制中所扮演的角色具有重要参考价值.     

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.     

具有时滞的抑制性自突触诱发的神经放电的加周期分岔

神经放电节律在神经系统功能实现中起着重要的作用.具有自突触(起始和结束于同一细胞的突触)的神经元普遍存在于神经系统,本文研究了单神经元模型在抑制性自突触作用下的放电节律.结果发现,随着时滞和/或耦合强度的增加,可以诱发Rulkov神经元模型放电节律的加周期分岔.随着放电节律的周期数的增加,平均放电频率增大,当时滞和/或耦合强度大于某一阈值时,频率大于没有自突触时的放电频率.用快慢变量分离方法可以获得没有自突触的神经放电节律的分岔结构,可用于认识外界负向脉冲诱发的新节律.这些新的节律模式与加周期分岔中的节律模式一致.研究结果不仅揭示了抑制性自突触可以诱发典型的非线性现象——加周期分岔,还给出了抑制性自突触可以提高放电频率的新现象,与以前的自突触压制放电的观点不同,进一步丰富了对抑制性自突触诱发的非线性现象的认识.     

利用相位响应曲线解释抑制性反馈增强神经电活动

在众多实验和理论研究中已经发现自突触通过自反馈电流调节神经元电活动和网络时空行为来实现生理功能.本文通过理论研究,发现在一些合适的时滞下,抑制性自反馈电流能引起放电频率增加,这是不同于传统结果—抑制性作用引起频率降低的新发现.进一步,对于没有自反馈的神经元,发现在作用相位合适的抑制性脉冲电流的作用下,放电的相位会提前,导致放电频率增加,这就表现出对应Hopf分岔的II型相位响应曲线的特征.引起放电频率增加的抑制性脉冲刺激的相位与自反馈的时滞相对应,这也就给出了自反馈能够引起放电频率增强的原因.最后,发现抑制性自反馈的时滞较长或耦合强度较大时,噪声诱发的神经元放电峰-峰间期的变异系数较小,也就是放电精确性提高,与实验发现的慢抑制性自突触诱发放电精确性增加的结果相一致.研究结果揭示了负反馈能增强系统响应这一新现象和相应的非线性动力学机制,提供了调控神经电活动的新手段,有助于认识现实神经系统的自突触的潜在功能.     

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.     

三个不同时间尺度的电耦合模型的组合簇放电

胰岛中间隙连接的胰腺β细胞的簇放电行为对胰岛素分泌起着重要的作用. 本文利用了最小的phantom 簇放电模型, 研究两个电耦合胰腺β细胞具有簇同步的组合簇放电, 其膜电位表现出一个长簇和几个短簇组成的放电簇集和振幅先减小后增大的小振幅阈下振荡的相互转迁. 在两个慢变量和快的膜电位的三维空间中, 分别考虑了中慢变量和慢慢变量作为分岔参数的多层次的快慢动力学分析, 研究这两个时间尺度不同的慢变量如何共同或单独地控制着这种组合簇放电的复杂动力学行为. 特别地, 探讨了耦合强度引起的组合簇放电的每个簇集中短簇个数变化的内在机理. 关键词： 电耦合 具有不同时间尺度的慢变量 组合簇放电 快慢动力学分析     

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.     

基于抑制性突触可塑性的反馈神经回路兴奋性与抑制性动态平衡

大脑皮层的兴奋性与抑制性平衡是维持正常脑功能的前提, 而其失衡会诱发癫痫、帕金森、抑郁症等多种神经疾病, 因此兴奋性与抑制性平衡的研究是脑科学领域的核心科学问题. 反馈神经回路是脑皮层网络的典型连接模式, 抑制性突触可塑性在兴奋性与抑制性平衡中扮演关键角色. 本文首先构建具有抑制性突触可塑性的反馈神经回路模型; 然后通过计算模拟研究揭示在抑制性突触可塑性的调控下反馈神经回路的兴奋性与抑制性可取得较高程度的动态平衡, 并且二者的平衡对输入扰动具有较强的鲁棒性; 其次给出了基于抑制性突触可塑性的反馈神经回路兴奋性与抑制性平衡机理的解释; 最后发现反馈回路神经元数目有利于提高兴奋性与抑制性平衡的程度, 这在一定程度上解释了为何神经元之间会存在较多的连接. 本文的研究对于理解脑皮层的兴奋性与抑制性动态平衡机理具有重要的参考价值.     

Delayed excitatory self-feedback-induced negative responses of complex neuronal bursting patterns

In traditional viewpoint, excitatory modulation always promotes neural firing activities. On contrary, the negative responses of complex bursting behaviors to excitatory self-feedback mediated by autapse with time delay are acquired in the present paper. Two representative bursting patterns which are identified respectively to be "Fold/Big Homoclinic"bursting and "Circle/Fold cycle" bursting with bifurcations are studied. For both burstings, excitatory modulation can induce less spikes per burst for suitable time delay and strength of the self-feedback/autapse, because the modulation can change the initial or termination phases of the burst. For the former bursting composed of quiescent state and burst, the mean firing frequency exhibits increase, due to that the quiescent state becomes much shorter than the burst. However, for the latter bursting pattern with more complex behavior which is depolarization block lying between burst and quiescent state, the firing frequency manifests decrease in a wide range of time delay and strength, because the duration of both depolarization block and quiescent state becomes long. Therefore, the decrease degree of spike number per burst is larger than that of the bursting period, which is the cause for the decrease of firing frequency. Such reduced bursting activity is explained with the relations between the bifurcation points of the fast subsystem and the bursting trajectory. The present paper provides novel examples of paradoxical phenomenon that the excitatory effect induces negative responses, which presents possible novel modulation measures and potential functions of excitatory self-feedback/autapse to reduce bursting activities.     

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.     

Response of Hodgkin–Huxley stochastic bursting neuron to single-pulse stimulus

We investigate Hodgkin–Huxley neuron model with external Gaussian noise in the range of parameters where it exhibits bistability of silent and firing states, and noise-induced bursts occur. We study the response of the system to brief single pulse of current. When noise amplitude increases, the delay time between the stimulus and the first spike decreases substantially even for subthreshold stimulus. The mean number of spikes in a post-stimulus burst has a maximum in a certain range of noise amplitudes. Therefore, we found that Hodgkin–Huxley neuron in the stochastic bursting regime has more improved sensitivity to single-pulse stimulus than in the silent one.     

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.     

Pre-B?tzinger复合体的从簇到峰放电的同步转迁及分岔机制

Pre-Bötzinger复合体是兴奋性耦合的神经元网络,通过产生复杂的放电节律和节律模式的同步转迁参与调控呼吸节律.本文选用复杂簇和峰放电节律的单神经元数学模型构建复合体模型,仿真了与生物学实验相关的多类同步节律模式及其复杂转迁历程,并利用快慢变量分离揭示了相应的分岔机制.当初值相同时,随着兴奋性耦合强度的增加,复合体模型依次表现出完全同步的“fold/homoclinic”,“subHopf/subHopf”簇放电和周期1峰放电.当初值不同时,随耦合强度增加,表现为由“fold/homoclinic”,到“fold/fold limit cycle”、到“subHopf/subHopf”与“fold/fold limit cycle”的混合簇放电、再到“subHopf/subHopf”簇放电的相位同步转迁,最后到反相同步周期1峰放电.完全(同相)同步和反相同步的周期1节律表现出了不同分岔机制.反相峰同步行为给出了与强兴奋性耦合容易诱发同相同步这一传统观念不同的新示例.研究结果给出了preBötzinger复合体的从簇到峰放电节律的同步转迁规律及复杂分岔机制,反常同步行为丰富了非线性动力学的内涵.     

Firing activities in a fractional-order Hindmarsh-Rose neuron with multistable memristor as autapse

Considering the fact that memristors have the characteristics similar to biological synapses, a fractional-order multistable memristor is proposed in this paper. It is verified that the fractional-order memristor has multiple local active regions and multiple stable hysteresis loops, and the influence of fractional-order on its nonvolatility is also revealed. Then by considering the fractional-order memristor as an autapse of Hindmarsh-Rose (HR) neuron model, a fractional-order memristive neuron model is developed. The effects of the initial value, external excitation current, coupling strength and fractional-order on the firing behavior are discussed by time series, phase diagram, Lyapunov exponent and inter spike interval (ISI) bifurcation diagram. Three coexisting firing patterns, including irregular asymptotically periodic (A-periodic) bursting, A-periodic bursting and chaotic bursting, dependent on the memristor initial values, are observed. It is also revealed that the fractional-order can not only induce the transition of firing patterns, but also change the firing frequency of the neuron. Finally, a neuron circuit with variable fractional-order is designed to verify the numerical simulations.     

Phase description of the Huber-Braun neuron model for mammalian cold receptors

The spiking activity of mammalian cold receptors is described by the Huber-Braun neuron model. Sweeping temperature as a control parameter across a biologically relevant range this model exhibits a complex bifurcation structure seen in the sequence of interspike intervals. The model’s distinctive feature is the interaction between a fast spike generating dynamics and a slow subthreshold oscillation. Viewing the spike generation as a cycle, the dynamics may also be modeled phenomenologically by two phases, one for the spike cycle and the second for the slow subthreshold oscillation. In fact, a phase model of temperature-dependent mammalian cold receptors was already proposed by Roper et al. (2000). Here we follow their approach and investigate to what extent this model is able to reproduce the bifurcation patterns of the Huber-Braun model. Special attention is paid to the tonic firing to bursting transition observed in the low temperature range.     

Noise-induced mixed-mode oscillations in a relaxation oscillator near the onset of a limit cycle

A detailed asymptotic study of the effect of small Gaussian white noise on a relaxation oscillator undergoing a supercritical Hopf bifurcation is presented. The analysis reveals an intricate stochastic bifurcation leading to several kinds of noise-driven mixed-mode oscillations at different levels of amplitude of the noise. In the limit of strong time-scale separation, five different scaling regimes for the noise amplitude are identified. As the noise amplitude is decreased, the dynamics of the system goes from the limit cycle due to self-induced stochastic resonance to the coherence resonance limit cycle, then to bursting relaxation oscillations, followed by rare clusters of several relaxation cycles (spikes), and finally to small-amplitude oscillations (or stable fixed point) with sporadic single spikes. These scenarios are corroborated by numerical simulations.