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.     

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.     

一类自突触作用下神经元电路的设计和模拟

神经元在自突触作用下可以诱发各类放电活动的迁移, 神经元动作电位对电自突触的响应比较敏感. 通常用包含延迟因子和增益的反馈回路电流来刻画自突触对神经元动作电位的影响. 基于Pspice软件, 设计了包含自突触效应的神经元电路, 用以延迟反馈电路来模拟电自突触对电位的调制作用. 研究结果发现: 1)在外界刺激和电自突触回路协同作用下, 神经元电路输出信号可以呈现静息态, 尖峰放电, 簇放电状态. 2)在时变增大的外界刺激下和自突触回路驱动下, 神经元电路的输出电位序列在多种电活动模式之间(静息, 尖峰放电, 簇放电)交替出现, 其机理在于自突触回路具有记忆特性, 神经元对于不同的外界刺激可以做出不同模式的响应. 3)在给定比较大外界刺激下, 改变反馈回路的增益, 发现电路输出的序列也可以呈现不同模式交替, 即神经元对于相同的刺激可以通过自我调节自突触增益来产生不同模式的响应, 其机理可能在于回路的有效反馈, 这有助于理解突触的可塑性.     

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.     

蚱蝉Cryptotympana atrata听觉的电生理研究

本文报道了蚱蝉Cryptotympana atrata听觉初级神经元和中间神经元的声反应特征和方向灵敏度。这些神经元有基本上相同、并与蚱蝉鸣声的主能峰一致的调谐频率。它们对声强编码的动态范围为阈上0-40 dB,声强每提高10dB神经脉冲发放约增加两个。它们有较好的方向灵敏度,在最佳反应频率处听觉神经元对对侧声源刺激与同侧声源刺激的反应阈差达10—12dB。     

二维格子神经元网络的振动共振和非线性振动共振

本文采用数值模拟的方法, 在通过电突触耦合或化学突触耦合的二维格子神经元网络中, 研究了FitzHugh-Nagumo神经元受到双频信号输入时神经元网络对低频信号的响应特性. 结果表明:当固定受到双频输入信号的神经元在体系中所占的比例且FitzHugh-Nagumo神经元参数处于可激发区域时双频信号中的高频部分可诱导出动作电位产生, 而且随着高频输入信号强度的增加, 神经元网络对低频输入信号响应先增大后减小, 出现了极大值, 即发生了振动共振现象. 另外本文还研究了神经元网络对低频输入信号的二次谐波的响应, 同样发现了非线性振动共振现象, 并且体系对低频信号的响应随着其频率ω 的增加也产生共振现象, 即发生了双共振现象. 上述共振现象在以电突触耦合的二维格子神经元网络中和以化学突触耦合的二维格子神经元网络中都可以观察到. 当固定双频输入信号中高频输入信号强度时, 随着受到双频输入信号的神经元在体系中所占比例的变化, 电突触耦合的二维格子神经元网络对低频输入信号的响应与化学突触耦合的二维格子神经元网络对低频输入信号的响应相比有很大的不同.     

两个非耦合Hindmarsh-Rose神经元同步的非线性特征研究

利用Hindmarsh-Rose(HR)神经元输出的膜电压作为刺激调整两个具有不同初始条件的非耦合HR神经元的电流输入，通过分析神经元放电峰峰间期(ISI)的分布揭示了两个神经元同步过程轨道演化的机理.在周期信号刺激下，两个具有相同参数原处于混沌状态的神经元可以 实现完全同步，且可以同步到不同于刺激信号频率的周期响应上；两个具有不同参数的神经 元可以实现相位同步，参数差别较小的两个神经元可以相位同步到与刺激信号不同频率的周 期响应上，参数差别较大的两个神经元只可能相位同步到与刺激信号相同频率的周期响应上 .混沌信号刺激两个神经元只可能同步到产生混沌信号神经元的放电模式上，可见混沌刺激 更有利于神经元信息编码与解码.分析两个被调整神经元系统的最大条件Lyapunov 指数(Lmc )与刺激强度k的关系表明当k达到某一阈值时两个系统的Lmc均为负值是两个系统实现同 步的必要条件.平均发放率相同的混沌刺激和周期刺激相比较混沌刺激更容易使两个神经元 实现同步，表明混沌刺激产生的效应更强，该结论与实验结果相符合. 关键词： 放电峰峰间期 同步 相位同步 条件Lyapunov 指数     

铝基薄膜忆阻器作为感觉神经系统的习惯化特性

感觉神经系统可在外界刺激与生物体反应之间建立联系.感觉神经系统中的最小单位神经元可直接将外界刺激传递至中枢神经,再由中枢神经通过控制和调节生物体对外界刺激作出反应.神经突触连接了相邻神经元进行脉冲信息传递功能.习惯化是神经突触在信息传递中过滤外界无关信息时的一个基本特性,可以让感觉神经系统更快速地适应外界环境变化.忆阻器模拟神经突触功能在近年获得进展,然而针对以忆阻器为基础的具有习惯化特性的神经突触以及完整神经系统的研究相对匮乏.本文利用磁控溅射技术制备了厚度约为40 nm且含铝纳米颗粒的氮化铝薄膜忆阻器,并发现这种结构忆阻器对于重复的外界刺激有明显的习惯化行为,该行为与感觉神经系统的习惯化特性极为相似.若将这种具有习惯化的神经突触与感觉神经元串联,可形成LIF(leaky integrate-and-fire)生物模型模拟完整的神经系统行为,也为忆阻器在第三代神经网络(脉冲神经网络)中的应用提供理论参考.     

双耳幅值差确定声源方向的神经信息处理机理研究

神经信息系统实质上是定量系统, 应引起足够重视. 关于神经系统的定量研究方面的报道比较少见. 这一问题将会影响进一步的研究, 如双耳声音定向. 双耳定向是定量测量, 用定性分析的方法无法满足要求. 已有的生理实验发现声音输入信号强度与听觉神经的输出频率存在单调递增关系, 所以本文中声音强度的变化被简化成神经脉冲频率的变化. 本文基于圆映射和符号动力学原理, 建立了神经回路定量模型, 模型中对同侧输入回路采用兴奋性耦合, 对侧输入回路采用抑制性耦合, 并考虑神经元间突触连接的量子释放特征, 采用化学耦合模型实现连接, 用耦合系数表示神经元间的耦合程度. 采用Hodgkin-Huxley模型仿真研究听觉神经回路的输入/输出脉冲序列关系. 在已经仿真过的参数范围, 模型在输入信号变化与输出脉冲频率变化间存在单调递增/递减的关系. 对于单输入单输出的神经元, 采用符号动力学方法进行符号化; 对于多输入单输出的神经元, 采用分析各输出脉冲的产生时间, 判断其变化位置, 从神经脉冲序列中得到对应的两耳声音幅值差变化, 以此定位声源. 随着输出脉冲数的增加, 符号序列的长度增加, 符号序列对输入信号变化敏感, 能够得到较高的测量精度. 仿真结果表明这个模型是定量的, 神经脉冲序列能够区分信号的大小.     

基于忆容器件的神经形态计算研究进展

人工智能的快速发展需要人工智能专用硬件的快速发展,受人脑存算一体、并行处理启发而构建的包含突触与神经元的神经形态计算架构,可以有效地降低人工智能中计算工作的能耗.记忆元件在神经形态计算的硬件实现中展现出巨大的应用价值;相比传统器件,用忆阻器构建突触、神经元能极大地降低计算能耗,然而在基于忆阻器构建的神经网络中,更新、读取等操作存在由忆阻电压电流造成的系统性能量损失.忆容器作为忆阻器衍生器件,被认为是实现低耗能神经网络的潜在器件,引起国内外研究者关注.本文综述了实物/仿真忆容器件及其在神经形态计算中的最新进展,主要包括目:前实物/仿真忆容器原理与特性,代表性的忆容突触、神经元及神经形态计算架构,并通过总结近年来忆容器研究所取得的成果,对当前该领域面临的挑战及未来忆容神经网络发展的重点进行总结与展望.     

Improvement of signal transmission through spike-timing-dependent plasticity in neural networks

We explore the effects of spike-timing-dependent plasticity (STDP) on weak signal transmission in a noisy neural network. We first consider the network where an ensemble of independent neurons, which are subjected to a common weak signal, are connected in parallel to a single postsynaptic neuron via excitatory synapses. STDP can make the signal transmission more efficient, and this effect is more prominent when the presynaptic activities exhibit some correlations. We further consider a two-layer network where there are only couplings between two layers and find that postsynaptic neurons can fire synchronously under suitable conditions. Both the reliability and timing precision of neuronal firing in the output layer are remarkably improved with STDP. These results indicate that STDP can play crucial roles in information processing in nervous systems.Received: 23 March 2004, Published online: 12 July 2004PACS: 87.18.Sn Neural networks - 87.17.Aa Theory and modeling; computer simulation     

Equalization of synaptic efficacy by synchronous neural activity

It is commonly believed that spike timings of a postsynaptic neuron tend to follow those of the presynaptic neuron. Such orthodromic firing may, however, cause a conflict with the functional integrity of complex neuronal networks due to asymmetric temporal Hebbian plasticity. We argue that reversed spike timing in a synapse is a typical phenomenon in the cortex, which has a stabilizing effect on the neuronal network structure. We further demonstrate how the firing causality in a synapse is perturbed by synchronous neural activity and how the equilibrium property of spike-timing dependent plasticity is determined principally by the degree of synchronization. Remarkably, even noise-induced activity and synchrony of neurons can result in equalization of synaptic efficacy.     

Impact of delays and rewiring on the dynamics of small-world neuronal networks with two types of coupling

We study synchronization transitions and pattern formation on small-world networks consisting of Morris-Lecar excitable neurons in dependence on the information transmission delay and the rewiring probability. In addition, networks formed via gap junctional connections and coupling via chemical synapses are considered separately. For gap-junctionally coupled networks we show that short delays can induce zigzag fronts of excitations, whereas long delays can further detriment synchronization due to a dynamic clustering anti-phase synchronization transition. For the synaptically coupled networks, on the other hand, we find that the clustering anti-phase synchronization can appear as a direct consequence of the prolongation of information transmission delay, without being accompanied by zigzag excitatory fronts. Irrespective of the coupling type, however, we show that an appropriate small-world topology can always restore synchronized activity if only the information transmission delays are short or moderate at most. Long information transmission delays always evoke anti-phase synchronization and clustering, in which case the fine-tuning of the network topology fails to restore the synchronization of neuronal activity.     

Phase synchronization of bursting neural networks with electrical and delayed dynamic chemical couplings

Diffusive electrical connections in neuronal networks are instantaneous, while excitatoryor inhibitory couplings through chemical synapses contain a transmission time-delay.Moreover, chemical synapses are nonlinear dynamical systems whose behavior can bedescribed by nonlinear differential equations. In this work, neuronal networks withdiffusive electrical couplings and time-delayed dynamic chemical couplings are considered.We investigate the effects of distributed time delays on phase synchronization of burstingneurons. We observe that in both excitatory and Inhibitory chemical connections, the phasesynchronization might be enhanced when time-delay is taken into account. This distributedtime delay can induce a variety of phase-coherent dynamical behaviors. We also study thecollective dynamics of network of bursting neurons. The network model presents theso-called Small-World property, encompassing neurons whose dynamics have two time scales(fast and slow time scales). The neuron parameters in such Small-World network, aresupposed to be slightly different such that, there may be synchronization of the bursting(slow) activity if the coupling strengths are large enough. Bounds for the criticalcoupling strengths to obtain burst synchronization in terms of the network structure aregiven. Our studies show that the network synchronizability is improved, as itsheterogeneity is reduced. The roles of synaptic parameters, more precisely those of thecoupling strengths and the network size are also investigated.     

Delay-induced synchronization transitions in small-world neuronal networks with hybrid electrical and chemical synapses

We study the dependence of synchronization transitions in small-world networks of bursting neurons with hybrid electrical–chemical synapses on the information transmission delay, the probability of electrical synapses, and the rewiring probability. It is shown that, irrespective of the probability of electrical synapses, the information transmission delay can always induce synchronization transitions in small-world neuronal networks, i.e., regions of synchronization and nonsynchronization appear intermittently as the delay increases. In particular, all these transitions to burst synchronization occur approximately at integer multiples of the bursting period of individual neurons. In addition, for larger probability of electrical synapses, the intermittent synchronization transition is more profound, due to the stronger synchronization ability of electrical synapses compared with chemical ones. More importantly, chemical and electrical synapses can perform complementary roles in the synchronization of hybrid small-world neuronal networks: the larger the electrical synapse strength is, the smaller the chemical synapse strength needed to achieve burst synchronization. Furthermore, the small-world topology has a significant effect on the synchronization transition in hybrid neuronal networks. It is found that increasing the rewiring probability can always enhance the synchronization of neuronal activity. The results obtained are instructive for understanding the synchronous behavior of neural systems.     

Equilibrium properties of temporally asymmetric Hebbian plasticity

A theory of temporally asymmetric Hebb rules, which depress or potentiate synapses depending upon whether the postsynaptic cell fires before or after the presynaptic one, is presented. Using the Fokker-Planck formalism, we show that the equilibrium synaptic distribution induced by such rules is highly sensitive to the manner in which bounds on the allowed range of synaptic values are imposed. In a biologically plausible multiplicative model, the synapses in asynchronous networks reach a distribution that is invariant to the firing rates of either the presynaptic or postsynaptic cells. When these cells are temporally correlated, the synaptic strength varies smoothly with the degree and phase of their synchrony.     

Development of synaptic connectivity onto interneurons in stratum radiatum in the CA1 region of the rat hippocampus

Background  

The impact of a given presynaptic neuron on the firing probability of the postsynaptic neuron critically depends on the number of functional release sites that connect the two neurons. One way of determining the average functional synaptic connectivity onto a postsynaptic neuron is to compare the amplitudes of action potential dependent spontaneous synaptic currents with the amplitude of the synaptic currents that are independent of action potentials ("minis"). With this method it has been found that average synaptic connectivity between glutamatergic CA3 and CA1 pyramidal cells increases from single connections in the neonatal rat, to multiple connections in the young adult rat. On the other hand, γ-aminobutyric acid (GABA)ergic interneurons form multiple connections onto CA1 pyramidal cells already in the neonatal rat, and the degree of multiple GABAergic connectivity is preserved into adulthood. In the present study, we have examined the development of glutamate and GABA connectivity onto GABAergic CA1 stratum radiatum interneurons in the hippocampal slice, and compared this to the connectivity onto CA1 pyramidal neurons.     

最小神经元模型放电起始动态控制与分析

本文采用最小神经元模型,从生理学角度设计wash-out滤波器,实现了不同放电起始动态机理之间的转换,并证明wash-out滤波器控制通过影响阈下电流的竞争结果改变了神经元的放电起始动态机理. 关键词： 放电起始动态机理 阈下电流竞争 最小神经元模型 wash-out滤波器     

Modeling and dynamics of double Hindmarsh-Rose neuron with memristor-based magnetic coupling and time delay

The firing of a neuron model is mainly affected by the following factors:the magnetic field, external forcing current, time delay, etc. In this paper, a new time-delayed electromagnetic field coupled dual Hindmarsh-Rose neuron network model is constructed. A magnetically controlled threshold memristor is improved to represent the self-connected and the coupled magnetic fields triggered by the dynamic change of neuronal membrane potential for the adjacent neurons. Numerical simulation confirms that the coupled magnetic field can activate resting neurons to generate rich firing patterns, such as spiking firings, bursting firings, and chaotic firings, and enable neurons to generate larger firing amplitudes. The study also found that the strength of magnetic coupling in the neural network also affects the number of peaks in the discharge of bursting firing. Based on the existing medical treatment background of mental illness, the effects of time lag in the coupling process against neuron firing are studied. The results confirm that the neurons can respond well to external stimuli and coupled magnetic field with appropriate time delay, and keep periodic firing under a wide range of external forcing current.     

Synaptic Plasticity and Spike Synchronisation in Neuronal Networks

Brain plasticity, also known as neuroplasticity, is a fundamental mechanism of neuronal adaptation in response to changes in the environment or due to brain injury. In this review, we show our results about the effects of synaptic plasticity on neuronal networks composed by Hodgkin-Huxley neurons. We show that the final topology of the evolved network depends crucially on the ratio between the strengths of the inhibitory and excitatory synapses. Excitation of the same order of inhibition revels an evolved network that presents the rich-club phenomenon, well known to exist in the brain. For initial networks with considerably larger inhibitory strengths, we observe the emergence of a complex evolved topology, where neurons sparsely connected to other neurons, also a typical topology of the brain. The presence of noise enhances the strength of both types of synapses, but if the initial network has synapses of both natures with similar strengths. Finally, we show how the synchronous behaviour of the evolved network will reflect its evolved topology.