耦合Pre-B?tzinger复合体中神经元的反相簇放电模式及同步研究

本文以pre-B?tzinger复合体中两个耦合兴奋性神经元为研究对象,分别研究了耦合神经元反相簇放电类型及其同步转迁.当钠电导参数在一定范围内变化时,耦合神经元分别表现为"sup-Hopf/fold cycle"型和"fold/fold cycle"型反相簇放电.通过计算耦合神经元的簇放电内的峰相位差,进而判定反相簇放电中的峰同步行为,并且研究了反相放电的类型与同步的关系.     

Pre-Botzinger复合体中耦合神经元簇同步模式及转迁的分岔分析

Pre-Botzinger复合体中兴奋性神经元节律性簇放电与呼吸节律的产生关系密切.泄漏电流对神经元簇放电具有重要的调节作用.本文利用双参数分岔分析和快慢变量分离等方法,研究了泄漏电流对耦合神经元簇同步模式及其转迁机制的影响.结果表明,在不同初始条件下,当泄漏电导改变时耦合神经元分别表现为同相“fold/homoclinic”型、“subHopf/homoclinic”型和反相“fold/fold cycle”型和“subHopf/fold cycle”型簇放电.本文的研究为进一步探索呼吸节律的产生机制提供了一些见解.     

Pre-Btzinger复合体中耦合神经元簇同步模式及转迁的分岔分析

Pre-Btzinger复合体中兴奋性神经元节律性簇放电与呼吸节律的产生关系密切.泄漏电流对神经元簇放电具有重要的调节作用.本文利用双参数分岔分析和快慢变量分离等方法,研究了泄漏电流对耦合神经元簇同步模式及其转迁机制的影响.结果表明,在不同初始条件下,当泄漏电导改变时耦合神经元分别表现为同相"fold/homoclinic"型、"sub Hopf/homoclinic"型和反相"fold/fold cycle"型和"sub Hopf/fold cycle"型簇放电.本文的研究为进一步探索呼吸节律的产生机制提供了一些见解.     

两房室神经元模型的同步簇放电的动力学分析

研究一个具有电流反馈的两房室锥体神经元的簇放电动力学问题.首先,利用数值模拟研究了该神经元的树突和胞体两个房室之间的峰相位同步行为.其次,基于快慢动力学分析方法,给出了快子系统的双参数分岔曲线图,结果表明快子系统产生了3个余维-2分岔点,它们分别为fold-Hopf分岔点ZH、Cusp分岔点CP和Bogdanov-Takens分岔点BT.最后,根据这些余维-2分岔点确定系统存在着丰富的簇放电模式,如"fold/fold"型,"Hopf/Hopf"型,"Hopf/homoclinic"型以"fold/homoclinic"型簇振荡等,并分析研究了簇放电模式的产生以及它们之间相互转迁的动力学机理.本文的研究结果进一步表明了神经元的几何形态特性对于神经元放电模式多样性的重要影响.     

耦合pre-B tzinger复合体神经元中混合簇放电的多时间尺度动力学分析

Pre-B tzinger复合体是新生哺乳动物呼吸节律起源的关键部位,是呼吸节律产生的中枢.本文以pre-B tzinger复合体中两个耦合的神经元为研究对象,并考虑钙离子动力学的耦合神经元模型.利用多时间尺度动力学、快慢尺度分解和分岔分析,研究混合簇同步放电模式及其产生机制,并研究了耦合神经元同相和反相簇放电类型及其同步转迁.结果表明钙离子的周期性波动对混合簇放电模式的产生有极大的影响,钙离子波动导致的时间尺度变化及分岔曲线相对位置的改变是混合簇放电产生的主要原因.本文的研究对认识pre-B tzinger中大规模网络的动力学有着重要的意义,为进一步探索呼吸节律的产生机制提供了一些有益的思考和见解.     

不同耦合类型的三维Hybrid神经元同步动力学

神经元网络的信息传递与多个神经元间的耦合同步密切相关.大量研究表明,神经元耦合系统的同步化问题是研究大脑处理信息的关键.本文基于三维混合神经元模型研究了神经元的复杂放电,该模型由Wilson模型的快子系统和H-R模型的慢子系统组成.该模型能够重现大脑皮层神经元一系列包括规则峰放电、快速峰放电和簇放电等神经动力学行为.本文基于三维混合神经元模型,探讨了三维混合神经元在电突触耦合、化学突触耦合和磁通耦合条件下的同步放电行为,模拟膜电位序列图、相位差图等探讨恒同及非恒同下耦合强度对神经元同步放电的影响.本研究将为人们进一步了解神经系统疾病的发病机制提供指导和帮助,并为神经科学领域提供可能的研究思路.     

对称电耦合连接方式下的多尺度同步行为和转迁过程

本文研究了改进的ML神经元模型在环式和链式两种对称连接结构下的多尺度同步转迁过程.通过定义峰相位、簇相位、网络的平均峰频率差和平均簇频率差,发现随着耦合强度的增加,耦合神经元从互不相关到簇同步再到峰同步过渡,最后达到几乎完全同步.簇同步和峰同步属于相位同步的两种节律类型,对应慢时间尺度的簇同步通常先于对应快时间尺度的峰...     

具有时滞的耦合Hindmarsh-Rose神经元系统的放电模式

基于在无时滞的情况下,非全同的HindmarshRose耦合神经元达到几乎完全同步的放电模式,通过数值模拟的方法,研究了时滞对耦合HindmarshRose神经元同步后放电模式的影响.结果表明时滞使得神经元的放电模式发生改变,同时时滞的增加能够诱导簇中的峰逐渐地减小或消失.这一研究将有助于我们更深入地了解时滞对耦合神经元系统行为的影响.     

ML神经元的放电模式及时滞对神经元同步的影响

研究了单个ML神经元的放电模式及其动力学特征．通过快慢动力学分析得出随着参数的变化,神经元可以呈现出静息态、簇放电及峰放电等多种放电模式．本文同时研究了耦合强度和时滞对突触耦合的两个神经元同步的影响．在无时滞时,随着耦合强度的增大,耦合神经元的在相同步得到增强．而在某段时滞范围内,神经元在比较小的耦合强度下就能达到同步,这说明有效的时滞能够增强同步．此外,时滞只能在某些耦合强度下才对耦合系统的同步起作用．     

模块神经元网络中耦合时滞诱导的簇同步转迁

利用Courbage-Nekorkin-Vdovin神经元构建含有耦合时滞的模块神经元网络模型,通过数值模拟研究了耦合强度及耦合时滞对模块神经元网络簇同步放电特性的影响.研究结果表明,适当大的耦合强度可以诱导模块神经元网络达到簇同步.同时,研究发现耦合时滞可以诱导模块神经元网络出现簇同步转迁,且当时滞大小约为网络中所有神经元平均振荡周期的整数倍数时,模块神经元网络的簇同步现象能够间歇性出现.此外,研究结果表明时滞诱导的簇同步转迁对子网络内的耦合强度、子网络间的连接概率具有鲁棒性.     

Influences of synaptic location on the synchronization of rhythmic bursting neurons

We study how the location of synaptic input influences the stablex firing states in coupled model neurons bursting rhythmically at the gamma frequencies (20-70 Hz). The model neuron consists of two compartments and generates one, two, three or four spikes in each burst depending on the intensity of input current and the maximum conductance of M-type potassium current. If the somata are connected by reciprocal excitatory synapses, we find strong correlations between the changes in the bursting mode and those in the stable phase-locked states of the coupled neurons. The stability of the in-phase phase-locked state (synchronously firing state) tends to change when the individual neurons change their bursting patterns. If, however, the synaptic connections are terminated on the dendritic compartments, no such correlated changes occur. In this case, the coupled bursting neurons do not show the in-phase phase-locked state in any bursting mode. These results indicate that synchronization behaviour of bursting neurons significantly depends on the synaptic location, unlike a coupled system of regular spiking neurons.     

Dynamical analysis of bursting oscillations in the Chay-Keizer model with three time scales

Based on the Chay-Keizer model with three time scales, we investigate the role of the slowest variable in generating bursting oscillations in pancreaticcells. It is shown that both of the two slow processes can interact to drive fast, medium and slow bursting oscillations typically observed in pancreaticcells. Moreover, diverse patterns of electrical bursting are presented, including the fold/fold bursting, fold/homoclinic bursting, fold/Hopf bursting via fold/fold hysteresis loop, and the fold/fold burstin...     

Frequency response of in-plane coupled resonators for investigating the acceleration sensitivity of MEMS tuning fork gyroscopes

The frequency response of in-plane coupled resonators is used for investigating the acceleration sensitivity of a MEMS tuning fork gyroscope (TFG) and a new method of suppressing the acceleration output is presented. The unbalancing of two sense resonators in the TFG caused by fabrication errors converted an external vibration into anti-phase mode excitation. To reduce the acceleration output, decoupling between in- and anti-phase modal frequencies [decoupling ratio (DR)] is crucial, since coupled resonators may cause large anti-phase vibrations from the acceleration. The acceleration output model was verified using two coupled resonators with 1 and 5?% stiffness unbalance. FEM simulation results showed a 25?% reduction in the anti-phase vibration by increasing the decoupling ratio from 0.09 to 0.29, irrespective of the coupled resonators designs. Quantitative analysis of a TFG based on coupled resonators with 1?% stiffness unbalance showed the acceleration output decreased from 5.65 to 1.43?deg/s/g.     

非线性时滞反馈实现离散神经元网络的去同步化

采用非线性时滞反馈实现离散神经元网络的去同步化控制．对于由映射神经元模型构建的神经网络，调节神经元之间的连接强度可以实现网络的混沌簇放电同步．在神经元的快变量中施加非线性时滞反馈信号可以实现网络的完全去同步化，且不改变神经元本身的放电特性．与线性时滞反馈相比，非线性时滞反馈能够实现强连接神经网络的去同步化，且对于参数的变化具有鲁棒性．     

Synchronization of multiple chaotic FitzHugh-Nagumo neurons with gap junctions under external electrical stimulation

This paper discusses the synchronization of three coupled chaotic FitzHugh-Nagumo (FHN) neurons with different gap junctions under external electrical stimulation. A nonlinear control law that guarantees the asymptotic synchronization of coupled neurons (with reduced computations) is proposed. The developed control law incorporates the synchronization error between two slave neurons in addition to the conventionally considered synchronization errors between the master and the slave neurons, which make the proposed scheme computationally more efficient. Further, a novel L₂ gain reduction criterion has been developed for multi-input multi-output systems with non-zero initial conditions, and is applied to robust synchronization of FHN neurons under L₂ norm bounded disturbance and uncertainties. Furthermore, a robust adaptive nonlinear control law is developed, which is capable of handling variations in nonlinear part of synchronization error dynamics, without using any neural-network-based training-oriented adaptive scheme. The proposed control schemes ensure global synchronization with computational simplicity, easy way of design and implementation and avoiding extra measurements. The results obtained with the proposed control laws are verified through numerical simulations.