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1.
交流外电场下映射神经元放电节律的分析 总被引:1,自引:0,他引:1
神经元不同的放电节律承载着不同的刺激信息。文章基于神经元映射模型,研究低频交流电场对神经元放电节律的影响。在外部刺激下映射模型表现出丰富的放电模式,包括周期簇放电、周期峰放电、交替放电和混沌放电。神经元对刺激频率和振幅的变化极为敏感,随着频率的增大,放电节律表现出从簇放电到峰放电和混沌放电的反向加周期分岔序列;在周期节律转迁过程中存在一种新的交替节律,其放电序列为两种周期放电模式的交替,峰峰间期序列具有整数倍特征。外电场的频率影响细胞内、外离子振荡周期,导致神经元放电与刺激信号同步,对放电节律的影响更为明显。研究结果揭示了交流外电场对神经元放电节律的作用规律,有助于探寻外电场对生物神经系统兴奋性的影响和神经系统疾病的致病机理。 相似文献
2.
神经放电节律转化的分岔序列模式 总被引:3,自引:0,他引:3
神经元接受到的外界信号是动态变化的,神经放电节律模式则会依据一定的规律动态转化来反映这种变化,以往确定性理论模型(如Chay模型和Rose-Hindmarsh模型)模拟出了部分神经放电模式转化的整体分岔规律。利用Chay模型仿真,通过调节具有生理学意义的参数,模拟出了神经元放电的一系列分岔序列,同时在神经起步点的实验中,应用与模型对应的参数进行调节,观察到了与仿真结果整体上一致的分岔序列,印证了数值模拟的结果,展现了真实的神经元放电整体分岔结构的基本规律,为理解具体的生理调节活动中神经放电节律的转化提供了理论基础。 相似文献
3.
神经放电加周期分岔中由随机自共振引起一类新节律 总被引:1,自引:1,他引:0
当改变实验性神经起步点细胞外[Ca^2 ]时,放电节律表现出从周期1节律转换为周期4节律的加周期分岔序列。其中,周期n节律转换为周期n 1节律的过程中(n=1,2,3)存在一种新的具有交替特征的节律,该新节律为周期n簇与周期n 1簇放电的交替,并且周期n 1簇的时间间隔序列呈现出整数倍特征。确定性神经放电理论模型(chay模型)只能模拟周期n节律直接到周期n 1节律的加周期分岔序列;而随机chay模型可以模拟实验中的加周期分岔过程和新节律。进一步,新节律被确认是经随机自共振机制产生的。这不仅解释了实验现象,也将随机自共振的产生区间从以前认识到的Hopf分岔点附近扩大到加周期分岔点附近,同时扩大了噪声在神经放电和神经编码中起重要作用的参数区间。 相似文献
4.
引起神经元“非周期敏感现象”的分岔机制 总被引:1,自引:1,他引:0
实验发现神经元平均发放率变化率在放电脉冲序列串(ISI序列)呈非周期节律时普遍大于ISI呈周期节律时的平均发放率变化率,称为“非周期敏感现象”。以HR神经元模型和胰腺β-细胞模型为例,在合适的参数改变量作用下观察到了“非周期敏感现象”,并进一步讨论了平均发放率变化率与ISI序列动力学性质的关系。发现当ISI序列经历混沌-周期分岔时“非周期敏感现象”表现明显,尤其在ISI序列经历从混沌到嵌入在混沌中的周期窗口的分岔时表现最为显著。进一步的分析表明周期窗口在整个混沌带中所占测度较大,故混沌.周期分岔及从混沌到嵌入在混沌中的周期窗口分岔是引起神经元“非周期敏感现象”的一种重要动力学机制。实验结果支持上述结论。 相似文献
5.
神经起步点自发放电节律及节律转化的分岔规律 总被引:2,自引:1,他引:1
在神经起步点的实验中观察到了复杂多样的神经放电([Ca^2 ]o)节律模式,如周期簇放电、周期峰放电、混沌簇放电、混沌峰放电以及随机放电节律等。随着细胞外钙离子浓度的降低,神经放电节律从周期l簇放电,经过复杂的分岔过程(包括经倍周期分岔到混沌簇放电、混沌簇放电经激变到混沌峰放电、以及混沌峰放电经逆倍周期分岔到周期峰放电)转化为周期l峰放电。在神经放电理论模型——Chay模型中,调节与实验相关的参数(Ca^2 平衡电位),可以获得与实验相似的神经放电节律和节律转换规律。这表明复杂的神经放电节律之间存在着一定的分岔规律,它们是理解神经元信息编码的基础。 相似文献
6.
为进一步研究损伤神经放电节律的分岔转迁规律,以实验性神经起步点模型为研究对象,在联合改变胞外的钙离子和钾离子浓度的条件下,记录神经单纤维的放电节律转迁方式。选取4-氨基吡啶(4-aminopyridine,4-AP)作为条件参数,Ca2+浓度作为分岔参数,观察了实验性神经起步点自发放电节律的分岔规律。28例实验结果中,有21例神经对本文所取的条件参数变化不敏感,7例实验性神经起步点的自发放电节律会在不同的条件参数下出现不同类型的分岔序列结构。在不同的4-AP浓度下,随着Ca2+浓度的降低,同一实验性神经起步点会表现出不同的放电节律模式的分岔序列,不同实验性神经起步点,双参数分岔序列是不同的。以上结果说明,不同参数配置下的神经放电节律的变化规律是不同的,而且分岔序列结构是认识放电节律转迁规律的基础。 相似文献
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8.
含快慢子系统的神经元数学模型仿真预期,神经放电节律经历加周期分岔序列,可以进一步表现激变,并通过逆倍周期分岔级联进入周期1峰放电。实验调节胞外钙离子浓度,观察到从周期1簇放电开始的带有随机节律的加周期分岔到簇内有多个峰的簇放电,再经激变转迁到峰放电节律的分岔序列,提供了这种分岔序列模式实验证据。实验所见之激变表现为簇放电节律的休止期消失,放电节律变为混沌峰放电和周期峰放电。作者利用随机Chay模型更加逼真地仿真再现了实验所见的分岔序列。该实验结果验证了以前的确定性数学模型的理论预期,并利用随机理论模型仿真了其在现实神经系统的表现;揭示了一类完整的神经放电节律的转换规律。 相似文献
9.
混沌放电的可兴奋性细胞对外界刺激反应敏感的动力学机制 总被引:1,自引:0,他引:1
在大鼠损伤背根节神经元受到去甲肾上腺(NE)、四乙基胺(TEA)和高浓度钙等剌激的实验中,观察到非周期放电的神经元明显地比周期放电的神经元对外界刺激的反应敏感程度高。现有的结果表明许多非周期放电的神经元实际上表现为确定性的混沌运动,比如混沌尖峰放电、混沌簇放电以及整数倍放电等。以修正的胰腺B细胞Chay模型为例,通过对其分岔结构的分析和对构成混沌吸引子的基本骨架的不稳定周期轨道的计算,揭示了分岔、激变和混沌运动对参数敏感依赖性是该现象产生的动力学机制。同时指出以往使用平均发放率来刻划可兴奋性细胞放电活动存在的缺陷,提出了一种新的利用周期轨道信息的刻划方法。 相似文献
10.
在实验性神经起步点自发放电中,发现了两种三态跃迁节律,其特征为静息、周期n及周期n+1(n=1,2)簇放电随机交替出现。应用随机Chay模型数值仿真,分别得到了与实验模型中相似的两种三态跃迁节律,这两种节律都是在两个紧邻的分岔点附近,由噪声驱动而产生的。理论分析提示,当神经元系统接近从静息经分岔到放电的临界状态,且从静息到周期n的分岔点,与从周期n到周期n+1的分岔点非常接近时,在噪声的作用下,系统运动会在静息、周期n和周期n+1三种状态之间随机跃迁,从而形成了这种三态跃迁节律。基于这种三态跃迁放电的随机共振,还有待进一步深入研究。 相似文献
11.
Guo-Sheng Yi Jiang Wang Xi-Le Wei Kai-Ming Tsang Wai-Lok Chan Bin Deng Chun-Xiao Han 《Journal of computational neuroscience》2014,36(3):383-399
To investigate how extracellular electric field modulates neuron activity, a reduced two-compartment neuron model in the presence of electric field is introduced in this study. Depending on neuronal geometric and internal coupling parameters, the behaviors of the model have been studied extensively. The neuron model can exist in quiescent state or repetitive spiking state in response to electric field stimulus. Negative electric field mainly acts as inhibitory stimulus to the neuron, positive weak electric field could modulate spiking frequency and spike timing when the neuron is already active, and positive electric fields with sufficient intensity could directly trigger neuronal spiking in the absence of other stimulations. By bifurcation analysis, it is observed that there is saddle-node on invariant circle bifurcation, supercritical Hopf bifurcation and subcritical Hopf bifurcation appearing in the obtained two parameter bifurcation diagrams. The bifurcation structures and electric field thresholds for triggering neuron firing are determined by neuronal geometric and coupling parameters. The model predicts that the neurons with a nonsymmetric morphology between soma and dendrite, are more sensitive to electric field stimulus than those with the spherical structure. These findings suggest that neuronal geometric features play a crucial role in electric field effects on the polarization of neuronal compartments. Moreover, by determining the electric field threshold of our biophysical model, we could accurately distinguish between suprathreshold and subthreshold electric fields. Our study highlights the effects of extracellular electric field on neuronal activity from the biophysical modeling point of view. These insights into the dynamical mechanism of electric field may contribute to the investigation and development of electromagnetic therapies, and the model in our study could be further extended to a neuronal network in which the effects of electric fields on network activity may be investigated. 相似文献
12.
On-off firing patterns, in which repetition of clusters of spikes are interspersed with epochs of subthreshold oscillations or quiescent states, have been observed in various nervous systems, but the dynamics of this event remain unclear. Here, we report that on-off firing patterns observed in three experimental models (rat sciatic nerve subject to chronic constrictive injury, rat CA1 pyramidal neuron, and rabbit blood pressure baroreceptor) appeared as an alternation between quiescent state and burst containing multiple period-1 spikes over time. Burst and quiescent state had various durations. The interspike interval (ISI) series of on-off firing pattern was suggested as stochastic using nonlinear prediction and autocorrelation function. The resting state was changed to a period-1 firing pattern via on-off firing pattern as the potassium concentration, static pressure, or depolarization current was changed. During the changing process, the burst duration of on-off firing pattern increased and the duration of the quiescent state decreased. Bistability of a limit cycle corresponding to period-1 firing and a focus corresponding to resting state was simulated near a sub-critical Hopf bifurcation point in the deterministic Morris—Lecar (ML) model. In the stochastic ML model, noise-induced transitions between the coexisting regimes formed an on-off firing pattern, which closely matched that observed in the experiment. In addition, noise-induced exponential change in the escape rate from the focus, and noise-induced coherence resonance were identified. The distinctions between the on-off firing pattern and stochastic firing patterns generated near three other types of bifurcations of equilibrium points, as well as other viewpoints on the dynamics of on-off firing pattern, are discussed. The results not only identify the on-off firing pattern as noise-induced stochastic firing pattern near a sub-critical Hopf bifurcation point, but also offer practical indicators to discriminate bifurcation types and neural excitability types. 相似文献
13.
Neurons in the primary visual cortex typically reach their highest firing rate after an abrupt image transition. Since the mutual information between the firing rate and the currently presented image is largest during this early firing period it is tempting to conclude this early firing encodes the current image. This view is, however, made more complicated by the fact that the response to the current image is dependent on the preceding image. Therefore we hypothesize that neurons encode a combination of current and previous images, and that the strength of the current image relative to the previous image changes over time. The temporal encoding is interesting, first, because neurons are, at different time points, sensitive to different features such as luminance, edges and textures; second, because the temporal evolution provides temporal constraints for deciphering the instantaneous population activity. To study the temporal evolution of the encoding we presented a sequence of 250 ms stimulus patterns during multiunit recordings in areas 17 and 18 of the anaesthetized ferret. Using a novel method we decoded the pattern given the instantaneous population-firing rate. Following a stimulus transition from stimulus A to B the decoded stimulus during the first 90ms was more correlated with the difference between A and B (B-A) than with B alone. After 90ms the decoded stimulus was more correlated with stimulus B than with B-A. Finally we related our results to information measures of previous (B) and current stimulus (A). Despite that the initial transient conveys the majority of the stimulus-related information; we show that it actually encodes a difference image which can be independent of the stimulus. Only later on, spikes gradually encode the stimulus more exclusively. 相似文献
14.
LOEWENSTEIN WR 《The Journal of general physiology》1958,41(4):825-845
Response patterns resulting from repetitive mechanical stimulation of the corpuscle depend on (1) the time course of recovery of the generator potential, on (2) the recovery of critical firing height, and on (3) the stimulus strength/generator potential function. By either augmenting stimulus frequency at constant strength, or by reducing strength at constant frequency, a sequence of propagated potentials is turned into a pattern of alternating regenerative and generator responses. In such a pattern an extra impulse can be set up whenever an extra stimulus produces a generator potential of enough amplitude to reach the firing height of the corresponding period. The new requirements of firing height introduced by the refractory trail of the extra impulse determine resetting of periodicity and appearance of a "compensatory pause." The decay time of the single generator potential is independent of stimulus duration. This is interpreted as a factor determining receptor adaptation. Upon repetitive stimulation at intervals above ½ decay time of the single generator potential, a compound generator potential is built up which shows no spontaneous decline. However, in spite of being considerably greater than the firing height for single impulses, the constant level of depolarization of the compound generator potential is unable to produce propagated potentials. A hypothesis is brought forward which considers the generator potential to arise from membrane units with fluctuating excitability scattered over the non-myelinated nerve ending. 相似文献
15.
Pyramidal cells in the electrosensory lateral line lobe (ELL) of weakly electric fish have been observed to produce high-frequency burst discharge with constant depolarizing current (Turner et al., 1994). We present a two-compartment model of an ELL pyramidal cell that produces burst discharges similar to those seen in experiments. The burst mechanism involves a slowly changing interaction between the somatic and dendritic action potentials. Burst termination occurs when the trajectory of the system is reinjected in phase space near the ghost of a saddle-node bifurcation of fixed points. The burst trajectory reinjection is studied using quasi-static bifurcation theory, that shows a period doubling transition in the fast subsystem as the cause of burst termination. As the applied depolarization is increased, the model exhibits first resting, then tonic firing, and finally chaotic bursting behavior, in contrast with many other burst models. The transition between tonic firing and burst firing is due to a saddle-node bifurcation of limit cycles. Analysis of this bifurcation shows that the route to chaos in these neurons is type I intermittency, and we present experimental analysis of ELL pyramidal cell burst trains that support this model prediction. By varying parameters in a way that changes the positions of both saddle-node bifurcations in parameter space, we produce a wide gallery of burst patterns, which span a significant range of burst time scales. 相似文献
16.
P. A. Robinson 《Journal of mathematical biology》2013,66(7):1475-1497
Previous neural field models have mostly been concerned with prediction of mean neural activity and with second order quantities such as its variance, but without feedback of second order quantities on the dynamics. Here the effects of feedback of the variance on the steady states and adiabatic dynamics of neural systems are calculated using linear neural field theory to estimate the neural voltage variance, then including this quantity in the total variance parameter of the nonlinear firing rate-voltage response function, and thus into determination of the fixed points and the variance itself. The general results further clarify the limits of validity of approaches with and without inclusion of variance dynamics. Specific applications show that stability against a saddle-node bifurcation is reduced in a purely cortical system, but can be either increased or decreased in the corticothalamic case, depending on the initial state. Estimates of critical variance scalings near saddle-node bifurcation are also found, including physiologically based normalizations and new scalings for mean firing rate and the position of the bifurcation. 相似文献