电突触耦合神经元的相位同步及放电节律的转化

研究了两个参数失配较大情况下,处于不同放电模式的两个电突触耦合Hindmarsh-rose(HR)神经元的相位同步问题,发现在适当耦合强度下可以实现相同步并呈现出复杂的放电节律.利用峰峰间期(Interspikeinterval,ISI)和平均放电频率证实了相同步的发生,给出并分析了不同放电状态的神经元在电突触耦合下实现相同步后的神经放电节律.从相同步的角度显示,神经元同步后呈现簇放电特征或峰放电特征,除与两耦合神经元独自放电模式有关外,还与电突触耦合强度有一定的内在关系.     

时滞援助的两抑制性突触耦合的Chay 神经元的同步

一对抑制性突触耦合的混沌Chay神经元的同步模式被研究。结果表明当耦合强度超过临界值时,两抑制耦合的混沌Chay神经元能达到反相的同步。与此同时,两混沌的神经元变为周期而不是原来的混沌运动。然而,如果考虑耦合神经元信息的传导时滞,在有效的时滞下,两个耦合神经元的在相簇同步能增加。在相簇同步窗口的大小随着耦合强度的增加而增加。此结果对于我们理解神经元集群的运动是一个指导。     

Synchronization and sensitivity enhancement of the Hodgkin-Huxley neurons due to inhibitory inputs

Recent experimental results imply that inhibitory postsynaptic potentials can play a functional role in realizing synchronization of neuronal firing in the brain. In order to examine the relation between inhibition and synchronous firing of neurons theoretically, we analyze possible effects of synchronization and sensitivity enhancement caused by inhibitory inputs to neurons with a biologically realistic model of the Hodgkin-Huxley equations. The result shows that, after an inhibitory spike, the firing probability of a single postsynaptic neuron exposed to random excitatory background activity oscillates with time. The oscillation of the firing probability can be related to synchronous firing of neurons receiving an inhibitory spike simultaneously. Further, we show that when an inhibitory spike input precedes an excitatory spike input, the presence of such preceding inhibition raises the firing probability peak of the neuron after the excitatory input. The result indicates that an inhibitory spike input can enhance the sensitivity of the postsynaptic neuron to the following excitatory spike input. Two neural network models based on these effects on postsynaptic neurons caused by inhibitory inputs are proposed to demonstrate possible mechanisms of detecting particular spatiotemporal spike patterns. Received: 15 April 1999 /Accepted in revised form: 25 November 1999     

Impact of adaptation currents on synchronization of coupled exponential integrate-and-fire neurons

The ability of spiking neurons to synchronize their activity in a network depends on the response behavior of these neurons as quantified by the phase response curve (PRC) and on coupling properties. The PRC characterizes the effects of transient inputs on spike timing and can be measured experimentally. Here we use the adaptive exponential integrate-and-fire (aEIF) neuron model to determine how subthreshold and spike-triggered slow adaptation currents shape the PRC. Based on that, we predict how synchrony and phase locked states of coupled neurons change in presence of synaptic delays and unequal coupling strengths. We find that increased subthreshold adaptation currents cause a transition of the PRC from only phase advances to phase advances and delays in response to excitatory perturbations. Increased spike-triggered adaptation currents on the other hand predominantly skew the PRC to the right. Both adaptation induced changes of the PRC are modulated by spike frequency, being more prominent at lower frequencies. Applying phase reduction theory, we show that subthreshold adaptation stabilizes synchrony for pairs of coupled excitatory neurons, while spike-triggered adaptation causes locking with a small phase difference, as long as synaptic heterogeneities are negligible. For inhibitory pairs synchrony is stable and robust against conduction delays, and adaptation can mediate bistability of in-phase and anti-phase locking. We further demonstrate that stable synchrony and bistable in/anti-phase locking of pairs carry over to synchronization and clustering of larger networks. The effects of adaptation in aEIF neurons on PRCs and network dynamics qualitatively reflect those of biophysical adaptation currents in detailed Hodgkin-Huxley-based neurons, which underscores the utility of the aEIF model for investigating the dynamical behavior of networks. Our results suggest neuronal spike frequency adaptation as a mechanism synchronizing low frequency oscillations in local excitatory networks, but indicate that inhibition rather than excitation generates coherent rhythms at higher frequencies.     

Equilibrium analysis and phase synchronization of two coupled HR neurons with gap junction

The properties of equilibria and phase synchronization involving burst synchronization and spike synchronization of two electrically coupled HR neurons are studied in this paper. The findings reveal that in the non-delayed system the existence of equilibria can be turned into intersection of two odd functions, and two types of equilibria with symmetry and non-symmetry can be found. With the stability and bifurcation analysis, the bifurcations of equilibria are investigated. For the delayed system, the equilibria remain unchanged. However, the Hopf bifurcation point is drastically affected by time delay. For the phase synchronization, we focus on the synchronization transition from burst synchronization to spike synchronization in the non-delayed system and the effect of coupling strength and time delay on spike synchronization in delayed system. In addition, corresponding firing rhythms and spike synchronized regions are obtained in the two parameters plane. The results allow us to better understand the properties of equilibria, multi-time-scale properties of synchronization and temporal encoding scheme in neuronal systems.     

Circadian rhythm formation in plant seedling: global synchronization and bifurcation as a coupled nonlinear oscillator system

Circadian rhythm formation is studied in seedlings after germination measuring their respiratory metabolism. The circadian rhythm is clearly observed at about 170h (the onset time t(CR-ON)) after germination of seeds in natural conditions in a dark incubator. There are no clear cyclic signals in gas exchange before t(CR-ON). Application of external triggers (temperature shocks) near the onset of the rhythm in seedling growth strongly affects formation processes. The onset is shifted earlier up to 50h by application of perturbations. This fact may suggest that the circadian rhythms appear via subcritical bifurcation.     

On the role of astrocytes in synchronization of two coupled neurons: a mathematical perspective

Based on recent findings, astrocytes, a subtype of glial cells, dynamically regulate the synaptic transmission of neuronal networks. In this research, a biologically inspired neuronal network model is constructed by connecting two Morris-Lecar neuron models. In this minimal network model, neuron–astrocyte interactions are considered in a functional-based procedure. Utilizing the developed model and according to the theoretical analysis carried out in the article, it is confirmed that, the astrocyte increases the threshold value of synchronization and provides appropriate feedback control in regulating the neural activities. Therefore, the healthy astrocyte has the potential to desynchronize the synchrony between two coupled neurons. Next, we investigate malfunction of the astrocyte in the regulatory feedback loop. Mathematically, we verify that pathologic astrocyte is no longer able to increase the synchronization threshold and therefore, it cannot compensate excessive increase in the excitation level. The main reason behind this is the fact that healthy astrocyte can optimally increase the input current of the individual neurons, while the so-called pathological astrocyte is unable to modify correctly the amount of this current. Consequently, disruptions of the signaling function of astrocyte initiate the hypersynchronous firing of neurons. In other words, reduction in neuron–astrocyte cross-talk will lead to synchronized firing of neurons. Therefore, our results propose that the astrocyte could have a key role in stabilizing neural activity.     

Loss of synchronization in partially coupled Hodgkin-Huxley equations

We study the loss of synchronization of two partially coupled space-clamped Hodgkin-Huxley equations, with symmetric coupling. This models the coupling of two cells through an electrical synapse. For strong enough coupling it is known that all solutions of the equations approach a state where the two cells are perfectly synchronized, having the same behaviour at each moment. We describe the local bifurcations that arise when the coupling strength is reduced, using a mixture of analytical and numerical methods. We find that perfect synchrony is retained for very small positive values of the coupling strength, for almost all initial conditions. Although perfect synchrony is lost for negative values of the coupling constant, the system always retains some degree of synchronization until it becomes totally unstable. This happens in two ways: in many cases for almost all initial conditions the solutions still approach a perfectly synchronized state. Even when this is not true, the attracting solutions are still synchronized, with a half-period phase shift.     

Noise controlled synchronization in potassium coupled neural models

The paper applies biologically plausible models to investigate how noise input to small ensembles of neurons, coupled via the extracellular potassium concentration, can influence their firing patterns. Using the noise intensity and the volume of the extracellular space as control parameters, we show that potassium induced depolarization underlies the formation of noise-induced patterns such as delayed firing and synchronization. These phenomena are associated with the appearance of new time scales in the distribution of interspike intervals that may be significant for the spatio-temporal oscillations in neuronal ensembles.     

Oxalate nephropathy due to gastrointestinal disorders.

Renal failure secondary to oxalate interstitial nephritis developed in three patients with malabsorption and steatorrhea following a jejunoileal bypass, extensive small intestine resection and a partial gastrectomy. Hyperoxaluria was documented in two of the cases. The possibility that this complication can occur in patients after a jejunoileal bypass operation is now recognized. This report shows that it can also occur in patients with other bowel disorders that cause malabsorption and steatorrhea. Since the prognosis for patients with oxalate nephropathy is poor, renal function should be closely monitored in patients who are at risk because of these disorders. Therapy should be directed at correcting malabsorption, steatorrhea and hyperoxaluria. When the renal function of patients with a jejunoileal bypass continues to decline despite intensive medical therapy, restoration of bowel continuity is strongly recommended.     

Famous faces demand attention due to reduced inhibitory processing

People have particular difficulty ignoring distractors that depict faces. This phenomenon has been attributed to the high level of biological significance that faces carry. The current study aimed to elucidate the mechanism by which faces gain processing priority. We used a focused attention paradigm that tracks the influence of a distractor over time and provides a measure of inhibitory processing. Upright famous faces served as test stimuli and inverted versions of the faces as well as upright non-face objects served as control stimuli. The results revealed that although all of the stimuli elicited similar levels of distraction, only inverted distractor faces and non-face objects elicited inhibitory effects. The lack of inhibitory effects for upright famous faces provides novel evidence that reduced inhibitory processing underlies the mandatory nature of face processing.     

Mechanisms of phase synchronization in neural even cyclic inhibitory networks

The mechanisms of synchronization have been studied in a mathematical model of the neurodynamics of navigation behavior that is based on even cyclic inhibitory networks. The following factors that affect the synchronized activity of the information units of the network have been highlighted: the weights of interunit connections, the duration of network activity, and the amplitude, duration, and timing of input signals.     

Leptin action on GABAergic neurons prevents obesity and reduces inhibitory tone to POMC neurons

Leptin acts in the brain to prevent obesity. The underlying neurocircuitry responsible for this is poorly understood, in part because of incomplete knowledge regarding first-order, leptin-responsive neurons. To address this, we and others have been removing leptin receptors from candidate first-order neurons. While functionally relevant neurons have been identified, the observed effects have been small, suggesting that most first-order neurons remain unidentified. Here we take an alternative approach and test whether first-order neurons are inhibitory (GABAergic, VGAT?) or excitatory (glutamatergic, VGLUT2?). Remarkably, the vast majority of leptin's antiobesity effects are mediated by GABAergic neurons; glutamatergic neurons play only a minor role. Leptin, working directly on presynaptic GABAergic neurons, many of which appear not to express AgRP, reduces inhibitory tone to postsynaptic POMC neurons. As POMC neurons prevent obesity, their disinhibition by leptin action on presynaptic GABAergic neurons probably mediates, at least in part, leptin's antiobesity effects.     

Partial phase synchronization of neural populations due to random Poisson inputs

We show that populations of identical uncoupled neurons exhibit partial phase synchronization when stimulated with independent, random unidirectional current spikes with interspike time intervals drawn from a Poisson distribution. We characterize this partial synchronization using the phase distribution of the population, and consider analytical approximations and numerical simulations of phase-reduced models and the corresponding conductance-based models of typical Type I (Hindmarsh-Rose) and Type II (Hodgkin-Huxley) neurons, showing quantitatively how the extent of the partial phase synchronization depends on the magnitude and mean interspike frequency of the stimulus. Furthermore, we present several simple examples that disprove the notion that phase synchrony must be strongly related to spike synchrony. Instead, the importance of partial phase synchrony is shown to lie in its influence on the response of the population to stimulation, which we illustrate using first spike time histograms.     

An inhibitory brainstem input to dopamine neurons encodes nicotine aversion

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