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.     

Studies of phase return map and symbolic dynamics in a periodically driven Hodgkin–Huxley neuron

How neuronal spike trains encode external information is a hot topic in neurodynamics studies.In this paper,we investigate the dynamical states of the Hodgkin–Huxley neuron under periodic forcing.Depending on the parameters of the stimulus,the neuron exhibits periodic,quasiperiodic and chaotic spike trains.In order to analyze these spike trains quantitatively,we use the phase return map to describe the dynamical behavior on a one-dimensional(1D)map.According to the monotonicity or discontinuous point of the 1D map,the spike trains are transformed into symbolic sequences by implementing a coarse-grained algorithm—symbolic dynamics.Based on the ordering rules of symbolic dynamics,the parameters of the external stimulus can be measured in high resolution with finite length symbolic sequences.A reasonable explanation for why the nervous system can discriminate or cognize the small change of the external signals in a short time is also presented.     

Characteristics of critical amplitude of a sinusoidal stimulus in a model neuron

The characteristics of the critical amplitude of a sinusoidal stimulus in a model neuron, Morris－Lecar model, are investigated numerically. It is important in the study of stochastic resonance to determine whether a periodic stimulus is subthreshold or not. The critical amplitude as a function of the stimulus frequency is not a constant, but a curve, which is the boundary between subthreshold and suprathreshold stimulation. It has been considered that this curve is U-shaped in the previous investigations, and this has been accepted as a universal phenomenon. Nevertheless, we think that it is only true for a type of neuron: namely, resonators. Actually, there exists another type of neuron, integrators, which can undergo a saddle-node on invariant circle bifurcation from the rest state to the firing state. For the latter we find that the critical amplitude increases monotonically as the frequency of sinusoidal stimulus is increased. This is shown by way of the Morris－Lecar model. As a consequence, the critical amplitude curve is studied further, and the dynamical mechanisms underlying the change in critical amplitude curve are uncovered. The results of this paper can provide a reference to choose the subthreshold periodic stimulus.     

Synchronization transition of a coupled system composed of neurons with coexisting behaviors near a Hopf bifurcation

The coexistence of a resting condition and period-1 firing near a subcritical Hopf bifurcation point, lying between the monostable resting condition and period-1 firing, is often observed in neurons of the central nervous systems. Near such a bifurcation point in the Morris-Lecar （ML） model, the attraction domain of the resting condition decreases while that of the coexisting period-1 firing increases as the bifurcation parameter value increases. With the increase of the coupling strength, and parameter and initial value dependent synchronization transition processes from non-synchronization to compete synchronization are simulated in two coupled ML neurons with coexisting behaviors： one neuron chosen as the resting condition and the other the coexisting period-1 firing. The complete synchronization is either a resting condition or period-1 firing dependent on the initial values of period-1 firing when the bifurcation parameter value is small or middle and is period- 1 firing when the parameter value is large. As the bifurcation parameter value increases, the probability of the initial values of a period- 1 firing neuron that lead to complete synchronization of period- 1 firing increases, while that leading to complete synchronization of the resting condition decreases. It shows that the attraction domain of a coexisting behavior is larger, the probability of initial values leading to complete synchronization of this behavior is higher. The bifurcations of the coupled system are investigated and discussed. The results reveal the complex dynamics of synchronization behaviors of the coupled system composed of neurons with the coexisting resting condition and period-1 firing, and are helpful to further identify the dynamics of the spatiotemporal behaviors of the central nervous system.     

Energy dependence on the electric activities of a neuron

A nonlinear circuit can be designed by using inductor, resistor, capacitor and other electric devices, and the electromagnetic field energy can be released from the circuit in the oscillating state. The generation of spikes or bursting states in neurons could be energetically a costly process. Based on the Helmholtz's theorem, a Hamilton energy function is defined to detect the energy shift induced by transition of electric modes in a Hindmarsh–Rose neuron. It is found that the energy storage is dependent on the external forcing, and energy release is associated with the electric mode. As a result, the bursting state and chaotic state could be helpful to release the energy in the neuron quickly.     

Environmental Impacts on Spiking Properties in Hodgkin-Huxley Neuron with Direct Current Stimulus

Based on the well accepted Hodgkin-Huxley neuron model, the neuronal intrinsic excitability is studied when the neuron is subject to varying environmental temperatures, the typical impact for its regulating ways. With computer simulation, it is found that altering environmental temperature can improve or inhibit the neuronal intrinsic excitability so as to influence the neuronal spiking properties. The impacts from environmental factors can be understood that,the neuronal spiking threshold is essentially influenced by the fluctuations in the environment. With the environmental temperature varying, burst spiking is realized for the neuronal membrane voltage because of the environment-dependent spiking threshold. This burst induced by changes in spiking threshold is different from that excited by input currents or other stimulus.     

Effect of stochastic electromagnetic disturbances on autapse neuronal systems

With the help of a magnetic flux variable, the effects of stochastic electromagnetic disturbances on autapse Hodgkin–Huxley neuronal systems are studied systematically. Firstly, owing to the autaptic function, the inter-spike interval series of an autapse neuron not only bifurcates, but also presents a quasi-periodic characteristic. Secondly, an irregular mixed-mode oscillation induced by a specific electromagnetic disturbance is analyzed using the coefficient of variation of inter-spike intervals. It is shown that the neuronal discharge activity has certain selectivity to the noise intensity, and the appropriate noise intensity can induce the significant mixed-mode oscillations. Finally, the modulation effects of electromagnetic disturbances on a ring field-coupled neuronal network with autaptic structures are explored quantitatively using the average spiking frequency and the average coefficient of variation. The electromagnetic disturbances can not only destroy the continuous and synchronous discharge state, but also induce the resting neurons to generate the intermittent discharge mode and realize the transmission of neural signals in the neuronal network. The studies can provide some theoretical guidance for applying electromagnetic disturbances to effectively control the propagation of neural signals and treat mental illness.     

Phase Locking Phenomena and Electroencephalogram-Like Activities in Dynamic Neuronal Systems

We study signal detection and transduction of dynamic neuronal systems under the influence of external noise,white and coloured. Based on simulations, we show explicitly phase locking phenomena between the output and the input of a single neuron and Electroencephalogram-like activities on neural networks with small-world connectivity. The numerical results prove that the dynamic neuronal system can be adjusted to an optimal sensitive state for signal processing in the presence of additive noise.     

Effect of Topological Connectivity on Firing Pattern Transitions in Coupled Neurons

By using the coupled model of Hindmarsh-Rose neuronal systems, we numerically investigate the effect of topology structures on the firing patterns transition （FPT）. A four-cell coupled system with all possible configurations are studied. We select the membrane current Iext as a controllable parameter, and set it to be near the left side for one of the bifurcation points. It is found that to have a response from some external stimuli with the proper amplitude and frequencies, the transition will appear between different firing states only when the cells in the system are coupled with some proper topological structures, which implies the occurrence of FPT induced by the configuration in the coupled system. Similar FPT phenomena could also be observed in a five-cell coupled system. Fbrthermore, we find that such transition behaviors may have some inherent relevance with the synchronization error and the average connective number among cells in the coupled system for different topology structures. These results suggest that the biological neuron systems may achieve an effective response to the external feeble stimulus by selecting the proper configuration and using the corresponding transition mode.     

Firing dynamics of an autaptic neuron

Autapses are synapses that connect a neuron to itself in the nervous system. Previously, both experimental and theoretical studies have demonstrated that autaptic connections in the nervous system have a significant physiological function. Autapses in nature provide self-delayed feedback, thus introducing an additional timescale to neuronal activities and causing many dynamic behaviors in neurons. Recently, theoretical studies have revealed that an autapse provides a control option for adjusting the response of a neuron: e.g., an autaptic connection can cause the electrical activities of the Hindmarsh–Rose neuron to switch between quiescent, periodic, and chaotic firing patterns; an autapse can enhance or suppress the mode-locking status of a neuron injected with sinusoidal current; and the firing frequency and interspike interval distributions of the response spike train can also be modified by the autapse. In this paper, we review recent studies that showed how an autapse affects the response of a single neuron.     

State-to-State Transitions in a Hindmarsh-Rose Neuron System

We investigate the dynamical response of the neuron system to a feeble external signal by using the Hindmarsh-Rose model, when the system is tuned below the first bifurcation point, which corresponds to the period-1 bursting state, and an external signal with a fixed period of about 170s is introduced to the system. It is found that to respond to the outside signal, the system changes from the period-1 state to a period-2 one with variation of the signal amplitude, indicating the occurrence of state-to-state transition （SST）. Moreover, when a signal with different fixed periods is introduced, we can also find a similar transition between other states. Furthermore, the effect of the frequency of the signal on the transition is also discussed. These results may imply that SST plays a constructive role in information processing in neuron systems.     

Bifurcation diagram globally underpinning neuronal firing behaviors modified by SK conductance

Neurons in the brain utilize various firing trains to encode the input signals they have received.Firing behavior of one single neuron is thoroughly explained by using a bifurcation diagram from polarized resting to firing,and then to depolarized resting.This explanation provides an important theoretical principle for understanding neuronal biophysical behaviors.This paper reports the novel experimental and modeling results of the modification of such a bifurcation diagram by adjusting small conductance potassium(SK)channel.In experiments,changes in excitability and depolarization block in nucleus accumbens shell and medium-spiny projection neurons are explored by increasing the intensity of injected current and blocking the SK channels by apamin.A shift of bifurcation points is observed.Then,a Hodgkin–Huxley type model including the main electrophysiological processes of such neurons is developed to reproduce the experimental results.The reduction of SK channel conductance also shifts the bifurcations,which is in consistence with experiment.A global bifurcation paradigm of this shift is obtained by adjusting two parameters,intensity of injected current and SK channel conductance.This work reveals the dynamics underpinning modulation of neuronal firing behaviors by biologically important ionic conductance.The results indicate that small ionic conductance other than that responsible for spike generation can modify bifurcation points and shift the bifurcation diagram and,thus,change neuronal excitability and adaptation.     

Complete and phase synchronization in a heterogeneous small-world neuronal network

Synchronous firing of neurons is thought to be important for information communication in neuronal networks. This paper investigates the complete and phase synchronization in a heterogeneous small-world chaotic Hindmarsh--Rose neuronal network. The effects of various network parameters on synchronization behaviour are discussed with some biological explanations. Complete synchronization of small-world neuronal networks is studied theoretically by the master stability function method. It is shown that the coupling strength necessary for complete or phase synchronization decreases with the neuron number, the node degree and the connection density are increased. The effect of heterogeneity of neuronal networks is also considered and it is found that the network heterogeneity has an adverse effect on synchrony.     

Estimation of biophysical properties of cell exposed to electric field

Excitable media,such as cells,can be polarized and magnetized in the presence of an external electromagnetic field.In fact,distinct geometric deformation can be induced by the external electromagnetic field,and also the capacitance of the membrane of cell can be changed to pump the field energy.Furthermore,the distribution of ion concentration inside and outside the cell can also be greatly adjusted.Based on the theory of bio-electromagnetism,the distribution of field energy and intracellular and extracellular ion concentrations in a single shell cell can be estimated in the case with or without external electric field.Also,the dependence of shape of cell on the applied electronic field is calculated.From the viewpoint of physics,the involvement of external electric field will change the gradient distribution of field energy blocked by the membrane.And the intracellular and extracellular ion concentration show a certain difference in generating timevarying membrane potential in the presence of electric field.When a constant electric field is applied to the cell,distinct geometric deformation is induced,and the cell triggers a transition from prolate to spherical and then to oblate ellipsoid shape.It is found that the critical frequency in the applied electric field for triggering the distinct transition from prolate to oblate ellipsoid shape obtains smaller value when larger dielectric constant of the cell membrane and intracellular medium,and smaller conductivity for the intracellular medium are used.Furthermore,the effect of cell deformation is estimated by analyzing the capacitance per unit area,the density of field energy,and the change of ion concentration on one side of cell membrane.The intensity of external applied electric field is further increased to detect the change of ion concentration.And the biophysical effect in the cell is discussed.So the deformation effect of cells in electric field should be considered when regulating and preventing harm to normal neural activities occurs in a nervous system.     

Bursting and spiking due to additional direct and stochastic currents in neuron models

Neurons at rest can exhibit diverse firing activities patterns in response to various external deterministic and random stimuli, especially additional currents. In this paper, neuronal firing patterns from bursting to spiking, induced by additional direct and stochastic currents, are explored in rest states corresponding to two values of the parameter $V_{\rm K}$ in the Chay neuron system. Three cases are considered by numerical simulation and fast/slow dynamic analysis, in which only the direct current or the stochastic current exists, or the direct and stochastic currents coexist. Meanwhile, several important bursting patterns in neuronal experiments, such as the period-1 ``circle/homoclinic" bursting and the integer multiple ``fold/homoclinic" bursting with one spike per burst, as well as the transition from integer multiple bursting to period-1 ``circle/homoclinic" bursting and that from stochastic ``Hopf/homoclinic" bursting to ``Hopf/homoclinic" bursting, are investigated in detail.     

Plasticity-induced characteristic changes of pattern dynamics and the related phase transitions in small-world neuronal networks

Phase transitions widely exist in nature and occur when some control parameters are changed. In neural systems, their macroscopic states are represented by the activity states of neuron populations, and phase transitions between different activity states are closely related to corresponding functions in the brain. In particular, phase transitions to some rhythmic synchronous firing states play significant roles on diverse brain functions and disfunctions, such as encoding rhythmical external stimuli, epileptic seizure, etc. However, in previous studies, phase transitions in neuronal networks are almost driven by network parameters （e.g., external stimuli）, and there has been no investigation about the transitions between typical activity states of neuronal networks in a self-organized way by applying plastic connection weights. In this paper, we discuss phase transitions in electrically coupled and lattice-based small-world neuronal networks （LBSW networks） under spike-timing-dependent plasticity （STDP）. By applying STDP on all electrical synapses, various known and novel phase transitions could emerge in LBSW networks, particularly, the phenomenon of self-organized phase transitions （SOPTs）： repeated transitions between synchronous and asynchronous firing states. We further explore the mechanics generating SOPTs on the basis of synaptic weight dynamics.     

Control Chaos in Hindmarsh--Rose Neuron by Using Intermittent Feedback with One Variable

The mechanism of the famous phase compression is discussed, and it is used to control the chaos in the Hindmarsh-Rose （H-R） model. It is numerically confirmed that the phase compression scheme can be understood as one kind of intermittent feedback scheme, which requires appropriate thresholds and feedback coeffcient, and the intermittent feedback can be realized with the Heaviside function. In the case of control chaos, the output variable （usually the voltage or the membrane potential of the neuron） is sampled and compared with the external standard signal of the electric electrode. The error between the sampled variable and the external standard signal of the electrode is input into the system only when the sampled variable surpasses the selected thresholds. The numerical simulation results confirm that the chaotic H-R system can be controlled to reach arbitrary n-periodical （n = 1, 2, 3, 4, 5, 6,...） orbit or stable state even when just one variable is feed backed into the system intermittently. The chaotic Chua circuit is also investigated to check its model independence and effectiveness of the schemes and the equivalence of the two schemes are confirmed again.     

Directional sensitivity of auditory ascending neuron in the bushcricket Gampsocleis gratiosa

Quantitative analyses on phonotactic behavior of the bushcricket havedemonstrated that the bushcricket possesses good capability to determine directionof sound source.The morphological structure,laterality and directional sensitivityof the auditory ascending neuron in the prothoracic ganglion of the bushcrickethave been studied.At its best frequency of 15 kHz,the laterality threshold differ-ence of the neuron is great up to about 16 dB.Its directional sensitivity dependsclosely on stimulus frequency.The higher the stimulus frequency,the greater thedirectional threshold differences.Spike count and latency shift of the ascendingneuron in response to each stimulus depend on the angle of incidence of sound.Therefore,the two parameters can be used as directional cues of sound source bythe ascending neuron.     

Effects of Pure Dzyaloshinskii-Moriya Interaction with Magnetic Field on Entanglement in Intrinsic Decoherence

We investigate the effects of pure Dzyaloshinskii-Moriya(DM) interaction with magnetic field on entanglement in intrinsic decoherence,assuming that the system is initially in four Bell states |φ± =(|00 ± |11)/2~(1/2) and|ψ± =(|01) ± |10)/2~(1/2) respectively.It is found that if the system is initially in the state ρ1(0) = |φ+φ+|,the entanglement can obtain its maximum when the DM interaction vector D is in the plane of XOZ and magnetic field B = B_y with the infinite time t,moreover the entanglement is independent of B_y and t when B_y is perpendicular to D.In addition,we obtain similar results when the system is initially in the states ρ2(0) =|φ-φ-| or ρ3(0) = |ψ+ψ+|.However,we find that if the system is initially in the state ρ4(0) =|ψ-ψ-|,the entanglement can obtain its maximum for infinite t,when the DM vector is in the plane of YOZ,XOZ,or XOY,with the magnetic field parallel to X,Y,or Z axis,respectively.Moreover,when the axial B is perpendicular to D for the initial state ρ4(0),the negativity oscillates with time t and reaches a stabie value,the larger the value of B is,the greater the stable value is,and the shorter the oscillation time of the negativity is.Thus we can adjust the direction and value of the external magnetic field to obtain the maximal entanglement,and avoid the adverse effects of external environment in some initial state.This is feasible within the current experimental technology.     

Chaotic dynamics and its analysis of Hindmarsh-Rose neurons by Shil'nikov approach

In this paper, the relationship between external current stimulus and chaotic behaviors of a Hindmarsh–Rose(HR)neuron is considered. In order to find out the range of external current stimulus which will produce chaotic behaviors of an HR neuron, the Shil'nikov technique is employed. The Cardano formula is taken to obtain the threshold of the chaotic motion, and series solution to a differential equation is utilized to obtain the homoclinic orbit of HR neurons. This analysis establishes mathematically the value of external current input in generating chaotic motion of HR neurons by the Shil'nikov method. The numerical simulations are performed to support the theoretical results.