Meromorphic solutions in the FitzHugh–Nagumo model

The FitzHugh–Nagumo model is studied in the framework of analytic theory of differential equations. The Nevanlinna theory is used to find all meromorphic solutions of a second-order ordinary differential equation related to the FitzHugh–Nagumo model. As a consequence new exact solutions of the FitzHugh–Nagumo system are obtained in explicit form.     

Pattern selection in the 2D FitzHugh–Nagumo model

We construct square and target patterns solutions of the FitzHugh–Nagumo reaction–diffusion system on planar bounded domains. We study the existence and stability of stationary square and super-square patterns by performing a close to equilibrium asymptotic weakly nonlinear expansion: the emergence of these patterns is shown to occur when the bifurcation takes place through a multiplicity-two eigenvalue without resonance. The system is also shown to support the formation of axisymmetric target patterns whose amplitude equation is derived close to the bifurcation threshold. We present several numerical simulations validating the theoretical results.

     

Robust synchronization of FitzHugh–Nagumo network with parameter disturbances by sliding mode control

In this paper, based on the sliding mode control method, the robust synchronization for a coupled FitzHugh–Nagumo (FHN) neurobiological network with parameter disturbances is investigated. Some theoretical criteria are derived to realize the robust synchronization of the FHN network with disturbed parameters, and the synchronization occurs without dependence on the type and magnitude of the noise, which greatly extend some existing results for two or three coupled FHN neurons. Finally, a numerical example is given to illustrate the effectiveness of the proposed theoretical results.     

Periodic solutions in an array of coupled FitzHugh–Nagumo cells

We analyse the dynamics of an array of N²$N^2$ identical cells coupled in the shape of a torus. Each cell is a 2-dimensional ordinary differential equation of FitzHugh–Nagumo type and the total system is _ZN×_ZN${\mathbb{Z}}_N\times {\mathbb{Z}}_N$-symmetric. The possible patterns of oscillation, compatible with the symmetry, are described. The types of patterns that effectively arise through Hopf bifurcation are shown to depend on the signs of the coupling constants, under conditions ensuring that the equations have only one equilibrium state.     

Two-frequency self-oscillations in a FitzHugh–Nagumo neural network

A new mathematical model of a one-dimensional array of FitzHugh–Nagumo neurons with resistive-inductive coupling between neighboring elements is proposed. The model relies on a chain of diffusively coupled three-dimensional systems of ordinary differential equations. It is shown that any finite number of coexisting stable invariant two-dimensional tori can be obtained in this chain by suitably increasing the number of its elements.     

Stability of Traveling Pulses with Oscillatory Tails in the FitzHugh–Nagumo System

The FitzHugh–Nagumo equations are known to admit fast traveling pulses that have monotone tails and arise as the concatenation of Nagumo fronts and backs in an appropriate singular limit, where a parameter \(\varepsilon \) goes to zero. These pulses are known to be nonlinearly stable with respect to the underlying PDE. Recently, the existence of fast pulses with oscillatory tails was proved for the FitzHugh–Nagumo equations. In this paper, we prove that the fast pulses with oscillatory tails are also nonlinearly stable. Similar to the case of monotone tails, stability is decided by the location of a nontrivial eigenvalue near the origin of the PDE linearization about the traveling pulse. We prove that this real eigenvalue is always negative. However, the expression that governs the sign of this eigenvalue for oscillatory pulses differs from that for monotone pulses, and we show indeed that the nontrivial eigenvalue in the monotone case scales with \(\varepsilon \), while the relevant scaling in the oscillatory case is \(\varepsilon ^{2/3}\).     

Control of space-time chaos in a system of equations of the FitzHugh–Nagumo type

We perform an analytic and numerical study of a system of partial differential equations that describes the propagation of nerve impulses in the heart muscle. We show that, for fixed parameter values, the system has infinitely many distinct stable wave solutions running along the spatial axis at arbitrary velocities and infinitely many distinct modes of space-time chaos, where the bifurcation parameter is the velocity of running wave propagation along the spatial axis, which does not explicitly occur in the original system of equations. We suggest an algorithm for controlling the space-time chaos in the system, which permits one to stabilize any of its unstable periodic running waves.     

Stability analysis for standing pulse solutions to FitzHugh–Nagumo equations

This paper studies standing pulse solutions to the FitzHugh–Nagumo equations. Since the reaction terms are coupled in a skew-gradient structure, a standing pulse solution is a homoclinic orbit of a second order Hamiltonian system. In this work, an index theory for the Hamiltonian system is employed to study the stability of standing pulses for the FitzHugh–Nagumo equations. Related results for more general skew-gradient systems are also obtained.     

Combined effects of correlated bounded noises and weak periodic signal input in the modified FitzHugh–Nagumo neural model

We study the dynamics of neurons via a bistable modified stochastic FitzHugh–Nagumo model having two stable fixed points separated by one unstable fixed point. Due to the ability of a neuron to detect and enhance weak information transmission, we show numerically that starting from the resting potential, we get firing activities (spiking) when operating slightly beyond the supercritical Hopf bifurcation. For real biological systems which are sometimes embedded in the complex environment, we observe that a gradual increase or decrease noise intensities did not result in a gradual change of the membrane potential distribution thanks to noise induced transition phenomena. We shown analytically that for zero correlation between two sine Wiener noises, additive noise has no effect on the transition between monostable and bistable phase on the neural model. We adapted a general expression of the signal-to-noise ratio for a general two-state theory extended in the asymmetric case and non-Gaussian noises in our model to study the influence of noise strength in stochastic resonance. Our investigation revealed that in the evolution of excitable system, neurons may use noises to their advantage by enhancing their sensitivity near a preferred phase to detect external stimuli or affect the efficiency and rate of information processing.     

Unidirectional synchronization of Hodgkin–Huxley neurons exposed to ELF electric field

In this paper, a hybrid control strategy, H_∞ variable universe adaptive fuzzy control, is derived and applied to synchronize two Hodgkin–Huxley (HH) neurons exposed to external electric field. Firstly, the modified model of HH neuron exposed to extremely low frequency (ELF) external electric field is established and its periodic and chaotic dynamics in response to sinusoidal electric field stimulation are described. And then the statement of the problem for unidirectional synchronization of two HH neurons is given. Finally H_∞ variable universe adaptive fuzzy control is designed to synchronize the HH systems and the simulation results demonstrate the effectiveness of the proposed control method.     

Unidirectional synchronization for Hindmarsh–Rose neurons via robust adaptive sliding mode control

This paper presents an adaptive neural network (NN) based sliding mode control for unidirectional synchronization of Hindmarsh–Rose (HR) neurons in a master–slave configuration. We first give the dynamics of single HR neuron which may exhibit spike-burst chaotic behaviors. Then we formulate the problem of unidirectional synchronization control of two HR neurons and propose a NN based sliding mode controller. The controller consists of two simple radial basis function (RBF) NNs which are used to approximate the desired sliding mode controller and the uncertain nonlinear part of the error dynamical system, respectively. The control scheme is robust to the uncertainties such as approximate errors, ionic channel noise and external disturbances. The simulation results demonstrate the validity of the proposed control method.     

On solutions to a FitzHugh–Rinzel type model

Ricerche di Matematica - A ternary autonomous dynamical system of FitzHugh–Rinzel type is analyzed. The system, at start, is reduced to a nonlinear integro differential equation. The...     

Controlling chaos in space-clamped FitzHugh–Nagumo neuron by adaptive passive method

The space-clamped FitzHugh–Nagumo (SCFHN) neuron exhibits complex chaotic firing when the amplitude of the external current falls into a certain area. To control the undesirable chaos in SCFHN neuron, a passive control law is presented in this paper, which transforms the chaotic SCFHN neuron into an equivalent passive system. It is proved that the equivalent system can be asymptotically stabilized at any desired fixed state, namely, chaos in SCFHN neuron can be controlled. Moreover, to eliminate the influence of undeterministic parameters, an adaptive law is introduced into the designed controller. Computer simulation results show that the proposed controller is very effective and robust against the uncertainty in systemic parameters.     

Self-synchronization of coupled chaotic FitzHugh–Nagumo systems with unreliable communication links

The problem for self-synchronization of coupled chaotic FitzHugh–Nagumo (FHN) systems with unreliable communication links is investigated in this paper. Different from ordinary coupled chaotic systems, the links between two neurons are long-distance and unreliable. Some special network characteristics, such as nonuniform sampling, transmission-induced delays and data packet dropouts, are analyzed in detail. The sufficient condition in terms of linear matrix inequality (LMI) is obtained to guarantee the asymptotical self-synchronization of coupled chaotic FHN systems with unreliable communication links. Lastly, an illustrative example is provided to show the validity of the proposed sufficient condition.     

Standing Waves Joining with Turing Patterns in FitzHugh–Nagumo Type Systems

An article by Kondo and Asai demonstrated that the pattern formation and change on the skin of tropical fishes can be predicted well by reaction-diffusion models of Turing type. As being observed, a common pattern structure is the rearrangement of stripe pattern, and defect like heteroclinic solution appeared between the patterns with different number of stripes. We consider FitzHugh–Nagumo type reaction-diffusion systems with anisotropic diffusion. Under a sufficient condition in diffusivity, we apply variational arguments to show the existence of standing waves joining with Turing patterns.