Coherence Resonance Research Articles

A bimembrane neuron for computational neuroscience

A biological neuron has endomembrane and extracellular membrane, and its capacitive effect can be described in an equiavlent neural circuit composed of two capacitors. In this paper, a smooth nonlinear resistor with cubic term for the current-voltage (i-v) is introduced into a nonlinear circuit connected with two capacitors and one inductor. The characteristic of field energy is analyzed and unknown parameters are identified with adaptive law. Furthermore, a magnetic flux-controlled memristor (MFCM) is connected to this circuit to estimate its memristive effect on dynamics and energy flow. After scale transformation, the two kinds of nonlinear circuits are replaced by equivalent neuron models, which can present similar spiking, bursting patterns as those presented in biological neurons. Energy function is obtained in theoretical way for discerning the relation between mode selection and energy level. Noisy disturbance is applied to induce coherence resonance, and the involvement of memristive current can induce coherence resonance with lower noise intensity. The results confirmed that energy flow can be controlled to regulate the electric activities in neurons, and higher energy level is obtained in periodic patterns of neuron under coherence resonance. This neural circuit and the memristive model are more suitable for identifying the neural activities in nervous system composed of biological neurons.

Dynamical and coherence resonance in a photoelectric neuron under autaptic regulation

Dynamical and coherence resonance in a photoelectric neuron under autaptic regulation

Delay-induced self-oscillation excitation in the Fitzhugh–Nagumo model: Regular and chaotic dynamics

The stochastic FitzHugh–Nagumo model with time delayed-feedback is often studied in excitable regime to demonstrate the time-delayed control of coherence resonance. Here, we show that the impact of time-delayed feedback in the FitzHugh–Nagumo neuron is not limited by control of noise-induced oscillation regularity (coherence), but also results in excitation of the regular and chaotic self-oscillatory dynamics in the deterministic model. We demonstrate this numerically by means of simulations, linear stability analysis, the study of Lyapunov exponents and basins of attraction for both positive and negative delayed-feedback strengths. It has been established that one can implement a route to chaos in the explored model, where the intrinsic peculiarities of the Feigenbaum scenario are exhibited. For large time delay, we complement the study of temporal evolution by the interpretation of the dynamics as patterns in virtual space.

Coherent magneto-optical resonances on the potassium D2 line in Hanle configuration for magnetometry applications

The coherent magneto-optical resonances on the potassium D2 line are investigated from the point of view of magnetometry applications. The measurements are performed in Hanle configuration with potassium excited by circularly polarized laser beam in cell with dimensions 8 mm and buffer gas 30 Torr Ne. The parameters of the resonances registered in fluorescence and transmission are compared. The capability of the laser system to work with magnetically unshielded cell is demonstrated. The registration of bright and dark magneto-optical resonances detected in fluorescence by controlling the optical thickness of potassium vapor is discussed. The influence of the laser power and transverse magnetic field are considered. The experimental results show the potential of the system for magnetic field sensing and calibration.

How random fluctuations can generate and suppress complex oscillatory regimes in continuous stirred tank reactors

Motivated by important chemical engineering applications, we study probabilistic mechanisms of stochastic effects in a randomly forced model of the continuous stirred tank reactor. The bifurcation analysis of the deterministic model reveals the parameter zone of bistability with coexistence of the equilibrium and oscillatory regimes. It is shown that the boundary between basins of these regimes is moving as the bifurcation parameter changes. We study noise-induced transitions across this boundary leading to the stochastic generation of spiking oscillations and backward effect of the noise-induced suppression of large-amplitude spiking. In the study of these stochastic effects, we use statistics extracted from the direct numerical simulation, and an analytical approach using confidence ellipses method. An important probabilistic phenomenon of coherence resonance is revealed and discussed.

Topological resonances in a Möbius ring resonator

A Möbius strip, fascinating for its unique topological property of being a one-side nonorientable surface, has inspired mathematicians, physicists, engineers, and artists for many centuries. In a coherent system, coherent waves on the nonorientable surfaces reveal rich topological dynamics due to the interplay of coherence and topology. Here we experimentally observe topological resonances in a Möbius ring resonator formed in a twisted optical fiber loop. The twisted polarization-maintaining fiber ring encourages the hybridization of two polarization states, giving rise to the crucial Berry phase. This geometrical phase leads to the frequency shifts of fiber resonant modes with a non-trivial fractional mode number. Moreover, the resonant modes are topological, only resonating with certain polarized modes with circular chirality. These topological features introduce geometrical factors into coherent wave resonances, paving the way for topological information processing for quantum information, and coherent wave dynamics.

Combined effects of spike-timing-dependent plasticity and homeostatic structural plasticity on coherence resonance.

Efficient processing and transfer of information in neurons have been linked to noise-induced resonance phenomena such as coherence resonance (CR), and adaptive rules in neural networks have been mostly linked to two prevalent mechanisms: spike-timing-dependent plasticity (STDP) and homeostatic structural plasticity (HSP). Thus this paper investigates CR in small-world and random adaptive networks of Hodgkin-Huxley neurons driven by STDP and HSP. Our numerical study indicates that the degree of CR strongly depends, and in different ways, on the adjusting rate parameter P, which controls STDP, on the characteristic rewiring frequency parameter F, which controls HSP, and on the parameters of the network topology. In particular, we found two robust behaviors. (i) Decreasing P (which enhances the weakening effect of STDP on synaptic weights) and decreasing F (which slows down the swapping rate of synapses between neurons) always leads to higher degrees of CR in small-world and random networks, provided that the synaptic time delay parameter τ_{c} has some appropriate values. (ii) Increasing the synaptic time delay τ_{c} induces multiple CR (MCR)-the occurrence of multiple peaks in the degree of coherence as τ_{c} changes-in small-world and random networks, with MCR becoming more pronounced at smaller values of P and F. Our results imply that STDP and HSP can jointly play an essential role in enhancing the time precision of firing necessary for optimal information processing and transfer in neural systems and could thus have applications in designing networks of noisy artificial neural circuits engineered to use CR to optimize information processing and transfer.

Transformations of spike and burst oscillations in the stochastic Rulkov model

We study the problem of modeling and analysis of complex oscillatory regimes in neuron dynamics on the basis of the two-dimensional Rulkov model. We focus on the parameter zone in which sharp changes in the type of oscillatory activity occur: burst oscillations with an active phase of a triangular shape are transformed into bimodal bursts combining triangular and trapezoidal phases. Mechanisms of such transformations are clarified geometrically by the technique of critical curves. For the stochastically forced model, we study two phenomena: (i) noise-induced splitting of tonic spiking; (ii) noise-induced transitions from the triangular mono-bursting to the more complicated bi-bursting. The phenomena of coherence and anti-coherence resonance are revealed and discussed.

Photonic-crystal surface-emitting lasers with modulated photonic crystals enabling 2D beam scanning and various beam pattern emission

Photonic-crystal surface-emitting lasers (PCSELs) with modulated photonic crystals have attracted much attention for their unrivaled capabilities, such as broad area coherent resonance, and lens-free beam scanning and flash illumination. In this paper, we first explain the principles and the development of PCSELs with modulated photonic crystals toward non-mechanical two-dimensional (2D) beam-scanning applications. Then, we show PCSELs with modulated photonic crystals, whose modulation is designed based on an inverse Fourier transform to enable the emission of various beam patterns, such as flash patterns and multi-dot patterns, from a single photonic crystal without using external optical elements. This demonstration underscores the flexibility of PCSELs with modulated photonic crystals as compact, highly functional light sources for a wide range of applications, including not only beam-scanning-type, flash-type, and multidot-type light detection and ranging but also advanced object recognition and adaptive illumination.

Noise-driven bursting birhythmicity in the Hindmarsh-Rose neuron model.

The stochastic Hindmarsh-Rose model is studied in the parameter region where two bursting limit cycles of different types coexist. We show that under the influence of noise, transitions between basins of attractions appear, which generates stochastic bursting oscillations of mixed modes. The formation of this new regime is accompanied by anti-coherence and coherence resonances as well as by the transition to chaos. We investigate the probabilistic mechanism of the noise-driven bursting birhythmicity using the stochastic sensitivity functions and confidence domains method.

Study on the mechanism of acid modified H-Beta zeolite acidic sites on the catalytic pyrolysis of Kraft lignin

In this study, Sn modified molecular sieves with Lewis (L) acid center and Al modified molecular sieves with Brönsted (B) acid center were prepared by post-synthesis method. They were applied to the catalytic pyrolysis of Kraft lignin for the preparation of bio-oil. The acid properties of acid modified zeolites were systematically investigated by XRD, SEM, EDS and Py-FT-IR, and the bio-oil is analyzed by heteronuclear single quantum coherent nuclear magnetic resonance (HSQC-NMR). By separating L acid and B acid from zeolite molecular sieves, the conformational relationships between these two acids on the oxygen-containing functional groups in Kraft lignin bio-oil are investigated separately. The results show that acid modified molecular sieves’ L acid and B acid can effectively improve the cleavage of aromatic C-O bonds including methoxy and ether bonds. The L acid of Sn modified molecular sieve tends to break the O-C4 bond and the natural methoxy bond, while the B acid of Al modified molecular sieve generates aliphatic hydrocarbon intermediates and phenolic compounds by breaking the Cβ-O bond and rearranging the methoxy bond. By chemical characterization of the acid modified molecular sieves and the bio-oil, the conformational relationship between the L acid and B acid of zeolite molecular sieves on the deoxygenation efficiency of Kraft lignin pyrolysis bio-oil is established.

Phase synchronization between neurons under nonlinear coupling via hybrid synapse

Biological neurons and nonlinear circuits contain certain inner field energy, and an equivalent Hamilton energy function can be obtained to discern the dependence of firing modes on the energy flow. In this paper, a voltage-controlled resistor is used to connect two neural circuits, and hybrid synapse is activated to control the synchronization stability and mode transition in neurons under phase lock. Realistic stimuli can be combined signals within certain frequency band rather than simple periodic stimulus, and the firing patterns will show multiple modes by applying mixed signals. Similar coherence resonance is detected in an isolated neuron driven by the filtered signals. Therefore, chaotic signals are encoded to represent filtered waves with finite frequency band, and then the mixed signals are used to excite two neural circuits via nonlinear coupling. Hamilton energy for the coupled neurons via hybrid synapse is estimated to detect the controllability of synchronization between neurons. The nonlinear resistor along the coupling channel can reproduce the biophysical property of hybrid synapse accompanying with field coupling, which mainly contributes the energy exchange between neurons. It is confirmed that this hybrid synapse is effective to control the synchronization stability and phase lock even the neurons presenting with different firing patterns/modes. The results confirmed that nonlinear coupling via specific components is helpful to design hybrid synapse, and it is effective to block the bursting synchronization between neurons driven by filtered chaotic signals. Therefore, activation of this hybrid synapse can prevent the occurrence of seizure in nervous system.

Spectrum and Light Shift of the Coherent Population Trapping Resonance in Cells with Antirelaxation Wall Coating in Specular and Diffuse Reflection Models

We consider the motion of atoms in a cell free of a buffer gas with an antirelaxation wall coating on the spectrum and shift of the coherent population trapping resonance. We compare two types of reflection of atoms, viz., elastic (specular) and diffuse reflection, when the velocity of an atom after its reflection is determined by the wall temperature, as well by the quality of the antirelaxation wall coating. It is shown that for both types of reflection, a nonmonotonic dependence of the coherent population trapping resonance shift on the cell size is observed. In the case of diffuse reflection, the shift can change sign, and a complex two-hump structure of the coherent population trapping resonance is observed in a certain range of cell lengths. The dependence of the detected effects on the laser radiation spectral width is analyzed.

Tuning magneto-electric coherent resonance with a deep-subwavelength localized spoof surface plasmonic structure.

It has been recently shown that an ultrathin corrugated spiral metal strip can simultaneously support electric and magnetic localized spoof plasmonic modes at lower frequencies. In this Letter, we report a mirror quasi-symmetrical corrugated spiral metal disk which can support coherent resonance of an orthogonal electric dipole and a magnetic dipole to achieve azimuthally symmetric unidirectional scattering. By tuning the geometric dimensions, reconfigurable magneto-electric (ME) coherent resonance enhancement is realized. Excellent agreement between numerical simulations and experimental results verifies the tunable ME coherent resonance phenomenon. Our finding could anticipate future sensitive and versatile functional devices based on high-Q coherent resonance from the microwave to the terahertz bands.

Spectrum and Light Shift of the Coherent Population Trapping Resonance in Cells with Antirelaxation Wall Coating in Specular and Diffuse Reflection Models

Spectrum and Light Shift of the Coherent Population Trapping Resonance in Cells with Antirelaxation Wall Coating in Specular and Diffuse Reflection Models

Coherence resonance and stochastic synchronization in a small-world neural network: an interplay in the presence of spike-timing-dependent plasticity

Coherence resonance (CR), stochastic synchronization (SS), and spike-timing-dependent plasticity (STDP) are ubiquitous dynamical processes in biological neural networks. Whether there exists an optimal network and STDP configuration at which CR and SS are both pronounced is a fundamental question of interest that is still elusive. We expect such a configuration to enable the brain to make synergistic and optimal use of these phenomena to process information efficiently. This paper considers a small-world network of excitable Hodgkin–Huxley neurons driven by channel noise and STDP with an asymmetric Hebbian time window. Numerical results indicate specific network topology and STDP parameter intervals in which CR and SS can be simultaneously enhanced. Our results imply that an optimally tuned inherent background noise, STDP rule, and network topology can play a constructive role in enhancing both the time precision of firing and the synchronization in neural systems.

Observations of Rapidly Growing Whistler Waves in Front of Space Plasma Shock due to Resonance Interaction between Fluctuating Electron Velocity Distributions and Electromagnetic Fields

The whistler-mode wave extending from the fast-magnetosonic wave branch is a fundamental perturbation of electromagnetic fields and plasmas in various environments including planetary space, laboratory, and astrophysics. The origin and evolution of the waves is a long-standing question due to the limited instrumental capability in resolving highly variable plasma and electromagnetic fields. Here, we analyze observational data with a high time resolution from the Magnetospheric Multiscale spacecraft in front of the terrestrial bow shock (e.g., foreshock). We develop a novel approach to extract the three-dimensional fluctuating electron velocity distributions (δf e( V )) from their background (f e0( V )), and have successfully captured the coherent resonance between fluctuating electrons (δf e( V )) and wavelike electromagnetic fields (δ B , δ E ) at an unprecedentedly high frequency (>1 Hz) for investigating wave–particle interactions. We provide that the unstable whistler wave grows rapidly over a timescale that is much shorter than the proton gyro-period. Regarding the energy origin for the waves, we find the ion distributions consisting of the solar wind ion flows and the ion beams reflected from the shock play crucial roles in providing the free energy and determining the eigenmode disturbances of fields and electrons. The quantification of wave growth rate and the characterization of wave–particle interactions for the instability driver can significantly advance the understandings of wave evolution and energy conversion between multisource multispecies particles and wave electromagnetic fields.

Frequency shift compensation for single and dual laser beam pass sensors of a coherent population trapping resonance based coupled dark state magnetometer

The Coupled Dark State Magnetometer is an atomic magnetometer designed for magnetic field measurements in space. Its measurement principle is based on the excitation of coupled dark state resonances prepared via the coherent population trapping effect. The coupled dark state resonances enable the compensation of disturbing frequency shifts which degrade the measurement accuracy. Results with a sensor design based on a single laser beam pass through the sensor unit reveal a reduced ability to compensate these disturbing effects compared to theoretical predictions. Therefore, a new sensor design is presented which enables a dual laser beam pass through the sensor unit. For almost all angles between the external magnetic field and the light propagation direction, the dual pass sensor design enables a better compensation of disturbing frequency shifts than the single pass sensor design - up to a factor of nine.

How noise transforms spiking into bursting in a neuron model having the Lukyanov–Shilnikov bifurcation

Motivated by an attractive biophysical problem related to revealing the underlying mechanisms of complex oscillatory forms of neural activity, we study a three-dimensional model having the Lukyanov–Shilnikov bifurcation in the parameter region where the system simulates tonic spiking oscillations. We reveal that additive white noise can transit this system from the spiking regime to the bursting. Moreover, it is found that this phenomenon is accompanied by the coherence resonance in generated oscillations and followed by transition to chaos. We investigate these noise-driven effects using both direct numerical simulation method with statistical post-processing of results as well as the theoretical stochastic sensitivity analysis and the methods of confidence domains and Mahalanobis metrics.

Coherence and stochastic resonance in the fractional-birhythmic self-sustained system subjected to fractional time-delay feedback and Lévy noise

This paper treats the nonlinear dynamics of an enzymatic-substrate modeled by the fractional multi-limit cycles Van der Pol oscillator with fractional time-delay feedback device subjected to Lévy noise perturbation and periodic excitation. The fractional electronic circuit has been used to model the system and the oscillations are described by a nonlinear fractional differential equation and show a new bifurcation parameter. The robustness of the stochastic resonance is examined by the use of standard measures within a continuous and a two-state description of the system. Firstly, the electronic circuit with the fractional-order operator and fractional delay feedback is used as a prototype of a fractional self-sustained system. Secondly, based on the minimum mean square error principle, the fractional derivative term is found to be equivalent to the linear combination of the damping force and restoring force, and the original system is further simplified to an equivalent integer order system. The stochastic bifurcation of a bistable Van der Pol system with fractional-order and time delay without and under Lévy noise excitation is studied where we show the considerable effect of these parameters on birhythmic region, escape time and energy barriers. Additionally, we study the multi-effects of fractional order and fractional time-delay feedback in the self-sustained system driven by Lévy noise. The effects of fractional-order parameter, time delay feedback parameter on the autocorrelation function, power spectral density and signal-to-noise-ratio used in this investigation are shown to be maximized for an appropriate choice of the Lévy noise intensity and for a convenient choice of fractional-order and time delay feedback parameters. For a choice of a control parameter in the birhythmic region, by varying the other parameters of the system like fractional and time delay parameters, it appears that, for a fixed value of skewness Lévy noise parameter, the initial selection of the attractor seems to have a large effect on the resonance and coherence.