Coherence Resonance Research Articles

3D Reconstruction of a Unitary Posterior Eye by Converging Optically Corrected Optical Coherence and Magnetic Resonance Tomography Images via 3D CAD.

PurposeIn acquiring images of the posterior eye, magnetic resonance imaging (MRI) provides low spatial resolution of the overall shape of the eye while optical coherence tomography (OCT) offers high spatial resolution of the limited range. Through the merger of the two devices, we attempted to acquire detailed anatomy of the posterior eye.MethodsOptical and display distortions in OCT images were corrected using the Listing reduced eye model. The 3.0T orbital MRI images were placed on the three-dimensional coordinate system of the computer-aided design (CAD) program. Employing anterior scleral canal opening, visual axis, and scleral curvature as references, original and corrected OCT images were ported into the CAD application. The radii of curvature of the choroid–scleral interfaces (Rc values) of all original and corrected OCT images were compared to the MRI images.ResultsSixty-five eyes of 33 participants (45.58 ± 19.82 years) with a mean Rc of 12.94 ± 1.24 mm on axial MRI and 13.66 ± 2.81 mm on sagittal MRI were included. The uncorrected horizontal OCT (30.51 ± 9.34 mm) and the uncorrected vertical OCT (34.35 ± 18.09 mm) lengths differed significantly from the MRI Rc values (both P < 0.001). However, the mean Rc values of the corrected horizontal (12.50 ± 1.21 mm) and vertical (13.05 ± 1.98 mm) images did not differ significantly from the Rc values of the corresponding MRI planes (P = 0.065 and P = 0.198, respectively).ConclusionsFeatures identifiable only on OCT and features only on MRI were successfully integrated into a unitary posterior eye.Translational RelevanceOur CAD-based converging method may establish the collective anatomy of the posterior eye and the neural canal, beyond the range of the OCT.

Neuronlike spiking dynamics in asymmetrically driven dissipative nonlinear photonic dimers

We demonstrate neuron-like spiking dynamics in the asymmetrically driven dissipative photonic Bose-Hubbard dimmer model which describes two coupled nonlinear passive Kerr cavities. Spiking dynamics appear due to the excitable nature of the system. In this context, excitable excursions in the phase space correspond to spikes in the temporal evolution of the field variables. In our case, excitability is mediated by the destruction of an oscillatory state in a global homoclinic bifurcation. In this type of excitability (known as type-I) the period of the oscillatory state diverges when approaching the bifurcation. Beyond this point, the system exhibits excitable dynamics under the application of suitable perturbations. We have also characterized the effect that additive Gaussian noise has on the spiking dynamics, showing that the system undergoes a coherence resonance for a given value of the noise strength.

Ultralow and anisotropic thermal conductivity in graphene phononic metamaterials

Phononic metamaterials based on the idea of phonon coherent resonance attract increasing research attention because of their unique properties. In this paper, we have studied the heat transport in graphene phononic metamaterials (GPMs, pillared graphene nanoribbons) using molecular dynamics simulations. The results show that, GPMs have lower thermal conductivities in the different in-plane directions and stronger anisotropy in thermal conductance, compared with graphene nanoribbons (GNRs). As the temperature decreases or the height and width of pillar increases, the GPM thermal conductivity in both directions decreases and the anisotropic ratio increases. The pillar-driven suppression of thermal conductivity along the periodic direction is attributed to the phonon localization and the local resonance leading to the flat bands and band gaps, while the reduction in thermal conductivity along the aperiodic direction is due to the phonon boundary scattering. The thermal anisotropy results from the anisotropic phonon relaxation times and the anisotropic contributions of low-frequency-phonons. Our findings reveal the phonon transport mechanisms of GPMs in different directions, and shed some light on the GPM potential for thermoelectric and directional heat management applications.

Optimal Resonances in Multiplex Neural Networks Driven by an STDP Learning Rule

In this paper, we numerically investigate two distinct phenomena, coherence resonance (CR) and self-induced stochastic resonance (SISR), in multiplex neural networks in the presence of spike-timing-dependent plasticity (STDP). The high degree of CR achieved in one layer network turns out to be more robust than that of SISR against variations in the network topology and the STDP parameters. This behavior is the opposite of the one presented by Yamakou and Jost (Phys. Rev. E 100, 022313, 2019), where SISR is more robust than CR against variations in the network parameters but in the absence of STDP. Moreover, the degree of SISR in one layer network increases with a decreasing (increasing) depression temporal window (potentiation adjusting rate) of STDP. However, the poor degree of SISR in one layer network can be significantly enhanced by multiplexing this layer with another one exhibiting a high degree of CR or SISR and suitable inter-layer STDP parameter values. In addition, for all inter-layer STDP parameter values, the enhancement strategy of SISR based on the occurrence of SISR outperforms the one based on CR. Finally, the optimal enhancement strategy of SISR based on the occurrence of SISR (CR) occurs via long-term potentiation (long-term depression) of the inter-layer synaptic weights.

Coherence resonance in paleoclimatic modeling

Through a unified mathematical framework, the stochastic behavior of three celebrated low-order lumped models, previously proposed for paleoclimate simulations, is considered. Due to the coherence resonance mechanism, the feedbacks between noise and the dynamical system reproduce the hallmark of the Pleistocene climate, i.e. the 100 ky pulsation, in a range of the model parameters that is unexpectedly wide and far from the original modeling setting. In this way, the issue of arbitrary coefficient tuning of lumped approaches in paleoclimatology can be partially bypassed. A stability analysis of the considered dynamical systems allowed the parameter space to be exploited, in order to separate the deterministic-dominated region from the stochastic-dominated region. Noise intensity is varied and the closeness in the parameter space to Hopf bifurcations and/or bistable conditions is investigated in order to understand what conditions make the models prone to coherence resonance with a 100-ky pulsation, with or without the forcing induced by varying astronomical parameters.

Magnetic coherence effects in the spectroscopy of transitions between energy levels with total angular momenta J = 1/2 and J = 1 using unidirectional waves

The physical processes that form the spectra of saturated absorption resonances at atomic transitions between energy levels with angular momenta J = 1/2 and J = 1 in the field of two unidirectional linearly polarised laser waves are studied analytically and numerically. It is shown that the specific features of the resonance spectra are formed in the Λ-schemes of transitions and manifest themselves in the form of narrow coherent structures – dips due to the magnetic coherence (optical orientation) of the transition levels induced by the optical fields. In this case, the energy levels of the lower state make the main contribution, and the contribution of the transfer of magnetic coherence from the sublevels of the upper state to the lower ones in the resonance amplitude manifests itself as an additive. Conditions are found under which the nonlinear resonance is exclusively coherent. The effect of the saturating wave field on the shape of coherent resonance structures is studied.

How noise can generate calcium spike-type oscillations in deterministic equilibrium modes.

Stochastic excitability of spiking oscillatory regimes in the calcium kinetics is studied on the basis of the Li-Rinzel conceptual model. The probabilistic mechanisms of the noise-induced generation of large-amplitude oscillations in parametric zones, where the original deterministic model has only stable equilibria, are investigated numerically and analytically. A parametric statistical description of interspike intervals is curried out and the phenomenon of coherence resonance is discussed. For the analytical study of the stochastic excitement, the confidence domain method using a stochastic sensitivity technique is applied. In this analysis, a key role of mutual arrangement of the confidence ellipses and separatrices detaching the sub- and supercritical regions is demonstrated. It is shown that in the Li-Rinzel model such separatrices are the stable manifolds of the saddle equilibria and the transient semiattractors.

Hopf and quasi-periodic Hopf bifurcations and deterministic coherence in coupled Duffing-Holmes and Van der Pol oscillators: the Arnol’d resonance web

A survey on coupled Van der Pol (VDP) and Duffing-Holmes (DH) oscillators, a model widely encountered in various branches of Physics and engineering is done. A bifurcation analysis of the model is presented when both unidirectional and mutual couplings are considered. It is found that stable, unstable and chaotic behaviors appear in the models. Using the method of charts of dynamics regimes in parameter planes, numerical study of the parameters space of the initial differential equations is done. Results from both approaches are compared and discussed. Features of the bifurcation picture are discussed when varying control parameters and analysis of slow-flow equations is presented. We show that the local bifurcation transition from an invariant one-torus (IT1) to an invariant two-torus (IT2) is caused by a Neimark-Saker (NS) bifurcation, also known as a one dimension-higher quasi-periodic Hopf (QH) bifurcation, these by analysing the graph of Lyapunov exponents. We observe that in the mutual coupling case, a complex structure generally-called Arnold’s resonance web phenomenon appears. Numerical simulations are compared to experimental measurements to illustrate the above behaviors. We also note the birth of coherence resonance in the slave oscillator for a certain coupling strength in the case of unidirectional coupling. We also analyze the effect of the coupling strength on the generalized synchronization between the master system and the slave system in the case of unidirectional coupling, through the concept of mutual false nearest neighbors. It allows us to understand when and how closeness in response space implies closeness in driving space.

A discrete Huber-Braun neuron model: from nodal properties to network performance.

The online version contains supplementary material available at 10.1007/s11571-022-09806-1.

Effects of correlated noises on binocular rivalry

Visual pathways are inherently stochastic and thus noisy. Such fluctuation is generally considered to be a nuisance, actually, it shows potential benefits to perceptual alteration. Here, we investigated binocular rivalry subjected to correlated noises (correlation between additive noise and multiplicative noise). Our numerical results reveal that: (i) Noise enhanced stability phenomenon appears for the correlated case, while vanishes for the uncorrelated case; (ii) Multiplicative noise intensity presents very limited impact on the perceptual alternation under some certain additive noise intensities; (iii) Coherence resonance takes place for negative correlation, while disappears for positive or non correlation; (iv) Imbalance of perceptual dominance, caused by the correlation strengthen difference between the eyes, weakens the perceptual stability, but it has beneficial effects for inducement of coherence resonance. These findings have the significant implication for a deeper understanding of rivalry and its relationship to binocular vision.PACS numbers: 02.50.-r, 05.40.-a, 87.10.-e

From Dynamic Superwettability to Ionic/Molecular Superfluidity.

Life systems present ultralow energy consumption in high-efficiency energy conversion, information transmission, and biosynthesis. The total energy intake of the human body is about 2000 kcal/day to maintain all of our activities, which is comparable to a power of ∼100 W. The energy required for the brain to work is equivalent to ∼20 W, and the rest of the energy (∼80 W) is used for other activities. All in vivo biosyntheses take place only at body temperature, which is much lower than that of in vitro reactions. To achieve these ultralow energy-consumption processes, there should be a kind of ultralow-resistivity matter transport in nanochannels (e.g., ionic and molecular channels), in which the directional collective motion of ions or molecules is a necessary condition rather than traditional Newton diffusion. The directional collective motion of ions and molecules is considered to be ionic/molecular superfluidity. The driving force of ionic/molecular superfluidity formation requires two necessary conditions: (1) Ions or molecules are confined at a certain distance (e.g., approximately twice Debye length (2λD) for ions or twice the van der Waals equilibrium distance (2d0) for molecules). (2) When the attractive potential energy (E0) is stronger than the thermal noise (kBTc), ionic/molecular superfluidity can be formed. The concept of ionic/molecular superfluidity will promote the understanding of energy conversion with ultralow energy consumption in biological systems. The swing of an eel's body generating electricity and cardiac resuscitation denote the conversion from mechanical energy to electrical energy, and mechanical modulation might result in a coherent resonance of ionic motion. The coherent resonance of Ca2+ in myocardium cells can induce a heartbeat, realizing the conversion from the electrical energy to the mechanical energy of a biological system. The macroscopic quantum state of ion channels is considered to be a carrier of neural information, and the environment field might play a significant role in regulating the macroscopic quantum states of various ion channels. In the biological ion channels system, the coupling of ion channels and their released photons might induce an environment wave which in turn regulates the ion oscillations in the channels to a coherent state. The states of decoherence and coherence might correspond to the states of sleep and action. We also demonstrated the decomposition of ATP to ADP released photons with a frequency of ∼34 THz, which could further drive DNA polymerization in the nanocavity of DNA polymerase. The photochemical (mid- and far-IR) reaction might be the driving force in high-efficiency biosynthesis. Quantized syntheses resonantly driven by multiple mid- and far-IR photons could be further designed in a tubular reactor with membranes of different microporous structures to achieve a high-efficiency synthesis with a low energy consumption. Finally, we point out that the Bose-Einstein condensate potentially widely exists. We expect that this Account will provide new ideas for the key problem in life science: how can life systems present ultralow energy consumption in high-efficiency energy conversion, information transmission, and biosynthesis?

Interlayer Connectivity Affects the Coherence Resonance and Population Activity Patterns in Two-Layered Networks of Excitatory and Inhibitory Neurons.

The firing patterns of neuronal populations often exhibit emergent collective oscillations, which can display substantial regularity even though the dynamics of individual elements is very stochastic. One of the many phenomena that is often studied in this context is coherence resonance, where additional noise leads to improved regularity of spiking activity in neurons. In this work, we investigate how the coherence resonance phenomenon manifests itself in populations of excitatory and inhibitory neurons. In our simulations, we use the coupled FitzHugh-Nagumo oscillators in the excitable regime and in the presence of neuronal noise. Formally, our model is based on the concept of a two-layered network, where one layer contains inhibitory neurons, the other excitatory neurons, and the interlayer connections represent heterotypic interactions. The neuronal activity is simulated in realistic coupling schemes in which neurons within each layer are connected with undirected connections, whereas neurons of different types are connected with directed interlayer connections. In this setting, we investigate how different neurophysiological determinants affect the coherence resonance. Specifically, we focus on the proportion of inhibitory neurons, the proportion of excitatory interlayer axons, and the architecture of interlayer connections between inhibitory and excitatory neurons. Our results reveal that the regularity of simulated neural activity can be increased by a stronger damping of the excitatory layer. This can be accomplished with a higher proportion of inhibitory neurons, a higher fraction of inhibitory interlayer axons, a stronger coupling between inhibitory axons, or by a heterogeneous configuration of interlayer connections. Our approach of modeling multilayered neuronal networks in combination with stochastic dynamics offers a novel perspective on how the neural architecture can affect neural information processing and provide possible applications in designing networks of artificial neural circuits to optimize their function via noise-induced phenomena.

Additive Noise-Induced System Evolution (ANISE)

Additive noise has been known for a long time to not change a systems stability. The discovery of stochastic and coherence resonance in nature and their analytical description has started to change this view in the last decades. The detailed studies of stochastic bifurcations in the last decades have also contributed to change the original view on the role of additive noise. The present work attempts to put these pieces of work in a broader context by proposing the research direction ANISE as a perspective in the research field. ANISE may embrace all studies that demonstrates how additive noise tunes a systems evolution beyond just scaling its magnitude. The article provides two perspective directions of research. The first perspective is the generalization of previous studies on the stationary state stability of a stochastic random network model subjected to additive noise. Here the noise induces novel stationary states. A second perspective is the application of subgrid-scale modeling in stochastic random network model. It is illustrated how numerical parameter estimation complements and extends subgrid-scale modeling and render it more powerful.

Coherence-resonance chimeras in coupled HR neurons with alpha-stable Lévy noise

Abstract In this paper, we have investigated the collective dynamical behaviors of a network of identical Hindmarsh–Rose neurons that are coupled under small-world schemes upon the addition of α-stable Lévy noise. According to the firing patterns of each neuron, we distinguish the neuronal network into spike state, burst state and spike-burst state coexistence of the neuron with both a spike firing pattern and a burst firing pattern. Moreover, the strength of the burst is proposed to identify the firing states of the system. Furthermore, an interesting phenomenon is observed that the system presents coherence resonance in time and chimera states in space, namely coherence-resonance chimeras (CRC). In addition, we show the influences of α-stable Lévy noise (noise intensity and stable parameter) and the small-world network (the rewiring probability) on the spike-burst state and CRC. We find that the stable parameter and noise intensity of the α-stable noise play a crucial role in determining the CRC and spike-burst state of the system.

Adaptive Stochastic Resonance for Bolt Looseness Identification Under Strong Noise Background

Abstract Nowadays, a large number of mechanical equipment working in harsh working environment will lead to strong background noise, which makes it difficult to extract feature information related to equipment fault. Bolt joint looseness inevitably occurs in engineering, which occupies a large proportion of all types of mechanical equipment faults. Therefore, it is quite difficult to extract the bolt looseness feature information. Based on this problem, a method based on subharmonic resonance and adaptive stochastic resonance (ASR) method is proposed to recognize whether the bolt is loose. First, a typical single bolted joint model is carried out dynamic analysis and numerical simulation, which verifies the specific conditions for the generation of subharmonic frequency related to bolt looseness. Then, a bolt looseness identification method based on ASR and coherence resonance (CR) is proposed. A quality factor index is defined, which is used to identify stochastic resonance (SR) and CR for bolt looseness identification. Finally, the effectiveness of this method is successfully verified by experiment, which effectively identifies bolt looseness under strong noise background.

White-noise-induced double coherence resonances in reduced Hodgkin-Huxley neuron model near subcritical Hopf bifurcation.

Coherence resonance (CR) describes a counterintuitive phenomenon in which the optimal oscillatory responses in nonlinear systems are shaped by a suitable noise amplitude. This phenomenon has been observed in neural systems. In this research, the generation of double coherence resonances (DCRs) due to white noise is investigated in a three-dimensional reduced Hodgkin-Huxley neuron model with multiple-timescale feature. We show that additive white noise can induce DCRs from the resting state near a subcritical Hopf bifurcation. The appearance of DCRs is related to the changes of the firing pattern aroused by the increases of the noise amplitude. The underlying dynamical mechanisms for the appearance of the DCRs and the changes of the firing pattern are interpreted using the phase space analysis and the dynamics of the stable focus-node near the subcritical Hopf bifurcation. We find that the multiple-timescale dynamics is essential for generating the DCRs and different firing patterns. The results not only present a case in which noise can induce DCRs near a Hopf bifurcation but also provide its dynamical mechanism, which enriches the phenomena in nonlinear dynamics and provides further understanding on the roles of noise in neural systems with multiple-timescale feature.

Stochastic Bifurcations and Excitement in the ZS-Model of a Thermochemical Reaction

The Zeldovich–Semenov model of the continuous stirred tank reactor with parametric random disturbances in temperature is considered. We study a phenomenon of noise-induced transformation of the equilibrium mode into the mixed-mode oscillatory stochastic regime with alternations between small and large amplitudes. In the parametric analysis of the stochastic excitement, we use the analytical method of confidence domains based on the stochastic sensitivity technique. Analyzing a mutual arrangement of the confidence ellipses and separatrices, we estimate the critical intensity of the noise that causes the excitation. The phenomena of stochastic P-bifurcations and coherence resonances are discovered and studied by probability density functions and the statistics of interspike intervals.

The nonlinear mechanisms underlying the various stochastic dynamics evoked from different bursting patterns in a neuronal model

The stochastic dynamics such as coherence resonance (CR) and anti-CR show that noise plays constructive roles in the nervous system, which are always evoked from the resting-state or the nearby coexisting behaviors instead of bursting. In the present paper, various stochastic dynamics are evoked from different bursting patterns and the corresponding nonlinear mechanisms are presented. Anti-CR, transition from CR to anti-CR, and non-CR characterized by the coefficient of variation (CV) of interspike intervals are induced by noise from the “Homoclinic/Homoclinic” bursting, “Fold/Big Homoclinic” bursting with quiescent state, and “Fold/Big Homoclinic” bursting with subthreshold oscillations, respectively, which are determined by different stochastic transition regularities between the burst/spike and quiescent state/subthreshold oscillations within the stochastic bursting. The more transitions from spike to subthreshold oscillations to form long duration of subthreshold oscillations evoked by noise near a homoclinic orbit bifurcation, noise-induced more transition from quiescent state to spikes prior to a fold bifurcation, and frequent transitions between spikes and quiescent state are the dominant dynamical mechanisms for the anti-CR, CR, and non-CR, respectively. More detailed causes for the three different stochastic dynamics can be acquired through building relationships between the transitions and the different nonlinear dynamics of the fast subsystem such as the bifurcations, coexisting behaviors, attraction domains, and the distance between the trajectory of bursting and the bifurcation point or border between attraction domains. The comprehensive viewpoint and nonlinear mechanism for the various stochastic dynamics of the different bursting patterns extend the occurrence conditions for the CR or anti-CR and presents modulation measures and potential functions of bursting neurons receiving synaptic noise.

Deterministic coherence resonance analysis of coupled chaotic oscillators: fractional approach

Recently, the stabilization of chaos by chaos has attracted the attention of researchers. A small deviation between the natural frequencies of unidirectionally coupled chaotic oscillators can cause the emerge of a coherence resonance in the slave oscillator for a given coupling strength. In this work, we investigate the phenomenon of coherence resonance for a coupled Rössler system under the influence of fractional operators in the frequency response of the slave oscillator. Based on the analysis of the fractional Rössler system, we determine a range of fractional orders in which the system retains its instability, and an analysis of the frequency response of the system to changes in natural frequency is developed. Finally, the frequency response of the slave system to changes in the fractional derivative order, the natural frequency of the master system, and the coupling strength is analyzed, and how these changes promote the occurrence of coherence resonance is examined.

Characterization of overlapping betatron resonances above the phase advance of 90° per cell

The space-charge-induced resonance band just above the betatron phase advance of 90\ifmmode^\circ\else\textdegree\fi{} per cell is of great practical importance. The instability is closely related to the linear collective mode and can thus give rise to severe emittance growth at high beam density. In a circular machine, this type of second-order resonance occurs not only at half-integer tunes but also near quarter-integer tunes, depending on the lattice superperiodicity. Self-consistent numerical simulations are carried out to elucidate the resonance feature above the 90\ifmmode^\circ\else\textdegree\fi{} cell tune. The present results suggest the existence of three different resonance mechanisms working there; namely, the fourth-order incoherent resonance in the beam tail, the second-order and fourth-order coherent resonances in the beam core. It is reconfirmed that no serious emittance growth occurs even if particles deep inside the core satisfy the incoherent resonance condition. The recently proposed stop-band diagram, free from the concept of incoherent tune spread, appears to be consistent with the numerical observations.