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Characterizing the brain’s dynamic pattern of response to an input in electroencephalography (EEG) is not a trivial task due to the entanglement of the complex spontaneous brain activity. In this context, the brain’s response can be defined as (1) the additional neural activity components generated after the input or (2) the changes in the ongoing spontaneous activities induced by the input. Moreover, the response can be manifested in multiple features. Three commonly studied examples of features are (1) transient temporal waveform, (2) time–frequency representation, and (3) phase dynamics. The most extensively used method of average event-related potentials (ERPs) captures the first one, while the latter two and other more complex features are attracting increasing attention. However, there has not been much work providing a systematic illustration and guidance for how to effectively exploit multifaceted features in neural cognitive research. Based on a visual oddball ERPs dataset with 200 participants, this work demonstrates how the information from the above-mentioned features are complementary to each other and how they can be integrated based on stereotypical neural-network-based machine learning approaches to better exploit neural dynamic information in basic and applied cognitive research.

The phase reduction approach has manifested its efficacy in investigating synchronization behaviors in limit-cycle oscillators. However, spatial distributions of the phase value on the limit cycle may lead to illusions of synchronizations for oscillators close to bifurcations. In this paper, we compared the phase sensitivity function in the spatial domain and time domain for oscillators close to saddle-node homoclinic (SNH) bifurcation, also known as saddle-node bifurcation on an invariant circle. It was found that the phase sensitivity function in the spatial domain can show the phase accumulation feature on the limit cycle, which can be ignored in the phase sensitivity function in the time domain. As an example, the synchronization distributions of uncoupled SNH oscillators driven by common and independent noises were investigated, where the space-dependent coupling function was considered on common noise. These results shed some light on the phase dynamics of oscillators close to bifurcations.

Light is the primary signal that calibrates circadian neural circuits and thus coordinates daily physiological and behavioral rhythms with solar entrainment cues. Drosophila and mammalian circadian circuits consist of diverse populations of cellular oscillators that exhibit a wide range of dynamic light responses, periods, phases, and degrees of synchrony. How heterogeneous circadian circuits can generate robust physiological rhythms while remaining flexible enough to respond to synchronizing stimuli has long remained enigmatic. Cryptochrome is a short-wavelength photoreceptor that is endogenously expressed in approximately half of Drosophila circadian neurons. In a previous study, physiological light response was measured using real-time bioluminescence recordings in Drosophila whole-brain explants, which remain intrinsically light-sensitive. Here we apply analysis of real-time bioluminescence experimental data to show detailed dynamic ensemble representations of whole circadian circuit light entrainment at single neuron resolution. Organotypic whole-brain explants were either maintained in constant darkness (DD) for 6 days or exposed to a phase-advancing light pulse on the second day. We find that stronger circadian oscillators support robust overall circuit rhythmicity in DD, whereas weaker oscillators can be pushed toward transient desynchrony and damped amplitude to facilitate a new state of phase-shifted network synchrony. Additionally, we use mathematical modeling to examine how a network composed of distinct oscillator types can give rise to complex dynamic signatures in DD conditions and in response to simulated light pulses. Simulations suggest that complementary coupling mechanisms and a combination of strong and weak oscillators may enable a robust yet flexible circadian network that promotes both synchrony and entrainment. A more complete understanding of how the properties of oscillators and their signaling mechanisms facilitate their distinct roles in light entrainment may allow us to direct and augment the circadian system to speed recovery from jet lag, shift work, and seasonal affective disorder.

A dynamic system showing stable rhythmic activity can be represented by the dynamics of phase oscillators. This would provide a useful mathematical framework through which one can understand the system's dynamic properties. A recent study proposed a Bayesian approach capable of extracting the underlying phase dynamics directly from time-series data of a system showing rhythmic activity. Here we extended this method to spike data that otherwise provide only limited phase information. To determine how this method performs with spike data, we applied it to simulated spike data generated by a realistic neuronal network model. We then compared the estimated dynamics obtained based on the spike data with the dynamics theoretically derived from the model. The method successfully extracted the modeled phase dynamics, particularly the interaction function, when the amount of available data was sufficiently large. Furthermore, the method was able to infer synaptic connections based on the estimated interaction function. Thus, the method was found to be applicable to spike data and practical for understanding the dynamic properties of rhythmic neural systems.

Characterizing the brain's dynamic pattern of response to an input in electroencephalography (EEG) is not a trivial task due to the entanglement of the complex spontaneous brain activity. In this context, the brain's response can be defined as (1) the additional neural activity components generated after the input or (2) the changes in the ongoing spontaneous activities induced by the input. Moreover, the response can be manifested in multiple features. Three commonly studied examples of features are (1) transient temporal waveform, (2) time–frequency representation, and (3) phase dynamics. The most extensively used method of average event-related potentials (ERPs) captures the first one, while the latter two and other more complex features are attracting increasing attention. However, there has not been much work providing a systematic illustration and guidance for how to effectively exploit multifaceted features in neural cognitive research. Based on a visual oddball ERPs dataset with 200 participants, this work demonstrates how the information from the above-mentioned features are complementary to each other and how they can be integrated based on stereotypical neural-network-based machine learning approaches to better exploit neural dynamic information in basic and applied cognitive research. [ABSTRACT FROM AUTHOR]

We consider networks of coupled phase oscillators of different complexity: Kuramoto–Daido-type networks, generalized Winfree networks, and hypernetworks with triple interactions. For these setups an inverse problem of reconstruction of the network connections and of the coupling function from the observations of the phase dynamics is addressed. We show how a reconstruction based on the minimization of the squared error can be implemented in all these cases. Examples include random networks with full disorder both in the connections and in the coupling functions, as well as networks where the coupling functions are taken from experimental data of electrochemical oscillators. The method can be directly applied to asynchronous dynamics of units, while in the case of synchrony, additional phase resettings are necessary for reconstruction. [ABSTRACT FROM AUTHOR]

The phase reduction approach has manifested its efficacy in investigating synchronization behaviors in limit-cycle oscillators. However, spatial distributions of the phase value on the limit cycle may lead to illusions of synchronizations for oscillators close to bifurcations. In this paper, we compared the phase sensitivity function in the spatial domain and time domain for oscillators close to saddle-node homoclinic (SNH) bifurcation, also known as saddle-node bifurcation on an invariant circle. It was found that the phase sensitivity function in the spatial domain can show the phase accumulation feature on the limit cycle, which can be ignored in the phase sensitivity function in the time domain. As an example, the synchronization distributions of uncoupled SNH oscillators driven by common and independent noises were investigated, where the space-dependent coupling function was considered on common noise. These results shed some light on the phase dynamics of oscillators close to bifurcations. [ABSTRACT FROM AUTHOR]

Although Mn-Ga alloys are discussed as novel permanent magnetic materials, there are several drawbacks, including the high price of Ga and the yet too small saturation magnetization to name a few. We used several guidelines to motivate the replacement of Ga by Sn to tackle these issues and explored the phase formation, structural and magnetic properties of a Mn 2.6 Ga 1− x Sn x alloy series. The structure of Sn-rich samples is dominated by the corresponding hexagonal and orthorhombic phases, while the structure of Ga-rich samples shows additional contributions from the tetragonal DO 22 structure. However, formation of the tetragonal phase happens only upon an appropriate annealing procedure. In contrast to the discussion in the literature, our experiments do not hint on the tetragonal DO 22 structure being metastable, but rather indicate the DO 22 structure being an equilibrium phase. In general, the experimentally found phase fractions impact on the magnetic properties and hard magnetic properties are downgraded very rapidly even if only a small amount of Ga is substituted by Sn. This indicates that the DO 22 phase found only in the Ga-rich samples is indeed the one which is most relevant for realization of high magnetic anisotropy. [ABSTRACT FROM AUTHOR]

High critical temperature superconductors (HTS) based devices can have impact in the study of the phase dynamics of Josephson junctions (JJs) thanks to the wide range of junction parameters they offer and to their unconventional properties. Measurements of current-voltage characteristics and of switching current distributions constitute a direct way to classify different regimes of the phase dynamics and of the transport, also in nontrivial case of the moderately damped regime (MDR). MDR is going to be more and more common in JJs with advances in nanopatterning superconductors and synthesizing novel hybrid systems. Distinctive signatures of macroscopic quantum tunneling and of thermal activation in presence of different tunable levels of dissipation have been detected in YBCO grain boundary JJs. Experimental data are supported by Monte Carlo simulations of the phase dynamics, in a wide range of temperatures and dissipation levels. This allows us to quantify dissipation in the MDR and partially reconstruct a phase diagram as guideline for a wide range of moderately damped systems. [ABSTRACT FROM AUTHOR]

A novel structural dynamic model for free standing hybrid riser (FSHR) is established based on the absolute nodal coordinate formulation (ANCF) in the present study. The position and slope coordinates are used in global framework to avoid coordinate transformation, and an accurate geometric relationship is introduced to describe geometric nonlinearity. The current loads on the risers and buoyancy can are simulated by Morrison equation and wake oscillator, respectively. After case validations, the vortex-induced motion (VIM) regimes of the buoyancy can and the phase dynamics of the riser and jumper in a FSHR system, subjected to the ocean current and vessel motion, is numerically investigated. It is found that the VIM of the buoyancy can experiences multiple motion switches among the periodic, quasiperiodic, multiple periodic, transition I and transition II regimes under different vessel motions. The y -motion of the jumper and both x - and y -motions of the riser present the phase trapping phenomenon along the structures. The phase trapping and locking, phase drifting and slipping, and other states are observed for x -motion of the jumper, which form a shape of "fish head" with opening mouth towards lower amplitude or higher period of vessel motion in regime map. • A novel structural dynamic model for FSHR system is established based on the ANCF. • Periodic, quasiperiodic, multiple periodic, transition I and II regimes of VIM are found under different vessel motions. • Three transition and multiple periodic bands are interspersed in the quasiperiodic regime of VIM. • The phase trapping and locking, drifting and slipping, and other states are captured for in-line motion along the jumper. • The phase dynamics of the jumper form a shape of "fish head" in the regime map. [ABSTRACT FROM AUTHOR]

The description of patterns in nonequilibrium systems is a fascinating subject. It becomes somewhat untractable if one insists to keep the original equations in their complete form, as the Oberbeck–Boussinesq equations for instance in Rayleigh–Be´nard convection. Various reduction scheme have been imagined, the ultimate one being the phase picture. I examine a simple version of the phase equation, relevant for systems of travelling rolls or for distributed self-oscillations. The boundary effects limit the ability of this phase to drift freely and yields a well-defined space structure, which can be analyzed in two different limits. [Copyright &y& Elsevier]

In this work, we investigate the dynamics of vortex-induced vibration of an elastically mounted cylinder with very low values of mass and damping. We use two methods to investigate this canonical problem: first we calculate the instantaneous phase between the cylinder motion and the fluid forcing; second we decompose the total hydrodynamic force into drag and lift components that act along and normal to, respectively, the instantaneous effective angle of attack. We focus on the phase dynamics in the large-amplitude–response range, consisting of the initial, upper and lower "branches" of response. The instantaneous phase between the transverse force and displacement shows repeated phase slips separating periods of constant, or continuous-drifting, phase in the second half of the upper branch. The phase between the lift component and displacement shows strong phase locking throughout the large-amplitude range – the average phase varies linearly with the primary frequency – however the modulation of this phase is largest in the second half of the upper branch. These observations suggest that the large-amplitude–response dynamics is driven by two distinct limit cycles – one that is stable over a very small range of reduced velocity at the beginning of the upper branch, and another that consists of the lower branch. The chaotic oscillation between them – the majority of the upper branch – occurs when neither limit cycle is stable. The transition between the upper and lower branches is marked by intermittent switching with epochs of time where different states exist at a constant reduced velocity. These different states are clearly apparent in the phase between the lift and displacement, illustrating the utility of the force decomposition employed. The decomposed force measurements also show that the drag component acts as a damping factor whereas the lift component provides the necessary fluid excitation for free vibration to be sustained. [ABSTRACT FROM AUTHOR]

A dynamic system showing stable rhythmic activity can be represented by the dynamics of phase oscillators. This would provide a useful mathematical framework through which one can understand the system's dynamic properties. A recent study proposed a Bayesian approach capable of extracting the underlying phase dynamics directly from time-series data of a system showing rhythmic activity. Here we extended this method to spike data that otherwise provide only limited phase information. To determine how this method performs with spike data, we applied it to simulated spike data generated by a realistic neuronal network model. We then compared the estimated dynamics obtained based on the spike data with the dynamics theoretically derived from the model. The method successfully extracted the modeled phase dynamics, particularly the interaction function, when the amount of available data was sufficiently large. Furthermore, the method was able to infer synaptic connections based on the estimated interaction function. Thus, the method was found to be applicable to spike data and practical for understanding the dynamic properties of rhythmic neural systems. [ABSTRACT FROM AUTHOR]

The effect of pumping methods on the gain and phase dynamics of quantum-dot vertical cavity semiconductor optical amplifier is investigated. The gain and phase recovery time is considered at the ground state transition wavelength. By including the effect of the excited state and wetting layer on the refractive index change, it is shown that under electrical pumping, the better gain dynamics is achieved compared to the optical pumping scheme. However, the phase recovery time can be accelerated by optical pumping. These behaviors result from the different mechanisms of population inversion in these two pumping methods. [ABSTRACT FROM PUBLISHER]

We describe the phase dynamics of a timing extraction system based on direct optical injection locking of a multifrequency oscillator employing an InGaAs/InP heterojunction bipolar phototransistor. We present a general model for the locking range, jitter transfer function, and output phase noise. The model is confirmed by a series of locking experiments. We consider first fundamental timing extraction, that is, a 10-GHz oscillator extracting the clock from a 10-Gbit/s data stream. Second, we address superharmonic timing extraction where 40-Gbit/s data lock the fourth harmonic of the 10-GHz oscillator. In the superharmonic timing extraction case, a clock is extracted at 40 GHz as well as its subharmonics at 10, 20, and 30 GHz. [ABSTRACT FROM PUBLISHER]

This paper studies the effects of distributed-delay coupling on the dynamics in a system of non-identical coupled Stuart-Landau oscillators. For uniform and gamma delay distribution kernels, the conditions for amplitude death are obtained in terms of average frequency, frequency detuning and the parameters of the coupling, including coupling strength and phase, as well as the mean time delay and the width of the delay distribution. To gain further insights into the dynamics inside amplitude death regions, the eigenvalues of the corresponding characteristic equations are computed numerically. Oscillatory dynamics of the system is also investigated, using amplitude and phase representation. Various branches of phase-locked solutions are identified, and their stability is analysed for different types of delay distributions. [ABSTRACT FROM AUTHOR]

In this study, a numerical analysis is carried out to investigate the coupled behaviour of a TLP (tension leg platform) -TAD (tender-assisted drilling) system under a series of regular waves in surge direction. The numerical model is established in the time domain considering the nonlinear characteristics of the mooring systems and the hydrodynamic interference. After the case validations, the effects of the wave periods and amplitudes on the nonlinear dynamic characteristics of the surge motions are investigated in detail. Then, the observed nonlinear dynamic characteristics are interpreted in detail through the existing theory of phase dynamics. The surge motions of the coupled system can show multiperiod nonlinear characteristics under regular waves in certain wave periods. Three forms of phase dynamic characteristics: phase locking, phase trapping, and phase drifting and slipping are observed in the surge motions of the tender-assisted drilling operation system. [ABSTRACT FROM AUTHOR]

We develop a technique for the multivariate data analysis of perturbed self-sustained oscillators. The approach is based on the reconstruction of the phase dynamics model from observations and on a subsequent exploration of this model. For the system, driven by several inputs, we suggest a dynamical disentanglement procedure, allowing us to reconstruct the variability of the system's output that is due to a particular observed input, or, alternatively, to reconstruct the variability which is caused by all the inputs except for the observed one. We focus on the application of the method to the vagal component of the heart rate variability caused by a respiratory influence. We develop an algorithm that extracts purely respiratoryrelated variability, using a respiratory trace and times of R-peaks in the electrocardiogram. The algorithm can be applied to other systems where the observed bivariate data can be represented as a point process and a slow continuous signal, e.g. for the analysis of neuronal spiking. [ABSTRACT FROM AUTHOR]

Abstract Modeling and interpreting (partial) synchronous neural activity can be a challenge. We illustrate this by deriving the phase dynamics of two seminal neural mass models: the Wilson-Cowan firing rate model and the voltage-based Freeman model. We established that the phase dynamics of these models differed qualitatively due to an attractive coupling in the first and a repulsive coupling in the latter. Using empirical structural connectivity matrices, we determined that the two dynamics cover the functional connectivity observed in resting state activity. We further searched for two pivotal dynamical features that have been reported in many experimental studies: (1) a partial phase synchrony with a possibility of a transition towards either a desynchronized or a (fully) synchronized state; (2) long-term autocorrelations indicative of a scale-free temporal dynamics of phase synchronization. Only the Freeman phase model exhibited scale-free behavior. Its repulsive coupling, however, let the individual phases disperse and did not allow for a transition into a synchronized state. The Wilson-Cowan phase model, by contrast, could switch into a (partially) synchronized state, but it did not generate long-term correlations although being located close to the onset of synchronization, i.e. in its critical regime. That is, the phase-reduced models can display one of the two dynamical features, but not both. Highlights • Networks of neural masses are reduced to phase oscillator models. • Freeman- and Wilson-Cowan-based phase models can resemble empirically observed functional connectivity. • Neither a network of Freeman nor of Wilson-Cowan phase models can. • Capture both partial synchronization and scale-free temporal correlations. [ABSTRACT FROM AUTHOR]

The phase dynamics of two phase wavetrains in the coupled non-linear Schrödinger (NLS) equations are investigated as an example of the dispersion arising from singular wave action. It is shown that when the wavetrain becomes singular, there is a reduction from coupled NLS to a scalar Korteweg–de Vries (KdV) equation, and if there is a further degeneracy the scalar two-way Boussinesq emerges. This is the first such derivation of the two-way Boussinesq reduction in this setting. A novelty in the theory is that the coefficients in the resulting equations are determined from properties of the wavetrain and underlying conservation laws. This theory generalizes the reduction from a single defocussing NLS equation to the KdV equation, and introduces Boussinesq dynamics to finite amplitude states in this family. A discussion of the effect of the phase dynamics on the wavetrain solution shows that the reductions provide an insight into a mechanism for the bifurcation of periodic wavetrains to dark and bright solitary waves. [ABSTRACT FROM AUTHOR]

We study a learning and recalling model of phase patterns in a two- or three-coupled BVP oscillators system with a time delay δ. The coupling strengths are modulated by the Hebbian learning rule. Assuming the first-order approximation, we calculate the optimal condition of δ for exact recall by applying the phase dynamics theory. When α = 0, where α represents the coupling from activator to inhibitor, the correlation between the learning and the retrieval phase depends on δ. When α = 1, exact recall is achieved independent of δ. The results can be explained by the phase dynamics theory. [ABSTRACT FROM AUTHOR]

A ferromagnetic Josephson junction (JJ) represents a special class of hybrid system where different ordered phases meet and generate novel physics. In this work we report on the transport measurements of underdamped ferromagnetic NbN/GdN/NbN JJs at low temperatures. In these junctions the ferromagnetic insulator gadolinium nitride barrier generates spin-filtering properties and a dominant second harmonic component in the current-phase relation. These features make spin filter junctions quite interesting also in terms of fundamental studies on phase dynamics and dissipation. We discuss the fingerprints of spin filter JJs, through complementary transport measurements, and their implications on the phase dynamics, through standard measurements of switching current distributions. NbN/GdN/NbN JJs, where spin filter properties can be controllably tuned along with the critical current density (J c ), turn to be a very relevant term of reference to understand phase dynamics and dissipation in an enlarged class of JJs, not necessarily falling in the standard tunnel limit characterized by low J c values. [ABSTRACT FROM AUTHOR]

We consider the dynamics of a lattice of phase oscillators with a nearest-neighbor coupling. The clustering hierarchy is described for the case of linear distribution of natural frequencies. We demonstrate that for small couplings prior to the appearance of the first cluster the dynamics is quasi-Hamiltonian: the phase volume is conserved in average, and the spectrum of the Lyapunov exponents is symmetric. We explain this unexpected for a dissipative system phenomenon using the concept of reversibility. We show that for a certain coupling a smooth transition from the quasi-Hamiltonian to the dissipative dynamics occurs, which is a novel type of chaos–chaos transition. [Copyright &y& Elsevier]

Macroscopic oscillations in the brain are involved in various cognitive and physiological processes, yet their precise function is not completely understood. Communication through coherence (CTC) theory proposes that these rhythmic electrical patterns might serve to regulate the information flow between neural populations. Thus, to communicate effectively, neural populations must synchronize their oscillatory activity, ensuring that input volleys from the presynaptic population reach the postsynaptic one at its maximum phase of excitability. We consider an Excitatory–Inhibitory (E–I) network whose macroscopic activity is described by an exact mean-field model. The E–I network receives periodic inputs from either one or two external sources, for which effective communication will not be achieved in the absence of control. We explore strategies based on optimal control theory for phase–amplitude dynamics to design a periodic control that sets the target population in the optimal phase to synchronize its activity with a specific presynaptic input signal and establish communication. The control mechanism resembles the role of a higher cortical area in the context of selective attention. To design the control, we use the phase–amplitude reduction of a limit cycle and leverage recent developments in this field in order to find the most effective control strategy regarding a defined cost function. Furthermore, we present results that guarantee the local controllability of the system close to the limit cycle. • Optimal-control strategies provide controls that suitably adjust the dynamics for enhanced communication. • Controlled synchronization is decisive for effective communication in mean-field models of E–I networks. • Using phase–amplitude description, optimal periodic controls minimally alter the oscillation, while enhance communication. [ABSTRACT FROM AUTHOR]

Building on semiological research (i.e., the study of signs and symbols of all kinds) investigating the use of symbols in cinematic portrayals of travel behavior, this article describes a phase dynamics theory of epiphany travel behavior. Core propositions of the theory include (1) epiphany travel behavior and storytelling about such travel includes identifiable phases: prequel, awakening, journey, catharsis, and post-journey storytelling and reinterpreting; (2) world and personal blocks occur; (3) during the journey the protagonist recognizes the need for help and experiences help from key facilitators to reach desired physical locations and other goal objects; and (4) experiencing an archetypal force is an outcome of the journey. Such theory building provides a gestalt view and understanding of epiphany travel behavior. [ABSTRACT FROM AUTHOR]

Abstract: We study the phase dynamics of a chain of autonomous, self-sustained, dispersively coupled oscillators. In the quasicontinuum limit the basic discrete model reduces to a Korteveg–de Vries-like equation, but with a nonlinear dispersion. The system supports compactons–solitary waves with a compact support–and kovatons–compact formations of glued together kink–antikink pairs that propagate with a unique speed, but may assume an arbitrary width. We demonstrate that lattice solitary waves, though not exactly compact, have tails which decay at a superexponential rate. They are robust and collide nearly elastically and together with wave sources are the building blocks of the dynamics that emerges from typical initial conditions. In finite lattices, after a long time, the dynamics becomes chaotic. Numerical studies of the complex Ginzburg–Landau lattice show that the non-dispersive coupling causes a damping and deceleration, or growth and acceleration, of compactons. A simple perturbation method is applied to study these effects. [Copyright &y& Elsevier]

Experimental and theoretical switching windows in an interferometric configuration with a gain-transparent semiconductor optical amplifier in a loop mirror (GT-SLALOM) are investigated. The amplifier gain and phase dynamics are analyzed in detail. For the gain dynamics, experimental and theoretical pump-probe results are presented. The phase dynamics is investigated theoretically. It is shown that the insertion of an optimized nonreciprocal phase shift in the GT-SLALOM configuration increases the contrast of the switching windows and, thus, improves the performance of the switch for demultiplexing applications. The influence of an asymmetric coupling ratio of the 3-dB input/output coupler on the switching contrast is also discussed [ABSTRACT FROM PUBLISHER]

A foremost challenge in modern network science is the inverse problem of reconstruction (inference) of coupling equations and network topology from the measurements of the network dynamics. Of particular interest are the methods that can operate on real (empirical) data without interfering with the system. One such earlier attempt (Tokuda et al. 2007 Phys. Rev. Lett. 99, 064101. (doi:10.1103/PhysRevLett.99.064101)) was a method suited for general limit-cycle oscillators, yielding both oscillators' natural frequencies and coupling functions between them (phase equations) from empirically measured time series. The present paper reviews the above method in a way comprehensive to domain-scientists other than physics. It also presents applications of the method to (i) detection of the network connectivity, (ii) inference of the phase sensitivity function, (iii) approximation of the interaction among phase-coherent chaotic oscillators, and (iv) experimental data from a forced Van der Pol electric circuit. This reaffirms the range of applicability of the method for reconstructing coupling functions and makes it accessible to a much wider scientific community. [ABSTRACT FROM AUTHOR]

• Joule heating phenomenon is incorporated in the AC Josephson effect. • The phase and temperature dynamic states are discussed for various parameters. • Device state diagrams are realized for Josephson weak-link – shunted and unshunted. • A useful thermal model as a guide for the experiments with weak-link-based devices. Superconducting weak-link (WL), behaving like a Josephson junction (JJ), is fundamental to many superconducting devices such as nanoSQUIDs, single-photon detectors, and bolometers. The interplay between unique nonlinear dynamics and inevitable Joule heating in a JJ leads to new characteristics. Here, we report a time-dependent model incorporating thermal effect in the AC Josephson regime for a Josephson WL shunted by a resistor together with an inductor to investigate the dynamics as well as the resulting current-voltage characteristics. We find that the dynamic regime where phase and temperature oscillate simply widens due to a pure resistive shunt. However, a significant inductive time-scale in the shunt loop, competing with the thermal time-scale, introduces high-frequency relaxation oscillations in the dynamic regime. Based on numerical analysis, we present state diagrams for different parameter regimes. Our model is a guide for better controlling the parameters in the experiments of WL-based devices. [ABSTRACT FROM AUTHOR]

Circadian rhythms are internal processes repeating approximately every 24 hours in living organisms. The dominant circadian pacemaker is synchronized to the environmental light-dark cycle. Other circadian pacemakers, which can have noncanonical circadian mechanisms, are revealed by arousing stimuli, such as scheduled feeding, palatable meals and running wheel access, or methamphetamine administration. Organisms also have ultradian rhythms, which have periods shorter than circadian rhythms. However, the biological mechanism, origin, and functional significance of ultradian rhythms are not well-elucidated. The dominant circadian rhythm often masks ultradian rhythms; therefore, we disabled the canonical circadian clock of mice by knocking out Per1/2/3 genes, where Per1 and Per2 are essential components of the mammalian light-sensitive circadian mechanism. Furthermore, we recorded wheel-running activity every minute under constant darkness for 272 days. We then investigated rhythmic components in the absence of external influences, applying unique multiscale time-resolved methods to analyze the oscillatory dynamics with time-varying frequencies. We found four rhythmic components with periods of ∼17 h, ∼8 h, ∼4 h, and ∼20 min. When the ∼17-h rhythm was prominent, the ∼8-h rhythm was of low amplitude. This phenomenon occurred periodically approximately every 2-3 weeks. We found that the ∼4-h and ∼20-min rhythms were harmonics of the ∼8-h rhythm. Coupling analysis of the ridge-extracted instantaneous frequencies revealed strong and stable phase coupling from the slower oscillations (∼17, ∼8, and ∼4 h) to the faster oscillations (∼20 min), and weak and less stable phase coupling in the reverse direction and between the slower oscillations. Together, this study elucidated the relationship between the oscillators in the absence of the canonical circadian clock, which is critical for understanding their functional significance. These studies are essential as disruption of circadian rhythms contributes to diseases, such as cancer and obesity, as well as mood disorders. [ABSTRACT FROM AUTHOR]

A model is used to analyze the gain and phase dynamics of a semiconductor optical amplifier with a carrier reservoir (CR-SOA). Coupled rate equations are solved numerically. Due to the fast transition of carriers from the carrier reservoir layer to the active region, the CR-SOA is shown to have faster gain and phase response than a regular SOA. Increasing the injection current will also decrease the response times. [ABSTRACT FROM PUBLISHER]

Abstract: Large-amplitude oscillations of macroscopic neuronal signals, such as local field potentials and electroencephalography or magnetoencephalography signals, are commonly considered as being generated by a population of mutually synchronized neurons. In a computational study in generic networks of phase oscillators and bursting neurons, however, we show that this common belief may be wrong if the neuronal population receives an external rhythmic input. The latter may stem from another neuronal population or an external, e.g., sensory or electrical, source. In that case the population field potential may be entrained by the rhythmic input, whereas the individual neurons are phase desynchronized both mutually and with their field potential. Intriguingly, the corresponding large-amplitude oscillations of the population mean field are generated by pairwise desynchronized neurons oscillating at frequencies shifted far away from the frequency of the macroscopic field potential. [Copyright &y& Elsevier]

Abstract: Based on the model system undergoing phase separation and chemical reactions, we investigate the dynamics of propagating dissipative waves under external forcing which is periodic both in space and time. A phase diagram for the entrained and non-entrained states under the external forcing is obtained numerically. Theoretical analysis in terms of phase description of the traveling waves is carried out to show that the transition between the entrained and the non-entrained states by changing the external frequency occurs either through a saddle–node bifurcation or through a Hopf bifurcation and that these two bifurcation lines are connected at a Bogdanov–Takens bifurcation point. [Copyright &y& Elsevier]

Abstract: The application of methods drawn from nonlinear and stochastic dynamics to the analysis of cardiovascular time series is reviewed, with particular reference to the identification of changes associated with ageing. The natural variability of the heart rate (HRV) is considered in detail, including the respiratory sinus arrhythmia (RSA) corresponding to modulation of the instantaneous cardiac frequency by the rhythm of respiration. HRV has been intensively studied using traditional spectral analyses, e.g. by Fourier transform or autoregressive methods, and, because of its complexity, has been used as a paradigm for testing several proposed new methods of complexity analysis. These methods are reviewed. The application of time–frequency methods to HRV is considered, including in particular the wavelet transform which can resolve the time-dependent spectral content of HRV. Attention is focused on the cardio-respiratory interaction by introduction of the respiratory frequency variability signal (RFV), which can be acquired simultaneously with HRV by use of a respiratory effort transducer. Current methods for the analysis of interacting oscillators are reviewed and applied to cardio-respiratory data, including those for the quantification of synchronization and direction of coupling. These reveal the effect of ageing on the cardio-respiratory interaction through changes in the mutual modulation of the instantaneous cardiac and respiratory frequencies. Analyses of blood flow signals recorded with laser Doppler flowmetry are reviewed and related to the current understanding of how endothelial-dependent oscillations evolve with age: the inner lining of the vessels (the endothelium) is shown to be of crucial importance to the emerging picture. It is concluded that analyses of the complex and nonlinear dynamics of the cardiovascular system can illuminate the mechanisms of blood circulation, and that the heart, the lungs and the vascular system function as a single entity in dynamical terms. Clear evidence is found for dynamical ageing. [Copyright &y& Elsevier]

Abstract: Objective: This study examines the utility of new measures of event-related spatio-temporal waves in the EEG as a marker of ADHD, previously shown to be closely related to the P3 ERP in an adult sample. Methods: Wave activity in the EEG was assessed during both an auditory Oddball and a visual continuous performance task (CPT) for an ADHD group ranging in age from 6 to 18 years and comprising mostly Combined and Inattentive subtypes, and for an age and gender matched control group. Results: The ADHD subjects had less wave activity at low frequencies (∼1Hz) during both tasks. For auditory Oddball targets, this effect was shown to be related to smaller P3 ERP amplitudes. During CPT, the ∼1Hz wave activity in the ADHD subjects was inversely related to clinical and behavioral measures of hyperactivity and impulsivity. CPT wave activity at ∼1Hz was seen to “normalise” following treatment with stimulant medication. Conclusions: The results identify a deficit in low frequency wave activity as a new marker for ADHD associated with levels of hyperactivity and impulsivity. Significance: The marker is evident across a range of tasks and may be specific to ADHD. While lower ∼1Hz activity partly accounts for reduced P3 ERPs in ADHD, the effect also arises for tasks that do not elicit a P3. Deficits in behavioral inhibition are hypothesized to arise from underlying dysregulation of cortical inhibition. [Copyright &y& Elsevier]

We present experimental results on hydrothermal traveling waves dynamics in long and narrow 1D channels. The onset of primary traveling-wave patterns is briefly presented for different fluid heights and for annular or bounded channels, i.e., within periodic or non-periodic boundary conditions. For periodic boundary conditions, by increasing the control parameter or changing the discrete mean wavenumber of the waves, we produce modulated wave patterns. These patterns range from stable periodic phase-solutions, due to supercritical Eckhaus instability, to spatio-temporal defect-chaos involving traveling holes and/or counter-propagating waves competition, i.e., traveling sources and sinks. The transition from non-linearly saturated Eckhaus modulations to transient pattern breaks by traveling holes and spatio-temporal defects is documented. Our observations are presented in the framework of coupled complex Ginzburg–Landau equations with additional fourth and fifth order terms which account for the reflection symmetry breaking at high wave-amplitude far from onset. The second part of this paper [N. Garnier, A. Chiffaudel, F. Daviaud, Nonlinear dynamics of waves and modulated waves in 1D thermocapillary flows. II. Convective/absolute transitions, Physica D (2003), this issue] extends this study to spatially non-periodic patterns observed in both annular and bounded channel. [Copyright &y& Elsevier]

We investigate the response of a Josephson-coupled multilayer to an ultra-short voltage pulse. The response is understood in terms of the dynamics of the phase differences across the layers, calculated from both the microscopic theory and the resistively shunted junction (RSJ) model. We discuss how such response might play a role in novel multilayered switching devices for use in electronics applications, such as flux quantum digital circuitry. [ABSTRACT FROM PUBLISHER]

Local magnetization curves at different times, extracted from high-temporal resolution magneto-optical measurements in Bi2Sr2CaCu2O8+δ, demonstrate the absence of the second magnetization peak (SMP) at short times, its appearance at longer times, and the movement of its onset toward higher induction fields approaching the limit of the thermodynamic order–disorder transition field. We utilize theoretical analysis, based on the Landau–Khalatnikov dynamic equation adopted for the vortex matter order parameter, to simulate the measured time evolution of the SMP. We show that the observed time evolution is a manifestation of a dynamic coexistence of transient-disordered and ordered vortex phases. [Copyright &y& Elsevier]