Phase Coupling Research Articles

Supramammillary Theta Oscillations in Water Maze Learning.

The supramammillary nucleus (SuM) in the hypothalamus, in conjunction with the hippocampus (HPC), has been implicated through theta oscillations in various brain functions ranging from locomotion to learning and memory. While the indispensable role of the SuM in HPC theta generation in anesthetized animals is well-characterized, the SuM is not always necessary for HPC theta in awake animals. This raises questions on the precise behavioral relevance of SuM theta activity and its interaction with HPC theta activity. We used simultaneously recorded SuM and HPC local field potentials (LFPs) in a one-day water maze (WM) learning paradigm in rats (n = 8), to show that theta activities recorded from the SuM itself were not positively correlated with locomotor (swimming) speed nor acceleration, but the individual relationship between acceleration and SuM theta frequency is correlated with WM learning rates. In contrast, we found that SuM-HPC theta phase coherence is strongly correlated with swimming speed and acceleration, but these do not relate to WM learning. SuM-HPC-directed coherence analysis demonstrated no swimming kinetics nor learning rate associations, but revealed that periods of high SuM-HPC theta phase coherence are driven by the SuM at relatively low (~6.2 Hz) frequencies. Additionally, we demonstrate that the SuM and the HPC also engage in non-random, non-coherent phase coupling modes where either structure preferentially displays a ± 2 Hz difference with the other. Our data indicate SuM theta LFPs do not appear to be related to either speed coding or spatial learning in swimming rats and display non-random out-of-phase theta frequency coupling with the HPC.

Tangential Mode Combustion Oscillation of a Bluff-Body-Stabilized Diffusion Flame: Experiments

Addressing the issue of tangential mode combustion oscillation prevalent in aviation engine afterburners, this study targets bluff body diffusion flames. Innovatively, acoustic cavities were installed on either side of the bluff body flame, forming a tangential mode oscillation. The study employed experimental methods to study the flame pulsation characteristics under tangential oscillation, identifying the phase distribution of the flame front as a distinct feature differentiating it from conventional longitudinal mode oscillation. Furthermore, it was noted that the multiperiodic pulsation of the flame surface significantly contributes to the complex variability of the flame transfer function/flame description function. The research then established a phase relationship among velocity pulsation, pressure pulsation, and heat release rate pulsation, uncovering the phase coupling mechanism inherent in oscillatory combustion. It also delved into the impact of equivalence ratio and bluff body structure on tangential mode oscillation. Modifications to the bluff body structure led to a significant suppression of oscillation, reducing the amplitude by up to 81.3%. Thus, the study concluded that the flame dynamic response characteristics play a crucial role in determining the thermoacoustic coupling intensity, especially when the combustion system’s acoustic properties are stable. This finding lays a theoretical foundation for future endeavors to mitigate tangential mode oscillatory combustion in afterburners.

Nonlinear vibro-acoustic modulation for microcrack detection of steel strands based on S-transform bispectrum

Fatigue crack detection is an important issue to ensure the safety of steel strands. The key to solve this problem is to extract the nonlinear response generated by fatigue cracks. In this paper, the nonlinear VAM method is used to detect the structural cracks. The structure with fatigue cracks is excited using low-frequency pumping and high-frequency probing, and the power spectrum analysis of the modulated signal is carried out. In view of the shortcomings of spectral analysis, a new method combining S-transform and bispectrum is proposed, which is called S-transform bispectrum. S transform contains the phase factor, which can retain the absolute phase characteristics of each frequency, and has good time–frequency multi-scale focusing performance. The bispectrum can suppress Gaussian noise, retain phase information, and quantitatively describe the quadratic phase coupling in the signal. Then the simulation and experiment of damaged straight rod, helical rod, and steel strands are carried out. The results show that the proposed method can effectively detect the nonlinear features by using the sideband peaks in the S-transform bispectrum three-dimensional plot, and the nonlinear features are important to identify the structure with damage. At the same time, in order to prove the ability of S-transform bispectrum, an S-transform bispectrum detector is used to verify it, which is superior to the spectrum in terms of its ability to localize modulation sidebands. The proposed S-transform bispectrum has a good application prospect and provides a new tool for structural damage detection.

Pushing the Operation Current Density of Alkaline Water Oxidation above 1 A cm2 via Electrocatalyst Engineering

AbstractRapid cost reduction of green hydrogen is essential for the large‐scale deployment of hydrogen‐based energy system. A major component in achieving this is the development of advanced water electrolyzers. Sluggish oxygen evolution reaction (OER) is the bottleneck for water electrolysis, and tremendous efforts have been devoted to develop electrocatalysts that accelerate the OER kinetics. Recent advances have highlighted the potential of precious metal‐free OER electrocatalyst capable of stable operation at current densities above 1 A cm2. This brings an opportunity of constructing new‐generation electrolyzer with lower cost and higher productivity. However, achieving such high operating current densities presents new challenges. This review summarize the recent progress of high‐performance OER catalysts, and identifies key factors that can be leveraged to enhance catalyst activity. These factors include interface/surface engineering, amorphous and crystal phase coupling, hierarchical structure design, structural reconstruction and phase conversion, high entropy catalyst, and defect engineering. Additionally, the pressing challenges that have been largely ignored in previous research is addressed, such as sustaining long‐term stability under crucial conditions, disadvantages of immobilized powder electrocatalysts, electrode scale design, the necessity of designing innovative electrolyzer cell designs and advance characterization techniques.

Gamma amplitude-envelope correlations are strongly elevated within hyperexcitable networks in focal epilepsy

Methods to quantify cortical hyperexcitability are of enormous interest for mapping epileptic networks in patients with focal epilepsy. We hypothesize that, in the resting state, cortical hyperexcitability increases firing-rate correlations between neuronal populations within seizure onset zones (SOZs). This hypothesis predicts that in the gamma frequency band (40–200 Hz), amplitude envelope correlations (AECs), a relatively straightforward measure of functional connectivity, should be elevated within SOZs compared to other areas. To test this prediction, we analyzed archived samples of interictal electrocorticographic (ECoG) signals recorded from patients who became seizure-free after surgery targeting SOZs identified by multiday intracranial recordings. We show that in the gamma band, AECs between nodes within SOZs are markedly elevated relative to those elsewhere. AEC-based node strength, eigencentrality, and clustering coefficient are also robustly increased within the SOZ with maxima in the low-gamma band (permutation test Z-scores > 8) and yield moderate discriminability of the SOZ using ROC analysis (maximal mean AUC ~ 0.73). By contrast to AECs, phase locking values (PLVs), a measure of narrow-band phase coupling across sites, and PLV-based graph metrics discriminate the seizure onset nodes weakly. Our results suggest that gamma band AECs may provide a clinically useful marker of cortical hyperexcitability in focal epilepsy.

Single-pulse Transcranial Magnetic Stimulation Affects Working-memory Performance via Posterior Beta-band Oscillations.

A single pulse of TMS (spTMS) during the delay period of a double serial retrocuing working-memory task can briefly rescue decodability of an unprioritized memory item (UMI). This physiological phenomenon, which is paralleled in behavior by involuntary retrieval of the UMI, is carried by the beta frequency band, implicating beta-band dynamics in priority coding in working memory. We decomposed EEG data from 12 participants performing double serial retrocuing with concurrent delivery of spTMS using Spatially distributed PhAse Coupling Extraction. This procedure decomposes the scalp-level signal into a set of discrete coupled oscillators, each with a component strength that can vary over time. The decomposition revealed a diversity of low-frequency components, a subset of them strengthening with the onset of the task, and the majority declining in strength across the trial, as well as within each delay period. Results with spTMS revealed no evidence that it works by activating previously "silent" sources; instead, it had the effect of modulating ongoing activity, specifically by exaggerating the within-delay decrease in strength of posterior beta components. Furthermore, the magnitude of the effect of spTMS on the loading strength of a posterior beta component correlated with the disruptive effect of spTMS on performance, a pattern also seen when analyses were restricted to trials with "UMI-lure" memory probes. Rather than reflecting the "activation" of a putatively "activity silent" UMI, these results implicate beta-band dynamics in a mechanism that distinguishes prioritized from unprioritized, and suggest that the effect of spTMS is to disrupt this code.

Relativistic head-on collisions of U(1) gauged Q -balls

We investigate the collision dynamics of U(1) gauged Q-balls by performing high-resolution numerical simulations in axisymmetry. Focusing on the case of relativistic head-on collisions, we consider the effects of the initial velocity, relative phase, relative charge, and electromagnetic coupling strength on the outcome of the collision. We find that the collision dynamics can depend strongly on these parameters; most notably, electromagnetic effects can significantly alter the outcome of the collision when the gauge coupling is large. When the gauge coupling is small, we find that the dynamics generally resemble those of ordinary (nongauged) Q-balls. Published by the American Physical Society 2024

The flame macrostructure and thermoacoustic instability in a centrally staged burner operating in different pilot stage equivalence ratios

The main focus of this paper is to discover the link between flame macrostructure and thermoacoustic instability in a centrally staged swirl burner. In practical combustors, the flow rate in the pilot stage is much smaller than that in the main stage. However, the modification in the pilot stage could alter the flame macrostructure while maintaining a similar total flow rate. Therefore, the thermoacoustic instability was examined at different flame macrostructures by varying the pilot stage equivalence ratio under identical main stage inlet conditions. High-frequency planar laser measurements and chemiluminescence measurement were conducted to enhance spatial and temporal accuracy, providing a more comprehensive understanding of thermoacoustic instability. Two different flame macrostructures, S-type and I-type flames, were identified based on the preheating zone distribution. They exhibit distinct thermoacoustic instabilities, with the I-type flames demonstrating more intense instability than S-type flames. The results indicate that the variation of flame macrostructure influences the coupling of flame heat release and flow field. Specifically, the preheating zone and heat release of I-type flames exhibit greater sensitivity to flow field fluctuations, resulting in a more intense and complex fluctuation of the flame. This discrepancy leads to variations in thermoacoustic instability intensity, as well as the changes in the phase coupling between heat release and acoustic pressure, which in turn impact the total Rayleigh index. Meanwhile, significant differences exist in the distribution pattern and range of flow field fluctuations between I-type and S-type flames.

Collective Hall current in chiral active fluids: Coupling of phase and mass transport through traveling bands

Active fluids composed of constituents that are constantly driven away from thermal equilibrium can support spontaneous currents and can be engineered to have unconventional transport properties. Here, we report the emergence of (meta)stable traveling bands in computer simulations of aligning circle swimmers. These bands are different from polar flocks and, through coupling phase with mass transport, induce a bulk particle current with a component perpendicular to the propagation direction, thus giving rise to a collective Hall (or Magnus) effect. Traveling bands require sufficiently small orbits and undergo a discontinuous transition into a synchronized state with transient polar clusters for large orbital radii. Within a minimal hydrodynamic theory, we show that the bands can be understood as nondispersive soliton solutions fully accounting for the numerically observed properties.

Recognition of regions of stroke injury using multi-modal frequency features of electroencephalogram.

Nowadays, increasingly studies are attempting to analyze strokes in advance. The identification of brain damage areas is essential for stroke rehabilitation. We proposed Electroencephalogram (EEG) multi-modal frequency features to classify the regions of stroke injury. The EEG signals were obtained from stroke patients and healthy subjects, who were divided into right-sided brain injury group, left-sided brain injury group, bilateral brain injury group, and healthy controls. First, the wavelet packet transform was used to perform a time-frequency analysis of the EEG signal and extracted a set of features (denoted as WPT features). Then, to explore the nonlinear phase coupling information of the EEG signal, phase-locked values (PLV) and partial directed correlations (PDC) were extracted from the brain network, and the brain network produced a second set of features noted as functional connectivity (FC) features. Furthermore, we fused the extracted multiple features and used the resnet50 convolutional neural network to classify the fused multi-modal (WPT + FC) features. The classification accuracy of our proposed methods was up to 99.75%. The proposed multi-modal frequency features can be used as a potential indicator to distinguish regions of brain injury in stroke patients, and are potentially useful for the optimization of decoding algorithms for brain-computer interfaces.

Dichotomous frequency-dependent phase synchrony in the sensorimotor network characterizes simplistic movement

It is hypothesized that disparate brain regions interact via synchronous activity to control behavior. The nature of these interconnected ensembles remains an area of active investigation, and particularly the role of high frequency synchronous activity in simplistic behavior is not well known. Using intracranial electroencephalography, we explored the spectral dynamics and network connectivity of sensorimotor cortical activity during a simple motor task in seven epilepsy patients. Confirming prior work, we see a “spectral tilt” (increased high-frequency (HF, 70–100 Hz) and decreased low-frequency (LF, 3–33 Hz) broadband oscillatory activity) in motor regions during movement compared to rest, as well as an increase in LF synchrony between these regions using time-resolved phase-locking. We then explored this phenomenon in high frequency and found a robust but opposite effect, where time-resolved HF broadband phase-locking significantly decreased during movement. This “connectivity tilt” (increased LF synchrony and decreased HF synchrony) displayed a graded anatomical dependency, with the most robust pattern occurring in primary sensorimotor cortical interactions and less robust pattern occurring in associative cortical interactions. Connectivity in theta (3–7 Hz) and high beta (23–27 Hz) range had the most prominent low frequency contribution during movement, with theta synchrony building gradually while high beta having the most prominent effect immediately following the cue. There was a relatively sharp, opposite transition point in both the spectral and connectivity tilt at approximately 35 Hz. These findings support the hypothesis that task-relevant high-frequency spectral activity is stochastic and that the decrease in high-frequency synchrony may facilitate enhanced low frequency phase coupling and interregional communication. Thus, the “connectivity tilt” may characterize behaviorally meaningful cortical interactions.

Spatial-to-spectral phase coupling mechanisms in bulk continuum generation

We study the coherence properties of continuum generation in YAG crystals seeded by 180 fs pulses at 1035 nm when the driving beam exhibits small fluctuations of the spatial phase. The relative stability of the continuum spectral phase is first assessed as a function of the driver wavefront aberrations. Furthermore, we evidence and quantify a coupling mechanism between these fluctuations and the spectral phase of the continuum. The coupling coefficients increase with the spectral broadening and are also unexpectedly large (up to tens of rad/rad at ≃ 750 nm). Experimental evidence supports that longitudinal shifts of the position of the filament within the crystal are responsible for such strong effects.

Combining enhanced spectral resolution of EMG and a deep learning approach for knee pathology diagnosis.

Knee osteoarthritis (OA) is a prevalent, debilitating joint condition primarily affecting the elderly. This investigation aims to develop an electromyography (EMG)-based method for diagnosing knee pathologies. EMG signals of the muscles surrounding the knee joint were examined and recorded. The principal components of the proposed method were preprocessing, high-order spectral analysis (HOSA), and diagnosis/recognition through deep learning. EMG signals from individuals with normal and OA knees while walking were extracted from a publicly available database. This examination focused on the quadriceps femoris, the medial gastrocnemius, the rectus femoris, the semitendinosus, and the vastus medialis. Filtration and rectification were utilized beforehand to eradicate noise and smooth EMG signals. Signals' higher-order spectra were analyzed with HOSA to obtain information about nonlinear interactions and phase coupling. Initially, the bicoherence representation of EMG signals was devised. The resulting images were fed into a deep-learning system for identification and analysis. A deep learning algorithm using adapted ResNet101 CNN model examined the images to determine whether the EMG signals were conventional or indicative of knee osteoarthritis. The validated test results demonstrated high accuracy and robust metrics, indicating that the proposed method is effective. The medial gastrocnemius (MG) muscle was able to distinguish Knee osteoarthritis (KOA) patients from normal with 96.3±1.7% accuracy and 0.994±0.008 AUC. MG has the highest prediction accuracy of KOA and can be used as the muscle of interest in future analysis. Despite the proposed method's superiority, some limitations still require special consideration and will be addressed in future research.

WITHDRAWN: The periodic evolution of the resonant mode in a lossy microfiber coil resonator with three turns

The periodic evolution of the resonant mode in a lossy microfiber coil resonator with three turns is unraveled, and two types of loss conditions are assumed to investigate the characteristics of resonant mode with respect to the coupling state by means of numerical modeling. Under a given loss condition, the resonant mode exhibits periodic evolution between normal resonance, white-light cavity effect and resonance mode splitting as the change of the phase shift and coupling state. When the coupling state exceeds a certain threshold under a specific loss coefficient, the microfiber coil resonator predominantly exhibits normal resonance with characteristics akin to a single-ring resonator. Once the coupling state decreases to this threshold and matches the loss, white-light cavity effect will be activated. Moreover, as the coupling state falls below this threshold, the degeneracy of the resonance mode is raised and the resonant phase undergoes a bifurcation. The excitation conditions for each resonant mode have been derived, and the critical coupling conditions exist for both normal resonance and mode splitting in the case of relatively small losses. It’s found that there exists a threshold loss at which the critical coupling states of normal resonance and mode splitting coincide with the condition of white-light cavity effect. The characteristics of each mode have also been discussed.

Mirror Symmetry Broken of Sound Vortex Transmission in a Single Passive Metasurface via Phase Coupling.

Asymmetric transmission in a passive vortex system is highly desirable, as it enables the development of compact vortex-based devices. However, breaking the mirror symmetry of transmission via a single metasurface poses challenges due to the inherent symmetric transmission properties in reciprocity. Here, we theoretically propose and experimentally demonstrate a novel transmission-reflection phase coupling mechanism to achieve the broken mirror symmetry of sound vortex transmission. This mechanism establishes a special coupling link between transmission and reflection waves, superimposing asymmetric reflection phases on the transmission phases. By utilizing a single passive phase gradient metasurface with asymmetric reflection phase twists, distinct transmission phase twists for mirror-symmetric incident vortices can be achieved within a cylindrical waveguide. This is typically difficult to imple-ment in a reciprocal system. Numerical and experimental results both demonstrate the broken mirror symmetry of vortex transmission and reflection. Our findings offer a new strategy for controlling vortex wave propagation, which may inspire new directional applications and extend to the field of photonics.

Motor Current Time-Varying Quadratic Phase Coupling Analysis and Its Application in Traction Motor Fault Detection Under Varying-Speed Condition

Motor Current Time-Varying Quadratic Phase Coupling Analysis and Its Application in Traction Motor Fault Detection Under Varying-Speed Condition

Self-organising phenomena in 2D complex plasma simulations withnon-mono dispersed dust size distributions

Complex plasma with a variety of continuous and discrete dust grain size distributions are simulated in 2D with molecular dynamics simulations with radial geometry to determine differences in self-organizing phenomena to more realistically represent the actual in situ variations in dust-size. The standard deviation of particle size σ(a) strongly correlates with phase separation and coupling parameter Γ for all distribution types. We observe local differences in bond order parameters and Voronoi diagrams for different size distributions, and our results suggest that phase transition is affected by continuous size distributions, particularly in the binary distribution case. Simulations with discrete size result in artifacts and discontinuities that are not found in the continuous distributions. The use of continuous distributions is observed to be beneficial both for more realistic approximation of complex plasma experiments and to study systems of strongly coupled particles in general.

Detection of quadratic phase coupling by cross-bicoherence and spectral Granger causality in bifrequencies interactions

Quadratic Phase Coupling (QPC) serves as an essential statistical instrument for evaluating nonlinear synchronization within multivariate time series data, especially in signal processing and neuroscience fields. This study explores the precision of QPC detection using numerical estimates derived from cross-bicoherence and bivariate Granger causality within a straightforward, yet noisy, instantaneous multiplier model. It further assesses the impact of accidental statistically significant bifrequency interactions, introducing new metrics such as the ratio of bispectral quadratic phase coupling and the ratio of bivariate Granger causality quadratic phase coupling. Ratios nearing 1 signify a high degree of accuracy in detecting QPC. The coupling strength between interacting channels is identified as a key element that introduces nonlinearities, influencing the signal-to-noise ratio in the output channel. The model is tested across 59 experimental conditions of simulated recordings, with each condition evaluated against six coupling strength values, covering a wide range of carrier frequencies to examine a broad spectrum of scenarios. The findings demonstrate that the bispectral method outperforms bivariate Granger causality, particularly in identifying specific QPC under conditions of very weak couplings and in the presence of noise. The detection of specific QPC is crucial for neuroscience applications aimed at better understanding the temporal and spatial coordination between different brain regions.

Identifying System Non-Linearities by Fusing Signal Bispectral Signatures

Higher-order statistics investigate the phase relationships between frequency components, an aspect which cannot be treated using conventional spectral measures such as the power spectrum. Among the widely used higher-order statistics, the bispectrum ranks prominently. By delving into higher-order correlations, the bispectrum offers a means of extracting additional merits and insights from frequency coupling, enhancing our understanding of complex signal interactions. This analytical approach overcomes the limitations of traditional methods, providing a more comprehensive view of the complex relationships within the frequency domain. In this paper, the extensive use of the bispectrum in various scientific and technical areas is firstly emphasized by presenting very recent applications. The main scope of this work is to investigate the consequences of various non-linearities in the creation of phase couplings. Specifically, the quadratic, the cubic and the logarithmic non-linearities are examined. In addition, simple recommendations are given on how the underlying nonlinearity could be detected. The total approach is novel, considering the capability to distinguish from the bispectral content if two non-linearities are simultaneously present.

The bicoherence study of quasi-periodic oscillations in MAXI J1535−571

ABSTRACT Bicoherence is a way to measure the phase coupling of triplets of Fourier frequencies. We use this method to analyse quasi-periodic oscillations (QPOs) in the black hole X-ray binary MAXI J1535−571 during its 2017 September–October outburst. The bicoherence provides an interesting new diagnostic to uncover QPO behaviour and the relationships between QPO harmonics and broad-band noise. The bicoherence pattern of type-C QPOs starts as a ‘web’ pattern and changes to a ‘hypotenuse’ pattern after the presence of type-B QPOs, indicating that MAXI J1535−571 is a low-inclination source. The intensity of bicoherence also exhibits variations across different energy bands. We try to explain the bicoherence results in the scenario of a dual-corona geometry.