Phase Coherence Research Articles

New Framework for Understanding Cross-Brain Coherence in Functional Near-Infrared Spectroscopy (fNIRS) Hyperscanning Studies.

Despite the growing body of functional near-infrared spectroscopy (fNIRS) hyperscanning studies, the assessment of coupling between two neural signals using wavelet transform coherence (WTC) seems to ignore the directionality of the interaction. The field is currently lacking a framework that allows researchers to determine whether a high coherence value obtained using a WTC function reflects in-phase synchronization (i.e., neural activation is seen in both members of the dyad at the same time), lagged synchronization (i.e., neural activation is seen in one member of the dyad prior to the other member), or anti-phase synchronization (i.e., neural activation is increased in one member of the dyad and decreased in the other). To address this need, a complementary and more sensitive approach for analyzing the phase coherence of two neural signals is proposed in this work. The toolbox allows investigators to estimate the coupling directionality by classifying the phase angle values obtained using traditional WTC into in-phase synchronization, lagged synchronization, and anti-phase synchronization. The toolbox also allows researchers to assess how the dynamics of interactions develop and change throughout the task. Using this novel WTC approach and the toolbox will advance our understanding of complex social interactions through their uses in fNIRS hyperscanning studies.

Virtual source total focusing method for crack detection in complex curved structure

Accurate non-destructive testing and evaluation of cracks is important for the quality assurance and life-cycle management of key components in aerospace and energy industries. This paper presents a novel imaging method for cracks detection in complex curved structure , combining virtual source technique, multi-mode total focusing method and phase coherence imaging method. The virtual source on the sample surface is employed as the emitter and receiver for the ultrasonic array imaging. In this way, the calculation complexity of imaging algorithm due to beam path search can be reduced, and the detection sensitivity in the region of interest can be improved. In addition, the phase coherence factor is used to suppress the background noise and imaging artifacts, which significantly improves the quality of ultrasonic array imaging. A complex curved sample with variable thickness and non-developable surface was used to examine the effectiveness of the virtual source total focusing method. The signal-to-noise ratio of the crack defect is increased by more than 25 dB using the novel method compared with that of the conventional total focusing method, and the quantitative evaluation error of defect is less than 2.67%.

High-temperature microstructure evolution of an advanced intermetallic nano-lamellar γ-TiAl-based alloy and associated diffusion processes

Nano-lamellar advanced γ-TiAl based alloys doped with small amounts of C and Si are being developed to improve the creep resistance in order to increase the performances of this kind of alloys applied in the low-pressure turbine of aircraft engines. In order to extend the service temperature up to 1073 K or even above, the control of the microstructure stability is key. In this work, a complete study of the microstructure evolution during high-temperature exposure up to 1153 K has been approached through different electron microscopy techniques including HRTEM and HRSTEM with microanalysis. The nucleation and growth of the ordered βo precipitates and the ζ silicides inside the α2 lamellae has been carefully characterized and new orientation relationships and the misfit between all crystalline lattices has been determined, as well as the chemical concentration of the different atomic species on each phase. The electron microscopy study shows that βo and ζ precipitates inside α2 prevents or retards the dissolution of the α2 lamellae and its final disintegration in favor of the γ lamellae. This phenomenon has been discussed in terms of the phase coherence and diffusion processes. These important results allow conclude that the coarsening of the γ lamellae is delayed because of the βo and ζ precipitation, allowing to explain the observed enhancement of the creep resistance in this γ-TiAl based alloy exhibiting a nano-lamellar microstructure.

An autonomic mode of brain activity.

The relevance of interactions between autonomic and central nervous systems remains unclear for human brain function and health, particularly when both systems are challenged under sleep deprivation (SD). We measured brain activity (with fMRI), pulse and respiratory signals, and baseline brain amyloid beta burden (with PET) in healthy participants. We found that SD relative to rested wakefulness (RW) resulted in a significant increase in synchronized low frequency (LF, < 0.1Hz) activity in an autonomically-related network (AN), including dorsal attention, visual, and sensorimotor regions, which we previously found to have consistent temporal coupling with LF pulse signal changes (regulated by sympathetic tone). SD resulted in a significant phase coherence between the LF component of the pulse signal and a medial network with peak effects in the midbrain reticular formation, and between LF component of the respiratory variations (regulated by respiratory motor output) and a cerebellar network. The LF power of AN during SD was significantly and independently correlated with pulse-medial network and respiratory-cerebellar network phase coherences (total adjusted R2 = 0.78). Higher LF power of AN during SD (but not RW) was associated with lower amyloid beta burden (Cohen's d = 0.8). In sum, SD triggered an autonomic mode of synchronized brain activity that was associated with distinct autonomic-central interactions. Findings highlight the direct relevance of global cortical synchronization to brain clearance mechanisms.

Peripheral neural synchrony in pediatric cochlear implant users

We recently developed a noninvasive method to quantify neural synchrony in the electrically stimulated cochlear nerve (i.e., peripheral neural synchrony) using an index named the phase locking value (PLV). The PLV is a measurement of trial-to-trial phase coherence in the summated activity of cochlear nerve fibers. Larger PLVs indicate better/stronger peripheral neural synchrony. This tool allows for investigating this important phenomenon in cochlear implant (CI) users for the first time in the literature. The aim of this study was to characterize peripheral neural synchrony in a large group of pediatric CI users with various etiologies. To date, study participants included 17 children with cochlear nerve deficiency, 28 children with Gap Junction Beta-2 mutation, nine children with normal inner ear anatomy and idiopathic hearing loss, three children with enlarged vestibular aqueducts, three children with Mondini malformation and two children with Usher syndrome. All participants use Cochlear™ Nucleus® devices in their test ears. For each implanted ear tested in each participant, peripheral neural synchrony was assessed at the maximum comfortable level and multiple electrode locations across the electrode array. Our preliminary results demonstrated substantial variations in peripheral neural synchrony among pediatric CI users. These variations appear to depend on hearing loss etiologies.

Left Ringing: Betelgeuse Illuminates the Connection between Convective Outbursts, Mode Switching, and Mass Ejection in Red Supergiants

Betelgeuse, the nearest red supergiant, dimmed to an unprecedented level in early 2020. The star emerged from this “Great Dimming” episode with its typical, roughly 400 days pulsation cycle halved, and a new dominant period of around 200 days. The dimming event has been attributed to a surface mass ejection, in which rising material drove shocks through the stellar atmosphere and expelled some material, partially obscuring the star as it formed molecules and dust. In this paper, we use hydrodynamic simulations to reveal the connections between Betelgeuse's vigorously convective envelope, the surface mass ejection, and the pulsation mode switching that ensued. An anomalously hot convective plume, generated rarely but naturally in the star's turbulent envelope, can rise and break free from the surface, powering an upwelling that becomes the surface mass ejection. The rising plume also breaks the phase coherence of the star's pulsation, causing the surface to keep expanding even as the deeper layers contract. This drives a switch from the 400 days fundamental mode of pulsation, in which the whole star expands and contracts synchronously, to the 200 days first overtone, where a radial node separates the interior and exterior of the envelope moving in opposite phase. We predict that the star's convective motions will damp the overtone oscillation and Betelgeuse will return to its previous, 400 days fundamental-mode pulsation in the next 5–10 yr. With its resolved surface and unprecedentedly detailed characterization, Betelgeuse opens a window to episodic surface mass ejection in the late-stage evolution of massive stars.

Intact Mismatch Negativity Responses in Clinical High Risk for Psychosis and First-Episode Psychosis: Evidence From Source-Reconstructed Event-Related Fields and Time-Frequency Data

BackgroundThis study examined whether mismatch negativity (MMN) responses are impaired in participants at clinical high risk for psychosis (CHR-P) and patients with first-episode psychosis (FEP) and whether MMN deficits predict clinical outcomes in CHR-Ps. MethodsMagnetoencephalography data were collected during a duration-deviant MMN paradigm for a group of 116 CHR-P participants, 33 FEP patients (15 antipsychotic-naïve), clinical high risk negative group (n = 38) with substance abuse and affective disorder, and 49 healthy control participants. Analysis of group differences of source-reconstructed event-related fields as well as time-frequency and intertrial phase coherence focused on the bilateral Heschl’s gyri and bilateral superior temporal gyri. ResultsSignificant magnetic MMN responses were found across participants in the bilateral Heschl’s gyri and bilateral superior temporal gyri. However, MMN amplitude as well as time-frequency and intertrial phase coherence responses were intact in CHR-P participants and FEP patients compared with healthy control participants. Furthermore, MMN deficits were not related to persistent attenuated psychotic symptoms or transitions to psychosis in CHR-P participants. ConclusionsOur data suggest that magnetic MMN responses in magnetoencephalography data are not impaired in early-stage psychosis and may not predict clinical outcomes in CHR-P participants.

Effect of depression on phase coherence between respiratory sinus arrhythmia and respiration during sleep in patients with obstructive sleep apnea.

Introduction: A high prevalence of major depressive disorder (MDD) among Obstructive Sleep Apnea (OSA) patients has been observed in both community and clinical populations. Due to the overlapping symptoms between both disorders, depression is usually misdiagnosed when correlated with OSA. Phase coherence between respiratory sinus arrhythmia (RSA) and respiration (λ RSA-RESP) has been proposed as an alternative measure for assessing vagal activity. Therefore, this study aims to investigate if there is any difference in λ RSA-RESP in OSA patients with and without MDD. Methods: Electrocardiograms (ECG) and breathing signals using overnight polysomnography were collected from 40 OSA subjects with MDD (OSAD+), 40 OSA subjects without MDD (OSAD-), and 38 control subjects (Controls) without MDD and OSA. The interbeat intervals (RRI) and respiratory movement were extracted from 5-min segments of ECG signals with a single apneic event during non-rapid eye movement (NREM) [353 segments] and rapid eye movement (REM) sleep stages [298 segments]. RR intervals (RRI) and respiration were resampled at 10 Hz, and the band passed filtered (0.10-0.4 Hz) before the Hilbert transform was used to extract instantaneous phases of the RSA and respiration. Subsequently, the λ RSA-RESP between RSA and Respiration and Heart Rate Variability (HRV) features were computed. Results: Our results showed that λ RSA-RESP was significantly increased in the OSAD+ group compared to OSAD- group during NREM and REM sleep. This increase was accompanied by a decrease in the low frequency (LF) component of HRV. Discussion: We report that the phase synchronization index between RSA and respiratory movement could provide a useful measure for evaluating depression in OSA patients. Our findings suggest that depression has lowered sympathetic activity when accompanied by OSA, allowing for stronger synchronization between RSA and respiration.

Spectral decoupled correction algorithm for multi-input multi-output random vibration control

The multi-output response spectral replication correction algorithms for the multi-shaker random vibration test are investigated. In the existing matrix power correction algorithm, the control of auto and cross spectral densities is coupled which may bring some unexpected errors. The ideal spectral correction mode is that the control of auto and cross spectral densities should be independent of each other. For this purpose, a novel spectral decoupled correction algorithm is proposed with a spectral decoupling decomposition method in this work. Two lower triangular matrices are introduced to modify the auto and cross spectral densities separately during equalization procedure. Due to the positive definite constraint for the power spectral matrix, the coherence coefficient and phase difference in the cross spectral densities cannot be controlled independently when the number of the control channels is more than two. A simulation example is provided and the control results with the matrix power correction algorithm and proposed spectral decoupled correction algorithm are compared. Finally, a tri-axial shaker random vibration test is carried out and the results prove the effectiveness and feasibility of the proposed method.

Phase coherence weighted ultrasound total focusing method towards the improved imaging of CFRP defects

Defect imaging in carbon fiber reinforced polymer (CFRP) combining the phase coherence imaging (PCI) and the total focusing method (TFM) is investigated in this study, in order to overcome the adverse influence on defect imaging from wave propagation anisotropy, inter-ply reflection, and high attenuation. Three kinds of coherence factors are proposed first to be combined with the wave velocity corrected TFM for defect imaging in CFRP. Then, the much stronger phase coherence (PC) from the signals scattered from the defect than those from the inter-ply is discovered experimentally. Finally, with the proposed PC-weighted-TFM, the noise of imaging from the inter-ply reflection is largely suppressed, resulting in largely improved signal-to-noise ratios of imaging with defects at different depths and close to each other. The findings demonstrate that the proposed PC-weighted-TFM is of great application potential in nondestructive testing of CFRP.

MLPER: A Machine Learning-Based Prediction Model for Building Earthquake Response Using Ambient Vibration Measurements

Deep neural networks (DNNs) have gained prominence in addressing regression problems, offering versatile architectural designs that cater to various applications. In the field of earthquake engineering, seismic response prediction is a critical area of study. Simplified models such as single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) systems have traditionally provided valuable insights into structural behavior, known for their computational efficiency facilitating faster simulations. However, these models have notable limitations in capturing the nuanced nonlinear behavior of structures and the spatial variability of ground motions. This study focuses on leveraging ambient vibration (AV) measurements of buildings, combined with earthquake (EQ) time-history data, to create a predictive model using a neural network (NN) in image format. The primary objective is to predict a specific building’s earthquake response accurately. The training dataset consists of 1197 MDOF 2D shear models, generating a total of 32,319 training samples. To evaluate the performance of the proposed model, termed MLPER (machine learning-based prediction of building structures’ earthquake response), several metrics are employed. These include the mean absolute percentage error (MAPE) and the mean deviation angle (MDA) for comparisons in the time domain. Additionally, we assess magnitude-squared coherence values and phase differences (Δφ) for comparisons in the frequency domain. This study underscores the potential of the MLPER as a reliable tool for predicting building earthquake responses, addressing the limitations of simplified models. By integrating AV measurements and EQ time-history data into a neural network framework, the MLPER offers a promising avenue for enhancing our understanding of structural behavior during seismic events, ultimately contributing to improved earthquake resilience in building design and engineering.

A Discrete-Variable Local Diabatic Representation of Conical Intersection Dynamics.

Conical intersections (CIs) are ubiquitous in polyatomic molecules and are responsible for a wide range of phenomena in photochemistry and photophysics. Modeling the conical intersection dynamics with adiabatic electronic states is hindered by the divergence of the first- and second-order derivative couplings at CIs due to electronic degeneracy. We introduce and implement a novel diabatic representation for exact correlated electron-nuclear wave packet dynamics through conical intersections. It directly employs the adiabatic electronic states but avoids the singular first- and second-order derivative couplings and is robust to different gauge choices of the electronic wave function phases. The reference nuclear geometries defining the adiabatic electronic states are determined by a discrete-variable representation of the nuclear coordinates. The nonadiabatic effects are accounted for by the electronic overlap matrix instead of derivative couplings as in the adiabatic representation. Illustrated by a two-mode conical intersection model, this representation captures all nonadiabatic effects, including electronic transitions, electronic coherence, and geometric phases. Thus, this representation provides a singularity-free framework for modeling ab initio conical intersection wave packet dynamics.

Simple, low-cost, and well-performing optical phase-locked loop for frequency and phase locking of semiconductor lasers.

We demonstrate a simple, low-cost, and well-performing optical phase-locked loop (OPLL) circuit with ADF4007 as the phase frequency detector chip to achieve frequency and phase locking of two semiconductor lasers in both short and long terms. The measured short term performances, determined by fast feedback, show that the spectral width of the beat signal is low, around 1Hz, and the residual phasing error is 0.04r a d 2. The measured long term performances, determined by slow feedback, show that the drift of the central frequency of the beat signal is within 1.1(1)Hz in 2h, and the derived Allan deviation is less than 0.4Hz within all integration times of up to 1000s. The phase noise measurement shows a suppression of phase noise of the beat signal from free running to closed-loop OPLLs in a Fourier frequency of 10Hz-20kHz. These measurements show that the OPLL circuit we modified can fit most scientific experiments requiring a fixed frequency difference and phase coherence.

Bayesian analysis of phase data in EEG and MEG.

Electroencephalography and magnetoencephalography recordings are non-invasive and temporally precise, making them invaluable tools in the investigation of neural responses in humans. However, these recordings are noisy, both because the neuronal electrodynamics involved produces a muffled signal and because the neuronal processes of interest compete with numerous other processes, from blinking to day-dreaming. One fruitful response to this noisiness has been to use stimuli with a specific frequency and to look for the signal of interest in the response at that frequency. Typically this signal involves measuring the coherence of response phase: here, a Bayesian approach to measuring phase coherence is described. This Bayesian approach is illustrated using two examples from neurolinguistics and its properties are explored using simulated data. We suggest that the Bayesian approach is more descriptive than traditional statistical approaches because it provides an explicit, interpretable generative model of how the data arises. It is also more data-efficient: it detects stimulus-related differences for smaller participant numbers than the standard approach.

Unraveling the Ultrafast Coherent Dynamics of Exciton Polariton Propagation at Room Temperature.

Exciton polaritons are widely considered as promising platforms for developing room-temperature polaritonic devices, owing to the high-speed propagation and nonlinear interactions. However, it remains challenging to explore the dynamics of exciton polaritons specifically at room temperature, where the lifetime could be as small as a few picoseconds and the prevailing time-averaged measurement cannot give access to the true nature of it. Herein, by using the time-resolved photoluminescence, we have successfully traced the ultrafast coherent dynamics of a moving exciton polariton condensate in a one-dimensional perovskite microcavity. The propagation speed is directly measured to be ∼12.2 ± 0.8 μm/ps. Moreover, we have developed a time-resolved Michelson interferometry to quantify the time-dependent phase coherence, which reveals that the actual coherence time of exciton polaritons could be much longer (nearly 100%) than what was believed before. Our work sheds new light on the ultrafast coherent propagation of exciton polaritons at room temperature.

Wavelet-Based Analysis of the Comovement Between Exchange Rate and Stock Returns in Sacu Countries

ABSTRACT: The Southern African Customs Union is the oldest customs union in the world and the member states form a currency union with the South African Rand being the regional currency anchor. Therefore, currency movements amongst SACU member are dependent on the developments on the Rand which, in turn, can affect stock market development in the region. We examine the time-frequency relationship between exchange rates and stock market returns in SACU countries using continuous wavelet transforms. Our empirical analysis is two-staged. Firstly, we employ wavelet power spectrum to examine the time-frequency properties of the individual series. Secondly, we use wavelet coherence analysis and phase dynamics to examine the synchronization between the variables in a time-frequency space. Our findings show stronger (weaker) exchange rate-stock returns relations are found during periods of higher (lower) inflation whereas we observe a stronger (weaker) relationship during periods of lower interest rate environment. Moreover, we find more significant long-run relationships for countries with more independent monetary policy (South Africa and Botswana) whereas these relations are more prominent over the short-run for countries with pegged exchange rates (Eswatini and Namibia). We also observe that periods of oil and currency shocks impact the exchange rate-stock returns relationship in SACU countries with pegged exchange rates (Eswatini and Namibia). Our findings bear important implications for different stakeholders. For instance, this study has implications for exchange rate policy as it addresses the issue of whether the exchange rate can be used to improve market performance or exchange rate developments spillover into the stock market. Furthermore, corporate managers and stock market participants would be interested in our findings as it identifies periods of market inefficiency when exchange rates can be used to beat the stock market.

Total Focusing Method (TFM) and Phase Coherence Imaging (PCI) applied to various industrial cases

Les techniques d’imageries ultrasonores basées sur la Total Focusing Method (TFM) sont de plus en plus utilisées dans les applications industrielles. L’adoption de la méthodes a été rendue plus facile avec la publication de la méthode dans les codes ASME V, ISO 23864 et 23865. La TFM est une technique qui implique deux étapes : la première est l’acquisition appelée Full Matrix Capture (FMC) et la deuxième est la reconstruction elle-même (TFM). La TFM consiste à focaliser l’énergie acoustique à tous les pixels d’une région d’intérêt procurant une image de forte résolution. De nombreux développements ont été apportés à la technique pour améliorer notamment la productivité en utilisant des modes d’excitations tels que le Plane Wave Imaging (PWI) pour atteindre des vitesses de scan similaires à celles obtenues en multiéléments traditionnels. Alors que la TFM est basée sur l’extraction des amplitudes de la FMC, une autre technique appelée Phase Cohérence Imaging (PCI) extrait l’information de phase. Le PCI montre un fort contraste quand les éléments contribuent en phase. C’est le cas pour des défauts qui diffractent de l’énergie dans toutes les directions comme des petits défauts (HTHA, porosités…), les extrémités de fissures ou le grain des matériaux. A l’opposé, les échos spéculaires tendent à être minimisés puisque peu d’éléments contribuent en phase..

Benefits of software beamforming for ultrasonic inspections

Nondestructive testing (NDT) is used in more and more industries and inspection techniques must constantly adapt to complex materials (coarse grained materials, composites, etc.), defects (corrosion, fatigue crack, HTHA, etc.) or new inspection standards. Ultrasonic imaging methods have long been limited by low data throughput and a small number of transducers, but this is no longer the case with nowadays electronic devices and computers which enable large amounts of raw data to be acquired and processed in real time. The Delay-and-Sum (DAS) algorithm, which has been used almost automatically in many applications over the past few years, is now outperformed by advanced processing methods. In this context, this article presents few real-time advanced reconstruction techniques that enhance the quality of ultrasonic images on typical industrial applications. The first example concerns coherence beamformers such as Phase Coherence Imaging (PCI) which exploit the phase information of the signals. This type of method proves to be highly effective in detecting diffraction echoes from crack-like defects or in improving contrast and resolution of images from corroded samples inspections. The second example uses cross-correlation techniques that have been known for years to improve detection in various fields. Correlating the data with the transmitted signal reduces electronic noise and improves signal-to-noise ratio. This application also benefits from recent progress of ultrasonic devices that are able to modulate complex excitation signals in emission. This type of method is very promising for the inspection of attenuative materials and coarse-grained steels.

Synergistic toughening effect of SiC whiskers and particles in ZrO2–Al2O3–SiC ceramics

Zirconia ceramics have a good application prospect in the high-tech fields, whereas their potential utilization is highly limited by their mechanical properties. To fabricate zirconia based ceramics with superior mechanical properties, SiC whiskers (SiCw) and SiC particles (SiCp) were selected as the toughening phases for the preparation of ZrO2–Al2O3–SiC ceramics, and an advanced sintering technique called as oscillatory pressure sintering (OPS) was applied in the present work. The mechanical properties of such ceramics with 5 vol% SiCw and 10 vol% SiCp were significantly improved. The Vickers hardness increased to 15.26 GPa while the bending strength reached 917 MPa, and the fracture toughness rose to 6.83 MPa·m1/2. The toughness of the ceramics was improved by synergistic toughening effects including whisker toughening, stress-induced phase transformation toughening and particle dispersion toughening. Furthermore, SiCp and ZrO2, Al2O3 and SiCp, ZrO2 and SiCw as well as Al2O3 and SiCw formed a well-matched coherent phase boundary. The semi-coherent relationship was also generated at the phase boundary of SiCp and SiCw.

Impact of Geopolitical Risk on Financial Assets: Evidence from Time-Varying Parameter Var

Geopolitical events are expected to affect all countries, asset classes, and sectors. Vietnam is a large open economy, actively participating in a vast network of free trade agreements. Therefore, political conflicts in some regions will have both positive and negative impacts on the Vietnamese economy. Aiming to explore the dependency structure between the geopolitical risk index and stock market returns, this study has evaluated quite in-depth using the TVP-VAR method combining the wavelet coherence phase between February 2012 and April 2022. The results show that geopolitical risk has a heterogeneous effect on the return of financial assets, and the market does not respond to geopolitical tensions in a uniform manner. Our research uncovers new and interesting implications for policymakers and investors involved in the Vietnamese stock market.