Time-frequency coherence analysis of phrenic and hypoglossal activity in the decerebrate rat during eupnea, hyperpnea, and gasping

2006 ◽  
Vol 291 (5) ◽  
pp. R1430-R1442 ◽  
Author(s):  
Vitaliy Marchenko ◽  
Robert F. Rogers
Keyword(s):  
Low Frequency ◽  
Adult Rats ◽  
Time Frequency ◽  
High Frequency Oscillations ◽  
Respiratory Network ◽  
Decerebrate Rat ◽  
State Changes ◽  
Nerve Recordings ◽  
Frequency Coherence ◽  
Respiratory Rhythms

Fast respiratory rhythms include medium- (MFO) and high-frequency oscillations (HFO), which are much faster than the fundamental breathing rhythm. According to previous studies, HFO is characterized by high coherence (Coh) in phrenic (Ph) nerve activity, thereby providing a means of distinguishing between these two types of oscillations. Changes in Coh between the Ph and hypoglossal (XII) nerves during the transition from normal eupnic breathing to gasping have not been characterized. Experiments were performed on nine unanesthetized, chemo- and barodenervated, decerebrate adult rats, in which sustained asphyxia elicited hyperpnea and gasping. A gated time-frequency Coh analysis was developed and applied to whole Ph and medial XII nerve recordings. The results showed dynamic Ph-Ph Coh during eupnea, including MFO and HFO. XII-XII Coh during eupnea was broadband and included four distinct peaks, with low-frequency Coh dominating the epochs preceding the onset of Ph activity. During gasping, only MFO-peaks were present in Ph-Ph Coh. Bilateral XII activity showed a significant reduction in Coh and a shift toward lower frequencies during gasping. In contrast, contralateral Ph-XII Coh progressively increased during state changes from eupnea to gasping, a tendency mirrored in the startup part of the Ph activity. These data suggest significant hypoxia/hypercapnia-induced alterations in synchronization between respiratory outputs during the transition from eupnea to gasping, reflecting a reconfiguration of the respiratory network and/or alterations in the circuitry associated with the motor pools, including dynamic coupling between outputs.

scholarly journals Motoneuron firing patterns underlying fast oscillations in phrenic nerve discharge in the rat

2012 ◽  
Vol 108 (8) ◽  
pp. 2134-2143 ◽  
Author(s):  
Vitaliy Marchenko ◽  
Michael G. Z. Ghali ◽  
Robert F. Rogers
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Medium Frequency ◽  
Adult Rats ◽  
Time Frequency ◽  
High Frequency Oscillations ◽  
Novel Method ◽  
Frequency Coherence ◽  
Fast Oscillations ◽  
First Time

Fast oscillations are ubiquitous throughout the mammalian central nervous system and are especially prominent in respiratory motor outputs, including the phrenic nerves (PhNs). Some investigators have argued for an epiphenomenological basis for PhN high-frequency oscillations because phrenic motoneurons (PhMNs) firing at these same frequencies have never been recorded, although their existence has never been tested systematically. Experiments were performed on 18 paralyzed, unanesthetized, decerebrate adult rats in which whole PhN and individual PhMN activity were recorded. A novel method for evaluating unit-nerve time-frequency coherence was applied to PhMN and PhN recordings. PhMNs were classified according to their maximal firing rate as high, medium, and low frequency, corresponding to the analogous bands in PhN spectra. For the first time, we report the existence of PhMNs firing at rates corresponding to high-frequency oscillations during eupneic motor output. The majority of PhMNs fired only during inspiration, but a small subpopulation possessed tonic activity throughout all phases of respiration. Significant time-varying PhMN-PhN coherence was observed for all PhMN classes. High-frequency, early-recruited units had significantly more consistent onset times than low-frequency, early/middle-recruited and medium-frequency, middle/late-recruited PhMNs. High- and medium-frequency PhMNs had significantly more consistent offset times than low-frequency units. This suggests that startup and termination of PhMNs with higher firing rates are more precisely controlled, which may contribute to the greater PhMN-PhN coherence at the beginning and end of inspiration. Our findings provide evidence that near-synchronous discharge of PhMNs firing at high rates may underlie fast oscillations in PhN discharge.

Selective loss of high-frequency oscillations in phrenic and hypoglossal activity in the decerebrate rat during gasping

2006 ◽  
Vol 291 (5) ◽  
pp. R1414-R1429 ◽  
Author(s):  
Vitaliy Marchenko ◽  
Robert F. Rogers
Keyword(s):  
Power Distribution ◽  
High Frequency ◽  
Spectral Characteristics ◽  
Low Frequency ◽  
High Amplitude ◽  
Medial Branch ◽  
Adult Rats ◽  
Time Frequency ◽  
High Frequency Oscillations ◽  
Nerve Recordings

Respiratory motor outputs contain medium-(MFO) and high-frequency oscillations (HFO) that are much faster than the fundamental breathing rhythm. However, the associated changes in power spectral characteristics of the major respiratory outputs in unanesthetized animals during the transition from normal eupneic breathing to hypoxic gasping have not been well characterized. Experiments were performed on nine unanesthetized, chemo- and barodenervated, decerebrate adult rats, in which asphyxia elicited hyperpnea, followed by apnea and gasping. A gated fast Fourier transform (FFT) analysis and a novel time-frequency representation (TFR) analysis were developed and applied to whole phrenic and to medial branch hypoglossal nerve recordings. Our results revealed one MFO and one HFO peak in the phrenic output during eupnea, where HFO was prominent in the first two-thirds of the burst and MFO was prominent in the latter two-thirds of the burst. The hypoglossal activity contained broadband power distribution with several distinct peaks. During gasping, two high-amplitude MFO peaks were present in phrenic activity, and this state was characterized by a conspicuous loss in HFO power. Hypoglossal activity showed a significant reduction in power and a shift in its distribution toward lower frequencies during gasping. TFR analysis of phrenic activity revealed the increasing importance of an initial low-frequency “start-up” burst that grew in relative intensity as hypoxic conditions persisted. Significant changes in MFO and HFO rhythm generation during the transition from eupnea to gasping presumably reflect a reconfiguration of the respiratory network and/or alterations in signal processing by the circuitry associated with the two motor pools.

Temperature and state dependence of dynamic phrenic oscillations in the decerebrate juvenile rat

2007 ◽  
Vol 293 (6) ◽  
pp. R2323-R2335 ◽  
Author(s):  
Vitaliy Marchenko ◽  
Robert F. Rogers
Keyword(s):  
Low Frequency ◽  
State Dependence ◽  
Temperature Dependent ◽  
Time Frequency ◽  
High Frequency Oscillations ◽  
Effects Of Temperature ◽  
Fast Oscillations ◽  
Incomplete Ischemia

The aim of the present study was to determine characteristics of fast oscillations in the juvenile rat phrenic nerve (Ph) and to establish their temperature and state dependence. Two different age-matched decerebrate, baro- and chemodenervated rat preparations, in vivo and in situ arterially perfused models, were used to examine three systemic properties: 1) generation and dynamics of fast oscillations in Ph activity (both preparations), 2) responses to anoxia (both preparations), and 3) the effects of temperature on fast oscillations (in situ only). Both juvenile preparations generated power and coherence in two major bands analogous to adult medium- and high-frequency oscillations (HFO) at frequencies that increased with temperature but were lower than in adults. At < 28°C, however, Ph oscillations were confined primarily to one low-frequency band (20–45 Hz). During sustained anoxia, both preparations produced stereotypical state changes from eupnea to hyperpnea to transition bursting (a behavior present only in vivo during incomplete ischemia) to gasping. Thus the juvenile rat produces a sequential pattern of responses to anoxia that are intermediate forms between those produced by neonates and those produced by adults. Time-frequency analysis determined that fast oscillations demonstrated dynamics over the course of the inspiratory burst and a state dependence similar to that of adults in vivo in which hyperpnea (and transition) bursts are associated with increases in HFO, while gasping contains no HFO. Our results confirm that both the fast oscillations in Ph activity and the coherence between Ph pairs produced by the juvenile rat are profoundly state- and temperature-dependent.

scholarly journals Cardiopulmonary coupling indices to assess weaning readiness from mechanical ventilation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pablo Armañac-Julián ◽  
David Hernando ◽  
Jesús Lázaro ◽  
Candelaria de Haro ◽  
Rudys Magrans ◽  
...  
Keyword(s):  
Heart Rate ◽  
Mechanical Ventilation ◽  
Spontaneous Breathing Trial ◽  
Sinus Arrhythmia ◽  
Time Frequency ◽  
Cardiopulmonary Coupling ◽  
Cardiac Pumping ◽  
Successful Weaning ◽  
Frequency Coherence ◽  
Subspace Projections

AbstractThe ideal moment to withdraw respiratory supply of patients under Mechanical Ventilation at Intensive Care Units (ICU), is not easy to be determined for clinicians. Although the Spontaneous Breathing Trial (SBT) provides a measure of the patients’ readiness, there is still around 15–20% of predictive failure rate. This work is a proof of concept focused on adding new value to the prediction of the weaning outcome. Heart Rate Variability (HRV) and Cardiopulmonary Coupling (CPC) methods are evaluated as new complementary estimates to assess weaning readiness. The CPC is related to how the mechanisms regulating respiration and cardiac pumping are working simultaneously, and it is defined from HRV in combination with respiratory information. Three different techniques are used to estimate the CPC, including Time-Frequency Coherence, Dynamic Mutual Information and Orthogonal Subspace Projections. The cohort study includes 22 patients in pressure support ventilation, ready to undergo the SBT, analysed in the 24 h previous to the SBT. Of these, 13 had a successful weaning and 9 failed the SBT or needed reintubation –being both considered as failed weaning. Results illustrate that traditional variables such as heart rate, respiratory frequency, and the parameters derived from HRV do not differ in patients with successful or failed weaning. Results revealed that HRV parameters can vary considerably depending on the time at which they are measured. This fact could be attributed to circadian rhythms, having a strong influence on HRV values. On the contrary, significant statistical differences are found in the proposed CPC parameters when comparing the values of the two groups, and throughout the whole recordings. In addition, differences are greater at night, probably because patients with failed weaning might be experiencing more respiratory episodes, e.g. apneas during the night, which is directly related to a reduced respiratory sinus arrhythmia. Therefore, results suggest that the traditional measures could be used in combination with the proposed CPC biomarkers to improve weaning readiness.

scholarly journals Complex Principal Component Analysis of Antarctic Ice Sheet Mass Balance

2021 ◽  
Vol 13 (3) ◽  
pp. 480
Author(s):  
Jingang Zhan ◽  
Hongling Shi ◽  
Yong Wang ◽  
Yixin Yao
Keyword(s):  
Principal Component Analysis ◽  
Ice Sheet ◽  
Low Frequency ◽  
Principal Component ◽  
Equatorial Pacific ◽  
Mass Change ◽  
Frequency Variation ◽  
Periodic Signal ◽  
Time Frequency ◽  
The Antarctic

Ice sheet changes of the Antarctic are the result of interactions among the ocean, atmosphere, and ice sheet. Studying the ice sheet mass variations helps us to understand the possible reasons for these changes. We used 164 months of Gravity Recovery and Climate Experiment (GRACE) satellite time-varying solutions to study the principal components (PCs) of the Antarctic ice sheet mass change and their time-frequency variation. This assessment was based on complex principal component analysis (CPCA) and the wavelet amplitude-period spectrum (WAPS) method to study the PCs and their time-frequency information. The CPCA results revealed the PCs that affect the ice sheet balance, and the wavelet analysis exposed the time-frequency variation of the quasi-periodic signal in each component. The results show that the first PC, which has a linear term and low-frequency signals with periods greater than five years, dominates the variation trend of ice sheet in the Antarctic. The ratio of its variance to the total variance shows that the first PC explains 83.73% of the mass change in the ice sheet. Similar low-frequency signals are also found in the meridional wind at 700 hPa in the South Pacific and the sea surface temperature anomaly (SSTA) in the equatorial Pacific, with the correlation between the low-frequency periodic signal of SSTA in the equatorial Pacific and the first PC of the ice sheet mass change in Antarctica found to be 0.73. The phase signals in the mass change of West Antarctica indicate the upstream propagation of mass loss information over time from the ocean–ice interface to the southward upslope, which mainly reflects ocean-driven factors such as enhanced ice–ocean interaction and the intrusion of warm saline water into the cavities under ice shelves associated with ice sheets which sit on retrograde slopes. Meanwhile, the phase signals in the mass change of East Antarctica indicate the downstream propagation of mass increase information from the South Pole toward Dronning Maud Land, which mainly reflects atmospheric factors such as precipitation accumulation.

Methods to isolate retrograde and prograde Rayleigh-wave signals

2019 ◽  
Vol 219 (2) ◽  
pp. 975-994 ◽  
Author(s):  
Gabriel Gribler ◽  
T Dylan Mikesell
Keyword(s):  
Rayleigh Wave ◽  
Time Domain ◽  
Fundamental Mode ◽  
Poisson Ratio ◽  
Low Frequency ◽  
Wave Dispersion ◽  
Low Frequencies ◽  
Retrograde Motion ◽  
Mode Identification ◽  
Time Frequency

SUMMARY Estimating shear wave velocity with depth from Rayleigh-wave dispersion data is limited by the accuracy of fundamental and higher mode identification and characterization. In many cases, the fundamental mode signal propagates exclusively in retrograde motion, while higher modes propagate in prograde motion. It has previously been shown that differences in particle motion can be identified with multicomponent recordings and used to separate prograde from retrograde signals. Here we explore the domain of existence of prograde motion of the fundamental mode, arising from a combination of two conditions: (1) a shallow, high-impedance contrast and (2) a high Poisson ratio material. We present solutions to isolate fundamental and higher mode signals using multicomponent recordings. Previously, a time-domain polarity mute was used with limited success due to the overlap in the time domain of fundamental and higher mode signals at low frequencies. We present several new approaches to overcome this low-frequency obstacle, all of which utilize the different particle motions of retrograde and prograde signals. First, the Hilbert transform is used to phase shift one component by 90° prior to summation or subtraction of the other component. This enhances either retrograde or prograde motion and can increase the mode amplitude. Secondly, we present a new time–frequency domain polarity mute to separate retrograde and prograde signals. We demonstrate these methods with synthetic and field data to highlight the improvements to dispersion images and the resulting dispersion curve extraction.

scholarly journals Multi-scale time-frequency domain full waveform inversion with a weighted local correlation-phase misfit function

2019 ◽  
Vol 16 (6) ◽  
pp. 1017-1031 ◽  
Author(s):  
Yong Hu ◽  
Liguo Han ◽  
Rushan Wu ◽  
Yongzhong Xu
Keyword(s):  
Frequency Domain ◽  
Seismic Data ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Full Waveform Inversion ◽  
Local Correlation ◽  
Time Frequency ◽  
Model Dependence ◽  
Full Waveform ◽  
Frequency Components

Abstract Full Waveform Inversion (FWI) is based on the least squares algorithm to minimize the difference between the synthetic and observed data, which is a promising technique for high-resolution velocity inversion. However, the FWI method is characterized by strong model dependence, because the ultra-low-frequency components in the field seismic data are usually not available. In this work, to reduce the model dependence of the FWI method, we introduce a Weighted Local Correlation-phase based FWI method (WLCFWI), which emphasizes the correlation phase between the synthetic and observed data in the time-frequency domain. The local correlation-phase misfit function combines the advantages of phase and normalized correlation function, and has an enormous potential for reducing the model dependence and improving FWI results. Besides, in the correlation-phase misfit function, the amplitude information is treated as a weighting factor, which emphasizes the phase similarity between synthetic and observed data. Numerical examples and the analysis of the misfit function show that the WLCFWI method has a strong ability to reduce model dependence, even if the seismic data are devoid of low-frequency components and contain strong Gaussian noise.

High-frequency seismic noise as a function of depth

1991 ◽  
Vol 81 (4) ◽  
pp. 1101-1114
Author(s):  
Jerry A. Carter ◽  
Noel Barstow ◽  
Paul W. Pomeroy ◽  
Eric P. Chael ◽  
Patrick J. Leahy
Keyword(s):  
New York ◽  
High Frequency ◽  
Seismic Noise ◽  
Low Frequency ◽  
Time Variability ◽  
Orthogonal Components ◽  
The Difference ◽  
Frequency Coherence ◽  
Cultural Noise ◽  
Natural Wind

Abstract Evidence is presented supporting the view that high-frequency seismic noise decreases with increased depth. Noise amplitudes are higher near the free surface where surface-wave noise, cultural noise, and natural (wind-induced) noise predominate. Data were gathered at a hard-rock site in the northwestern Adirondack lowlands of northern New York. Between 15- and 40-Hz noise levels at this site are more than 10 dB less at 945-m depth than they are at the surface, and from 40 to 100 Hz the difference is more than 20 dB. In addition, time variability of the spectra is shown to be greater at the surface than at either 335- or 945-m depths. Part of the difference between the surface and subsurface noise variability may be related to wind-induced noise. Coherency measurements between orthogonal components of motion show high-frequency seismic noise is more highly organized at the surface than it is at depth. Coherency measurements between the same component of motion at different vertical offsets show a strong low-frequency coherence at least up to 945-m vertical offsets. As the vertical offset decreases, the frequency band of high coherence increases.

scholarly journals Analysis of stimulus-related activity in rat auditory cortex using complex spectral coefficients

2013 ◽  
Vol 110 (3) ◽  
pp. 621-639 ◽  
Author(s):  
Bryan M. Krause ◽  
Matthew I. Banks
Keyword(s):  
Low Frequency ◽  
Phase Changes ◽  
Induced Response ◽  
Top Down ◽  
Time Frequency ◽  
State Dependent ◽  
Spectral Coefficients ◽  
The Mean ◽  
Sensory Responses ◽  
Mean Variance

The neural mechanisms of sensory responses recorded from the scalp or cortical surface remain controversial. Evoked vs. induced response components (i.e., changes in mean vs. variance) are associated with bottom-up vs. top-down processing, but trial-by-trial response variability can confound this interpretation. Phase reset of ongoing oscillations has also been postulated to contribute to sensory responses. In this article, we present evidence that responses under passive listening conditions are dominated by variable evoked response components. We measured the mean, variance, and phase of complex time-frequency coefficients of epidurally recorded responses to acoustic stimuli in rats. During the stimulus, changes in mean, variance, and phase tended to co-occur. After the stimulus, there was a small, low-frequency offset response in the mean and modest, prolonged desynchronization in the alpha band. Simulations showed that trial-by-trial variability in the mean can account for most of the variance and phase changes observed during the stimulus. This variability was state dependent, with smallest variability during periods of greatest arousal. Our data suggest that cortical responses to auditory stimuli reflect variable inputs to the cortical network. These analyses suggest that caution should be exercised when interpreting variance and phase changes in terms of top-down cortical processing.

scholarly journals An Investigation into Error Source Identification of Machine Tools Based on Time-Frequency Feature Extraction

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Dongju Chen ◽  
Shuai Zhou ◽  
Lihua Dong ◽  
Jinwei Fan
Keyword(s):  
Machine Tool ◽  
Frequency Domain ◽  
Surface Topography ◽  
High Frequency ◽  
Low Frequency ◽  
Frequency Signal ◽  
High Frequency Signal ◽  
Time Frequency ◽  
Cross Correlation Analysis ◽  
Correlation Analysis Method

This paper presents a new identification method to identify the main errors of the machine tool in time-frequency domain. The low- and high-frequency signals of the workpiece surface are decomposed based on the Daubechies wavelet transform. With power spectral density analysis, the main features of the high-frequency signal corresponding to the imbalance of the spindle system are extracted from the surface topography of the workpiece in the frequency domain. With the cross-correlation analysis method, the relationship between the guideway error of the machine tool and the low-frequency signal of the surface topography is calculated in the time domain.

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