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

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.     

Dynamic processes in the human EEG

The possible mechanisms which determine the temporal dynamics of discrete narrow-band spectral components of human EEG recorded by a single electrode in the state of rest were analyzed. The dynamics of short-segment spectra was observed by application of Fast Fourier Transform (FFT) to 5-s EEG epochs successively shifted by 0.32 s. For each subject the matrices were formed and presented in a graphic mode. Matrix rows represented the number of points in each short-segment spectrum, and the columns represented the number of short-segment spectra. The columns reflect the amplitude dynamics of a given frequency, and power transition between the columns reflects the frequency dynamics. The most common type of the amplitude dynamics consisted in short (2-8 s) periods of stable activity of the discrete spectral components replaced by symmetrical bifurcation or confluence of spectral peaks. The obtained results suggest by the presence of both additive and multiplicative mechanisms of oscillatory interactions in the EEG. More detailed analysis of the amplitude-modulated EEG processes is provided by application of some additive features of the FFT to both EEG and computer-simulated signals.     

Technique for the quantification of transient quadratic phase couplings between heart rate components.

A technique for the time-variant analysis of quadratic phase coupling (QPC) in heart rate data is introduced and tested in 6 human neonates during quiet sleep. The set up of the approach is based up on the assumption that QPCs in the heart rate variability (HRV) are related to amplitude modulation effects. The application of the biamplitude deals with the detection of the coupling pattern and the bicoherence is used for the statistical quantification of coupling. By means of the results of bispectral analysis the time-variant processing has been adapted. The frequency-selective complex demodulation of the HRV leads to the envelope of the respiratory sinus arrhythmia (RSA), this has been used as one input for a time-variant coherence analysis. The other input is the low-pass filtered 10-second-rhythm of the HRV. A time-continuous quantification of the QPC, caused by amplitude modulation (10-second-rhythm modulates the RSA), is possible using this approach. According to our observed results in neonatal HRV both a phase co-ordination between the 10-second-rhythm and RSA as well as a non-linear coupling (amplitude modulation) between these HRV components can be seen.     

Analysis of EEG signals during epileptic and alcoholic states using AR modeling techniques

Electroencephalogram (EEG) analysis remains problematic due to limited understanding of the signal origin, which leads to the difficulty of designing evaluation methods. In spite of these shortcomings, the EEG is a valuable tool in the evaluation of some neurological disorders as well as in the evaluation of overall cerebral activity. In most studies, which use quantitative EEG analysis, the properties of measured EEG are computed by applying power spectral density (PSD) estimation for selected representative EEG samples. The sample for which the PSD is calculated is assumed to be stationary. This work deals with a comparative study of the PSD obtained from normal, epileptic and alcoholic EEG signals. The power density spectra were calculated using fast Fourier transform (FFT) by Welch's method, auto regressive (AR) method by Yule–Walker and Burg's method. The results are tabulated for these different classes of EEG signals.     

Noninvasive determination of baroreflex sensitivity in man by means of spectral analysis.

The spectral analysis technique was applied for noninvasive assessment of heart-rate baroreflex sensitivity (BRS). The coherence between fluctuation of blood pressure and heart rate at 0.1 Hz and at respiratory frequency is high. This fact enables the assessment of BRS by means of calculating the modulus (or gain) of the transfer function between variations in blood pressure and heart rate. The noninvasive continuous blood pressure registration according to Penáz was used. During voluntarily controlled breathing intervals, the amplitude of 0.1 Hz and respiratory peaks in the spectra of heart rate and blood pressure changed markedly. Nevertheless, the average sensitivity of the baroreflex (modulus) changed insignificantly. This result indicated that the stability of BRS can be advantageous for the use of BRS in clinical practice. The difference between the modulus at 0.1 Hz and at the breathing rate indicates that baroreflex is only one of the factors causing respiratory arrhythmia. We also compared the determination of BRS by spectral analysis with the following alternative method: both lower extremities were occluded for 5 minutes. The release of pressure in the occluding cuffs decreased blood pressure which was followed by a baroreceptor-mediated increase of heart rate. Both methods correlated, but more detailed analysis revealed the role of the low pressure receptors in BRS determined by spectral analysis.     

Medullary lateral tegmental field: control of respiratory rate and vagal lung inflation afferent influences on sympathetic nerve discharge

We used spectral analysis and event-triggered averaging to determine the effects of chemical inactivation of the medullary lateral tegmental field (LTF) on 1) the relationship of intratracheal pressure (ITP, an index of vagal lung inflation afferent activity) to sympathetic nerve discharge (SND) and phrenic nerve activity (PNA) and 2) central respiratory rate in paralyzed, artificially ventilated dial-urethane-anesthetized cats. ITP-SND coherence value at the frequency of artificial ventilation was significantly (P<0.05; n=18) reduced from 0.73+/-0.04 (mean+/-SE) to 0.24+/-0.04 after bilateral microinjection of muscimol into the LTF. Central respiratory rate was unexpectedly increased in 12 of these experiments (0.28+/-0.03 vs. 0.95+/-0.25 Hz). The ITP-PNA coherence value was variably affected by chemical inactivation of the LTF. It was unchanged when central respiratory rate was also not altered, decreased when respiratory rate was increased above the rate of artificial ventilation, and increased when respiratory rate was raised from a value below the rate of artificial ventilation to the same frequency as the ventilator. Chemical inactivation of the LTF increased central respiratory rate in four of six vagotomized cats but did not significantly affect the PNA-SND coherence value. These data demonstrate that the LTF 1) plays a critical role in mediating the effects of vagal lung inflation afferents on SND but not PNA, 2) helps maintain central respiratory rate in the physiological range, but 3) is not involved in the coupling of central respiratory and sympathetic circuits.     

Comparison of different methods of time shift measurement in EEG

Digital signal processing techniques are often used for measurement of small time shifts between EEG signals. In our work we tested properties of linear cross-correlation and phase/coherence method. The last mentioned method was used in two versions. The first version used fast Fourier transform (FFT) algorithm and the second was based on autoregressive modeling with fixed or adaptive model order. Methods were compared on several testing signals mimicking real EEG signals. The accuracy index for each method was computed. Results showed that for long signal segments all methods bring comparably good results. Accuracy of FFT phase/coherence method significantly decreased when very short segments were used and also decreased with an increasing level of the additive noise. The best results were obtained with autoregressive version of phase/coherence. This method is more reliable and may be used with high accuracy even in very short signals segments and it is also resistant to additive noise.     

AutoTT: Automated Detection and Analysis of T-Tubule Architecture in Cardiomyocytes

Cardiac transverse (T)-tubules provide a specialized structure for synchronization and stabilization of sarcoplasmic reticulum Ca²⁺ release in healthy cardiomyocytes. The application of laser scanning confocal microscopy and the use of fluorescent lipophilic membrane dyes have boosted the discoveries that T-tubule remodeling is a significant factor contributing to cardiac contractile dysfunction. However, the analysis and quantification of the remodeling of T-tubules have been a challenge and remain inconsistent among different research laboratories. Fast Fourier transformation (FFT) is the major analysis method applied to calculate the spatial frequency spectrum, which is used to represent the regularity of T-tubule systems. However, this approach is flawed because the density of T-tubules as well as non-T-tubule signals in the images influence the spectrum power generated by FFT. Preprocessing of images and topological architecture extracting is necessary to remove non-T-tubule noise from the analysis. In addition, manual analysis of images is time consuming and prone to errors and investigator bias. Therefore, we developed AutoTT, an automated analysis program that incorporates image processing, morphological feature extraction, and FFT analysis of spectrum power. The underlying algorithm is implemented in MATLAB (The MathWorks, Natick, MA). The program outputs the densities of transversely oriented T-tubules and longitudinally oriented T-tubules, power spectrum of the overall T-tubule systems, and averaged spacing of T-tubules. We also combined the density and regularity of T-tubules to give an index of T-tubule integrity (TT_int), which provides a global evaluation of T-tubule alterations. In summary, AutoTT provides a reliable, easy to use, and fast approach for analyzing myocyte T-tubules. This program can also be applied to measure the density and integrity of other cellular structures.     

AutoTT: Automated Detection and Analysis of T-Tubule Architecture in Cardiomyocytes

Cardiac transverse (T)-tubules provide a specialized structure for synchronization and stabilization of sarcoplasmic reticulum Ca²⁺ release in healthy cardiomyocytes. The application of laser scanning confocal microscopy and the use of fluorescent lipophilic membrane dyes have boosted the discoveries that T-tubule remodeling is a significant factor contributing to cardiac contractile dysfunction. However, the analysis and quantification of the remodeling of T-tubules have been a challenge and remain inconsistent among different research laboratories. Fast Fourier transformation (FFT) is the major analysis method applied to calculate the spatial frequency spectrum, which is used to represent the regularity of T-tubule systems. However, this approach is flawed because the density of T-tubules as well as non-T-tubule signals in the images influence the spectrum power generated by FFT. Preprocessing of images and topological architecture extracting is necessary to remove non-T-tubule noise from the analysis. In addition, manual analysis of images is time consuming and prone to errors and investigator bias. Therefore, we developed AutoTT, an automated analysis program that incorporates image processing, morphological feature extraction, and FFT analysis of spectrum power. The underlying algorithm is implemented in MATLAB (The MathWorks, Natick, MA). The program outputs the densities of transversely oriented T-tubules and longitudinally oriented T-tubules, power spectrum of the overall T-tubule systems, and averaged spacing of T-tubules. We also combined the density and regularity of T-tubules to give an index of T-tubule integrity (TT_int), which provides a global evaluation of T-tubule alterations. In summary, AutoTT provides a reliable, easy to use, and fast approach for analyzing myocyte T-tubules. This program can also be applied to measure the density and integrity of other cellular structures.     

Inhibition of heart rate variability during sleep in humans by 6700 K pre-sleep light exposure

Two different spectral analyses of heart rate (HR) variability (HRV) were performed on seven young male subjects to evaluate the effects of different color temperatures of light exposure (6700 K, 5000 K, 3000 K) before sleep on cardiac vagal activity. In investigating HRV, we used an ordinary fast Fourier transform (FFT) and coarse graining spectral analysis (CGSA), which selectively extracts random fractal components from a given time series. The results showed that suppressions of HR during sleep after 6700 K light exposure were more inhibited than the other two lighting conditions. Increases in high-frequency (HF) components of HRV during sleep were also inhibited by 6700 K pre-sleep lighting. These results indicate that pre-sleep exposure to light of a higher color temperature may inhibit the enhancement of cardiac vagal activity during sleep. Moreover, significant HF alterations were shown in fractal-free HF (not in ordinary HF) components by CGSA. Because the HF component originates from respiratory sinus arrhythmia with periodical fluctuations, CGSA may be an appropriate approach for HRV evaluation during sleep.     

Wavelet and Fourier analysis of ventricular and main arteries pulsations in anesthetized dogs

The purpose of this study was to characterize time-frequency behavior using the Continuous Wavelet Transform (CWT) and Fast Fourier Transform (FFT) to analyze ventricular and arterial pressure signals from anesthetized mongrel dogs. Both ventricular and arterial pressure pulsations were recorded using catheter-tip manometers and the CWT was applied to these signals to obtain module coefficients, associated contours, and the 3-D representation of these modules. FFT was applied to obtain the Fourier spectrum. The mathematical analysis of the cardiovascular pressure pulsations permitted the identification of the evolution of the frequency components for the aortic and pulmonary valve functions as well as the intra-ventricular and respiratory influences on the cardiovascular dynamics. The CWT is a very sensitive and reliable procedure for determining the three-dimensional (time-frequency-amplitude) of the oscillatory phenomena during each cardiac cycle, providing more, although complementary, information than the spectral analysis obtained with the FFT. Thanks to the FFT, exact values in Hz could be found for the different events produced in each cycle, and thus the information provided by CWT could be related to the information provided by FFT. The combination of both mathematical methodologies permitted identification of each component of the analyzed signals. The 3D representation allowed an easy comparison of the relative importance of the complex magnitudes in frequency for the different components of the pulsatile waves.     

Multiple coherence of cerebral blood flow velocity in humans

The coherence function has been used in transfer function analysis of dynamic cerebral autoregulation to assess the statistical significance of spectral estimates of gain and phase frequency response. Interpretation of the coherence function and choice of confidence limits has not taken into account the intrinsic nonlinearity represented by changes in cerebrovascular resistance due to vasomotor activity. For small spontaneous changes in arterial blood pressure (ABP), the relationship between ABP and cerebral blood flow velocity (CBFV) can be linearized, showing that corresponding changes in cerebrovascular resistance should be included as a second input variable. In this case, the standard univariate coherence function needs to be replaced by the multiple coherence, which takes into account the contribution of both inputs to explain CBFV variability. With the use of two different indicators of cerebrovascular resistance index [CVRI = ABP/CBFV and the resistance-area product (RAP)], multiple coherences were calculated for 42 healthy control subjects, aged 20 to 40 yr (28 +/- 4.6 yr, mean +/- SD), at rest in the supine position. CBFV was measured in both middle cerebral arteries, and ABP was recorded noninvasively by finger photoplethysmography. Results for the ABP + RAP inputs show that the multiple coherence of CBFV for frequencies <0.05 Hz is significantly higher than the corresponding values obtained for univariate coherence (P < 10(-5)). Corresponding results for the ABP + CVRI inputs confirm the principle of multiple coherence but are less useful due to the interdependence between CVRI, ABP, and CBFV. The main conclusion is that values of univariate coherence between ABP and CBFV should not be used to reject spectral estimates of gain and phase, derived from small fluctuations in ABP, because the true explained power of CBFV in healthy subjects is much higher than what has been usually predicted by the univariate coherence functions.     

基于时间机理与部位机理整合的鲁棒性语音信号表达

传统语音信号谱特征的提取是基于ＦＦＴ 的能谱分析方法,在噪音环境情况下,对噪音的频谱成分与语音信号的频谱成分的处理采用“平均主义”的原则。也就是说噪音的频谱成分与语音信号的频谱成分占同等重要的地位。显然在噪音环境中这种处理方法会使噪音掩蔽掉语音信号的成分。在听觉系统中这种处理编码方式如同耳蜗滤波器的频率分析功能那样,也就是部位机理。实际上听觉系统对噪音和周期信号的处理不是“平均主义”原则,而是对周期信号敏感, 对噪音不敏感,听觉神经纤维通过神经脉冲发放的周期间隔来编码刺激信号, 这对应听觉处理机制中的时间编码方式。基于这两种处理机制,文中提出整合部位机理和时间机理的方法,这正是听觉的处理刺激的方式。这样处理的方法很好地结合了两种处理机制的优点,能有效地探测噪音环境中的语音信号     

Baroreflex stabilization of the double (pressure-rate) product at 0.05 Hz in conscious rabbits

The product of heart rate (HR) and systolic blood pressure (SBP), the double product (DP), is an indirect index of cardiac oxygen consumption. We used spectral analysis to test the hypothesis that baroreflex adjustments of HR stabilize the DP during spontaneous variations in SBP. SBP and HR were recorded by telemetry in five male conscious rabbits. HR and SBP power spectra each exhibited a low frequency peak at approximately 0.05 Hz that was associated with high (>0.5) spectral coherence and a positive phase relationship between SBP and HR (SBP leading). A prominent peak was absent in the spectra of their product, suggesting that SBP and HR interacted to reduce DP variability in this frequency region. In contrast, a prominent 0.05-Hz peak was present in the power spectrum of calculated surrogates of the DP in which reflex interactions between HR and SBP had been removed. Our results suggest that baroreflex adjustments of HR stabilize the DP during spontaneous low-frequency variations in SBP in conscious rabbits.     

Quantifying cardiac sympathetic and parasympathetic nervous activities using principal dynamic modes analysis of heart rate variability

The ratio between low-frequency (LF) and high-frequency (HF) spectral power of heart rate has been used as an approximate index for determining the autonomic nervous system (ANS) balance. An accurate assessment of the ANS balance can only be achieved if clear separation of the dynamics of the sympathetic and parasympathetic nervous activities can be obtained, which is a daunting task because they are nonlinear and have overlapping dynamics. In this study, a promising nonlinear method, termed the principal dynamic mode (PDM) method, is used to separate dynamic components of the sympathetic and parasympathetic nervous activities on the basis of ECG signal, and the results are compared with the power spectral approach to assessing the ANS balance. The PDM analysis based on the 28 subjects consistently resulted in a clear separation of the two nervous systems, which have similar frequency characteristics for parasympathetic and sympathetic activities as those reported in the literature. With the application of atropine, in 13 of 15 supine subjects there was an increase in the sympathetic-to-parasympathetic ratio (SPR) due to a greater decrease of parasympathetic than sympathetic activity (P=0.003), and all 13 subjects in the upright position had a decrease in SPR due to a greater decrease of sympathetic than parasympathetic activity (P<0.001) with the application of propranolol. The LF-to-HF ratio calculated by the power spectral density is less accurate than the PDM because it is not able to separate the dynamics of the parasympathetic and sympathetic nervous systems. The culprit is equivalent decreases in both the sympathetic and parasympathetic activities irrespective of the pharmacological blockades. These findings suggest that the PDM shows promise as a noninvasive and quantitative marker of ANS imbalance, which has been shown to be a factor in many cardiac and stress-related diseases.     

Chaotic Signatures of Heart Rate Variability and Its Power Spectrum in Health,Aging and Heart Failure

A paradox regarding the classic power spectral analysis of heart rate variability (HRV) is whether the characteristic high- (HF) and low-frequency (LF) spectral peaks represent stochastic or chaotic phenomena. Resolution of this fundamental issue is key to unraveling the mechanisms of HRV, which is critical to its proper use as a noninvasive marker for cardiac mortality risk assessment and stratification in congestive heart failure (CHF) and other cardiac dysfunctions. However, conventional techniques of nonlinear time series analysis generally lack sufficient sensitivity, specificity and robustness to discriminate chaos from random noise, much less quantify the chaos level. Here, we apply a ‘litmus test’ for heartbeat chaos based on a novel noise titration assay which affords a robust, specific, time-resolved and quantitative measure of the relative chaos level. Noise titration of running short-segment Holter tachograms from healthy subjects revealed circadian-dependent (or sleep/wake-dependent) heartbeat chaos that was linked to the HF component (respiratory sinus arrhythmia). The relative ‘HF chaos’ levels were similar in young and elderly subjects despite proportional age-related decreases in HF and LF power. In contrast, the near-regular heartbeat in CHF patients was primarily nonchaotic except punctuated by undetected ectopic beats and other abnormal beats, causing transient chaos. Such profound circadian-, age- and CHF-dependent changes in the chaotic and spectral characteristics of HRV were accompanied by little changes in approximate entropy, a measure of signal irregularity. The salient chaotic signatures of HRV in these subject groups reveal distinct autonomic, cardiac, respiratory and circadian/sleep-wake mechanisms that distinguish health and aging from CHF.     

延髓头端腹外侧区神经元电活动与心血管活动相干性的研究

本文分析了大鼠延头端腹外侧区（ＲＶＬＭ）神经元单位活动与心血管活动的相干性,观察了ＲＶＬＭ区神经元电 对电刺激中脑防御反应区的诱发反应,以及对压力感受性反射的反应,并用ＦＦＴ对ＲＶＬＭ区神经元自发单位放电和血压波进行频域的相干性分析,以判断是具有心节律。还分析了ＲＶＬＭ区单位放电变异性与心率变异性的相干性。结果显示：ＲＶＬＭ区大多数神经元对电刺激中脑防御反应区呈兴奋反应（６７％）,７０％神经元放电     

Equilibrating errors: reliable estimation of information transmission rates in biological systems with spectral analysis-based methods

Shannon’s seminal approach to estimating information capacity is widely used to quantify information processing by biological systems. However, the Shannon information theory, which is based on power spectrum estimation, necessarily contains two sources of error: time delay bias error and random error. These errors are particularly important for systems with relatively large time delay values and for responses of limited duration, as is often the case in experimental work. The window function type and size chosen, as well as the values of inherent delays cause changes in both the delay bias and random errors, with possibly strong effect on the estimates of system properties. Here, we investigated the properties of these errors using white-noise simulations and analysis of experimental photoreceptor responses to naturalistic and white-noise light contrasts. Photoreceptors were used from several insect species, each characterized by different visual performance, behavior, and ecology. We show that the effect of random error on the spectral estimates of photoreceptor performance (gain, coherence, signal-to-noise ratio, Shannon information rate) is opposite to that of the time delay bias error: the former overestimates information rate, while the latter underestimates it. We propose a new algorithm for reducing the impact of time delay bias error and random error, based on discovering, and then using that size of window, at which the absolute values of these errors are equal and opposite, thus cancelling each other, allowing minimally biased measurement of neural coding.     

Partial correlation analysis for the identification of synaptic connections

In this paper, we investigate the use of partial correlation analysis for the identification of functional neural connectivity from simultaneously recorded neural spike trains. Partial correlation analysis allows one to distinguish between direct and indirect connectivities by removing the portion of the relationship between two neural spike trains that can be attributed to linear relationships with recorded spike trains from other neurons. As an alternative to the common frequency domain approach based on the partial spectral coherence we propose a new statistic in the time domain. The new scaled partial covariance density provides additional information on the direction and the type, excitatory or inhibitory, of the connectivities. In simulation studies, we investigated the power and limitations of the new statistic. The simulations show that the detectability of various connectivity patterns depends on various parameters such as connectivity strength and background activity. In particular, the detectability decreases with the number of neurons included in the analysis and increases with the recording time. Further, we show that the method can also be used to detect multiple direct connectivities between two neurons. Finally, the methods of this paper are illustrated by an application to neurophysiological data from spinal dorsal horn neurons.     

Interhemispheric differences in the spectral power and coherence of EEG rhythms in children with autism spectrum disorders

Electroencephalographic examination of boys aged 4–9 years with autism spectrum disorders (ASDs) showed spectral power values and coherence in high-frequency bands (20–60 Hz) in various brain areas were higher than normal. Differences in spectral power were greater in the anterior areas of the left hemisphere; differences in coherence, in the right anterior and posterior areas. Interhemispheric differences typical of healthy subjects were absent in the children with ASDs. The spectral power of the θ rhythm was lower in autism, especially in the left hemisphere. The spectral power of the α rhythm in the autistic children was lower than normal, especially in the posterior areas of the left hemisphere. The μ rhythm was higher than normal in spectral power and was localized in the right, rather than left, anterior areas. The children were examined again after corrective procedures. The α-rhythm spectral power increased (became closer to the norm) in the left posterior areas, while the γ-rhythm spectral power decreased (became closer to the norm) in the right anterior areas in some of the autistic children. The electrophysiological changes were associated with improved psychological testing results, especially in nonverbal measures.