The comodulation measure of neuronal oscillations with general harmonic wavelet bicoherence and application to sleep analysis

Interictal EEG features as computational biomarkers of West syndrome

BACKGROUND

West syndrome (WS) is a devastating epileptic encephalopathy with onset in infancy and early childhood. It is characterized by clustered epileptic spasms, developmental arrest, and interictal hypsarrhythmia on electroencephalogram (EEG). Hypsarrhythmia is considered the hallmark of WS, but its visual assessment is challenging due to its wide variability and lack of a quantifiable definition. This study aims to analyze the EEG patterns in WS and identify computational diagnostic biomarkers of the disease.

METHOD

Linear and non-linear features derived from EEG recordings of 31 WS patients and 20 age-matched controls were compared. Subsequently, the correlation of the identified features with structural and genetic abnormalities was investigated.

RESULTS

WS patients showed significantly elevated alpha-band activity (0.2516 vs. 0.1914, p < 0.001) and decreased delta-band activity (0.5117 vs. 0.5479, p < 0.001), particularly in the occipital region, as well as globally strengthened theta-band activity (0.2145 vs. 0.1655, p < 0.001) in power spectrum analysis. Moreover, wavelet-bicoherence analysis revealed significantly attenuated cross-frequency coupling in WS patients. Additionally, bi-channel coherence analysis indicated minor connectivity alterations in WS patients. Among the four non-linear characteristics of the EEG data (i.e., approximate entropy, sample entropy, permutation entropy, and wavelet entropy), permutation entropy showed the most prominent global reduction in the EEG of WS patients compared to controls (1.4411 vs. 1.5544, p < 0.001). Multivariate regression results suggested that genetic etiologies could influence the EEG profiles of WS, whereas structural factors could not.

SIGNIFICANCE

A combined global strengthening of theta activity and global reduction of permutation entropy can serve as computational EEG biomarkers for WS. Implementing these biomarkers in clinical practice may expedite diagnosis and treatment in WS, thereby improving long-term outcomes.

Age-dependent coupling characteristics of bilateral frontal EEG during desflurane anesthesia

Objectives.The purpose of this study is to investigate the age dependence of bilateral frontal electroencephalogram (EEG) coupling characteristics, and find potential age-independent depth of anesthesia monitoring indicators for the elderlies.Approach.We recorded bilateral forehead EEG data from 41 patients (ranged in 19-82 years old), and separated into three age groups: 18-40 years (n= 12); 40-65 years (n= 14), >65 years (n= 15). All these patients underwent desflurane maintained general anesthesia (GA). We analyzed the age-related EEG spectra, phase amplitude coupling (PAC), coherence and phase lag index (PLI) of EEG data in the states of awake, GA, and recovery.Main results.The frontal alpha power shows age dependence in the state of GA maintained by desflurane. Modulation index in slow oscillation-alpha and delta-alpha bands showed age dependence and state dependence in varying degrees, the PAC pattern also became less pronounced with increasing age. In the awake state, the coherence in delta, theta and alpha frequency bands were all significantly higher in the >65 years age group than in the 18-40 years age group (p< 0.05 for three frequency bands). The coherence in alpha-band was significantly enhanced in all age groups in GA (p< 0.01) and then decreased in recovery state. Notably, the PLI in the alpha band was able to significantly distinguish the three states of awake, GA and recovery (p< 0.01) and the results of PLI in delta and theta frequency bands had similar changes to those of coherence.Significance.We found the EEG coupling and synchronization between bilateral forehead are age-dependent. The PAC, coherence and PLI portray this age-dependence. The PLI and coherence based on bilateral frontal EEG functional connectivity measures and PAC based on frontal single-channel are closely associated with anesthesia-induced unconsciousness.

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.

Frequency modulation of cortical rhythmicity governs behavioral variability, excitability and synchrony of neurons in the visual cortex

Research in cognitive neuroscience has renewed the idea that brain oscillations are a core organization implicated in fundamental brain functions. Growing evidence reveals that the characteristic features of these oscillations, including power, phase and frequency, are highly non-stationary, fluctuating alongside alternations in sensation, cognition and behavior. However, there is little consensus on the functional implications of the instantaneous frequency variation in cortical excitability and concomitant behavior. Here, we capitalized on intracortical electrophysiology in the macaque monkey's visual area MT performing a visuospatial discrimination task with visual cues. We observed that the instantaneous frequency of the theta-alpha oscillations (4-13 Hz) is modulated among specific neurons whose RFs overlap with the cued stimulus location. Interestingly, we found that such frequency modulation is causally correlated with MT excitability at both scales of individual and ensemble of neurons. Moreover, studying the functional relevance of frequency variations indicated that the average theta-alpha frequencies foreshadow the monkey's reaction time. Our results also revealed that the neural synchronization strength alters with the average frequency shift in theta-alpha oscillations, suggesting frequency modulation is critical for mutually adjusting MTs' rhythms. Overall, our findings propose that theta-alpha frequency variations modulate MT's excitability, regulate mutual neurons' rhythmicity and indicate variability in behavior.

Wavelet-Based Biphase Analysis of Brain Rhythms in Automated Wake-Sleep Classification

Many studies in the field of sleep have focused on connectivity and coherence. Still, the nonstationary nature of electroencephalography (EEG) makes many of the previous methods unsuitable for automatic sleep detection. Time-frequency representations and high-order spectra are applied to nonstationary signal analysis and nonlinearity investigation, respectively. Therefore, combining wavelet and bispectrum, wavelet-based bi-phase (Wbiph) was proposed and used as a novel feature for sleep-wake classification. The results of the statistical analysis with emphasis on the importance of the gamma rhythm in sleep detection show that the Wbiph is more potent than coherence in the wake-sleep classification. The Wbiph has not been used in sleep studies before. However, the results and inherent advantages, such as the use of wavelet and bispectrum in its definition, suggest it as an excellent alternative to coherence. In the next part of this paper, a convolutional neural network (CNN) classifier was applied for the sleep-wake classification by Wbiph. The classification accuracy was 97.17% in nonLOSO and 95.48% in LOSO cross-validation, which is the best among previous studies on sleep-wake classification.

Age-dependent cross frequency coupling features from children to adults during general anesthesia

BACKGROUND

The frequency coupling characteristics in electroencephalogram (EEG) induced by anesthetics have been well studied in adults, but the investigation of the age-dependent cross frequency coupling features from children to adults is still lacking.

METHODS

We analyzed EEG signals recorded from pediatric to adult patients (n = 131), separated into six age groups: <1 year (n = 15), 1-3 years (n = 23), 3-6 years (n = 19), 6-12 years (n = 18), 12-18 years (n = 16), and 18-45 years (n = 40). Age related EEG power and cross frequency coupling analysis (phase amplitude coupling (PAC) and quadratic phase coupling) of data from maintenance of a surgical state of anesthesia (MOSSA) was conducted. Also, for patients of ages less than 6 years, we analyzed the performance of cross frequency coupling derived indices in distinguishing the states of wakefulness, MOSSA, and recovery of consciousness (ROC).

RESULTS

(1) During MOSSA, EEG power substantially increased with age from infancy to 3-6 years then decreased with age in the theta-gamma frequency bands. The infant group (<1 year) had the highest slow oscillation (SO) power among all age groups. (2) The distinct PAC pattern is absent in patients less than 1 year of age both in SO-alpha and delta-alpha frequency band coupling during propofol induced unconsciousness. The modulation index between delta and alpha oscillations in MOSSA increased with age. (3) Wavelet bicoherence derived indices reach their peaks in the 3-6 years group and then decrease with age growth. (4) The Diag_En index (normalized entropy of the diagonal bicoherence entries of the bicoherence matrix) performed the best at distinguishing different states for ages less than 6 years (p<0.05).

CONCLUSIONS

The combination of propofol induction and sevoflurane maintenance exhibited age-dependent EEG power spectra, PAC, and bicoherence, likely related to brain development. These observations suggest new rules for infant and child brain state monitoring during general anesthesia are needed.

Spectrum Degradation of Hippocampal LFP During Euthanasia

The hippocampal local field potential (LFP) exhibits a strong correlation with behavior. During rest, the theta rhythm is not prominent, but during active behavior, there are strong rhythms in the theta, theta harmonics, and gamma ranges. With increasing running velocity, theta, theta harmonics and gamma increase in power and in cross-frequency coupling, suggesting that neural entrainment is a direct consequence of the total excitatory input. While it is common to study the parametric range between the LFP and its complementing power spectra between deep rest and epochs of high running velocity, it is also possible to explore how the spectra degrades as the energy is completely quenched from the system. Specifically, it is unknown whether the 1/f slope is preserved as synaptic activity becomes diminished, as low frequencies are generated by large pools of neurons while higher frequencies comprise the activity of more local neuronal populations. To test this hypothesis, we examined rat LFPs recorded from the hippocampus and entorhinal cortex during barbiturate overdose euthanasia. Within the hippocampus, the initial stage entailed a quasi-stationary LFP state with a power-law feature in the power spectral density. In the second stage, there was a successive erosion of power from high- to low-frequencies in the second stage that continued until the only dominant remaining power was <20 Hz. This stage was followed by a rapid collapse of power spectrum toward the absolute electrothermal noise background. As the collapse of activity occurred later in hippocampus compared with medial entorhinal cortex, it suggests that the ability of a neural network to maintain the 1/f slope with decreasing energy is a function of general connectivity. Broadly, these data support the energy cascade theory where there is a cascade of energy from large cortical populations into smaller loops, such as those that supports the higher frequency gamma rhythm. As energy is pulled from the system, neural entrainment at gamma frequency (and higher) decline first. The larger loops, comprising a larger population, are fault-tolerant to a point capable of maintaining their activity before a final collapse.

Transcranial magnetic stimulation-evoked connectivity reveals modulation effects of repetitive transcranial magnetic stimulation on patients with disorders of consciousness

Several studies have investigated possible role of repetitive transcranial magnetic stimulation (rTMS) in patients with disorder of consciousness (DOC). But the details of patients' brain responses to the rTMS are yet to be disclosed. The aim of the study is to explore the neural electrical responses of DOC patients to rTMS modulation. DOC Patients [14 vegetative state, seven minimally conscious state (MCS)] and healthy subjects were enrolled and received one session of rTMS. The TMS-electroencephalogram was recorded at before and immediately after rTMS stimulation. TMS-evoked potentials as well as TMS-evoked connectivity were proposed to capture the effective connectivity alteration induced by rTMS. Significant changes of TMS-evoked potential were found in the healthy group but not in DOC patients. TMS-evoked connectivity was significantly enhanced by the rTMS in healthy and MCS groups. In addition, the enhancement was positively correlated with patients' Coma Recovery Scale-Revised scores. Global synchrony of the TMS-evoked connectivity matrix significantly enhanced by rTMS in the control and MCS groups but not in vegetative state patients. Furthermore, after rTMS stimulation, the similarity of TMS-evoked connectivity patterns between pairwise patients was significantly raised in MCS patients. But no significant changes were found in vegetative state patients. TMS-evoked connectivity reveals that rTMS can effectively modulate effective connectivity of MCS patients, but no evidence of changes in vegetative state patients.

Characterizing the orientation selectivity in V1 and V4 of macaques by quadratic phase coupling

OBJECTIVE

Orientation selectivity is one of the significant characteristics of neurons in the primary visual cortex (V1). Some neurons in extrastriate visual cortical areas also exhibit certain orientation selectivity. But it is still not well understood that how the orientation selectivity generates. Most previous studies about the orientation selectivity are based on the spike firing rate. However, the spikes are prone to be biased by the detection and sorting algorithms. Then, in this paper, the local field potential (LFP) is adopted to investigate the mechanism of orientation selectivity.

APPROACH

We used the quadratic phase coupling (QPC), which was calculated by wavelet bicoherence, to describe the characteristics of orientation selectivity available in V1 and V4. The raw wideband neural signals were recorded by two chronically implanted multi-electrode arrays, which were placed in V1 and V4 respectively in two macaques performing a selective visual attention task.

MAIN RESULTS

There is a strong correlation between the total bicoherence (TotalBic), which is a quantization for the overall QPC of frequency pairs in gamma band, and the grating orientation. Furthermore, the QPC distribution at the non-preferred orientation is mainly concentrated in the low frequencies (30-40 Hz) of gamma; while the QPC distribution at the preferred orientation concentrates in both the low frequencies and high frequencies (60-80 Hz) of gamma. In addition, the TotalBic of the gamma-band LFP between V1 and V4 varies with the grating orientations, indicating that the QPC is available in the feedforward link and the gamma-band LFP in V1 modulates the QPC in V4.

SIGNIFICANCE

The QPC reflects the orientations of the sinusoidal grating and describes the interaction of gamma-band LFP between different brain regions. Our results suggest that the QPC is an alternative avenue to explore the mechanism for generating orientation selectivity of visual neurons effectively.

Anaesthesia-dependent oscillatory EEG features in the super-elderly

OBJECTIVE

Although the characteristics of electroencephalograms (EEGs) have been reported to change with age, anaesthesia-dependent oscillatory features and reactivity of the super-elderly EEG to anaesthesia have not been examined in detail.

METHODS

Participants comprised 20 super-elderly patients (age; mean ± standard deviation, 87.1 ± 3.8 years) and 20 young adult patients (35.5 ± 8.5 years). At three levels of sevoflurane anaesthesia (minimum alveolar concentration [MAC] of 0.3, 0.7, and 1.4), oscillatory features of the frontal EEG were examined by analysing quadratic phase coupling (bicoherence) and power spectrum in α and δ-θ areas and compared in an anaesthesia-dependent manner, using the Friedman test.

RESULTS

Among super-elderly individuals, bicoherences in the δ-θ area showed anaesthesia-dependent increases (median [interquartile range], 12.9% [5.2%], 19.2% [9.1%], 23.3% [8.7%]; 0.3, 0.7, 1.4 MAC sevoflurane, p = 0.000), whereas bicoherence in the α area did not change at these different anaesthesia levels (11.2% [3.9%], 12.5% [4.4%], 14.1% [5.7%], respectively; p = 0.142), counter to the results found in young adult patients, where both δ-θ and α bicoherences changed with anaesthesia.

CONCLUSIONS

In the super-elderly, δ-θ bicoherence of EEG shows anaesthesia- dependent changes, whereas α activity remains small irrespective of anaesthesia level.

SIGNIFICANCE

Quantification of δ-θ bicoherence is a candidate for anaesthesia monitoring in the super-elderly.

Decoding Adaptive Visuomotor Behavior Mediated by Non-linear Phase Coupling in Macaque Area MT

The idea that a flexible behavior relies on synchronous neural activity within intra- and inter-associated cortical areas has been a matter of intense research in human and animal neuroscience. The neurophysiological mechanisms underlying this behavioral correlate of the synchronous activity are still unknown. It has been suggested that the strength of neural synchrony at the level of population is an important neural code to guide an efficient transformation of the sensory input into the behavioral action. In this study, we have examined the non-linear synchronization between neural ensembles in area MT of the macaque visual cortex by employing a non-linear cross-frequency coupling technique, namely bicoherence. We trained a macaque monkey to detect a brief change in the cued stimulus during a visuomotor detection task. The results show that the non-linear phase synchronization in the high-gamma frequency band (100-250 Hz) predicts the animal's reaction time. The strength of non-linear phase synchronization is selective to the target stimulus location. In addition, the non-linearity characteristics of neural synchronization are selectively modulated when the monkey covertly attends to the stimulus inside the neuron's receptive field. This additional evidence indicates that non-linear neuronal synchronization may be affected by a cognitive function like spatial attention. Our neural and behavioral observations reflect that two crucial processes may be involved in processing of visuomotor information in area MT: (I) a non-linear cortical process (measured by the bicoherence) and (II) a linear process (measured by the spectral power).

Methodological Considerations on the Use of Different Spectral Decomposition Algorithms to Study Hippocampal Rhythms

Local field potential (LFP) oscillations are primarily shaped by the superposition of postsynaptic currents. Hippocampal LFP oscillations in the 25- to 50-Hz range (“slow γ”) are proposed to support memory retrieval independent of other frequencies. However, θ harmonics extend up to 48 Hz, necessitating a study to determine whether these oscillations are fundamentally the same. We compared the spectral analysis methods of wavelet, ensemble empirical-mode decomposition (EEMD), and Fourier transform. EEMD, as previously applied, failed to account for the θ harmonics. Depending on analytical parameters selected, wavelet may convolve over high-order θ harmonics due to the variable time-frequency atoms, creating the appearance of a broad 25- to 50-Hz rhythm. As an illustration of this issue, wavelet and EEMD depicted slow γ in a synthetic dataset that only contained θ and its harmonics. Oscillatory transience cannot explain the difference in approaches as Fourier decomposition identifies ripples triggered to epochs of high-power, 120- to 250-Hz events. When Fourier is applied to high power, 25- to 50-Hz events, only θ harmonics are resolved. This analysis challenges the identification of the slow γ rhythm as a unique fundamental hippocampal oscillation. While there may be instances in which slow γ is present in the rat hippocampus, the analysis presented here shows that unless care is exerted in the application of EEMD and wavelet techniques, the results may be misleading, in this case misrepresenting θ harmonics. Moreover, it is necessary to reconsider the characteristics that define a fundamental hippocampal oscillation as well as theories based on multiple independent γ bands.

Electroencephalography quadratic phase self-coupling correlates with consciousness states and restoration in patients with disorders of consciousness

OBJECTIVE

The objective of this study was to explore the role for quadratic phase coupling within electroencephalography (EEG) oscillations in the diagnosis of consciousness and consciousness restoration for disorders of consciousness (DOC).

METHODS

Fifty-one DOC patients were enrolled in this study. For each patient, a Coma Recovery Scale-Revised (CRS-R) score and 20-min resting-state EEG were recorded. Consciousness recovery was assessed with a CRS-R score at a three-month follow-up. Twenty healthy subjects were included as controls. General harmonic wavelet transform-based bicoherence was used to quantify the quadratic phase coupling characteristics of the EEG oscillations.

RESULTS

Quadratic phase self-coupling (QPSC) at the delta (QPSC_delta), theta (QPSC_theta) and alpha (QPSC_alpha) bands were closely correlated with patient CRS-R scores. Particularly, the QPSC_theta value could significantly differentiate between vegetative state (VS) patients, minimally conscious state (MCS) patients and healthy control subjects. As compared to VS patients, patients with MCS had a lower QPSC_theta value on the left as well as a higher QPSC_alpha value in right frontal regions. The frontal QPSC_theta value showed significant differences between recovered and unrecovered patients.

CONCLUSION

QPSC characteristics could differentiate between consciousness states and show a predictive ability for the recovery of consciousness in DOC patients.

SIGNIFICANCE

Changes in QPSC accompany consciousness injury and restoration in DOC patients. A QPSC assessment is helpful in the diagnosis and prognosis of DOC patients.

Warped phase coherence: An empirical synchronization measure combining phase and amplitude information

The entrainment between weakly coupled nonlinear oscillators, as well as between complex signals such as those representing physiological activity, is frequently assessed in terms of whether a stable relationship is detectable between the instantaneous phases extracted from the measured or simulated time-series via the analytic signal. Here, we demonstrate that adding a possibly complex constant value to this normally null-mean signal has a non-trivial warping effect. Among other consequences, this introduces a level of sensitivity to the amplitude fluctuations and average relative phase. By means of simulations of Rössler systems and experiments on single-transistor oscillator networks, it is shown that the resulting coherence measure may have an empirical value in improving the inference of the structural couplings from the dynamics. When tentatively applied to the electroencephalogram recorded while performing imaginary and real movements, this straightforward modification of the phase locking value substantially improved the classification accuracy. Hence, its possible practical relevance in brain-computer and brain-machine interfaces deserves consideration.

Theta-gamma cascades and running speed

Oscillations in the hippocampal local field potential at theta and gamma frequencies are prominent during awake behavior and have demonstrated several behavioral correlates. Both oscillations have been observed to increase in amplitude and frequency as a function of running speed. Previous investigations, however, have examined the relationship between speed and each of these oscillation bands separately. Based on energy cascade models where "…perturbations of slow frequencies cause a cascade of energy dissipation at all frequency scales" (Buzsaki G. Rhythms of the Brain, 2006), we hypothesized that cross-frequency interactions between theta and gamma should increase as a function of speed. We examined these relationships across multiple layers of the CA1 subregion, which correspond to synaptic zones receiving different afferents. Across layers, we found a reliable correlation between the power of theta and the power of gamma, indicative of an amplitude-amplitude relationship. Moreover, there was an increase in the coherence between the power of gamma and the phase of theta, demonstrating increased phase-amplitude coupling with speed. Finally, at higher velocities, phase entrainment between theta and gamma increases. These results have important implications and provide new insights regarding how theta and gamma are integrated for neuronal circuit dynamics, with coupling strength determined by the excitatory drive within the hippocampus. Specifically, rather than arguing that different frequencies can be attributed to different psychological processes, we contend that cognitive processes occur across multiple frequency bands simultaneously with organization occurring as a function of the amount of energy iteratively propagated through the brain. NEW & NOTEWORTHY Often, the theta and gamma oscillations in the hippocampus have been believed to be a consequence of two marginally overlapping phenomena. This perspective, however, runs counter to an alternative hypothesis in which a slow-frequency, high-amplitude oscillation provides energy that cascades into higher frequency, lower amplitude oscillations. We found that as running speed increases, all measures of cross-frequency theta-gamma coupling intensify, providing evidence in favor of the energy cascade hypothesis.

Enhanced Gamma Activity and Cross-Frequency Interaction of Resting-State Electroencephalographic Oscillations in Patients with Alzheimer's Disease

Cognitive impairment, functional decline and behavioral symptoms that characterize Alzheimer’s disease (AD) are associated with perturbations of the neuronal network. The typical electroencephalographic (EEG) features in AD patients are increased delta or theta rhythm and decreased alpha or beta rhythm activities. However, considering the role of cross-frequency couplings in cognition, the alternation of cross-frequency couplings in AD patients is still obscure. This study aims to explore the interaction dynamics between different EEG oscillations in AD patients. We recorded the resting eye-closed EEG signals in 8 AD patients and 12 healthy volunteers. By analyzing the wavelet power spectrum and bicoherence of EEG, we found enhanced gamma rhythm power in AD patients in addition to the increased delta and decreased alpha power. Furthermore, an enhancement of the cross-frequency coupling strength between the beta/gamma and low-frequency bands was observed in AD patients compared to healthy controls (HCs). We propose that the pathological increase of ongoing gamma-band power might result from the disruption of the GABAergic interneuron network in AD patients. Furthermore, the cross-frequency overcouplings, which reflect the enhanced synchronization, might indicate the attenuated complexity of the neuronal network, and AD patients have to use more neural resources to maintain the resting brain state. Overall, our findings provide new evidence of the disturbance of the brain oscillation network in AD and further deepen our understanding of the central mechanisms of AD.

Spinal cord stimulation modulates frontal delta and gamma in patients of minimally consciousness state

Spinal cord stimulation (SCS) has been suggested as a therapeutic technique for treating patients with disorder of consciousness (DOC). Although studies have reported its benefits for patients, the underlying pathophysiological mechanisms remain unclear. The aim of this study was to measure the effects of SCS on the EEG of patients in a minimally conscious state (MCS), which would allow us to explore the possible workings underpinning of the approach. Resting state EEG was recorded before and immediately after SCS, using various frequencies (5Hz, 20Hz, 50Hz, 70Hz and 100Hz), for 11 patients in MCS. Relative power, coherence, S-estimator and bicoherence were calculated to assess the EEG changes. Five frequency bands (delta, theta, alpha, beta and gamma) and three regions (frontal, central and posterior) were divided in the calculation. The main findings of this study were that: (1) significantly altered relative power and synchronisation was found in delta and gamma bands after one SCS stimulation using 5Hz, 70Hz or 100Hz; (2) bicoherence showed that coupling within delta was significantly decreased after stimulation using 70Hz, while reduction of coupling between delta and gamma was found when using 5Hz and 100Hz. However, SCS of 20Hz, 50Hz and sham stimulation did not induce changes in any frequency band at any region. This study showed EEG evidence that SCS can modulate the brain function of MCS patients, speculatively by activating the formation-thalamus-cortex network.

Detecting Interactions between the Renal Autoregulation Mechanisms in Time and Space

OBJECTIVE

Our objective is to identify localized interactions between the renal autoregulation mechanisms over time.

METHODS

A time-varying phase-randomized wavelet bicoherence detector for quadratic phase coupling between tubuloglomerular feedback and the myogenic response is presented. Through simulations we show its ability to interrogate quadratic phase coupling. The method is applied to kidney blood flow and laser speckle imaging sequences of cortical perfusion from anesthetized rats before and after nonselective inhibition of nitric-oxide synthase.

RESULTS

Quadratic phase coupling in kidney blood flow data was present in four out of nine animals during the control period for 13.0 ± 5.6% (mean ± SD) of time and in five out of nine animals during inhibition of nitric-oxide synthase for 15.8 ± 8.2% of time. Approximately 60% of time-series extracted from laser speckle imaging pixels of the renal cortex showed significant quadratic phase coupling. Pixels with significant coupling had a median coupling length of 10.8 ± 2.2% and 12.1 ± 3.1% of time with the 95th percentile of pixels being coupled for 25.5 ± 4.4% and 30.9 ± 6.4% of time during control and inhibition of nitric-oxide synthase, respectively.

CONCLUSION

These results indicate quadratic phase coupling exists in short time intervals between tubuloglomerular feedback and the myogenic response and is detected more often in local renal perfusion signals than whole kidney blood flow in anesthetized rats.

SIGNIFICANCE

Combining the detector and laser speckle imaging provides identification of coordination between renal autoregulation mechanisms that is localized in time and space.

A wavelet bicoherence-based quadratic nonlinearity feature for translational axis condition monitoring

The translational axis is one of the most important subsystems in modern machine tools, as its degradation may result in the loss of the product qualification and lower the control precision. Condition-based maintenance (CBM) has been considered as one of the advanced maintenance schemes to achieve effective, reliable and cost-effective operation of machine systems, however, current vibration-based maintenance schemes cannot be employed directly in the translational axis system, due to its complex structure and the inefficiency of commonly used condition monitoring features. In this paper, a wavelet bicoherence-based quadratic nonlinearity feature is proposed for translational axis condition monitoring by using the torque signature of the drive servomotor. Firstly, the quadratic nonlinearity of the servomotor torque signature is discussed, and then, a biphase randomization wavelet bicoherence is introduced for its quadratic nonlinear detection. On this basis, a quadratic nonlinearity feature is proposed for condition monitoring of the translational axis. The properties of the proposed quadratic nonlinearity feature are investigated by simulations. Subsequently, this feature is applied to the real-world servomotor torque data collected from the X-axis on a high precision vertical machining centre. All the results show that the performance of the proposed feature is much better than that of original condition monitoring features.

Modulation of brain electroencephalography oscillations by electroacupuncture in a rat model of postincisional pain

The present study aimed to investigate how ongoing brain rhythmical oscillations changed during the postoperative pain and whether electroacupuncture (EA) regulated these brain oscillations when it relieved pain. We established a postincisional pain model of rats with plantar incision to mimic the clinical pathological pain state, tested the analgesic effects of EA, and recorded electroencephalography (EEG) activities before and after the EA application. By analysis of power spectrum and bicoherence of EEG, we found that in rats with postincisional pain, ongoing activities at the delta-frequency band decreased, while activities at theta-, alpha-, and beta-frequency bands increased. EA treatment on these postincisional pain rats decreased the power at high-frequency bands especially at the beta-frequency band and reversed the enhancement of the cross-frequency coupling strength between the beta band and low-frequency bands. After searching for the PubMed, our study is the first time to describe that brain oscillations are correlated with the processing of spontaneous pain information in postincisional pain model of rats, and EA could regulate these brain rhythmical frequency oscillations, including the power and cross-frequency couplings.

Cross-frequency coupling during isoflurane anaesthesia as revealed by electroencephalographic harmonic wavelet bicoherence

BACKGROUND

Fourier bicoherence has previously been applied to investigate phase coupling in the EEG in anaesthesia. However, there are significant theoretical limitations regarding its sensitivity in detecting transient episodes of inter-frequency coupling. Therefore, we used a recently developed wavelet bicoherence method to investigate the cross-frequency coupling in the EEG of patients under isoflurane anaesthesia; examining the relationship between the patterns of wavelet bicoherence and the isoflurane concentrations.

METHODS

We analysed a set of previously published EEG data, obtained from 29 patients who underwent elective abdominal surgery under isoflurane anaesthesia. Artifact-free, 1 min EEG segments at different isoflurane concentrations were extracted from each subject and the wavelet bicoherence calculated for all pairs of frequencies from 0.5 to 20 Hz.

RESULTS

Isoflurane caused two peaks in the α (6-13 Hz) and slow δ (<1 Hz) regions of the bicoherence matrix diagonal. Higher concentrations of isoflurane shifted the α peak to lower frequencies [11.3 (0.9) Hz at 0.3% to 7.1 (1.2) Hz at 1.5%], as has been previously observed in the power spectra. Outside the diagonal, we also found a significant α peak that was phase-coupled to the slow δ waves; higher concentrations of isoflurane shifted this peak to lower frequencies [10.8 (1.2) to 7.7 (0.7) Hz].

CONCLUSIONS

Isoflurane caused cross-frequency coupling between α and slow δ waves. Increasing isoflurane concentration slowed the α frequencies where the coupling had occurred. This phenomenon of α-δ coupling suggests that slow cortical oscillations organize the higher α band activity, which is consistent with other studies in natural sleep.