Strength Of Phase Synchronization Research Articles

Optimizing phase variability threshold for automated synchrogram analysis of cardiorespiratory interactions in amateur cyclists.

We propose a procedure suitable for automated synchrogram analysis for setting the threshold below which phase variability between two marker event series is of such a negligible amount that the null hypothesis of phase desynchronization can be rejected. The procedure exploits the principle of maximizing the likelihood of detecting phase synchronization epochs and it is grounded on a surrogate data approach testing the null hypothesis of phase uncoupling. The approach was applied to assess cardiorespiratory phase interactions between heartbeat and inspiratory onset in amateur cyclists before and after 11-week inspiratory muscle training (IMT) at different intensities and compared to a more traditional approach to set phase variability threshold. The proposed procedure was able to detect the decrease in cardiorespiratory phase locking strength during vagal withdrawal induced by the modification of posture from supine to standing. IMT had very limited effects on cardiorespiratory phase synchronization strength and this result held regardless of the training intensity. In amateur athletes training, the inspiratory muscles did not limit the decrease in cardiorespiratory phase synchronization observed in the upright position as a likely consequence of the modest impact of this respiratory exercise, regardless of its intensity, on cardiac vagal control. This article is part of the theme issue 'Advanced computation in cardiovascular physiology: new challenges and opportunities'.

Increasing Local Excitability of Brainstem Respiratory Nuclei Reveals a Distributed Network Underlying Respiratory Motor Pattern Formation.

The core circuit of the respiratory central pattern generator (rCPG) is located in the ventrolateral medulla, especially in the pre-Bötzinger complex (pre-BötC) and the neighboring Bötzinger complex (BötC). To test the hypothesis that this core circuit is embedded within an anatomically distributed pattern-generating network, we investigated whether local disinhibition of the nucleus tractus solitarius (NTS), the Kölliker-Fuse nuclei (KFn), or the midbrain periaqueductal gray area (PAG) can similarly affect the respiratory pattern compared to disinhibition of the pre-BötC/BötC core. In arterially-perfused brainstem preparations of rats, we recorded the three-phase respiratory pattern (inspiration, post-inspiration and late-expiration) from phrenic and vagal nerves before and after bilateral microinjections of the GABA(A)R antagonist bicuculline (50 nl, 10 mM). Local disinhibition of either NTS, pre-BötC/BötC, or KFn, but not PAG, triggered qualitatively similar disruptions of the respiratory pattern resulting in a highly significant increase in the variability of the respiratory cycle length, including inspiratory and expiratory phase durations. To quantitatively analyze these motor pattern perturbations, we measured the strength of phase synchronization between phrenic and vagal motor outputs. This analysis showed that local disinhibition of all brainstem target nuclei, but not the midbrain PAG, significantly decreased the strength of phase synchronization. The convergent perturbations of the respiratory pattern suggest that the rCPG expands rostrally and dorsally from the designated core but does not include higher mid-brain structures. Our data also suggest that excitation-inhibition balance of respiratory network synaptic interactions critically determines the network dynamics that underlie vital respiratory rhythm and pattern formation.

Excitation-inhibition balance regulates the patterning of spinal and cranial inspiratory motor outputs in rats in situ

Spinal phrenic nerve activity (PNA) drives the diaphragm but cranial hypoglossal nerve activity (HNA) also expresses synchronous activity during inspiration. Here, we investigated the effects of local disinhibition (bilateral microinjections of bicuculline) of the nucleus tractus solitarius (NTS), the pre-Bötzinger complex and Bötzinger complex core circuit (pre-BötC/BötC) and the Kölliker-Fuse nuclei (KFn) on the synchronization of PNA and HNA in arterially-perfused brainstem preparations of rats. To quantitatively analyze the bicuculline effects on a putatively distributed inspiratory central pattern generator (i-CPG), we quantified the phase synchronization properties between PNA and HNA. The analysis revealed that bicuculline-evoked local disinhibition significantly reduced the strength of phase synchronization between PNA and HNA at any target site. However, the emergence of desynchronized HNA following disinhibition was more prevalent after NTS or pre-BötC/BötC microinjections compared to the KFn. We conclude that the primary i-CPG is located in a distributed medullary circuit whereas pontine contributions are restricted to synaptic gating of synchronous HNA and PNA.

Modeling Oscillatory Phase and Phase Synchronization With Neuronal Excitation and Input Strength in Cortical Network

Neuronal oscillatory phase is suggested to be associated with feature coding, carrying information for stimulus identity and neuronal activation, while phase synchronization is indicated to be correlated with signal routing, establishing flexible communication structures for neuronal interactions. Recent electrophysiological and computational studies have revealed that oscillatory phase has close relationships with neuronal excitation and input stimulus. To simulate and further investigate these issues, we simulated orientation columns with a spiking neural network and performed spectral computations according to physiological experiments. Besides, six network activity states, pre-stimulus, and stimulus periods were introduced in our simulation for both independent and comparative analyses. The simulation results demonstrated that gamma band neuronal oscillations existed in the network and even emerged during pre-stimulus period. An input stimulus orientation, if approximately preferred, could produce smaller and more concentrated oscillatory phases, but relatively stronger phase synchronization. In particular, the oscillatory phase and phase synchronization had quantifiable relationships with neuronal excitation and input strength. With the network activity state transforming gradually from strong oscillation to non-oscillation, the oscillatory phase became more and more scattered and the strength of phase synchronization declined significantly. Their relationships with neuronal excitation and input strength became increasingly unstable, and finally collapsed.

The pairwise phase consistency in cortical network and its relationship with neuronal activation

Gamma-band neuronal oscillation and synchronization with the range of 30-90 Hz are ubiquitous phenomenon across numerous brain areas and various species, and correlated with plenty of cognitive functions. The phase of the oscillation, as one aspect of CTC (Communication through Coherence) hypothesis, underlies various functions for feature coding, memory processing and behaviour performing. The PPC (Pairwise Phase Consistency), an improved coherence measure, statistically quantifies the strength of phase synchronization. In order to evaluate the PPC and its relationships with input stimulus, neuronal activation and firing rate, a simplified spiking neuronal network is constructed to simulate orientation columns in primary visual cortex. If the input orientation stimulus is preferred for a certain orientation column, neurons within this corresponding column will obtain higher firing rate and stronger neuronal activation, which consequently engender higher PPC values, with higher PPC corresponding to higher firing rate. In addition, we investigate the PPC in time resolved analysis with a sliding window.

Neural oscillations as a bridge between glutamatergic system and emotional behaviors in simulated microgravity-induced mice

This study aims to investigate if neural oscillations can play a role as a bridge between the alteration of glutamatergic system and emotional behaviors in simulated microgravity (SM) mice. Adult male C57BL/6J mice were randomly divided into two groups: SM and control groups. The animal model was established by hindlimb unloading (HU). The mice were exposed to HU continued for 14days. Weight and sucrose consumption were measured. The degree of anxious and depressive was evaluated by Open field test and Elevated plus maze test. Local field potentials were recorded in the hippocampal perforant path (PP) and dentate gyrus (DG) regions. The NMDAR2A/2B (NR2A/2B) subunits expression and glutamate level were measured by Western and high performance liquid chromatography (HPLC), respectively. After 14days, SM mice exhibited depressive-like and anxiety-like behaviors, while the expression of NR2A/2B subunits and the glutamate level were significantly decreased in the SM group. Moreover, the power distribution of theta (3–8Hz) was decreased by HU, which further significantly attenuated the identical-frequency strength of phase synchronization and the neural information flow at theta rhythm on the PP-DG pathway. The theta-gamma phase synchronization strength was also significantly reduced by HU. The data imply that the neural oscillations measurements is a sign of the emotional behaviors impairment and the glutamatergic system change induced by HU.

Genuine and Spurious Phase Synchronization Strengths during Consciousness and General Anesthesia

Spectral content in a physiological dataset of finite size has the potential to produce spurious measures of coherence. This is especially true for electroencephalography (EEG) during general anesthesia because of the significant alteration of the power spectrum. In this study we quantitatively evaluated the genuine and spurious phase synchronization strength (PSS) of EEG during consciousness, general anesthesia, and recovery. A computational approach based on the randomized data method was used for evaluating genuine and spurious PSS. The validity of the method was tested with a simulated dataset. We applied this method to the EEG of normal subjects undergoing general anesthesia and investigated the finite size effects of EEG references, data length and spectral content on phase synchronization. The most influential factor for genuine PSS was the type of EEG reference; the most influential factor for spurious PSS was the spectral content. Genuine and spurious PSS showed characteristic temporal patterns for each frequency band across consciousness and anesthesia. Simultaneous measurement of both genuine and spurious PSS during general anesthesia is necessary in order to avoid incorrect interpretations regarding states of consciousness.

Analysis of a phase synchronized functional network based on the rhythm of brain activities**Project supported by the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 30800242).yCorresponding author. E-mail: libin@uestc.edu.cn

Rhythm of brain activities represents oscillations of postsynaptic potentials in neocortex, therefore it can serve as an indicator of the brain activity state. In order to check the connectivity of brain rhythm, this paper develops a new method of constructing functional network based on phase synchronization. Electroencephalogram (EEG) data were collected while subjects looking at a green cross in two states, performing an attention task and relaxing with eyes-open. The EEG from these two states was filtered by three band-pass filters to obtain signals of theta (4–7 Hz), alpha (8–13 Hz) and beta (14–30 Hz) bands. Mean resultant length was used to estimate strength of phase synchronization in three bands to construct networks of both states, and mean degree K and cluster coefficient C of networks were calculated as a function of threshold. The result shows higher cluster coefficient in the attention state than in the eyes-open state in all three bands, suggesting that cluster coefficient reflects brain state. In addition, an obvious fronto-parietal network is found in the attention state, which is a well-known attention network. These results indicate that attention modulates the fronto-parietal connectivity in different modes as compared with the eyes-open state. Taken together this method is an objective and important tool to study the properties of neural networks of brain rhythm.

Error-Related Oscillations

The present study assesses the origins of reduction of error negativity (Ne) with advancing age in humans. Response-related potentials were recorded from young (mean age 22.5 years, n = 10) and older (mean age 58.3 years, n = 11) adults while they performed a four-choice reaction task (4CRT) in two modalities, auditory and visual. Trials from correct and error responses were analyzed separately for each modality. To achieve a reference-free evaluation, the current source density (CSD) of the signals was computed. RRPs were analyzed in the time-frequency (TF) domain by means of wavelet decomposition. Two TF components of RRPs from the delta (1.5–3.5 Hz) and theta (3.5–7 Hz) frequency ranges were assessed. The measured parameters were total power reflecting both the phase-locked and non-phase-locked activity, and phase-locking factor (PLF) reflecting the strength of phase-synchronization with stimulus, independent of magnitude. It was found that the total power of both the delta and theta TF components increased after errors in the two age groups, although this increase was more pronounced in young than older adults. Response-locked synchronization of delta responses also increased after errors, with this synchronizing ability being preserved in older subjects. What differentiated the error processing in the two age groups was the synchronization of theta oscillations with error responses, with this parameter being substantially reduced in older subjects. The results demonstrate that Ne reduction with aging is the result of an overall decrease in the power of delta and theta components, primarily of a decrease in the response-locked synchronization of theta oscillations after errors.

EIGENVALUE DECOMPOSITION AS A GENERALIZED SYNCHRONIZATION CLUSTER ANALYSIS

Motivated by the recent demonstration of its use as a tool for the detection and characterization of phase-shape correlations in multivariate time series, we show that eigenvalue decomposition can also be applied to a matrix of indices of bivariate phase synchronization strength. The resulting method is able to identify clusters of synchronized oscillators, and to quantify their strength as well as the degree of involvement of an oscillator in a cluster. Since for the case of a single cluster the method gives similar results as our previous approach, it can be seen as a generalized Synchronization Cluster Analysis, extending its field of application to more complex situations. The performance of the method is tested by applying it to simulation data.

Synchronization and modulation in the human cardiorespiratory system

We analyse phase and frequency synchronization in the human cardio-respiratory system. The method for analysis of noisy nonstationary bivariate data is applied to simultaneously measured cardiac and respiratory activity. Short epochs of phase and/or frequency locking between respiratory and cardiac rhythms are detected in healthy relaxed subjects (non-athletes). We reveal that the strength of phase synchronization is inversely related to the extent of respiratory modulation of the heart rate.