Cross-frequency Phase-phase Coupling Research Articles

Ictal ECG-based assessment of sudden unexpected death in epilepsy.

Previous case-control studies of sudden unexpected death in epilepsy (SUDEP) patients failed to identify ECG features (peri-ictal heart rate, heart rate variability, corrected QT interval, postictal heart rate recovery, and cardiac rhythm) predictive of SUDEP risk. This implied a need to derive novel metrics to assess SUDEP risk from ECG. We applied Single Spectrum Analysis and Independent Component Analysis (SSA-ICA) to remove artifact from ECG recordings. Then cross-frequency phase-phase coupling (PPC) was applied to a 20-s mid-seizure window and a contour of -3 dB coupling strength was determined. The contour centroid polar coordinates, amplitude (alpha) and angle (theta), were calculated. Association of alpha and theta with SUDEP was assessed and a logistic classifier for alpha was constructed. Alpha was higher in SUDEP patients, compared to non-SUDEP patients (p < 0.001). Theta showed no significant difference between patient populations. The receiver operating characteristic (ROC) of a logistic classifier for alpha resulted in an area under the ROC curve (AUC) of 94% and correctly classified two test SUDEP patients. This study develops a novel metric alpha, which highlights non-linear interactions between two rhythms in the ECG, and is predictive of SUDEP risk.

Multi-Granularity Analysis of Brain Networks Assembled With Intra-Frequency and Cross-Frequency Phase Coupling for Human EEG After Stroke.

Evaluating the impact of stroke on the human brain based on electroencephalogram (EEG) remains a challenging problem. Previous studies are mainly analyzed within frequency bands. This article proposes a multi-granularity analysis framework, which uses multiple brain networks assembled with intra-frequency and cross-frequency phase-phase coupling to evaluate the stroke impact in temporal and spatial granularity. Through our experiments on the EEG data of 11 patients with left ischemic stroke and 11 healthy controls during the mental rotation task, we find that the brain information interaction is highly affected after stroke, especially in delta-related cross-frequency bands, such as delta-alpha, delta-low beta, and delta-high beta. Besides, the average phase synchronization index (PSI) of the right hemisphere between patients with stroke and controls has a significant difference, especially in delta-alpha (p = 0.0186 in the left-hand mental rotation task, p = 0.0166 in the right-hand mental rotation task), which shows that the non-lesion hemisphere of patients with stroke is also affected while it cannot be observed in intra-frequency bands. The graph theory analysis of the entire task stage reveals that the brain network of patients with stroke has a longer feature path length and smaller clustering coefficient. Besides, in the graph theory analysis of three sub-stags, the more stable significant difference between the two groups is emerging in the mental rotation sub-stage (500–800 ms). These findings demonstrate that the coupling between different frequency bands brings a new perspective to understanding the brain's cognitive process after stroke.

No evidence for spontaneous cross-frequency phase-phase coupling in the human hippocampus.

Cross-frequency phase-phase coupling (PPC) has been suggested to play a role in cognitive processing and, in particular, in memory consolidation during sleep. Controversial results have been reported regarding the existence of spontaneous phase-phase coupling in the hippocampus. Here, we investigated this phenomenon in intracranial EEG recordings from the human hippocampus acquired during waking state and different sleep stages. We estimated the strength of interactions between different pairs of frequency bands and evaluated the statistical significance of findings using surrogates that build on different null hypotheses. Indications for spontaneous phase-phase coupling were only observed when testing with less rigorous surrogates. When requiring that all four surrogate tests be passed, however, there were no significant indications for phase-phase coupling. In conclusion, we did not detect evidence for spontaneous cross-frequency phase-phase coupling in the human hippocampus.

Using Contour Plots of Bicoherence to Illustrate and Investigate Cross-Frequency Coupling of EEG Oscillations

My 12/2017 SSRN e-paper investigated possible cross-frequency phase-phase coupling of scalp-recorded EEG signals. Essentially, the quadratic-coupling metric of harmonic wavelet bicoherence was applied to 1-hr blocks of data centered at identified seizures, with results presented in graphical form. That paper was motivated in part by earlier studies of delta-theta band and theta-gamma band couplings. The former studied correlations between delta-theta couplings and depth of anesthesia during surgery, using this metric; the latter demonstrated such theta-gamma couplings in rat hippocampus. In this paper MATLAB figures of contour plots of bicoherence were chosen to better illustrate and investigate cross-frequency phase-phase coupling of EEG oscillations. The graphical framework is a frequency vs. frequency matrix, 0.5-50 Hz, with colored contour plots of bicoherence, for frequency steps of 1 Hz. To demonstrate ‘proof of concept’ in a limited amount of space, some restrictions from the previous paper were made.

On cross-frequency phase-phase coupling between theta and gamma oscillations in the hippocampus.

Phase-amplitude coupling between theta and multiple gamma sub-bands is a hallmark of hippocampal activity and believed to take part in information routing. More recently, theta and gamma oscillations were also reported to exhibit phase-phase coupling, or n:m phase-locking, suggesting an important mechanism of neuronal coding that has long received theoretical support. However, by analyzing simulated and actual LFPs, here we question the existence of theta-gamma phase-phase coupling in the rat hippocampus. We show that the quasi-linear phase shifts introduced by filtering lead to spurious coupling levels in both white noise and hippocampal LFPs, which highly depend on epoch length, and that significant coupling may be falsely detected when employing improper surrogate methods. We also show that waveform asymmetry and frequency harmonics may generate artifactual n:m phase-locking. Studies investigating phase-phase coupling should rely on appropriate statistical controls and be aware of confounding factors; otherwise, they could easily fall into analysis pitfalls.

Cingulate-Hippocampus Coherence and Trajectory Coding in a Sequential Choice Task

Interactions between cortex and hippocampus are believed to play a role in the acquisition and maintenance of memories. Distinct types of coordinated oscillatory activity, namely at theta frequency, are hypothesized to regulate information processing in these structures. We investigated how information processing in cingulate cortex and hippocampus relates to cingulate-hippocampus coordination in a behavioral task in which rats choose from four possible trajectories according to a sequence. We found that the accuracy with which cingulate and hippocampal populations encode individual trajectories changes with the pattern of cingulate-hippocampal theta coherence over the course of a trial. Initial theta coherence at ~8 Hz during trial onsets lowers by ~1 Hz as animals enter decision stages. At these stages, hippocampus precedes cingulate in processing increased amounts of task-relevant information. We hypothesize that lower theta frequency coordinates the integration of hippocampal contextual information by cingulate neuronal populations, to inform choices in a task-phase-dependent manner.

Dysfunction of cross-frequency phase-phase coupling in primary dysmenorrhea: a resting magnetoencephalographic study

Cross-frequency synchronization between neuronal ensembles has been studied recently, which is related to coupling between neuronal oscillations of different frequency contents [1]. This study aimed at the investigation of how cross-frequency phase-phase coupling of local network during rest is modulated by pain experience. Ten primary dysmenorrhea (PDM) females suffering lower abdominal pain during menstrual phase and ten age-matched healthy females were enrolled. Three-minute eye-open resting magnetoencephalographic (MEG) signals of each individual during menstrual phase were recorded using a 306-channel MEG system. For each channel, synchronization value of cross-frequency coupling was estimated by calculating phase-locking statistics of phase differences between two frequency bands, including 2, 4, 8, 12, 16, 24, 32, and 40 Hz, respectively. The results of one-sample binomial test showed that in low alpha/beta (8 / 16 Hz) oscillations, the PDM group displayed coupling in the medial parietal area whereas no coupling in the control group (Figure 1(a)). On the other hand, coupling at the prefrontal area found in the NC group was not found in the PDM group. These two regions have been reported as part of resting state networks [2]. No difference of coupling between the PDM and control groups was found in other combinations of frequency pairs, for instance, high alpha/beta (Figure 1(b)) and beta/gamma (Figure 1(c)). Figure 1 Topography of different pairs of cross-frequency coupling between PDM and normal controls. The color represents significant level of phase-locking statistics at the respective channel for each group.