scholarly journals Multivariate Phase–Amplitude Cross-Frequency Coupling in Neurophysiological Signals

2012 ◽  
Vol 59 (1) ◽  
pp. 8-11 ◽  
Author(s):  
R. T. Canolty ◽  
C. F. Cadieu ◽  
K. Koepsell ◽  
R. T. Knight ◽  
J. M. Carmena
Keyword(s):  
Frequency Coupling ◽  
Phase Amplitude ◽  
Cross Frequency Coupling

scholarly journals Gamma Entrainment Improves Synchronization Deficits in Dementia Patients

2021 ◽  
Author(s):  
Mojtaba Lahijanian ◽  
Hamid Aghajan ◽  
Zahra Vahabi ◽  
Arshia Afzal
Keyword(s):  
Oscillatory Activity ◽  
Therapeutic Effects ◽  
Phase Coupling ◽  
Non Invasive ◽  
Temporal Phase ◽  
Dementia Patients ◽  
Frequency Coupling ◽  
Phase Amplitude ◽  
Cross Frequency Coupling

AbstractNon-invasive gamma entrainment has shown promising results in alleviating cognitive symptoms of Alzheimer’s disease in mice and humans. In this study, we examine improvements in the synchronization characteristics of the brain’s oscillations induced by 40Hz auditory stimulation based on electroencephalography data recorded from a group of dementia patients. We observed that when the quality of entrainment surpasses a certain level, several indicators of brain synchronization significantly improve. Specifically, the entrained oscillatory activity maintains temporal phase stability in the frontal, parietal, and occipital regions, and persistent spatial phase coupling between them. In addition, notable theta-gamma phase-amplitude coupling is observed in these areas. Interestingly, a high theta power at rest predicts the quality of entrainment. We identify differentiating attributes of temporal/spatial synchronization and cross-frequency coupling in the data of two groups with entrained and non-entrained responses which point to enhanced network synchronization caused by entrainment and can explain its potential therapeutic effects.

scholarly journals Shifted Phase of EEG Cross-Frequency Coupling in Individuals with Phelan-McDermid Syndrome

2020 ◽  
Author(s):  
Michael G Mariscal ◽  
Elizabeth Berry-Kravis ◽  
Joseph D Buxbaum ◽  
Lauren E Ethridge ◽  
Rajna Filip-Dhima ◽  
...  
Keyword(s):  
Repetitive Behavior ◽  
Rare Condition ◽  
Autism Spectrum ◽  
Typically Developing ◽  
Compulsive Behaviors ◽  
Oscillatory Power ◽  
Phase Bias ◽  
Frequency Coupling ◽  
Phase Amplitude ◽  
Cross Frequency Coupling

Abstract Background Phelan-McDermid Syndrome (PMS) is a rare condition caused by deletion or mutation of the SHANK3 gene. Individuals with PMS frequently present with intellectual disability, symptoms of autism spectrum disorder (ASD), and other neurodevelopmental challenges. Electroencephalography (EEG) can provide a window into network-level function in PMS. Methods Here, we analyze EEG data collected across multiple sites in individuals with PMS (n = 26) and typically developing individuals (n = 15). We quantify oscillatory power, phase-amplitude coupling strength, and phase bias, a measure of the phase of cross frequency coupling thought to reflect the balance of feedforward and feedback activity. Results We find individuals with PMS display increased phase bias (U = 3.841, p < 0.0005), predominantly over posterior electrodes. Most individuals with PMS demonstrate positive overall phase bias while most typically developing individuals demonstrate negative overall phase bias. Among individuals with PMS, strength of phase-amplitude coupling was associated with Sameness, Ritualistic, and Compulsive behaviors as measured by the Repetitive Behavior Scales-Revised (Beta= 0.545, p= 0.011). Conclusions Increased phase bias suggests potential circuit-level mechanisms underlying phenotype in PMS, offering opportunities for back-translation of findings into animal models and targeting in clinical trials.

scholarly journals Shifted phase of EEG cross-frequency coupling in individuals with Phelan-McDermid syndrome

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Michael. G. Mariscal ◽  
◽  
Elizabeth Berry-Kravis ◽  
Joseph D. Buxbaum ◽  
Lauren E. Ethridge ◽  
...  
Keyword(s):  
Repetitive Behavior ◽  
Rare Condition ◽  
Autism Spectrum ◽  
Gamma Phase ◽  
Typically Developing ◽  
Compulsive Behaviors ◽  
Phase Bias ◽  
Frequency Coupling ◽  
Phase Amplitude ◽  
Cross Frequency Coupling

Abstract Background Phelan-McDermid Syndrome (PMS) is a rare condition caused by deletion or mutation of the SHANK3 gene. Individuals with PMS frequently present with intellectual disability, autism spectrum disorder, and other neurodevelopmental challenges. Electroencephalography (EEG) can provide a window into network-level function in PMS. Methods Here, we analyze EEG data collected across multiple sites in individuals with PMS (n = 26) and typically developing individuals (n = 15). We quantify oscillatory power, alpha-gamma phase-amplitude coupling strength, and phase bias, a measure of the phase of cross frequency coupling thought to reflect the balance of feedforward (bottom-up) and feedback (top-down) activity. Results We find individuals with PMS display increased alpha-gamma phase bias (U = 3.841, p < 0.0005), predominantly over posterior electrodes. Most individuals with PMS demonstrate positive overall phase bias while most typically developing individuals demonstrate negative overall phase bias. Among individuals with PMS, strength of alpha-gamma phase-amplitude coupling was associated with Sameness, Ritualistic, and Compulsive behaviors as measured by the Repetitive Behavior Scales-Revised (Beta = 0.545, p = 0.011). Conclusions Increased phase bias suggests potential circuit-level mechanisms underlying phenotype in PMS, offering opportunities for back-translation of findings into animal models and targeting in clinical trials.

scholarly journals Dissociating harmonic and non-harmonic phase-amplitude coupling in the human brain

2020 ◽  
Author(s):  
Janet Giehl ◽  
Nima Noury ◽  
Markus Siegel
Keyword(s):  
Human Brain ◽  
Resting State ◽  
Higher Harmonics ◽  
Spectral Leakage ◽  
Harmonic Phase ◽  
Harmonic Signals ◽  
Cast Doubt ◽  
Frequency Coupling ◽  
Phase Amplitude ◽  
Cross Frequency Coupling

AbstractPhase-amplitude coupling (PAC) has been hypothesized to coordinate cross-frequency interactions of neuronal activity in the brain. However, little is known about the distribution of PAC across the human brain and the frequencies involved. Furthermore, it remains unclear to what extend PAC may reflect spurious cross-frequency coupling induced by physiological artifacts or rhythmic non-sinusoidal signals with higher harmonics. Here, we combined MEG, source-reconstruction and different measures of cross-frequency coupling to systematically characterize PAC across the resting human brain. We show that cross-frequency measures of phase-amplitude, phase-phase, and amplitude-amplitude coupling are all sensitive to signals with higher harmonics. In conjunction, these measures allow to distinguish harmonic and non-harmonic PAC. Based on these insights, we found no evidence for non-harmonic PAC in resting-state MEG. Instead, we found cortically and spectrally wide-spread PAC driven by harmonic signals. Furthermore, we show how physiological artifacts and spectral leakage cause spurious PAC across wide frequency ranges. Our result clarify how different measures of cross-frequency interactions can be combined to characterize PAC and cast doubt on the presence of prominent non-harmonic phase-amplitude coupling in human resting-state MEG.

scholarly journals A statistical framework to assess cross-frequency coupling while accounting for confounding analysis effects

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Jessica K Nadalin ◽  
Louis-Emmanuel Martinet ◽  
Ethan B Blackwood ◽  
Meng-Chen Lo ◽  
Alik S Widge ◽  
...  
Keyword(s):  
High Frequency ◽  
Statistical Power ◽  
Brain Activity ◽  
Low Frequency ◽  
Modeling Framework ◽  
Frequency Coupling ◽  
Phase Amplitude ◽  
Cross Frequency Coupling ◽  
Frequency Phase

Cross frequency coupling (CFC) is emerging as a fundamental feature of brain activity, correlated with brain function and dysfunction. Many different types of CFC have been identified through application of numerous data analysis methods, each developed to characterize a specific CFC type. Choosing an inappropriate method weakens statistical power and introduces opportunities for confounding effects. To address this, we propose a statistical modeling framework to estimate high frequency amplitude as a function of both the low frequency amplitude and low frequency phase; the result is a measure of phase-amplitude coupling that accounts for changes in the low frequency amplitude. We show in simulations that the proposed method successfully detects CFC between the low frequency phase or amplitude and the high frequency amplitude, and outperforms an existing method in biologically-motivated examples. Applying the method to in vivo data, we illustrate examples of CFC during a seizure and in response to electrical stimuli.

Cross-sensory cuing drives cross-frequency neural coupling, dramatically altering performance of a taxing visual-detection task

2012 ◽  
Vol 25 (0) ◽  
pp. 62
Author(s):  
John J. Foxe ◽  
Adam C. Snyder ◽  
Manuel R. Mercier ◽  
John S. Butler ◽  
Sophie Molholm ◽  
...  
Keyword(s):  
Target Detection ◽  
Visual Detection ◽  
Visual Target ◽  
Phase Detection ◽  
Perceptual Sensitivity ◽  
Attention Task ◽  
Neuronal Ensembles ◽  
Frequency Coupling ◽  
Phase Amplitude ◽  
Cross Frequency Coupling

Functional networks are comprised of neuronal ensembles bound through synchronization across multiple intrinsic oscillatory frequencies. Various coupled interactions between brain oscillators have been described (e.g., phase–amplitude coupling), but with little evidence that these interactions actually influence perceptual sensitivity. Here, electroencephalographic recordings were made during a sustained-attention task to demonstrate that cross-frequency coupling, driven by cross-sensory cuing, has significant consequences for perceptual outcomes (i.e., whether participants detect a near-threshold visual target). Our results reveal that phase-detection relationships at higher frequencies are entirely dependent on the phase of lower frequencies, such that higher frequencies alternate between periods when their phase is strongly predictive of visual-target detection and periods when their phase has no influence whatsoever. These data thus bridge the crucial gap between complex oscillatory phenomena and perceptual outcomes. Accounting for cross-frequency coupling between lower (i.e., delta and theta) and higher frequencies (e.g., beta and gamma), we show that visual-target detection fluctuates dramatically as a function of pre-stimulus phase, with performance swings of as much as 80%.

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