Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings

Siebenhuehner, Felix; Wang, Sheng H.; Arnulfo, Gabriele; Nobili, Lino; Palva, Satu

doi:10.1101/547638

Cited by 16 publications

(47 citation statements)

References 115 publications

(282 reference statements)

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“…However, the presented models assume homogenous circuit properties of the underlying model. Conversely, it has recently been shown that relaxing those parameters (such as allowing for recurrent connection strength and excitatory subcortical input to differ across cortical regions) can improve the fit to empirical fMRI (Wang et al, 2019). While-as discussed abovethe global view puts forward a common spatial organization across all timescales, the relaxed parameters proposed by Wang et al implicate the possibility that individual regions oscillate at different frequencies.…”

Section: Phase Couplingmentioning

confidence: 99%

Intrinsic connectome organization across temporal scales: New insights from cross-modal approaches

Sadaghiani

Wirsich

2020

Network Neuroscience

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The discovery of a stable, whole-brain functional connectivity organization that is largely independent of external events has drastically extended our view of human brain function. However, this discovery has been primarily based on functional magnetic resonance imaging (fMRI). The role of this whole-brain organization in fast oscillation-based connectivity as measured, for example, by electroencephalography (EEG) and magnetoencephalography (MEG) is only beginning to emerge. Here, we review studies of intrinsic connectivity and its whole-brain organization in EEG, MEG, and intracranial electrophysiology with a particular focus on direct comparisons to connectome studies in fMRI. Synthesizing this literature, we conclude that irrespective of temporal scale over four orders of magnitude, intrinsic neurophysiological connectivity shows spatial similarity to the connectivity organization commonly observed in fMRI. A shared structural connectivity basis and cross-frequency coupling are possible mechanisms contributing to this similarity. Acknowledging that a stable whole-brain organization governs long-range coupling across all timescales of neural processing motivates researchers to take “baseline” intrinsic connectivity into account when investigating brain-behavior associations, and further encourages more widespread exploration of functional connectomics approaches beyond fMRI by using EEG and MEG modalities.

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Section: Phase Couplingmentioning

confidence: 99%

Intrinsic connectome organization across temporal scales: New insights from cross-modal approaches

Sadaghiani

Wirsich

2020

Network Neuroscience

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“…Another approach suggested in [37] refers to the use of multimodal recordings (e.g. LFP, inter area PAC in which the slow and fast rhythms are generated in distinct oscillators reduce concerns on spurious coupling [37,39]. In this regard, it has been noted that one-to-one mapping between electrode measurement (i.e.…”

Section: Discussionmentioning

confidence: 99%

On the complex interplay between spectral harmonicity and different types of cross frequency couplings in non linear oscillators and biologically plausible neural network models

Dellavale

Velarde

Mato

et al. 2020

Preprint

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Background: Cross-frequency coupling (CFC) refers to the non linear interaction between oscillations in different frequency bands, and it is a rather ubiquitous phenomenon that has been observed in a variety of physical and biophysical systems. In particular, the coupling between the phase of slow oscillations and the amplitude of fast oscillations, referred as phase-amplitude coupling (PAC), has been intensively explored in the brain activity recorded from animals and humans. However, the interpretation of these CFC patterns remains challenging since harmonic spectral correlations characterizing non sinusoidal oscillatory dynamics can act as a confounding factor. Methods: Specialized signal processing techniques are proposed to address the complex interplay between spectral harmonicity and different types of CFC, not restricted only to PAC. For this, we provide an in-depth characterization of the Time Locked Index (TLI) as a novel tool aimed to efficiently quantify the harmonic content of noisy time series. It is shown that the proposed TLI measure is more robust and outperform traditional phase coherence metrics (e.g. Phase Locking Value) in several aspects. Results: We found that a non linear oscillator under the effect of additive noise can produce spurious CFC with low spectral harmonic content. On the other hand, two coupled oscillatory dynamics with independent fundamental frequencies can produce true CFC with high spectral harmonic content via a rectification mechanism or other post-interaction nonlinear processing mechanisms. These results reveal a complex interplay between CFC and harmonicity emerging from biologically plausible neural network models and more generic non linear and parametric oscillators, which in turn suggests that the harmonicity-CFC interplay is more complex than previously thought. Conclusions: We show that, contrary to what is usually assumed in the literature, the high harmonic content observed in non sinusoidal oscillatory dynamics, is neither sufficient nor necessary condition to interpret the associated CFC patterns as epiphenomenal. There is mounting evidence suggesting that the combination of multimodal recordings, specialized signal processing techniques and theoretical modeling is becoming a required step to completely understand CFC patterns observed in oscillatory rich dynamics of physical and biophysical systems.

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“…Moreover, they identified a flaw in the surrogate testing applied by Belluscio et al (). Recently, Siebenhühner et al () reported spontaneous cross‐frequency PPC within prefrontal, visual and sensorimotor cortices. The analysis was based on stereo‐electroencephalography and source‐reconstructed magnetoencephalography data and calculations were adjusted for the influence of non‐sinusoidal waveforms.…”

Section: Discussionmentioning

confidence: 99%

No evidence for spontaneous cross‐frequency phase–phase coupling in the human hippocampus

Rings

Cox

Rüber

et al. 2019

Eur J of Neuroscience

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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.

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Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings

Cited by 16 publications

References 115 publications

Intrinsic connectome organization across temporal scales: New insights from cross-modal approaches

Intrinsic connectome organization across temporal scales: New insights from cross-modal approaches

On the complex interplay between spectral harmonicity and different types of cross frequency couplings in non linear oscillators and biologically plausible neural network models

No evidence for spontaneous cross‐frequency phase–phase coupling in the human hippocampus

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