Phase-lags in large scale brain synchronization: Methodological considerations and in-silico analysis

Petkoski, Spase; Palva, J. Matias; Jirsa, Viktor K.

doi:10.1371/journal.pcbi.1006160

Cited by 75 publications

(153 citation statements)

References 80 publications

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“…To test this rigorously, we developed a generative four-population-Kuramoto model [71] for investigating the joint effects of within-and cross-frequency phase coupling (see Methods I). The model comprised of two "areas" that each contained two populations of weakly coupled oscillators; one at low frequency (LF) and another at high frequency (HF) so that fHF = 2·fLF, i.e., with the n:m ratio (hereafter defined as LF:HF ratio) of 1:2 (Fig 2a).…”

Section: Simulation Of Cfc and Spurious Interactions With Kuramoto Modelmentioning

confidence: 99%

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

Siebenhuehner

Wang

Arnulfo

et al. 2019

Preprint

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AbstractPhase synchronization of neuronal oscillations in specific frequency bands coordinates anatomically distributed neuronal processing and communication. Typically, oscillations and synchronization take place concurrently in many distinct frequencies, which serve separate computational roles in cognitive functions. While within-frequency phase synchronization has been studied extensively, less is known about the mechanisms that govern neuronal processing distributed across frequencies and brain regions. Such integration of processing between frequencies could be achieved via cross-frequency coupling (CFC), either by phase-amplitude coupling (PAC) or by n:m-cross-frequency phase synchrony (CFS). So far, studies have mostly focused on local CFC in individual brain regions, whereas the presence and functional organization of CFC between brain areas have remained largely unknown. We posit that inter-areal CFC may be essential for large-scale coordination of neuronal activity and investigate here whether genuine CFC networks are present in human resting-state brain activity.To assess the functional organization of CFC networks, we identified brain-wide CFC networks at meso-scale resolution from stereo-electroencephalography (SEEG) and at macro-scale resolution from source-reconstructed magnetoencephalography (MEG) data. We developed a novel graph-theoretical method to distinguish genuine CFC from spurious CFC that may arise from non-sinusoidal signals ubiquitous in neuronal activity. We show that genuine inter-areal CFC is present in human resting-state activity in both MEG and SEEG data. Both CFS and PAC networks coupled theta and alpha oscillations with higher frequencies in large-scale networks connecting anterior and posterior brain regions. CFS and PAC networks had distinct spectral patterns and opposing distribution of low- and high frequency network hubs, implying that they constitute distinct CFC mechanisms. The strength of CFS networks was also predictive of cognitive performance in a separate neuropsychological assessment. In conclusion, these results provide evidence for inter-areal CFS and PAC being two distinct mechanisms for coupling oscillations across frequencies in large-scale brain networks.

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Section: Simulation Of Cfc and Spurious Interactions With Kuramoto Modelmentioning

confidence: 99%

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

Siebenhuehner

Wang

Arnulfo

et al. 2019

Preprint

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“…These models do not include transmission delays, but exhibit exponents expected for a critical branching process. Less abstract analysis regarding the coexistence of critical and oscillatory dynamics must incorporate biologically relevant transmission delays to which neuronal oscillations are known to exhibit high sensitivity 75,76 .…”

Section: The Temporal Profile Of Neuronal Avalanches 15mentioning

confidence: 99%

The scale-invariant, temporal profile of neuronal avalanches in relation to cortical γ–oscillations

Miller

Plenz

2019

Preprint

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Miller et al.The temporal profile of neuronal avalanches 2 ABSTRACT Activity cascades are found in many complex systems. In the cortex, they arise in the form of neuronal avalanches which capture ongoing and evoked neuronal activities at many spatial and temporal scales. The scale-invariant nature of avalanches suggests that the brain is in a critical state, yet predictions from critical theory on the temporal unfolding of avalanches have yet to be confirmed in vivo. Here we show in awake nonhuman primates that the temporal profile of avalanches, which describes how avalanches initiate locally, extend spatially and shrink as they evolve in time, follows a symmetrical, inverted parabola spanning up to hundreds of milliseconds. Parabolas of different durations can be collapsed with a scaling exponent close to 2 supporting critical generational models of neuronal avalanches. Spontaneously emerging, transient γ-oscillations coexist with and modulate these avalanche parabolas thereby providing a temporal segmentation to inherently scale-invariant, critical dynamics. Our results identify avalanches and oscillations as dual principles in the temporal organization of brain activity. Significance StatementThe most common framework for understanding the temporal organization of brain activity is that of oscillations, or "brain waves". In oscillations, distinct physiological frequencies emerge at well-defined temporal scales, dividing brain activity into time segments underlying cortex function. Here, we identify a fundamentally different temporal parsing of activity in cortex. In awake Macaque monkeys, we demonstrate the motif of an inverted parabola that governs the temporal unfolding of brain activity in the form of neuronal avalanches. This symmetrical motif is scale-invariant, that is, it is not tied to time segments, and exhibits a scaling exponent close to 2 in line with prediction from theory of critical systems. We suggest that oscillations provide a Miller et al.The temporal profile of neuronal avalanches 3 transient "wrinkle" of regularity in an otherwise scale-invariant temporal organization pervading cortical activity at numerous scales.

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“…Participants. 30,20,50,30,20 and 15 participants (age range: 18-35 years; 69% of females) were respectively recruited for experiments 1 to 6. The experiments followed the local ethics guidelines from Aix-Marseille University.…”

Section: Methodsmentioning

confidence: 99%

“…The noise is additive and Gaussian with an intensity D, such as ⟨ ( )⟩ = 0 and ⟨ ( ) (t′)⟩ = 2 δ(t − t′)δ (where ⟨•⟩ denotes the time-average operator and δ the delta function). In line with studies implementing models of coupled oscillators, we ran the simulation during 1e4 seconds, in order to obtain an equilibrium in the interaction between the coupled oscillators 50,92 . The sampling rate of the simulation was 25 ms. We thus set internal time-delays to 0 ms (i.e., < 25 ms).…”

Section: Timing Of Motor Acts In Tracking Sessionsmentioning

confidence: 99%

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Attention to rhythms: sensory-specific constrained sampling of temporal regularities

Zalta

Petkoski

Morillon

2019

Preprint

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words)That attention is a fundamentally rhythmic process has recently received abundant empirical evidence. The essence of temporal attention, however, is to flexibly focus in time. Whether this function is hampered by an underlying rhythmic mechanism is unknown. In six interrelated experiments, we behaviourally quantify the sampling capacities of periodic temporal attention during auditory or visual perception. We reveal the presence of limited attentional capacities, with an optimal sampling rate of ~1.4 Hz in audition and ~0.7 Hz in vision. Investigating the motor contribution to temporal attention, we show that it scales with motor rhythmic precision, maximal at ~1.7 Hz. Critically, the motor modulation is beneficial to auditory but detrimental to visual temporal attention. These results are captured by a computational model of coupled oscillators, that reveals the underlying structural constraints governing the temporal alignment between motor and attention fluctuations.

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Phase-lags in large scale brain synchronization: Methodological considerations and in-silico analysis

Cited by 75 publications

References 80 publications

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

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

The scale-invariant, temporal profile of neuronal avalanches in relation to cortical γ–oscillations

Attention to rhythms: sensory-specific constrained sampling of temporal regularities

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