Abstract
Spatiotemporal dynamics of EEG/MEG (electro-/magneto-encephalogram) have typically been investigated by applying time-frequency decomposition and examining amplitude-amplitude, phase-phase, or phase-amplitude associations between combinations of frequency bands and scalp sites, primarily to identify neural correlates of behaviors and traits. Instead, we directly extracted global EEG spatiotemporal dynamics as trajectories of k-dimensional state vectors (k = the number of estimated current sources) to investigate potential global rules governing neural dynamics. We chose timescale-dependent measures of trajectory instability (approximately the 2nd temporal derivative) and speed (approximately the 1st temporal derivative) as state variables, that succinctly characterized trajectory forms. We compared trajectories across posterior, central, anterior, and lateral scalp regions as the current sources under those regions may serve distinct functions. We recorded EEG while participants rested with their eyes closed (likely engaged in spontaneous thoughts) to investigate intrinsic neural dynamics. Some potential global rules emerged. Time-averaged trajectory instability from all five regions tightly converged (with their variability minimized) at the level of generating nearly unconstrained but slightly conservative turns (~100° on average) on the timescale of ~25 ms, suggesting that spectral-amplitude profiles are globally adjusted to maintain this convergence. Further, within-frequency and cross-frequency phase relations appear to be independently coordinated to reduce average trajectory speed and increase the variability in trajectory speed and instability in a relatively timescale-invariant manner, and to make trajectories less oscillatory. Future research may investigate the functional relevance of these intrinsic global-dynamics rules by examining how they adjust to various sensory environments and task demands or remain invariant. The current results also provide macroscopic constraints for quantitative modeling of neural dynamics as the timescale dependencies of trajectory instability and speed are relatable to oscillatory dynamics.
Highlights
EEG/MEG offer non-invasive methods to study large-scale neural dynamics with millisecond temporal precision
On the shorter timescales (Δt < ~25 ms), the trajectories were most stable in the posterior region, intermediate in the central and left/right-lateral regions, and least stable in the anterior region, whereas the pattern flipped on the intermediate timescales (Δt = 25–80 ms)
We investigated potential global rules governing large-scale intrinsic neural dynamics by characterizing the spatiotemporal dynamics of resting-state EEG as trajectories of k-dimensional state vectors where k is the number of scalp sites
Summary
EEG/MEG offer non-invasive methods to study large-scale neural dynamics with millisecond temporal precision (see [1] for a review). Temporal associations have been examined between the phase of a lower-frequency band (typically θ-α) and the amplitude of a higher-frequency band (typically γ) either within or across sites. These analyses using time-frequency decomposition have elucidated how amplitude-amplitude, phase-phase, and/or phase-amplitude couplings within and across sites in different brain regions may contribute to various perceptual, attentional, and cognitive functions (e.g., [2,3,4,5,6,7,8,9,10,11]).
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