Influence of time delay in coupling.

<p>(A) Standard Granger causality; (B) spectral causality; (C) transfer entropy as functions of the observed time diffrence at 10 Hz; and (D) phase difference at 10 Hz as a function of the time delay in coupling, given that the strength of coupling was unchanged.</p

Scenario 2: causality and phase synchronization.

<p>Relations between the reconstructed causality and phase-related effects in the case where the phase shift between the driver and response is : (A) measure of spectral Granger causality as a function of frequency; (B) transfer entropy as a function of the time lag ; (C) phase-locking index and (D) phase shift as functions of frequency.</p

ECoG data: spectral power.

<p>Mean spectral density and cross power spectral density of two ECoG channels, averaged across trials. The errorbars represent the standard error computed across trials.</p

Scenario 1: causality and phase synchronization.

<p>Relations between the reconstructed causality and effects of phase-locking and phase differences in the case where there is no phase shift at the main frequency ( Hz): (A) measure of spectral Granger causality as a function of frequency; (B) transfer entropy as a function of the time lag between the past of one signal and the future of the other; (C) phase-locking index and (D) phase shift as functions of frequency.</p

ECoG data: causality and phase synchronization.

<p>(A) Estimated spectral causality; (B) transfer entropy; (C) phase-locking index; and (D) phase differences, computed using local field potentials recorded from a pair of ECoG electrodes. Solid lines represent the mean of statistics under investigation, averaged across trials. The shaded area represents the variability (- and -quantiles) of the corresponding statistics based on surrogate data.</p

Influence of coupling strength.

<p>(A) Standard Granger causality; (B) spectral causality; (C) transfer entropy as functions of phase difference at 10 Hz; and (D) phase difference at 10 Hz as a function of the coupling strength, with the time delay in coupling kept constant.</p

Scenario 2: time series and spectral power.

<p>Characteristics of the driver and response in the case of a negative phase difference () between them at Hz (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0053588#pone-0053588-g003" target="_blank">Fig. 3</a>): (A) simulated signals (two seconds of a randomly chosen realization); and (B) mean spectral density and cross power spectral density, averaged across realizations. The errorbars represent the standard error computed across realizations.</p

Correlation between spectral power and non-stationarity.

<p>Distribution of correlations between relative spectral power and a measure of non-stationarity: (a) mean quasi-stationary segment length and (b) number of quasi-stationary states.</p

Condition effects (modeled).

<p>The “eyes open” versus “eyes closed” hypothesis tested with contrast PLS analyses to track changes in non-stationarity in terms of: (a) the mean quasi-stationary segment length, and (b) the number of quasi-stationary states. Similar to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057217#pone-0057217-g002" target="_blank">Fig. 2</a>, the topographic maps represent the spatial distribution of the electrodes' contribution to the contrast specified <i>a priori</i>.</p

Two mechanisms of non-stationarity.

<p>A schematic illustration of two scenarios: (a) n, the number of states, increases, whereas L, their duration, remains the same, and (b) the states get shorter, although the number of states is kept constant.</p