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Synchronization was assessed with a technique derived from dynamical system theory, the S estimator, which measures synchronization by relating it to the shrinking of the embedding dimension of the network of neural oscillators underlying the activity at the different electrode sites [14].
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We defined experiments to measure synchronization mismatch vernier acuity.
They define experiments to measure synchronization mismatch perception between individual tiles.
Section 2 describes our proposed experiment for measuring synchronization mismatch vernier acuity of moving images.
This study proposes an approach that measures the synchronization strength of bivariate non-stationary nonlinear data against phase differences.
S-estimator, as other measures of synchronization [54], [55], is affected by EEG power.
Indeed, recent work in nonlinear dynamical systems resulted in new application-independent multivariate measures of synchronization [32], [33], [34], [35].
As other measures of synchronization [54], [55], the S-estimator is affected by the amplitude of the EEG signals.
Although several measures of synchronization have been introduced, particularly for studying chaotic systems, only a few have been widely adopted in neuroscience.
Nevertheless, being used in the analysis of the same data, various measures of synchronization detect coupling, although with different sensitivity [33], [56].
In particular, information-based measures of synchronization can reveal non-linear relationships between the time courses of complex oscillators, and can even reveal directionality of influence in their time series (e.g., [62]).
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