Neural synchronization plays a critical role in information processing, storage, and transmission. Characterizing the pattern of synchronization is therefore of great interest. It has recently been suggested that the brain displays broadband criticality based on two measures of synchronization, phase-locking intervals and global lability of synchronization, showing power-law statistics at the critical threshold in a classical model of synchronization. In this paper, we provide evidence that, within the limits of the model selection approach used to ascertain the presence of power-law statistics, the pooling of pairwise phase-locking intervals from a noncritically interacting system can produce a distribution that is similarly assessed as being power law. In contrast, the global lability of synchronization measure is shown to better discriminate critical from noncritical interaction.
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Botcharova et al. (2012) studied this question.
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