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It has been known that in complex networks, synchronization analysis can lead to several pitfalls, especially if the data come from different sources [F. C. Meinecke, A. Ziehe, J. Kurths, and K.-R. Müller, Phys. Rev. Lett. 94, 084102 (2005)]. It can also happen that indirect connections could caus
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It has been known that in complex networks, synchronization analysis can lead to several pitfalls, especially if the data come from different sources [F. C. Meinecke, A. Ziehe, J. Kurths, and K.-R. Müller, Phys. Rev. Lett. 94, 084102 (2005)]. It can also happen that indirect connections could cause some synchronization [B. Schelter, M. Winterhalder, R. Dahlhaus, J. Kurths, and J. Timmer, Phys. Rev. Lett. 96, 208103 (2006)]. For EEG or ECoG data, while the tissue that generates focal seizures has both direct and indirect connections with other brain regions, which may be enhanced or weakened temporarily around the time of the seizure, it is difficult to obtain quantitative information about these connections. The problem of figuring out the amount of coupling between brain regions responsible for the signals recorded by any pair of channels, based solely on data, is of paramount interest but may be extremely challenging.
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Whether absence seizures are truly primary generalized seizures or instead focal frontal seizures which spread rapidly over the cortex has been a matter of debate [see, for example, H. Meeren, G. van Luijtelaar, F. L. da Silva, and A. Coenen, Arch. Neurol. 62, 371 (2005)].
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Whether absence seizures are truly primary generalized seizures or instead focal frontal seizures which spread rapidly over the cortex has been a matter of debate [see, for example, H. Meeren, G. van Luijtelaar, F. L. da Silva, and A. Coenen, Arch. Neurol. 62, 371 (2005)].
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