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Degenerate time-dependent network dynamics anticipate seizures in human epileptic brain
Author(s) -
Adrià Tauste Campo,
Alessandro Príncipe,
Miguel Ley,
Rodrigo Rocamora,
Gustavo Deco
Publication year - 2018
Publication title -
plos biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.127
H-Index - 271
eISSN - 1545-7885
pISSN - 1544-9173
DOI - 10.1371/journal.pbio.2002580
Subject(s) - neuroscience , epilepsy , electroencephalography , network dynamics , biology , nerve net , default mode network , mechanism (biology) , dynamics (music) , functional connectivity , psychology , physics , pedagogy , mathematics , discrete mathematics , quantum mechanics
Epileptic seizures are known to follow specific changes in brain dynamics. While some algorithms can nowadays robustly detect these changes, a clear understanding of the mechanism by which these alterations occur and generate seizures is still lacking. Here, we provide crossvalidated evidence that such changes are initiated by an alteration of physiological network state dynamics. Specifically, our analysis of long intracranial electroencephalography (iEEG) recordings from a group of 10 patients identifies a critical phase of a few hours in which time-dependent network states become less variable ("degenerate"), and this phase is followed by a global functional connectivity reduction before seizure onset. This critical phase is characterized by an abnormal occurrence of highly correlated network instances and is shown to be particularly associated with the activity of the resected regions in patients with validated postsurgical outcome. Our approach characterizes preseizure network dynamics as a cascade of 2 sequential events providing new insights into seizure prediction and control.

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