2020
DOI: 10.1038/s41598-020-63430-9
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Dynamic network properties of the interictal brain determine whether seizures appear focal or generalised

Abstract: Current explanatory concepts suggest seizures emerge from ongoing dynamics of brain networks. It is unclear how brain network properties determine focal or generalised seizure onset, or how network properties can be described in a clinically-useful manner. Understanding network properties would cast light on seizure-generating mechanisms and allow to quantify to which extent a seizure is focal or generalised. Functional brain networks were estimated in segments of scalp-EEG without interictal discharges (68 pe… Show more

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Cited by 32 publications
(36 citation statements)
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“…Simulation studies have demonstrated that PLV (in the absence of leakage correction) can accurately capture functional connectivity in the source space solution [57,93,94], and has high within-subject consistency between January 19, 2021 18/30 recording sessions [73]. Furthermore, PLV is a useful measure of large-scale connectivity for simulating seizure dynamics [26,39,40,65,81]. These results justify our use of PLV in this study.…”
Section: Methodssupporting
confidence: 60%
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“…Simulation studies have demonstrated that PLV (in the absence of leakage correction) can accurately capture functional connectivity in the source space solution [57,93,94], and has high within-subject consistency between January 19, 2021 18/30 recording sessions [73]. Furthermore, PLV is a useful measure of large-scale connectivity for simulating seizure dynamics [26,39,40,65,81]. These results justify our use of PLV in this study.…”
Section: Methodssupporting
confidence: 60%
“…eLORETA was used for source reconstruction. eLORETA has been demonstrated to outperform other source reconstruction algorithms for resting-state data [44,57,58] and is suitable for phase synchronization [56,57], particularly in studies with a similar number of electrodes (60)(61)(62)(63)(64)(65)(66)(67)(68)(69)(70)(71) to the one presented here [56][57][58]. eLORETA has also been shown to be useful for computational modelling of BNI in source space [39].…”
Section: Methodsmentioning
confidence: 84%
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“…free from discharges or other abnormalities) [40]. Very recently, this approach has been further extended by Woldman et al to account for different network properties characterizing both focal and generalized seizures [41]. Martinet et al show that network characteristics can influence recruitment dynamics of the neocortex in focal to bilateral tonic-clonic seizures [42].…”
Section: Discussionmentioning
confidence: 99%
“…In the sensor-based models, neural mass models are positioned in each sensor location, i.e., electrode position of iEEG or scalp EEG, and they are coupled by the functional connectivity analyzed from the corresponding data. 94 96 In the region-based models, neural mass models are located in each brain region and they are coupled by structural brain connectivity analyzed from structural brain imaging data, mainly T1-weighted and diffusion-weighted images. 97 102 The retrospective modeling studies have demonstrated that poor surgical outcomes are frequently observed when target sites identified by simulations are not sufficiently resected during actual surgery, 96 , 99 In other words, they indicate that in-depth analysis considering network dynamics based on the data is required rather than interpretation of the data itself in order to determine the optimal surgical target.…”
Section: Patient-specific Whole-brain Modelsmentioning
confidence: 99%