2016
DOI: 10.1186/s10194-016-0697-7
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Resting-state EEG power and coherence vary between migraine phases

Abstract: BackgroundMigraine is characterized by a series of phases (inter-ictal, pre-ictal, ictal, and post-ictal). It is of great interest whether resting-state electroencephalography (EEG) is differentiable between these phases.MethodsWe compared resting-state EEG energy intensity and effective connectivity in different migraine phases using EEG power and coherence analyses in patients with migraine without aura as compared with healthy controls (HCs). EEG power and isolated effective coherence of delta (1–3.5 Hz), t… Show more

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Cited by 62 publications
(48 citation statements)
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“…In order to determine the effect of physical activities only, a physical task without 2-back task should be analyzed in future studies. EEG connectivity was also estimated by isolated effective coherence ( 59 , 60 ). The connectivity with direction may be a new attempt to explore the mental fatigue states.…”
Section: Discussionmentioning
confidence: 99%
“…In order to determine the effect of physical activities only, a physical task without 2-back task should be analyzed in future studies. EEG connectivity was also estimated by isolated effective coherence ( 59 , 60 ). The connectivity with direction may be a new attempt to explore the mental fatigue states.…”
Section: Discussionmentioning
confidence: 99%
“…MIM is a multivariate extension of the imaginary part of coherence: it is a multivariate linear measure of functional connectivity at a specified frequency robust to artifacts resulting from volume conduction, implying that a non-vanishing value cannot be explained by an instantaneous mixture of sources that are actually independent. This is in contrast to classical coherence and also to other newly developed coherence based methods like icoh 48 , 49 which is in particular designed as a measure of directed (and direct) interaction. For MIM, for each pair of grid points the functional dependence is measured between the two 3-dimensional spaces spanned by three possible dipole orientations for each grid point.…”
Section: Methodsmentioning
confidence: 98%
“…Given a time series recorded physiological data, all data samples were carried by a vector. The power spectrum analysis of the time series has often been applied for investigating physiological (e.g., EEG) oscillations by computational intelligence models [7][8][9][10][11][12][13][14] and associated healthcare applications [15][16][17][18][19][20]. Recently, multiple electrodes are often used to collect EEG data in the experiment.…”
Section: Multi-view Eeg Signalsmentioning
confidence: 99%