Functional Connectivity of EEG Signals Under Laser Stimulation in Migraine

Tommaso, Marina de; Trotta, Gabriele; Vecchio, Eleonora; Ricci, Katia; Steen, Frederik Van de; Montemurno, Anna; Lorenzo, Marta; Marinazzo, Daniele; Bellotti, R.; Stramaglia, Sebastiano

doi:10.3389/fnhum.2015.00640

Cited by 29 publications

(35 citation statements)

References 48 publications

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“…Previously, the synchronization levels of cortical activity during visual stimulation in migraine patients have been shown to differ from those in HCs [11, 12]. Our findings provide new evidence of cortical abnormalities during a resting state as detected by EEG power spectra and coherence analyses.…”

Section: Discussionsupporting

confidence: 60%

“…Specifically, compared to controls, migraine patients show increased phase synchronization after stimulation during the migraine-free inter-ictal phase (between post- and pre-ictal phases) [11, 12]. Furthermore, in the pre-ictal phase (before migraine attacks), migraine patients exhibit normal habituation of visually-evoked and auditory-evoked potentials [13], but decreased motor cortex activity [14].…”

Section: Introductionmentioning

confidence: 99%

“…High-level coherence between two EEG signals reflects synchronized neuronal oscillations, whereas low-level coherence suggests desynchronized neural activity. Although EEG coherence analysis has been applied to study migraine-related neural abnormalities in stimulation tasks [11, 12], resting-state EEG coherence in different phases of migraine has not yet been examined. The notion of EEG-detected connectivity is supported by resting-state functional MRI studies showing significant network changes in migraine [20, 21].…”

Section: Introductionmentioning

confidence: 99%

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Resting-state EEG power and coherence vary between migraine phases

et al. 2016

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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), theta (4–7.5 Hz), alpha (8–12.5 Hz), and beta (13–30 Hz) bands were calculated in the frontal, central, temporal, parietal, and occipital regions.ResultsFifty patients with episodic migraine (1–5 headache days/month) and 20 HCs completed the study. Patients were classified into inter-ictal, pre-ictal, ictal, and post-ictal phases (n = 22, 12, 8, 8, respectively), using 36-h criteria. Compared to HCs, inter-ictal and ictal patients, but not pre- or post-ictal patients, had lower EEG power and coherence, except for a higher effective connectivity in fronto-occipital network in inter-ictal patients (p < .05). Compared to data obtained from the inter-ictal group, EEG power and coherence were increased in the pre-ictal group, with the exception of a lower effective connectivity in fronto-occipital network (p < .05). Inter-ictal and ictal patients had decreased EEG power and coherence relative to HCs, which were “normalized” in the pre-ictal or post-ictal groups.ConclusionResting-state EEG power density and effective connectivity differ between migraine phases and provide an insight into the complex neurophysiology of migraine.Electronic supplementary materialThe online version of this article (doi:10.1186/s10194-016-0697-7) contains supplementary material, which is available to authorized users.

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Section: Discussionsupporting

confidence: 60%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Resting-state EEG power and coherence vary between migraine phases

et al. 2016

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“…Electroencephalography (EEG) has been used in the study of functional connectivity or neural network in migraine [ 16 – 18 ]. By analysis of EEG signals in 0.5–30 Hz, de Tommaso and colleagues have found that migraineurs have increased connectivity between the bilateral temporal-parietal and the frontal regions around the midline as compared with healthy controls after laser stimulation [ 16 ]. It has been shown that neural network can reproduce the abnormality of the neurophysiological dysfunction in migraine [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Multi-frequency analysis of brain connectivity networks in migraineurs: a magnetoencephalography study

Zhou

Xiang

et al. 2016

J Headache Pain

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BackgroundAlthough alterations in resting-state neural network have been previously reported in migraine using functional MRI, whether this atypical neural network is frequency dependent remains unknown. The aim of this study was to investigate the alterations of the functional connectivity of neural network and their frequency specificity in migraineurs as compared with healthy controls by using magnetoencephalography (MEG) and concepts from graph theory.MethodsTwenty-three episodic migraine patients with and without aura, during the interictal period, and 23 age- and gender-matched healthy controls at resting state with eye-closed were studied with MEG. Functional connectivity of neural network from low (0.1–1 Hz) to high (80–250 Hz) frequency ranges was analyzed with topographic patterns and quantified with graph theory.ResultsThe topographic patterns of neural network showed that the migraineurs had significantly increased functional connectivity in the slow wave (0.1–1 Hz) band in the frontal area as compared with controls. Compared with the migraineurs without aura (MwoA), the migraineurs with aura (MwA) had significantly increased functional connectivity in the theta (4–8 Hz) band in the occipital area. Graph theory analysis revealed that the migraineurs had significantly increased connection strength in the slow wave (0.1–1 Hz) band, increased path length in the theta (4–8 Hz) and ripple (80–250 Hz) bands, and increased clustering coefficient in the slow wave (0.1–1 Hz) and theta (4–8 Hz) bands. The clinical characteristics had no significant correlation with interictal MEG parameters.ConclusionsResults indicate that functional connectivity of neural network in migraine is significantly impaired in both low- and high-frequency ranges. The alteration of neural network may imply that migraine is associated with functional brain reorganization.

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“…An inability to habituate to pain or a fast disruption of habituation (dishabituation) may foster chronic pain problems [3]. Several studies have found that certain pain types, such as fibromyalgia [47,56,57], migraine [2,16,51,58,59] and chronic low back pain [15,37,43,61], are characterized by deficits in habituation to pain. Future research needs to unravel whether the attenuation of habituation in chronic pain patients stems from deficits in sensory processing and/or from deficits in contextual processing, for instance by activation of responses to pain in inappropriate contexts.…”

Section: Discussionmentioning

confidence: 99%