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

Wu D, Zhou Y, Xiang J, Tang L, Liu H, Huang S, Wu T, Chen Q, Wang X - J Headache Pain (2016)

Bottom Line: The 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Road, Nanjing, Jiangsu, 210029, China.

ABSTRACT

Background: Although 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.

Methods: Twenty-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.

Results: The 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.

Conclusions: Results 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.

No MeSH data available.


Related in: MedlinePlus

Number of the MwA, MwoA, and controls in different functional connectivity patterns in 4–8 Hz. The MwoA and controls have significantly higher odds of inhibitory connections in the occipital area compared with the MwA. The blue bars indicate that no inhibitory connections exist in the occipital area, and the orange bars indicate that inhibitory connections exist in the occipital area
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Fig4: Number of the MwA, MwoA, and controls in different functional connectivity patterns in 4–8 Hz. The MwoA and controls have significantly higher odds of inhibitory connections in the occipital area compared with the MwA. The blue bars indicate that no inhibitory connections exist in the occipital area, and the orange bars indicate that inhibitory connections exist in the occipital area

Mentions: In the theta (4–8 Hz) band, no significant difference was observed between the MwoA and the controls. The neural network revealed that both the MwoA and the controls had excitatory connections in bilateral temporal and occipital sensors as well as inhibitory connections between the bilateral occipital sensors. However, differences were found between MwA and MwoA. The neural network revealed that the MwA had excitatory connections in bilateral temporal and occipital sensors. However, most MwA (9 of 10) had no inhibitory connections between bilateral occipital sensors and had inhibitory connections between bilateral temporal sensors (p = 0.007, Fig. 4). This result may indicate that the MwA had significantly increased functional connectivity between the bilateral occipital sensors than that of the MwoA and the controls. The typical topographic distributions of functional connectivity patterns are shown in Fig. 2.Fig. 4


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

Wu D, Zhou Y, Xiang J, Tang L, Liu H, Huang S, Wu T, Chen Q, Wang X - J Headache Pain (2016)

Number of the MwA, MwoA, and controls in different functional connectivity patterns in 4–8 Hz. The MwoA and controls have significantly higher odds of inhibitory connections in the occipital area compared with the MwA. The blue bars indicate that no inhibitory connections exist in the occipital area, and the orange bars indicate that inhibitory connections exist in the occipital area
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4835413&req=5

Fig4: Number of the MwA, MwoA, and controls in different functional connectivity patterns in 4–8 Hz. The MwoA and controls have significantly higher odds of inhibitory connections in the occipital area compared with the MwA. The blue bars indicate that no inhibitory connections exist in the occipital area, and the orange bars indicate that inhibitory connections exist in the occipital area
Mentions: In the theta (4–8 Hz) band, no significant difference was observed between the MwoA and the controls. The neural network revealed that both the MwoA and the controls had excitatory connections in bilateral temporal and occipital sensors as well as inhibitory connections between the bilateral occipital sensors. However, differences were found between MwA and MwoA. The neural network revealed that the MwA had excitatory connections in bilateral temporal and occipital sensors. However, most MwA (9 of 10) had no inhibitory connections between bilateral occipital sensors and had inhibitory connections between bilateral temporal sensors (p = 0.007, Fig. 4). This result may indicate that the MwA had significantly increased functional connectivity between the bilateral occipital sensors than that of the MwoA and the controls. The typical topographic distributions of functional connectivity patterns are shown in Fig. 2.Fig. 4

Bottom Line: The 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurology, Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Road, Nanjing, Jiangsu, 210029, China.

ABSTRACT

Background: Although 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.

Methods: Twenty-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.

Results: The 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.

Conclusions: Results 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.

No MeSH data available.


Related in: MedlinePlus