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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

Typical topographic distributions of functional connectivity patterns for seven frequency bands recorded from a migraineur and a control. The red color indicates excitatory connection and the blue color indicates inhibitory connections on contour maps. Compared with the controls, the migraineurs show significantly altered functional connectivity patterns in 0.1–1 Hz. Compared with the MwoA, the MwA shows significantly altered functional connectivity patterns in 4–8 Hz. The MwoA shows the same functional connectivity patterns as the controls in 4–8 Hz
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Fig2: Typical topographic distributions of functional connectivity patterns for seven frequency bands recorded from a migraineur and a control. The red color indicates excitatory connection and the blue color indicates inhibitory connections on contour maps. Compared with the controls, the migraineurs show significantly altered functional connectivity patterns in 0.1–1 Hz. Compared with the MwoA, the MwA shows significantly altered functional connectivity patterns in 4–8 Hz. The MwoA shows the same functional connectivity patterns as the controls in 4–8 Hz

Mentions: In the slow wave (0.1–1 Hz) band, a significant difference was observed in functional connectivity patterns in the frontal cortex between the migraineurs and the controls. Typical topographic distributions of functional connectivity patterns are shown in Fig. 2. The neural network revealed that both the migraine group and the controls had excitatory connections in the left and right temporal sensors, and the connections between the bilateral temporal sensors were inhibitory connections. However, most of the migraineurs (17 of 23) had excitatory connections in the frontal sensors, whereas the controls did not (p = 0.001, Fig. 3). This result indicated that the migraineurs had significantly increased functional connectivity in the frontal sensors than that of the controls. No significant difference was observed between the MwA and MwoA in this frequency band.Fig. 2


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)

Typical topographic distributions of functional connectivity patterns for seven frequency bands recorded from a migraineur and a control. The red color indicates excitatory connection and the blue color indicates inhibitory connections on contour maps. Compared with the controls, the migraineurs show significantly altered functional connectivity patterns in 0.1–1 Hz. Compared with the MwoA, the MwA shows significantly altered functional connectivity patterns in 4–8 Hz. The MwoA shows the same functional connectivity patterns as the controls in 4–8 Hz
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig2: Typical topographic distributions of functional connectivity patterns for seven frequency bands recorded from a migraineur and a control. The red color indicates excitatory connection and the blue color indicates inhibitory connections on contour maps. Compared with the controls, the migraineurs show significantly altered functional connectivity patterns in 0.1–1 Hz. Compared with the MwoA, the MwA shows significantly altered functional connectivity patterns in 4–8 Hz. The MwoA shows the same functional connectivity patterns as the controls in 4–8 Hz
Mentions: In the slow wave (0.1–1 Hz) band, a significant difference was observed in functional connectivity patterns in the frontal cortex between the migraineurs and the controls. Typical topographic distributions of functional connectivity patterns are shown in Fig. 2. The neural network revealed that both the migraine group and the controls had excitatory connections in the left and right temporal sensors, and the connections between the bilateral temporal sensors were inhibitory connections. However, most of the migraineurs (17 of 23) had excitatory connections in the frontal sensors, whereas the controls did not (p = 0.001, Fig. 3). This result indicated that the migraineurs had significantly increased functional connectivity in the frontal sensors than that of the controls. No significant difference was observed between the MwA and MwoA in this frequency band.Fig. 2

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