Abnormal functional connectivity under somatosensory stimulation in migraine: a multi-frequency magnetoencephalography study

Abstract

Background: Although altered neural networks have been demonstrated in recent MEG (magnetoencephalography) research in migraine patients during resting state, it is unknown whether this alteration can be detected in task-related networks. The present study aimed to investigate the abnormalities of the frequency-specific somatosensory-related network in migraine patients by using MEG.

Methods: Twenty-two migraineurs in the interictal phase and twenty-two sex- and age-matched healthy volunteers were studied using a whole-head magnetoencephalography (MEG) system. Electrical stimuli were delivered alternately to the median nerve on the right wrists of all subjects. MEG data were analyzed in a frequency range of 1-1000 Hz in multiple bands.

Results: The brain network patterns revealed that the patients with migraine exhibited remarkably increased functional connectivity in the high-frequency (250-1000 Hz) band between the sensory cortex and the frontal lobe. The results of quantitative analysis of graph theory showed that the patients had (1) an increased degree of connectivity in the theta (4-8 Hz), beta (13-30 Hz) and gamma (30-80 Hz) bands; (2) an increased connectivity strength in the beta (13-30 Hz) and gamma (30-80 Hz) bands; (3) an increased path length in the beta (13-30 Hz), gamma (30-80 Hz) and ripple (80-250 Hz) bands; and (4) an increased clustering coefficient in the theta (4-8 Hz), beta (13-30 Hz) and gamma (30-80 Hz) bands.

Conclusions: The results indicate that migraine is associated with aberrant connections from the somatosensory cortex to the frontal lobe. The frequency-specific increases in connectivity in terms of strength, path length and clustering coefficients support the notion that migraineurs have elevated cortical networks. This alteration in functional connectivity may be involved in somatosensory processing in migraine patients and may contribute to understanding migraine pathophysiology and to providing convincing evidence for a spatially targeted migraine therapy.

Keywords: Functional connectivity; Magnetoencephalography; Migraine; Multi-frequency; Somatosensory.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1

Magnetoencephalography (MEG) waveforms showing neuromagnetic activation evoked by right median nerve stimulation in a migraine subject (“Migraine”) and a healthy subject (“Control”) in a frequency band of 30–80 Hz. There are at least two responses in the somatosensory-evoked magnetic fields (SEFs), “SEFs1” and “SEFs2”. Our analyzed time window is 10-40 ms, which contained the two main responses under somatosensory stimulation. The “Trigger” indicates the start of median nerve stimuli. The “SEFs1” and “SEFs2” indicate the first and second SEF responses, respectively

Fig. 2

Real time source images showing spatial activities under somatosensory stimulation in gamma band (30–80 Hz) recorded from migraine patients and control. 3D images are displayed in axial, coronal and oblique sagittal positions. The black arrow indacates the source activity flow from the deep brain to the sensory cortex

Fig. 3

Typical functional connectivity network patterns in the 1–1000 Hz frequency range in migraine patients and controls, visualized from the lateral (left column) and axial (right column) views. Migraineurs show a significantly altered pattern of functional connectivity network at 250–1000 Hz compared with the controls, showing more connections between the sensory cortex and the frontal lobe. (Color figure online)

Fig. 4

Number of migraineurs and controls with different functional connectivity patterns at 250–1000 Hz. Patients have significantly higher odds of functional connectivity in the frontal lobe than the controls. The orange bars indicate that functional connections are present in frontal cortices. The blues bars indicate that no excitatory connections exist in frontal cortices

Fig. 5

Comparison of the organization of the functional connectivity networks measured by four parameters (degree, strength, path length, and clustering coefficient) between migraine patients and healthy controls. *p < 0.05, and the result is still significant after correction for multiple comparisons using the FDR controlling procedure (corrected for 7 × 4 tests), **p < 0.01. (Color figure online)

Fig. 6

Charts of Spearman’s correlation showing significant relationships between the parameters of network and clinical characteristics in migraineurs. Duration of migraine attacks shows a negative correlation with network strength in the 4–8 Hz range. Migraine attack frequency shows a positive correlation with path length in both the 1–4 Hz and 30–80 Hz frequencies