Dataset Information

Mapping brain functional networks topological characteristics in new daily persistent headache: a magnetoencephalography study.

ABSTRACT:

Background

The brain functional network topology in new daily persistent headache (NDPH) is not well understood. In this study, we aim to assess the cortical functional network topological characteristics of NDPH using non-invasive neural signal recordings.

Methods

Resting-state magnetoencephalography (MEG) was used to measure power fluctuations in neuronal oscillations from distributed cortical parcels in 35 patients with NDPH and 40 healthy controls (HCs). Their structural data were collected by 3T MRI. Functional connectivity (FC) of neural networks from 1 to 80 Hz frequency ranges was analyzed with topographic patterns and calculated network topological parameters with graph theory.

Results

In the delta (1-4 Hz) and beta (13-30 Hz) bands, the lateral occipital cortex and superior frontal gyrus FC were increased in NDPH groups compared to HCs. Graph theory analysis revealed that the NDPH had significantly increased global efficiency in the delta band and decreased nodal clustering coefficient (left medial orbitofrontal cortex) in the theta (4-8 Hz) band. The clinical characteristics had a significant correlation with network topological parameters. Age at onset of patients showed a positive correlation with global efficiency in the delta band. The degree of depression of patients showed a negative correlation with the nodal clustering coefficient (left medial orbitofrontal cortex) in the theta band.

Conclusion

The FC and topology of NDPH in brain networks may be altered, potentially leading to cortical hyperexcitability. Moreover, medial orbitofrontal cortex is involved in the pathophysiological mechanism of depression in patients with NDPH. Increased FC observed in the lateral occipital cortex and superior frontal gyrus during resting-state MEG could serve as one of the imaging characteristics associated with NDPH.

SUBMITTER: Qiu D

PROVIDER: S-EPMC10698903 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Publications

Mapping brain functional networks topological characteristics in new daily persistent headache: a magnetoencephalography study.

Qiu Dong D Ge Zhaoli Z Mei Yanliang Y Wang Wei W Xiong Zhonghua Z Li Xiaoshuang X Yuan Ziyu Z Zhang Peng P Zhang Mantian M Liu Xin X Zhang Yaqing Y Yu Xueying X Tang Hefei H Wang Yonggang Y

The journal of headache and pain 20231206 1

<h4>Background</h4>The brain functional network topology in new daily persistent headache (NDPH) is not well understood. In this study, we aim to assess the cortical functional network topological characteristics of NDPH using non-invasive neural signal recordings.<h4>Methods</h4>Resting-state magnetoencephalography (MEG) was used to measure power fluctuations in neuronal oscillations from distributed cortical parcels in 35 patients with NDPH and 40 healthy controls (HCs). Their structural data ...[more]

PMID: 38053071

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Project description:BackgroundNew daily persistent headache (NDPH) is a rare but debilitating primary headache disorder that poses a significant burden on individuals and society. Despite its clinical importance, the underlying pathophysiological mechanisms of NDPH remain unclear. In this study, we aimed to investigate the brain structural changes and neural activity patterns in patients with NDPH using multimodal brain imaging analysis of structural magnetic resonance imaging (sMRI) combined with magnetoencephalography (MEG).MethodsTwenty-eight patients with NDPH and 37 healthy controls (HCs) were recruited for this study, and their structural and resting-state data were collected by 3.0 Tesla MRI and MEG. We analyzed the brain morphology using voxel-based morphometry and source-based morphometry. In each brain region, MEG sensor signals from 1 to 200 Hz were analyzed using an adapted version of Welch's method. MEG source localization was conducted using the dynamic statistical parametric mapping, and the difference of source distribution between patients with NDPH and HCs was examined.ResultsOur results revealed significant differences in the regional grey matter volume, cortical thickness, and cortical surface area between the two groups. Specifically, compared with HCs, patients with NDPH showed a significant decrease in cortical thickness of the left rostral cortex in the middle frontal gyrus, decreased cortical surface area of the left fusiform gyrus, decreased grey matter volume of the left superior frontal gyrus and the left middle frontal gyrus, and increased grey matter volume of the left calcarine. Furthermore, the power of the whole brain, bilateral frontal lobes, and right temporal lobe in the NDPH group were higher than that in HCs in the ripple frequency band (80-200 Hz). Functional and structural analysis suggested that there were structural changes and abnormal high frequency cortical activity in both frontal and temporal lobes in patients with NDPH.ConclusionOur findings indicated that patients with NDPH have abnormalities in brain morphology, such as cortical area, cortical thickness, and grey matter volume, accompanied by abnormal cortical neural activity. Brain structural changes in the frontotemporal cortex and abnormalities in cortical ripple activity may be involved in the pathogenesis of NDPH.

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Project description:IntroductionStructural MRI has long been used to characterize local morphological features of the human brain. Coordination patterns of the local morphological features among regions, however, are not well understood. Here, we constructed individual-level morphological brain networks and systematically examined their topological organization and long-term test-retest reliability under different analytical schemes of spatial smoothing, brain parcellation, and network type.MethodsThis study included 57 healthy participants and all participants completed two MRI scan sessions. Individual morphological brain networks were constructed by estimating interregional similarity in the distribution of regional gray matter volume in terms of the Kullback-Leibler divergence measure. Graph-based global and nodal network measures were then calculated, followed by the statistical comparison and intra-class correlation analysis.ResultsThe morphological brain networks were highly reproducible between sessions with significantly larger similarities for interhemispheric connections linking bilaterally homotopic regions. Further graph-based analyses revealed that the morphological brain networks exhibited nonrandom topological organization of small-worldness, high parallel efficiency and modular architecture regardless of the analytical choices of spatial smoothing, brain parcellation and network type. Moreover, several paralimbic and association regions were consistently revealed to be potential hubs. Nonetheless, the three studied factors particularly spatial smoothing significantly affected quantitative characterization of morphological brain networks. Further examination of long-term reliability revealed that all the examined network topological properties showed fair to excellent reliability irrespective of the analytical strategies, but performing spatial smoothing significantly improved reliability. Interestingly, nodal centralities were positively correlated with their reliabilities, and nodal degree and efficiency outperformed nodal betweenness with respect to reliability.ConclusionsOur findings support single-subject morphological network analysis as a meaningful and reliable method to characterize structural organization of the human brain; this method thus opens a new avenue toward understanding the substrate of intersubject variability in behavior and function and establishing morphological network biomarkers in brain disorders.

Dataset Information

Mapping brain functional networks topological characteristics in new daily persistent headache: a magnetoencephalography study.

Background

Methods

Results

Conclusion

Publications

Mapping brain functional networks topological characteristics in new daily persistent headache: a magnetoencephalography study.

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