Evidence map›Paper›PMID 42811291›Full record

ArticleThe journal of headache and pain2026

Temporal neural dynamics patterns in episodic and chronic migraine: a magnetoencephalography study.

Cunxin Lin, Dong Qiu, Pan Liao, Geyu Liu, Jie Liang, Zhonghua Xiong, Xiaoshuang Li, Chenyang Duan, Zhe Wang, Zhi Guo and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The journal of headache and pain, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Cunxin Lin *Headache Center, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China.
Dong Qiu *Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Pan Liao *Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China.
Geyu LiuHeadache Center, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China.
Jie LiangCenter for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China.
Zhonghua XiongHeadache Center, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China.
Xiaoshuang LiHeadache Center, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China.
Chenyang DuanDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Erqi District, Zhengzhou, 450052, Henan Province, China.
Zhe WangDepartment of Neurology, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Zhi GuoHeadache Center, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China.
Yongxiang ZhangHeadache Center, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China.
Zhaoli GeDepartment of Neurology, Shenzhen Second People's Hospital, Shenzhen, Guangdong, 518000, China.
Xin LiuHeadache Center, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China.
Yuanxiang LiDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Erqi District, Zhengzhou, 450052, Henan Province, China.
Tianshuang GaoHeadache Center, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China.
Mantian ZhangHeadache Center, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China.
Jia-Hong GaoCenter for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China.
Bingjiang LyuChangping Laboratory, No. 19 Life Science Park, Beiqing Road, Beijing, 102206, China. blyu@cpl.ac.cn.
Yonggang WangHeadache Center, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China. w100yg@gmail.com.

Funding

Beijing Natural Science Foundation F252058Joint Funds of the National Natural Science Foundation of China U24A20683Shenzhen Medical Research Fund C2501004
6 · The paper itself

Abstract

backgroundChronic migraine (CM) severely affects patients' work and daily life, imposing a significant economic burden. However, the underlying neural mechanisms of migraine chronification remain unclear. This study aimed to characterize temporal neural dynamics patterns of migraine via magnetoencephalography (MEG) combined with dynamic network mode (DyNeMo), providing further neuroimaging evidence for migraine chronification.

methodsThis cross-sectional study recruited patients with episodic migraine (EM), CM, and healthy controls (HC). MEG data were acquired during resting and somatosensory stimulation states. The DyNeMo model was applied to source-reconstructed MEG data to quantify temporal neural dynamics metrics, including mean lifetime, mean interval, switching rate and fractional occupancy. Permutation-based analysis of covariance (ANCOVA) with Bonferroni correction and Spearman correlation with false discovery rate (FDR) correction were applied.

resultsSix distinct brain modes were identified: visual network (VN), anterior and posterior default mode networks (aDMN/pDMN), right and left sensorimotor networks (rSMN/lSMN), and auditory network (AN). During resting state, EM showed prolonged mean lifetime and decreased switching rate of the VN vs. HC; CM showed increased switching rate of the VN vs. EM; CM showed prolonged mean lifetime and decreased switching rate of the AN vs. HC. During somatosensory stimulation state, both EM and CM showed prolonged mean lifetime and decreased switching rate of the AN vs. HC. In CM patients, longer duration of disease was correlated with shorter mean lifetime and higher switching rate of the AN during somatosensory stimulation state.

conclusionsThis study identifies distinct alterations in the temporal dynamics of VN and AN in EM and CM. Abnormalities in AN were observed during both resting and somatosensory stimulation states, while disease duration in CM was associated with altered temporal metrics of the AN. These cross-sectional findings support the involvement of altered sensory and cross-modal network processing in migraine and warrant longitudinal validation.

Indexed as

BrainMagnetoencephalographyMigraine DisordersNerve NetAdultChronic DiseaseCross-Sectional StudiesFemaleHumansMaleMiddle AgedYoung AdultAuditory networkDynamic network modeMagnetoencephalographyMigraineVisual network

Identifiers

PMID42811291
PMCPMC13625361

What Socratic holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.