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Data from: An fMRI-based neural marker for migraine without aura

Cite this dataset

Tu, Yiheng et al. (2020). Data from: An fMRI-based neural marker for migraine without aura [Dataset]. Dryad.


Objective: To identify and validate a functional magnetic resonance imaging (fMRI)-based neural marker for migraine without aura (MwoA) and examine its association with treatment response. Methods: Cross-sectional studies with resting-state fMRI data from 230 participants and machine learning analyses were conducted. In Studies 1-3, we identified, cross-validated, independently validated, and cross-sectionally validated an fMRI-based neural marker for MwoA. In Study 4, we assessed the relationship between the neural marker and treatment responses in migraineurs who received a 4-week acupuncture treatment in a registered clinical trial. Results: In Study 1 (n = 116), we identified a neural marker with abnormal functional connectivity within the visual, default mode, sensorimotor, and frontal-parietal networks that could discriminate migraineurs from healthy controls (HCs) with 93% sensitivity and 89% specificity. In Study 2 (n = 38), we investigated the generalizability of the marker by applying it on an independent cohort of migraineurs and HCs and achieved 84% sensitivity and specificity. In Study 3 (n = 76), we verified the specificity of the marker with new datasets of migraineurs and other chronic pain disorders (chronic low back pain and fibromyalgia) and demonstrated 78% sensitivity and 76% specificity for discriminating migraineurs from non-migraineurs. In Study 4 (n = 116), we found that the changes in the marker responses showed significant correlation with the changes in headache frequency in response to real acupuncture. Conclusion: We identified an fMRI-based neural marker that captures distinct characteristics of MwoA and can link disease pattern changes to brain changes.

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