Decoding Pain Sensitivity in Migraine With Multimodal Brainstem-based Neurosignature
Status:
Recruiting
Trial end date:
2025-12-01
Target enrollment:
Participant gender:
Summary
Migraine is a highly prevalent and disabling neurological disease, which has a tremendous
impact on sufferers, healthcare systems, and the economy. According to the 2016 WHO report,
migraine is the second leading cause of years lived with disability, greater than all other
neurological diseases combined. Yet, the treatment in migraine is far from optimum; the
sufferers often abuse painkillers and complicated with medication overuse headache. Migraine
is characterized by the hypersensitivity of the sensory system, potentially attributed to
dysfunctional pain modulatory networks located in the deep brain structures, particularly the
brainstem. However, the current understanding of these deeply seated, dysregulated pain
modulatory circuits in migraine is limited due to technological constraints. Besides, studies
with an in-depth analysis of the clinical manifestations (i.e., deep phenotyping) are
lacking, and there is no corresponding animal model readily available for translational
research. In this project, the investigators propose a multimodal approach to address these
issues by applying the technologies and platforms developed by our team to explore the
correlation between pain sensitivity and dysregulated connectivities from brainstem to other
brain regions. In this four-year project, the investigators will recruit 400 migraine
patients and 200 healthy subjects. The investigators aim at decomposing the key brainstem
mechanisms underlying dysmodulated pain sensitivity in migraine from 5 comprehensive
perspectives: (1) clinical deep phenotyping, (2) high-resolution brainstem structural MRI and
functional connectivity analysis, (3) innovative brainstem EEG signal detecting technique,
(4) multimodal data fusion platform with neural network analysis, and (5)
ultrahigh-resolution brainstem-based connectomes, intravital manipulations and recording, and
connectome-sequencing in animal models. Moreover, the investigators will collaborate with
Taiwan Semiconductor Research Institute to develop a wearable high-density EEG equipment,
integrated with a System-on-Chip capable of edge-computing the signal using algorithms
derived from our brainstem decoding platform. The ultimate goal is to build a real-time
brainstem decoding system for clinical application.