Decoding Pain Sensitivity in Migraine With Multimodal Brainstem-based Neurosignature
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.
Start: February 2021