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Pain is the leading cause of disability worldwide. However, the pain sensitivity of individuals varies to a large extent, which often results in the mismatch between clinical diagnosis or treatment and individual's actual needs. There are still no established objective indicators for comparisons between individuals. This integrated pilot project is the first large-scale, multi-modal brain decoding study for pain sensitivity. We will explore the brain network signature of pain sensitivity by analyzing electroencephalogram (EEG) signals and magnetic resonance imaging (MRI.) Meanwhile, we will integrate the innate, environmental, and humanity factors with aforementioned brain network signatures to establish multi- modal objective model of pain sensitivity using machine learning. This research team is composed of more than 30 physicians, scientists, and IT experts, along with international collaborators with expertise in the fields of neuroscience, medical imaging, and human philosophy. The five elite groups constitute this international research team and establish five multi-disciplinary sub-projects: Sub-project A: Pain sensitivity and associated innate and environmental factors Sub-project B: Electrophysiological brain signatures of pain sensitivity Sub-project C: MRI brain signatures of pain sensitivity Sub-project D: Innovative brain computer interface (BCI) technology in pain sensitivity measurement and prediction Sub-project E: Pain and Art: neuro-mental mechanisms and potential applications There are three key features of this integrated project: scientific novelty, technology and humanity. In terms of scientific novelty, in addition to machine learning and big data applications, we will focus on the deep brain structure such as brainstem, in which the image acquisition has been difficult in the past. We will develop an MRI sequence and EEG protocol optimized for brainstem. In terms of technology, we will develop a wearable EEG cap implanted with algorithm chip for clinical measurement to decode the pain sensitivity real time. In terms of humanity, we will combine music and painting appreciation to explore their impact on brain signatures related to pain sensitivity. Furthermore, we will develop potential applications of art intervention in pain modulation. We expect this pilot project to achieve the four following goals:
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| healthy control | healthy control |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| no intervention for healthy control | Other | observational study - no intervention |
|
| Measure | Description | Time Frame |
|---|---|---|
| sensory thresholds | Using quantitative sensory testing (QST) to evaluate the sensory threshold | 30 minutes |
| EEG change (1) | Linear analysis of EEG with pain sensitivity | 10 minutes |
| EEG change (2) | Nonlinear analysis of EEG with pain sensitivity | 10 minutes |
| MRI | Analysis of MRI correlatin with pain sensitivity | 90 minutes |
| fMRI | Analysis of fMRI correlatin with pain sensitivity | 90 minutes |
| Humoral relationship (1) | Test the related hormones to evaluate the relationship with sensitivity | 5 minutes |
| Humoral relationship (2) | Test the related cytokines to evaluate the relationship with sensitivity | 5 minutes |
| Measure | Description | Time Frame |
|---|---|---|
| innate and environmental factors associated with pain sensitivity | explory potential factors that may influence the pain sensitivity | 5 minutes |
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Inclusion Criteria:
Exclusion Criteria:
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Healthy control
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| National Yang-Ming University | Taipei | 112 | Taiwan |
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