Multimodal Brain Decoding of Pain Sensitivity

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