This project adds multimodal data collection to a study of a low intensity focused ultrasound (FUS) for chronic pain. The study will track brain activity, pain-related biological signals, and information from remote monitoring tools to better understand how the treatment works, impact on depression symptoms and sleep disturbance, and to identify measures that may help predict pain relief. The team will generate models for predicting chronic pain scores from multimodal data and identify key measures for carrying forward at scale. In addition, this project also builds an accessible mobile treatment site and data collection platform enabling a population-level safety, tolerability, and efficacy study. Data collected under this award will be deidentified and housed in the ARPA-H EVIDENT Data Repository.