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The purpose of this study is to evaluate the safety and efficacy of accelerated intermittent theta burst stimulation (aiTBS) targeting personalized nodes within the somato-cognitive action network (SCAN) and action motor network (AMN) for the treatment of chronic pain. The study will employ Thompson Sampling, a Bayesian reinforcement learning algorithm, to optimize stimulation site selection based on individual response patterns. This approach has the potential to revolutionize pain management by improving treatment accessibility through shortened timelines, addressing individual variations in pain networks through precision targeting, and potentially achieving more robust pain relief through accelerated neuroplasticity.
The specific aims of the study are:
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30 participants in 1 patient group
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Matthew Maple
Data sourced from clinicaltrials.gov
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