Awarded in 2019
Home Department: Neurosciences
Faculty Advisors: Amit Etkin (Psychiatry & Behavioral Sciences), Fei-Fei Li (Computer Science), and Russell Poldrack (Psychology)

Research Title: Closed-Loop Treatment Optimization for Repetitive Transcranial Magnetic Stimulation with Reinforcement Learning

Research Description: Major depression is a highly prevalent (and often drug-resistant) disorder. Repetitive Transcranial Magnetic Stimulation (rTMS) leads to remission in about 30-40% of patients, which is impressive in spite of this being a first-generation treatment protocol. There is much room for improvement, particularly with regards to selecting stimulation parameters to maximize therapeutic effects. Using reinforcement learning algorithms, Molly will develop a fully-automated, individualized approach for rTMS. This adaptive protocol will modify treatment parameters in real time for each unique subject with the goal of eliciting a certain brain state quantified by electroencephalography (EEG) with higher efficacy than traditional rTMS.

WHERE IS SHE NOW?

Molly is an Associate Director of Data Science at Johnson & Johnson Innovative Medicine.