Major depression (MDD) is a common psychiatric condition and a leading cause of disability worldwide. While psychotherapy and pharmacotherapy are effective treatments for the majority of people, a substantial number of patients remain refractory to all available treatments. Neuromodulation such as deep brain stimulation (DBS), is a promising solution for these people. However, results from randomized controlled trials of DBS for depression have been inconsistent, suggesting novel strategies for neuromodulation are needed. One such strategy is personalized closed-loop neurostimulation. It addresses the challenge posed by the etiological and diagnostic heterogeneity of depression. Personalized closed-loop neurostimulation involves individualized target selection, customized biomarker driven stimulation, and continuous neural sensing so that treatment is both spatially and temporally individualized. In this talk, I will discuss efforts toward personalizing brain stimulation. I will then present interim findings from a safety and feasibility study of personalized closed-loop DBS at UCSF.
1. State 3 approaches for personalized deep brain stimulation.
2. Identify 3 important properties of stimulation response.
3. Explain the concept of closed-loop control.
4. Explain how spectral and network features can be integrated to identify individual depression subnetworks.