#16: Julian Neumann – Machine-Learning for adaptive Deep Brain Stimulation

In this episode, Julian Neumann and I talk about his research toward adaptive deep brain stimulation. Julian has recorded local field potentials from DBS electrodes implanted in patients with Parkinson's Disease, dystonia, essential tremor, obsessive compulsive disorder and depression and is a true expert on the mechanism of action of DBS.

With his laboratory for interventional & cognitive neuromodulation, he has recently ventured into machine-learning based applications to decode brain states from local field potential and electrocorticography recordings in the human brain. We talk about a multitude of conventional and novel physiomarkers that are envisioned for use to guide adaptive (or closed-loop) DBS applications in a tour-de-force across DBS targets, indications and concepts.