Model-Based Closed-Loop Control of Thalamic Deep Brain Stimulation

Abstract

Closed-loop control of deep brain stimulation (DBS) is crucial for effective and automatic treatments of various neurological disorders like Parkinsons disease (PD) and essential tremor (ET). Manual (open-loop) DBS programming solely based on clinical observations relies on neurologists expertise and patients experience. The continuous stimulation in open-loop DBS may decrease battery life and cause side effects. On the contrary, a closed-loop DBS system utilizes a feedback biomarker/signal to track worsening (or improving) patients symptoms and offers several advantages compared to open-loop DBS. Existing closed-loop DBS control systems do not incorporate physiological mechanisms underlying the DBS or symptoms, for example how DBS modulates dynamics of synaptic plasticity. In this work, we proposed a computational framework for development of a model-based DBS controller where a biophysically-reasonable model can describe the relationship between DBS and neural activity, and a polynomial-based approximation can estimate the relationship between the neural and behavioral activity. A controller is utilized in our model in a quasi-real-time manner to find DBS patterns that significantly reduce the worsening of symptoms. These DBS patterns can be tested clinically by predicting the effect of DBS before delivering it to the patient. We applied this framework to the problem of finding optimal DBS frequencies for essential tremor given EMG recordings solely. Building on our recent network model of ventral intermediate nuclei (Vim), the main surgical target of the tremor, in response to DBS, we developed a biophysically-reasonable simulation in which physiological mechanisms underlying Vim-DBS are linked to symptomatic changes in EMG signals. By utilizing a PID controller, we showed that a closed-loop system can track EMG signals and adjusts the stimulation frequency of Vim-DBS so that the power of EMG in [2, 200] Hz reaches a desired target. We demonstrated that our model-based closed-loop control system of Vim-DBS finds an appropriate DBS frequency that aligns well with clinical studies. Our model-based closed-loop system is adaptable to different control targets, highlighting its potential usability for different diseases and personalized systems.