Internal KCN:The Firing Rate Network Model for Controlling Essential Tremor with Thalamic Deep Brain Stimulation

Thalamic ventral intermediate nucleus (Vim) is the primary surgical target of deep brain stimulation (DBS) for treating essential tremor. In-vivo single unit recordings of patients with essential tremor revealed that low frequency Vim-DBS (50Hz) induces periodic excitatory responses, and high-frequency Vim-DBS (100Hz) induces a transient excitatory response lasting for ≤600ms followed by a suppressed steady-state. Previously developed models could not accurately reproduce Vim-DBS responses across DBS frequencies. Here we develop a firing rate network model to track the instantaneous firing rate of Vim neurons in response to low- and high-frequency (5~200Hz) Vim-DBS. We show that the Vim-network can be explained by the balanced amplification mechanism, in which strong excitation (Vim) is stabilized by strong feedback inhibition. Such balanced amplification mechanism can be generalizable to studying various brain circuits, receiving different types of neuromodulations besides DBS. Based on the Vim-network model, we develop a computational model that predict the EMG dynamics in response to different frequencies of Vim-DBS. Based on the EMG model, we develop a closed-loop DBS control system that automatically updates the appropriate DBS frequency. Our closed-loop DBS system is novel, because it incorporates the understanding of the physiological mechanisms underlying the neuronal networks.