Algorithmic design of a noise-resistant and efficient closed-loop deep brain stimulation system: A computational approach

Abstract

Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthalamic nucleus deep brain stimulation system for advanced Parkinson’s disease and treatment-refractory obsessive-compulsive disorder, ensuring remarkable performance in terms of both efficiency and selectivity of stimulation, as well as in terms of computational speed. First, we propose an efficient method drawn from dynamical systems theory, for the reliable assessment of significant nonlinear coupling between beta and high-frequency subthalamic neuronal activity, as a biomarker for feedback control. Further, we present a model-based strategy through which optimal parameters of stimulation for minimum energy desynchronizing control of neuronal activity are being identified. The strategy integrates stochastic modeling and derivative-free optimization of neural dynamics based on quadratic modeling. On the basis of numerical simulations, we demonstrate the potential of the presented modeling approach to identify, at a relatively low computational cost, stimulation settings potentially associated with a significantly higher degree of efficiency and selectivity compared with stimulation settings determined post-operatively. Our data reinforce the hypothesis that model-based control strategies are crucial for the design of novel stimulation protocols at the backstage of clinical applications.

Closed-Loop Deep Brain Stimulation for Refractory Chronic Pain

“…Solutions to developing fully-closed loop algorithms and optimizing stimulation based on biomarkers have been suggested by computational studies. Recent models have used LFP spectra (beta and gamma power) as feedback-control signals to provide efficient and selective target stimulation in Parkinson's Disease (Karamintziou et al, 2017 ) and essential tremor (Santaniello et al, 2011 ). Using finite element modeling, anatomical models from imaging data can be combined with electrical models to optimize how current is delivered from the DBS electrode (Xiao et al, 2016 ).…”

Use of Functional Magnetic Resonance Imaging to Assess How Motor Phenotypes of Parkinson’s Disease Respond to Deep Brain Stimulation

“…DBS may normalize firing patterns in the indirect pathway affected by PD , overcoming thalamic inhibition which would further result in MI activation based of the Delong theory of PD . One study utilizing fMRI data with DBS ON and an externalized IPG found activation in the SMA, MI, the premotor cortex and thalamus as compared to DBS OFF, supporting the above presumption .…”

“…The current understanding is that the loss of dopaminergic input into the striatum disrupts normal neurotransmitter release, eventually resulting in an increase in inhibition of the thalamus . By altering pulse width, DBS may normalize firing patterns in the indirect pathway affected by PD , overcoming thalamic inhibition. Thus, a greater amount of activation of the thalamus would imply normalization of the basal ganglia pathway.…”

Ablative neurosurgery and deep brain stimulation for obsessive-compulsive disorder

“…This would greatly help reduce the amount of charge used and prolong battery life of the DBS stimulators, thus reducing adverse effects and cost over long term. [64] Another potential way of reducing the cost of DBS is through use of refurbished and resterilized pulse generators, an approach that has been attempted by cardiologists in India for pacemakers and implantable cardiac defibrillators. [6566] The safety and efficacy of these techniques have to be studied rigorously before wider clinical application.…”