Closed-loop deep brain stimulation by pulsatile delayed feedback with increased gap between pulse phases

Abstract

Computationally it was shown that desynchronizing delayed feedback stimulation methods are effective closed-loop techniques for the control of synchronization in ensembles of interacting oscillators. We here computationally design stimulation signals for electrical stimulation of neuronal tissue that preserve the desynchronizing delayed feedback characteristics and comply with mandatory charge deposit-related safety requirements. For this, the amplitude of the high-frequency (HF) train of biphasic charge-balanced pulses used by the standard HF deep brain stimulation (DBS) is modulated by the smooth feedback signals. In this way we combine the desynchronizing delayed feedback approach with the HF DBS technique. We show that such a pulsatile delayed feedback stimulation can effectively and robustly desynchronize a network of model neurons comprising subthalamic nucleus and globus pallidus external and suggest this approach for desynchronizing closed-loop DBS. Intriguingly, an interphase gap introduced between the recharging phases of the charge-balanced biphasic pulses can significantly improve the stimulation-induced desynchronization and reduce the amount of the administered stimulation. In view of the recent experimental and clinical studies indicating a superiority of the closed-loop DBS to open-loop HF DBS, our results may contribute to a further development of effective stimulation methods for the treatment of neurological disorders characterized by abnormal neuronal synchronization.

Multisite Delayed Feedback for Electrical Brain Stimulation

“…Each GPe neuron receives an exitatory input from a single neighboring STN neuron and inhibits three neighboring STN neurons. The considered model was introduced to study pathological neuronal dynamics in PD and was investigated in several papers (Terman et al, 2002 ; Rubin and Terman, 2004 ; Park et al, 2011 ; Popovych et al, 2017a , b ). The neurons are interacting via chemical synapses, where the synaptic currents are Summation is taken over all corresponding presynaptic neurons, where j is the index of neurons.…”

“…Variable of Equation (6) has a zero phase shift with respect to the input raw LFP signal (Tukhlina et al, 2007 ), and we consider it as the filtered LFP. The other parameters of Equation (6) were chosen α d = k f = 0.008, which approximately preserves the amplitude of the input LFP signal (Popovych et al, 2017a , b ).…”

“…Direct electrical stimulation of the neuronal tissue with smooth and slowly oscillating feedback signal may however cause an irreversible charge deposit in the neuronal tissue that can exceed safety limits (Harnack et al, 2004 ; Kuncel and Grill, 2004 ; Merrill et al, 2005 ). Two desynchronizing delayed feedback methods, linear delayed feedback (LDF) and nonlinear delayed feedback (NDF) were recently adapted and computationally tested for electrical closed-loop DBS (Popovych et al, 2017a , b ). In both cases, the amplitude of charge-balanced short pulses composing the stimulation signal of the standard HF DBS was modulated by the slow feedback signal.…”

Approaches to closed-loop deep brain stimulation for movement disorders

“…25 Popovych et al presented a delayed feedback stimulation method, which combined high-frequency DBS stimulation and pulsatile delayed feedback to desynchronize abnormal neuronal activity. 46,47 Such methods include pulsatile linear delayed feedback (LDF) or pulsatile nonlinear delayed feedback as methods to use to counteract abnormal neuronal synchronization present in PD. Further studies have employed pulsatile multisite LDF by using signal not only from the STN but also external globus pallidus neurons.…”

Multi-Scale Computational Models for Electrical Brain Stimulation

“…With respect to network activity, a large-scale neuronal model with connections has been developed to investigate the effects of neural stimulation on the oscillatory activity patterns and to provide appropriate stimulation parameters. For example, there is a network model of the basal ganglia for closed-loop DBS combined with the desynchronizing delayed feedback approach (Popovych et al, 2017 ), a model of the motor cortex for reproduction of indirect responses for TMS (Esser et al, 2005 ; Rusu et al, 2014 ), and a thalamocortical network that exhibits gamma oscillation, sleep spindles and epileptogenic bursts (Traub et al, 2005 ). In addition, a neural field model can reproduce the human electroencephalogram (EEG) signals by taking into account cortico-cortical fibers as a major factor (Nunez and Cutillo, 1995 ).…”