Robust desynchronization of Parkinson’s disease pathological oscillations by frequency modulation of delayed feedback deep brain stimulation

Abstract

The hyperkinetic symptoms of Parkinson’s Disease (PD) are associated with the ensembles of interacting oscillators that cause excess or abnormal synchronous behavior within the Basal Ganglia (BG) circuitry. Delayed feedback stimulation is a closed loop technique shown to suppress this synchronous oscillatory activity. Deep Brain Stimulation (DBS) via delayed feedback is known to destabilize the complex intermittent synchronous states. Computational models of the BG network are often introduced to investigate the effect of delayed feedback high frequency stimulation on partially synchronized dynamics. In this study, we develop a reduced order model of four interacting nuclei of the BG as well as considering the Thalamo-Cortical local effects on the oscillatory dynamics. This model is able to capture the emergence of 34 Hz beta band oscillations seen in the Local Field Potential (LFP) recordings of the PD state. Train of high frequency pulses in a delayed feedback stimulation has shown deficiencies such as strengthening the synchronization in case of highly fluctuating neuronal activities, increasing the energy consumed as well as the incapability of activating all neurons in a large-scale network. To overcome these drawbacks, we propose a new feedback control variable based on the filtered and linearly delayed LFP recordings. The proposed control variable is then used to modulate the frequency of the stimulation signal rather than its amplitude. In strongly coupled networks, oscillations reoccur as soon as the amplitude of the stimulus signal declines. Therefore, we show that maintaining a fixed amplitude and modulating the frequency might ameliorate the desynchronization process, increase the battery lifespan and activate substantial regions of the administered DBS electrode. The charge balanced stimulus pulse itself is embedded with a delay period between its charges to grant robust desynchronization with lower amplitudes needed. The efficiency of the proposed Frequency Adjustment Stimulation (FAS) protocol in a delayed feedback method might contribute to further investigation of DBS modulations aspired to address a wide range of abnormal oscillatory behavior observed in neurological disorders.

Simulation of Closed-Loop Deep Brain Stimulation Control Schemes for Suppression of Pathological Beta Oscillations in Parkinson’s Disease

“…Previous modeling studies of closed-loop DBS have investigated LFP derived measures of network beta-band activity (Daneshzand et al, 2018;Popovych and Tass, 2019). However, only a small number of models have simulated the coupled DBS electric field and network model during stimulation (Santaniello et al, 2011;Grant and Lowery, 2013).…”

A review of computational modeling and deep brain stimulation: applications to Parkinson’s disease

“…Guo and Rubin [76] used a computational model of the BGTH to explore a multi-site delayed feedback stimulation (MDFS), which filters the simulated LFP signal to generate a stimulus signal. A new frequency adaptive stimulation control strategy based on the LFP in the closed-loop model was proposed [77] . For example, high-frequency stimulation is only triggered at the peak of the filtered LFP (see Fig.…”

Multi-Dimensional, Short-Timescale Quantification of Parkinson's Disease and Essential Tremor Motor Dysfunction

“…Our task's correlation with MDS-UPDRS-III lends it validity, but it was specifically designed to assess motor dysfunction with high temporal precision and thus provide insight into the short-timescale fluctuations in PD symptomatology (38)(39)(40). Importantly, such high-resolution temporal measurement of these fluctuations in motor dysfunction is necessary to correlate behavioral phenotypes with neural activity, a crucial step in the development of adaptive or closed-loop DBS systems (41-44).…”