Beta-triggered adaptive deep brain stimulation during reaching movement in Parkinson’s disease

Abstract

Subthalamic nucleus (STN) beta-triggered adaptive deep brain stimulation (ADBS) has been shown to provide clinical improvement comparable to conventional continuous DBS (CDBS) in people with Parkinson's disease (PD) with less energy delivered to the brain and less stimulation induced side-effects. However, several questions remain unanswered. First, there is a normal physiological reduction of STN beta band power just prior to and during voluntary movement. ADBS systems will therefore reduce or cease stimulation during movement and could therefore compromise motor performance compared to CDBS. Second, beta power was smoothed and estimated over time periods of 400ms or longer in most previous ADBS studies. A shorter smoothing period could have the advantage of being more sensitive to changes in beta power which could enhance motor performance. In this study, we addressed these two questions by evaluating the effectiveness of STN beta-triggered ADBS using a standard 400ms and a shorter 200ms smoothing window during reaching movements. Results from 13 people with PD showed that STN beta-triggered ADBS is effective in improving motor performance during reaching movements as it better preserves gamma oscillation than CDBS in people with PD, and that shortening the smoothing window does not result in any additional behavioural benefit. ADBS significantly improved tremor compared with no DBS but was not as effective as CDBS. When developing ADBS systems for PD, it might not be necessary to track very fast beta dynamics; combining beta, gamma, and motor decoding might be more beneficial with additional biomarkers needed for optimal treatment of tremor.

Evoked resonant neural activity in subthalamic local field potentials reflects basal ganglia network dynamics

“…If the slow ERNA dynamics during cDBS are caused by synaptic failure, it is conceivable that synapses have ample time to replenish between aDBS bursts and therefore never deplete completely and never reach a steady state. While aDBS was at least as effective as cDBS in this cohort and previous studies ( He et al, 2022 ; Little and Brown, 2020 ), we hypothesise that different network states could cause clinical improvement in both instances. More studies will be needed to explore if the difference in the synaptic status during aDBS compared with cDBS, as revealed by the ERNA, could explain why aDBS can help reduce side effects and preserve physiological function of the cortico-subthalamic-GPe circuit.…”

“…While the exact mechanism underlying aDBS is unclear, it is believed to specifically target long beta bursts, which are linked with bradykinetic movements ( Tinkhauser et al, 2017 ; Torrecillos et al, 2018 ). Here, we show that ERNA parameters are differently modulated during cDBS and aDBS ( Figure 8C ), while cDBS and aDBS equally improved motor performance compared with no DBS ( He et al, 2022 ). While both ERNA amplitudes and latencies drift towards a steady state in cDBS, we did not observe that drift in aDBS due to the discontinuous burst stimulation during aDBS.…”

Single Threshold Adaptive Deep Brain Stimulation in Parkinson's Disease Depends on Parameter Selection, Movement State and Controllability of Subthalamic Beta Activity

“…Adaptive DBS exploits biomarkers indicative of the patient's clinical state to adjust stimulation parameters in real-time. For PD, the most promising biomarker is spectral power in the beta frequency range (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) extracted from subthalamic local field potentials (LFPs) as it scales with the changes in motor performance induced by DBS [7][8][9]. Beta power based aDBS approaches encompass various types of feedback control such as single threshold [10][11][12], dual threshold [13,14] and proportional [15,16] algorithms with randomized controlled trials having commenced recently [17,18].…”

“…With the advent of adaptive DBS in clinical use [19], however, practical questions remain to be addressed to facilitate clinical translation: First, aDBS increases the parameter space of DBS programming [6]. So far, limited data is available on the effect of aDBS parameters like ramping rate, thresholds and others on clinical efficacy or patient safety [20][21][22]. Two parameters may be of particular importance to single threshold aDBS, which aims at suppressing pathologically prolonged bursts of beta power [23]: The onset time, which is the duration of supra-threshold power triggering stimulation ramp-up [24] and the amount of smoothing applied to real-time beta power.…”

“…Second, most aDBS studies so far have investigated patients at rest. However, recent reports indicate that movement may interact with aDBS due to its suppressive effect on beta power [20,28]. Clinically, aDBS must be efficacious across a range of behavioral states, raising the question of how aDBS responsivity is affected by movement and whether this depends on parameter choice.…”