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

Subthalamic stimulation evokes hyperdirect high beta interruption and cortical high gamma entrainment in Parkinson's disease

Compound network dynamics in beta and gamma bands determine the severity of bradykinesia in Parkinson's disease. We explored its subthalamic stimulation related changes parallel with improvement of complex hand movements. Thirty eight patients with Parkinson's disease treated with bilateral stimulation accomplished voluntary and traced spiral drawing with their more affected hand on a digital tablet. A 64 channel electroencephalography was recorded, low and high beta and gamma power was computed in subthalamic and motor cortical sources at four stimulation levels. Subthalamic cortical effective connectivity was calculated, and subnetwork models were created. Beta power decreased, and gamma power increased in sources ipsilateral to stimulation with increasing stimulation intensity. Networks comprising the primary motor cortex played a dominant role in predicting the improvement of voluntary drawing speed. Subthalamic stimulation diminished the hyperdirect high beta information processing and promoted the cortico cortical interactions of the primary motor cortex in the high gamma band.

Subthalamic γ Oscillation Underlying Rapid Eye Movement Sleep Abnormality in Parkinsonian Patients

BACKGROUND

Abnormal rapid eye movement (REM) sleep, including REM sleep behavior disorder (RBD) and reduced REM sleep, is common in Parkinson's disease (PD), highlighting the importance of further study on REM sleep. However, the biomarkers of REM disturbances remain unknown, leading to the lack of REM-specific neuromodulation interventions.

OBJECTIVE

This study aims to investigate the neurophysiological biomarkers of REM disturbance in parkinsonian patients.

METHODS

Ten PD patients implanted with bilateral subthalamic nucleus-deep brain stimulation (STN-DBS) were included in this study, of whom 4 were diagnosed with RBD. Sleep monitoring was conducted 1 month after surgery. Subthalamic local field potentials (LFP) were recorded through sensing-enabled DBS. The neurophysiological features of subthalamic LFP during phasic and tonic microstates of REM sleep and their correlation with REM sleep fragmentation and RBD were analyzed.

RESULTS

Differences in subthalamic γ oscillation between phasic and tonic REM correlated positively with the severity of REM sleep fragmentation. Patients with RBD also exhibited stronger γ oscillations during REM sleep compared with non-RBD patients, and both increased β and γ were found before the onset of RBD episodes. Stimulation changes in simulated γ-triggered feedback modulation followed more closely with phasic REM density, whereas an opposite trend was found in simulated β-triggered feedback modulation.

CONCLUSION

Excess subthalamic γ oscillations may contribute to REM instability and RBD, suggesting that γ oscillation could serve as a feedback signal for adaptive DBS for REM sleep disorders. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Field-Programmable Gate Array-Based Ultra-Low Power Discrete Fourier Transforms for Closed-Loop Neural Sensing

Digital implementations of discrete Fourier transforms (DFT) are a mainstay in feature assessment of recorded biopotentials, particularly in the quantification of biomarkers of neurological disease state for adaptive deep brain stimulation. Fast Fourier transform (FFT) algorithms and architectures present a substantial power demand from onboard batteries in implantable medical devices, necessitating the development of ultra-low power Fourier transform methods in resource-constrained environments. Numerous FFT architectures aim to optimize power and resource demand through computational efficiency; however, prioritizing the reduction of logic complexity at the cost of additional computations can be equally or more effective. This paper introduces a minimal architecture single-delay feedback discrete Fourier transform (mSDF-DFT) for use in ultra-low-power field programmable gate array applications and shows energy and power improvements over state-of-the-art FFT methods. We observe a 33% reduction in dynamic power and 4% reduction in resource utilization in a neural sensing application when compared to state-of-the-art FFT algorithms. While designed for use in closed-loop deep brain stimulation and medical device implementations, the mSDF-DFT is also easily extendable to any ultra-low power embedded application.

Closed-loop systems for deep brain stimulation to treat neuropsychiatric disorders

INTRODUCTION

A closed-loop or feedback-control system is a process which considers the system's output in order to automatically adjust the input. Compared to a traditional open-loop system, a closed-loop system allows for a higher degree of accuracy with minimal human intervention. Novel methods of closed loop 'adaptive' deep brain stimulation DBS (aDBS) are being developed.

AREAS COVERED

This review focuses on the current state of aDBS for various neuropsychiatric conditions: common movement disorders such as Parkinson's disease, dystonia, essential tremor, and Tourette syndrome, as well as psychiatric disorders of depression and obsessive-compulsive disorder. Finally, the future directions of closed-loop neuromodulation treatments are also discussed.

EXPERT OPINION

Recently, aDBS has been shown to offer benefits compared to open-loop DBS. Understanding the biomarkers of pathological states across various disorders is, however, crucial to implementation of aDBS, and improved sensing-capable hardware and advances in machine learning are poised to allow its effective implementation.

The Scalp Nerve Block Combined with Intercostal Nerve Block Improves Recovery After Deep Brain Stimulation in Patients with Parkinson's Disease: A Prospective, Randomized Controlled Trial

Objective

To explore the effect of scalp nerve block (SNB) combined with intercostal nerve block (ICNB) on quality of recovery (QoR) after deep brain stimulation (DBS) in patients with Parkinson's disease (PD).

Methods

We conducted a prospective randomized controlled trial in which 88 patients with PD were randomly assigned to undergo SNB combined with ICNB (SNB group) or not (control group) before surgery. The primary outcome was the 15-item QoR (QoR-15) score 24 h after surgery. The secondary outcomes included QoR-15 scores at 72 h and 1 month after surgery, pain-related events, recovery events in post-anesthesia care unit (PACU), duration of anesthesia and surgery, and nerve block-related adverse events.

Results

The QoR-15 score at 24 h after surgery was significantly higher in SNB group than Control group: 122.0 ± 7.6 vs 113.5 ± 11.3 (P = 0.006). SNB combined with ICNB improved QoR-15 scores at 72 h (P = 0.004) but not at 1 month after surgery (P = 0.230). The SNB group was positively related to QoR-15 scores 24 h after surgery (β = 8.92; 95% CI = 4.52~13.32) after adjusting for confounding variables. The numeric rating scale pain scores at PACU discharge and at 24 h, intraoperative opioid consumption, rescue analgesic use, and the incidence of postoperative nausea and vomiting (PONV) in SNB group were significantly lower than Control group (P < 0.05).

Conclusion

Preoperative SNB combined with ICNB improved QoR and analgesia after surgery, and reduced intraoperative opioid consumption and the incidence of PONV in patients with PD who underwent DBS.

Current and future applications of local field potential-guided programming for Parkinson's disease with the Percept™ rechargeable neurostimulator

Deep brain stimulation (DBS) has been established as an effective neuromodulatory treatment for Parkinson's disease (PD) with motor complications or refractory tremor. Various DBS devices with unique technology platforms are commercially available and deliver continuous, open-loop stimulation. The Percept™ family of neurostimulators use BrainSense™ technology with five key features to sense local field potentials while stimulating, enabling integration of physiologic data into the routine practice of DBS programming. The newly approved Percept™ rechargeable RC implantable pulse generator offers a smaller, thinner design and reduced recharge time with prolonged recharge interval. In this review, we describe the application of local field potential sensing-based programming in PD and highlight the potential future clinical implementation of closed-loop stimulation using the Percept™ RC implantable pulse generator.

Quantifying local field potential dynamics with amplitude and frequency stability between ON and OFF medication and stimulation in Parkinson's disease

Neural oscillations are critical to understanding the synchronisation of neural activities and their relevance to neurological disorders. For instance, the amplitude of beta oscillations in the subthalamic nucleus has gained extensive attention, as it has been found to correlate with medication status and the therapeutic effects of continuous deep brain stimulation in people with Parkinson's disease. However, the frequency stability of subthalamic nucleus beta oscillations, which has been suggested to be associated with dopaminergic information in brain states, has not been well explored. Moreover, the administration of medicine can have inverse effects on changes in frequency and amplitude. In this study, we proposed a method based on the stationary wavelet transform to quantify the amplitude and frequency stability of subthalamic nucleus beta oscillations and evaluated the method using simulation and real data for Parkinson's disease patients. The results suggest that the amplitude and frequency stability quantification has enhanced sensitivity in distinguishing pathological conditions in Parkinson's disease patients. Our quantification shows the benefit of combining frequency stability information with amplitude and provides a new potential feedback signal for adaptive deep brain stimulation.

Beta Burst-Driven Adaptive Deep Brain Stimulation Improves Gait Impairment and Freezing of Gait in Parkinson's Disease

Background

Freezing of gait (FOG) is a debilitating symptom of Parkinson's disease (PD) that is often refractory to medication. Pathological prolonged beta bursts within the subthalamic nucleus (STN) are associated with both worse impairment and freezing behavior in PD, which are improved with deep brain stimulation (DBS). The goal of the current study was to investigate the feasibility, safety, and tolerability of beta burst-driven adaptive DBS (aDBS) for FOG in PD.

Methods

Seven individuals with PD were implanted with the investigational Summit™ RC+S DBS system (Medtronic, PLC) with leads placed bilaterally in the STN. A PC-in-the-loop architecture was used to adjust stimulation amplitude in real-time based on the observed beta burst durations in the STN. Participants performed either a harnessed stepping-in-place task or a free walking turning and barrier course, as well as clinical motor assessments and instrumented measures of bradykinesia, OFF stimulation, on aDBS, continuous DBS (cDBS), or random intermittent DBS (iDBS).

Results

Beta burst driven aDBS was successfully implemented and deemed safe and tolerable in all seven participants. Gait metrics such as overall percent time freezing and mean peak shank angular velocity improved from OFF to aDBS and showed similar efficacy as cDBS. Similar improvements were also seen for overall clinical motor impairment, including tremor, as well as quantitative metrics of bradykinesia.

Conclusion

Beta burst driven adaptive DBS was feasible, safe, and tolerable in individuals with PD with gait impairment and FOG.

Proceedings of the 11th Annual Deep Brain Stimulation Think Tank: pushing the forefront of neuromodulation with functional network mapping, biomarkers for adaptive DBS, bioethical dilemmas, AI-guided neuromodulation, and translational advancements

The Deep Brain Stimulation (DBS) Think Tank XI was held on August 9-11, 2023 in Gainesville, Florida with the theme of "Pushing the Forefront of Neuromodulation". The keynote speaker was Dr. Nico Dosenbach from Washington University in St. Louis, Missouri. He presented his research recently published in Nature inn a collaboration with Dr. Evan Gordon to identify and characterize the somato-cognitive action network (SCAN), which has redefined the motor homunculus and has led to new hypotheses about the integrative networks underpinning therapeutic DBS. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers, and researchers (from industry and academia) can freely discuss current and emerging DBS technologies, as well as logistical and ethical issues facing the field. The group estimated that globally more than 263,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: cutting-edge translational neuromodulation, cutting-edge physiology, advances in neuromodulation from Europe and Asia, neuroethical dilemmas, artificial intelligence and computational modeling, time scales in DBS for mood disorders, and advances in future neuromodulation devices.

Dopaminergic reinforcement in the motor system: Implications for Parkinson's disease and deep brain stimulation

Millions of people suffer from dopamine-related disorders spanning disturbances in movement, cognition and emotion. These changes are often attributed to changes in striatal dopamine function. Thus, understanding how dopamine signalling in the striatum and basal ganglia shapes human behaviour is fundamental to advancing the treatment of affected patients. Dopaminergic neurons innervate large-scale brain networks, and accordingly, many different roles for dopamine signals have been proposed, such as invigoration of movement and tracking of reward contingencies. The canonical circuit architecture of cortico-striatal loops sparks the question, of whether dopamine signals in the basal ganglia serve an overarching computational principle. Such a holistic understanding of dopamine functioning could provide new insights into symptom generation in psychiatry to neurology. Here, we review the perspective that dopamine could bidirectionally control neural population dynamics, increasing or decreasing their strength and likelihood to reoccur in the future, a process previously termed neural reinforcement. We outline how the basal ganglia pathways could drive strengthening and weakening of circuit dynamics and discuss the implication of this hypothesis on the understanding of motor signs of Parkinson's disease (PD), the most frequent dopaminergic disorder. We propose that loss of dopamine in PD may lead to a pathological brain state where repetition of neural activity leads to weakening and instability, possibly explanatory for the fact that movement in PD deteriorates with repetition. Finally, we speculate on how therapeutic interventions such as deep brain stimulation may be able to reinstate reinforcement signals and thereby improve treatment strategies for PD in the future.

Unraveling the complexities of programming neural adaptive deep brain stimulation in Parkinson's disease

Over the past three decades, deep brain stimulation (DBS) for Parkinson's disease (PD) has been applied in a continuous open loop fashion, unresponsive to changes in a given patient's state or symptoms over the course of a day. Advances in recent neurostimulator technology enable the possibility for closed loop adaptive DBS (aDBS) for PD as a treatment option in the near future in which stimulation adjusts in a demand-based manner. Although aDBS offers great clinical potential for treatment of motor symptoms, it also brings with it the need for better understanding how to implement it in order to maximize its benefits. In this perspective, we outline considerations for programing several key parameters for aDBS based on our experience across several aDBS-capable research neurostimulators. At its core, aDBS hinges on successful identification of relevant biomarkers that can be measured reliably in real-time working in cohesion with a control policy that governs stimulation adaption. However, auxiliary parameters such as the window in which stimulation is allowed to adapt, as well as the rate it changes, can be just as impactful on performance and vary depending on the control policy and patient. A standardize protocol for programming aDBS will be crucial to ensuring its effective application in clinical practice.