Past, Present, and Future of Deep Brain Stimulation: Hardware, Software, Imaging, Physiology and Novel Approaches

Development of a Neuropeptide Y-Sensitive Implantable Microelectrode for Continuous Measurements

In this work, we present the development of the first implantable aptamer-based platinum microelectrode for continuous measurement of a nonelectroactive molecule, neuropeptide Y (NPY). The aptamer immobilization was performed via conjugation chemistry and characterized using cyclic voltammetry before and after the surface modification. The redox label, methylene blue (MB), was attached at the end of the aptamer sequence and characterized using square wave voltammetry (SWV). NPY standard solutions in a three-electrode cell were used to test three aptamers in steady-state measurement using SWV for optimization. The aptamer with the best performance in the steady-state measurements was chosen, and continuous measurements were performed in a flow cell system using intermittent pulse amperometry. Dynamic measurements were compared against confounding and similar peptides such as pancreatic polypeptide and peptide YY, as well as somatostatin to determine the selectivity in the same modified microelectrode. Our Pt-microelectrode aptamer-based NPY biosensor provides signals 10 times higher for NPY compared to the confounding molecules. This proof-of-concept shows the first potential implantable microelectrode that is selectively sensitive to NPY concentration changes.

Lead-free dual-frequency ultrasound implants for wireless, biphasic deep brain stimulation

Ultrasound-driven bioelectronics could offer a wireless scheme with sustainable power supply; however, current ultrasound implantable systems present critical challenges in biocompatibility and harvesting performance related to lead/lead-free piezoelectric materials and devices. Here, we report a lead-free dual-frequency ultrasound implants for wireless, biphasic deep brain stimulation, which integrates two developed lead-free sandwich porous 1-3-type piezoelectric composite elements with enhanced harvesting performance in a flexible printed circuit board. The implant is ultrasonically powered through a portable external dual-frequency transducer and generates programmable biphasic stimulus pulses in clinically relevant frequencies. Furthermore, we demonstrate ultrasound-driven implants for long-term biosafety therapy in deep brain stimulation through an epileptic rodent model. With biocompatibility and improved electrical performance, the lead-free materials and devices presented here could provide a promising platform for developing implantable ultrasonic electronics in the future.

Electrocardiographic approach strategies in patients with Parkinson disease treated with deep brain stimulation

Deep brain stimulation (DBS) is an interdisciplinary and reversible therapy that uses high-frequency electrical stimulation to correct aberrant neural pathways in motor and cognitive neurological disorders. However, the high frequency of the waves used in DBS can interfere with electrical recording devices (e.g., electrocardiogram, electroencephalogram, cardiac monitor), creating artifacts that hinder their interpretation. The compatibility of DBS with these devices varies and depends on factors such as the underlying disease and the configuration of the neurostimulator. In emergencies where obtaining an electrocardiogram is crucial, the need for more consensus on reducing electrical artifacts in patients with DBS becomes a significant challenge. Various strategies have been proposed to attenuate the artifact generated by DBS, such as changing the DBS configuration from monopolar to bipolar, temporarily deactivating DBS during electrocardiographic recording, applying frequency filters both lower and higher than those used by DBS, and using non-standard leads. However, the inexperience of medical personnel, variability in DBS models, or the lack of a controller at the time of approach limit the application of these strategies. Current evidence on their reproducibility and efficacy is limited. Due to the growing elderly population and the rising utilization of DBS, it is imperative to create electrocardiographic methods that are easily accessible and reproducible for general physicians and emergency services.

Bioelectronic modulation of carotid sinus nerve to treat type 2 diabetes: current knowledge and future perspectives

Bioelectronic medicine are an emerging class of treatments aiming to modulate body nervous activity to correct pathological conditions and restore health. Recently, it was shown that the high frequency electrical neuromodulation of the carotid sinus nerve (CSN), a small branch of the glossopharyngeal nerve that connects the carotid body (CB) to the brain, restores metabolic function in type 2 diabetes (T2D) animal models highlighting its potential as a new therapeutic modality to treat metabolic diseases in humans. In this manuscript, we review the current knowledge supporting the use of neuromodulation of the CSN to treat T2D and discuss the future perspectives for its clinical application. Firstly, we review in a concise manner the role of CB chemoreceptors and of CSN in the pathogenesis of metabolic diseases. Secondly, we describe the findings supporting the potential therapeutic use of the neuromodulation of CSN to treat T2D, as well as the feasibility and reversibility of this approach. A third section is devoted to point up the advances in the neural decoding of CSN activity, in particular in metabolic disease states, that will allow the development of closed-loop approaches to deliver personalized and adjustable treatments with minimal side effects. And finally, we discuss the findings supporting the assessment of CB activity in metabolic disease patients to screen the individuals that will benefit therapeutically from this bioelectronic approach in the future.

Biophysical Principles and Computational Modeling of Deep Brain Stimulation

BACKGROUND

Deep brain stimulation (DBS) has revolutionized the treatment of neurological disorders, yet the mechanisms of DBS are still under investigation. Computational models are important in silico tools for elucidating these underlying principles and potentially for personalizing DBS therapy to individual patients. The basic principles underlying neurostimulation computational models, however, are not well known in the clinical neuromodulation community.

OBJECTIVE

In this study, we present a tutorial on the derivation of computational models of DBS and outline the biophysical contributions of electrodes, stimulation parameters, and tissue substrates to the effects of DBS.

RESULTS

Given that many aspects of DBS are difficult to characterize experimentally, computational models have played an important role in understanding how material, size, shape, and contact segmentation influence device biocompatibility, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Neural activation is dictated by stimulation parameters including frequency, current vs voltage control, amplitude, pulse width, polarity configurations, and waveform. These parameters also affect the potential for tissue damage, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Activation of the neural substrate also is influenced by the encapsulation layer surrounding the electrode, the conductivity of the surrounding tissue, and the size and orientation of white matter fibers. These properties modulate the effects of the electric field and determine the ultimate therapeutic response.

CONCLUSION

This article describes biophysical principles that are useful for understanding the mechanisms of neurostimulation.

Neurostimulation treatments for epilepsy: Deep brain stimulation, responsive neurostimulation and vagus nerve stimulation

Epilepsy is a common and debilitating neurological disorder, and approximately one-third of affected individuals have ongoing seizures despite appropriate trials of two anti-seizure medications. This population with drug-resistant epilepsy (DRE) may benefit from neurostimulation approaches, such as vagus nerve stimulation (VNS), deep brain stimulation (DBS) and responsive neurostimulation (RNS). In some patient populations, these techniques are FDA-approved for treating DRE. VNS is used as adjuvant therapy for children and adults. Acting via the vagus afferent network, VNS modulates thalamocortical circuits, reducing seizures in approximately 50 ​% of patients. RNS uses an adaptive (closed-loop) system that records intracranial EEG patterns to activate the stimulation at the appropriate time, being particularly well-suited to treat seizures arising within eloquent cortex. For DBS, the most promising therapeutic targets are the anterior and centromedian nuclei of the thalamus, with anterior nucleus DBS being used for treating focal and secondarily generalized forms of DRE and centromedian nucleus DBS being applied for treating generalized epilepsies such as Lennox-Gastaut syndrome. Here, we discuss the indications, advantages and limitations of VNS, DBS and RNS in treating DRE and summarize the spatial distribution of neuroimaging observations related to epilepsy and stimulation using NeuroQuery and NeuroSynth.

The history of deep brain stimulation

Deep brain stimulation (DBS) surgery is an established and effective treatment for several movement disorders (tremor, Parkinson's disease, and dystonia), and is under investigation in numerous other neurological and psychiatric disorders. However, the origins and development of this neurofunctional technique are not always well understood and recognized. In this mini-review, we review the history of DBS, highlighting important milestones and the most remarkable protagonists (neurosurgeons, neurologists, and neurophysiologists) who pioneered and fostered this therapy throughout the 20th and early 21st century. Alongside DBS historical markers, we also briefly discuss newer developments in the field, and the future challenges which accompany such progress.

The Potential Regulation of Working Anode for Long-Term Zero-Volt Storage at 37 °C in Li-Ion Batteries

The advanced lithium-ion batteries that can tolerate zero-volt storage (ZVS) are in high demand for implantable medical devices and spacecraft. However, ZVS can raise the anode potential, leading to Cu current collector dissolution and solid-electrolyte interphase (SEI) degradation, especially at 37 °C. In this contribution, by quantitatively regulating the dosage of Li6CoO4 cathode additives, controllable potential of the working anode under abusive-discharge conditions is demonstrated. The addition of Li6CoO4 keeps zero-crossing potential (ZCP) and the potential of ZVS below 2.0 V (vs Li/Li+) for LiCoO2|mesocarbon microbead cells at 37 °C. The capacity retention ratio (CRR) increases from 69.1% and 35.9% to 98.6% and 90.8% after 10 and 20 days of ZVS, respectively. The Cu dissolution and SEI degradation are effectively suppressed, while the over-lithiated cathode exhibits high reversible capacity after ZVS. The limiting conditions of long-term ZVS are further explored and a corresponding guide map is designed. When quantitatively regulating ZCP and the potential in ZVS, Cu dissolution, SEI degradation, and irreversible conversion of the cathode constitute the limiting conditions. This contribution designs the most reasonable potential range for ZVS protection at 37 °C, and realizes the best CRR record through precise potential regulation for the first time.

Preventing Sudden Cessation of Implantable Pulse Generators in Deep Brain Stimulation: A Systematic Review and Protocol Proposal

INTRODUCTION

Deep brain stimulation (DBS) requires a consistent electrical supply from the implantable pulse generator (IPG). Patients may struggle to monitor their IPG, risking severe complications in battery failure. This review assesses current literature on DBS IPG battery life management and proposes a protocol for healthcare providers.

METHODS

A literature search using four databases identified best practices for DBS IPG management. Studies were appraised for IPG management guidelines, categorized as qualitative, quantitative, or both.

RESULTS

Of 408 citations, only seven studies were eligible, none providing clear patient management strategies. Current guidelines lack specificity, relying on clinician suggestions.

CONCLUSION

Limited guidelines exist for IPG management. Specificity and adaptability to emerging technology are crucial. The findings highlight the need for specificity in patients' needs and adaptability to emerging technology in future studies. To address this need, we developed a protocol for DBS IPG management that we have implemented at our own institution. Further research is needed for effective DBS IPG battery life management, preventing therapy cessation complications.

Multi-night cortico-basal recordings reveal mechanisms of NREM slow-wave suppression and spontaneous awakenings in Parkinson's disease

Sleep disturbance is a prevalent and disabling comorbidity in Parkinson's disease (PD). We performed multi-night (n = 57) at-home intracranial recordings from electrocorticography and subcortical electrodes using sensing-enabled Deep Brain Stimulation (DBS), paired with portable polysomnography in four PD participants and one with cervical dystonia (clinical trial: NCT03582891). Cortico-basal activity in delta increased and in beta decreased during NREM (N2 + N3) versus wakefulness in PD. DBS caused further elevation in cortical delta and decrease in alpha and low-beta compared to DBS OFF state. Our primary outcome demonstrated an inverse interaction between subcortical beta and cortical slow-wave during NREM. Our secondary outcome revealed subcortical beta increases prior to spontaneous awakenings in PD. We classified NREM vs. wakefulness with high accuracy in both traditional (30 s: 92.6 ± 1.7%) and rapid (5 s: 88.3 ± 2.1%) data epochs of intracranial signals. Our findings elucidate sleep neurophysiology and impacts of DBS on sleep in PD informing adaptive DBS for sleep dysfunction.

Bioelectronic Medicine: a multidisciplinary roadmap from biophysics to precision therapies

Bioelectronic Medicine stands as an emerging field that rapidly evolves and offers distinctive clinical benefits, alongside unique challenges. It consists of the modulation of the nervous system by precise delivery of electrical current for the treatment of clinical conditions, such as post-stroke movement recovery or drug-resistant disorders. The unquestionable clinical impact of Bioelectronic Medicine is underscored by the successful translation to humans in the last decades, and the long list of preclinical studies. Given the emergency of accelerating the progress in new neuromodulation treatments (i.e., drug-resistant hypertension, autoimmune and degenerative diseases), collaboration between multiple fields is imperative. This work intends to foster multidisciplinary work and bring together different fields to provide the fundamental basis underlying Bioelectronic Medicine. In this review we will go from the biophysics of the cell membrane, which we consider the inner core of neuromodulation, to patient care. We will discuss the recently discovered mechanism of neurotransmission switching and how it will impact neuromodulation design, and we will provide an update on neuronal and glial basis in health and disease. The advances in biomedical technology have facilitated the collection of large amounts of data, thereby introducing new challenges in data analysis. We will discuss the current approaches and challenges in high throughput data analysis, encompassing big data, networks, artificial intelligence, and internet of things. Emphasis will be placed on understanding the electrochemical properties of neural interfaces, along with the integration of biocompatible and reliable materials and compliance with biomedical regulations for translational applications. Preclinical validation is foundational to the translational process, and we will discuss the critical aspects of such animal studies. Finally, we will focus on the patient point-of-care and challenges in neuromodulation as the ultimate goal of bioelectronic medicine. This review is a call to scientists from different fields to work together with a common endeavor: accelerate the decoding and modulation of the nervous system in a new era of therapeutic possibilities.

Deep brain stimulation of the subthalamic nucleus in Parkinson disease 2013-2023: where are we a further 10 years on?

Deep brain stimulation has been in clinical use for 30 years and during that time it has changed markedly from a small-scale treatment employed by only a few highly specialized centers into a widespread keystone approach to the management of disorders such as Parkinson's disease. In the intervening decades, many of the broad principles of deep brain stimulation have remained unchanged, that of electrode insertion into stereotactically targeted brain nuclei, however the underlying technology and understanding around the approach have progressed markedly. Some of the most significant advances have taken place over the last decade with the advent of artificial intelligence, directional electrodes, stimulation/recording implantable pulse generators and the potential for remote programming among many other innovations. New therapeutic targets are being assessed for their potential benefits and a surge in the number of deep brain stimulation implantations has given birth to a flourishing scientific literature surrounding the pathophysiology of brain disorders such as Parkinson's disease. Here we outline the developments of the last decade and look to the future of deep brain stimulation to attempt to discern some of the most promising lines of inquiry in this fast-paced and rapidly evolving field.

Neural repair and regeneration interfaces: a comprehensive review

Neural interfaces play a pivotal role in neuromodulation, as they enable precise intervention into aberrant neural activity and facilitate recovery from neural injuries and resultant functional impairments by modulating local immune responses and neural circuits. This review outlines the development and applications of these interfaces and highlights the advantages of employing neural interfaces for neural stimulation and repair, including accurate targeting of specific neural populations, real-time monitoring and control of neural activity, reduced invasiveness, and personalized treatment strategies. Ongoing research aims to enhance the biocompatibility, stability, and functionality of these interfaces, ultimately augmenting their therapeutic potential for various neurological disorders. The review focuses on electrophysiological and optophysiology neural interfaces, discussing functionalization and power supply approaches. By summarizing the techniques, materials, and methods employed in this field, this review aims to provide a comprehensive understanding of the potential applications and future directions for neural repair and regeneration devices.

The future of brain circuit-targeted therapeutics

The principle of targeting brain circuits has drawn increasing attention with the growth of brain stimulation treatments such as transcranial magnetic stimulation (TMS), deep brain stimulation (DBS), and focused ultrasound (FUS). Each of these techniques can effectively treat different neuropsychiatric disorders, but treating any given disorder depends on choosing the right treatment target. Here, we propose a three-phase framework for identifying and modulating these targets. There are multiple approaches to identifying a target, including correlative neuroimaging, retrospective optimization based on existing stimulation sites, and lesion localization. These techniques can then be optimized using personalized neuroimaging, physiological monitoring, and engagement of a specific brain state using pharmacological or psychological interventions. Finally, a specific stimulation modality or combination of modalities can be chosen after considering the advantages and tradeoffs of each. While there is preliminary literature to support different components of this framework, there are still many unanswered questions. This presents an opportunity for the future growth of research and clinical care in brain circuit therapeutics.

Sensing-Enabled Deep Brain Stimulation in Epilepsy

Deep brain stimulation has demonstrated efficacy in reducing seizure frequency in patients with drug-resistant epilepsy who may otherwise not be candidates for other surgical procedures. Recently, a clinical device that can monitor neural activity in the form of local field potentials around the deep brain stimulator lead implant site has been introduced. While this technology has been clinically adopted in other disorders treated with deep brain stimulation, such as Parkinson's disease, its application in epilepsy remains unclear. Previous research using investigational devices has suggested that specific frequency bands may correlate with clinical response to deep brain stimulation in epilepsy, but features of the clinical device may prevent its use. The authors present their experience with using this technology in epilepsy patients and describe some of its limitations. Ultimately, novel biomarkers will need to be identified to elucidate how neural activity at deep brain stimulation sites may change with clinical response.

Applicability of clinical genetic testing for deep brain stimulation treatment in monogenic Parkinson's disease and monogenic dystonia: a multidisciplinary team perspective

In this perspective article, we highlight the possible applicability of genetic testing in Parkinson's disease and dystonia patients treated with deep brain stimulation (DBS). DBS, a neuromodulatory technique employing electrical stimulation, has historically targeted motor symptoms in advanced PD and dystonia, yet its precise mechanisms remain elusive. Genetic insights have emerged as potential determinants of DBS efficacy. Known PD genes such as GBA, SNCA, LRRK2, and PRKN are most studied, even though further studies are required to make firm conclusions. Variable outcomes depending on genotype is present in genetic dystonia, as DYT-TOR1A, NBIA/DYTPANK2, DYT-SCGE and X-linked dystonia-parkinsonism have demonstrated promising outcomes following GPi-DBS, while varying outcomes have been documented in DYT-THAP1. We present two clinical vignettes that illustrate the applicability of genetics in clinical practice, with one PD patient with compound GBA mutations and one GNAL dystonia patient. Integrating genetic testing into clinical practice is pivotal, particularly with advancements in next-generation sequencing. However, there is a clear need for further research, especially in rarer monogenic forms. Our perspective is that applying genetics in PD and dystonia is possible today, and despite challenges, it has the potential to refine patient selection and enhance treatment outcomes.

Advances in Deep Brain Stimulation: From Mechanisms to Applications

Deep brain stimulation (DBS) is an effective therapy for various neurologic and neuropsychiatric disorders, involving chronic implantation of electrodes into target brain regions for electrical stimulation delivery. Despite its safety and efficacy, DBS remains an underutilized therapy. Advances in the field of DBS, including in technology, mechanistic understanding, and applications have the potential to expand access and use of DBS, while also improving clinical outcomes. Developments in DBS technology, such as MRI compatibility and bidirectional DBS systems capable of sensing neural activity while providing therapeutic stimulation, have enabled advances in our understanding of DBS mechanisms and its application. In this review, we summarize recent work exploring DBS modulation of target networks. We also cover current work focusing on improved programming and the development of novel stimulation paradigms that go beyond current standards of DBS, many of which are enabled by sensing-enabled DBS systems and have the potential to expand access to DBS.

Effects of deep brain stimulation of the subthalamic nucleus on patients with Parkinson's disease: a machine-learning voice analysis

Introduction

Deep brain stimulation of the subthalamic nucleus (STN-DBS) can exert relevant effects on the voice of patients with Parkinson's disease (PD). In this study, we used artificial intelligence to objectively analyze the voices of PD patients with STN-DBS.

Materials and methods

In a cross-sectional study, we enrolled 108 controls and 101 patients with PD. The cohort of PD was divided into two groups: the first group included 50 patients with STN-DBS, and the second group included 51 patients receiving the best medical treatment. The voices were clinically evaluated using the Unified Parkinson's Disease Rating Scale part-III subitem for voice (UPDRS-III-v). We recorded and then analyzed voices using specific machine-learning algorithms. The likelihood ratio (LR) was also calculated as an objective measure for clinical-instrumental correlations.

Results

Clinically, voice impairment was greater in STN-DBS patients than in those who received oral treatment. Using machine learning, we objectively and accurately distinguished between the voices of STN-DBS patients and those under oral treatments. We also found significant clinical-instrumental correlations since the greater the LRs, the higher the UPDRS-III-v scores.

Discussion

STN-DBS deteriorates speech in patients with PD, as objectively demonstrated by machine-learning voice analysis.

Interactions between cathodic- and anodic-pulses during high-frequency stimulations with the monophasic-pulses alternating in polarity at axons-experiment and simulation studies

Background. Electrical neuromodulation therapies commonly utilize high-frequency stimulations (HFS) of biphasic-pulses to treat neurological disorders. The biphasic pulse consists of a leading cathodic-phase to activate neurons and a lagging anodic-phase to balance electrical charges. Because both monophasic cathodic- and anodic-pulses can depolarize neuronal membranes, splitting biphasic-pulses into alternate cathodic- and anodic-pulses could be a feasible strategy to improve stimulation efficiency.Objective. We speculated that neurons in the volume initially activated by both polarity pulses could change to be activated only by anodic-pulses during sustained HFS of alternate monophasic-pulses. To verify the hypothesis, we investigated the interactions of the monophasic pulses during HFS and revealed possible underlying mechanisms.Approach. Different types of pulse stimulations were applied at the alvear fibers (i.e. the axons of CA1 pyramidal neurons) to antidromically activate the neuronal cell bodies in the hippocampal CA1 region of anesthetized ratsin-vivo. Sequences of antidromic HFS (A-HFS) were applied with alternate monophasic-pulses or biphasic-pulses. The pulse frequency in the A-HFS sequences was 50 or 100 Hz. The A-HFS duration was 120 s. The amplitude of antidromically-evoked population spike was measured to evaluate the neuronal firing induced by each pulse. A computational model of axon was used to explore the possible mechanisms of neuronal modulations. The changes of model variables during sustained A-HFS were analyzed.Main results. In rat experiments, with a same pulse intensity, the activation volume of a cathodic-pulse was greater than that of an anodic-pulse. In paired-pulse tests, a preceding cathodic-pulse was able to prevent a following anodic-pulse from activating neurons due to refractory period. This indicated that the activation volume of a cathodic-pulse covered that of an anodic-pulse. However, during sustained A-HFS of alternate monophasic-pulses, the anodic-pulses were able to prevail over the cathodic-pulses in activating neurons in the overlapped activation volume. Model simulation results show the mechanisms of the activation failures of cathodic-pulses. They include the excessive membrane depolarization caused by an accumulation of potassium ions, the obstacle of hyperpolarization in the conduction pathway and the interactions from anodic-pulses.Significance. The study firstly showed the domination of anodic-pulses over cathodic-pulses in their competitions to activate neurons during sustained HFS. The finding provides new clues for designing HFS paradigms to improve the efficiency of neuromodulation therapies.

A structural magnetic resonance imaging review of clinical motor outcomes from deep brain stimulation in movement disorders

Patients with movement disorders treated by deep brain stimulation do not always achieve successful therapeutic alleviation of motor symptoms, even in cases where surgery is without complications. Magnetic resonance imaging (MRI) offers methods to investigate structural brain-related factors that may be predictive of clinical motor outcomes. This review aimed to identify features which have been associated with variability in clinical post-operative motor outcomes in patients with Parkinson's disease, dystonia, and essential tremor from structural MRI modalities. We performed a literature search for articles published between 1 January 2000 and 1 April 2022 and identified 5197 articles. Following screening through our inclusion criteria, we identified 60 total studies (39 = Parkinson's disease, 11 = dystonia syndromes and 10 = essential tremor). The review captured a range of structural MRI methods and analysis techniques used to identify factors related to clinical post-operative motor outcomes from deep brain stimulation. Morphometric markers, including volume and cortical thickness were commonly identified in studies focused on patients with Parkinson's disease and dystonia syndromes. Reduced metrics in basal ganglia, sensorimotor and frontal regions showed frequent associations with reduced motor outcomes. Increased structural connectivity to subcortical nuclei, sensorimotor and frontal regions was also associated with greater motor outcomes. In patients with tremor, increased structural connectivity to the cerebellum and cortical motor regions showed high prevalence across studies for greater clinical motor outcomes. In addition, we highlight conceptual issues for studies assessing clinical response with structural MRI and discuss future approaches towards optimizing individualized therapeutic benefits. Although quantitative MRI markers are in their infancy for clinical purposes in movement disorder treatments, structural features obtained from MRI offer the powerful potential to identify candidates who are more likely to benefit from deep brain stimulation and provide insight into the complexity of disorder pathophysiology.

Closed-Loop Adaptive Deep Brain Stimulation in Parkinson's Disease: Procedures to Achieve It and Future Perspectives

Parkinson's disease (PD) is a neurodegenerative disease with a heavy burden on patients, families, and society. Deep brain stimulation (DBS) can improve the symptoms of PD patients for whom medication is insufficient. However, current open-loop uninterrupted conventional DBS (cDBS) has inherent limitations, such as adverse effects, rapid battery consumption, and a need for frequent parameter adjustment. To overcome these shortcomings, adaptive DBS (aDBS) was proposed to provide responsive optimized stimulation for PD. This topic has attracted scientific interest, and a growing body of preclinical and clinical evidence has shown its benefits. However, both achievements and challenges have emerged in this novel field. To date, only limited reviews comprehensively analyzed the full framework and procedures for aDBS implementation. Herein, we review current preclinical and clinical data on aDBS for PD to discuss the full procedures for its achievement and to provide future perspectives on this treatment.

Deep brain stimulation - New programming algorithms and teleprogramming

INTRODUCTION

Thanks to a variety of factors, the field of neuromodulation has evolved significantly over the past decade. Developments include new indications and innovations of hardware, software, and stimulation techniques leading to an expansion in scope and role of these techniques as powerful therapies. They also imply the realization that practical application involves new nuances that make patient selection, surgical technique and the programming process even more complex, requiring continuous education and an organized structured approach.

AREAS COVERED

In this review, the authors explore the developments in deep brain stimulation technology, including electrodes, implantable pulse generators, contact configurations (i.e, directional leads and independent current control), remote programming and sensing using local field potentials.

EXPERT OPINION

The innovations in the field of deep brain stimulation discussed in this review potentially provide increased effectiveness and flexibility not only to improve therapeutic response but also to address troubleshooting challenges seen in clinical practice. Directional leads and shorter pulse widths may broaden the therapeutic window of stimulation, avoiding current spread to structures that might trigger stimulation-related side effects. Similarly, independent control of current to individual contacts allows for the shaping of the electric field. Finally, sensing and remote programming represent important developments for more effective and individualized patient care.

Association of subthalamic beta frequency sub-bands to symptom severity in patients with Parkinson's disease: A systematic review

OBJECTIVE

Local field potentials (LFP), specifically beta (13-30Hz) frequency measures, have been found to be associated with motor dysfunction in people with Parkinson's disease (PwPD). A consensus on beta subband (low- and high-beta) relationships to clinical state or therapy response has yet to be determined. The objective of this review is to synthesize literature reporting the association of low- and high-beta characteristics to clinical ratings of motor symptoms in PwPD.

METHODS

A systematic search of existing literature was completed using EMBASE. Articles which collected subthalamic nucleus (STN) LFPs using macroelectrodes in PwPD, analyzed low- (13-20 Hz) and high-beta (21-35 Hz) bands, collected UPDRS-III, and reported correlational strength or predictive capacity of LFPs to UPDRS-III scores.

RESULTS

The initial search yielded 234 articles, with 11 articles achieving inclusion. Beta measures included power spectral density, peak characteristics, and burst characteristics. High-beta was a significant predictor of UPDRS-III responses to therapy in 5 (100%) articles. Low-beta was significantly associated with UPDRS-III total score in 3 (60%) articles. Low- and high-beta associations to UPDRS-III subscores were mixed.

CONCLUSION

This systematic review reinforces previous reports that beta band oscillatory measures demonstrate a consistent relationship to Parkinsonian motor symptoms and ability to predict motor response to therapy. Specifically, high-beta, demonstrated a consistent ability to predict UPDRS-III responses to common PD therapies, while low-beta measures were associated with general Parkinsonian symptom severity. Continued research is needed to determine which beta subband demonstrates the greatest association to motor symptom subtypes and potentially offers clinical utility toward LFP-guided DBS programming and adaptive DBS.

Deep brain stimulation in Parkinson's disease: state of the art and future perspectives

For more than 30 years, Deep Brain Stimulation (DBS) has been a therapeutic option for Parkinson's disease (PD) treatment. However, this therapy is still underutilized mainly due to misinformation regarding risks and clinical outcomes. DBS can ameliorate several motor and non-motor symptoms, improving patients' quality of life. Furthermore, most of the improvement after DBS is long-lasting and present even in advanced PD. Adequate patient selection, precise electric leads placement, and correct DBS programming are paramount for good surgical outcomes. Nonetheless, DBS still has many limitations: axial symptoms and signs, such as speech, balance and gait, do not improve to the same extent as appendicular symptoms and can even be worsened as a direct or indirect consequence of surgery and stimulation. In addition, there are still unanswered questions regarding patient's selection, surgical planning and programming techniques, such as the role of surgicogenomics, more precise imaging-based lead placement, new brain targets, advanced programming strategies and hardware features. The net effect of these innovations should not only be to refine the beneficial effect we currently observe on selected symptoms and signs but also to improve treatment resistant facets of PD, such as axial and non-motor features. In this review, we discuss the current state of the art regarding DBS selection, implant, and programming, and explore new advances in the DBS field.