Randomized, Blinded Pilot Testing of Nonconventional Stimulation Patterns and Shapes in Parkinson's Disease and Essential Tremor: Evidence for Further Evaluating Narrow and Biphasic Pulses

Role of Neurosurgical Interventions in the Treatment of Movement Disorders Like Parkinson's Disease, Dystonia, and Tourette Syndrome

This article provides an overview of neurosurgical therapies for movement disorders (MDs), including Tourette syndrome, dystonia, Parkinson's disease (PD), and others. It focuses on the benefits of these treatments and suggests directions for further research. A total of 10 years' worth of English-language PubMed articles were combed through, with an emphasis on studies conducted in North America. To manage MDs like Parkinson's disease and Tourette syndrome, the results suggest that non-invasive neuromodulation techniques, closed-loop deep brain stimulation (DBS), and other advanced therapies may become the treatment of choice in the future. Research on dystonia is being focused on improving treatment methods by investigating new areas of the brain that might be stimulated through neurosurgery and looking at gene therapy. Modern technological developments, such as non-invasive neuromodulation procedures and improved imaging, provide promising substitutes for traditional surgical approaches. This study highlights the need for continuous clinical trials for better outcomes, which is why research and development in this area must continue.

Pilot Study of Acute Behavioral Effects of Pallidal Burst Stimulation in Parkinson's Disease

BACKGROUND

Burst-patterned pallidal deep brain stimulation (DBS) in an animal model of Parkinson's disease (PD) yields significantly prolonged therapeutic benefit compared to conventional continuous DBS, but its value in patients remains unclear.

OBJECTIVES

The aims were to evaluate the safety and tolerability of acute (<2 hours) burst DBS in PD patients and to evaluate preliminary clinical effectiveness relative to conventional DBS.

METHODS

Six PD patients were studied with DBS OFF, conventional DBS, and burst DBS. Unified Parkinson's Disease Rating Scale III (UPDRS-III) and proactive inhibition (using stop-signal task) were evaluated for each condition.

RESULTS

Burst and conventional DBS were equally tolerated without significant adverse events. Both stimulation patterns provided equivalent significant UPDRS-III reduction and increased proactive inhibition relative to DBS OFF.

CONCLUSIONS

This pilot study supports the safety and tolerability of burst DBS, with acute effects similar to conventional DBS. Further larger-scale studies are warranted given the potential benefits of burst DBS due to decreased total energy delivery. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Machine learning for adaptive deep brain stimulation in Parkinson's disease: closing the loop

Parkinson's disease (PD) is the second most common neurodegenerative disease bearing a severe social and economic impact. So far, there is no known disease modifying therapy and the current available treatments are symptom oriented. Deep Brain Stimulation (DBS) is established as an effective treatment for PD, however current systems lag behind today's technological potential. Adaptive DBS, where stimulation parameters depend on the patient's physiological state, emerges as an important step towards "smart" DBS, a strategy that enables adaptive stimulation and personalized therapy. This new strategy is facilitated by currently available neurotechnologies allowing the simultaneous monitoring of multiple signals, providing relevant physiological information. Advanced computational models and analytical methods are an important tool to explore the richness of the available data and identify signal properties to close the loop in DBS. To tackle this challenge, machine learning (ML) methods applied to DBS have gained popularity due to their ability to make good predictions in the presence of multiple variables and subtle patterns. ML based approaches are being explored at different fronts such as the identification of electrophysiological biomarkers and the development of personalized control systems, leading to effective symptom relief. In this review, we explore how ML can help overcome the challenges in the development of closed-loop DBS, particularly its role in the search for effective electrophysiology biomarkers. Promising results demonstrate ML potential for supporting a new generation of adaptive DBS, with better management of stimulation delivery, resulting in more efficient and patient-tailored treatments.

Comparison of subthalamic unilateral and bilateral theta burst deep brain stimulation in Parkinson's disease

High-frequency, conventional deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD) is usually applied bilaterally under the assumption of additive effects due to interhemispheric crosstalk. Theta burst stimulation (TBS-DBS) represents a new patterned stimulation mode with 5 Hz interburst and 200 Hz intraburst frequency, whose stimulation effects in a bilateral mode compared to unilateral are unknown. This single-center study evaluated acute motor effects of the most affected, contralateral body side in 17 PD patients with unilateral subthalamic TBS-DBS and 11 PD patients with bilateral TBS-DBS. Compared to therapy absence, both unilateral and bilateral TBS-DBS significantly improved (p < 0.05) lateralized Movement Disorder Society-Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) scores. Bilateral TBS-DBS revealed only slight, but not significant additional effects in comparison to unilateral TBS-DBS on total lateralized motor scores, but on the subitem lower limb rigidity. These results indicate that bilateral TBS-DBS has limited additive beneficial effects compared to unilateral TBS-DBS in the short term.

Myogenic and cortical evoked potentials vary as a function of stimulus pulse geometry delivered in the subthalamic nucleus of Parkinson's disease patients

Introduction

The therapeutic efficacy of deep brain stimulation (DBS) of the subthalamic nucleus (STN) for Parkinson's disease (PD) may be limited for some patients by the presence of stimulation-related side effects. Such effects are most often attributed to electrical current spread beyond the target region. Prior computational modeling studies have suggested that changing the degree of asymmetry of the individual phases of the biphasic, stimulus pulse may allow for more selective activation of neural elements in the target region. To the extent that different neural elements contribute to the therapeutic vs. side-effect inducing effects of DBS, such improved selectivity may provide a new parameter for optimizing DBS to increase the therapeutic window.

Methods

We investigated the effect of six different pulse geometries on cortical and myogenic evoked potentials in eight patients with PD whose leads were temporarily externalized following STN DBS implant surgery. DBS-cortical evoked potentials were quantified using peak to peak measurements and wavelets and myogenic potentials were quantified using RMS.

Results

We found that the slope of the recruitment curves differed significantly as a function of pulse geometry for both the cortical- and myogenic responses. Notably, this effect was observed most frequently when stimulation was delivered using a monopolar, as opposed to a bipolar, configuration.

Discussion

Manipulating pulse geometry results in differential physiological effects at both the cortical and neuromuscular level. Exploiting these differences may help to expand DBS' therapeutic window and support the potential for incorporating pulse geometry as an additional parameter for optimizing therapeutic benefit.

A review of neurophysiological effects and efficiency of waveform parameters in deep brain stimulation

Neurostimulation has diverse clinical applications and potential as a treatment for medically refractory movement disorders, epilepsy, and other neurological disorders. However, the parameters used to program electrodes-polarity, pulse width, amplitude, and frequency-and how they are adjusted have remained largely untouched since the 1970 s. This review summarizes the state-of-the-art in Deep Brain Stimulation (DBS) and highlights the need for further research to uncover the physiological mechanisms of neurostimulation. We focus on studies that reveal the potential for clinicians to use waveform parameters to selectively stimulate neural tissue for therapeutic benefit, while avoiding activating tissue associated with adverse effects. DBS uses cathodic monophasic rectangular pulses with passive recharging in clinical practice to treat neurological conditions such as Parkinson's Disease. However, research has shown that stimulation efficiency can be improved, and side effects reduced, through modulating parameters and adding novel waveform properties. These developments can prolong implantable pulse generator lifespan, reducing costs and surgery-associated risks. Waveform parameters can stimulate neurons based on axon orientation and intrinsic structural properties, providing clinicians with more precise targeting of neural pathways. These findings could expand the spectrum of diseases treatable with neuromodulation and improve patient outcomes.

Double blind, nonrandomized crossover study of active recharge biphasic deep brain stimulation for primary dystonia

BACKGROUND

Deep brain stimulation (DBS) of the globus pallidus interna (GPi) is an effective therapy for select patients with primary dystonia. DBS programming for dystonia is often challenging due to variable time to symptomatic improvement or stimulation induced side effects (SISE) such as capsular or optic tract activation which can prolong device optimization.

OBJECTIVE

To characterize the safety and tolerability of active recharge biphasic DBS (bDBS) in primary dystonia and to compare it to conventional clinical DBS (clinDBS).

METHODS

Ten subjects with primary dystonia and GPi DBS underwent a single center, double blind, nonrandomized crossover study comparing clinDBS versus bDBS. The testing occurred over two-days. bDBS and clinDBS were administered on separate days and each was activated for 6 h. Rating scales were collected by video recording and scored by four blinded movement disorders trained neurologists.

RESULTS

The bDBS paradigm was safe and well-tolerated in all ten subjects. There were no persistent SISE reported. The mean change in the Unified Dystonia Rating Scale after 4 h of stimulation was greater in bDBS when compared to clinDBS (-6.5 vs 0.3, p < 0.04).

CONCLUSION

In this pilot study, we demonstrated that biphasic DBS is a novel stimulation paradigm which can be administered safely. The biphasic waveform revealed a greater immediate improvement. Further studies are needed to determine whether this immediate improvement persists with chronic stimulation or if clinDBS will eventually achieve similar levels of improvement to bDBS over time.

Artificial neural network-based rapid predictor of biological nerve fiber activation for DBS applications

Objective.Computational models are powerful tools that can enable the optimization of deep brain stimulation (DBS). To enhance the clinical practicality of these models, their computational expense and required technical expertise must be minimized. An important aspect of DBS models is the prediction of neural activation in response to electrical stimulation. Existing rapid predictors of activation simplify implementation and reduce prediction runtime, but at the expense of accuracy. We sought to address this issue by leveraging the speed and generalization abilities of artificial neural networks (ANNs) to create a novel predictor of neural fiber activation in response to DBS.Approach.We developed six variations of an ANN-based predictor to predict the response of individual, myelinated axons to extracellular electrical stimulation. ANNs were trained using datasets generated from a finite-element model of an implanted DBS system together with multi-compartment cable models of axons. We evaluated the ANN-based predictors using three white matter pathways derived from group-averaged connectome data within a patient-specific tissue conductivity field, comparing both predicted stimulus activation thresholds and pathway recruitment across a clinically relevant range of stimulus amplitudes and pulse widths.Main results.The top-performing ANN could predict the thresholds of axons with a mean absolute error (MAE) of 0.037 V, and pathway recruitment with an MAE of 0.079%, across all parameters. The ANNs reduced the time required to predict the thresholds of 288 axons by four to five orders of magnitude when compared to multi-compartment cable models.Significance.We demonstrated that ANNs can be fast, accurate, and robust predictors of neural activation in response to DBS.

Adding a single pulse into high-frequency pulse stimulations can substantially alter the following episode of neuronal firing in rat hippocampus

Background. High-frequency stimulation (HFS) sequences of electrical pulses are commonly utilized in many types of neuromodulation therapies. The temporal pattern of pulse sequences characterized by varying inter-pulse intervals (IPI) has emerged as an adjustable dimension to generate diverse effects of stimulations to meet the needs for developing the therapies.Objective:To explore the hypothesis that a simple manipulation of IPI by inserting a pulse in HFS with a constant IPI can substantially change the neuronal responses.Approach. Antidromic HFS (A-HFS) and orthodromic HFS (O-HFS) sequences were respectively applied at the alveus (the efferent axons) and the Schaffer collaterals (the afferent axons) of hippocampal CA1 region in anesthetized ratsin-vivo. The HFS sequences lasted 120 s with a pulse frequency of 100 Hz and an IPI of 10 ms. In the late steady period (60-120 s) of the HFS, additional pulses were inserted into the original pulse sequences to investigate the alterations of neuronal responses to the changes in IPI. The amplitudes and latencies of antidromic/orthodromic population spikes (APS/OPS) evoked by pulses were measured to evaluate the alterations of the evoked firing of CA1 pyramidal neurons caused by the pulse insertions.Main Results. During the steady period of A-HFS at efferent axons, the evoked APSs were suppressed due to intermittent axonal block. Under this situation, inserting a pulse to shorten an IPI was able to redistribute the following neuronal firing thereby generating an episode of oscillation in the evoked APS sequence including APSs with significantly increased and decreased amplitudes. Also, during the steady period of O-HFS without obvious OPS, a pulse insertion was able to generate a large OPS, indicating a synchronized firing of a large population of post-synaptic neurons induced by a putative redistribution of activations at the afferent axons under O-HFS.Significance. This study firstly showed that under the situation of HFS-induced axonal block, changing an IPI by a single-pulse insertion can substantially redistribute the evoked neuronal responses to increase synchronized firing of neuronal populations during both antidromic and O-HFS with a constant IPI originally. The finding provides a potential way to enhance the HFS action on neuronal networks without losing some other functions of HFS such as generating axonal block.

Benchtop and bedside validation of a low-cost programmable cortical stimulator in a testbed for bi-directional brain-computer-interface research

Introduction

Bi-directional brain-computer interfaces (BD-BCI) to restore movement and sensation must achieve concurrent operation of recording and decoding of motor commands from the brain and stimulating the brain with somatosensory feedback.

Methods

A custom programmable direct cortical stimulator (DCS) capable of eliciting artificial sensorimotor response was integrated into an embedded BCI system to form a safe, independent, wireless, and battery powered testbed to explore BD-BCI concepts at a low cost. The BD-BCI stimulator output was tested in phantom brain tissue by assessing its ability to deliver electrical stimulation equivalent to an FDA-approved commercial electrical cortical stimulator. Subsequently, the stimulator was tested in an epilepsy patient with subcortical electrocorticographic (ECoG) implants covering the sensorimotor cortex to assess its ability to elicit equivalent responses as the FDA-approved counterpart. Additional safety features (impedance monitoring, artifact mitigation, and passive and active charge balancing mechanisms) were also implemeneted and tested in phantom brain tissue. Finally, concurrent operation with interleaved stimulation and BCI decoding was tested in a phantom brain as a proof-of-concept operation of BD-BCI system.

Results

The benchtop prototype BD-BCI stimulator's basic output features (current amplitude, pulse frequency, pulse width, train duration) were validated by demonstrating the output-equivalency to an FDA-approved commercial cortical electrical stimulator (R 2 > 0.99). Charge-neutral stimulation was demonstrated with pulse-width modulation-based correction algorithm preventing steady state voltage deviation. Artifact mitigation achieved a 64.5% peak voltage reduction. Highly accurate impedance monitoring was achieved with R 2 > 0.99 between measured and actual impedance, which in-turn enabled accurate charge density monitoring. An online BCI decoding accuracy of 93.2% between instructional cues and decoded states was achieved while delivering interleaved stimulation. The brain stimulation mapping via ECoG grids in an epilepsy patient showed that the two stimulators elicit equivalent responses.

Significance

This study demonstrates clinical validation of a fully-programmable electrical stimulator, integrated into an embedded BCI system. This low-cost BD-BCI system is safe and readily applicable as a testbed for BD-BCI research. In particular, it provides an all-inclusive hardware platform that approximates the limitations in a near-future implantable BD-BCI. This successful benchtop/human validation of the programmable electrical stimulator in a BD-BCI system is a critical milestone toward fully-implantable BD-BCI systems.

Deep brain-machine interfaces: sensing and modulating the human deep brain

Different from conventional brain-machine interfaces that focus more on decoding the cerebral cortex, deep brain-machine interfaces enable interactions between external machines and deep brain structures. They sense and modulate deep brain neural activities, aiming at function restoration, device control and therapeutic improvements. In this article, we provide an overview of multiple deep brain recording and stimulation techniques that can serve as deep brain-machine interfaces. We highlight two widely used interface technologies, namely deep brain stimulation and stereotactic electroencephalography, for technical trends, clinical applications and brain connectivity research. We discuss the potential to develop closed-loop deep brain-machine interfaces and achieve more effective and applicable systems for the treatment of neurological and psychiatric disorders.

Subthalamic nucleus deep brain stimulation driven by primary motor cortex γ2 activity in parkinsonian monkeys

In parkinsonism, subthalamic nucleus (STN) electrical deep brain stimulation (DBS) improves symptoms, but may be associated with side effects. Adaptive DBS (aDBS), which enables modulation of stimulation, may limit side effects, but limited information is available about clinical effectiveness and efficaciousness. We developed a brain-machine interface for aDBS, which enables modulation of stimulation parameters of STN-DBS in response to γ2 band activity (80-200 Hz) of local field potentials (LFPs) recorded from the primary motor cortex (M1), and tested its effectiveness in parkinsonian monkeys. We trained two monkeys to perform an upper limb reaching task and rendered them parkinsonian with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. Bipolar intracortical recording electrodes were implanted in the M1, and a recording chamber was attached to access the STN. In aDBS, the M1 LFPs were recorded, filtered into the γ2 band, and discretized into logic pulses by a window discriminator, and the pulses were used to modulate the interval and amplitude of DBS pulses. In constant DBS (cDBS), constant stimulus intervals and amplitudes were used. Reaction and movement times during the task were measured and compared between aDBS and cDBS. The M1-γ2 activities were increased before and during movements in parkinsonian monkeys and these activities modulated the aDBS pulse interval, amplitude, and dispersion. With aDBS and cDBS, reaction and movement times were significantly decreased in comparison to DBS-OFF. The electric charge delivered was lower with aDBS than cDBS. M1-γ2 aDBS in parkinsonian monkeys resulted in clinical benefits that did not exceed those from cDBS. However, M1-γ2 aDBS achieved this magnitude of benefit for only two thirds of the charge delivered by cDBS. In conclusion, M1-γ2 aDBS is an effective therapeutic approach which requires a lower electrical charge delivery than cDBS for comparable clinical benefits.

An Anodic Phase Can Facilitate Rather Than Weaken a Cathodic Phase to Activate Neurons in Biphasic-Pulse Axonal Stimulations

Electrical pulses have been promisingly utilized in neural stimulations to treat various diseases. Usually, charge-balanced biphasic pulses are applied in the clinic to eliminate the possible side effects caused by charge accumulations. Because of its reversal action to the preceding cathodic phase, the subsequent anodic phase has been commonly considered to lower the activation efficiency of biphasic pulses. However, an anodic pulse itself can also activate axons with its “virtual cathode” effect. Therefore, we hypothesized that the anodic phase of a biphasic pulse could facilitate neuronal activation in some circumstances. To verify the hypothesis, we compared the activation efficiencies of cathodic pulse, biphasic pulse, and anodic pulse applied in both monopolar and bipolar modes in the axonal stimulation of alveus in rat hippocampal CA1 region in vivo. The antidromically evoked population spikes (APS) were recorded and used to evaluate the amount of integrated firing of pyramidal neurons induced by pulse stimulations. We also used a computational model to investigate the pulse effects on axons at various distances from the stimulation electrode. The experimental results showed that, with a small pulse intensity, a cathodic pulse recruited more neurons to fire than a biphasic pulse. However, the situation was reversed with an increased pulse intensity. In addition, setting an inter-phase gap of 100 μs was able to increase the activation efficiency of a biphasic pulse to exceed a cathodic pulse even with a relatively small pulse intensity. Furthermore, the latency of APS evoked by a cathodic pulse was always longer than that of APS evoked by a biphasic pulse, indicating different initial sites of the neuronal firing evoked by the different types of pulses. The computational results of axon modeling showed that the subsequent anodic phase was able to relieve the hyperpolarization block in the flanking regions generated by the preceding cathodic phase, thereby increasing rather than decreasing the activation efficiency of a biphasic pulse with a relatively great intensity. These results of both rat experiments and computational modeling firstly reveal a facilitation rather than an attenuation effect of the anodic phase on biphasic-pulse stimulations, which provides important information for designing electrical stimulations for neural therapies.

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

Deep brain stimulation (DBS) has advanced treatment options for a variety of neurologic and neuropsychiatric conditions. As the technology for DBS continues to progress, treatment efficacy will continue to improve and disease indications will expand. Hardware advances such as longer-lasting batteries will reduce the frequency of battery replacement and segmented leads will facilitate improvements in the effectiveness of stimulation and have the potential to minimize stimulation side effects. Targeting advances such as specialized imaging sequences and "connectomics" will facilitate improved accuracy for lead positioning and trajectory planning. Software advances such as closed-loop stimulation and remote programming will enable DBS to be a more personalized and accessible technology. The future of DBS continues to be promising and holds the potential to further improve quality of life. In this review we will address the past, present and future of DBS.

Deep brain stimulation: is it time to change gears by closing the loop?

Objective.Adaptive deep brain stimulation (aDBS) is a form of invasive stimulation that was conceived to overcome the technical limitations of traditional DBS, which delivers continuous stimulation of the target structure without considering patients' symptoms or status in real-time. Instead, aDBS delivers on-demand, contingency-based stimulation. So far, aDBS has been tested in several neurological conditions, and will be soon extensively studied to translate it into clinical practice. However, an exhaustive description of technical aspects is still missing.Approach.in this topical review, we summarize the knowledge about the current (and future) aDBS approach and control algorithms to deliver the stimulation, as reference for a deeper undestending of aDBS model.Main results.We discuss the conceptual and functional model of aDBS, which is based on the sensing module (that assesses the feedback variable), the control module (which interpretes the variable and elaborates the new stimulation parameters), and the stimulation module (that controls the delivery of stimulation), considering both the historical perspective and the state-of-the-art of available biomarkers.Significance.aDBS modulates neuronal circuits based on clinically relevant biofeedback signals in real-time. First developed in the mid-2000s, many groups have worked on improving closed-loop DBS technology. The field is now at a point in conducting large-scale randomized clinical trials to translate aDBS into clinical practice. As we move towards implanting brain-computer interfaces in patients, it will be important to understand the technical aspects of aDBS.

Implantable Pulse Generators for Deep Brain Stimulation: Challenges, Complications, and Strategies for Practicality and Longevity

Deep brain stimulation (DBS) represents an important treatment modality for movement disorders and other circuitopathies. Despite their miniaturization and increasing sophistication, DBS systems share a common set of components of which the implantable pulse generator (IPG) is the core power supply and programmable element. Here we provide an overview of key hardware and software specifications of commercially available IPG systems such as rechargeability, MRI compatibility, electrode configuration, pulse delivery, IPG case architecture, and local field potential sensing. We present evidence-based approaches to mitigate hardware complications, of which infection represents the most important factor. Strategies correlating positively with decreased complications include antibiotic impregnation and co-administration and other surgical considerations during IPG implantation such as the use of tack-up sutures and smaller profile devices.Strategies aimed at maximizing battery longevity include patient-related elements such as reliability of IPG recharging or consistency of nightly device shutoff, and device-specific such as parameter delivery, choice of lead configuration, implantation location, and careful selection of electrode materials to minimize impedance mismatch. Finally, experimental DBS systems such as ultrasound, magnetoelectric nanoparticles, and near-infrared that use extracorporeal powered neuromodulation strategies are described as potential future directions for minimally invasive treatment.

Clinical perspectives of adaptive deep brain stimulation

BACKGROUND

The application of stimulators implanted directly over deep brain structures (i.e., deep brain stimulation, DBS) was developed in the late 1980s and has since become a mainstream option to treat several neurological conditions. Conventional DBS involves the continuous stimulation of the target structure, which is an approach that cannot adapt to patients' changing symptoms or functional status in real-time. At the beginning of 2000, a more sophisticated form of stimulation was conceived to overcome these limitations. Adaptive deep brain stimulation (aDBS) employs on-demand, contingency-based stimulation to stimulate only when needed. So far, aDBS has been tested in several pathological conditions in animal and human models.

OBJECTIVE

To review the current findings obtained from application of aDBS to animal and human models that highlights effects on motor, cognitive and psychiatric behaviors.

FINDINGS

while aDBS has shown promising results in the treatment of Parkinson's disease and essential tremor, the possibility of its use in less common DBS indications, such as cognitive and psychiatric disorders (Alzheimer's disease, obsessive-compulsive disorder, post-traumatic stress disorder) is still challenging.

CONCLUSIONS

While aDBS seems to be effective to treat movement disorders (Parkinson's disease and essential tremor), its role in cognitive and psychiatric disorders is to be determined, although neurophysiological assumptions are promising.

Digital Health Integration With Neuromodulation Therapies: The Future of Patient-Centric Innovation in Neuromodulation

Digital health can drive patient-centric innovation in neuromodulation by leveraging current tools to identify response predictors and digital biomarkers. Iterative technological evolution has led us to an ideal point to integrate digital health with neuromodulation. Here, we provide an overview of the digital health building-blocks, the status of advanced neuromodulation technologies, and future applications for neuromodulation with digital health integration.

Safety and Tolerability of Burst-Cycling Deep Brain Stimulation for Freezing of Gait in Parkinson's Disease

Background: Freezing of gait (FOG) is a common symptom in Parkinson’s disease (PD) and can be difficult to treat with dopaminergic medications or with deep brain stimulation (DBS). Novel stimulation paradigms have been proposed to address suboptimal responses to conventional DBS programming methods. Burst-cycling deep brain stimulation (BCDBS) delivers current in various frequencies of bursts (e.g., 4, 10, or 15 Hz), while maintaining an intra-burst frequency identical to conventional DBS.

Objective: To evaluate the safety and tolerability of BCDBS in PD patients with FOG.

Methods: Ten PD subjects with STN or GPi DBS and complaints of FOG were recruited for this single center, single blinded within-subject crossover study. For each subject, we compared 4, 10, and 15 Hz BCDBS to conventional DBS during the PD medication-OFF state.

Results: There were no serious adverse events with BCDBS. It was feasible and straightforward to program BCDBS in the clinic setting. The benefit was comparable to conventional DBS in measures of FOG, functional mobility and in PD motor symptoms. BCDBS had lower battery consumption when compared to conventional DBS.

Conclusions: BCDBS was feasible, safe and well tolerated and it has potential to be a viable future DBS programming strategy.

Wearable and Implantable Electroceuticals for Therapeutic Electrostimulations

Wearable and implantable electroceuticals (WIEs) for therapeutic electrostimulation (ES) have become indispensable medical devices in modern healthcare. In addition to functionality, device miniaturization, conformability, biocompatibility, and/or biodegradability are the main engineering targets for the development and clinical translation of WIEs. Recent innovations are mainly focused on wearable/implantable power sources, advanced conformable electrodes, and efficient ES on targeted organs and tissues. Herein, nanogenerators as a hotspot wearable/implantable energy-harvesting technique suitable for powering WIEs are reviewed. Then, electrodes for comfortable attachment and efficient delivery of electrical signals to targeted tissue/organ are introduced and compared. A few promising application directions of ES are discussed, including heart stimulation, nerve modulation, skin regeneration, muscle activation, and assistance to other therapeutic modalities.

Technology of deep brain stimulation: current status and future directions

Deep brain stimulation (DBS) is a neurosurgical procedure that allows targeted circuit-based neuromodulation. DBS is a standard of care in Parkinson disease, essential tremor and dystonia, and is also under active investigation for other conditions linked to pathological circuitry, including major depressive disorder and Alzheimer disease. Modern DBS systems, borrowed from the cardiac field, consist of an intracranial electrode, an extension wire and a pulse generator, and have evolved slowly over the past two decades. Advances in engineering and imaging along with an improved understanding of brain disorders are poised to reshape how DBS is viewed and delivered to patients. Breakthroughs in electrode and battery designs, stimulation paradigms, closed-loop and on-demand stimulation, and sensing technologies are expected to enhance the efficacy and tolerability of DBS. In this Review, we provide a comprehensive overview of the technical development of DBS, from its origins to its future. Understanding the evolution of DBS technology helps put the currently available systems in perspective and allows us to predict the next major technological advances and hurdles in the field.

Time-dynamic pulse modulation of spinal cord stimulation reduces mechanical hypersensitivity and spontaneous pain in rats

Enhancing the efficacy of spinal cord stimulation (SCS) is needed to alleviate the burden of chronic pain and dependence on opioids. Present SCS therapies are characterized by the delivery of constant stimulation in the form of trains of tonic pulses (TPs). We tested the hypothesis that modulated SCS using novel time-dynamic pulses (TDPs) leads to improved analgesia and compared the effects of SCS using conventional TPs and a collection of TDPs in a rat model of neuropathic pain according to a longitudinal, double-blind, and crossover design. We tested the effects of the following SCS patterns on paw withdrawal threshold and resting state EEG theta power as a biomarker of spontaneous pain: Tonic (conventional), amplitude modulation, pulse width modulation, sinusoidal rate modulation, and stochastic rate modulation. Results demonstrated that under the parameter settings tested in this study, all tested patterns except pulse width modulation, significantly reversed mechanical hypersensitivity, with stochastic rate modulation achieving the highest efficacy, followed by the sinusoidal rate modulation. The anti-nociceptive effects of sinusoidal rate modulation on EEG outlasted SCS duration on the behavioral and EEG levels. These results suggest that TDP modulation may improve clinical outcomes by reducing pain intensity and possibly improving the sensory experience.

Advances and Future Directions of Neuromodulation in Neurologic Disorders

"Deep brain stimulation is a safe and effective therapy for the management of a variety of neurologic conditions with Food and Drug Administration or humanitarian exception approval for Parkinson disease, dystonia, tremor, and obsessive-compulsive disorder. Advances in neurophysiology, neuroimaging, and technology have driven increasing interest in the potential benefits of neurostimulation in other neuropsychiatric conditions including dementia, depression, pain, Tourette syndrome, and epilepsy, among others. New anatomic or combined targets are being investigated in these conditions to improve symptoms refractory to medications or standard stimulation."

Optimal Parameters of Deep Brain Stimulation in Essential Tremor: A Meta-Analysis and Novel Programming Strategy

The programming of deep brain stimulation (DBS) parameters for tremor is laborious and empirical. Despite extensive efforts, the end-result is often suboptimal. One reason for this is the poorly understood relationship between the stimulation parameters’ voltage, pulse width, and frequency. In this study, we aim to improve DBS programming for essential tremor (ET) by exploring a new strategy. At first, the role of the individual DBS parameters in tremor control was characterized using a meta-analysis documenting all the available parameters and tremor outcomes. In our novel programming strategy, we applied 10 random combinations of stimulation parameters in eight ET-DBS patients with suboptimal tremor control. Tremor severity was assessed using accelerometers and immediate and sustained patient-reported outcomes (PRO’s), including the occurrence of side-effects. The meta-analysis showed no substantial relationship between individual DBS parameters and tremor suppression. Nevertheless, with our novel programming strategy, a significantly improved (accelerometer p = 0.02, PRO p = 0.02) and sustained (p = 0.01) tremor suppression compared to baseline was achieved. Less side-effects were encountered compared to baseline. Our pilot data show that with this novel approach, tremor control can be improved in ET patients with suboptimal tremor control on DBS. In addition, this approach proved to have a beneficial effect on stimulation-related complications.

Proceedings of the Seventh Annual Deep Brain Stimulation Think Tank: Advances in Neurophysiology, Adaptive DBS, Virtual Reality, Neuroethics and Technology

The Seventh Annual Deep Brain Stimulation (DBS) Think Tank held on September 8th of 2019 addressed the most current: (1) use and utility of complex neurophysiological signals for development of adaptive neurostimulation to improve clinical outcomes; (2) Advancements in recent neuromodulation techniques to treat neuropsychiatric disorders; (3) New developments in optogenetics and DBS; (4) The use of augmented Virtual reality (VR) and neuromodulation; (5) commercially available technologies; and (6) ethical issues arising in and from research and use of DBS. These advances serve as both "markers of progress" and challenges and opportunities for ongoing address, engagement, and deliberation as we move to improve the functional capabilities and translational value of DBS. It is in this light that these proceedings are presented to inform the field and initiate ongoing discourse. As consistent with the intent, and spirit of this, and prior DBS Think Tanks, the overarching goal is to continue to develop multidisciplinary collaborations to rapidly advance the field and ultimately improve patient outcomes.

Deep brain stimulation in essential tremor: targets, technology, and a comprehensive review of clinical outcomes

Introduction: Essential tremor (ET) is a common movement disorder with an estimated prevalence of 0.9% worldwide. Deep brain stimulation (DBS) is an established therapy for medication refractory and debilitating tremor. With the arrival of next generation technology, the implementation and delivery of DBS has been rapidly evolving. This review will highlight the current applications and constraints for DBS in ET.Areas covered: The mechanism of action, targets for neuromodulation, next generation guidance techniques, symptom-specific applications, and long-term efficacy will be reviewed.Expert opinion: The posterior subthalamic area and zona incerta are alternative targets to thalamic DBS in ET. However, they may be associated with additional stimulation-induced side effects. Novel stimulation paradigms and segmented electrodes provide innovative approaches to DBS programming and stimulation-induced side effects.

Model-based optimized phase-deviation deep brain stimulation for Parkinson 's disease

High-frequency deep brain stimulation (HF-DBS) of the subthalamic nucleus (STN), globus pallidus interna (GPi) and globus pallidus externa (GPe) are often considered as effective methods for the treatment of Parkinson's disease (PD). However, the stimulation of a single nucleus by HF-DBS can cause specific physical damage, produce side effects and usually consume more electrical energy. Therefore, we use a biophysically-based model of basal ganglia-thalamic circuits to explore more effective stimulation patterns to reduce adverse effects and save energy. In this paper, we computationally investigate the combined DBS of two nuclei with the phase deviation between two stimulation waveforms (CDBS). Three different stimulation combination strategies are proposed, i.e., STN and GPe CDBS (SED), STN and GPi CDBS (SID), as well as GPi and GPe CDBS (GGD). Resultantly, it is found that anti-phase CDBS is more effective in improving parkinsonian dynamical properties, including desynchronization of neurons and the recovery of the thalamus relay ability. Detailed simulation investigation shows that anti-phase SED and GGD are superior to SID. Besides, the energy consumption can be largely reduced by SED and GGD (72.5% and 65.5%), compared to HF-DBS. These results provide new insights into the optimal stimulation parameter and target choice of PD, which may be helpful for the clinical practice.

Square Biphasic Pulse Deep Brain Stimulation for Parkinson's Disease: The BiP-PD Study

Background

Conventional Parkinson’s disease (PD) deep brain stimulation (DBS) utilizes a pulse with an active phase and a passive charge-balancing phase. A pulse-shaping strategy that eliminates the passive phase may be a promising approach to addressing movement disorders.

Objectives

The current study assessed the safety and tolerability of square biphasic pulse shaping (sqBIP) DBS for use in PD.

Methods

This small pilot safety and tolerability study compared sqBiP versus conventional DBS. Nine were enrolled. The safety and tolerability were assessed over a 3-h period on sqBiP. Friedman’s test compared blinded assessments at baseline, washout, and 30 min, 1 h, 2 h, and 3 h post sqBIP.

Results

Biphasic pulses were safe and well tolerated by all participants. SqBiP performed as well as conventional DBS without significant differences in motor scores nor accelerometer or gait measures.

Conclusion

Biphasic pulses were well-tolerated and provided similar benefit to conventional DBS. Further studies should address effectiveness of sqBIP in select PD patients.

Temporally irregular electrical stimulation to the epileptogenic focus delays epileptogenesis in rats

BACKGROUND

Variation in the temporal patterns of electrical pulses in stimulation trains has opened a new field of opportunity for the treatment of neurological disorders, such as pharmacoresistant temporal lobe epilepsy. Whether this novel type of stimulation affects epileptogenesis remains to be investigated.

OBJECTIVE

The purpose of this study was to analyze the effects of temporally irregular deep brain stimulation on kindling-induced epileptogenesis in rats.

METHODS

Temporally irregular deep brain stimulation was delivered at different times with respect to the kindling stimulation. Behavioral and electrographic changes on kindling acquisition were compared with a control group and a temporally regular deep brain stimulation-treated group. The propagation of epileptiform activity was analyzed with wavelet cross-correlation analysis, and interictal epileptiform discharge ratios were obtained.

RESULTS

Temporally irregular deep brain stimulation delivered in the epileptogenic focus during the interictal period shortened the daily afterdischarge duration, slowed the progression of seizure stages, diminished the generalized seizure duration and interfered with the propagation of epileptiform activity from the seizure onset zone to the ipsi- and contralateral motor cortex. We also found a negative correlation between seizure severity and interictal epileptiform discharges in rats stimulated with temporally irregular deep brain stimulation.

CONCLUSION

These results provide evidence that temporally irregular deep brain stimulation interferes with the establishment of epilepsy by delaying epileptogenesis by almost twice as long in kindling animals. Thus, temporally irregular deep brain stimulation could be a preventive approach against epilepsy.

Analysis of a poly(ε-decalactone)/silver nanowire composite as an electrically conducting neural interface biomaterial

Background

Advancement in polymer technologies, facilitated predominantly through chemical engineering approaches or through the identification and utilization of novel renewable resources, has been a steady focus of biomaterials research for the past 50 years. Aliphatic polyesters have been exploited in numerous biomedical applications including the formulation of soft-tissue sutures, bone fixation devices, cardiovascular stents etc. Biomimetic ‘soft’ polymer formulations are of interest in the design of biological interfaces and specifically, in the development of implantable neuroelectrode systems intended to interface with neural tissues. Critically, soft polymer formulations have been shown to address the challenges associated with the disregulation of mechanotransductive processes and micro-motion induced inflammation at the electrode/tissue interface. In this study, a polyester-based poly(ε-decalactone)/silver nanowire (EDL:Ag) composite was investigated as a novel electrically active biomaterial with neural applications.

Neural interfaces were formulated through spin coating of a polymer/nanowire formulation onto the surface of a Pt electrode to form a biocompatible EDL matrix supported by a percolated network of silver nanowires. As-formed EDL:Ag composites were characterized by means of infrared spectroscopy, scanning electron microscopy and electrochemical methods, with their cytocompatibility assessed using primary cultures of a mixed neural population obtained from the ventral mesencephalon of Sprague-Dawley rat embryos.

Results

Electrochemical characterization of various EDL:Ag composites indicated EDL:Ag 10:1 as the most favourable formulation, exhibiting high charge storage capacity (8.7 ± 1.0 mC/cm²), charge injection capacity (84.3 ± 1.4 μC/cm²) and low impedance at 1 kHz (194 ± 28 Ω), outperforming both pristine EDL and bare Pt electrodes. The in vitro biological evaluation showed that EDL:Ag supported significant neuron viability in culture and to promote neurite outgrowth, which had the average length of 2300 ± 6 μm following 14 days in culture, 60% longer than pristine EDL and 120% longer than bare Pt control substrates.

Conclusions

EDL:Ag nanocomposites are shown to serve as robust neural interface materials, possessing favourable electrochemical characteristics together with high neural cytocompatibility.

An update on best practice of deep brain stimulation in Parkinson's disease

During the last 30 years, deep brain stimulation (DBS) has evolved into the clinical standard of care as a highly effective treatment for advanced Parkinson’s disease. Careful patient selection, an individualized anatomical target localization and meticulous evaluation of stimulation parameters for chronic DBS are crucial requirements to achieve optimal results. Current hardware-related advances allow for a more focused, individualized stimulation and hence may help to achieve optimal clinical results. However, current advances also increase the degrees of freedom for DBS programming and therefore challenge the skills of healthcare providers. This review gives an overview of the clinical effects of DBS, the criteria for patient, target, and device selection, and finally, offers strategies for a structured programming approach.

A review of basal ganglia circuits and physiology: Application to deep brain stimulation

INTRODUCTION

Drawing on the seminal work of DeLong, Albin, and Young, we have now entered an era of basal ganglia neuromodulation. Understanding, re-evaluating, and leveraging the lessons learned from neuromodulation will be crucial to facilitate an increased and improved application of neuromodulation in human disease.

METHODS

We will focus on deep brain stimulation (DBS) - the most common form of basal ganglia neuromodulation - however, similar principles can apply to other neuromodulation modalities. We start with a brief review of DBS for Parkinson's disease, essential tremor, dystonia, and Tourette syndrome. We then review hallmark studies on basal ganglia circuits and electrophysiology resulting from decades of experience in neuromodulation. The organization and content of this paper follow Dr. Okun's Lecture from the 2018 Parkinsonism and Related Disorders World Congress.

RESULTS

Information gained from neuromodulation has led to an expansion of the basal ganglia rate model, an enhanced understanding of nuclei dynamics, an emerging focus on pathological oscillations, a revision of the tripartite division of the basal ganglia, and a redirected focus toward individualized symptom-specific stimulation. Though there have been many limitations of the basal ganglia "box model," the construct provided the necessary foundation to advance the field. We now understand that information in the basal ganglia is encoded through complex neural responses that can be reliably measured and used to infer disease states for clinical translation.

CONCLUSIONS

Our deepened understanding of basal ganglia physiology will drive new neuromodulation strategies such as adaptive DBS or cell-specific neuromodulation through the use of optogenetics.

An update on adaptive deep brain stimulation in Parkinson's disease

Advancing conventional open‐loop DBS as a therapy for PD is crucial for overcoming important issues such as the delicate balance between beneficial and adverse effects and limited battery longevity that are currently associated with treatment. Closed‐loop or adaptive DBS aims to overcome these limitations by real‐time adjustment of stimulation parameters based on continuous feedback input signals that are representative of the patient's clinical state. The focus of this update is to discuss the most recent developments regarding potential input signals and possible stimulation parameter modulation for adaptive DBS in PD. Potential input signals for adaptive DBS include basal ganglia local field potentials, cortical recordings (electrocorticography), wearable sensors, and eHealth and mHealth devices. Furthermore, adaptive DBS can be applied with different approaches of stimulation parameter modulation, the feasibility of which can be adapted depending on specific PD phenotypes. Implementation of technological developments like machine learning show potential in the design of such approaches; however, energy consumption deserves further attention. Furthermore, we discuss future considerations regarding the clinical implementation of adaptive DBS in PD. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Systems approaches to optimizing deep brain stimulation therapies in Parkinson's disease

Over the last 30 years, deep brain stimulation (DBS) has been used to treat chronic neurological diseases like dystonia, obsessive-compulsive disorders, essential tremor, Parkinson's disease, and more recently, dementias, depression, cognitive disorders, and epilepsy. Despite its wide use, DBS presents numerous challenges for both clinicians and engineers. One challenge is the design of novel, more efficient DBS therapies, which are hampered by the lack of complete understanding about the cellular mechanisms of therapeutic DBS. Another challenge is the existence of redundancy in clinical outcomes, that is, different DBS programs can result in similar clinical benefits but very little information (e.g., predictive models, longitudinal data, metrics, etc.) is available to select one program over another. Finally, there is high variability in patients' responses to DBS, which forces clinicians to carefully adjust the stimulation settings to each patient via lengthy programming sessions. Researchers in neural engineering and systems biology have been tackling these challenges over the past few years with the specific goal of developing novel DBS therapies, design methodologies, and computational tools that optimize the therapeutic effects of DBS in each patient. Furthermore, efforts are being made to automatically adapt the DBS treatment to the fluctuations of disease symptoms. A review of the quantitative approaches currently available for the treatment of Parkinson's disease is presented here with an emphasis on the contributions that systems theoretical approaches have provided to understand the global dynamics of complex neuronal circuits in the brain under DBS. This article is categorized under: Translational, Genomic, and Systems Medicine > Therapeutic Methods Analytical and Computational Methods > Computational Methods Analytical and Computational Methods > Dynamical Methods Physiology > Mammalian Physiology in Health and Disease.

Effects of the temporal pattern of subthalamic deep brain stimulation on the neuronal complexity in the globus pallidus

Deep brain stimulation (DBS) is a surgical treatment for Parkinson's disease (PD) but, despite clinical efficacy, the mechanisms of DBS still require investigation. Recent evidence suggests that the temporal pattern of the electrical pulses may be critical to the therapeutic merit of DBS and carefully-designed, non-regular patterns could ameliorate some of the motor symptoms in PD. It is unclear, though, how different stimulation patterns affect the neural activity in the basal ganglia and whether this is related to the pathophysiology of PD. In this study, a non-human primate was treated with DBS of the subthalamic nucleus while single-unit recordings were collected in the animal's globus pallidus internus (GPi). Three stimulation patterns were applied (one regular, two non-regular) and the stimulation effects on the GPi spike trains were assessed via point process modeling. On a preliminary set of 23 GPi neurons, we show that regular DBS maximized the neuronal complexity, which is a measure of the amount of information that a single neuron can encode, and significantly increased the dependency of the neurons' spike trains on the background ensemble activity through an articulated balance of excitation and inhibition. Overall, regular DBS caused the largest modulation in the neurons' spiking pattern and the largest increment in encoding capabilities. Both results may be relevant to the mechanisms of therapeutic DBS.

Closed-loop low-frequency DBS restores thalamocortical relay fidelity in a computational model of the motor loop

Closed-loop modulation of deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD) is investigated to automatically adjust the stimulation to the patients' conditions, optimize the clinical outcomes, and reduce the energy requirements. This study proposes a closed-loop control system for real-time adaptation of the STN-DBS amplitude based on the neural activity in the motor thalamus. Population-averaged post-stimulus time histograms are used to measure the average effects of STN-DBS on the thalamocortical neurons and a L₂-norm minimization problem is solved to design the control algorithm, while the frequency of stimulation is kept constant. Applied on a large-scale, biophysically-based, anatomically-compliant model of the cortico-basal ganglia-thalamo-cortical motor loop under PD conditions, our adaptive DBS significantly (P-value P<;0.05) improved the relay fidelity of the thalamocortical neurons and restored the average power of the thalamocortical spike trains in the band [3, 100] Hz, two indicators of restored thalamocortical activity. Furthermore, adaptive-DBS significantly decreased the energy requirements when compared with non-adaptive-DBS at the same frequency. Finally, 30- and 60-Hz-adaptive-DBS determined the maximal restoration of thalamocortical activity and outperformed high-frequency, non-adaptive-DBS. Overall, results suggest that a feedback-controlled, low-frequency DBS pattern may result in significant restoration of the thalamocortical encoding while lowering the energy requirements.

Evolving Applications, Technological Challenges and Future Opportunities in Neuromodulation: Proceedings of the Fifth Annual Deep Brain Stimulation Think Tank

The annual Deep Brain Stimulation (DBS) Think Tank provides a focal opportunity for a multidisciplinary ensemble of experts in the field of neuromodulation to discuss advancements and forthcoming opportunities and challenges in the field. The proceedings of the fifth Think Tank summarize progress in neuromodulation neurotechnology and techniques for the treatment of a range of neuropsychiatric conditions including Parkinson's disease, dystonia, essential tremor, Tourette syndrome, obsessive compulsive disorder, epilepsy and cognitive, and motor disorders. Each section of this overview of the meeting provides insight to the critical elements of discussion, current challenges, and identified future directions of scientific and technological development and application. The report addresses key issues in developing, and emphasizes major innovations that have occurred during the past year. Specifically, this year's meeting focused on technical developments in DBS, design considerations for DBS electrodes, improved sensors, neuronal signal processing, advancements in development and uses of responsive DBS (closed-loop systems), updates on National Institutes of Health and DARPA DBS programs of the BRAIN initiative, and neuroethical and policy issues arising in and from DBS research and applications in practice.

An evaluation of the effect of pulse-shape on grey and white matter stimulation in the rat brain

Despite the current success of neuromodulation, standard biphasic, rectangular pulse shapes may not be optimal to achieve symptom alleviation. Here, we compared stimulation efficiency (in terms of charge) between complex and standard pulses in two areas of the rat brain. In motor cortex, Gaussian and interphase gap stimulation (IPG) increased stimulation efficiency in terms of charge per phase compared with a standard pulse. Moreover, IPG stimulation of the deep mesencephalic reticular formation in freely moving rats was more efficient compared to a standard pulse. We therefore conclude that complex pulses are superior to standard stimulation, as less charge is required to achieve the same behavioral effects in a motor paradigm. These results have important implications for the understanding of electrical stimulation of the nervous system and open new perspectives for the design of the next generation of safe and efficient neural implants.

Square biphasic pulse deep brain stimulation for essential tremor: The BiP tremor study

BACKGROUND

Conventional deep brain stimulation (DBS) utilizes regular, high frequency pulses to treat medication-refractory symptoms in essential tremor (ET). Modifications of DBS pulse shape to achieve improved effectiveness is a promising approach.

OBJECTIVES

The current study assessed the safety, tolerability and effectiveness of square biphasic pulse shaping as an alternative to conventional ET DBS.

METHODS

This pilot study compared biphasic pulses (BiP) versus conventional DBS pulses (ClinDBS). Eleven ET subjects with clinically optimized ventralis intermedius nucleus DBS were enrolled. Objective measures were obtained over 3 h while ON BiP stimulation.

RESULTS

There was observed benefit in the Fahn-Tolosa Tremor Rating Scale (TRS) for BiP conditions when compared to the DBS off condition and to ClinDBS setting. Total TRS scores during the DBS OFF condition (28.5 IQR = 24.5-35.25) were significantly higher than the other time points. Following active DBS, TRS improved to (20 IQR = 13.8-24.3) at ClinDBS setting and to (16.5 IQR = 12-20.75) at the 3 h period ON BiP stimulation (p = 0.001). Accelerometer recordings revealed improvement in tremor at rest (χ² = 16.1, p = 0.006), posture (χ² = 15.9, p = 0.007) and with action (χ² = 32.1, p=<0.001) when comparing median total scores at ClinDBS and OFF DBS conditions to 3 h ON BiP stimulation. There were no adverse effects and gait was not impacted.

CONCLUSION

BiP was safe, tolerable and effective on the tremor symptoms when tested up to 3 h. This study demonstrated the feasibility of applying a novel DBS waveform in the clinic setting. Larger prospective studies with longer clinical follow-up will be required.

DBS Programming: An Evolving Approach for Patients with Parkinson's Disease

Deep brain stimulation (DBS) surgery is a well-established therapy for control of motor symptoms in Parkinson's disease. Despite an appropriate targeting and an accurate placement of DBS lead, a thorough and efficient programming is critical for a successful clinical outcome. DBS programming is a time consuming and laborious manual process. The current approach involves use of general guidelines involving determination of the lead type, electrode configuration, impedance check, and battery check. However there are no validated and well-established programming protocols. In this review, we will discuss the current practice and the recent advances in DBS programming including the use of interleaving, fractionated current, directional steering of current, and the use of novel DBS pulses. These technological improvements are focused on achieving a more efficient control of clinical symptoms with the least possible side effects. Other promising advances include the introduction of computer guided programming which will likely impact the efficiency of programming for the clinicians and the possibility of remote Internet based programming which will improve access to DBS care for the patients.

Reengineering deep brain stimulation for movement disorders: Emerging technologies

Deep brain stimulation (DBS) is a neurosurgical technique, which consists of continuous delivery of an electrical pulse through chronically implanted electrodes connected to a neurostimulator, programmable in amplitude, pulse width, frequency, and stimulation channel. DBS is a promising treatment option for addressing severe and drug-resistant movement disorders. The success of DBS therapy is a combination of surgical implantation techniques, device technology, and clinical programming strategies. Changes in device settings require highly trained and experienced clinicians to achieve maximal therapeutic benefit for each targeted symptom, and optimization of stimulation parameters can take many visits. Thus, the development of innovative DBS technologies that can optimize the clinical implementation of DBS will lead to wider scale utilization. This review aims to present engineering approaches that have the potential to improve clinical outcomes of DBS, focusing on the development novel temporal patterns, innovative electrode designs, computational models to guide stimulation, closed-loop DBS, and remote programming.

Current Practice and the Future of Deep Brain Stimulation Therapy in Parkinson's Disease

Deep brain stimulation (DBS) is an effective therapy for Parkinson's disease patients experiencing motor fluctuations, medication-resistant tremor, and/or dyskinesia. Currently, the subthalamic nucleus and the globus pallidus internus are the two most widely used targets, with individual advantages and disadvantages influencing patient selection. Potential DBS patients are selected using the few existing guidelines and the available DBS literature, and many centers employ an interdisciplinary team review of the individual's risk-benefit profile. Programmed settings vary based on institution- or physician-specific protocols designed to maximize benefits and limit adverse effects. Expectations should be realistic and clearly defined during the evaluation process, and each bothersome symptom should be addressed in the context of building the risk-benefit profile. Current DBS research is focused on improved symptom control, the development of newer technologies, and the improved efficiency of stimulation delivery. Techniques deliver stimulation in a more personalized way, and methods of adaptive DBS such as closed-loop approaches are already on the horizon.

A pilot trial of square biphasic pulse deep brain stimulation for dystonia: The BIP dystonia study

BACKGROUND

Dystonia often has inconsistent benefits and requires more energy-demanding DBS settings. Studies suggest that squared biphasic pulses could provide significant clinical benefit; however, dystonia patients have not been explored.

OBJECTIVES

To assess safety and tolerability of square biphasic DBS in dystonia patients.

METHODS

This study included primary generalized or cervical dystonia patients with bilateral GPi DBS. Square biphasic pulses were implemented and patients were assessed at baseline, immediately postwashout, post-30-minute washout, 1 hour post- and 2 hours postinitiation of investigational settings.

RESULTS

Ten participants completed the study. There were no patient-reported or clinician-observed side effects. There was improvement across time on the Toronto Western Spasmodic Torticollis Rating Scale (χ2  = 10.7; P = 0.031). Similar improvement was detected in objective gait measurements.

CONCLUSIONS

Square biphasic stimulation appears safe and feasible in dystonia patients with GPi DBS. Further studies are needed to evaluate possible effectiveness particularly in cervical and gait features. © 2016 International Parkinson and Movement Disorder Society.