Toward adaptive deep brain stimulation for dystonia

Chronic Pallidal Local Field Potentials Are Associated With Dystonic Symptoms in Children

BACKGROUND

Novel deep brain stimulation devices can record local field potentials (LFPs), which represent the synchronous synaptic activity of neuronal populations. The clinical relevance of LFPs in patients with dystonia remains unclear.

OBJECTIVES

We sought to determine whether chronic LFPs recorded from the globus pallidus internus (GPi) were associated with symptoms of dystonia in children.

MATERIALS AND METHODS

Ten patients with heterogeneous forms of dystonia (genetic and acquired) were implanted with neurostimulators that recorded LFP spectral snapshots. Spectra were compared across parent-reported asymptomatic and symptomatic periods, with daily narrowband data superimposed in 24 one-hour bins.

RESULTS

Spectral power increased during periods of registered dystonic symptoms: mean increase = 102%, CI: (76.7, 132). Circadian rhythms within the LFP narrowband time series correlated with dystonic symptoms: for delta/theta-waves, correlation = 0.33, CI: (0.18, 0.47) and for alpha waves, correlation = 0.27, CI: (0.14, 0.40).

CONCLUSIONS

LFP spectra recorded in the GPi indicate a circadian pattern and are associated with the manifestation of dystonic symptoms.

A localized pallidal physiomarker in Meige syndrome

Objectives

Oscillatory patterns in local field potentials (LFPs) have been recognized as disease-specific physiomarkers, particularly in the context of Parkinson's disease and cervical dystonia. This characteristic oscillatory feature is currently employed in adaptive deep brain stimulation (aDBS). However, for other types of dystonia, especially Meige syndrome, a distinct physiomarker of this nature is yet to be identified.

Methods

Local field potentials were recorded during microelectrode-guided deep brain stimulation surgery from 28 patients with primary Meige syndrome. Before surgery, the severity of patients' motor syndrome were assessed using the Burke-Fahn-Marsden Dystonia Rating Scale-Motor (BFMDRS-M). An instantaneous oscillation detection method was employed to identify true narrowband oscillations. Subsequently, a linear mixed effects model was utilized to examine the relationship between oscillatory activities (including power amplitude and burst duration) and symptom severity.

Results

The focal peaks of "oscillatory activities" detected were predominantly concentrated in the narrow theta band (4-8 Hz), constituting 81.5% of the total detected oscillations in all recording sites near active DBS contacts in the globus pallidus internus (GPi). The linear mixed effects model revealed a positive correlation between the theta burst duration and the severity of preoperative motor impairment, but no correlation with postoperative motor scores. Additionally, there was no significant lateralization effect observed between the left and right GPi.

Conclusion

Our findings suggest that the exaggerated narrowband theta activity (mainly the burst duration) in the GPi is predictive of dystonia symptom severity and may be used as a physiomarker for optimized DBS target during surgery and adaptive DBS for the treatment of Meige syndrome.

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.

Balance between pallidal neural oscillations correlated with dystonic activity and severity

BACKGROUND AND OBJECTIVE

The balance between neural oscillations provides valuable insights into the organisation of neural oscillations related to brain states, which may play important roles in dystonia. We aim to investigate the relationship of the balance in the globus pallidus internus (GPi) with the dystonic severity under different muscular contraction conditions.

METHODS

Twenty-one patients with dystonia were recruited. All of them underwent bilateral GPi implantation, and local field potentials (LFPs) from the GPi were recorded via simultaneous surface electromyography. The power spectral ratio between neural oscillations was computed as the measure of neural balance. This ratio was calculated under high and low dystonic muscular contraction conditions, and its correlation with the dystonic severity was assessed using clinical scores.

RESULTS

The power spectral of the pallidal LFPs peaked in the theta and alpha bands. Within participant comparison showed that the power spectral of the theta oscillations significantly increased during high muscle contraction compared with that during low contraction. The power spectral ratios between the theta and alpha, theta and low beta, and theta and high gamma oscillations were significantly higher during high contraction than during low contraction. The total score and motor score were associated with the power spectral ratio between the low and high beta oscillations, which was correlated with the dystonic severity both during high and low contractions. The power spectral ratios between the low beta and low gamma and between the low beta and high gamma oscillations showed a significantly positive correlation with the total score during both high and low contractions; a correlation with the motor scale score was found only during high contraction. Meanwhile, the power spectral ratio between the theta and alpha oscillations during low contraction showed a significantly negative correlation with the total score. The power spectral ratios between the alpha and high beta, alpha and low gamma, and alpha and high gamma oscillations were significantly correlated with the dystonic severity only during low contraction.

CONCLUSION

The balance between neural oscillations, as quantified by the power ratio between specific frequency bands, differed between the high and low muscular contraction conditions and was correlated with the dystonic severity. The balance between the low and high beta oscillations was correlated with the dystonic severity during both conditions, making this parameter a new possible biomarker for closed-loop deep brain stimulation in patients with dystonia.

Physiology of dystonia: Human studies

In this chapter, we discuss neurophysiological techniques that have been used in the study of dystonia. We examine traditional disease models such as inhibition and excessive plasticity and review the evidence that these play a causal role in pathophysiology. We then review the evidence for sensory and peripheral influences within pathophysiology and look at an emergent literature that tries to probe how oscillatory brain activity may be linked to dystonia pathophysiology.

Adaptive Deep Brain Stimulation: From Experimental Evidence Toward Practical Implementation

Closed-loop adaptive deep brain stimulation (aDBS) can deliver individualized therapy at an unprecedented temporal precision for neurological disorders. This has the potential to lead to a breakthrough in neurotechnology, but the translation to clinical practice remains a significant challenge. Via bidirectional implantable brain-computer-interfaces that have become commercially available, aDBS can now sense and selectively modulate pathophysiological brain circuit activity. Pilot studies investigating different aDBS control strategies showed promising results, but the short experimental study designs have not yet supported individualized analyses of patient-specific factors in biomarker and therapeutic response dynamics. Notwithstanding the clear theoretical advantages of a patient-tailored approach, these new stimulation possibilities open a vast and mostly unexplored parameter space, leading to practical hurdles in the implementation and development of clinical trials. Therefore, a thorough understanding of the neurophysiological and neurotechnological aspects related to aDBS is crucial to develop evidence-based treatment regimens for clinical practice. Therapeutic success of aDBS will depend on the integrated development of strategies for feedback signal identification, artifact mitigation, signal processing, and control policy adjustment, for precise stimulation delivery tailored to individual patients. The present review introduces the reader to the neurophysiological foundation of aDBS for Parkinson's disease (PD) and other network disorders, explains currently available aDBS control policies, and highlights practical pitfalls and difficulties to be addressed in the upcoming years. Finally, it highlights the importance of interdisciplinary clinical neurotechnological research within and across DBS centers, toward an individualized patient-centered approach to invasive brain stimulation. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Pallidal Beta Activity Is Linked to Stimulation-Induced Slowness in Dystonia

BACKGROUND

Pallidal deep brain stimulation (DBS) effectively alleviates symptoms in dystonia patients, but may induce movement slowness as a side-effect. In Parkinson's disease, hypokinetic symptoms have been associated with increased beta oscillations (13-30 Hz). We hypothesize that this pattern is symptom-specific, thus accompanying DBS-induced slowness in dystonia.

METHODS

In 6 dystonia patients, pallidal rest recordings with a sensing-enabled DBS device were performed and tapping speed was assessed using marker-less pose estimation over 5 time points following cessation of DBS.

RESULTS

After cessation of pallidal stimulation, movement speed increased over time (P < 0.01). A linear mixed-effects model revealed that pallidal beta activity explained 77% of the variance in movement speed across patients (P = 0.01).

CONCLUSIONS

The association between beta oscillations and slowness across disease entities provides further evidence for symptom-specific oscillatory patterns in the motor circuit. Our findings might help DBS therapy improvements, as DBS-devices able to adapt to beta oscillations are already commercially available. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Subthalamic beta bursts correlate with dopamine-dependent motor symptoms in 106 Parkinson's patients

Pathologically increased beta power has been described as a biomarker for Parkinson's disease (PD) and related to prolonged bursts of subthalamic beta synchronization. Here, we investigate the association between subthalamic beta dynamics and motor impairment in a cohort of 106 Parkinson's patients in the ON- and OFF-medication state, using two different methods of beta burst determination. We report a frequency-specific correlation of low beta power and burst duration with motor impairment OFF dopaminergic medication. Furthermore, reduction of power and burst duration correlated significantly with symptom alleviation through dopaminergic medication. Importantly, qualitatively similar results were yielded with two different methods of beta burst definition. Our findings validate the robustness of previous results on pathological changes in subcortical oscillations both in the frequency- as well as in the time-domain in the largest cohort of PD patients to date with important implications for next-generation adaptive deep brain stimulation control algorithms.

Elective and Emergency Deep Brain Stimulation in Refractory Pediatric Monogenetic Movement Disorders Presenting with Dystonia: Current Practice Illustrated by Two Cases

BACKGROUND

Dystonia is characterized by sustained or intermittent muscle contractions, leading to abnormal posturing and twisting movements. In pediatric patients, dystonia often negatively influences quality of life. Pharmacological treatment for dystonia is often inadequate and causes adverse effects. Deep brain stimulation (DBS) appears to be a valid therapeutic option for pharmacoresistant dystonia in children.

METHODS

To illustrate the current clinical practice, we hereby describe two pediatric cases of monogenetic movement disorders presenting with dystonia and treated with DBS. We provide a literature review of similar previously described cases and on different clinical aspects of DBS in pediatric dystonia.

RESULTS

The first patient, a 6-year-old girl with severe dystonia, chorea, and myoclonus due to an ADCY5 gene mutation, received DBS in an elective setting. The second patient, an 8-year-old boy with GNAO1-related dystonia and chorea, underwent emergency DBS due to a pharmacoresistant status dystonicus. A significant amelioration of motor symptoms (65% on the Burke-Fahn-Marsden Dystonia Rating Scale) was observed postoperatively in the first patient and her personal therapeutic goals were achieved. DBS was previously reported in five patients with ADCY5-related movement disorders, of which three showed objective improvement. Emergency DBS in our second patient resulted in the successful termination of his GNAO1-related status dystonicus, this being the eighth case reported in the literature.

CONCLUSION

DBS can be effective in monogenetic pediatric dystonia and should be considered early in the disease course. To better evaluate the effects of DBS on patients' functioning, patient-centered therapeutic goals should be discussed in a multidisciplinary approach.

Markerless Radio Frequency Indoor Monitoring for Telemedicine: Gait Analysis, Indoor Positioning, Fall Detection, Tremor Analysis, Vital Signs and Sleep Monitoring

Quantitative indoor monitoring, in a low-invasive and accurate way, is still an unmet need in clinical practice. Indoor environments are more challenging than outdoor environments, and are where patients experience difficulty in performing activities of daily living (ADLs). In line with the recent trends of telemedicine, there is an ongoing positive impulse in moving medical assistance and management from hospitals to home settings. Different technologies have been proposed for indoor monitoring over the past decades, with different degrees of invasiveness, complexity, and capabilities in full-body monitoring. The major classes of devices proposed are inertial-based sensors (IMU), vision-based devices, and geomagnetic and radiofrequency (RF) based sensors. In recent years, among all available technologies, there has been an increasing interest in using RF-based technology because it can provide a more accurate and reliable method of tracking patients' movements compared to other methods, such as camera-based systems or wearable sensors. Indeed, RF technology compared to the other two techniques has higher compliance, low energy consumption, does not need to be worn, is less susceptible to noise, is not affected by lighting or other physical obstacles, has a high temporal resolution without a limited angle of view, and fewer privacy issues. The aim of the present narrative review was to describe the potential applications of RF-based indoor monitoring techniques and highlight their differences compared to other monitoring technologies.

Dystonia Diagnosis: Clinical Neurophysiology and Genetics

Dystonia diagnosis is based on clinical examination performed by a neurologist with expertise in movement disorders. Clues that indicate the diagnosis of a movement disorder such as dystonia are dystonic movements, dystonic postures, and three additional physical signs (mirror dystonia, overflow dystonia, and geste antagonists/sensory tricks). Despite advances in research, there is no diagnostic test with a high level of accuracy for the dystonia diagnosis. Clinical neurophysiology and genetics might support the clinician in the diagnostic process. Neurophysiology played a role in untangling dystonia pathophysiology, demonstrating characteristic reduction in inhibition of central motor circuits and alterations in the somatosensory system. The neurophysiologic measure with the greatest evidence in identifying patients affected by dystonia is the somatosensory temporal discrimination threshold (STDT). Other parameters need further confirmations and more solid evidence to be considered as support for the dystonia diagnosis. Genetic testing should be guided by characteristics such as age at onset, body distribution, associated features, and coexistence of other movement disorders (parkinsonism, myoclonus, and other hyperkinesia). The aim of the present review is to summarize the state of the art regarding dystonia diagnosis focusing on the role of neurophysiology and genetic testing.

Diving into the Subcortex: The Potential of Chronic Subcortical Sensing for Unravelling Basal Ganglia Function and Optimization of Deep Brain STIMULATION

Subcortical structures are a relative neurophysiological 'terra incognita' owing to their location within the skull. While perioperative subcortical sensing has been performed for more than 20 years, the neurophysiology of the basal ganglia in the home setting has remained almost unexplored. However, with the recent advent of implantable pulse generators (IPG) that are able to record neural activity, the opportunity to chronically record local field potentials (LFPs) directly from electrodes implanted for deep brain stimulation opens up. This allows for a breakthrough of chronic subcortical sensing into fundamental research and clinical practice. In this review an extensive overview of the current state of subcortical sensing is provided. The widespread potential of chronic subcortical sensing for investigational and clinical use is discussed. Finally, status and future perspectives of the most promising application of chronic subcortical sensing -i.e., adaptive deep brain stimulation (aDBS)- are discussed in the context of movement disorders. The development of aDBS based on both chronic subcortical and cortical sensing has the potential to dramatically change clinical practice and the life of patients with movement disorders. However, several barriers still stand in the way of clinical implementation. Advancements regarding IPG and lead technology, physiomarkers, and aDBS algorithms as well as harnessing artificial intelligence, multimodality and sensing in the naturalistic setting are needed to bring aDBS to clinical practice.

Concurrent stimulation and sensing in bi-directional brain interfaces: a multi-site translational experience

OBJECTIVE

To provide a design analysis and guidance framework for the implementation of concurrent stimulation and sensing during adaptive deep brain stimulation (aDBS) with particular emphasis on artifact mitigations.

APPROACH

We defined a general architecture of feedback-enabled devices, identified key components in the signal chain which might result in unwanted artifacts and proposed methods that might ultimately enable improved aDBS therapies. We gathered data from research subjects chronically-implanted with an investigational aDBS system, Summit RC+S, to characterize and explore artifact mitigations arising from concurrent stimulation and sensing. We then used a prototype investigational implantable device, DyNeuMo, and a bench-setup that accounts for tissue-electrode properties, to confirm our observations and verify mitigations. The strategies to reduce transient stimulation artifacts and improve performance during aDBS were confirmed in a chronic implant using updated configuration settings.

MAIN RESULTS

We derived and validated a "checklist" of configuration settings to improve system performance and areas for future device improvement. Key considerations for the configuration include 1) active instead of passive recharge, 2) sense-channel blanking in the amplifier, 3) high-pass filter settings, 4) tissue-electrode impedance mismatch management, 5) time-frequency trade-offs in the classifier, 6) algorithm blanking and transition rate limits. Without proper channel configuration, the aDBS algorithm was susceptible to limit-cycles of oscillating stimulation independent of physiological state. By applying the checklist, we could optimize each block's performance characteristics within the overall system. With system-level optimization, a 'fast' aDBS prototype algorithm was demonstrated to be feasible without reentrant loops, and with noise performance suitable for subcortical brain circuits.

SIGNIFICANCE

We present a framework to study sources and propose mitigations of artifacts in devices that provide chronic aDBS. This work highlights the trade-offs in performance as novel sensing devices translate to the clinic. Finding the appropriate balance of constraints is imperative for successful translation of aDBS therapies.

Classification of Dystonia

Dystonia is a hyperkinetic movement disorder characterized by abnormal movement or posture caused by excessive muscle contraction. Because of its wide clinical spectrum, dystonia is often underdiagnosed or misdiagnosed. In clinical practice, dystonia could often present in association with other movement disorders. An accurate physical examination is essential to describe the correct phenomenology. To help clinicians reaching the proper diagnosis, several classifications of dystonia have been proposed. The current classification consists of axis I, clinical characteristics, and axis II, etiology. Through the application of this classification system, movement disorder specialists could attempt to correctly characterize dystonia and guide patients to the most effective treatment. The aim of this article is to describe the phenomenological spectrum of dystonia, the last approved dystonia classification, and new emerging knowledge.

Brain oscillatory dysfunctions in dystonia

Dystonia is a hyperkinetic movement disorder associated with loss of inhibition, abnormal plasticity, dysfunctional sensorimotor integration, and brain oscillatory dysfunctions at cortical and subcortical levels of the central nervous system. Hence, dystonia is considered a network disorder that can, in many cases, be efficiently treated by pallidal deep brain stimulation (DBS). Abnormal oscillatory activity has been identified across the motor circuit of patients with dystonia. Increased low frequency (LF) synchronization in the internal pallidum is the most prominent abnormality. LF oscillations have been associated with the severity of dystonic motor symptoms; they are suppressed by DBS and localized to the clinically most effective stimulation site. Although the origin of these pathologic changes in brain activity needs further clarifications, their characterization will help in adjusting DBS parameters for successful clinical outcome.

Should the Globus Pallidus Targeting Be Refined in Dystonia?

BACKGROUND AND STUDY AIMS

 Deep brain stimulation (DBS) of the globus pallidus internus (GPi) is a highly effective therapy for primary generalized and focal dystonias, but therapeutic success is compromised by a nonresponder rate of up to 20%. Variability in electrode placement and in tissue stimulated inside the GPi may explain in part different outcomes among patients. Refinement of the target within the pallidal area could be helpful for surgery planning and clinical outcomes. The objective of this study was to discuss current and potential methodological (somatotopy, neuroimaging, and neurophysiology) aspects that might assist neurosurgical targeting of the GPi, aiming to treat generalized or focal dystonia.

METHODS

 We selected published studies by searching electronic databases and scanning the reference lists for articles that examined the anatomical and electrophysiologic aspects of the GPi in patients with idiopathic/inherited dystonia who underwent functional neurosurgical procedures.

RESULTS

 The sensorimotor sector of the GPi was the best target to treat dystonic symptoms, and was localized at its lateral posteroventral portion. The effective volume of tissue activated (VTA) to treat dystonia had a mean volume of 153 mm³ in the posterior GPi area. Initial tractography studies evaluated the close relation between the electrode localization and pallidothalamic tract to control dystonic symptoms.Regarding the somatotopy, the more ventral, lateral, and posterior areas of the GPi are associated with orofacial and cervical representation. In contrast, the more dorsal, medial, and anterior areas are associated with the lower limbs; between those areas, there is the representation of the upper limb. Excessive pallidal synchronization has a peak at the theta band of 3 to 8 Hz, which might be responsible for generating dystonic symptoms.

CONCLUSIONS

 Somatotopy assessment of posteroventral GPi contributes to target-specific GPi sectors related to segmental body symptoms. Tractography delineates GPi output pathways that might guide electrode implants, and electrophysiology might assist in pointing out areas of excessive theta synchronization. Finally, the identification of oscillatory electrophysiologic features that correlate with symptoms might enable closed-loop approaches in the future.

Embedded adaptive deep brain stimulation for cervical dystonia controlled by motor cortex theta oscillations

Dystonia is a disabling movement disorder characterized by excessive muscle contraction for which the underlying pathophysiology is incompletely understood and treatment interventions limited in efficacy. Here we utilize a novel, sensing-enabled, deep brain stimulator device, implanted in a patient with cervical dystonia, to record local field potentials from chronically implanted electrodes in the sensorimotor cortex and subthalamic nuclei bilaterally. This rechargeable device was able to record large volumes of neural data at home, in the naturalistic environment, during unconstrained activity. We confirmed the presence of theta (3-7 Hz) oscillatory activity, which was coherent throughout the cortico-subthalamic circuit and specifically suppressed by high-frequency stimulation. Stimulation also reduced the duration, rate and height of theta bursts. These findings motivated a proof-of-principle trial of a new form of adaptive deep brain stimulation - triggered by theta-burst activity recorded from the motor cortex. This facilitated increased peak stimulation amplitudes without induction of dyskinesias and demonstrated improved blinded clinical ratings compared to continuous DBS, despite reduced total electrical energy delivered. These results further strengthen the pathophysiological role of low frequency (theta) oscillations in dystonia and demonstrate the potential for novel adaptive stimulation strategies linked to cortico-basal theta bursts.

Electrophysiological biomarkers for deep brain stimulation outcomes in movement disorders: state of the art and future challenges

Several neurological diseases are accompanied by rhythmic oscillatory dysfunctions in various frequency ranges and disturbed cross-frequency relationships on regional, interregional, and whole brain levels. Knowledge of these disease-specific oscillopathies is important mainly in the context of deep brain stimulation (DBS) therapy. Electrophysiological biomarkers have been used as input signals for adaptive DBS (aDBS) as well as preoperative outcome predictors. As movement disorders, particularly Parkinson's disease (PD), are among the most frequent DBS indications, the current research of DBS is the most advanced in the movement disorders field. We reviewed the literature published mainly between 2010 and 2020 to identify the most important findings concerning the current evolution of electrophysiological biomarkers in DBS and to address future challenges for prospective research.

Deep Brain Stimulation for Tremor and Dystonia

Deep brain stimulation (DBS) is the most commonly used surgical treatment for drug-refractory movement disorders such as tremor and dystonia. Appropriate patient selection along with target selection is important to ensure optimal outcome without complications. This review summarizes the recent literature regarding the mechanism of action, indications, outcome, and complications of DBS in tremor and dystonia. A comparison with other modalities of surgical interventions is discussed along with a note of the recent advances in technology. Future research needs to be directed to understand the underlying etiopathogenesis of the disease and the way in which DBS modulates the intracranial abnormal networks.

The future of neuromodulation: smart neuromodulation

Introduction: The International Neuromodulation Society defines neuromodulation as the alteration of nerve activity through targeted delivery of a stimulus, such as electrical stimulation or chemical agents, to specific neurological sites in the body.Areas covered: In the near future (<5 years) increasingly complex implantable neuromodulation systems will enter the market. These devices are capable of closed-loop stimulation and the delivery of novel stimulation designs, pushing the need for upgradability. But what about the near-to-far future, meaning 5-10 years from now?Expert opinion: We propose that neuromodulation in the near to far future (5-10 years) will involve integration of adaptive network neuromodulation with predictive artificial intelligence, automatically adjusted by brain and external sensors, and controlled via cloud-based applications. The components will be introduced in a phased approach, culminating in a fully autonomous brain-stimulator-cloud interface. This may, in the long future (>10 years), lead to the brain of the future, a brain with integrated artificial intelligence.

Device profile of the percept PC deep brain stimulation system for the treatment of Parkinson's disease and related disorders

INTRODUCTION

Several software and hardware advances in the field of deep brain stimulation (DBS) have been realized in recent years and devices from three manufacturers are available. The Percept™ PC platform (Medtronic, Inc.) enables brain sensing, the latest innovation. Clinicians should be familiar with the differences in devices, and with the latest technologies to deliver optimized patient care.Areas covered: In this device profile, the sensing capabilities of the Percept™ PC platform are described, and the system capabilities are differentiated from other available platforms. The development of the preceding Activa™ PC+S research platform, an investigational device to simultaneously sense brain signals and provide therapeutic stimulation, is provided to place Percept™ PC in the appropriate context.Expert opinion: Percept™ PC offers unique sensing and diary functions as a means to refine therapeutic stimulation, track symptoms and correlate them to neurophysiologic characteristics. Additional features enhance the patient experience with DBS, including 3 T magnetic resonance imaging compatibility, wireless telemetry, a smaller and thinner battery profile, and increased battery longevity. Future work will be needed to illustrate the clinical utility and added value of using sensing to optimize DBS therapy. Patients implanted with Percept™ PC will have ready access to future technology developments.

Neurobiological mechanisms associated with antipsychotic drug-induced dystonia

Dystonia is by far the most intrusive and invalidating extrapyramidal side effect of potent classical antipsychotic drugs. Antipsychotic drug-induced dystonia is classified in both acute and tardive forms. The incidence of drug-induced dystonia is associated with the affinity to inhibitory dopamine D2 receptors. Particularly acute dystonia can be treated with anticholinergic drugs, but the tardive form may also respond to such antimuscarinic treatment, which contrasts their effects in tardive dyskinesia. Combining knowledge of the pathophysiology of primary focal dystonia with the anatomical and pharmacological organization of the extrapyramidal system may shed some light on the mechanism of antipsychotic drug-induced dystonia. A suitable hypothesis is derived from the understanding that focal dystonia may be due to a faulty processing of somatosensory input, so leading to inappropriate execution of well-trained motor programmes. Neuroplastic alterations of the sensitivity of extrapyramidal medium-sized spiny projection neurons to stimulation, which are induced by the training of specific complex movements, lead to the sophisticated execution of these motor plans. The sudden and non-selective disinhibition of indirect pathway medium-sized spiny projection neurons by blocking dopamine D2 receptors may distort this process. Shutting down the widespread influence of tonically active giant cholinergic interneurons on all medium-sized spiny projection neurons by blocking muscarinic receptors may result in a reduction of the influence of extrapyramidal cortical-striatal-thalamic-cortical regulation. Furthermore, striatal cholinergic interneurons have an important role to play in integrating cerebellar input with the output of cerebral cortex, and are also targeted by dopaminergic nigrostriatal fibres affecting dopamine D2 receptors.

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.

Deep brain stimulation by optimized stimulators in a phenotypic model of dystonia: Effects of different frequencies

Deep brain stimulation (DBS) of the globus pallidus internus (GPi, entopeduncular nucleus, EPN, in rodents) has become important for the treatment of generalized dystonia, a severe and often intractable movement disorder. It is unclear if lower frequencies of GPi-DBS or stimulations of the subthalamic nucleus (STN) are of advantage. In the present study, the main objective was to examined the effects of bilateral EPN-DBS at different frequencies (130 Hz, 40 Hz, 15 Hz) on the severity of dystonia in the dt^sz mutant hamster. In addition, STN stimulations were done at a frequency, proven to be effective by the present EPN-DBS in dystonic hamsters. In order to obtain precise bilateral electrical stimuli with magnitude of 50 μA, a pulse width of 60 μs and defined frequencies, it was necessary to develop a new optimized stimulator prior to the experiments. Since the individual highest severity of dystonic episodes is known to be reached within three hours after induction in dt^sz hamsters, the duration of DBS was 180 min. During DBS with 130 Hz the severity of dystonia was significantly lower within the third hour than without DBS in the same animals (p < 0.05). DBS with 40 Hz tended to exert antidystonic effects after three hours, while 15 Hz stimulations of the EPN and 130 Hz stimulations of the STN failed to show any effects on the severity. DBS of the EPN at 130 Hz was most effective against generalized dystonia in the dt^sz mutant. The response to EPN-DBS confirms that the dt^sz mutant is suitable to further investigate the effects of long-term DBS on severity of dystonia and neuronal network activities, important to give insights into the mechanisms of DBS.

What is the true discharge rate and pattern of the striatal projection neurons in Parkinson's disease and Dystonia?

Dopamine and striatal dysfunctions play a key role in the pathophysiology of Parkinson's disease (PD) and Dystonia, but our understanding of the changes in the discharge rate and pattern of striatal projection neurons (SPNs) remains limited. Here, we recorded and examined multi-unit signals from the striatum of PD and dystonic patients undergoing deep brain stimulation surgeries. Contrary to earlier human findings, we found no drastic changes in the spontaneous discharge of the well-isolated and stationary SPNs of the PD patients compared to the dystonic patients or to the normal levels of striatal activity reported in healthy animals. Moreover, cluster analysis using SPN discharge properties did not characterize two well-separated SPN subpopulations, indicating no SPN subpopulation-specific (D1 or D2 SPNs) discharge alterations in the pathological state. Our results imply that small to moderate changes in spontaneous SPN discharge related to PD and Dystonia are likely amplified by basal ganglia downstream structures.

[Historical view on the pathogenesis and surgical treatment of cervical dystonia]

In the past few decades, approaches to surgical treatment of dystonia passed through paradigmatic shift. Intradural upper cervical anterior rhizotomy was replaced by selective peripheral denervation with lesser spectrum of side-effects. Such techniques as microvascular decompression of accessory nerve or spinal cord stimulation for cervical dystonia were abandoned due to lack of proven efficacy. Introducing globus pallidus interna (GPi) DBS in 1990's to treat all types of dystonia, including cervical dystonia, was a fundamental factor. With the growing body of knowledge on the pathophysiology of dystonia, GPi DBS appears to be the most expedient, effective and safe method with limited indications to peripheral destructive procedures.

The characteristics of pallidal low-frequency and beta bursts could help implementing adaptive brain stimulation in the parkinsonian and dystonic internal globus pallidus

INTRODUCTION

Adaptive deep brain stimulation (aDBS) has been applied in Parkinson's disease (PD), based on the presence of brief high-amplitude beta (13-35 Hz) oscillation bursts in the subthalamic nucleus (STN), which correlate with symptom severity. Analogously, average low-frequency (LF) oscillatory power (4-12 Hz) in the internal globus pallidus (GPi) correlates with dystonic symptoms and might be a suitable physiomarker for aDBS in dystonia. Characterization of pallidal bursts could facilitate the implementation of aDBS in the GPi of PD and dystonia patients.

OBJECTIVE AND METHODS

We aimed to describe the bursting behaviour of LF and beta oscillations in a cohort of five GPi-DBS PD patients and compare their amplitude and length with those of a cohort of seven GPi-DBS dystonia, and six STN-DBS PD patients (n electrodes = 34). Furthermore, we used the information obtained to set up aDBS and test it in the GPi of both a dystonia and a PD patient (n = 2), using either LF (dystonia) or beta oscillations (PD) as feedback signals.

RESULTS

LF and beta oscillations in the dystonic and parkinsonian GPi occur as phasic, short-lived bursts, similarly to the parkinsonian STN. The amplitude profile of such bursts, however, differed significantly. Dystonia showed higher LF burst amplitudes, while PD presented higher beta burst amplitudes. Burst characteristics in the parkinsonian GPi and STN were similar. Furthermore, aDBS applied in the GPi was feasible and well tolerated in both diseases.

CONCLUSION

Pallidal LF and beta burst amplitudes have different characteristics in PD and dystonia. The presence of increased burst amplitudes could be employed as feedback for GPi-aDBS.