Fully implanted adaptive deep brain stimulation in freely moving essential tremor patients

Brain-machine interactive neuromodulation research tool with edge AI computing

Closed-loop neuromodulation with intelligence methods has shown great potentials in providing novel neuro-technology for treating neurological and psychiatric diseases. Development of brain-machine interactive neuromodulation strategies could lead to breakthroughs in precision and personalized electronic medicine. The neuromodulation research tool integrating artificial intelligent computing and performing neural sensing and stimulation in real-time could accelerate the development of closed-loop neuromodulation strategies and translational research into clinical application. In this study, we developed a brain-machine interactive neuromodulation research tool (BMINT), which has capabilities of neurophysiological signals sensing, computing with mainstream machine learning algorithms and delivering electrical stimulation pulse by pulse in real-time. The BMINT research tool achieved system time delay under 3 ms, and computing capabilities in feasible computation cost, efficient deployment of machine learning algorithms and acceleration process. Intelligent computing framework embedded in the BMINT enable real-time closed-loop neuromodulation developed with mainstream AI ecosystem resources. The BMINT could provide timely contribution to accelerate the translational research of intelligent neuromodulation by integrating neural sensing, edge AI computing and stimulation with AI ecosystems.

Objective clinical registration of tremor, bradykinesia, and rigidity during awake stereotactic neurosurgery: a scoping review

Tremor, bradykinesia, and rigidity are incapacitating motor symptoms that can be suppressed with stereotactic neurosurgical treatment like deep brain stimulation (DBS) and ablative surgery (e.g., thalamotomy, pallidotomy). Traditionally, clinicians rely on clinical rating scales for intraoperative evaluation of these motor symptoms during awake stereotactic neurosurgery. However, these clinical scales have a relatively high inter-rater variability and rely on experienced raters. Therefore, objective registration (e.g., using movement sensors) is a reasonable extension for intraoperative assessment of tremor, bradykinesia, and rigidity. The main goal of this scoping review is to provide an overview of electronic motor measurements during awake stereotactic neurosurgery. The protocol was based on the PRISMA extension for scoping reviews. After a systematic database search (PubMed, Embase, and Web of Science), articles were screened for relevance. Hundred-and-three articles were subject to detailed screening. Key clinical and technical information was extracted. The inclusion criteria encompassed use of electronic motor measurements during stereotactic neurosurgery performed under local anesthesia. Twenty-three articles were included. These studies had various objectives, including correlating sensor-based outcome measures to clinical scores, identifying optimal DBS electrode positions, and translating clinical assessments to objective assessments. The studies were highly heterogeneous in device choice, sensor location, measurement protocol, design, outcome measures, and data analysis. This review shows that intraoperative quantification of motor symptoms is still limited by variable signal analysis techniques and lacking standardized measurement protocols. However, electronic motor measurements can complement visual evaluations and provide objective confirmation of correct placement of the DBS electrode and/or lesioning. On the long term, this might benefit patient outcomes and provide reliable outcome measures in scientific research.

Usefulness of thalamic beta activity for closed-loop therapy in essential tremor

A partial loss of effectiveness of deep brain stimulation of the ventral intermediate nucleus of the thalamus (VIM) has been reported in some patients with essential tremor (ET), possibly due to habituation to permanent stimulation. This study focused on the evolution of VIM local-field potentials (LFPs) data over time to assess the long-term feasibility of closed-loop therapy based on thalamic activity. We performed recordings of thalamic LFPs in 10 patients with severe ET using the ACTIVA™ PC + S (Medtronic plc.) allowing both recordings and stimulation in the same region. Particular attention was paid to describing the evolution of LFPs over time from 3 to 24 months after surgery when the stimulation was Off. We demonstrated a significant decrease in high-beta LFPs amplitude during movements inducing tremor in comparison to the rest condition 3 months after surgery (1.91 ± 0.89 at rest vs. 1.27 ± 1.37 µV2/Hz during posture/action for N = 8/10 patients; p = 0.010), 12 months after surgery (2.92 ± 1.75 at rest vs. 2.12 ± 1.78 µV2/Hz during posture/action for N = 7/10 patients; p = 0.014) and 24 months after surgery (2.32 ± 0.35 at rest vs 0.75 ± 0.78 µV2/Hz during posture/action for 4/6 patients; p = 0.017). Among the patients who exhibited a significant decrease of high-beta LFP amplitude when stimulation was Off, this phenomenon was observed at least twice during the follow-up. Although the extent of this decrease in high-beta LFPs amplitude during movements inducing tremor may vary over time, this thalamic biomarker of movement could potentially be usable for closed-loop therapy in the long term.

Cerebellar Transcranial Alternating Current Stimulation in Essential Tremor Patients with Thalamic Stimulation: A Proof-of-Concept Study

Essential tremor (ET) is a disabling condition resulting from a dysfunction of cerebello-thalamo-cortical circuitry. Deep brain stimulation (DBS) or lesion of the ventral-intermediate thalamic nucleus (VIM) is an effective treatment for severe ET. Transcranial cerebellar brain stimulation has recently emerged as a non-invasive potential therapeutic option. Here, we aim to investigate the effects of high-frequency non-invasive cerebellar transcranial alternating current stimulation (tACS) in severe ET patients already operated for VIM-DBS. Eleven ET patients with VIM-DBS, and 10 ET patients without VIM-DBS and matched for tremor severity, were included in this double-blind proof-of-concept controlled study. All patients received unilateral cerebellar sham-tACS and active-tACS for 10 min. Tremor severity was blindly assessed at baseline, without VIM-DBS, during sham-tACS, during and at 0, 20, 40 min after active-tACS, using kinetic recordings during holding posture and action ('nose-to-target') task and videorecorded Fahn-Tolosa-Marin (FTM) clinical scales. In the VIM-DBS group, active-tACS significantly improved both postural and action tremor amplitude and clinical (FTM scales) severity, relative to baseline, whereas sham-tACS did not, with a predominant effect for the ipsilateral arm. Tremor amplitude and clinical severity were also not significantly different between ON VIM-DBS and active-tACS conditions. In the non-VIM-DBS group, we also observed significant improvements in ipsilateral action tremor amplitude, and clinical severity after cerebellar active-tACS, with a trend for improved postural tremor amplitude. In non-VIM-DBS group, sham- active-tACS also decreased clinical scores. These data support the safety and potential efficacy of high-frequency cerebellar-tACS to reduce ET amplitude and severity.

Alternative patterns of deep brain stimulation in neurologic and neuropsychiatric disorders

Deep brain stimulation (DBS) is a widely used clinical therapy that modulates neuronal firing in subcortical structures, eliciting downstream network effects. Its effectiveness is determined by electrode geometry and location as well as adjustable stimulation parameters including pulse width, interstimulus interval, frequency, and amplitude. These parameters are often determined empirically during clinical or intraoperative programming and can be altered to an almost unlimited number of combinations. Conventional high-frequency stimulation uses a continuous high-frequency square-wave pulse (typically 130-160 Hz), but other stimulation patterns may prove efficacious, such as continuous or bursting theta-frequencies, variable frequencies, and coordinated reset stimulation. Here we summarize the current landscape and potential clinical applications for novel stimulation patterns.

Machine learning based brain signal decoding for intelligent adaptive deep brain stimulation

Sensing enabled implantable devices and next-generation neurotechnology allow real-time adjustments of invasive neuromodulation. The identification of symptom and disease-specific biomarkers in invasive brain signal recordings has inspired the idea of demand dependent adaptive deep brain stimulation (aDBS). Expanding the clinical utility of aDBS with machine learning may hold the potential for the next breakthrough in the therapeutic success of clinical brain computer interfaces. To this end, sophisticated machine learning algorithms optimized for decoding of brain states from neural time-series must be developed. To support this venture, this review summarizes the current state of machine learning studies for invasive neurophysiology. After a brief introduction to the machine learning terminology, the transformation of brain recordings into meaningful features for decoding of symptoms and behavior is described. Commonly used machine learning models are explained and analyzed from the perspective of utility for aDBS. This is followed by a critical review on good practices for training and testing to ensure conceptual and practical generalizability for real-time adaptation in clinical settings. Finally, first studies combining machine learning with aDBS are highlighted. This review takes a glimpse into the promising future of intelligent adaptive DBS (iDBS) and concludes by identifying four key ingredients on the road for successful clinical adoption: i) multidisciplinary research teams, ii) publicly available datasets, iii) open-source algorithmic solutions and iv) strong world-wide research collaborations.

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.

Soft Devices for High-Resolution Neuro-Stimulation: The Interplay Between Low-Rigidity and Resolution

The field of neurostimulation has evolved over the last few decades from a crude, low-resolution approach to a highly sophisticated methodology entailing the use of state-of-the-art technologies. Neurostimulation has been tested for a growing number of neurological applications, demonstrating great promise and attracting growing attention in both academia and industry. Despite tremendous progress, long-term stability of the implants, their large dimensions, their rigidity and the methods of their introduction and anchoring to sensitive neural tissue remain challenging. The purpose of this review is to provide a concise introduction to the field of high-resolution neurostimulation from a technological perspective and to focus on opportunities stemming from developments in materials sciences and engineering to reduce device rigidity while optimizing electrode small dimensions. We discuss how these factors may contribute to smaller, lighter, softer and higher electrode density devices.

Closing the Loop With Cortical Sensing: The Development of Adaptive Deep Brain Stimulation for Essential Tremor Using the Activa PC+S

Deep Brain Stimulation (DBS) is an important tool in the treatment of pharmacologically resistant neurological movement disorders such as essential tremor (ET) and Parkinson's disease (PD). However, the open-loop design of current systems may be holding back the true potential of invasive neuromodulation. In the last decade we have seen an explosion of activity in the use of feedback to "close the loop" on neuromodulation in the form of adaptive DBS (aDBS) systems that can respond to the patient's therapeutic needs. In this paper we summarize the accomplishments of a 5-year study at the University of Washington in the use of neural feedback from an electrocorticography strip placed over the sensorimotor cortex. We document our progress from an initial proof of hardware all the way to a fully implanted adaptive stimulation system that leverages machine-learning approaches to simplify the programming process. In certain cases, our systems out-performed current open-loop approaches in both power consumption and symptom suppression. Throughout this effort, we collaborated with neuroethicists to capture patient experiences and take them into account whilst developing ethical aDBS approaches. Based on our results we identify several key areas for future work. "Graded" aDBS will allow the system to smoothly tune the stimulation level to symptom severity, and frequent automatic calibration of the algorithm will allow aDBS to adapt to the time-varying dynamics of the disease without additional input from a clinician. Additionally, robust computational models of the pathophysiology of ET will allow stimulation to be optimized to the nuances of an individual patient's symptoms. We also outline the unique advantages of using cortical electrodes for control and the remaining hardware limitations that need to be overcome to facilitate further development in this field. Over the course of this study we have verified the potential of fully-implanted, cortically driven aDBS as a feasibly translatable treatment for pharmacologically resistant ET.

Robustness of Beta Desynchronization from Chronically Implanted Cortical Electrodes on Multiple Time Scales

Adaptive deep brain stimulation (aDBS) promises a significant improvement in patient outcomes, compared to existing deep brain stimulation devices. Fully implanted systems represent the next step to the clinical adoption of aDBS. We take advantage of a unique longitudinal data set formed as part of an effort to investigate aDBS for essential tremor to verify the long term reliability of electrocorticography strips over the motor cortex as a source of bio-markers for control of adaptive stimulation. We show that beta band event related de-synchronization, a promising bio-marker for movement, is robust even when used to trigger aDBS. Over the course of several months we show a minor increase in beta band event related de-synchronization in patients with active deep brain stimulation confirming that it could be used in chronically implanted systems.Clinical relevance - We show the promise and practicality of cortical electrocorticography strips for use in fully implanted, clinically translatable, aDBS systems.

Wearable sensor-driven responsive deep brain stimulation for essential tremor

BACKGROUND

Deep brain stimulation (DBS) is an effective surgical therapy for individuals with essential tremor (ET). However, DBS operates continuously, resulting in adverse effects such as postural instability or dysarthria. Continuous DBS (cDBS) also presents important practical issues including limited battery life of the implantable neurostimulator (INS). Collectively, these shortcomings impact optimal therapeutic benefit in ET.

OBJECTIVE

The goal of the study was to establish a physiology-driven responsive DBS (rDBS) system to provide targeted and personalized therapy based on electromyography (EMG) signals.

METHODS

Ten participants with ET underwent rDBS using Nexus-D, a Medtronic telemetry wand that acts as a direct conduit to the INS by modulating stimulation voltage. Two different rDBS paradigms were tested: one driven by one EMG (single-sensor) and another driven by two or more EMGs (multi-sensor). The feature(s) used in the rDBS algorithms was the pow2er in the participant's tremor frequency band derived from the sensors controlling stimulation. Both algorithms were trained on kinetic and postural data collected during DBS off and cDBS states.

RESULTS

Using established clinical scales and objective measurements of tremor severity, we confirm that both rDBS paradigms deliver equivalent clinical benefit as cDBS. Moreover, both EMG-driven rDBS paradigms delivered less total electrical energy translating to an increase in the battery life of the INS.

CONCLUSIONS

The results of this study verify that EMG-driven rDBS provides clinically equivalent tremor suppression compared to cDBS, while delivering less total electrical energy. Controlling stimulation using a dynamic rDBS paradigm can mitigate limitations of traditional cDBS systems.

Deep Brain Stimulation for Tremor: Update on Long-Term Outcomes, Target Considerations and Future Directions

Deep brain stimulation (DBS) of the thalamic ventral intermediate nucleus is one of the main advanced neurosurgical treatments for drug-resistant tremor. However, not every patient may be eligible for this procedure. Nowadays, various other functional neurosurgical procedures are available. In particular cases, radiofrequency thalamotomy, focused ultrasound and radiosurgery are proven alternatives to DBS. Besides, other DBS targets, such as the posterior subthalamic area (PSA) or the dentato-rubro-thalamic tract (DRT), may be appraised as well. In this review, the clinical characteristics and pathophysiology of tremor syndromes, as well as long-term outcomes of DBS in different targets, will be summarized. The effectiveness and safety of lesioning procedures will be discussed, and an evidence-based clinical treatment approach for patients with drug-resistant tremor will be presented. Lastly, the future directions in the treatment of severe tremor syndromes will be elaborated.