Directional Recording of Subthalamic Spectral Power Densities in Parkinson's Disease and the Effect of Steering Deep Brain Stimulation

Local Field Potentials Predict Motor Performance in Deep Brain Stimulation for Parkinson's Disease

BACKGROUND

Deep brain stimulation (DBS) is an effective treatment option for patients with Parkinson's disease (PD). However, clinical programming remains challenging with segmented electrodes.

OBJECTIVE

Using novel sensing-enabled neurostimulators, we investigated local field potentials (LFPs) and their modulation by DBS to assess whether electrophysiological biomarkers may facilitate clinical programming in chronically implanted patients.

METHODS

Sixteen patients (31 hemispheres) with PD implanted with segmented electrodes in the subthalamic nucleus and a sensing-enabled neurostimulator were included in this study. Recordings were conducted 3 months after DBS surgery following overnight withdrawal of dopaminergic medication. LFPs were acquired while stimulation was turned OFF and during a monopolar review of both directional and ring contacts. Directional beta power and stimulation-induced beta power suppression were computed. Motor performance, as assessed by a pronation-supination task, clinical programming and electrode placement were correlated to directional beta power and stimulation-induced beta power suppression.

RESULTS

Better motor performance was associated with stronger beta power suppression at higher stimulation amplitudes. Across directional contacts, differences in directional beta power and the extent of stimulation-induced beta power suppression predicted motor performance. However, within individual hemispheres, beta power suppression was superior to directional beta power in selecting the contact with the best motor performance. Contacts clinically activated for chronic stimulation were associated with stronger beta power suppression than non-activated contacts.

CONCLUSIONS

Our results suggest that stimulation-induced β power suppression is superior to directional β power in selecting the clinically most effective contact. In sum, electrophysiological biomarkers may guide programming of directional DBS systems in PD patients. © 2023 The Authors. 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.

Directional versus ring-mode deep brain stimulation for Parkinson's disease: protocol of a multi-centre double-blind randomised crossover trial

BACKGROUND

The effectiveness of Deep Brain Stimulation (DBS) therapy for Parkinson's disease can be limited by side-effects caused by electrical current spillover into structures adjacent to the target area. The objective of the STEEred versus RING-mode DBS for Parkinson's disease (STEERING) study is to investigate if directional DBS for Parkinson's disease results in a better clinical outcome when compared to ring-mode DBS.

METHODS

The STEERING study is a prospective multi-centre double-blind randomised crossover trial. Inclusion criteria are Parkinson's disease, subthalamic nucleus DBS in a 'classic' ring-mode setting for a minimum of six months, and optimal ring-mode settings have been established. Participants are categorised into one of two subgroups according to their clinical response to the ring-mode settings as 'responders' (i.e., patient with a satisfactory effect of ring-mode DBS) or 'non-responder' (i.e., patient with a non-satisfactory effect of ring-mode DBS). A total of 64 responders and 38 non-responders will be included (total 102 patients). After an optimisation period in which an optimal directional setting is found, participants are randomised to first receive ring-mode DBS for 56 days (range 28-66) followed by directional DBS for 56 days (28-66) or vice-versa. The primary outcome is the difference between ring-mode DBS and directional DBS settings on the Movement Disorders Society Unified Parkinson's Disease Rating Scale - Motor Evaluation (MDS-UPDRS-ME) in the off-medication state. Secondary outcome measures consist of MDS-UPDRS-ME in the on-medication state, MDS-UPDRS Activities of Daily Living, MDS-UPDRS Motor Complications-Dyskinesia, disease related quality of life measured with the Parkinson's Disease Questionnaire 39, stimulation-induced side-effects, antiparkinsonian medication use, and DBS-parameters. Participants' therapy preference is measured at the end of the study. Outcomes will be analysed for both responder and non-responder groups, as well as for both groups pooled together.

DISCUSSION

The STEERING trial will provide insights into whether or not directional DBS should be standardly used in all Parkinson's disease DBS patients or if directional DBS should only be used in a case-based approach.

TRIAL REGISTRATION

This trial was registered on the Netherlands Trial Register, as trial NL6508 ( NTR6696 ) on June 23, 2017.

Low-frequency deep brain stimulation reveals resonant beta-band evoked oscillations in the pallidum of Parkinson's Disease patients

Introduction

Evidence suggests that spontaneous beta band (11-35 Hz) oscillations in the basal ganglia thalamocortical (BGTC) circuit are linked to Parkinson's disease (PD) pathophysiology. Previous studies on neural responses in the motor cortex evoked by electrical stimulation in the subthalamic nucleus have suggested that circuit resonance may underlie the generation of spontaneous and stimulation-evoked beta oscillations in PD. Whether these stimulation-evoked, resonant oscillations are present across PD patients in the internal segment of the globus pallidus (GPi), a primary output nucleus in the BGTC circuit, is yet to be determined.

Methods

We characterized spontaneous and stimulation-evoked local field potentials (LFPs) in the GPi of four PD patients (five hemispheres) using deep brain stimulation (DBS) leads externalized after DBS implantation surgery.

Results

Our analyses show that low-frequency (2-4 Hz) stimulation in the GPi evoked long-latency (>50 ms) beta-band neural responses in the GPi in 4/5 hemispheres. We demonstrated that neural sources generating both stimulation-evoked and spontaneous beta oscillations were correlated in their frequency content and spatial localization.

Discussion

Our results support the hypothesis that the same neuronal population and resonance phenomenon in the BGTC circuit generates both spontaneous and evoked pallidal beta oscillations. These data also support the development of closed-loop control systems that modulate the GPi spontaneous oscillations across PD patients using beta band stimulation-evoked responses.

Spectral Topography of the Subthalamic Nucleus to Inform Next-Generation Deep Brain Stimulation

BACKGROUND

The landscape of neurophysiological symptoms and behavioral biomarkers in basal ganglia signals for movement disorders is expanding. The clinical translation of sensing-based deep brain stimulation (DBS) also requires a thorough understanding of the anatomical organization of spectral biomarkers within the subthalamic nucleus (STN).

OBJECTIVES

The aims were to systematically investigate the spectral topography, including a wide range of sub-bands in STN local field potentials (LFP) of Parkinson's disease (PD) patients, and to evaluate its predictive performance for clinical response to DBS.

METHODS

STN-LFPs were recorded from 70 PD patients (130 hemispheres) awake and at rest using multicontact DBS electrodes. A comprehensive spatial characterization, including hot spot localization and focality estimation, was performed for multiple sub-bands (delta, theta, alpha, low-beta, high-beta, low-gamma, high-gamma, and fast-gamma (FG) as well as low- and fast high-frequency oscillations [HFO]) and compared to the clinical hot spot for rigidity response to DBS. A spectral biomarker map was established and used to predict the clinical response to DBS.

RESULTS

The STN shows a heterogeneous topographic distribution of different spectral biomarkers, with the strongest segregation in the inferior-superior axis. Relative to the superiorly localized beta hot spot, HFOs (FG, slow HFO) were localized up to 2 mm more inferiorly. Beta oscillations are spatially more spread compared to other sub-bands. Both the spatial proximity of contacts to the beta hot spot and the distance to higher-frequency hot spots were predictive for the best rigidity response to DBS.

CONCLUSIONS

The spatial segregation and properties of spectral biomarkers within the DBS target structure can additionally be informative for the implementation of next-generation sensing-based DBS. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Combining Multimodal Biomarkers to Guide Deep Brain Stimulation Programming in Parkinson Disease

BACKGROUND

Deep brain stimulation (DBS) programming of multicontact DBS leads relies on a very time-consuming manual screening procedure, and strategies to speed up this process are needed. Beta activity in subthalamic nucleus (STN) local field potentials (LFP) has been suggested as a promising marker to index optimal stimulation contacts in patients with Parkinson disease.

OBJECTIVE

In this study, we investigate the advantage of algorithmic selection and combination of multiple resting and movement state features from STN LFPs and imaging markers to predict three relevant clinical DBS parameters (clinical efficacy, therapeutic window, side-effect threshold).

MATERIALS AND METHODS

STN LFPs were recorded at rest and during voluntary movements from multicontact DBS leads in 27 hemispheres. Resting- and movement-state features from multiple frequency bands (alpha, low beta, high beta, gamma, fast gamma, high frequency oscillations [HFO]) were used to predict the clinical outcome parameters. Subanalyses included an anatomical stimulation sweet spot as an additional feature.

RESULTS

Both resting- and movement-state features contributed to the prediction, with resting (fast) gamma activity, resting/movement-modulated beta activity, and movement-modulated HFO being most predictive. With the proposed algorithm, the best stimulation contact for the three clinical outcome parameters can be identified with a probability of almost 90% after considering half of the DBS lead contacts, and it outperforms the use of beta activity as single marker. The combination of electrophysiological and imaging markers can further improve the prediction.

CONCLUSION

LFP-guided DBS programming based on algorithmic selection and combination of multiple electrophysiological and imaging markers can be an efficient approach to improve the clinical routine and outcome of DBS patients.

StimFit-A Data-Driven Algorithm for Automated Deep Brain Stimulation Programming

BACKGROUND

Finding the optimal deep brain stimulation (DBS) parameters from a multitude of possible combinations by trial and error is time consuming and requires highly trained medical personnel.

OBJECTIVE

We developed an automated algorithm to identify optimal stimulation settings in Parkinson's disease (PD) patients treated with subthalamic nucleus (STN) DBS based on imaging-derived metrics.

METHODS

Electrode locations and monopolar review data of 612 stimulation settings acquired from 31 PD patients were used to train a predictive model for therapeutic and adverse stimulation effects. Model performance was then evaluated within the training cohort using cross-validation and on an independent cohort of 19 patients. We inverted the model by applying a brute-force approach to determine the optimal stimulation sites in the target region. Finally, an optimization algorithm was established to identify optimal stimulation parameters. Suggested stimulation parameters were compared to the ones applied in clinical practice.

RESULTS

Predicted motor outcome correlated with observed outcome (R = 0.57, P < 10^-10 ) across patients within the training cohort. In the test cohort, the model explained 28% of the variance in motor outcome differences between settings. The stimulation site for maximum motor improvement was located at the dorsolateral border of the STN. When compared to two empirical settings, model-based suggestions more closely matched the setting with superior motor improvement.

CONCLUSION

We developed and validated a data-driven model that can suggest stimulation parameters leading to optimal motor improvement while minimizing the risk of stimulation-induced side effects. This approach might provide guidance for DBS programming in the future. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Surgical Strategy for Directional Deep Brain Stimulation

Deep brain stimulation (DBS) is a well-established treatment for drug-resistant involuntary movements. However, the conventional quadripole cylindrical lead creates electrical fields in all directions, and the resulting spread to adjacent eloquent structures may induce unintended effects. Novel directional leads have therefore been designed to allow directional stimulation (DS). Directional leads have the advantage of widening the therapeutic window (TW), compensating for slight misplacement of the lead and requiring less electrical power to provide the same effect as a cylindrical lead. Conversely, the increase in the number of contacts from four to eight and the addition of directional elements has made stimulation programming more complex. For these reasons, new treatment strategies are required to allow effective directional DBS. During lead implantation, the directional segment should be placed in a "sweet spot," and the orientation of the directional segment is important for programming. Trial-and-error testing of a large number of contacts is unnecessary, and efficient and systematic execution of the programmed procedure is desirable. Recent improvements in imaging technologies have enabled image-guided programming. In the future, optimal stimulations are expected to be programmed by directional recording of local field potentials.

Influence of inter-electrode distance on subthalamic nucleus local field potential recordings in Parkinson's disease

OBJECTIVES

To evaluate spectra and their correlations with clinical symptoms of local field potentials (LFP) acquired from wide- and close-spaced contacts (i.e. between contacts 0-3 or LFP03, and contacts 1-2 or LFP12 respectively) on the same DBS electrode within the subthalamus (STN) in Parkinson's disease (PD), before and after levodopa administration.

METHODS

LFP12 and LFP03 were recorded from 20 PD patients. We evaluated oscillatory power, local and switched phase-amplitude coupling (l- and Sw-PAC) and correlation with motor symptoms (UPDRSIII).

RESULTS

Before levodopa, both LFP03 and LFP12 power in the α band inversely correlated with UPDRSIII. Differences between contacts were found in the low-frequency bands power. After levodopa, differences in UPDRSIII were associated to changes in LFP03 low-β and LFP12 HFO (high frequency oscillations, 250-350 Hz) power, while a modulation of the low-β power and an increased β-LFO (low frequency oscillations, 15-45 Hz) PAC was found only for LFP12.

CONCLUSION

This study reveals differences in spectral pattern between LFP12 and LFP03 before and after levodopa administration, as well as different correlations with PD motor symptoms.

SIGNIFICANCE

Differences between LFP12 and LFP03 may offer an opportunity for optimizing adaptive deep brain stimulation (aDBS) protocols for PD. LFP12 can be used to detect β-HFO coupling and β power (i.e. bradykinesia), while LFP03 are optimal for low frequency oscillations (dyskinesias).

Deep brain stimulation programming strategies: segmented leads, independent current sources, and future technology

Introduction: Advances in neuromodulation and deep brain stimulation (DBS) technologies have facilitated opportunities for improved clinical benefit and side effect management. However, new technologies have added complexity to clinic-based DBS programming.Areas covered: In this article, we review basic basal ganglia physiology, proposed mechanisms of action and technical aspects of DBS. We discuss novel DBS technologies for movement disorders including the role of advanced imaging software, lead design, IPG design, novel programming techniques including directional stimulation and coordinated reset neuromodulation. Additional topics include the use of potential biomarkers, such as local field potentials, electrocorticography, and adaptive stimulation. We will also discuss future directions including optogenetically inspired DBS.Expert opinion: The introduction of DBS for the management of movement disorders has expanded treatment options. In parallel with our improved understanding of brain physiology and neuroanatomy, new technologies have emerged to address challenges associated with neuromodulation, including variable effectiveness, side-effects, and programming complexity. Advanced functional neuroanatomy, improved imaging, real-time neurophysiology, improved electrode designs, and novel programming techniques have collectively been driving improvements in DBS outcomes.

Longitudinal analysis of local field potentials recorded from directional deep brain stimulation lead implants in the subthalamic nucleus

Objective.The electrode-tissue interface surrounding a deep brain stimulation (DBS) lead is known to be highly dynamic following implantation, which may have implications on the interpretation of intraoperatively recorded local field potentials (LFPs). We characterized beta-band LFP dynamics following implantation of a directional DBS lead in the sensorimotor subthalamic nucleus (STN), which is a primary target for treating Parkinson's disease.Approach.Directional STN-DBS leads were implanted in four healthy, non-human primates. LFPs were recorded over two weeks and again 1-4 months after implantation. Impedance was measured for two weeks post-implant without stimulation to compare the reactive tissue response to changes in LFP oscillations. Beta-band (12-30 Hz) peak power was calculated from the LFP power spectra using both common average referencing (CAR) and intra-row bipolar referencing (IRBR).Results.Resting-state LFPs in two of four subjects revealed a steady increase of beta power over the initial two weeks post-implant whereas the other two subjects showed variable changes over time. Beta power variance across days was significantly larger in the first two weeks compared to 1-4 months post-implant in all three long-term subjects. Further, spatial maps of beta power several hours after implantation did not correlate with those measured two weeks or 1-4 months post-implant. CAR and IRBR beta power correlated across short- and long-term time points. However, depending on the time period, subjects showed a significant bias towards larger beta power using one referencing scheme over the other. Lastly, electrode-tissue impedance increased over the two weeks post-implant but showed no significant correlation to beta power.Significance.These results suggest that beta power in the STN may undergo significant changes following DBS lead implantation. DBS lead diameter and electrode recording configurations can affect the post-implant interpretation of oscillatory features. Such insights will be important for extrapolating results from intraoperative and externalized LFP recordings.

Local field potentials in Parkinson's disease: A frequency-based review

Deep brain stimulation (DBS) surgery offers a unique opportunity to record local field potentials (LFPs), the electrophysiological population activity of neurons surrounding the depth electrode in the target area. With direct access to the subcortical activity, LFP research has provided valuable insight into disease mechanisms and cognitive processes and inspired the advent of adaptive DBS for Parkinson's disease (PD). A frequency-based framework is usually employed to interpret the implications of LFP signatures in LFP studies on PD. This approach standardizes the methodology, simplifies the interpretation of LFP patterns, and makes the results comparable across studies. Importantly, previous works have found that activity patterns do not represent disease-specific activity but rather symptom-specific or task-specific neuronal signatures that relate to the current motor, cognitive or emotional state of the patient and the underlying disease. In the present review, we aim to highlight distinguishing features of frequency-specific activities, mainly within the motor domain, recorded from DBS electrodes in patients with PD. Associations of the commonly reported frequency bands (delta, theta, alpha, beta, gamma, and high-frequency oscillations) to motor signs are discussed with respect to band-related phenomena such as individual tremor and high/low beta frequency activity, as well as dynamic transients of beta bursts. We provide an overview on how electrophysiology research in DBS patients has revealed and will continuously reveal new information about pathophysiology, symptoms, and behavior, e.g., when combining deep LFP and surface electrocorticography recordings.

Biophysical characterization of local field potential recordings from directional deep brain stimulation electrodes

OBJECTIVE

Two major advances in clinical deep brain stimulation (DBS) technology have been the introduction of local field potential (LFP) recording capabilities, and the deployment of directional DBS electrodes. However, these two technologies are not operationally integrated within current clinical DBS devices. Therefore, we evaluated the theoretical advantages of using directional DBS electrodes for LFP recordings, with a focus on measuring beta-band activity in the subthalamic nucleus (STN).

METHODS

We used a computational model of human STN neural activity to simulate LFP recordings. The model consisted of 235,280 anatomically and electrically detailed STN neurons surrounding the DBS electrode, which was previously optimized to mimic beta-band synchrony in the dorsolateral STN. We then used that model system to compare LFP recordings from cylindrical and directional DBS contacts, and evaluate how the selection of different contacts for bipolar recording affected the LFP measurements.

RESULTS

The model predicted two advantages of directional DBS electrodes over cylindrical DBS electrodes for STN LFP recording. First, recording from directional contacts could provide additional insight on the location of a synchronous volume of neurons within the STN. Second, directional contacts could detect a smaller volume of synchronous neurons than cylindrical contacts, which our simulations predicted to be a ~0.5 mm minimum radius.

CONCLUSIONS

STN LFP recordings from 8-contact directional DBS electrodes (28 possible bipolar pairs) can provide more information than 4-contact cylindrical DBS electrodes (6 possible bipolar pairs), but they also introduce additional complexity in analyzing the signals.

SIGNIFICANCE

Integration of directional electrodes with DBS systems that are capable of LFP recordings could improve localization of targeted volumes of synchronous neurons in PD patients.

Mapping of subthalamic nucleus using microelectrode recordings during deep brain stimulation

Alongside stereotactic magnetic resonance imaging, microelectrode recording (MER) is frequently used during the deep brain stimulation (DBS) surgery for optimal target localization. The aim of this study is to optimize subthalamic nucleus (STN) mapping using MER analytical patterns. 16 patients underwent bilateral STN-DBS. MER was performed simultaneously for 5 microelectrodes in a setting of Ben’s-gun pattern in awake patients. Using spikes and background activity several different parameters and their spectral estimates in various frequency bands including low frequency (2–7 Hz), Alpha (8–12 Hz), Beta (sub-divided as Low_Beta (13–20 Hz) and High_Beta (21–30 Hz)) and Gamma (31 to 49 Hz) were computed. The optimal STN lead placement with the most optimal clinical effect/side-effect ratio accorded to the maximum spike rate in 85% of the implantation. Mean amplitude of background activity in the low beta frequency range was corresponding to right depth in 85% and right location in 94% of the implantation respectively. MER can be used for STN mapping and intraoperative decisions for the implantation of DBS electrode leads with a high accuracy. Spiking and background activity in the beta range are the most promising independent parameters for the delimitation of the proper anatomical site.

Directional Local Field Potentials in the Subthalamic Nucleus During Deep Brain Implantation of Parkinson's Disease Patients

Segmented deep brain stimulation leads feature directional electrodes that allow for a finer spatial control of electrical stimulation compared to traditional ring-shaped electrodes. These segmented leads have demonstrated enlarged therapeutic windows and have thus the potential to improve the treatment of Parkinson's disease patients. Moreover, they provide a unique opportunity to record directional local field potentials. Here, we investigated whether directional local field potentials can help identify the best stimulation direction to assist device programming. Four Parkinson's disease patients underwent routine implantation of the subthalamic nucleus. Firstly, local field potentials were recorded in three directions for two conditions: In one condition, the patient was at rest; in the other condition, the patient's arm was moved. Secondly, current thresholds for therapeutic and side effects were identified intraoperatively for directional stimulation. Therapeutic windows were calculated from these two thresholds. Thirdly, the spectral power of the total beta band (13-35 Hz) and its sub-bands low, high, and peak beta were analyzed post hoc. Fourthly, the spectral power was used by different algorithms to predict the ranking of directions. The spectral power profiles were patient-specific, and spectral peaks were found both in the low beta band (13-20 Hz) and in the high beta band (20.5-35 Hz). The direction with the highest spectral power in the total beta band was most indicative of the 1st best direction when defined by therapeutic window. Based on the total beta band, the resting condition and the moving condition were similarly predictive about the direction ranking and classified 83.3% of directions correctly. However, different algorithms were needed to predict the ranking defined by therapeutic window or therapeutic current threshold. Directional local field potentials may help predict the best stimulation direction. Further studies with larger sample sizes are needed to better distinguish the informative value of different conditions and the beta sub-bands.

Rapid motor fluctuations reveal short-timescale neurophysiological biomarkers of Parkinson's disease

Objective.

Identifying neural activity biomarkers of brain disease is essential to provide objective estimates of disease burden, obtain reliable feedback regarding therapeutic efficacy, and potentially to serve as a source of control for closed-loop neuromodulation. In Parkinson’s disease (PD), microelectrode recordings (MER) are routinely performed in the basal ganglia to guide electrode implantation for deep brain stimulation (DBS). While pathologically-excessive oscillatory activity has been observed and linked to PD motor dysfunction broadly, the extent to which these signals provide quantitative information about disease expression and fluctuations, particularly at short timescales, is unknown. Furthermore, the degree to which informative signal features are similar or different across patients has not been rigorously investigated. We sought to determine the extent to which motor error in PD across patients can be decoded on a rapid timescale using spectral features of neural activity.

Approach.

Here, we recorded neural activity from the subthalamic nucleus (STN) of subjects with PD undergoing awake DBS surgery while they performed an objective, continuous behavioral assessment that synthesized heterogenous PD motor manifestations to generate a scalar measure of motor dysfunction at short timescales. We then leveraged natural motor performance variations as a ‘ground truth’ to identify corresponding neurophysiological biomarkers.

Main results.

Support vector machines using multi-spectral decoding of neural signals from the STN succeeded in tracking the degree of motor impairment at short timescales (as short as one second). Spectral power across a wide range of frequencies, beyond the classic ‘β’ oscillations, contributed to this decoding, and multi-spectral models consistently outperformed those generated using more isolated frequency bands. While generalized decoding models derived across subjects were able to estimate motor impairment, patient-specific models typically performed better.

Significance.

These results demonstrate that quantitative information about short-timescale PD motor dysfunction is available in STN neural activity, distributed across various patient-specific spectral components, such that an individualized approach will be critical to fully harness this information for optimal disease tracking and closed-loop neuromodulation.

Functional Use of Directional Local Field Potentials in the Subthalamic Nucleus Deep Brain Stimulation

Background

Directional deep brain stimulation (DBS) technology aims to address the limitations, such as stimulation-induced side effects, by delivering selective, focal modulation via segmented contacts. However, DBS programming becomes more complex and time-consuming for clinical feasibility. Local field potentials (LFPs) might serve a functional role in guiding clinical programming.

Objective

In this pilot study, we investigated the spectral dynamics of directional LFPs in subthalamic nucleus (STN) and their relationship to motor symptoms of Parkinson’s disease (PD).

Methods

We recorded intraoperative STN-LFPs from 8-contact leads (Infinity-6172, Abbott Laboratories, Illinois, United States) in 8 PD patients at rest. Directional LFPs were referenced to their common average and time-frequency analysis was computed using a modified Welch periodogram method. The beta band (13–35 Hz) features were extracted and their correlation to preoperative UPDRS-III scores were assessed.

Results

Normalized beta power (13–20 Hz) and normalized peak power (13–35 Hz) were found to be higher in anterior direction despite lack of statistical significance (p > 0.05). Results of the Spearman correlation analysis demonstrated positive trends with bradykinesia/rigidity in dorsoanterior direction (r = 0.659, p = 0.087) and with axial scores in the dorsomedial direction (r = 0.812, p = 0.072).

Conclusion

Given that testing all possible combinations of contact pairs and stimulation parameters is not feasible in a single clinic visit, spatio-spectral LFP dynamics obtained from intraoperative recordings might be used as an initial marker to select optimal contact(s).

Soft, Implantable Bioelectronic Interfaces for Translational Research

The convergence of materials science, electronics, and biology, namely bioelectronic interfaces, leads novel and precise communication with biological tissue, particularly with the nervous system. However, the translation of lab-based innovation toward clinical use calls for further advances in materials, manufacturing and characterization paradigms, and design rules. Herein, a translational framework engineered to accelerate the deployment of microfabricated interfaces for translational research is proposed and applied to the soft neurotechnology called electronic dura mater, e-dura. Anatomy, implant function, and surgical procedure guide the system design. A high-yield, silicone-on-silicon wafer process is developed to ensure reproducible characteristics of the electrodes. A biomimetic multimodal platform that replicates surgical insertion in an anatomy-based model applies physiological movement, emulates therapeutic use of the electrodes, and enables advanced validation and rapid optimization in vitro of the implants. Functionality of scaled e-dura is confirmed in nonhuman primates, where epidural neuromodulation of the spinal cord activates selective groups of muscles in the upper limbs with unmet precision. Performance stability is controlled over 6 weeks in vivo. The synergistic steps of design, fabrication, and biomimetic in vitro validation and in vivo evaluation in translational animal models are of general applicability and answer needs in multiple bioelectronic designs and medical technologies.

Toward Electrophysiology-Based Intelligent Adaptive Deep Brain Stimulation for Movement Disorders

Deep brain stimulation (DBS) represents one of the major clinical breakthroughs in the age of translational neuroscience. In 1987, Benabid and colleagues demonstrated that high-frequency stimulation can mimic the effects of ablative neurosurgery in Parkinson's disease (PD), while offering two key advantages to previous procedures: adjustability and reversibility. Deep brain stimulation is now an established therapeutic approach that robustly alleviates symptoms in patients with movement disorders, such as Parkinson's disease, essential tremor, and dystonia, who present with inadequate or adverse responses to medication. Currently, stimulation electrodes are implanted in specific target regions of the basal ganglia-thalamic circuit and stimulation pulses are delivered chronically. To achieve optimal therapeutic effect, stimulation frequency, amplitude, and pulse width must be adjusted on a patient-specific basis by a movement disorders specialist. The finding that pathological neural activity can be sampled directly from the target region using the DBS electrode has inspired a novel DBS paradigm: closed-loop adaptive DBS (aDBS). The goal of this strategy is to identify pathological and physiologically normal patterns of neuronal activity that can be used to adapt stimulation parameters to the concurrent therapeutic demand. This review will give detailed insight into potential biomarkers and discuss next-generation strategies, implementing advances in artificial intelligence, to further elevate the therapeutic potential of DBS by capitalizing on its modifiable nature. Development of intelligent aDBS, with an ability to deliver highly personalized treatment regimens and to create symptom-specific therapeutic strategies in real-time, could allow for significant further improvements in the quality of life for movement disorders patients with DBS that ultimately could outperform traditional drug treatment.

Understanding the Effects and Adverse Reactions of Deep Brain Stimulation: Is It Time for a Paradigm Shift Toward a Focus on Heterogenous Biophysical Tissue Properties Instead of Electrode Design Only?

Deep brain stimulation (DBS) has been proven to be an effective treatment modality for various late-stage neurological and psychiatric disorders. However, knowledge on the electrical field distribution in the brain tissue is still scarce. Most recent attempts to understand electric field spread were primarily focused on the effect of different electrodes on rather simple tissue models. The influence of microanatomic, biophysical tissue properties in particular has not been investigated in depth. Ethical concerns restrict thorough research on field distribution in human in vivo brain tissue. By means of a simplified model, we investigated the electric field distribution in a broader area of the subthalamic nucleus (STN). Pivotal biophysical parameters including conductivity, permittivity and permeability of brain tissue were incorporated in the model. A brain tissue model was created with the finite element method (FEM). Stimulation was mimicked with parameters used for monopolar stimulation of patients suffering from Parkinson's disease. Our results were visualized with omnidirectional and segmented electrodes. The stimulated electric field was visualized with superimpositions on a stereotactic atlas (Morel). Owing to the effects of regional tissue properties near the stimulating electrode, marked field distortions occur. Such effects include, for example, isolating effects of heavily myelinated neighboring structures, e.g., the internal capsule. In particular, this may be illustrated through the analysis of a larger coronal area. While omnidirectional stimulation has been associated with vast current leakage, higher targeting precision was obtained with segmented electrodes. Finally, targeting was improved when the influence of microanatomic structures on the electric spread was considered. Our results confirm that lead design is not the sole influence on current spread. An omnidirectional lead configuration does not automatically result in an omnidirectional spread of current. In turn, segmented electrodes do not automatically imply an improved steering of current. Our findings may provide an explanation for side-effects secondary to current leakage. Furthermore, a possible explanation for divergent results in the comparison of the intraoperative awake patient and the postoperative setting is given. Due to the major influence of biophysical tissue properties on electric field shape, the local microanatomy should be considered for precise surgical targeting and optimal hardware implantation.

Local field potentials of subthalamic nucleus contain electrophysiological footprints of motor subtypes of Parkinson's disease

Although motor subtypes of Parkinson's disease (PD), such as tremor dominant (TD) and postural instability and gait difficulty (PIGD), have been defined based on symptoms since the mid-1990s, no underlying neural correlates of these clinical subtypes have yet been identified. Very limited data exist regarding the electrophysiological abnormalities within the subthalamic nucleus (STN) that likely accompany the symptom severity or the phenotype of PD. Here, we show that activity in subbands of local field potentials (LFPs) recorded with multiple microelectrodes from subterritories of STN provide distinguishing neurophysiological information about the motor subtypes of PD. We studied 24 patients with PD and found distinct patterns between TD (n = 13) and PIGD (n = 11) groups in high-frequency oscillations (HFOs) and their nonlinear interactions with beta band in the superior and inferior regions of the STN. Particularly, in the superior region of STN, the power of the slow HFO (sHFO) (200-260 Hz) and the coupling of its amplitude with beta-band phase were significantly stronger in the TD group. The inferior region of STN exhibited fast HFOs (fHFOs) (260-450 Hz), which have a significantly higher center frequency in the PIGD group. The cross-frequency coupling between fHFOs and beta band in the inferior region of STN was significantly stronger in the PIGD group. Our results indicate that the spatiospectral dynamics of STN-LFPs can be used as an objective method to distinguish these two motor subtypes of PD. These observations might lead to the development of sensing and stimulation strategies targeting the subterritories of STN for the personalization of deep-brain stimulation (DBS).

Biophysical basis of subthalamic local field potentials recorded from deep brain stimulation electrodes

Clinical deep brain stimulation (DBS) technology is evolving to enable chronic recording of local field potentials (LFPs) that represent electrophysiological biomarkers of the underlying disease state. However, little is known about the biophysical basis of LFPs, or how the patient's unique brain anatomy and electrode placement impact the recordings. Therefore, we developed a patient-specific computational framework to analyze LFP recordings within a clinical DBS context. We selected a subject with Parkinson's disease implanted with a Medtronic Activa PC+S DBS system and reconstructed their subthalamic nucleus (STN) and DBS electrode location using medical imaging data. The patient-specific STN volume was populated with 235,280 multicompartment STN neuron models, providing a neuron density consistent with histological measurements. Each neuron received time-varying synaptic inputs and generated transmembrane currents that gave rise to the LFP signal recorded at DBS electrode contacts residing in a finite element volume conductor model. We then used the model to study the role of synchronous beta-band inputs to the STN neurons on the recorded power spectrum. Three bipolar pairs of simultaneous clinical LFP recordings were used in combination with an optimization algorithm to customize the neural activity parameters in the model to the patient. The optimized model predicted a 2.4-mm radius of beta-synchronous neurons located in the dorsolateral STN. These theoretical results enable biophysical dissection of the LFP signal at the cellular level with direct comparison to the clinical recordings, and the model system provides a scientific platform to help guide the design of DBS technology focused on the use of subthalamic beta activity in closed-loop algorithms. NEW & NOTEWORTHY The analysis of deep brain stimulation of local field potential (LFP) data is rapidly expanding from scientific curiosity to the basis for clinical biomarkers capable of improving the therapeutic efficacy of stimulation. With this growing clinical importance comes a growing need to understand the underlying electrophysiological fundamentals of the signals and the factors contributing to their modulation. Our model reconstructs the clinical LFP from first principles and highlights the importance of patient-specific factors in dictating the signals recorded.

How stimulation frequency and intensity impact on the long-lasting effects of coordinated reset stimulation

Several brain diseases are characterized by abnormally strong neuronal synchrony. Coordinated Reset (CR) stimulation was computationally designed to specifically counteract abnormal neuronal synchronization processes by desynchronization. In the presence of spike-timing-dependent plasticity (STDP) this may lead to a decrease of synaptic excitatory weights and ultimately to an anti-kindling, i.e. unlearning of abnormal synaptic connectivity and abnormal neuronal synchrony. The long-lasting desynchronizing impact of CR stimulation has been verified in pre-clinical and clinical proof of concept studies. However, as yet it is unclear how to optimally choose the CR stimulation frequency, i.e. the repetition rate at which the CR stimuli are delivered. This work presents the first computational study on the dependence of the acute and long-term outcome on the CR stimulation frequency in neuronal networks with STDP. For this purpose, CR stimulation was applied with Rapidly Varying Sequences (RVS) as well as with Slowly Varying Sequences (SVS) in a wide range of stimulation frequencies and intensities. Our findings demonstrate that acute desynchronization, achieved during stimulation, does not necessarily lead to long-term desynchronization after cessation of stimulation. By comparing the long-term effects of the two different CR protocols, the RVS CR stimulation turned out to be more robust against variations of the stimulation frequency. However, SVS CR stimulation can obtain stronger anti-kindling effects. We revealed specific parameter ranges that are favorable for long-term desynchronization. For instance, RVS CR stimulation at weak intensities and with stimulation frequencies in the range of the neuronal firing rates turned out to be effective and robust, in particular, if no closed loop adaptation of stimulation parameters is (technically) available. From a clinical standpoint, this may be relevant in the context of both invasive as well as non-invasive CR stimulation.

The oscillatory boundary conditions of different frequency bands in Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disease that is common in the elderly population. The most important pathological change in PD is the degeneration and death of dopaminergic neurons in the substantia nigra of the midbrain, which results in a decrease in the dopamine (DA) content of the striatum. The exact cause of this pathological change is still unknown. Numerous studies have shown that the evolution of PD is associated with abnormal oscillatory activities in the basal ganglia, with different oscillation frequency ranges, such as the typical beta band (13-30 Hz), the alpha band (8-12 Hz), the theta band (4-7 Hz) and the delta band (1-3 Hz). Although some studies have implied that abnormal interactions between the subthalamic nucleus (STN) and globus pallidus (GP) neurons may be a key factor required to induce these oscillations, the relative mechanism is still unclear. The effects of other nerve nuclei in the basal ganglia, such as the striatum, on these oscillations are still unknown. The thalamus and cortex both have close input and output relationships with the basal ganglia, and many previous studies have indicated that they may also exert effects on Parkinson's disease oscillation, but the mechanisms involved are unclear. In this paper, we built a corticothalamic-basal ganglia (CTBG) mean firing-rate model to explore the onset mechanisms of these different oscillation phenomena. We found that, in addition to the STN-GP network, Parkinson's disease oscillations may also be induced by changing the coupling strength and delays in other pathways. Different frequency bands appear in the oscillating region, and various boundary conditions are depicted in parameter diagrams. The onset mechanism is well explained both by the model and by the numerical simulation results. Therefore, this model provides a unifying framework for studying the mechanism of Parkinson's disease oscillations, and we hope that the results obtained in this work can inspire future experimental studies.

Recent Trends in the Use of Electrical Neuromodulation in Parkinson's Disease

PURPOSE OF REVIEW

This review aims to survey recent trends in electrical forms of neuromodulation, with a specific application to Parkinson's disease (PD). Emerging trends are identified, highlighting synergies in state-of-the-art neuromodulation strategies, with directions for future improvements in stimulation efficacy suggested.

RECENT FINDINGS

Deep brain stimulation remains the most common and effective form of electrical stimulation for the treatment of PD. Evidence suggests that transcranial direct current stimulation (tDCS) most likely impacts the motor symptoms of the disease, with the most prominent results relating to rehabilitation. However, utility is limited due to its weak effects and high variability, with medication state a key confound for efficacy level. Recent innovations in transcranial alternating current stimulation (tACS) offer new areas for investigation.

SUMMARY

Our understanding of the mechanistic foundations of electrical current stimulation is advancing and as it does so, trends emerge which steer future clinical trials towards greater efficacy.

High-resolution local field potentials measured with deep brain stimulation arrays

OBJECTIVE

Local field potential (LFP) recordings along a deep brain stimulation (DBS) lead can provide useful feedback for titrating DBS therapy. However, conventional DBS leads with four cylindrical macroelectrodes likely undersample the spatial distribution of sinks and sources in a given brain region. In this study, we investigated the spectral power and spatial feature sizes of LFP activity in non-human primate subthalamic nucleus and globus pallidus using chronically implanted 32-channel directional DBS arrays.

APPROACH

Subthalamic nucleus and globus pallidus LFP signals were recorded from directional DBS arrays in the resting state and during a reach-and-retrieval task in two non-human primates in naïve and parkinsonian conditions. LFP recordings were compared amongst bipolar pairs of electrodes using individual and grouped electrode configurations, with the latter mimicking the cylindrical macroelectrode configurations used in current clinical LFP recordings.

MAIN RESULTS

Recordings from these DBS arrays showed that (1) beta oscillations have spatial 'fingerprints' in the subthalamic nucleus and globus pallidus, and (2) that these oscillations were muted when grouping electrode contacts together to create cylindrical macroelectrodes similar in relative dimension to those used clinically. Further, these maps depended on parkinsonian condition and whether the subject was resting or performing a motor task.

SIGNIFICANCE

Development of future closed-loop DBS therapies that rely on LFP feedback will benefit from implanting DBS arrays with electrode sizes and spacings that are more consistent with the dimensions of oscillatory sinks and sources within the brain.

Intra-operative characterisation of subthalamic oscillations in Parkinson's disease

OBJECTIVE

This study aims to use the activities recorded directly from the deep brain stimulation (DBS) electrode to address the focality and distinct nature of the local field potential (LFP) activities of different frequency.

METHODS

Pre-operative and intra-operative magnetic resonance imaging (MRI) were acquired from patients with Parkinson's disease (PD) who underwent DBS in the subthalamic nucleus and intra-operative LFP recording at rest and during cued movements. Images were reconstructed and 3-D visualized using Lead-DBS® toolbox to determine the coordinates of contact. The resting spectral power and movement-related power modulation of LFP oscillations were estimated.

RESULTS

Both subthalamic LFP activity recorded at rest and its modulation by movement had focal maxima in the alpha, beta and gamma bands. The spatial distribution of alpha band activity and its modulation was significantly different to that in the beta band. Moreover, there were significant differences in the scale and timing of movement related modulation across the frequency bands.

CONCLUSION

Subthalamic LFP activities within specific frequency bands can be distinguished by spatial topography and pattern of movement related modulation.

SIGNIFICANCE

Assessment of the frequency, focality and pattern of movement related modulation of subthalamic LFPs reveals a heterogeneity of neural population activity in this region. This could potentially be leveraged to finesse intra-operative targeting and post-operative contact selection.

Subthalamic Nucleus Deep Brain Stimulation in Parkinson's Disease: The Effect of Varying Stimulation Parameters

Subthalamic Nucleus Deep Brain Stimulation (STN DBS) is a well-established and effective treatment modality for selected patients with Parkinson's disease (PD). Since its advent, systematic exploration of the effect of stimulation parameters including the stimulation intensity, frequency, and pulse width have been carried out to establish optimal therapeutic ranges. This review examines published data on these stimulation parameters in terms of efficacy of treatment and adverse effects. Altering stimulation intensity is the mainstay of titration in DBS programming via alterations in voltage or current settings, and is characterised by a lower efficacy threshold and a higher side effect threshold which define the therapeutic window. In addition, much work has been done in exploring the effects of frequency modulation, which may help patients with gait freezing and other axial symptoms. However, there is a paucity of data on the use of ultra-short pulse width settings which are now possible with technological advances. We also discuss current evidence for the use of novel programming techniques including directional and adaptive stimulation, and highlight areas for future research.

Directional local field potentials: A tool to optimize deep brain stimulation

BACKGROUND

Although recently introduced directional DBS leads provide control of the stimulation field, programing is time-consuming.

OBJECTIVES

Here, we validate local field potentials recorded from directional contacts as a predictor of the most efficient contacts for stimulation in patients with PD.

METHODS

Intraoperative local field potentials were recorded from directional contacts in the STN of 12 patients and beta activity compared with the results of the clinical contact review performed after 4 to 7 months.

RESULTS

Normalized beta activity was positively correlated with the contact's clinical efficacy. The two contacts with the highest beta activity included the most efficient stimulation contact in up to 92% and that with the widest therapeutic window in 74% of cases.

CONCLUSION

Local field potentials predict the most efficient stimulation contacts and may provide a useful tool to expedite the selection of the optimal contact for directional DBS. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Localization of beta and high-frequency oscillations within the subthalamic nucleus region

Parkinsonian bradykinesia and rigidity are typically associated with excessive beta band oscillations in the subthalamic nucleus. Recently another spectral peak has been identified that might be implicated in the pathophysiology of the disease: high-frequency oscillations (HFO) within the 150–400 Hz range. Beta-HFO phase-amplitude coupling (PAC) has been found to correlate with severity of motor impairment. However, the neuronal origin of HFO and its usefulness as a potential target for deep brain stimulation remain to be established. For example, it is unclear whether HFO arise from the same neural populations as beta oscillations. We intraoperatively recorded local field potentials from the subthalamic nucleus while advancing DBS electrodes in 2 mm steps from 4 mm above the surgical target point until 2 mm below, resulting in 4 recording sites. Data from 26 nuclei from 14 patients were analysed. For each trajectory, we identified the recording site with the largest spectral peak in the beta range (13–30 Hz), and the largest peak in the HFO range separately. In addition, we identified the recording site with the largest beta-HFO PAC. Recording sites with largest beta power and largest HFO power coincided in 50% of cases. In the other 50%, HFO was more likely to be detected at a more superior recording site in the target area. PAC followed more closely the site with largest HFO (45%) than beta power (27%). HFO are likely to arise from spatially close, but slightly more superior neural populations than beta oscillations. Further work is necessary to determine whether the different activities can help fine-tune deep brain stimulation targeting.

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LFPs were recorded from multiple sites within and around the subthalamic nucleus.

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Sites with largest beta and high-frequency oscillations (HFO) were identified.

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HFO were located slightly more superior than beta oscillations.

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Phase-amplitude coupling more closely followed the site with largest HFO.

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This work hints at different neural generators for beta and HFO.

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.

Spatial Localization of Sources in the Rat Subthalamic Motor Region Using an Inverse Current Source Density Method

Objective: In this study we introduce the use of the current source density (CSD) method as a way to visualize the spatial organization of evoked responses in the rat subthalamic nucleus (STN) at fixed time stamps resulting from motor cortex stimulation. This method offers opportunities to visualize neuronal input and study the relation between the synaptic input and the neural output of neural populations.

Approach: Motor cortex evoked local field potentials and unit activity were measured in the subthalamic region, with a 3D measurement grid consisting of 320 measurement points and high spatial resolution. This allowed us to visualize the evoked synaptic input by estimating the current source density (CSD) from the measured local field potentials, using the inverse CSD method. At the same time, the neuronal output of the cells within the grid is assessed by calculating post stimulus time histograms.

Main results: The CSD method resulted in clear and distinguishable sources and sinks of the neuronal input activity in the STN after motor cortex stimulation. We showed that the center of the synaptic input of the STN from the motor cortex is located dorsal to the input from globus pallidus.

Significance: For the first time we have performed CSD analysis on motor cortex stimulation evoked LFP responses in the rat STN as a proof of principle. Our results suggest that the CSD method can be used to gain new insights into the spatial extent of synaptic pathways in brain structures.

DBS for Obesity

Obesity is a chronic, progressive and prevalent disorder. Morbid obesity, in particular, is associated with numerous comorbidities and early mortality. In patients with morbid obesity, pharmacological and behavioral approaches often have limited results. Bariatric surgery is quite effective but is associated with operative failures and a non-negligible incidence of side effects. In the last decades, deep brain stimulation (DBS) has been investigated as a neurosurgical modality to treat various neuropsychiatric disorders. In this article we review the rationale for selecting different brain targets, surgical results and future perspectives for the use of DBS in medically refractory obesity.

Computational Modeling and Neuroimaging Techniques for Targeting during Deep Brain Stimulation

Accurate surgical localization of the varied targets for deep brain stimulation (DBS) is a process undergoing constant evolution, with increasingly sophisticated techniques to allow for highly precise targeting. However, despite the fastidious placement of electrodes into specific structures within the brain, there is increasing evidence to suggest that the clinical effects of DBS are likely due to the activation of widespread neuronal networks directly and indirectly influenced by the stimulation of a given target. Selective activation of these complex and inter-connected pathways may further improve the outcomes of currently treated diseases by targeting specific fiber tracts responsible for a particular symptom in a patient-specific manner. Moreover, the delivery of such focused stimulation may aid in the discovery of new targets for electrical stimulation to treat additional neurological, psychiatric, and even cognitive disorders. As such, advancements in surgical targeting, computational modeling, engineering designs, and neuroimaging techniques play a critical role in this process. This article reviews the progress of these applications, discussing the importance of target localization for DBS, and the role of computational modeling and novel neuroimaging in improving our understanding of the pathophysiology of diseases, and thus paving the way for improved selective target localization using DBS.

Model-Based Comparison of Deep Brain Stimulation Array Functionality with Varying Number of Radial Electrodes and Machine Learning Feature Sets

Deep brain stimulation (DBS) leads with radially distributed electrodes have potential to improve clinical outcomes through more selective targeting of pathways and networks within the brain. However, increasing the number of electrodes on clinical DBS leads by replacing conventional cylindrical shell electrodes with radially distributed electrodes raises practical design and stimulation programming challenges. We used computational modeling to investigate: (1) how the number of radial electrodes impact the ability to steer, shift, and sculpt a region of neural activation (RoA), and (2) which RoA features are best used in combination with machine learning classifiers to predict programming settings to target a particular area near the lead. Stimulation configurations were modeled using 27 lead designs with one to nine radially distributed electrodes. The computational modeling framework consisted of a three-dimensional finite element tissue conductance model in combination with a multi-compartment biophysical axon model. For each lead design, two-dimensional threshold-dependent RoAs were calculated from the computational modeling results. The models showed more radial electrodes enabled finer resolution RoA steering; however, stimulation amplitude, and therefore spatial extent of the RoA, was limited by charge injection and charge storage capacity constraints due to the small electrode surface area for leads with more than four radially distributed electrodes. RoA shifting resolution was improved by the addition of radial electrodes when using uniform multi-cathode stimulation, but non-uniform multi-cathode stimulation produced equivalent or better resolution shifting without increasing the number of radial electrodes. Robust machine learning classification of 15 monopolar stimulation configurations was achieved using as few as three geometric features describing a RoA. The results of this study indicate that, for a clinical-scale DBS lead, more than four radial electrodes minimally improved in the ability to steer, shift, and sculpt axonal activation around a DBS lead and a simple feature set consisting of the RoA center of mass and orientation enabled robust machine learning classification. These results provide important design constraints for future development of high-density DBS arrays.

Proceedings of the Third Annual Deep Brain Stimulation Think Tank: A Review of Emerging Issues and Technologies

The proceedings of the 3rd Annual Deep Brain Stimulation Think Tank summarize the most contemporary clinical, electrophysiological, imaging, and computational work on DBS for the treatment of neurological and neuropsychiatric disease. Significant innovations of the past year are emphasized. The Think Tank's contributors represent a unique multidisciplinary ensemble of expert neurologists, neurosurgeons, neuropsychologists, psychiatrists, scientists, engineers, and members of industry. Presentations and discussions covered a broad range of topics, including policy and advocacy considerations for the future of DBS, connectomic approaches to DBS targeting, developments in electrophysiology and related strides toward responsive DBS systems, and recent developments in sensor and device technologies.

Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson's disease

Chronic dopamine depletion in Parkinson's disease leads to progressive motor and cognitive impairment, which is associated with the emergence of characteristic patterns of synchronous oscillatory activity within cortico-basal-ganglia circuits. Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson's disease, but its influence on synchronous activity in cortico-basal-ganglia loops remains to be fully characterized. Here, we demonstrate that deep brain stimulation selectively suppresses certain spatially and spectrally segregated resting state subthalamic nucleus-cortical networks. To this end we used a validated and novel approach for performing simultaneous recordings of the subthalamic nucleus and cortex using magnetoencephalography (during concurrent subthalamic nucleus deep brain stimulation). Our results highlight that clinically effective subthalamic nucleus deep brain stimulation suppresses synchrony locally within the subthalamic nucleus in the low beta oscillatory range and furthermore that the degree of this suppression correlates with clinical motor improvement. Moreover, deep brain stimulation relatively selectively suppressed synchronization of activity between the subthalamic nucleus and mesial premotor regions, including the supplementary motor areas. These mesial premotor regions were predominantly coupled to the subthalamic nucleus in the high beta frequency range, but the degree of deep brain stimulation-associated suppression in their coupling to the subthalamic nucleus was not found to correlate with motor improvement. Beta band coupling between the subthalamic nucleus and lateral motor areas was not influenced by deep brain stimulation. Motor cortical coupling with subthalamic nucleus predominantly involved driving of the subthalamic nucleus, with those drives in the higher beta frequency band having much shorter net delays to subthalamic nucleus than those in the lower beta band. These observations raise the possibility that cortical connectivity with the subthalamic nucleus in the high and low beta bands may reflect coupling mediated predominantly by the hyperdirect and indirect pathways to subthalamic nucleus, respectively, and that subthalamic nucleus deep brain stimulation predominantly suppresses the former. Yet only the change in strength of local subthalamic nucleus oscillations correlates with the degree of improvement during deep brain stimulation, compatible with the current view that a strengthened hyperdirect pathway is a prerequisite for locally generated beta activity but that it is the severity of the latter that may determine or index motor impairment.

A Novel Lead Design for Modulation and Sensing of Deep Brain Structures

GOAL

Develop and characterize the functionality of a novel thin-film probe technology with a higher density of electrode contacts than are currently available with commercial deep brain stimulation (DBS) lead technology. Such technology has potential to enhance the spatial precision of DBS and enable a more robust approach to sensing local field potential activity in the context of adaptive DBS strategies.

METHODS

Thin-film planar arrays were microfabricated and then assembled on a cylindrical carrier to achieve a lead with 3-D conformation. Using an integrated and removable stylet, the arrays were chronically implanted in the subthalamic nucleus and globus pallidus in two parkinsonian nonhuman primates.

RESULTS

This study provides the first in vivo data from chronically implanted DBS arrays for translational nonhuman primate studies. Stimulation through the arrays induced a decrease in parkinsonian rigidity, and directing current around the lead showed an orientation dependence for eliciting motor capsule side effects. The array recordings also showed that oscillatory activity in the basal ganglia is heterogeneous at a smaller scale than detected by the current DBS lead technology.

CONCLUSION

These 3-D DBS arrays provide an enabling tool for future studies that seek to monitor and modulate deep brain activity through chronically implanted leads.

SIGNIFICANCE

DBS lead technology with a higher density of electrode contacts has potential to enable sculpting DBS current flow and sensing biomarkers of disease and therapy.

Local field potential recordings in a non-human primate model of Parkinsons disease using the Activa PC + S neurostimulator

OBJECTIVE

Using the Medtronic Activa® PC + S system, this study investigated how passive joint manipulation, reaching behavior, and deep brain stimulation (DBS) modulate local field potential (LFP) activity in the subthalamic nucleus (STN) and globus pallidus (GP).

APPROACH

Five non-human primates were implanted unilaterally with one or more DBS leads. LFPs were collected in montage recordings during resting state conditions and during motor tasks that facilitate the expression of parkinsonian motor signs. These recordings were made in the naïve state in one subject, in the parkinsonian state in two subjects, and in both naïve and parkinsonian states in two subjects.

MAIN RESULTS

LFPs measured at rest were consistent over time for a given recording location and parkinsonian state in a given subject; however, LFPs were highly variable between subjects, between and within recording locations, and across parkinsonian states. LFPs in both naïve and parkinsonian states across all recorded nuclei contained a spectral peak in the beta band (10-30 Hz). Moreover, the spectral content of recorded LFPs was modulated by passive and active movement of the subjects' limbs. LFPs recorded during a cued-reaching task displayed task-related beta desynchronization in STN and GP. The bidirectional capabilities of the Activa® PC + S also allowed for recording LFPs while delivering DBS. The therapeutic effect of STN DBS on parkinsonian rigidity outlasted stimulation for 30-60 s, but there was no correlation with beta band power.

SIGNIFICANCE

This study emphasizes (1) the variability in spontaneous LFPs amongst subjects and (2) the value of using the Activa® PC + S system to record neural data in the context of behavioral tasks that allow one to evaluate a subject's symptomatology.