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

Computational models advance deep brain stimulation for Parkinson's disease

Deep brain stimulation(DBS) has become an effective intervention for advanced Parkinson's disease(PD), but the exact mechanism of DBS is still unclear. In this review, we discuss the history of DBS, the anatomy and internal architecture of the basal ganglia (BG), the abnormal pathological changes of the BG in PD, and how computational models can help understand and advance DBS. We also describe two types of models: mathematical theoretical models and clinical predictive models. Mathematical theoretical models simulate neurons or neural networks of BG to shed light on the mechanistic principle underlying DBS, while clinical predictive models focus more on patients' outcomes, helping to adapt treatment plans for each patient and advance novel electrode designs. Finally, we provide insights and an outlook on future technologies.

Functional Enhancement and Characterization of an Electrophysiological Mapping Electrode Probe with Carbonic, Directional Macrocontacts

Electrophysiological mapping (EM) using acute electrode probes is a common procedure performed during functional neurosurgery. Due to their constructive specificities, the EM probes are lagging in innovative enhancements. This work addressed complementing a clinically employed EM probe with carbonic and circumferentially segmented macrocontacts that are operable both for neurophysiological sensing ("recording") of local field potentials (LFP) and for test stimulation. This paper illustrates in-depth the development that is based on the direct writing of functional materials. The unconventional fabrication processes were optimized on planar geometry and then transferred to the cylindrically thin probe body. We report and discuss the constructive concept and architecture of the probe, characteristics of the electrochemical interface deduced from voltammetry and chronopotentiometry, and the results of in vitro and in vivo recording and pulse stimulation tests. Two- and three-directional macrocontacts were added on probes having shanks of 550 and 770 μm diameters and 10-23 cm lengths. The graphitic material presents a ~2.7 V wide, almost symmetric water electrolysis window, and an ultra-capacitive charge transfer. When tested with clinically relevant 150 μs biphasic current pulses, the interfacial polarization stayed safely away from the water window for pulse amplitudes up to 9 mA (135 μC/cm2). The in vivo experiments on adult rat models confirmed the high-quality sensing of LFPs. Additionally, the in vivo-prevailing increase in the electrode impedance and overpotential are discussed and modeled by an ionic mobility-reducing spongiform structure; this restricted diffusion model gives new applicative insight into the in vivo-uprisen stimulation overpotential.

Oscillatory beta dynamics inform biomarker-driven treatment optimization for Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disorder characterized by loss of dopaminergic neurons and dysregulation of the basal ganglia. Cardinal motor symptoms include bradykinesia, rigidity, and tremor. Deep brain stimulation (DBS) of select subcortical nuclei is standard of care for medication-refractory PD. Conventional open-loop DBS delivers continuous stimulation with fixed parameters that do not account for a patient's dynamic activity state or medication cycle. In comparison, closed-loop DBS, or adaptive DBS (aDBS), adjusts stimulation based on biomarker feedback that correlates with clinical state. Recent work has identified several neurophysiological biomarkers in local field potential recordings from PD patients, the most promising of which are 1) elevated beta (∼13-30 Hz) power in the subthalamic nucleus (STN), 2) increased beta synchrony throughout basal ganglia-thalamocortical circuits, notably observed as coupling between the STN beta phase and cortical broadband gamma (∼50-200 Hz) amplitude, and 3) prolonged beta bursts in the STN and cortex. In this review, we highlight relevant frequency and time domain features of STN beta measured in PD patients and summarize how spectral beta power, oscillatory beta synchrony, phase-amplitude coupling, and temporal beta bursting inform PD pathology, neurosurgical targeting, and DBS therapy. We then review how STN beta dynamics inform predictive, biomarker-driven aDBS approaches for optimizing PD treatment. We therefore provide clinically useful and actionable insight that can be applied toward aDBS implementation for PD.

Developments in the mechanistic understanding and clinical application of deep brain stimulation for Parkinson's disease

INTRODUCTION. Deep brain stimulation (DBS) is a life-changing treatment for patients with Parkinson's disease (PD) and gives the unique opportunity to directly explore how basal ganglia work. Despite the rapid technological innovation of the last years, the untapped potential of DBS is still high.

AREAS COVERED. This review summarizes the developments in the mechanistic understanding of DBS and the potential clinical applications of cutting-edge technological advances. Rather than a univocal local mechanism, DBS exerts its therapeutic effects through several multimodal mechanisms and involving both local and network-wide structures, although crucial questions remain unexplained. Nonetheless, new insights in mechanistic understanding of DBS in PD have provided solid bases for advances in preoperative selection phase, prediction of motor and non-motor outcomes, leads placement and postoperative stimulation programming.

EXPERT OPINION. DBS has not only strong evidence of clinical effectiveness in PD treatment, but technological advancements are revamping its role of neuromodulation of brain circuits and key to better understanding PD pathophysiology. In the next few years, the worldwide use of new technologies in clinical practice will provide large data to elucidate their role and to expand their applications for PD patients, providing useful insights to personalize DBS treatment and follow-up.

Stability and Effect of Parkinsonian State on Deep Brain Stimulation Cortical Evoked Potentials

OBJECTIVES

To characterize and compare the stability of cortical potentials evoked by deep brain stimulation (DBS) of the subthalamic nucleus (STN) across the naïve, parkinsonian, and pharmacologically treated parkinsonian states. To advance cortical potentials as possible biomarkers for DBS programming.

MATERIALS AND METHODS

Serial electrocorticographic (ECoG) recordings were made more than nine months from a single non-human primate instrumented with bilateral ECoG grids spanning anterior parietal to prefrontal cortex. Cortical evoked potentials (CEPs) were generated through time-lock averaging of the ECoG recordings to DBS pulses delivered unilaterally in the STN region using a chronically implanted, six-contact, scaled DBS lead. Recordings were made across the naïve followed by mild and moderate parkinsonian conditions achieved by staged injections of the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) neurotoxin. In addition to characterizing the spatial distribution and stability of the response within each state, changes in the amplitude and latency of CEP components as well as in the frequency content were examined in relation to parkinsonian severity and dopamine replacement.

RESULTS

In the naïve state, the STN DBS CEP presented as a multiphase response maximal over M1 cortex, with components attributable to physiological activity distinguishable from stimulus artifact as early as 0.45-0.75 msec poststimulation. When delivered using therapeutically effective parameters in the parkinsonian state, the CEP was highly stable across multiple recording sessions within each behavioral state. Across states, significant differences were present with respect to both the latency and amplitude of individual response components, with greater differences present for longer-latency components (all p < 0.05). Power spectral density analysis revealed a high-beta peak within the evoked response, with significant changes in power between disease states across multiple frequency bands.

CONCLUSIONS

Our findings underscore the spatiotemporal specificity and relative stability of the DBS-CEP associated with different disease states and with therapeutic benefit. DBS-CEP may be a viable biomarker for therapeutic programming.

Meta-Bayesian Optimization for Deep Brain Stimulation

Deep brain stimulation (DBS) is becoming a fundamental tool for the treatment and study of neurological and psychiatric diseases and disorders. Recently developed DBS devices and electrodes have allowed for more flexible and precise stimulation. Densely packed stimulation contacts can be independently stimulated to shape the electric field, targeting pathways of interest, and avoiding those that may cause side-effects. However, this flexibility comes at a cost. Each additional stimulation setting causes an exponential increase in the number of potential stimulation settings. Recent works have addressed this problem using Bayesian optimization. However, this approach has a limited ability to learn from multiple subjects to improve performance. In this study we extend a recently developed meta-Bayesian optimization algorithm to the DBS domain. We evaluated this approach compared to classical Bayesian optimization and a random search using data collected from a nonhuman primate during stimulation of the subthalamic nucleus while recording evoked potentials in the motor cortex and locally within the subthalamic nucleus. On the task of finding the stimulation setting that maximized the evoked potential across a distribution of generated objective functions, meta-Bayesian optimization significantly outperformed the other approaches with a cumulative reward of 8.93±0.70, compared to 7.17±1.64 for Bayesian optimization (p < 10^-9) and 6.89±1.56 for the random search (p < 10^-9). Moreover, the algorithm outperformed Bayesian optimization when tested on an objective function not used during training. These results demonstrate that meta-Bayesian optimization can take advantage of the structure underlying a distribution of objective function and learn an optimal search strategy that can generalize beyond the objective functions that were not part of the training data. Clinical Relevance - This extends a meta-Bayesian optimization approach for optimizing DBS stimulation settings that outperforms state-of-art algorithms by 24.6%.

Directions of Deep Brain Stimulation for Epilepsy and Parkinson's Disease

BACKGROUND

Deep brain stimulation (DBS) is an effective treatment for movement disorders and neurological/psychiatric disorders. DBS has been approved for the control of Parkinson disease (PD) and epilepsy.

OBJECTIVES

A systematic review and possible future direction of DBS system studies is performed in the open loop and closed-loop configuration on PD and epilepsy.

METHODS

We searched Google Scholar database for DBS system and development. DBS search results were categorized into clinical device and research system from the open-loop and closed-loop perspectives.

RESULTS

We performed literature review for DBS on PD and epilepsy in terms of system development by the open loop and closed-loop configuration. This study described development and trends for DBS in terms of electrode, recording, stimulation, and signal processing. The closed-loop DBS system raised a more attention in recent researches.

CONCLUSION

We overviewed development and progress of DBS. Our results suggest that the closed-loop DBS is important for PD and epilepsy.

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.

Orientation-selective and directional deep brain stimulation in swine assessed by functional MRI at 3T

Functional MRI (fMRI) has become an important tool for probing network-level effects of deep brain stimulation (DBS). Previous DBS-fMRI studies have shown that electrical stimulation of the ventrolateral (VL) thalamus can modulate sensorimotor cortices in a frequency and amplitude dependent manner. Here, we investigated, using a swine animal model, how the direction and orientation of the electric field, induced by VL-thalamus DBS, affects activity in the sensorimotor cortex. Adult swine underwent implantation of a novel 16-electrode (4 rows × 4 columns) directional DBS lead in the VL thalamus. A within-subject design was used to compare fMRI responses for (1) directional stimulation consisting of monopolar stimulation in four radial directions around the DBS lead, and (2) orientation-selective stimulation where an electric field dipole was rotated 0°−360° around a quadrangle of electrodes. Functional responses were quantified in the premotor, primary motor, and somatosensory cortices. High frequency electrical stimulation through leads implanted in the VL thalamus induced directional tuning in cortical response patterns to varying degrees depending on DBS lead position. Orientation-selective stimulation showed maximal functional response when the electric field was oriented approximately parallel to the DBS lead, which is consistent with known axonal orientations of the cortico-thalamocortical pathway. These results demonstrate that directional and orientation-selective stimulation paradigms in the VL thalamus can tune network-level modulation patterns in the sensorimotor cortex, which may have translational utility in improving functional outcomes of DBS therapy.

Slim electrodes for improved targeting in deep brain stimulation

OBJECTIVE

The efficacy of deep brain stimulation can be limited by factors including poor selectivity of stimulation, targeting error, and complications related to implant reliability and stability. We aimed to improve surgical outcomes by evaluating electrode leads with smaller diameter electrode and microelectrodes incorporated which can be used for assisting targeting.

APPROACH

Electrode arrays were constructed with two different diameters of 0.65 mm and the standard 1.3 mm. Micro-electrodes were incorporated into the slim electrode arrays for recording spiking neural activity. Arrays were bilaterally implanted into the medial geniculate body (MGB) in nine anaesthetised cats for 24-40 h using stereotactic techniques. Recordings of auditory evoked field potentials and multi-unit activity were obtained at 1 mm intervals along the electrode insertion track. Insertion trauma was evaluated histologically.

MAIN RESULTS

Evoked auditory field potentials were recorded from ring and micro-electrodes in the vicinity of the medial geniculate body. Spiking activity was recorded from 81% of the microelectrodes approaching the MGB. Histological examination showed localized surgical trauma along the implant. The extent of haemorrhage surrounding the track was measured and found to be significantly reduced with the slim electrodes (541 ± 455 µm vs. 827 ± 647 µm; P < 0.001). Scoring of the trauma, focusing on tissue disruption, haemorrhage, oedema of glial parenchyma and pyknosis, revealed a significantly lower trauma score for the slim electrodes (P < 0.0001).

SIGNIFICANCE

The slim electrodes reduced the extent of acute trauma, while still providing adequate electrode impedance for both stimulating and recording, and providing the option to target stimulate smaller volumes of tissue. The incorporation of microelectrodes into the electrode array may allow for a simplified, single-step surgical approach where confirmatory micro-targeting is done with the same lead used for permanent implantation.

A Review: Electrode and Packaging Materials for Neurophysiology Recording Implants

To date, a wide variety of neural tissue implants have been developed for neurophysiology recording from living tissues. An ideal neural implant should minimize the damage to the tissue and perform reliably and accurately for long periods of time. Therefore, the materials utilized to fabricate the neural recording implants become a critical factor. The materials of these devices could be classified into two broad categories: electrode materials as well as packaging and substrate materials. In this review, inorganic (metals and semiconductors), organic (conducting polymers), and carbon-based (graphene and carbon nanostructures) electrode materials are reviewed individually in terms of various neural recording devices that are reported in recent years. Properties of these materials, including electrical properties, mechanical properties, stability, biodegradability/bioresorbability, biocompatibility, and optical properties, and their critical importance to neural recording quality and device capabilities, are discussed. For the packaging and substrate materials, different material properties are desired for the chronic implantation of devices in the complex environment of the body, such as biocompatibility and moisture and gas hermeticity. This review summarizes common solid and soft packaging materials used in a variety of neural interface electrode designs, as well as their packaging performances. Besides, several biopolymers typically applied over the electrode package to reinforce the mechanical rigidity of devices during insertion, or to reduce the immune response and inflammation at the device-tissue interfaces are highlighted. Finally, a benchmark analysis of the discussed materials and an outlook of the future research trends are concluded.

Understanding Parkinson's disease and deep brain stimulation: Role of monkey models

Parkinson's disease (PD) is a progressive neurodegenerative movement disorder affecting over 10 million people worldwide. In the 1930s and 1940s there was little understanding regarding what caused PD or how to treat it. In a desperate attempt to improve patients' lives different regions of the neuraxis were ablated. Morbidity and mortality were common, but some patients' motor signs improved with lesions involving the basal ganglia or thalamus. With the discovery of l-dopa the advent of medical therapy began and surgical approaches became less frequent. It soon became apparent, however, that medical therapy was associated with side effects in the form of drug-induced dyskinesia and motor fluctuations and surgical therapies reemerged. Fortunately, during this time studies in monkeys had begun to lay the groundwork to understand the functional organization of the basal ganglia, and with the discovery of the neurotoxin MPTP a monkey model of PD had been developed. Using this model scientists were characterizing the physiological changes that occurred in the basal ganglia in PD and models of basal ganglia function and dysfunction were proposed. This work provided the rationale for the return of pallidotomy, and subsequently deep brain stimulation procedures. In this paper we describe the evolution of these monkey studies, how they provided a greater understanding of the pathophysiology underlying the development of PD and provided the rationale for surgical procedures, the search to understand mechanisms of DBS, and how these studies have been instrumental in understanding PD and advancing the development of surgical therapies for its treatment.

Emerging technologies for improved deep brain stimulation

Deep brain stimulation (DBS) is an effective treatment for common movement disorders and has been used to modulate neural activity through delivery of electrical stimulation to key brain structures. The long-term efficacy of stimulation in treating disorders, such as Parkinson's disease and essential tremor, has encouraged its application to a wide range of neurological and psychiatric conditions. Nevertheless, adoption of DBS remains limited, even in Parkinson's disease. Recent failed clinical trials of DBS in major depression, and modest treatment outcomes in dementia and epilepsy, are spurring further development. These improvements focus on interaction with disease circuits through complementary, spatially and temporally specific approaches. Spatial specificity is promoted by the use of segmented electrodes and field steering, and temporal specificity involves the delivery of patterned stimulation, mostly controlled through disease-related feedback. Underpinning these developments are new insights into brain structure-function relationships and aberrant circuit dynamics, including new methods with which to assess and refine the clinical effects of stimulation.

Comparing Current Steering Technologies for Directional Deep Brain Stimulation Using a Computational Model That Incorporates Heterogeneous Tissue Properties

Objective

A computational model that accounts for heterogeneous tissue properties was used to compare multiple independent current control (MICC), multi‐stim set (MSS), and concurrent activation (co‐activation) current steering technologies utilized in deep brain stimulation (DBS) on volume of tissue activated (VTA) and power consumption.

Methods

A computational model was implemented in Sim4Life v4.0 with the multimodal image‐based detailed anatomical (MIDA) model, which accounts for heterogeneous tissue properties. A segmented DBS lead placed in the subthalamic nucleus (STN). Three milliamperes of current (with a 90 μs pseudo‐biphasic waveform) was distributed between two electrodes with various current splits. The laterality, directional accuracy, volume, and shape of the VTAs using MICC, MSS and co‐activation, and their power consumption were computed and compared.

Results

MICC, MSS, and coactivation resulted in less laterality of steering than single‐segment activation. Both MICC and MSS show directional inaccuracy (more pronounced with MSS) during radial current steering. Co‐activation showed greater directional accuracy than MICC and MSS at centerline between the two activated electrodes. MSS VTA volume was smaller and more compact with less current spread outside the active electrode plane than MICC VTA. There was no consistent pattern of power drain between MSS and MICC, but electrode co‐activation always used less power than either fractionating paradigm.

Conclusion

While current fractionalization technologies can achieve current steering between two segmented electrodes, this study shows that there are important limitations in accuracy and focus of tissue activation when tissue heterogeneity is accounted for.

Integrity Assessment of a Hybrid DBS Probe that Enables Neurotransmitter Detection Simultaneously to Electrical Stimulation and Recording

Deep brain stimulation (DBS) is a successful medical therapy for many treatment resistant neuropsychiatric disorders such as movement disorders; e.g., Parkinson's disease, Tremor, and dystonia. Moreover, DBS is becoming more and more appealing for a rapidly growing number of patients with other neuropsychiatric diseases such as depression and obsessive compulsive disorder. In spite of the promising outcomes, the current clinical hardware used in DBS does not match the technological standards of other medical applications and as a result could possibly lead to side effects such as high energy consumption and others. By implementing more advanced DBS devices, in fact, many of these limitations could be overcome. For example, a higher channels count and smaller electrode sites could allow more focal and tailored stimulation. In addition, new materials, like carbon for example, could be incorporated into the probes to enable adaptive stimulation protocols by biosensing neurotransmitters in the brain. Updating the current clinical DBS technology adequately requires combining the most recent technological advances in the field of neural engineering. Here, a novel hybrid multimodal DBS probe with glassy carbon microelectrodes on a polyimide thin-film device assembled on a silicon rubber tubing is introduced. The glassy carbon interface enables neurotransmitter detection using fast scan cyclic voltammetry and electrophysiological recordings while simultaneously performing electrical stimulation. Additionally, the presented DBS technology shows no imaging artefacts in magnetic resonance imaging. Thus, we present a promising new tool that might lead to a better fundamental understanding of the underlying mechanism of DBS while simultaneously paving our way towards better treatments.

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.

Deep brain stimulation induces sparse distributions of locally modulated neuronal activity

Deep brain stimulation (DBS) therapy is a potent tool for treating a range of brain disorders. High frequency stimulation (HFS) patterns used in DBS therapy are known to modulate neuronal spike rates and patterns in the stimulated nucleus; however, the spatial distribution of these modulated responses are not well understood. Computational models suggest that HFS modulates a volume of tissue spatially concentrated around the active electrode. Here, we tested this theory by investigating modulation of spike rates and patterns in non-human primate motor thalamus while stimulating the cerebellar-receiving area of motor thalamus, the primary DBS target for treating Essential Tremor. HFS inhibited spike activity in the majority of recorded cells, but increasing stimulation amplitude also shifted the response to a greater degree of spike pattern modulation. Modulated responses in both categories exhibited a sparse and long-range spatial distribution within motor thalamus, suggesting that stimulation preferentially affects afferent and efferent axonal processes traversing near the active electrode and that the resulting modulated volume strongly depends on the local connectome of these axonal processes. Such findings have important implications for current clinical efforts building predictive computational models of DBS therapy, developing directional DBS lead technology, and formulating closed-loop DBS strategies.

Adaptive Deep Brain Stimulation for Movement Disorders: The Long Road to Clinical Therapy

Continuous high-frequency DBS is an established treatment for essential tremor and Parkinson's disease. Current developments focus on trying to widen the therapeutic window of DBS. Adaptive DBS (aDBS), where stimulation is dynamically controlled by feedback from biomarkers of pathological brain circuit activity, is one such development. Relevant biomarkers may be central, such as local field potential activity, or peripheral, such as inertial tremor data. Moreover, stimulation may be directed by the amplitude or the phase (timing) of the biomarker signal. In this review, we evaluate existing aDBS studies as proof-of-principle, discuss their limitations, most of which stem from their acute nature, and propose what is needed to take aDBS into a chronic setting. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Orientation selective deep brain stimulation

OBJECTIVE

Target selectivity of deep brain stimulation (DBS) therapy is critical, as the precise locus and pattern of the stimulation dictates the degree to which desired treatment responses are achieved and adverse side effects are avoided. There is a clear clinical need to improve DBS technology beyond currently available stimulation steering and shaping approaches. We introduce orientation selective neural stimulation as a concept to increase the specificity of target selection in DBS.

APPROACH

This concept, which involves orienting the electric field along an axonal pathway, was tested in the corpus callosum of the rat brain by freely controlling the direction of the electric field on a plane using a three-electrode bundle, and monitoring the response of the neurons using functional magnetic resonance imaging (fMRI). Computational models were developed to further analyze axonal excitability for varied electric field orientation.

MAIN RESULTS

Our results demonstrated that the strongest fMRI response was observed when the electric field was oriented parallel to the axons, while almost no response was detected with the perpendicular orientation of the electric field relative to the primary fiber tract. These results were confirmed by computational models of the experimental paradigm quantifying the activation of radially distributed axons while varying the primary direction of the electric field.

SIGNIFICANCE

The described strategies identify a new course for selective neuromodulation paradigms in DBS based on axonal fiber orientation.

Particle swarm optimization for programming deep brain stimulation arrays

OBJECTIVE

Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently.

APPROACH

Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption.

MAIN RESULTS

The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (⩽9.2%) and ROA (⩽1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n  =  3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies of  <1% between approaches.

SIGNIFICANCE

The PSO algorithm provides a computationally efficient way to program DBS systems especially those with higher electrode counts.

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.

Deep Brain Stimulation: A Paradigm Shifting Approach to Treat Parkinson's Disease

Parkinson disease (PD) is a chronic and progressive movement disorder classically characterized by slowed voluntary movements, resting tremor, muscle rigidity, and impaired gait and balance. Medical treatment is highly successful early on, though the majority of people experience significant complications in later stages. In advanced PD, when medications no longer adequately control motor symptoms, deep brain stimulation (DBS) offers a powerful therapeutic alternative. DBS involves the surgical implantation of one or more electrodes into specific areas of the brain, which modulate or disrupt abnormal patterns of neural signaling within the targeted region. Outcomes are often dramatic following DBS, with improvements in motor function and reductions motor complications having been repeatedly demonstrated. Given such robust responses, emerging indications for DBS are being investigated. In parallel with expansions of therapeutic scope, advancements within the areas of neurosurgical technique and the precision of stimulation delivery have recently broadened as well. This review focuses on the revolutionary addition of DBS to the therapeutic armamentarium for PD, and summarizes the technological advancements in the areas of neuroimaging and biomedical engineering intended to improve targeting, programming, and overall management.