Current steering to control the volume of tissue activated during deep brain stimulation

Directional Deep Brain Stimulation Programming: Is the Segment Clearly Identifiable and Stable Over Time?

BACKGROUND

In our early experience programming directional deep brain stimulation (d-DBS) in PD, we found the optimal directional segment changed over time in some patients. To determine the frequency/reasons for this we examined whether (1) different programmers would identify the same segment as "optimal"; and (2) the same programmer would select the same "optimal" segment over time. We hypothesized there would be a moderately high level of agreement on optimal electrode selection between different assessors and repeated assessments by the same evaluator.

METHODS

This was a prospective, double-blind investigation evaluating the reliability and stability of programming d-DBS. Each patient underwent a mono-polar survey four times (2 time points by 2 separate assessors). The primary aim was the inter-rater agreement of selecting the optimal electrode at 1 and 6 months. The secondary aim was to determine the intra-rater agreement of selecting the optimal electrode from 1 to 6 months.

RESULTS

Twenty-one patients were enrolled. There was fair inter-rater agreement at 1 month and moderate at 6 months. There was minimal intra-rater agreement between 1 and 6 months.

DISCUSSION

The data refuted our hypothesis. Potential reasons for low agreement include (1) the arduous/subjective nature of identifying the optimal electrode in d-DBS systems, especially in well-placed electrodes; and/or (2) acute changes to the location of stimulation delivery offering temporary improvement in symptoms. Key takeaways gathered were it may, (1) behoove the programmer to explore different electrode montages after a period of time; and (2) be more efficient to review the directional electrode montage only when dictated by clinical symptoms/disease progression.

Focused stimulation of dorsal versus ventral subthalamic nucleus enhances action-outcome learning in patients with Parkinson's disease

Deep brain stimulation of the subthalamic nucleus is an effective treatment for the clinical motor symptoms of Parkinson's disease, but may alter the ability to learn contingencies between stimuli, actions and outcomes. We investigated how stimulation of the functional subregions in the subthalamic nucleus (motor and cognitive regions) modulates stimulus-action-outcome learning in Parkinson's disease patients. Twelve Parkinson's disease patients with deep brain stimulation of the subthalamic nucleus completed a probabilistic stimulus-action-outcome task while undergoing ventral and dorsal subthalamic nucleus stimulation (within subjects, order counterbalanced). The task orthogonalized action choice and outcome valence, which created four action-outcome learning conditions: action-reward, inhibit-reward, action-punishment avoidance and inhibit-punishment avoidance. We compared the effects of deep brain stimulation on learning rates across these conditions as well as on computed Pavlovian learning biases. Dorsal stimulation was associated with higher overall learning proficiency relative to ventral subthalamic nucleus stimulation. Compared to ventral stimulation, stimulating the dorsal subthalamic nucleus led to a particular advantage in learning to inhibit action to produce desired outcomes (gain reward or avoid punishment) as well as better learning proficiency across all conditions providing reward opportunities. The Pavlovian reward bias was reduced with dorsal relative to ventral subthalamic nucleus stimulation, which was reflected by improved inhibit-reward learning. Our results show that focused stimulation in the dorsal compared to the ventral subthalamic nucleus is relatively more favourable for learning action-outcome contingencies and reduces the Pavlovian bias that could lead to reward-driven behaviour. Considering the effects of deep brain stimulation of the subthalamic nucleus on learning and behaviour could be important when optimizing stimulation parameters to avoid side effects like impulsive reward-driven behaviour.

Biophysical Principles and Computational Modeling of Deep Brain Stimulation

BACKGROUND

Deep brain stimulation (DBS) has revolutionized the treatment of neurological disorders, yet the mechanisms of DBS are still under investigation. Computational models are important in silico tools for elucidating these underlying principles and potentially for personalizing DBS therapy to individual patients. The basic principles underlying neurostimulation computational models, however, are not well known in the clinical neuromodulation community.

OBJECTIVE

In this study, we present a tutorial on the derivation of computational models of DBS and outline the biophysical contributions of electrodes, stimulation parameters, and tissue substrates to the effects of DBS.

RESULTS

Given that many aspects of DBS are difficult to characterize experimentally, computational models have played an important role in understanding how material, size, shape, and contact segmentation influence device biocompatibility, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Neural activation is dictated by stimulation parameters including frequency, current vs voltage control, amplitude, pulse width, polarity configurations, and waveform. These parameters also affect the potential for tissue damage, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Activation of the neural substrate also is influenced by the encapsulation layer surrounding the electrode, the conductivity of the surrounding tissue, and the size and orientation of white matter fibers. These properties modulate the effects of the electric field and determine the ultimate therapeutic response.

CONCLUSION

This article describes biophysical principles that are useful for understanding the mechanisms of neurostimulation.

Nanoporous graphene-based thin-film microelectrodes for in vivo high-resolution neural recording and stimulation

One of the critical factors determining the performance of neural interfaces is the electrode material used to establish electrical communication with the neural tissue, which needs to meet strict electrical, electrochemical, mechanical, biological and microfabrication compatibility requirements. This work presents a nanoporous graphene-based thin-film technology and its engineering to form flexible neural interfaces. The developed technology allows the fabrication of small microelectrodes (25 µm diameter) while achieving low impedance (∼25 kΩ) and high charge injection (3-5 mC cm-2). In vivo brain recording performance assessed in rodents reveals high-fidelity recordings (signal-to-noise ratio >10 dB for local field potentials), while stimulation performance assessed with an intrafascicular implant demonstrates low current thresholds (<100 µA) and high selectivity (>0.8) for activating subsets of axons within the rat sciatic nerve innervating tibialis anterior and plantar interosseous muscles. Furthermore, the tissue biocompatibility of the devices was validated by chronic epicortical (12 week) and intraneural (8 week) implantation. This work describes a graphene-based thin-film microelectrode technology and demonstrates its potential for high-precision and high-resolution neural interfacing.

Neurostimulation for Generalized Epilepsy: Should Therapy be Syndrome-specific?

Current applications of neurostimulation for generalized epilepsy use a one-target-fits-all approach that is agnostic to the specific epilepsy syndrome and seizure type being treated. The authors describe similarities and differences between the 2 "archetypes" of generalized epilepsy-Lennox-Gastaut syndrome and Idiopathic Generalized Epilepsy-and review recent neuroimaging evidence for syndrome-specific brain networks underlying seizures. Implications for stimulation targeting and programming are discussed using 5 clinical questions: What epilepsy syndrome does the patient have? What brain networks are involved? What is the optimal stimulation target? What is the optimal stimulation paradigm? What is the plan for adjusting stimulation over time?

Deep Brain Stimulation (DBS) in Treatment-Resistant Depression (TRD): Hope and Concern

In this chapter, we explore the historical evolution, current applications, and future directions of Deep Brain Stimulation (DBS) for Treatment-Resistant Depression (TRD). We begin by highlighting the early efforts of neurologists and neurosurgeons who laid the foundations for today's DBS techniques, moving from controversial lobotomies to the precision of stereotactic surgery. We focus on the advent of DBS, emphasizing its emergence as a significant breakthrough for movement disorders and its extension to psychiatric conditions, including TRD. We provide an overview of the neural networks implicated in depression, detailing the rationale for the choice of common DBS targets. We also cover the technical aspects of DBS, from electrode placement to programming and parameter selection. We then critically review the evidence from clinical trials and open-label studies, acknowledging the mixed outcomes and the challenges posed by placebo effects and trial design. Safety and ethical considerations are also discussed. Finally, we explore innovative directions for DBS research, including the potential of closed-loop systems, dual stimulation strategies, and noninvasive alternatives like ultrasound neuromodulation. In the last section, we outline recommendations for future DBS studies, including the use of alternative designs for placebo control, the collection of neural and behavioral recordings, and the application of machine-learning approaches.

An optimization framework for targeted spinal cord stimulation

Objective. Spinal cord stimulation (SCS) is a common neurostimulation therapy to manage chronic pain. Technological advances have produced new neurostimulation systems with expanded capabilities in an attempt to improve the clinical outcomes associated with SCS. However, these expanded capabilities have dramatically increased the number of possible stimulation parameters and made it intractable to efficiently explore this large parameter space within the context of standard clinical programming procedures. Therefore, in this study, we developed an optimization approach to define the optimal current amplitudes or fractions across individual contacts in an SCS electrode array(s).Approach. We developed an analytic method using the Lagrange multiplier method along with smoothing approximations. To test our optimization framework, we used a hybrid computational modeling approach that consisted of a finite element method model and multi-compartment models of axons and cells within the spinal cord. Moreover, we extended our approach to multi-objective optimization to explore the trade-off between activating regions of interest (ROIs) and regions of avoidance (ROAs).Main results. For simple ROIs, our framework suggested optimized configurations that resembled simple bipolar configurations. However, when we considered multi-objective optimization, our framework suggested nontrivial stimulation configurations that could be selected from Pareto fronts to target multiple ROIs or avoid ROAs.Significance. We developed an optimization framework for targeted SCS. Our method is analytic, which allows for the fast calculation of optimal solutions. For the first time, we provided a multi-objective approach for selective SCS. Through this approach, we were able to show that novel configurations can provide neural recruitment profiles that are not possible with conventional stimulation configurations (e.g. bipolar stimulation). Most importantly, once integrated with computational models that account for sources of interpatient variability (e.g. anatomy, electrode placement), our optimization framework can be utilized to provide stimulation settings tailored to the needs of individual patients.

Variations in Determining Actual Orientations of Segmented Deep Brain Stimulation Leads Using the DiODe Algorithm: A Retrospective Study Across Different Lead Designs and Medical Institutions

INTRODUCTION

Directional deep brain stimulation (DBS) leads have become widely used in the past decade. Understanding the asymmetric stimulation provided by directional leads requires precise knowledge of the exact orientation of the lead in respect to its anatomical target. Recently, the DiODe algorithm was developed to automatically determine the orientation angle of leads from the artifact on postoperative computed tomography (CT) images. However, manual DiODe results are user-dependent. This study analyzed the extent of lead rotation as well as the user agreement of DiODe calculations across the two most common DBS systems, namely, Boston Scientific's Vercise and Abbott's Infinity, and two independent medical institutions.

METHODS

Data from 104 patients who underwent an anterior-facing unilateral/bilateral directional DBS implantation at either Northwestern Memorial Hospital (NMH) or Albany Medical Center (AMC) were retrospectively analyzed. Actual orientations of the implanted leads were independently calculated by three individual users using the DiODe algorithm in Lead-DBS and patients' postoperative CT images. The deviation from the intended orientation and user agreement were assessed.

RESULTS

All leads significantly deviated from the intended 0° orientation (p < 0.001), regardless of DBS lead design (p < 0.05) or institution (p < 0.05). However, the Boston Scientific leads showed an implantation bias toward the left at both institutions (p = 0.014 at NMH, p = 0.029 at AMC). A difference of 10° between at least two users occurred in 28% (NMH) and 39% (AMC) of all Boston Scientific and 76% (NMH) and 53% (AMC) of all Abbott leads.

CONCLUSION

Our results show that there is a significant lead rotation from the intended surgical orientation across both DBS systems and both medical institutions; however, a bias toward a single direction was only seen in the Boston Scientific leads. Additionally, these results raise questions into the user error that occurs when manually refining the orientation angles calculated with DiODe.

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.

Identifying the therapeutic zone in globus pallidus deep brain stimulation for Parkinson's disease

OBJECTIVE

The globus pallidus internus (GPI) has been demonstrated to be an effective surgical target for deep brain stimulation (DBS) treatment in patients with medication-refractory Parkinson's disease (PD). The ability of neurosurgeons to define the area of greatest therapeutic benefit within the globus pallidus (GP) may improve clinical outcomes in these patients. The objective of this study was to determine the best DBS therapeutic implantation site within the GP for effective treatment in PD patients.

METHODS

The authors performed a retrospective review of 56 patients who underwent bilateral GP DBS implantation at their institution during the period from January 2015 to January 2020. Each implanted contact was anatomically localized. Patients were followed for stimulation programming for at least 6 months. The authors reviewed preoperative and 6-month postsurgery clinical outcomes based on data from the Unified Parkinson's Disease Rating Scale Part III (UPDRS III), dyskinesia scores, and levodopa equivalent daily dose (LEDD).

RESULTS

Of the 112 leads implanted, the therapeutic cathode was most frequently located in the lamina between the GPI external segment (GPIe) and the GP externus (GPE) (n = 40). Other common locations included the GPE (n = 24), the GPIe (n = 15), and the lamina between the GPI internal segment (GPIi) and the GPIe (n = 14). In the majority of patients (73%) a monopolar programming configuration was used. At 6 months postsurgery, UPDRS III off medications (OFF) and on stimulation (ON) scores significantly improved (z = -4.02, p < 0.001), as did postsurgery dyskinesia ON scores (z = -4.08, p < 0.001) and postsurgery LEDD (z = -4.7, p < 0.001).

CONCLUSIONS

Though the ventral GP (pallidotomy target) has been a commonly used target for GP DBS, a more dorsolateral target may be more effective for neuromodulation strategies. The assessment of therapeutic contact locations performed in this study showed that the lamina between GPI and GPE used in most patients is the optimal central stimulation target. This information should improve preoperative GP targeting.

Closed-loop direct control of seizure focus in a rodent model of temporal lobe epilepsy via localized electric fields applied sequentially

Direct electrical stimulation of the seizure focus can achieve the early termination of epileptic oscillations. However, direct intervention of the hippocampus, the most prevalent seizure focus in temporal lobe epilepsy is thought to be not practicable due to its large size and elongated shape. Here, in a rat model, we report a sequential narrow-field stimulation method for terminating seizures, while focusing stimulus energy at the spatially extensive hippocampal structure. The effects and regional specificity of this method were demonstrated via electrophysiological and biological responses. Our proposed modality demonstrates spatiotemporal preciseness and selectiveness for modulating the pathological target region which may have potential for further investigation as a therapeutic approach.

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.

Electrochemical and biological performance of hierarchical platinum-iridium electrodes structured by a femtosecond laser

Neural electrode interfaces are essential to the stimulation safety and recording quality of various bioelectronic therapies. The recently proposed hierarchical platinum-iridium (Pt-Ir) electrodes produced by femtosecond lasers have exhibited superior electrochemical performance in vitro, but their in vivo performance is still unclear. In this study, we explored the electrochemical performance, biological response, and tissue adhesion of hierarchical Pt-Ir electrodes by implantation in adult rat brains for 1, 8, and 16 weeks. Regular smooth Pt-Ir electrodes were used as a control. The results showed that the electrochemical performance of both electrodes decreased and leveled off during implantation. However, after 16 weeks, the charge storage capacity of hierarchical electrodes stabilized at ~16.8 mC/cm2, which was 15 times that of the smooth control electrodes (1.1 mC/cm2). Moreover, the highly structured electrodes had lower impedance amplitude and cutoff frequency values. The similar histological response to smooth electrodes indicated good biocompatibility of the hierarchically structured Pt-Ir electrodes. Given their superior in vivo performance, the femtosecond laser-treated Pt-Ir electrode showed great potential for neuromodulation applications.

Impacts of stimulus parameters and configurations on motor cortex direct electrical stimulation using intrinsic optical imaging: a pilot study

Background

Motor cortex stimulation applied as a clinical treatment for neuropathic disorders for decades. With stimulation electrodes placed directly on the cortical surface, this neuromodulation method provides higher spatial resolution than other non-invasive therapies. Yet, the therapeutic effects reported were not in conformity with different syndromes. One of the main issues is that the stimulation parameters are always determined by clinical experience. The lack of understanding about how the stimulation current propagates in the cortex and various stimulation parameters and configurations obstruct the development of this method.

Methods

In this study, we investigated the effect of different stimulation configurations on cortical responses to motor cortical stimulations using intrinsic optical imaging.

Results

Our results showed that the cortical activation of electrical stimulation is not only related to the current density but also related to the propagation distance. Besides, stimulation configurations also affect the propagation of the stimulation current.

Conclusions

All these results provide preliminary experimental evidence for parameter and electrode configuration optimizations.

Microgaskets for High-Channel-Density Reconnectable Implantable Packaging

Demands for implantable bioelectronic devices to increase the number of channels for greater functional capacity and resolution, shrink implant size to minimize tissue response and patient burden, and support battery changes and electronics upgrades for long-term operational viability, cannot be met with existing implant-connector technology. In this paper we describe our novel approach to develop a rematable high-channel-density implant-connector technology, with a focus on the design, fabrication, and characterization of its microgasket. The microgaskets made of polydimethylsiloxane elastomer (PDMSe) have achieved much better electrical isolation for neural stimulation (~5 MΩ at 10 kHz) compared with conventional implant connectors (50 kΩ at 10 kHz), despite a 200-fold increase in channel density (conventional: ~0.0644 ch/mm², microgasket: ~12.8 ch/mm²). The microgaskets also achieved high electrical isolation for neural recording (i.e., ~35 MΩ at 1 kHz) at the same high channel density. When mechanically compressed the microscale vias in the PDMSe microgaskets deform laterally, which could damage or enhance gasket-traversing conductive spring elements in each microscale via depending on their design. We have demonstrated that by lowering the height-to-width aspect ratio of the gasket vias, they can maintain their shape under clamping pressures high enough to achieve high isolation.

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

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

Modulation of Emotion Perception via Amygdala Stimulation in Humans

Background

Multiple lines of evidence show that the human amygdala is part of a neural network important for perception of emotion from environmental stimuli, including for processing of intrinsic attractiveness/“goodness” or averseness/“badness,” i.e., affective valence.

Objective/Hypothesis

With this in mind, we investigated the effect of electrical brain stimulation of the human amygdala on perception of affective valence of images taken from the International Affective Picture Set (IAPS).

Methods

Using intracranial electrodes in patients with epilepsy, we first obtained event-related potentials (ERPs) in eight patients as they viewed IAPS images of varying affective valence. Next, in a further cohort of 10 patients (five female and five male), we measured the effect of 50 Hz electrical stimulation of the left amygdala on perception of affective valence from IAPS images.

Results

We recorded distinct ERPs from the left amygdala and found significant differences in the responses between positively and negatively valenced stimuli (p = 0.002), and between neutral and negatively valenced stimuli (p = 0.017) 300–500 ms after stimulus onset. Next, we found that amygdala stimulation did not significantly affect how patients perceived valence for neutral images (p = 0.58), whereas stimulation induced patients to report both positively (p = 0.05) and negatively (< 0.01) valenced images as more neutral.

Conclusion

These results render further evidence that the left amygdala participates in a neural network for perception of emotion from environmental stimuli. These findings support the idea that electrical stimulation disrupts this network and leads to partial disruption of perception of emotion. Harnessing this effect may have clinical implications in treatment of certain neuropsychiatric disorders using deep brain stimulation (DBS) and neuromodulation.

Non-motor effects of subthalamic nucleus stimulation in Parkinson patients

The current white matter connectivity analyses of the subthalamic region have focused on the motor effects of deep brain stimulation. We investigate white matter connectivity associated with the stimulation-induced non-motor acute clinical effects in three domains: mood changes, dizziness, and sweating. We performed whole-brain probabilistic tractography seeded from the domain-specific stimulation volumes. The resultant connectivity maps were statistically compared across patients. The cortical voxels associated with each non-motor domain were compared with stimulation-induced motor improvements in a multivariate model. The resulting voxel maps were thresholded for false discovery (FDR q < 0.05) and clustered using a multimodal atlas. We also performed a group-level parcellation of stimulation volumes to identify the local pathways associated with each non-motor domain. The non-motor effects were rarely observed during stimulation titration: from 1100 acute clinical effects, mood change was observed in 14, dizziness in 23, and sweating in 20. Distinct cortical clusters were associated with each domain; notably, mood change was associated with voxels in the salience network and dizziness with voxels in the visual association cortex. The subthalamic parcellation yielded a mediolateral gradient, with the motor parcel being lateral and the non-motor parcels medial. We also observed an anteroposterior organization in the medial non-motor clusters with mood changes being anterior, followed posteriorly by dizziness, and sweating. We interpret these findings based on the literature and foresee these to be useful in guiding DBS programming.

MaDoPO: Magnetic Detection of Positions and Orientations of Segmented Deep-Brain Stimulation Electrodes: A Radiation-Free Method Based on Magnetoencephalography

Background: Current approaches to detect the positions and orientations of directional deep-brain stimulation (DBS) electrodes rely on radiative imaging data. In this study, we aim to present an improved version of a radiation-free method for magnetic detection of the position and the orientation (MaDoPO) of directional electrodes based on a series of magnetoencephalography (MEG) measurements and a possible future solution for optimized results using emerging on-scalp MEG systems. Methods: A directional DBS system was positioned into a realistic head–torso phantom and placed in the MEG scanner. A total of 24 measurements of 180 s each were performed with different predefined electrode configurations. Finite element modeling and model fitting were used to determine the position and orientation of the electrode in the phantom. Related measurements were fitted simultaneously, constraining solutions to the a priori known geometry of the electrode. Results were compared with the results of the high-quality CT imaging of the phantom. Results: The accuracy in electrode localization and orientation detection depended on the number of combined measurements. The localization error was minimized to 2.02 mm by considering six measurements with different non-directional bipolar electrode configurations. Another six measurements with directional bipolar stimulations minimized the orientation error to 4°. These values are mainly limited due to the spatial resolution of the MEG. Moreover, accuracies were investigated as a function of measurement time, number of sensors, and measurement direction of the sensors in order to define an optimized MEG device for this application. Conclusion: Although MEG introduces inaccuracies in the detection of the position and orientation of the electrode, these can be accepted when evaluating the benefits of a radiation-free method. Inaccuracies can be further reduced by the use of on-scalp MEG sensor arrays, which may find their way into clinics in the foreseeable future.

Reducing Behavioral Detection Thresholds per Electrode via Synchronous, Spatially-Dependent Intracortical Microstimulation

Intracortical microstimulation (ICMS) has shown promise in restoring quality of life to patients suffering from paralysis, specifically when used in the primary somatosensory cortex (S1). However, these benefits can be hampered by long-term degradation of electrode performance due to the brain's foreign body response. Advances in microfabrication techniques have allowed for the development of neuroprostheses with subcellular electrodes, which are characterized by greater versatility and a less detrimental immune response during chronic use. These probes are hypothesized to enable more selective, higher-resolution stimulation of cortical tissue with long-term implants. However, microstimulation using physiologically relevant charges with these smaller-scale devices can damage electrode sites and reduce the efficacy of the overall device. Studies have shown promise in bypassing this limitation by spreading the stimulation charge between multiple channels in an implanted electrode array, but to our knowledge the usefulness of this strategy in laminar arrays with electrode sites spanning each layer of the cortex remains unexplored. To investigate the efficacy of simultaneous multi-channel ICMS in electrode arrays with stimulation sites spanning cortical depth, we implanted laminar electrode arrays in the primary somatosensory cortex of rats trained in a behavioral avoidance paradigm. By measuring detection thresholds, we were able to quantify improvements in ICMS performance using a simultaneous multi-channel stimulation paradigm. The charge required per site to elicit detection thresholds was halved when stimulating from two adjacent electrode sites, although the overall charge used by the implant was increased. This reduction in threshold charge was more pronounced when stimulating with more than two channels and lessened with greater distance between stimulating channels. Our findings suggest that these improvements are based on the synchronicity and polarity of each stimulus, leading us to conclude that these improvements in stimulation efficiency per electrode are due to charge summation as opposed to a summation of neural responses to stimulation. Additionally, the per-site charge reductions are seen regardless of the cortical depth of each utilized channel. This evocation of physiological detection thresholds with lower stimulation currents per electrode site has implications for the feasibility of stimulation regimes in future advanced neuroprosthetic devices, which could benefit from reducing the charge output per site.

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

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

Experimental deep brain stimulation in rodent models of movement disorders

Deep brain stimulation (DBS) is the preferred treatment for therapy-resistant movement disorders such as dystonia and Parkinson's disease (PD), mostly in advanced disease stages. Although DBS is already in clinical use for ~30 years and has improved patients' quality of life dramatically, there is still limited understanding of the underlying mechanisms of action. Rodent models of PD and dystonia are essential tools to elucidate the mode of action of DBS on behavioral and multiscale neurobiological levels. Advances have been made in identifying DBS effects on the central motor network, neuroprotection and neuroinflammation in DBS studies of PD rodent models. The phenotypic dt^sz mutant hamster and the transgenic DYT-TOR1A (ΔETorA) rat proved as valuable models of dystonia for preclinical DBS research. In addition, continuous refinements of rodent DBS technologies are ongoing and have contributed to improvement of experimental quality. We here review the currently existing literature on experimental DBS in PD and dystonia models regarding the choice of models, experimental design, neurobiological readouts, as well as methodological implications. Moreover, we provide an overview of the technical stage of existing DBS devices for use in rodent studies.

Determining the rotational orientation of directional deep brain stimulation electrodes using magnetoencephalography

Objective.The aim of the present study was to evaluate the effect of different electrode configurations on the accuracy of determining the rotational orientation of the directional deep brain stimulation (DBS) electrode with our previously published magnetoencephalography (MEG)-based method.Approach.A directional DBS electrode, along with its implantable pulse generator, was integrated into a head phantom and placed within the MEG sensor array. Predefined bipolar electrode configurations, based on activation of different directional and omnidirectional contacts of the electrode, were set to generate a defined magnetic field during stimulation. This magnetic field was then measured with MEG. Finite element modeling and model fitting approach were used to calculate electrode orientation.Main results.The accuracy of electrode orientation detection depended on the electrode configuration: the vertical configuration (activation of two directional contacts arranged one above the other) achieved an average accuracy of only about 41 ^∘. The diagonal configuration (activation of the electrode tip and a single directional contact at the next higher level of the electrode) achieved an accuracy of 13^∘, while the horizontal electrode configuration (activation of two adjacent directional contacts at the same electrode level) achieved the best accuracy of 6^∘. The accuracy of orientation detection of the DBS electrode depends on the change in spatial distribution of the magnetic field with the rotation of the electrode along its own axis. In the vertical configuration, rotation of the electrode has a small effect on the magnetic field distribution, while in the diagonal or horizontal configuration, electrode rotation has a significant effect on the magnetic field distribution.Significance.Our work suggests that in order to determine rotational orientation of a DBS electrode using MEG, horizontal configuration should be used as it provides the most accurate results compared to other possible configurations.

Validation of a parameterized, open-source model of nerve stimulation

Peripheral nerve stimulation is an effective treatment for various neurological disorders. The method of activation and stimulation parameters used impact the efficacy of the therapy, which emphasizes the need for tools to model this behavior. Computational modeling of nerve stimulation has proven to be a useful tool for estimating stimulation thresholds, optimizing electrode design, and exploring previously untested stimulation methods. Despite their utility, these tools require access to and familiarity with several pieces of specialized software. A simpler, streamlined process would increase accessibility significantly. We developed an open-source, parameterized model with a simple online user interface that allows user to adjust up to 36 different parameters (https://nervestimlab.utdallas.edu). The model accurately predicts fiber activation thresholds for nerve and electrode combinations reported in literature. Additionally, it replicates characteristic differences between stimulation methods, such as lower thresholds with monopolar stimulation as compared to tripolar stimulation. The model predicted that the difference in threshold between monophasic and biphasic waveforms, a well-characterized phenomenon, is not present during stimulation with bipolar electrodes.In vivotesting on the rat sciatic nerve validated this prediction, which has not been previously reported. The accuracy of the model when compared to previous experiments, as well as the ease of use and accessibility to generate testable hypotheses, indicate that this software may represent a useful tool for a variety of nerve stimulation applications.

How accurately are subthalamic nucleus electrodes implanted relative to the ideal stimulation location for Parkinson's disease?

INTRODUCTION

The efficacy of subthalamic nucleus (STN) deep brain stimulation (DBS) in Parkinson's disease (PD) depends on how closely electrodes are implanted relative to an individual's ideal stimulation location. Yet, previous studies have assessed how closely electrodes are implanted relative to the planned location, after homogenizing data to a reference. Thus here, we measured how accurately electrodes are implanted relative to an ideal, dorsal STN stimulation location, assessed on each individual's native imaging. This measure captures not only the technical error of stereotactic implantation but also constraints imposed by planning a suitable trajectory.

METHODS

This cross-sectional study assessed 226 electrodes in 113 consecutive PD patients implanted with bilateral STN-DBS by experienced clinicians utilizing awake, microelectrode guided, surgery. The error (Euclidean distance) between the actual electrode trajectory versus a nominated ideal, dorsal STN stimulation location was determined in each hemisphere on native imaging and predictive factors sought.

RESULTS

The median electrode location error was 1.62 mm (IQR = 1.23 mm). This error exceeded 3 mm in 28/226 electrodes (12.4%). Location error did not differ between hemispheres implanted first or second, suggesting brain shift was minimised. Location error did not differ between electrodes positioned with (48/226), or without, a preceding microelectrode trajectory shift (suggesting such shifts were beneficial). There was no relationship between location error and case order, arguing against a learning effect.

DISCUSSION/CONCLUSION

The proximity of STN-DBS electrodes to a nominated ideal, dorsal STN, stimulation location is highly variable, even when implanted by experienced clinicians with brain shift minimized, and without evidence of a learning effect. Using this measure, we found that assessments on awake patients (microelectrode recordings and clinical examination) likely yielded beneficial intraoperative decisions to improve positioning. In many patients the error is likely to have reduced therapeutic efficacy. More accurate methods to implant STN-DBS electrodes relative to the ideal stimulation location are needed.

Motor Evoked Potential Recordings During Segmented Deep Brain Stimulation-A Feasibility Study

BACKGROUND

Segmented deep brain stimulation (DBS) leads, which are capable of steering current in the direction of any 1 of 3 segments, can result in a wider therapeutic window by directing current away from unintended structures, particularly, the corticospinal tract (CST). It is unclear whether the use of motor evoked potentials (MEPs) is feasible during DBS surgery via stimulation of individual contacts/segments in order to quantify CST activation thresholds and optimal contacts/segments intraoperatively.

OBJECTIVE

To assess the feasibility of using MEP to identify CST thresholds for ring and individual segments of the DBS lead under general anesthesia.

METHODS

MEP testing was performed during pulse generator implantation under general anesthesia on subjects who underwent DBS lead implantation into the subthalamic nucleus (STN). Stimulation of each ring and segmented contacts of the directional DBS lead was performed until CST threshold was reached. Stereotactic coordinates and thresholds for each contact/segment were recorded along with the initially activated muscle group.

RESULTS

A total of 34 hemispheres were included for analysis. MEP thresholds were recorded from 268 total contacts/segments. For segmented contacts (2 and 3, respectively), the mean highest CST thresholds were 2.33 and 2.62 mA, while the mean lowest CST thresholds were 1.7 and 1.89 mA, suggesting differential thresholds in relation to CST. First dorsal interosseous and abductor pollicis brevis (34% each) were the most commonly activated muscle groups.

CONCLUSION

MEP threshold recording from segmented DBS leads is feasible. MEP recordings can identify segments with highest CST thresholds and may identify segment orientation in relation to CST.

Selective Facial Muscle Activation with Acute and Chronic Multichannel Cuff Electrode Implantation in a Feline Model

OBJECTIVES

Facial paralysis is a debilitating condition with substantial functional and psychological consequences. This feline-model study evaluates whether facial muscles can be selectively activated in acute and chronic implantation of 16-channel multichannel cuff electrodes (MCE).

METHODS

Two cats underwent acute terminal MCE implantation experiments, 2 underwent chronic MCE implantation in uninjured facial nerves (FN) and tested for 6 months, and 2 underwent chronic MCE implantation experiments after FN transection injury and tested for 3 months. The MCE were wrapped around the main trunk of the skeletonized FN, and data collection consisted of EMG thresholds, amplitudes, and selectivity of muscle activation.

RESULTS

In acute experimentation, activation of specific channels (ie, channels 1-3 and 6-8) resulted in selective activation of orbicularis oculi, whereas activation of other channels (ie, channels 4, 5, or 8) led to selective activation of levator auris longus with higher EMG amplitudes. MCE implantation yielded stable and selective facial muscle activation EMG thresholds and amplitudes up to a 5-month period. Modest selective muscle activation was furthermore obtained after a complete transection-reapproximating nerve injury after a 3-month recovery period and implantation reoperation. Chronic implantation of MCE did not lead to fibrosis on histology. Field steering was achieved to activate distinct facial muscles by sending simultaneous subthreshold currents to multiple channels, thus theoretically protecting against nerve damage from chronic electrical stimulation.

CONCLUSION

Our proof-of-concept results show the ability of an MCE, supplemented with field steering, to provide a degree of selective facial muscle stimulation in a feline model, even following nerve regeneration after FN injury.

LEVEL OF EVIDENCE

N/A.

Semi-automated approaches to optimize deep brain stimulation parameters in Parkinson's disease

BACKGROUND

Deep brain stimulation (DBS) is a treatment option for Parkinson's disease patients when medication does not sufficiently manage their symptoms. DBS can be a highly effect therapy, but only after a time-consuming trial-and-error stimulation parameter adjustment process that is susceptible to clinician bias. This trial-and-error process will be further prolonged with the introduction of segmented electrodes that are now commercially available. New approaches to optimizing a patient's stimulation parameters, that can also handle the increasing complexity of new electrode and stimulator designs, is needed.

METHODS

To improve DBS parameter programming, we explored two semi-automated optimization approaches: a Bayesian optimization (BayesOpt) algorithm to efficiently determine a patient's optimal stimulation parameter for minimizing rigidity, and a probit Gaussian process (pGP) to assess patient's preference. Quantified rigidity measurements were obtained using a robotic manipulandum in two participants over two visits. Rigidity was measured, in 5Hz increments, between 10-185Hz (total 30-36 frequencies) on the first visit and at eight BayesOpt algorithm-selected frequencies on the second visit. The participant was also asked their preference between the current and previous stimulation frequency. First, we compared the optimal frequency between visits with the participant's preferred frequency. Next, we evaluated the efficiency of the BayesOpt algorithm, comparing it to random and equal interval selection of frequency.

RESULTS

The BayesOpt algorithm estimated the optimal frequency to be the highest tolerable frequency, matching the optimal frequency found during the first visit. However, the participants' pGP models indicate a preference at frequencies between 70-110 Hz. Here the stimulation frequency is lowest that achieves nearly maximal suppression of rigidity. BayesOpt was efficient, estimating the rigidity response curve to stimulation that was almost indistinguishable when compared to the longer brute force method.

CONCLUSIONS

These results provide preliminary evidence of the feasibility to use BayesOpt for determining the optimal frequency, while pGP patient's preferences include more difficult to measure outcomes. Both novel approaches can shorten DBS programming and can be expanded to include multiple symptoms and parameters.

Impact of brain shift on neural pathways in deep brain stimulation: a preliminary analysis via multi-physics finite element models

OBJECTIVE

The effectiveness of deep brain stimulation (DBS) depends on electrode placement accuracy, which can be compromised by brain shift during surgery. While there have been efforts in assessing the impact of electrode misplacement due to brain shift using preop- and postop- imaging data, such analysis using preop- and intraop- imaging data via biophysical modeling has not been conducted. This work presents a preliminary study that applies a multi-physics analysis framework using finite element biomechanical and bioelectric models to examine the impact of realistic intraoperative shift on neural pathways determined by tractography.

APPROACH

The study examined six patients who had undergone interventional magnetic resonance (iMR)-guided DBS surgery. The modeling framework utilized a biomechanical approach to update preoperative MR to reflect shift-induced anatomical changes. Using this anatomically deformed image and its undeformed counterpart, bioelectric effects from shifting electrode leads could be simulated and neural activation differences were approximated. Specifically, for each configuration, volume of tissue activation (VTA) was computed and subsequently used for tractography estimation. Total tract volume and overlapping volume with motor regions as well as connectivity profile were compared. In addition, volumetric overlap between different fiber bundles among configurations was computed and correlated to estimated shift.

MAIN RESULT

The study found deformation-induced differences in tract volume, motor region overlap, and connectivity behavior, suggesting the impact of shift. There is a strong correlation (R=-0.83) between shift from intended target and intended neural pathway recruitment, where at threshold of ~2.94 mm, intended recruitment completely degrades. The determined threshold is consistent with and provides quantitative support to prior observations and literature that deviations of 2-3 mm are detrimental.

SIGNIFICANCE

The findings support and advance prior studies and understanding to illustrate the need to account for shift in DBS and the potentiality of computational modeling for estimating influence of shift on neural activation.

Long-Lasting Desynchronization of Plastic Neural Networks by Random Reset Stimulation

Excessive neuronal synchrony is a hallmark of neurological disorders such as epilepsy and Parkinson's disease. An established treatment for medically refractory Parkinson's disease is high-frequency (HF) deep brain stimulation (DBS). However, symptoms return shortly after cessation of HF-DBS. Recently developed decoupling stimulation approaches, such as Random Reset (RR) stimulation, specifically target pathological connections to achieve long-lasting desynchronization. During RR stimulation, a temporally and spatially randomized stimulus pattern is administered. However, spatial randomization, as presented so far, may be difficult to realize in a DBS-like setup due to insufficient spatial resolution. Motivated by recently developed segmented DBS electrodes with multiple stimulation sites, we present a RR stimulation protocol that copes with the limited spatial resolution of currently available depth electrodes for DBS. Specifically, spatial randomization is realized by delivering stimuli simultaneously to L randomly selected stimulation sites out of a total of M stimulation sites, which will be called L/M-RR stimulation. We study decoupling by L/M-RR stimulation in networks of excitatory integrate-and-fire neurons with spike-timing dependent plasticity by means of theoretical and computational analysis. We find that L/M-RR stimulation yields parameter-robust decoupling and long-lasting desynchronization. Furthermore, our theory reveals that strong high-frequency stimulation is not suitable for inducing long-lasting desynchronization effects. As a consequence, low and high frequency L/M-RR stimulation affect synaptic weights in qualitatively different ways. Our simulations confirm these predictions and show that qualitative differences between low and high frequency L/M-RR stimulation are present across a wide range of stimulation parameters, rendering stimulation with intermediate frequencies most efficient. Remarkably, we find that L/M-RR stimulation does not rely on a high spatial resolution, characterized by the density of stimulation sites in a target area, corresponding to a large M. In fact, L/M-RR stimulation with low resolution performs even better at low stimulation amplitudes. Our results provide computational evidence that L/M-RR stimulation may present a way to exploit modern segmented lead electrodes for long-lasting therapeutic effects.

DBS electrode localization and rotational orientation detection using SQUID-based magnetoencephalography

The aim of the present study was to investigate the accuracy of localization and rotational orientation detection of a directional deep brain stimulation (DBS) electrode using a state-of-the-art magnetoencephalography (MEG) scanner. A directional DBS electrode along with its stimulator was integrated into a head phantom and placed inside the MEG sensor array. The electrode was comprised of six directional and two omnidirectional contacts. Measurements were performed while stimulating with different contacts and parameters in the phantom. Finite element modeling and fitting approach were used to compute electrode position and orientation. The electrode was localized with a mean accuracy of 2.2 mm while orientation was determined with a mean accuracy of 11°. The limitation in detection accuracy was due to the lower measurement precision of the MEG system. Considering an ideal measurement condition, these values represent the lower bound of accuracy that can be achieved in patients. However, a future magnetic measuring system with higher precision will potentially detect location and orientation of a DBS electrode with an even increased accuracy.

Recruitment of upper-limb motoneurons with epidural electrical stimulation of the cervical spinal cord

Epidural electrical stimulation (EES) of lumbosacral sensorimotor circuits improves leg motor control in animals and humans with spinal cord injury (SCI). Upper-limb motor control involves similar circuits, located in the cervical spinal cord, suggesting that EES could also improve arm and hand movements after quadriplegia. However, the ability of cervical EES to selectively modulate specific upper-limb motor nuclei remains unclear. Here, we combined a computational model of the cervical spinal cord with experiments in macaque monkeys to explore the mechanisms of upper-limb motoneuron recruitment with EES and characterize the selectivity of cervical interfaces. We show that lateral electrodes produce a segmental recruitment of arm motoneurons mediated by the direct activation of sensory afferents, and that muscle responses to EES are modulated during movement. Intraoperative recordings suggested similar properties in humans at rest. These modelling and experimental results can be applied for the development of neurotechnologies designed for the improvement of arm and hand control in humans with quadriplegia.

The efficacy of epidural electrical stimulation (EES) to engage arm muscles and improve movement after spinal cord injury is still unclear. Here, the authors investigated how EES can recruit upper-limb motor neurons by combining computational modelling with experiments in non-human primates.

Subthalamic Nucleus Subregion Stimulation Modulates Inhibitory Control

Patients with Parkinson's disease (PD) often experience reductions in the proficiency to inhibit actions. The motor symptoms of PD can be effectively treated with deep brain stimulation (DBS) of the subthalamic nucleus (STN), a key structure in the frontal-striatal network that may be directly involved in regulating inhibitory control. However, the precise role of the STN in stopping control is unclear. The STN consists of functional subterritories linked to dissociable cortical networks, although the boundaries of the subregions are still under debate. We investigated whether stimulating the dorsal and ventral subregions of the STN would show dissociable effects on ability to stop. We studied 12 PD patients with STN DBS. Patients with two adjacent contacts positioned within the bounds of the dorsal and ventral STN completed two testing sessions (OFF medication) with low amplitude stimulation (0.4 mA) at either the dorsal or ventral contacts bilaterally, while performing the stop task. Ventral, but not dorsal, DBS improved stopping latencies. Go reactions were similar between dorsal and ventral DBS STN. Stimulation in the ventral, but not dorsal, subregion of the STN improved stopping speed, confirming the involvement of the STN in stopping control and supporting the STN functional subregions.

In silico Accuracy and Energy Efficiency of Two Steering Paradigms in Directional Deep Brain Stimulation

Background: In Deep Brain Stimulation (DBS), stimulation field steering is used to achieve stimulation spatial specificity, which is critical to obtain clinical benefits and avoid side effects. Multiple Independent Current Control (MICC) and Interleaving/Multi Stim Set (Interleaving/MSS) are two stimulation field steering paradigms in commercially available DBS systems. This work investigates the stimulation field steering accuracy and energy efficiency of these two paradigms in directional DBS.

Methods: Volumes of Tissue Activated (VTAs) were generated in silico using pulse widths of 60 μs and five pulse amplitude fractionalizations intended to steer the VTAs radially in 12° steps. For each fractionalization, VTAs were generated with nine pre-defined target radii. Stimulation field steering accuracy was assessed based on the VTAs rotation angle. Energy efficiency was inferred from current draw from battery values, which were calculated based on the pulse amplitudes needed to generate and steer the VTAs, as well as electrode impedance measurements of clinically implanted directional leads.

Results: For radial steering, MICC needed a single VTA. In contrast, Interleaving/MSS required the generation of two VTAs, whose union and intersection created an Interleaving/MSS VTA and an Intersection VTA, respectively. MICC VTAs were 6.8 (−3.2–11.8)% larger than Interleaving/MSS VTAs. The Intersection VTAs accounted for 26.2 (16.0–32.8)% of Interleaving/MSS VTAs and were exposed to a higher stimulation frequency. For all VTA radius-fractionalization combinations, steering accuracy was 7.0 (4.5–10.5)° for MICC and 24.0 (9.0–25.3)° for Interleaving/MSS. Pulse amplitudes were 16.1 (9.2–28.6)% lower for MICC than for Interleaving/MSS, leading to a 45.9 (18.8–72.6)% lower current draw from battery for MICC.

Conclusions: The results of this work show that in silico, MICC achieves a significantly better stimulation field steering accuracy and has a significantly higher energy efficiency than Interleaving/MSS. Although direct evidence still needs to be generated to translate the results of this work to clinical practice, clinical outcomes may profit from the better stimulation field steering accuracy of MICC and longevity of DBS systems may profit from its higher energy efficiency.

Computational challenges and opportunities for a bi-directional artificial retina

A future artificial retina that can restore high acuity vision in blind people will rely on the capability to both read (observe) and write (control) the spiking activity of neurons using an adaptive, bi-directional and high-resolution device. Although current research is focused on overcoming the technical challenges of building and implanting such a device, exploiting its capabilities to achieve more acute visual perception will also require substantial computational advances. Using high-density large-scale recording and stimulation in the primate retina with an ex vivo multi-electrode array lab prototype, we frame several of the major computational problems, and describe current progress and future opportunities in solving them. First, we identify cell types and locations from spontaneous activity in the blind retina, and then efficiently estimate their visual response properties by using a low-dimensional manifold of inter-retina variability learned from a large experimental dataset. Second, we estimate retinal responses to a large collection of relevant electrical stimuli by passing current patterns through an electrode array, spike sorting the resulting recordings and using the results to develop a model of evoked responses. Third, we reproduce the desired responses for a given visual target by temporally dithering a diverse collection of electrical stimuli within the integration time of the visual system. Together, these novel approaches may substantially enhance artificial vision in a next-generation device.

Deep brain stimulation: a review of the open neural engineering challenges

OBJECTIVE

Deep brain stimulation (DBS) is an established and valid therapy for a variety of pathological conditions ranging from motor to cognitive disorders. Still, much of the DBS-related mechanism of action is far from being understood, and there are several side effects of DBS whose origin is unclear. In the last years DBS limitations have been tackled by a variety of approaches, including adaptive deep brain stimulation (aDBS), a technique that relies on using chronically implanted electrodes on 'sensing mode' to detect the neural markers of specific motor symptoms and to deliver on-demand or modulate the stimulation parameters accordingly. Here we will review the state of the art of the several approaches to improve DBS and summarize the main challenges toward the development of an effective aDBS therapy.

APPROACH

We discuss models of basal ganglia disorders pathogenesis, hardware and software improvements for conventional DBS, and candidate neural and non-neural features and related control strategies for aDBS.

MAIN RESULTS

We identify then the main operative challenges toward optimal DBS such as (i) accurate target localization, (ii) increased spatial resolution of stimulation, (iii) development of in silico tests for DBS, (iv) identification of specific motor symptoms biomarkers, in particular (v) assessing how LFP oscillations relate to behavioral disfunctions, and (vi) clarify how stimulation affects the cortico-basal-ganglia-thalamic network to (vii) design optimal stimulation patterns.

SIGNIFICANCE

This roadmap will lead neural engineers novel to the field toward the most relevant open issues of DBS, while the in-depth readers might find a careful comparison of advantages and drawbacks of the most recent attempts to improve DBS-related neuromodulatory strategies.

Steering the Volume of Tissue Activated With a Directional Deep Brain Stimulation Lead in the Globus Pallidus Pars Interna: A Modeling Study With Heterogeneous Tissue Properties

Objective: To study the effect of directional deep brain stimulation (DBS) electrode configuration and vertical electrode spacing on the volume of tissue activated (VTA) in the globus pallidus, pars interna (GPi). Background: Directional DBS leads may allow clinicians to precisely direct current fields to different functional networks within traditionally targeted brain areas. Modeling the shape and size of the VTA for various monopolar or bipolar configurations can inform clinical programming strategies for GPi DBS. However, many computational models of VTA are limited by assuming tissue homogeneity. Methods: We generated a multimodal image-based detailed anatomical (MIDA) computational model with a directional DBS lead (1.5 mm or 0.5 mm vertical electrode spacing) placed with segmented contact 2 at the ventral posterolateral "sensorimotor" region of the GPi. The effect of tissue heterogeneity was examined by replacing the MIDA tissues with a homogeneous tissue of conductance 0.3 S/m. DBS pulses (amplitude: 1 mA, pulse width: 60 μs, frequency: 130 Hz) were used to produce VTAs. The following DBS contact configurations were tested: single-segment monopole (2B-/Case+), two-segment monopole (2A-/2B-/Case+ and 2B-/3B-/Case+), ring monopole (2A-/2B-/2C-/Case+), one-cathode three-anode bipole (2B-/3A+/3B+/3C+), three-cathode three-anode bipole (2A-/2B-/2C-/3A+/3B+/3C+). Additionally, certain vertical configurations were repeated with 2 mA current amplitude. Results: Using a heterogeneous tissue model affected both the size and shape of the VTA in GPi. Electrodes with both 0.5 mm and 1.5 mm vertical spacing (1 mA) modeling showed that the single segment monopolar VTA was entirely contained within the GPi when the active electrode is placed at the posterolateral "sensorimotor" GPi. Two segments in a same ring and ring settings, however, produced VTAs outside of the GPi border that spread into adjacent white matter pathways, e.g., optic tract and internal capsule. Both stacked monopolar settings and vertical bipolar settings allowed activation of structures dorsal to the GPi in addition to the GPi. Modeling of the stacked monopolar settings with the DBS lead with 0.5 mm vertical electrode spacing further restricted VTAs within the GPi, but the VTA volumes were smaller compared to the equivalent settings of 1.5 mm spacing.

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.

Update on Current Technologies for Deep Brain Stimulation in Parkinson's Disease

Deep brain stimulation (DBS) is becoming increasingly central in the treatment of patients with Parkinson's disease and other movement disorders. Recent developments in DBS lead and implantable pulse generator design provide increased flexibility for programming, potentially improving the therapeutic benefit of stimulation. Directional DBS leads may increase the therapeutic window of stimulation by providing a means of avoiding current spread to structures that might give rise to stimulation-related side effects. Similarly, control of current to individual contacts on a DBS lead allows for shaping of the electric field produced between multiple active contacts. The following review aims to describe the recent developments in DBS system technology and the features of each commercially available DBS system. The advantages of each system are reviewed, and general considerations for choosing the most appropriate system are discussed.

Modeling of Electric Fields in Individual Imaging Atlas for Capsular Threshold Prediction of Deep Brain Stimulation in Parkinson's Disease: A Pilot Study

Background: Modeling of deep brain stimulation electric fields and anatomy-based software might improve post-operative management of patients with Parkinson's disease (PD) who have benefitted from subthalamic nucleus deep brain stimulation (STN-DBS).

Objective: We compared clinical and software-guided determination of the thresholds for current diffusion to the pyramidal tract, the most frequent limiting side effect in post-operative management of STN-DBS PD patients.

Methods: We assessed monopolar reviews in 16 consecutive STN-DBS PD patients and retrospectively compared clinical capsular thresholds, which had been assessed according to standard clinical practice, to those predicted by volume of tissue activated (VTA) model software. All the modeling steps were performed blinded from patients' clinical evaluations.

Results: At the group level, we found a significant correlation (p = 0.0001) when performing statistical analysis on the z-scored capsular thresholds, but with a low regression coefficient (r = 0.2445). When considering intra-patient analysis, we found significant correlations (p < 0.05) between capsular threshold as modeled with the software and capsular threshold as determined clinically in five patients (31.2%).

Conclusions: In this pilot study, the VTA model software was of limited assistance in identifying capsular thresholds for the whole cohort due to a large inter-patient variability. Clinical testing remains the gold standard in selecting stimulation parameters for STN-DBS in PD.

Short-wave Infrared Neural Stimulation Drives Graded Sciatic Nerve Activation Across A Continuum of Wavelengths

Infrared neural stimulation (INS) is an optical stimulation technique which uses coherent light to stimulate nerves and neurons and which shows increased spatial selectivity compared to electrical stimulation. This could improve deep brain, high channel count, or vagus nerve stimulation. In this study, we seek to understand the wavelength dependence of INS in the near-infrared optical window. Rat sciatic nerves were excised ex vivo and stimulated with wavelengths between 700 and 900 nm. Recorded compound nerve action potentials (CNAPs) showed that stimulation was maximized in the 700 nm window despite comparable laser power levels across wavelengths. Computational models demonstrated that wavelength-based activation dependencies were not a result of passive optical properties. This data demonstrates that INS is both wavelength and power level dependent, which inform stimulation systems to actively target neural microcircuits in humans.

Optical stimulation of neural tissue

Electrical stimulation has been used for decades in devices such as pacemakers, cochlear implants and more recently for deep brain and retinal stimulation and electroceutical treatment of disease. However, current spread from the electrodes limits the precision of neural activation, leading to a low quality therapeutic outcome or undesired side-effects. Alternative methods of neural stimulation such as optical stimulation offer the potential to deliver higher spatial resolution of neural activation. Direct optical stimulation is possible with infrared light, while visible light can be used to activate neurons if the neural tissue is genetically modified with a light sensitive ion channel. Experimentally, both methods have resulted in highly precise stimulation with little spread of activation at least in the cochlea, each with advantages and disadvantages. Infrared neural stimulation does not require modification of the neural tissue, but has very high power requirements. Optogenetics can achieve precision of activation with lower power, but only in conjunction with targeted insertion of a light sensitive ion channel into the nervous system via gene therapy. This review will examine the advantages and limitations of optical stimulation of neural tissue, using the cochlea as an exemplary model and recent developments for retinal and deep brain stimulation.

Electrical Isolation Performance of Microgasket Technology for Implant Packaging

High-channel-count neural interfaces are typically packaged by being permanently bonded to their packaged electronics followed by encapsulation. Such interfaces are often intimately integrated into neural tissue, their removal to replace the battery or upgrade electronics is not undesirable. Gaskets are widely used to provide liquid/electrical isolation and to seal the connection between two or more mating parts. Pressure-driven microgaskets are well established in the field of microfluidics. Although rematable microgaskets for fluidic interconnects exist, the use of microgaskets for electrical isolation have not been demonstrated. Our approach is to electrically isolate 2-D arrays of contact pads using a compressible silicone microgasket. Electrochemical impedance spectroscopy (EIS) was used to quantify the electrical isolation of the microgasket on contact pads, which were formed in a polyimide flex circuit, as a function of frequency after being soaked in saline. Experiments have shown that the compressed sub-millimeter PDMSe microgasket can provide excellent isolation (i.e., >30 MΩ at 1 KHz) that is comparable to the other more conventional packaging methods, such as encapsulation in polydimethylsiloxane elastomer (PDMSe) or parylene-C. Our microgasket-based approach should be scalable to high channel counts and high channel densities enabling much smaller and higher-performance neural implants.

Assessing the effect of current steering on the total electrical energy delivered and ambulation in Parkinson's disease

Vertical current steering (vCS) divides current between multiple contacts, which reduces radial spread to fine-tune the electric field shape and improves neuroanatomical targeting. vCS may improve the variable responsiveness of Parkinsonian gait to conventional deep brain stimulation. We hypothesized that vCS elicits greater improvement in ambulation in Parkinson’s disease patients compared to conventional, single-contact stimulation. vCS was implemented with divisions of 70%/30% and 50%/50% and compared to single-contact stimulation with four therapeutic window amplitudes in current-controlled systems. Walking at a self-selected pace was evaluated in seven levodopa-responsive patients. Integrative measures of gait and stimulation parameters were assessed with the functional ambulation performance (FAP) score and total electrical energy delivered (TEED), respectively. A two-tailed Wilcoxon matched-pairs signed rank test assessed the effect of each stimulation condition on FAP and TEED and compared regression slopes; further, a two-tailed Spearman test identified correlations. vCS significantly lowered the TEED (P < 0.0001); however, FAP scores were not different between conditions (P = 0.786). Compared to single-contact stimulation, vCS elicited higher FAP scores with lower TEED (P = 0.031). FAP and TEED were positively correlated in vCS (P = 2.000 × 10^-5, r = 0.397) and single-contact stimulation (P = 0.034, r = 0.205). Therefore, vCS and single-contact stimulation improved ambulation similarly but vCS reduced the TEED and side-effects at higher amplitudes.

Activation robustness with directional leads and multi-lead configurations in deep brain stimulation

OBJECTIVE

Clinical outcomes from deep brain stimulation (DBS) can be highly variable, and two critical factors underlying this variability are the location and type of stimulation. In this study we quantified how robustly DBS activates a target region when taking into account a range of different lead designs and realistic variations in placement. The objective of the study is to assess the likelihood of achieving target activation.

APPROACH

We performed finite element computational modeling and established a metric of performance robustness to evaluate the ability of directional and multi-lead configurations to activate target fiber pathways while taking into account location variability. A more robust lead configuration produces less variability in activation across all stimulation locations around the target.

MAIN RESULTS

Directional leads demonstrated higher overall performance robustness compared to axisymmetric leads, primarily 1-2 mm outside of the target. Multi-lead configurations demonstrated higher levels of robustness compared to any single lead due to distribution of electrodes in a broader region around the target.

SIGNIFICANCE

Robustness measures can be used to evaluate the performance of existing DBS lead designs and aid in the development of novel lead designs to better accommodate known variability in lead location and orientation. This type of analysis may also be useful to understand how DBS clinical outcome variability is influenced by lead location among groups of patients.

Orientation selective deep brain stimulation of the subthalamic nucleus in rats

Deep brain stimulation (DBS) has become an important tool in the management of a wide spectrum of diseases in neurology and psychiatry. Target selection is a vital aspect of DBS so that only the desired areas are stimulated. Segmented leads and current steering have been shown to be promising additions to DBS technology enabling better control of the stimulating electric field. Recently introduced orientation selective DBS (OS-DBS) is a related development permitting sensitization of the stimulus to axonal pathways with different orientations by freely controlling the primary direction of the electric field using multiple contacts. Here, we used OS-DBS to stimulate the subthalamic nucleus (STN) in healthy rats while simultaneously monitoring the induced brain activity with fMRI. Maximal activation of the sensorimotor and basal ganglia-thalamocortical networks was observed when the electric field was aligned mediolaterally in the STN pointing in the lateral direction, while no cortical activation was observed with the electric field pointing medially to the opposite direction. Such findings are consistent with mediolateral main direction of the STN fibers, as seen with high resolution diffusion imaging and histology. The asymmetry of the OS-DBS dipolar field distribution using three contacts along with the potential stimulation of the internal capsule, are also discussed. We conclude that OS-DBS offers an additional degree of flexibility for optimization of DBS of the STN which may enable a better treatment response.

High resolution transcranial acoustoelectric imaging of current densities from a directional deep brain stimulator

OBJECTIVE

New innovations in deep brain stimulation (DBS) enable directional current steering-allowing more precise electrical stimulation of the targeted brain structures for Parkinson's disease, essential tremor and other neurological disorders. While intra-operative navigation through MRI or CT approaches millimeter accuracy for placing the DBS leads, no existing modality provides feedback of the currents as they spread from the contacts through the brain tissue. In this study, we investigate transcranial acoustoelectric imaging (tAEI) as a new modality to non-invasively image and characterize current produced from a directional DBS lead. tAEI uses ultrasound (US) to modulate tissue resistivity to generate detectable voltage signals proportional to the local currents.

APPROACH

An 8-channel directional DBS lead (Infinity 6172ANS, Abbott Inc) was inserted inside three adult human skulls submerged in 0.9% NaCl. A 2.5 MHz linear array delivered US pulses through the transtemporal window and focused near the contacts on the lead, while a custom amplifier and acquisition system recorded the acoustoelectric (AE) interaction used to generate images.

MAIN RESULTS

tAEI detected monopolar current with stimulation pulses as short as 100 µs with an SNR ranging from 10-27 dB when using safe US pressure (mechanical indices  <0.78) and injected current of ~2 mA peak amplitude. Adjacent contacts were discernable along the length and within each ring of the lead with a mean radial separation between contacts of 2.10 and 1.34 mm, respectively.

SIGNIFICANCE

These results demonstrate the feasibility of tAEI for high resolution mapping of directional DBS currents using clinically-relevant stimulation parameters. This new modality may improve the accuracy for placing the DBS leads, guide calibration and programming, and monitor long-term performance of DBS for treatment of Parkinson's disease.

A review of computational modeling and deep brain stimulation: applications to Parkinson's disease

Biophysical computational models are complementary to experiments and theories, providing powerful tools for the study of neurological diseases. The focus of this review is the dynamic modeling and control strategies of Parkinson's disease (PD). In previous studies, the development of parkinsonian network dynamics modeling has made great progress. Modeling mainly focuses on the cortex-thalamus-basal ganglia (CTBG) circuit and its sub-circuits, which helps to explore the dynamic behavior of the parkinsonian network, such as synchronization. Deep brain stimulation (DBS) is an effective strategy for the treatment of PD. At present, many studies are based on the side effects of the DBS. However, the translation from modeling results to clinical disease mitigation therapy still faces huge challenges. Here, we introduce the progress of DBS improvement. Its specific purpose is to develop novel DBS treatment methods, optimize the treatment effect of DBS for each patient, and focus on the study in closed-loop DBS. Our goal is to review the inspiration and insights gained by combining the system theory with these computational models to analyze neurodynamics and optimize DBS treatment.