Multi-objective particle swarm optimization for postoperative deep brain stimulation targeting of subthalamic nucleus pathways

Closing the loop in psychiatric deep brain stimulation: physiology, psychometrics, and plasticity

Deep brain stimulation (DBS) is an invasive approach to precise modulation of psychiatrically relevant circuits. Although it has impressive results in open-label psychiatric trials, DBS has also struggled to scale to and pass through multi-center randomized trials. This contrasts with Parkinson disease, where DBS is an established therapy treating thousands of patients annually. The core difference between these clinical applications is the difficulty of proving target engagement, and of leveraging the wide range of possible settings (parameters) that can be programmed in a given patient's DBS. In Parkinson's, patients' symptoms change rapidly and visibly when the stimulator is tuned to the correct parameters. In psychiatry, those same changes take days to weeks, limiting a clinician's ability to explore parameter space and identify patient-specific optimal settings. I review new approaches to psychiatric target engagement, with an emphasis on major depressive disorder (MDD). Specifically, I argue that better engagement may come by focusing on the root causes of psychiatric illness: dysfunction in specific, measurable cognitive functions and in the connectivity and synchrony of distributed brain circuits. I overview recent progress in both those domains, and how it may relate to other technologies discussed in companion articles in this issue.

Interactive mobile application for Parkinson's disease deep brain stimulation (MAP DBS): An open-label, multicenter, randomized, controlled clinical trial

INTRODUCTION

Deep brain stimulation (DBS) is an effective treatment for Parkinson's disease (PD), but its efficacy is tied to DBS programming, which is often time consuming and burdensome for patients, caregivers, and clinicians. Our aim is to test whether the Mobile Application for PD DBS (MAP DBS), a clinical decision support system, can improve programming.

METHODS

We conducted an open-label, 1:1 randomized, controlled, multicenter clinical trial comparing six months of SOC standard of care (SOC) to six months of MAP DBS-aided programming. We enrolled patients between 30 and 80 years old who received DBS to treat idiopathic PD at six expert centers across the United States. The primary outcome was time spent DBS programming and secondary outcomes measured changes in motor symptoms, caregiver strain and medication requirements.

RESULTS

We found a significant reduction in initial visit time (SOC: 43.8 ± 28.9 min n = 37, MAP DBS: 27.4 ± 13.0 min n = 35, p = 0.001). We did not find a significant difference in total programming time between the groups over the 6-month study duration. MAP DBS-aided patients experienced a significantly larger reduction in UPDRS III on-medication scores (-7.0 ± 7.9) compared to SOC (-2.7 ± 6.9, p = 0.01) at six months.

CONCLUSION

MAP DBS was well tolerated and improves key aspects of DBS programming time and clinical efficacy.

Lateral cerebellothalamic tract activation underlies DBS therapy for Essential Tremor

BACKGROUND

While deep brain stimulation (DBS) therapy can be effective at suppressing tremor in individuals with medication-refractory Essential Tremor, patient outcome variability remains a significant challenge across centers. Proximity of active electrodes to the cerebellothalamic tract (CTT) is likely important in suppressing tremor, but how tremor control and side effects relate to targeting parcellations within the CTT and other pathways in and around the ventral intermediate (VIM) nucleus of thalamus remain unclear.

METHODS

Using ultra-high field (7T) MRI, we developed high-dimensional, subject-specific pathway activation models for 23 directional DBS leads. Modeled pathway activations were compared with post-hoc analysis of clinician-optimized DBS settings, paresthesia thresholds, and dysarthria thresholds. Mixed-effect models were utilized to determine how the six parcellated regions of the CTT and how six other pathways in and around the VIM contributed to tremor suppression and induction of side effects.

RESULTS

The lateral portion of the CTT had the highest activation at clinical settings (p < 0.05) and a significant effect on tremor suppression (p < 0.001). Activation of the medial lemniscus and posterior-medial CTT was significantly associated with severity of paresthesias (p < 0.001). Activation of the anterior-medial CTT had a significant association with dysarthria (p < 0.05).

CONCLUSIONS

This study provides a detailed understanding of the fiber pathways responsible for therapy and side effects of DBS for Essential Tremor, and suggests a model-based programming approach will enable more selective activation of lateral fibers within the CTT.

Programming of subthalamic nucleus deep brain stimulation for Parkinson's disease with sweet spot-guided parameter suggestions

Deep Brain Stimulation (DBS) is an effective treatment for advanced Parkinson's disease. However, identifying stimulation parameters, such as contact and current amplitudes, is time-consuming based on trial and error. Directional leads add more stimulation options and render this process more challenging with a higher workload for neurologists and more discomfort for patients. In this study, a sweet spot-guided algorithm was developed that automatically suggested stimulation parameters. These suggestions were retrospectively compared to clinical monopolar reviews. A cohort of 24 Parkinson's disease patients underwent bilateral DBS implantation in the subthalamic nucleus at our center. First, the DBS' leads were reconstructed with the open-source toolbox Lead-DBS. Second, a sweet spot for rigidity reduction was set as the desired stimulation target for programming. This sweet spot and estimations of the volume of tissue activated were used to suggest (i) the best lead level, (ii) the best contact, and (iii) the effect thresholds for full therapeutic effect for each contact. To assess these sweet spot-guided suggestions, the clinical monopolar reviews were considered as ground truth. In addition, the sweet spot-guided suggestions for best lead level and best contact were compared against reconstruction-guided suggestions, which considered the lead location with respect to the subthalamic nucleus. Finally, a graphical user interface was developed as an add-on to Lead-DBS and is publicly available. With the interface, suggestions for all contacts of a lead can be generated in a few seconds. The accuracy for suggesting the best out of four lead levels was 56%. These sweet spot-guided suggestions were not significantly better than reconstruction-guided suggestions (p = 0.3). The accuracy for suggesting the best out of eight contacts was 41%. These sweet spot-guided suggestions were significantly better than reconstruction-guided suggestions (p < 0.001). The sweet spot-guided suggestions of each contact's effect threshold had a mean error of 1.2 mA. On an individual lead level, the suggestions can vary more with mean errors ranging from 0.3 to 4.8 mA. Further analysis is warranted to improve the sweet spot-guided suggestions and to account for more symptoms and stimulation-induced side effects.

Patient-specific connectomic models correlate with, but do not reliably predict, outcomes in deep brain stimulation for obsessive-compulsive disorder

Deep brain stimulation (DBS) of the ventral internal capsule/ventral striatum (VCVS) is an emerging treatment for obsessive-compulsive disorder (OCD). Recently, multiple studies using normative connectomes have correlated DBS outcomes to stimulation of specific white matter tracts. Those studies did not test whether these correlations are clinically predictive, and did not apply cross-validation approaches that are necessary for biomarker development. Further, they did not account for the possibility of systematic differences between DBS patients and the non-diagnosed controls used in normative connectomes. To address these gaps, we performed patient-specific diffusion imaging in 8 patients who underwent VCVS DBS for OCD. We delineated tracts connecting thalamus and subthalamic nucleus (STN) to prefrontal cortex via VCVS. We then calculated which tracts were likely activated by individual patients' DBS settings. We fit multiple statistical models to predict both OCD and depression outcomes from tract activation. We further attempted to predict hypomania, a VCVS DBS complication. We assessed all models' performance on held-out test sets. With this best-practices approach, no model predicted OCD response, depression response, or hypomania above chance. Coefficient inspection partly supported prior reports, in that capture of tracts projecting to cingulate cortex was associated with both YBOCS and MADRS response. In contrast to prior reports, however, tracts connected to STN were not reliably correlated with response. Thus, patient-specific imaging and a guideline-adherent analysis were unable to identify a tractographic target with sufficient effect size to drive clinical decision-making or predict individual outcomes. These findings suggest caution in interpreting the results of normative connectome studies.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Home Health Management of Parkinson Disease Deep Brain Stimulation: A Randomized Clinical Trial

Importance

The travel required to receive deep brain stimulation (DBS) programming causes substantial burden on patients and limits who can access DBS therapy.

Objective

To evaluate the efficacy of home health DBS postoperative management in an effort to reduce travel burden and improve access.

Design, Settings, and Participants

This open-label randomized clinical trial was conducted at University of Florida Health from November 2017 to April 2020. Eligible participants had a diagnosis of Parkinson disease (PD) and were scheduled to receive DBS independently of the study. Consenting participants were randomized 1:1 to receive either standard of care or home health postoperative DBS management for 6 months after surgery. Primary caregivers, usually spouses, were also enrolled to assess caregiver strain.

Interventions

The home health postoperative management was conducted by a home health nurse who chose DBS settings with the aid of the iPad-based Mobile Application for PD DBS system. Prior to the study, the home health nurse had no experience providing DBS care.

Main Outcomes and Measures

The primary outcome was the number of times each patient traveled to the movement disorders clinic during the study period. Secondary outcomes included changes from baseline on the Unified Parkinson's Disease Rating Scale part III.

Results

Approximately 75 patients per year were scheduled for DBS. Of the patients who met inclusion criteria over the entire study duration, 45 either declined or were excluded for various reasons. Of the 44 patients enrolled, 19 of 21 randomized patients receiving the standard of care (mean [SD] age, 64.1 [10.0] years; 11 men) and 23 of 23 randomized patients receiving home health who underwent a minimum of 1 postoperative management visit (mean [SD] age, 65.0 [10.9] years; 13 men) were included in analysis. The primary outcome revealed that patients randomized to home health had significantly fewer clinic visits than the patients in the standard of care arm (mean [SD], 0.4 [0.8] visits vs 4.8 [0.4] visits; P < .001). We found no significant differences between the groups in the secondary outcomes measuring the efficacy of DBS. No adverse events occurred in association with the study procedure or devices.

Conclusions and Relevance

This study provides evidence supporting the safety and feasibility of postoperative home health DBS management.

Trial Registration

ClinicalTrials.gov Identifier: NCT02474459.

Multi-objective data-driven optimization for improving deep brain stimulation in Parkinson's disease

Objective.Deep brain stimulation (DBS) is an effective treatment for Parkinson's disease (PD) but its success depends on a time-consuming process of trial-and-error to identify the optimal stimulation settings for each individual patient. Data-driven optimization algorithms have been proposed to efficiently find the stimulation setting that maximizes a quantitative biomarker of symptom relief. However, these algorithms cannot efficiently take into account stimulation settings that may control symptoms but also cause side effects. Here we demonstrate how multi-objective data-driven optimization can be used to find the optimal trade-off between maximizing symptom relief and minimizing side effects.Approach.Cortical and motor evoked potential data collected from PD patients during intraoperative stimulation of the subthalamic nucleus were used to construct a framework for designing and prototyping data-driven multi-objective optimization algorithms. Using this framework, we explored how these techniques can be applied clinically, and characterized the design features critical for solving this optimization problem. Our two optimization objectives were to maximize cortical evoked potentials, a putative biomarker of therapeutic benefit, and to minimize motor potentials, a biomarker of motor side effects.Main Results.Using thisin silicodesign framework, we demonstrated how the optimal trade-off between two objectives can substantially reduce the stimulation parameter space by 61 ± 19%. The best algorithm for identifying the optimal trade-off between the two objectives was a Bayesian optimization approach with an area under the receiver operating characteristic curve of up to 0.94 ± 0.02, which was possible with the use of a surrogate model and a well-tuned acquisition function to efficiently select which stimulation settings to sample.Significance.These findings show that multi-objective optimization is a promising approach for identifying the optimal trade-off between symptom relief and side effects in DBS. Moreover, these approaches can be readily extended to newly discovered biomarkers, adapted to DBS for disorders beyond PD, and can scale with the development of more complex DBS devices.

Proceedings of the Eighth Annual Deep Brain Stimulation Think Tank: Advances in Optogenetics, Ethical Issues Affecting DBS Research, Neuromodulatory Approaches for Depression, Adaptive Neurostimulation, and Emerging DBS Technologies

We estimate that 208,000 deep brain stimulation (DBS) devices have been implanted to address neurological and neuropsychiatric disorders worldwide. DBS Think Tank presenters pooled data and determined that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. The DBS Think Tank was founded in 2012 providing a space where clinicians, engineers, researchers from industry and academia discuss current and emerging DBS technologies and logistical and ethical issues facing the field. The emphasis is on cutting edge research and collaboration aimed to advance the DBS field. The Eighth Annual DBS Think Tank was held virtually on September 1 and 2, 2020 (Zoom Video Communications) due to restrictions related to the COVID-19 pandemic. The meeting focused on advances in: (1) optogenetics as a tool for comprehending neurobiology of diseases and on optogenetically-inspired DBS, (2) cutting edge of emerging DBS technologies, (3) ethical issues affecting DBS research and access to care, (4) neuromodulatory approaches for depression, (5) advancing novel hardware, software and imaging methodologies, (6) use of neurophysiological signals in adaptive neurostimulation, and (7) use of more advanced technologies to improve DBS clinical outcomes. There were 178 attendees who participated in a DBS Think Tank survey, which revealed the expansion of DBS into several indications such as obesity, post-traumatic stress disorder, addiction and Alzheimer’s disease. This proceedings summarizes the advances discussed at the Eighth Annual DBS Think Tank.

Directional Stimulation in Parkinson's Disease and Essential Tremor: The Cleveland Clinic Experience

OBJECTIVE

To assess use of directional stimulation in Parkinson's disease and essential tremor patients programmed in routine clinical care.

MATERIALS AND METHODS

Patients with Parkinson's disease or essential tremor implanted at Cleveland Clinic with a directional deep brain stimulation (DBS) system from November 2017 to October 2019 were included in this retrospective case series. Omnidirectional was compared against directional stimulation using therapeutic current strength, therapeutic window percentage, and total electrical energy delivered as outcome variables.

RESULTS

Fifty-seven Parkinson's disease patients (36 males) were implanted in the subthalamic nucleus (105 leads) and 33 essential tremor patients (19 males) were implanted in the ventral intermediate nucleus of the thalamus (52 leads). Seventy-four percent of patients with subthalamic stimulation (65% of leads) and 79% of patients with thalamic stimulation (79% of leads) were programmed with directional stimulation for their stable settings. Forty-six percent of subthalamic leads and 69% of thalamic leads were programmed on single segment activation. There was no correlation between the length of microelectrode trajectory through the STN and use of directional stimulation.

CONCLUSIONS

Directional programming was more common than omnidirectional programming. Substantial gains in therapeutic current strength, therapeutic window, and total electrical energy were found in subthalamic and thalamic leads programmed on directional stimulation.

7T MRI and Computational Modeling Supports a Critical Role of Lead Location in Determining Outcomes for Deep Brain Stimulation: A Case Report

Subthalamic nucleus (STN) deep brain stimulation (DBS) is an established therapy for Parkinson’s disease motor symptoms. The ideal site for implantation within STN, however, remains controversial. While many argue that placement of a DBS lead within the sensorimotor territory of the STN yields better motor outcomes, others report similar effects with leads placed in the associative or motor territory of the STN, while still others assert that placing a DBS lead “anywhere within a 6-mm-diameter cylinder centered at the presumed middle of the STN (based on stereotactic atlas coordinates) produces similar clinical efficacy.” These discrepancies likely result from methodological differences including targeting preferences, imaging acquisition and the use of brain atlases that do not account for patient-specific anatomic variability. We present a first-in-kind within-patient demonstration of severe mood side effects and minimal motor improvement in a Parkinson’s disease patient following placement of a DBS lead in the limbic/associative territory of the STN who experienced marked improvement in motor benefit and resolution of mood side effects following repositioning the lead within the STN sensorimotor territory. 7 Tesla (7 T) magnetic resonance imaging (MRI) data were used to generate a patient-specific anatomical model of the STN with parcellation into distinct functional territories and computational modeling to assess the relative degree of activation of motor, associative and limbic territories.

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.

Kilohertz waveforms optimized to produce closed-state Na+ channel inactivation eliminate onset response in nerve conduction block

The delivery of kilohertz frequency alternating current (KHFAC) generates rapid, controlled, and reversible conduction block in motor, sensory, and autonomic nerves, but causes transient activation of action potentials at the onset of the blocking current. We implemented a novel engineering optimization approach to design blocking waveforms that eliminated the onset response by moving voltage-gated Na⁺ channels (VGSCs) to closed-state inactivation (CSI) without first opening. We used computational models and particle swarm optimization (PSO) to design a charge-balanced 10 kHz biphasic current waveform that produced conduction block without onset firing in peripheral axons at specific locations and with specific diameters. The results indicate that it is possible to achieve onset-free KHFAC nerve block by causing CSI of VGSCs. Our novel approach for designing blocking waveforms and the resulting waveform may have utility in clinical applications of conduction block of peripheral nerve hyperactivity, for example in pain and spasticity.

Many neurological disorders, including pain and spasticity, are characterized by undesirable increases in sensory, motor, or autonomic nerve activity. Local application of kilohertz frequency alternating currents (KHFAC) can effectively and completely block the conduction of undesired hyperactivity through peripheral nerves and could be a therapeutic approach for alleviating disease symptoms. However, KHFAC nerve block produces an undesirable initial burst of action potentials prior to achieving block. This onset firing may result in muscle contraction and pain and is a significant impediment to potential clinical applications of KHFAC nerve block. We present a novel engineering optimization approach for designing a blocking waveform that completely eliminated the onset firing in peripheral axons by moving voltage-gated Na⁺ channels to closed-state inactivation. Our results suggest that the resulting KHFAC waveform can generate electric nerve block without an onset response. Our approach for optimizing blocking waveforms represents a novel engineering design methodology with myriad potential applications and has relevance for the conduction block of peripheral nerve hyperactivity.

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.

Evaluation of methodologies for computing the deep brain stimulation volume of tissue activated

Objective.

Computational models are a popular tool for predicting the effects of deep brain stimulation (DBS) on neural tissue. One commonly used model, the volume of tissue activated (VTA), is computed using multiple methodologies. We quantified differences in the VTAs generated by five methodologies: the traditional axon model method, the electric field norm, and three activating function based approaches—the activating function at each grid point in the tangential direction (AF-Tan) or in the maximally activating direction (AF-3D), and the maximum activating function along the entire length of a tangential fiber (AF-Max).

Approach.

We computed the VTA using each method across multiple stimulation settings. The resulting volumes were compared for similarity, and the methodologies were analyzed for their differences in behavior.

Main results.

Activation threshold values for both the electric field norm and the activating function varied with regards to electrode configuration, pulse width, and frequency. All methods produced highly similar volumes for monopolar stimulation. For bipolar electrode configurations, only the maximum activating function along the tangential axon method, AF-Max, produced similar volumes to those produced by the axon model method. Further analysis revealed that both of these methods are biased by their exclusive use of tangential fiber orientations. In contrast, the activating function in the maximally activating direction method, AF-3D, produces a VTA that is free of axon orientation and projection bias.

Significance.

Simulating tangentially oriented axons, the standard approach of computing the VTA, is too computationally expensive for widespread implementation and yields results biased by the assumption of tangential fiber orientation. In this work, we show that a computationally efficient method based on the activating function, AF-Max, reliably reproduces the VTAs generated by direct axon modeling. Further, we propose another method, AF-3D as a potentially superior model for representing generic neural tissue activation.

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.

Direct Electrical Stimulation in Electrocorticographic Brain-Computer Interfaces: Enabling Technologies for Input to Cortex

Electrocorticographic brain computer interfaces (ECoG-BCIs) offer tremendous opportunities for restoring function in individuals suffering from neurological damage and for advancing basic neuroscience knowledge. ECoG electrodes are already commonly used clinically for monitoring epilepsy and have greater spatial specificity in recording neuronal activity than techniques such as electroencephalography (EEG). Much work to date in the field has focused on using ECoG signals recorded from cortex as control outputs for driving end effectors. An equally important but less explored application of an ECoG-BCI is directing input into cortex using ECoG electrodes for direct electrical stimulation (DES). Combining DES with ECoG recording enables a truly bidirectional BCI, where information is both read from and written to the brain. We discuss the advantages and opportunities, as well as the barriers and challenges presented by using DES in an ECoG-BCI. In this article, we review ECoG electrodes, the physics and physiology of DES, and the use of electrical stimulation of the brain for the clinical treatment of disorders such as epilepsy and Parkinson’s disease. We briefly discuss some of the translational, regulatory, financial, and ethical concerns regarding ECoG-BCIs. Next, we describe the use of ECoG-based DES for providing sensory feedback and for probing and modifying cortical connectivity. We explore future directions, which may draw on invasive animal studies with penetrating and surface electrodes as well as non-invasive stimulation methods such as transcranial magnetic stimulation (TMS). We conclude by describing enabling technologies, such as smaller ECoG electrodes for more precise targeting of cortical areas, signal processing strategies for simultaneous stimulation and recording, and computational modeling and algorithms for tailoring stimulation to each individual brain.

Analysis of patient-specific stimulation with segmented leads in the subthalamic nucleus

Objective

Segmented deep brain stimulation leads in the subthalamic nucleus have shown to increase therapeutic window using directional stimulation. However, it is not fully understood how these segmented leads with reduced electrode size modify the volume of tissue activated (VTA) and how this in turn relates with clinically observed therapeutic and side effect currents. Here, we investigated the differences between directional and omnidirectional stimulation and associated VTAs with patient-specific therapeutic and side effect currents for the two stimulation modes.

Approach

Nine patients with Parkinson’s disease underwent DBS implantation in the subthalamic nucleus. Therapeutic and side effect currents were identified intraoperatively with a segmented lead using directional and omnidirectional stimulation (these current thresholds were assessed in a blinded fashion). The electric field around the lead was simulated with a finite-element model for a range of stimulation currents for both stimulation modes. VTAs were estimated from the electric field by numerical differentiation and thresholding. Then for each patient, the VTAs for given therapeutic and side effect currents were projected onto the patient-specific subthalamic nucleus and lead position.

Results

Stimulation with segmented leads with reduced electrode size was associated with a significant reduction of VTA and a significant increase of radial distance in the best direction of stimulation. While beneficial effects were associated with activation volumes confined within the anatomical boundaries of the subthalamic nucleus at therapeutic currents, side effects were associated with activation volumes spreading beyond the nucleus’ boundaries.

Significance

The clinical benefits of segmented leads are likely to be obtained by a VTA confined within the subthalamic nucleus and a larger radial distance in the best stimulation direction, while steering the VTA away from unwanted fiber tracts outside the nucleus. Applying the same concepts at a larger scale and in chronically implanted patients may help to predict the best stimulation area.