Dissecting deep brain stimulation evoked neural activity in the basal ganglia

Deep brain stimulation (DBS) is an established therapeutic tool for the treatment of Parkinson's disease (PD). The mechanisms of DBS for PD are likely rooted in modulation of the subthalamo-pallidal network. However, it can be difficult to electrophysiologically interrogate that network in human patients. The recent identification of large amplitude evoked potential (EP) oscillations from DBS in the subthalamic nucleus (STN) or globus pallidus internus (GPi) are providing new scientific opportunities to expand understanding of human basal ganglia network activity. In turn, the goal of this review is to provide a summary of DBS-induced EPs in the basal ganglia and attempt to explain various components of the EP waveforms from their likely network origins. Our analyses suggest that DBS-induced antidromic activation of globus pallidus externus (GPe) is a key driver of these oscillatory EPs, independent of stimulation location (i.e. STN or GPi). This suggests a potentially more important role for GPe in the mechanisms of DBS for PD than typically assumed. And from a practical perspective, DBS EPs are poised to become clinically useful electrophysiological biomarker signals for verification of DBS target engagement.

Subcallosal cingulate deep brain stimulation evokes two distinct cortical responses via differential white matter activation

Subcallosal cingulate (SCC) deep brain stimulation (DBS) is an emerging therapy for refractory depression. Good clinical outcomes are associated with the activation of white matter adjacent to the SCC. This activation produces a signature cortical evoked potential (EP), but it is unclear which of the many pathways in the vicinity of SCC is responsible for driving this response. Individualized biophysical models were built to achieve selective engagement of two target bundles: either the forceps minor (FM) or cingulum bundle (CB). Unilateral 2 Hz stimulation was performed in seven patients with treatment-resistant depression who responded to SCC DBS, and EPs were recorded using 256-sensor scalp electroencephalography. Two distinct EPs were observed: a 120 ms symmetric response spanning both hemispheres and a 60 ms asymmetrical EP. Activation of FM correlated with the symmetrical EPs, while activation of CB was correlated with the asymmetrical EPs. These results support prior model predictions that these two pathways are predominantly activated by clinical SCC DBS and provide first evidence of a link between cortical EPs and selective fiber bundle activation.

Model-Based Analysis of Pathway Recruitment During Subthalamic Deep Brain Stimulation

BACKGROUND

Subthalamic deep brain stimulation (DBS) is an established clinical therapy, but an anatomically clear definition of the underlying neural target(s) of the stimulation remains elusive. Patient-specific models of DBS are commonly used tools in the search for stimulation targets, and recent iterations of those models are focused on characterizing the brain connections that are activated by DBS.

OBJECTIVE

The goal of this study was to quantify axonal pathway activation in the subthalamic region from DBS at different electrode locations and stimulation settings.

MATERIALS AND METHODS

We used an anatomically and electrically detailed computational model of subthalamic DBS to generate recruitment curves for eight different axonal pathways of interest, at three generalized DBS electrode locations in the subthalamic nucleus (STN) (ie, central STN, dorsal STN, posterior STN). These simulations were performed with three levels of DBS electrode localization uncertainty (ie, 0.5 mm, 1.0 mm, 1.5 mm).

RESULTS

The recruitment curves highlight the diversity of pathways that are theoretically activated with subthalamic DBS, in addition to the dependence of the stimulation location and parameter settings on the pathway activation estimates. The three generalized DBS locations exhibited distinct pathway recruitment curve profiles, suggesting that each stimulation location would have a different effect on network activity patterns. We also found that the use of anodic stimuli could help limit activation of the internal capsule relative to other pathways. However, incorporating realistic levels of DBS electrode localization uncertainty in the models substantially limits their predictive capabilities.

CONCLUSIONS

Subtle differences in stimulation location and/or parameter settings can impact the collection of pathways that are activated during subthalamic DBS.

Does Vestibular Motion Perception Correlate with Axonal Pathways Stimulated by Subthalamic Deep Brain Stimulation in Parkinson's Disease?

Perception of our linear motion - heading - is critical for postural control, gait, and locomotion, and it is impaired in Parkinson's disease (PD). Deep brain stimulation (DBS) has variable effects on vestibular heading perception, depending on the location of the electrodes within the subthalamic nucleus (STN). Here, we aimed to find the anatomical correlates of heading perception in PD. Fourteen PD participants with bilateral STN DBS performed a two-alternative forced-choice discrimination task where a motion platform delivered translational forward movements with a heading angle varying between 0 and 30° to the left or to the right with respect to the straight-ahead direction. Using psychometric curves, we derived the heading discrimination threshold angle of each patient from the response data. We created patient-specific DBS models and calculated the percentages of stimulated axonal pathways that are anatomically adjacent to the STN and known to play a major role in vestibular information processing. We performed correlation analyses to investigate the extent of these white matter tracts' involvement in heading perception. Significant positive correlations were identified between improved heading discrimination for rightward heading and the percentage of activated streamlines of the contralateral hyperdirect, pallido-subthalamic, and subthalamo-pallidal pathways. The hyperdirect pathways are thought to provide top-down control over STN connections to the cerebellum. In addition, STN may also antidromically activate collaterals of hyperdirect pathway that projects to the precerebellar pontine nuclei. In select cases, there was strong activation of the cerebello-thalamic projections, but it was not consistently present in all participants. Large volumetric overlap between the volume of tissue activation and the STN in the left hemisphere positively impacted rightward heading perception. Altogether, the results suggest heavy involvement of basal ganglia cerebellar network in STN-induced modulation of vestibular heading perception in PD.

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.

Coupled Activation of the Hyperdirect and Cerebellothalamic Pathways with Zona Incerta Deep Brain Stimulation

BACKGROUND

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) or ventral intermediate nucleus (VIM) are established targets for the treatment of Parkinson's disease (PD) or essential tremor (ET), respectively. However, DBS of the zona incerta (ZI) can be effective for both disorders. VIM DBS is assumed to achieve its therapeutic effect via activation of the cerebellothalamic (CBT) pathway, whereas the activation of the hyperdirect (HD) pathway likely plays a role in the mechanisms of STN DBS. Interestingly, HD pathway axons also emit collaterals to the ZI and red nucleus (RN) and the CBT pathway courses nearby to the ZI.

OBJECTIVE

The aim was to examine the ability of ZI DBS to mutually activate the HD and CBT pathways in a detailed computational model of human DBS.

METHODS

We extended a previous model of the human HD pathway to incorporate axon collaterals to the ZI and RN. The anatomical framework of the model system also included representations of the CBT pathway and internal capsule (IC) fibers of passage. We then performed detailed biophysical simulations to quantify DBS activation of the HD, CBT, and IC pathways with electrodes located in either the STN or ZI.

RESULTS

STN DBS and ZI DBS both robustly activated the HD pathway. However, STN DBS was limited by IC activation at higher stimulus amplitudes. Alternatively, ZI DBS avoided IC activation while simultaneously activating the HD and CBT pathways.

CONCLUSIONS

From both neuroanatomical and biophysical perspectives, ZI DBS represents an advantageous target for coupled activation of the HD and CBT pathways. © 2024 International Parkinson and Movement Disorder Society.

Proceedings of the 11th Annual Deep Brain Stimulation Think Tank: pushing the forefront of neuromodulation with functional network mapping, biomarkers for adaptive DBS, bioethical dilemmas, AI-guided neuromodulation, and translational advancements

The Deep Brain Stimulation (DBS) Think Tank XI was held on August 9-11, 2023 in Gainesville, Florida with the theme of "Pushing the Forefront of Neuromodulation". The keynote speaker was Dr. Nico Dosenbach from Washington University in St. Louis, Missouri. He presented his research recently published in Nature inn a collaboration with Dr. Evan Gordon to identify and characterize the somato-cognitive action network (SCAN), which has redefined the motor homunculus and has led to new hypotheses about the integrative networks underpinning therapeutic DBS. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers, and researchers (from industry and academia) can freely discuss current and emerging DBS technologies, as well as logistical and ethical issues facing the field. The group estimated that globally more than 263,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: cutting-edge translational neuromodulation, cutting-edge physiology, advances in neuromodulation from Europe and Asia, neuroethical dilemmas, artificial intelligence and computational modeling, time scales in DBS for mood disorders, and advances in future neuromodulation devices.

Estimations of Charge Deposition Onto Convoluted Axon Surfaces Within Extracellular Electric Fields

OBJECTIVE

Biophysical models of neural stimulation are a valuable approach to explaining the mechanisms of neuronal recruitment via applied extracellular electric fields. Typically, the applied electric field is estimated via a macroscopic finite element method solution and then applied to cable models as an extracellular voltage source. However, the field resolution is limited by the finite element size (typically 10's-100's of times greater than average neuronal cross-section). As a result, induced charges deposited onto anatomically realistic curved membrane interfaces are not taken into consideration. However, these details may alter estimates of the applied electric field and predictions of neural tissue activation.

METHODS

To estimate microscopic variations of the electric field, data for intra-axonal space segmented from 3D scanning electron microscopy of the mouse brain genu of corpus callosum were used. The boundary element fast multipole method was applied to accurately compute the extracellular solution. Neuronal recruitment was then estimated via an activating function.

RESULTS

Taking the physical structure of the arbor into account generally predicts higher values of the activating function. The relative integral 2-norm difference is 90% on average when the entire axonal arbor is present. A large fraction of this difference might be due to the axonal body itself. When an isolated physical axon is considered with all other axons removed, the relative integral 2-norm difference between the single-axon solution and the complete solution is 25% on average.

CONCLUSION

Our result may provide an explanation as to why Deep Brain Stimulation experiments typically predict lower activation thresholds than commonly used FEM/Cable model approaches to predicting neuronal responses to extracellular electrical stimulation.

SIGNIFICANCE

These results may change methods for bi-domain neural modeling and neural excitation.

Conversion of a medical implant into a versatile computer-brain interface

BACKGROUND

Information transmission into the human nervous system is the basis for a variety of prosthetic applications. Spinal cord stimulation (SCS) systems are widely available, have a well documented safety record, can be implanted minimally invasively, and are known to stimulate afferent pathways. Nonetheless, SCS devices are not yet used for computer-brain-interfacing applications.

OBJECTIVE

Here we aimed to establish computer-to-brain communication via medical SCS implants in a group of 20 individuals who had been operated for the treatment of chronic neuropathic pain.

METHODS

In the initial phase, we conducted interface calibration with the aim of determining personalized stimulation settings that yielded distinct and reproducible sensations. These settings were subsequently utilized to generate inputs for a range of behavioral tasks. We evaluated the required calibration time, task training duration, and the subsequent performance in each task.

RESULTS

We could establish a stable spinal computer-brain interface in 18 of the 20 participants. Each of the 18 then performed one or more of the following tasks: A rhythm-discrimination task (n = 13), a Morse-decoding task (n = 3), and/or two different balance/body-posture tasks (n = 18; n = 5). The median calibration time was 79 min. The median training time for learning to use the interface in a subsequent task was 1:40 min. In each task, every participant demonstrated successful performance, surpassing chance levels.

CONCLUSION

The results constitute the first proof-of-concept of a general purpose computer-brain interface paradigm that could be deployed on present-day medical SCS platforms.

Role of the volume conductor on simulations of local field potential recordings from deep brain stimulation electrodes

OBJECTIVE

Local field potential (LFP) recordings from deep brain stimulation (DBS) electrodes are commonly used in research analyses, and are beginning to be used in clinical practice. Computational models of DBS LFPs provide tools for investigating the biophysics and neural synchronization that underlie LFP signals. However, technical standards for DBS LFP model parameterization remain to be established. Therefore, the goal of this study was to evaluate the role of the volume conductor (VC) model complexity on simulated LFP signals in the subthalamic nucleus (STN).

APPROACH

We created a detailed human head VC model that explicitly represented the inhomogeneity and anisotropy associated with 12 different tissue structures. This VC model represented our "gold standard" for technical detail and electrical realism. We then incrementally decreased the complexity of the VC model and quantified the impact on the simulated LFP recordings. Identical STN neural source activity was used when comparing the different VC model variants. Results Ignoring tissue anisotropy reduced the simulated LFP amplitude by ~12%, while eliminating soft tissue heterogeneity had a negligible effect on the recordings. Simplification of the VC model to consist of a single homogenous isotropic tissue medium with a conductivity of 0.215 S/m contributed an additional ~3% to the error.

SIGNIFICANCE

Highly detailed VC models do generate different results than simplified VC models. However, with errors in the range of ~15%, the use of a well-parameterized simple VC model is likely to be acceptable in most contexts for DBS LFP modeling.

Stereo-EEG-guided network modulation for psychiatric disorders: Surgical considerations

BACKGROUND

Deep brain stimulation (DBS) and other neuromodulatory techniques are being increasingly utilized to treat refractory neurologic and psychiatric disorders.

OBJECTIVE

/Hypothesis: To better understand the circuit-level pathophysiology of treatment-resistant depression (TRD) and treat the network-level dysfunction inherent to this challenging disorder, we adopted an approach of inpatient intracranial monitoring borrowed from the epilepsy surgery field.

METHODS

We implanted 3 patients with 4 DBS leads (bilateral pair in both the ventral capsule/ventral striatum and subcallosal cingulate) and 10 stereo-electroencephalography (sEEG) electrodes targeting depression-relevant network regions. For surgical planning, we used an interactive, holographic visualization platform to appreciate the 3D anatomy and connectivity. In the initial surgery, we placed the DBS leads and sEEG electrodes using robotic stereotaxy. Subjects were then admitted to an inpatient monitoring unit for depression-specific neurophysiological assessments. Following these investigations, subjects returned to the OR to remove the sEEG electrodes and internalize the DBS leads to implanted pulse generators.

RESULTS

Intraoperative testing revealed positive valence responses in all 3 subjects that helped verify targeting. Given the importance of the network-based hypotheses we were testing, we required accurate adherence to the surgical plan (to engage DBS and sEEG targets) and stability of DBS lead rotational position (to ensure that stimulation field estimates of the directional leads used during inpatient monitoring were relevant chronically), both of which we confirmed (mean radial error 1.2±0.9 mm; mean rotation 3.6±2.6°).

CONCLUSION

This novel hybrid sEEG-DBS approach allows detailed study of the neurophysiological substrates of complex neuropsychiatric disorders.

Stereo-EEG-guided network modulation for psychiatric disorders: Interactive holographic planning

BACKGROUND

Connectomic modeling studies are expanding understanding of the brain networks that are modulated by deep brain stimulation (DBS) therapies. However, explicit integration of these modeling results into prospective neurosurgical planning is only beginning to evolve. One challenge of employing connectomic models in patient-specific surgical planning is the inherent 3D nature of the results, which can make clinically useful data integration and visualization difficult.

METHODS

We developed a holographic stereotactic neurosurgery research tool (HoloSNS) that integrates patient-specific brain models into a group-based visualization environment for interactive surgical planning using connectomic hypotheses. HoloSNS currently runs on the HoloLens 2 platform and it enables remote networking between headsets. This allowed us to perform surgical planning group meetings with study co-investigators distributed across the country.

RESULTS

We used HoloSNS to plan stereo-EEG and DBS electrode placements for each patient participating in a clinical trial (NCT03437928) that is targeting both the subcallosal cingulate and ventral capsule for the treatment of depression. Each patient model consisted of multiple components of scientific data and anatomical reconstructions of the head and brain (both patient-specific and atlas-based), which far exceed the data integration capabilities of traditional neurosurgical planning workstations. This allowed us to prospectively discuss and evaluate the positioning of the electrodes based on novel connectomic hypotheses.

CONCLUSIONS

The 3D nature of the surgical procedure, brain imaging data, and connectomic modeling results all highlighted the utility of employing holographic visualization to support the design of unique clinical experiments to explore brain network modulation with DBS.

Influence of charges deposited on membranes of human hyperdirect pathway axons on depolarization during subthalamic deep brain stimulation

Objective.The motor hyperdirect pathway (HDP) is a key target in the treatment of Parkinson's disease with deep brain stimulation (DBS). Biophysical models of HDP DBS have been used to explore the mechanisms of stimulation. Built upon finite element method volume conductor solutions, such models are limited by a resolution mismatch, where the volume conductor is modeled at the macro scale, while the neural elements are at the micro scale. New techniques are needed to better integrate volume conductor models with neuron models.Approach.We simulated subthalamic DBS of the human HDP using finely meshed axon models to calculate surface charge deposition on insulting membranes of nonmyelinated axons. We converted the corresponding double layer extracellular problem to a single layer problem and applied the well-conditioned charge-based boundary element fast multipole method (BEM-FMM) with unconstrained numerical spatial resolution. Commonly used simplified estimations of membrane depolarization were compared with more realistic solutions.Main result.Neither centerline potential nor estimates of axon recruitment were impacted by the estimation method used except at axon bifurcations and hemispherical terminations. Local estimates of axon polarization were often much higher at bifurcations and terminations than at any other place along the axon and terminal arbor. Local average estimates of terminal electric field are higher by 10%-20%.Significance. Biophysical models of action potential initiation in the HDP suggest that axon terminations are often the lowest threshold elements for activation. The results of this study reinforce that hypothesis and suggest that this phenomenon is even more pronounced than previously realized.

Quantifying the Variability Associated with Postoperative Localization of Deep Brain Stimulation Electrodes

INTRODUCTION

Computational models of deep brain stimulation (DBS) have become common tools in clinical research studies that attempt to establish correlations between stimulation locations in the brain and behavioral outcome measures. However, the accuracy of any patient-specific DBS model depends heavily upon accurate localization of the DBS electrodes within the anatomy, which is typically defined via co-registration of clinical CT and MRI datasets. Several different approaches exist for this challenging registration problem, and each approach will result in a slightly different electrode localization. The goal of this study was to better understand how different processing steps (e.g., cost-function masking, brain extraction, intensity remapping) affect the estimate of the DBS electrode location in the brain.

METHODS

No "gold standard" exists for this kind of analysis, as the exact location of the electrode in the living human brain cannot be determined with existing clinical imaging approaches. However, we can estimate the uncertainty associated with the electrode position, which can be used to guide statistical analyses in DBS mapping studies. Therefore, we used high-quality clinical datasets from 10 subthalamic DBS subjects and co-registered their long-term postoperative CT with their preoperative surgical targeting MRI using 9 different approaches. The distances separating all of the electrode location estimates were calculated for each subject.

RESULTS

On average, electrodes were located within a median distance of 0.57 mm (0.49-0.74) of one another across the different registration approaches. However, when considering electrode location estimates from short-term postoperative CTs, the median distance increased to 2.01 mm (1.55-2.78).

CONCLUSIONS

The results of this study suggest that electrode location uncertainty needs to be factored into statistical analyses that attempt to define correlations between stimulation locations and clinical outcomes.

Comparison of Anatomical Pathway Models with Tractography Estimates of the Pallidothalamic, Cerebellothalamic, and Corticospinal Tracts

Introduction: Models of structural connectivity in the human brain are typically simulated using tractographic approaches. However, the nonlinear fitting of anatomical pathway atlases to de novo subject brains represents a simpler alternative that is hypothesized to provide more anatomically realistic results. Therefore, the goal of this study was to perform a side-by-side comparison of the streamline estimates generated by either pathway atlas fits or tractographic reconstructions in the same subjects. Methods: Our analyses focused on reconstruction of the corticospinal tract (CST), cerebellothalamic (CBT), and pallidothalamic (PT) pathways using example datasets from the Human Connectome Project (HCP). We used MRtrix3 to explore whole brain, as well as manual seed-to-target, tractography approaches. In parallel, we performed nonlinear fits of an axonal pathway atlas to each HCP dataset using Advanced Normalization Tools (ANTs). Results: The different methods produced notably different estimates for each pathway in each subject. The fitted atlas pathways were highly stereotyped and exhibited low variability in their streamline trajectories. Manual tractography resulted in pathway estimates that generally corresponded with the fitted atlas pathways, but with a higher degree of variability in the individual streamlines. Pathway reconstructions derived from whole-brain tractography exhibited the highest degree of variability and struggled to create anatomically realistic representations for either the CBT or PT pathways. Conclusion: The speed, simplicity, reproducibility, and realism of anatomical pathway model fits makes them an appealing option for some forms of structural connectivity modeling in the human brain. Impact statement Axonal pathway modeling is an important component of deep brain stimulation (DBS) research studies that seek to identify the brain connections that are directly activated by stimulation. The corticospinal tract, cerebellothalamic (CBT), and pallidothalamic (PT) pathways are specifically relevant to the study of subthalamic DBS for the treatment of Parkinson's disease. Our results suggest that anatomical pathway model fits of the CBT and PT pathways to de novo subject brains represent a more anatomically realistic option than tractographic approaches when studying subthalamic DBS.

Future directions in psychiatric neurosurgery: Proceedings of the 2022 American Society for Stereotactic and Functional Neurosurgery meeting on surgical neuromodulation for psychiatric disorders

OBJECTIVE

Despite advances in the treatment of psychiatric diseases, currently available therapies do not provide sufficient and durable relief for as many as 30-40% of patients. Neuromodulation, including deep brain stimulation (DBS), has emerged as a potential therapy for persistent disabling disease, however it has not yet gained widespread adoption. In 2016, the American Society for Stereotactic and Functional Neurosurgery (ASSFN) convened a meeting with leaders in the field to discuss a roadmap for the path forward. A follow-up meeting in 2022 aimed to review the current state of the field and to identify critical barriers and milestones for progress.

DESIGN

The ASSFN convened a meeting on June 3, 2022 in Atlanta, Georgia and included leaders from the fields of neurology, neurosurgery, and psychiatry along with colleagues from industry, government, ethics, and law. The goal was to review the current state of the field, assess for advances or setbacks in the interim six years, and suggest a future path forward. The participants focused on five areas of interest: interdisciplinary engagement, regulatory pathways and trial design, disease biomarkers, ethics of psychiatric surgery, and resource allocation/prioritization. The proceedings are summarized here.

CONCLUSION

The field of surgical psychiatry has made significant progress since our last expert meeting. Although weakness and threats to the development of novel surgical therapies exist, the identified strengths and opportunities promise to move the field through methodically rigorous and biologically-based approaches. The experts agree that ethics, law, patient engagement, and multidisciplinary teams will be critical to any potential growth in this area.

Holographic visualization for stereotactic neurosurgery research

Background:

Stereotactic neurosurgical planning for the placement of depth electrodes requires the integration of wide-ranging 3D datasets on the anatomy of the patient.

Objective:

Our goal was to create an interactive group-based holographic visualization tool (HoloSNS) that facilitates evaluation of depth electrode positioning relative to the available medical imaging data, as well as models of the anatomical nuclei and structural connectivity of the brain.

Methods:

HoloSNS is currently designed to run on the HoloLens 2 platform, and was developed using the Unity Game Engine and the Mixed Reality Toolkit from Microsoft.

Results:

HoloSNS currently supports research analyses with deep brain stimulation (DBS) and/or stereo-electroencephalography (SEEG) electrodes. Two example software applications (HoloDBS and HoloSEEG) are available for free download on the Microsoft App Store.

Conclusions:

HoloSNS is the latest culmination of our efforts to integrate advances in brain imaging data, intracranial electrode modeling, and advanced visualization techniques to enhance stereotactic neurosurgery research.

Evolving characterization of the human hyperdirect pathway

The hyperdirect pathway (HDP) represents the main glutamatergic input to the subthalamic nucleus (STN), through which the motor and prefrontal cerebral cortex can modulate basal ganglia activity. Further, direct activation of the motor HDP is thought to be an important component of therapeutic deep brain stimulation (DBS), mediating the disruption of pathological oscillations. Alternatively, unintended recruitment of the prefrontal HDP may partly explain some cognitive side effects of DBS therapy. Previous work describing the HDP has focused on non-human primate (NHP) histological pathway tracings, diffusion-weighted MRI analysis of human white matter, and electrophysiology studies involving paired cortical recordings with DBS. However, none of these approaches alone yields a complete understanding of the complexities of the HDP. As such, we propose that generative modeling methods hold promise to bridge anatomy and physiology results, from both NHPs and humans, into a more detailed representation of the human HDP. Nonetheless, numerous features of the HDP remain to be experimentally described before model-based methods can simulate corticosubthalamic activity with a high degree of scientific detail. Therefore, the goals of this review are to examine the experimental evidence for HDP projections from across the primate neocortex and discuss new data which are required to improve the utility of anatomical and biophysical models of the human corticosubthalamic system.

Mitigating Mismatch Compression in Differential Local Field Potentials

Deep brain stimulation (DBS) devices capable of measuring differential local field potentials ( ∂ LFP) enable neural recordings alongside clinical therapy. Efforts to identify oscillatory correlates of various brain disorders, or disease readouts, are growing but must proceed carefully to ensure readouts are not distorted by brain environment. In this report we identified, characterized, and mitigated a major source of distortion in ∂ LFP that we introduce as mismatch compression (MC). Using in vivo, in silico, and in vitro models of MC, we showed that impedance mismatches in the two recording electrodes can yield incomplete rejection of stimulation artifact and subsequent gain compression that distorts oscillatory power. We then developed and validated an opensource mitigation pipeline that mitigates the distortions arising from MC. This work enables more reliable oscillatory readouts for adaptive DBS applications.

Deep Brain Stimulation for Depression Informed by Intracranial Recordings

The success of deep brain stimulation (DBS) for treating Parkinson's disease has led to its application to several other disorders, including treatment-resistant depression. Results with DBS for treatment-resistant depression have been heterogeneous, with inconsistencies largely driven by incomplete understanding of the brain networks regulating mood, especially on an individual basis. We report results from the first subject treated with DBS for treatment-resistant depression using an approach that incorporates intracranial recordings to personalize understanding of network behavior and its response to stimulation. These recordings enabled calculation of individually optimized DBS stimulation parameters using a novel inverse solution approach. In the ensuing double-blind, randomized phase incorporating these bespoke parameter sets, DBS led to remission of symptoms and dramatic improvement in quality of life. Results from this initial case demonstrate the feasibility of this personalized platform, which may be used to improve surgical neuromodulation for a vast array of neurologic and psychiatric disorders.

Automated optimization of deep brain stimulation parameters for modulating neuroimaging-based targets

Objective.Therapeutic efficacy of deep brain stimulation (DBS) in both established and emerging indications, is highly dependent on accurate lead placement and optimized clinical programming. The latter relies on clinicians' experience to search among available sets of stimulation parameters and can be limited by the time constraints of clinical practice. Recent innovations in device technology have expanded the number of possible electrode configurations and parameter sets available to clinicians, amplifying the challenge of time constraints. We hypothesize that patient specific neuroimaging data can effectively assist the clinical programming using automated algorithms.Approach.This paper introduces the DBS Illumina 3D algorithm as a tool which uses patient-specific imaging to find stimulation settings that optimizes activating a target area while minimizing the stimulation of areas outside the target that could result in unknown or undesired side effects. This approach utilizes preoperative neuroimaging data paired with the postoperative reconstruction of the lead trajectory to search the available stimulation space and identify optimized stimulation parameters. We describe the application of this algorithm in three patients with treatment-resistant depression who underwent bilateral implantation of DBS in subcallosal cingulate cortex and ventral capsule/ventral striatum using tractography optimized targeting with an imaging defined target previously described.Main results.Compared to the stimulation settings selected by the clinicians (informed by anatomy), stimulation settings produced by the algorithm that achieved similar or greater target coverage, produced a significantly smaller stimulation area that spilled outside the target (P= 0.002).Significance. The DBS Illumina 3D algorithm is seamlessly integrated with the clinician programmer software and effectively and rapidly assists clinicians with the analysis of image based anatomy, and provides a starting point to search the highly complex stimulation parameter space and arrive at the stimulation settings that optimize activating a target area.

Imaging versus electrographic connectivity in human mood-related fronto-temporal networks

BACKGROUND

The efficacy of psychiatric DBS is thought to be driven by the connectivity of stimulation targets with mood-relevant fronto-temporal networks, which is typically evaluated using diffusion-weighted tractography.

OBJECTIVE

Leverage intracranial electrophysiology recordings to better predict the circuit-wide effects of neuromodulation to white matter targets. We hypothesize strong convergence between tractography-predicted structural connectivity and stimulation-induced electrophysiological responses.

METHODS

Evoked potentials were elicited by single-pulse stimulation to two common DBS targets for treatment-resistant depression - the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VCVS) - in two patients undergoing DBS with stereo-electroencephalographic (sEEG) monitoring. Evoked potentials were compared with predicted structural connectivity between DBS leads and sEEG contacts using probabilistic, patient-specific diffusion-weighted tractography.

RESULTS

Evoked potentials and tractography showed strong convergence in both patients in orbitofrontal, ventromedial prefrontal, and lateral prefrontal cortices for both SCC and VCVS stimulation targets. Low convergence was found in anterior cingulate (ACC), where tractography predicted structural connectivity from SCC targets but produced no evoked potentials during SCC stimulation. Further, tractography predicted no connectivity to ACC from VCVS targets, but VCVS stimulation produced robust evoked potentials.

CONCLUSION

The two connectivity methods showed significant convergence, but important differences emerged with respect to the ability of tractography to predict electrophysiological connectivity between SCC and VCVS to regions of the mood-related network. This multimodal approach raises intriguing implications for the use of tractography in surgical targeting and provides new data to enhance our understanding of the network-wide effects of neuromodulation.

Subthalamic deep brain stimulation of an anatomically detailed model of the human hyperdirect pathway

The motor hyperdirect pathway (HDP) is considered a key target in the treatment of Parkinson's disease with subthalamic deep brain stimulation (DBS). This hypothesis is partially derived from the association of HDP activation with evoked potentials (EPs) generated in the motor cortex and subthalamic nucleus (STN) after a DBS pulse. However, the biophysical details of how and when DBS-induced action potentials (APs) in HDP neurons reach their terminations in the cortex or STN remain unclear. Therefore, we used an anatomically detailed representation of the motor HDP, as well as the internal capsule (IC), in a model of human subthalamic DBS to explore AP activation and transmission in the HDP and IC. Our results show that small diameter HDP axons exhibited AP initiation in their subthalamic terminal arbor, which resulted in relatively long transmission latencies to cortex (∼3.5-8 ms). Alternatively, large diameter HDP axons were most likely to be directly activated in the capsular region, which resulted in short transmission times to the cortex (∼1-3 ms). However, those large diameter HDP antidromic APs would be indistinguishable from any other IC axons that were also activated by the stimulus. Conversely, DBS-induced APs in both small and large diameter HDP axons reached their synaptic boutons in the STN with similar timings, but both spanned a wide temporal range (∼0.5-5 ms). We also found that using anodic or bipolar stimulation helped to bias activation of the HDP over the IC. These computational results provide useful information for linking HDP activation with EP recordings in clinical experiments.NEW & NOTEWORTHY We used biophysical models to study pathway recruitment and conduction latencies of the hyperdirect pathway (HDP) in response to subthalamic deep brain stimulation (DBS). The model system allowed us to assess the influence of increased anatomical realism on pathway activity and the possibility of identifying HDP activity in evoked potentials (EPs) recorded in either the subthalamic nucleus (STN) or cortex. The model predicts that HDP activation is accentuated by complex axonal branching in the STN.

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.

Temporal Patterns of Spontaneous Fixational Eye Movements: The Influence of Basal Ganglia

BACKGROUND

Spontaneity is a unique feature of the nervous system. One of the fundamentally critical and recognized forms of spontaneous motor activity is witnessed in the visuomotor system. Microsaccades, the miniature spontaneous eye movements, are critical for the visual perception. We hypothesized that microsaccades follow specific temporal patterns that are modulated by the basal ganglia output.

METHODS

We used high-resolution video-oculography to capture microsaccades in 48 subjects (31 healthy and 17 with Parkinson's disease) when subjects were asked to hold their gaze on a straight-ahead target projected on white background. We analyzed spontaneous discharge patterns of microsaccades.

RESULTS

The first analysis considering coefficient of variation in intersaccadic interval distribution demonstrated that microsaccades in Parkinson's disease are more dispersed than the control group. The second analysis scrutinized microsaccades' temporal variability and revealed 3 distinct occurrence patterns: regular rhythmic, clustered, and randomly occurring following a Poisson-like process. The regular pattern was relatively more common in Parkinson's disease. Subthalamic DBS modulated this temporal pattern. The amount of change in the temporal variability depended on the DBS-induced volume of tissue activation and its overlap with the subthalamic nucleus. The third analysis determined the autocorrelations of microsaccades within 2-second time windows. We found that Parkinson's disease altered local temporal organization in microsaccade generation, and DBS had a modulatory effect.

CONCLUSION

The microsaccades occur in 3 temporal patterns. The basal ganglia are one of the modulators of the microsaccade spontaneity.

Cingulum bundle connectivity in treatment-refractory compared to treatment-responsive patients with bipolar disorder and healthy controls: a tractography and surgical targeting analysis

OBJECTIVE

The clinical response of patients with bipolar disorder to medical treatment is variable. A better understanding of the underlying neural circuitry involved in bipolar treatment responsivity subtypes may provide insight into treatment resistance and aid in identifying an effective surgical target for deep brain stimulation (DBS) specific to the disorder. Despite considerable imaging research related to the disease, a paucity of comparative imaging analyses of treatment responsiveness exists. There are also no DBS targets designed expressly for patients with bipolar disorder. Therefore, the authors analyzed cingulum bundle axonal connectivity in relation to cortico-striatal-thalamo-cortical (CSTC) loops implicated in bipolar disorder across subjects who are responsive to treatment (RSP) and those who are refractory to therapy (REF), compared to healthy controls (HCs).

METHODS

Twenty-five subjects with bipolar disorder (13 RSP and 12 REF), diagnosed using the Mini International Neuropsychiatric Interview and classified with standardized rating scales, and 14 HCs underwent MRI with diffusion sequences for probabilistic diffusion-weighted tractography analysis. Image processing and tractography were performed using MRTrix. Region of interest (ROI) masks were created manually for 10 anterior cingulum bundle subregions, including surgical targets previously evaluated for the treatment of bipolar disorder (cingulotomy and subgenual cingulate DBS targets). Cortical and subcortical ROIs of brain areas thought to be associated with bipolar disorder and described in animal tract-tracing models were created via FreeSurfer. The number of axonal projections from the cingulum bundle subregion ROIs to cortical/subcortical ROIs for each group was compared.

RESULTS

Significant differences were found across groups involving cingulum bundle and CSTC loops. Subjects in the RSP group had increased connections from rostral cingulum bundle to medial orbitofrontal cortex, which is part of the limbic CSTC loop, whereas subjects in the REF group had increased connectivity from rostral cingulum bundle to thalamus. Additionally, compared to HCs, both RSP and REF subjects had decreased cingulum bundle dorsal connectivity (dorsal anterior/posterior cingulate, dorsomedial/lateral frontal cortex) and increased cingulum bundle ventral connectivity (subgenual cingulate, frontal pole, lateral orbitofrontal cortex) involving limbic and associative CSTC loops.

CONCLUSIONS

Findings demonstrate that bipolar treatment responsivity may be associated with significant differences in cingulum bundle connectivity in relation to CSTC loops, which may help identify a surgical target for bipolar disorder treatment via DBS in the future.

Comparison of methodologies for modeling directional deep brain stimulation electrodes

Deep brain stimulation (DBS) is an established clinical therapy, and directional DBS electrode designs are now commonly used in clinical practice. Directional DBS leads have the ability to increase the therapeutic window of stimulation, but they also increase the complexity of clinical programming. Therefore, computational models of DBS have become available in clinical software tools that are designed to assist in the identification of therapeutic settings. However, the details of how the DBS model is implemented can influence the predictions of the software. The goal of this study was to compare different methods for representing directional DBS electrodes within finite element volume conductor (VC) models. We evaluated 15 different DBS VC model variants and quantified how their differences influenced estimates on the spatial extent of axonal activation from DBS. Each DBS VC model included the same representation of the brain and head, but the details of the current source and electrode contact were different for each model variant. The more complex VC models explicitly represented the DBS electrode contacts, while the more simple VC models used boundary condition approximations. The more complex VC models required 2-3 times longer to mesh, build, and solve for the DBS voltage distribution than the more simple VC models. Differences in individual axonal activation thresholds across the VC model variants were substantial (-24% to +47%). However, when comparing total activation of an axon population, or estimates of an activation volume, the differences between model variants decreased (-7% to +8%). Nonetheless, the technical details of how the electrode contact and current source are represented in the DBS VC model can directly affect estimates of the voltage distribution and electric field in the brain tissue.

Histology-driven model of the macaque motor hyperdirect pathway

Emerging appreciation for the hyperdirect pathway (HDP) as an important cortical glutamatergic input to the subthalamic nucleus (STN) has motivated a wide range of recent investigations on its role in motor control, as well as the mechanisms of subthalamic deep brain stimulation (DBS). However, the pathway anatomy and terminal arbor morphometry by which the HDP links cortical and subthalamic activity are incompletely understood. One critical hindrance to advancing understanding is the lack of anatomically detailed population models which can help explain how HDP pathway anatomy and neuronal biophysics give rise to spatiotemporal patterns of stimulus-response activity observed in vivo. Therefore, the goal of this study was to establish a population model of motor HDP axons through application of generative algorithms constrained by recent histology and imaging data. The products of this effort include a de novo macaque brain atlas, detailed statistical analysis of histological reconstructions of macaque motor HDP axons, and the generation of 10,000 morphometrically constrained synthetic motor HDP axons. The synthetic HDP axons exhibited a 3.8% mean error with respect to parametric distributions of the fiber target volume, total length, number of bifurcations, bifurcation angles, meander angles, and segment lengths measured in BDA-labeled HDP axon reconstructions. As such, this large population of synthetic motor HDP axons represents an anatomically based foundation for biophysical simulations that can be coupled to electrophysiological and/or behavioral measurements, with the goal of better understanding the role of the HDP in motor system activity.

Subthalamic deep brain stimulation affects heading perception in Parkinson's disease

Parkinson's disease (PD) presents with visuospatial impairment and falls. It is critical to understand how subthalamic deep brain stimulation (STN DBS) modulates visuospatial perception. We hypothesized that DBS has different effects on visual and vestibular perception of linear motion (heading), a critical aspect of visuospatial navigation; and such effects are specific to modulated STN location. Two-alternative forced-choice experiments were performed in 14 PD patients with bilateral STN DBS and 19 age-matched healthy controls (HC) during passive en bloc linear motion and 3D optic-flow in immersive virtual reality measured vestibular and visual heading. Objective measure of perception with Weibull psychometric function revealed that PD has significantly lower accuracy [L: 60.71 (17.86)%, R: 74.82 (17.44)%] and higher thresholds [L: 16.68 (12.83), R: 10.09 (7.35)] during vestibular task in both directions compared to HC (p < 0.05). DBS significantly improved vestibular discrimination accuracy [81.40 (14.36)%] and threshold [4.12 (5.87), p < 0.05] in the rightward direction. There were no DBS effects on the slopes of vestibular psychometric curves. Visual heading perception was better than vestibular and it was comparable to HC. There was no significant effect of DBS on visual heading response accuracy or discrimination threshold (p > 0.05). Patient-specific DBS models revealed an association between change in vestibular heading perception and the modulation of the dorsal STN. In summary, DBS may have different effects on vestibular and visual heading perception in PD. These effects may manifest via dorsal STN putatively by its effects on the cerebellum.

Image-based biophysical modeling predicts cortical potentials evoked with subthalamic deep brain stimulation

BACKGROUND

Subthalamic deep brain stimulation (DBS) is an effective surgical treatment for Parkinson's disease and continues to advance technologically with an enormous parameter space. As such, in-silico DBS modeling systems have become common tools for research and development, but their underlying methods have yet to be standardized and validated.

OBJECTIVE

Evaluate the accuracy of patient-specific estimates of neural pathway activations in the subthalamic region against intracranial, cortical evoked potential (EP) recordings.

METHODS

Pathway activations were modeled in eleven patients using the latest advances in connectomic modeling of subthalamic DBS, focusing on the hyperdirect pathway (HDP) and corticospinal/bulbar tract (CSBT) for their relevance in human research studies. Correlations between pathway activations and respective EP amplitudes were quantified.

RESULTS

Good model performance required accurate lead localization and image fusions, as well as appropriate selection of fiber diameter in the biophysical model. While optimal model parameters varied across patients, good performance could be achieved using a global set of parameters that explained 60% and 73% of electrophysiologic activations of CSBT and HDP, respectively. Moreover, restricted models fit to only EP amplitudes of eight standard (monopolar and bipolar) electrode configurations were able to extrapolate variation in EP amplitudes across other directional electrode configurations and stimulation parameters, with no significant reduction in model performance across the cohort.

CONCLUSIONS

Our findings demonstrate that connectomic models of DBS with sufficient anatomical and electrical details can predict recruitment dynamics of white matter. These results will help to define connectomic modeling standards for preoperative surgical targeting and postoperative patient programming applications.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

SIGNIFICANCE

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

StimVision v2: Examples and Applications in Subthalamic Deep Brain Stimulation for Parkinson's Disease

OBJECTIVE

Subthalamic deep brain stimulation (DBS) is an established therapy for Parkinson's disease. Connectomic DBS modeling is a burgeoning subfield of research aimed at characterizing the axonal connections activated by DBS. This article describes our approach and methods for evolving the StimVision software platform to meet the technical demands of connectomic DBS modeling in the subthalamic region.

MATERIALS AND METHODS

StimVision v2 was developed with Visualization Toolkit (VTK) libraries and integrates four major components: 1) medical image visualization, 2) axonal pathway visualization, 3) electrode positioning, and 4) stimulation calculation.

RESULTS

StimVision v2 implemented two key technological advances for connectomic DBS analyses in the subthalamic region. First was the application of anatomical axonal pathway models to patient-specific DBS models. Second was the application of a novel driving-force method to estimate the response of those axonal pathways to DBS. Example simulations with directional DBS electrodes and clinically defined therapeutic DBS settings are presented to demonstrate the general outputs of StimVision v2 models.

CONCLUSIONS

StimVision v2 provides the opportunity to evaluate patient-specific axonal pathway activation from subthalamic DBS using anatomically detailed pathway models and electrically detailed electric field distributions with interactive adjustment of the DBS electrode position and stimulation parameter settings.

Clinical Evaluation of Cingulum Bundle Connectivity for Neurosurgical Hypothesis Development

BACKGROUND

The cingulum bundle (CB) has long been a target for psychiatric neurosurgical procedures, but with limited understanding of the brain networks being impacted. Recent advances in human tractography could provide a foundation to better understand the effects of neurosurgical interventions on the CB; however, the reliability of tractography remains in question.

OBJECTIVE

To evaluate the ability of different tractography techniques, derived from typical, human diffusion-weighted imaging (DWI) data, to characterize CB connectivity described in animal models. This will help validate the clinical applicability of tractography, and generate insight on current and future neurosurgical targets for psychiatric disorders.

METHODS

Connectivity of the CB in 15 healthy human subjects was evaluated using DWI-based tractography, and compared to tract-tracing findings from nonhuman primates. Brain regions of interest were defined to coincide with the animal model. Tractography was performed using 3 techniques (FSL probabilistic, Camino probabilistic, and Camino deterministic). Differences in connectivity were assessed, and the CB segment with the greatest connectivity was determined.

RESULTS

Each tractography technique successfully reproduced the animal tracing model with a mean accuracy of 72% (68-75%, P < .05). Additionally, one region of the CB, the rostral dorsal segment, had significantly greater connectivity to associated brain structures than all other CB segments (P < .05).

CONCLUSION

Noninvasive, in vivo human analysis of the CB, using clinically available DWI for tractography, consistently reproduced the results of an animal tract-tracing model. This suggests that tractography of the CB can be used for clinical applications, which may aid in neurosurgical targeting for psychiatric disorders.

Levodopa Versus Dopamine Agonist after Subthalamic Stimulation in Parkinson's Disease

Background

No clinical trials have been specifically designed to compare medical treatments after surgery in Parkinson's disease (PD).

Objective

Study's objective was to compare the efficacy and safety of levodopa versus dopamine agonist monotherapy after deep brain stimulation (DBS) in PD.

Methods

Thirty‐five surgical candidates were randomly assigned to receive postoperative monotherapy with either levodopa or dopamine agonist in a randomized, single‐blind study. All patients were reevaluated in short‐ (3 months), mid‐ (6 months), and long‐term (2.5 years) follow‐up after surgery. The primary outcome measure was the change in the Non‐Motor Symptoms Scale (NMSS) 3 months after surgery. Secondary outcome measures were the percentage of patients maintaining monotherapy, change in motor symptoms, and specific non‐motor symptoms (NMS). Analysis was performed primarily in the intention‐to‐treat population.

Results

Randomization did not significantly affect the primary outcome (difference in NMSS between treatment groups was 4.88 [95% confidence interval: −11.78–21.53, P = 0.566]). In short‐ and mid‐term follow‐up, monotherapy was safe and feasible in more than half of patients (60% in short‐ and 51.5% in mid‐term follow‐up), but it was more often possible for patients on levodopa. The ability to maintain dopamine agonist monotherapy was related to optimal contact location. In the long term, levodopa monotherapy was feasible only in a minority of patients (34.2%), whereas dopamine agonist monotherapy was not tolerated due to worsening of motor conditions or occurrence of impulse control disorders.

Conclusions

This trial provides evidence for simplifying pharmacological treatment after functional neurosurgery for PD. The reduction in dopamine receptor agonists should be attempted while monitoring for occurrence of NMSs, such as apathy and sleep disturbances. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Deep brain stimulation of terminating axons

BACKGROUND

Deep brain stimulation (DBS) of the subthalamic region is an established treatment for the motor symptoms of Parkinson's disease. Several types of neural elements reside in the subthalamic region, including subthalamic nucleus (STN) neurons, fibers of passage, and terminating afferents. Recent studies suggest that direct activation of a specific population of subthalamic afferents, known as the hyperdirect pathway, may be responsible for some of the therapeutic effects of subthalamic DBS.

OBJECTIVE

The goal of this study was to quantify how axon termination affects neural excitability from DBS. We evaluated how adjusting different stimulation parameters influenced the relative excitability of terminating axons (TAs) compared to fibers of passage (FOPs).

METHODS

We used finite element electric field models of DBS, coupled to multi-compartment cable models of axons, to calculate activation thresholds for populations of TAs and FOPs. These generalized models were used to evaluate the response to anodic vs. cathodic stimulation, with short vs. long stimulus pulses.

RESULTS

Terminating axons generally exhibited lower thresholds than fibers of passage across all tested parameters. Short pulse widths accentuated the relative excitability of TAs over FOPs.

CONCLUSION(S)

Our computational results demonstrate a hyperexcitability of terminating axons to DBS that is robust to variation in the stimulation parameters, as well as the axon model parameters.

Feasibility of Interferential and Pulsed Transcranial Electrical Stimulation for Neuromodulation at the Human Scale

OBJECTIVES

Transcranial electrical stimulation (tES) is a promising tool for modulating neural activity, but tES has poor penetrability and spatiotemporal resolution compared to invasive techniques like deep brain stimulation (DBS). Interferential strategies for alternating-current stimulation (IF-tACS) and pulsed/intersectional strategies for transcranial direct-current stimulation (IS-tDCS) address some of the limitations of tES, but the comparative advantages and disadvantages of these new techniques is not well understood. This study's objective was to evaluate the suprathreshold and subthreshold membrane dynamics of neurons in response to IF-tACS and IS-tDCS.

MATERIALS AND METHODS

We analyzed the biophysics of IF-tACS and IS-tDCS using a bioelectric field model of tES. Neural responses were quantified for suprathreshold generation of action potentials in axons and for subthreshold modulation of membrane dynamics in spiking pyramidal neurons.

RESULTS

IF-tACS and IS-tDCS could not directly activate axons at or below 10 mA, but within this current range, these fields were able to modulate, albeit indirectly, spiking activity in the neuron model. IF-tACS facilitated phase synchronization similar to tACS, and IS-tDCS enhanced and suppressed spiking activity similar to tDCS; however, in either case, the modulatory effects of these fields were less potent than their standard counterparts at a matched field intensity. Moreover, neither IF-tACS nor IS-tDCS improved the spatial selectivity of their parent strategies.

CONCLUSIONS

Enhancing the spatiotemporal precision and penetrability of tES with interferential and intersectional strategies is possible at the human scale. However, IF-tACS or IS-tDCS will likely require spatial multiplexing with multiple simultaneous sources to counteract their reduced potency, compared to standard techniques, to maintain stimulation currents at tolerable levels.

Proceedings of the Sixth Deep Brain Stimulation Think Tank Modulation of Brain Networks and Application of Advanced Neuroimaging, Neurophysiology, and Optogenetics

The annual deep brain stimulation (DBS) Think Tank aims to create an opportunity for a multidisciplinary discussion in the field of neuromodulation to examine developments, opportunities and challenges in the field. The proceedings of the Sixth Annual Think Tank recapitulate progress in applications of neurotechnology, neurophysiology, and emerging techniques for the treatment of a range of psychiatric and neurological conditions including Parkinson’s disease, essential tremor, Tourette syndrome, epilepsy, cognitive disorders, and addiction. Each section of this overview provides insight about the understanding of neuromodulation for specific disease and discusses current challenges and future directions. This year’s report addresses key issues in implementing advanced neurophysiological techniques, evolving use of novel modulation techniques to deliver DBS, ans improved neuroimaging techniques. The proceedings also offer insights into the new era of brain network neuromodulation and connectomic DBS to define and target dysfunctional brain networks. The proceedings also focused on innovations in applications and understanding of adaptive DBS (closed-loop systems), the use and applications of optogenetics in the field of neurostimulation and the need to develop databases for DBS indications. Finally, updates on neuroethical, legal, social, and policy issues relevant to DBS research are discussed.

Theoretical principles of deep brain stimulation induced synaptic suppression

BACKGROUND

Deep brain stimulation (DBS) is a successful clinical therapy for a wide range of neurological disorders; however, the physiological mechanisms of DBS remain unresolved. While many different hypotheses currently exist, our analyses suggest that high frequency (∼100 Hz) stimulation-induced synaptic suppression represents the most basic concept that can be directly reconciled with experimental recordings of spiking activity in neurons that are being driven by DBS inputs.

OBJECTIVE

The goal of this project was to develop a simple model system to characterize the excitatory post-synaptic currents (EPSCs) and action potential signaling generated in a neuron that is strongly connected to pre-synaptic glutamatergic inputs that are being directly activated by DBS.

METHODS

We used the Tsodyks-Markram (TM) phenomenological synapse model to represent depressing, facilitating, and pseudo-linear synapses driven by DBS over a wide range of stimulation frequencies. The EPSCs were then used as inputs to a leaky integrate-and-fire neuron model and we measured the DBS-triggered post-synaptic spiking activity.

RESULTS

Synaptic suppression was a robust feature of high frequency stimulation, independent of the synapse type. As such, the TM equations were used to define alternative DBS pulsing strategies that maximized synaptic suppression with the minimum number of stimuli.

CONCLUSIONS

Synaptic suppression provides a biophysical explanation to the intermittent, but still time-locked, post-synaptic firing characteristics commonly seen in DBS experimental recordings. Therefore, network models attempting to analyze or predict the effects of DBS on neural activity patterns should integrate synaptic suppression into their simulations.

A Driving-Force Predictor for Estimating Pathway Activation in Patient-Specific Models of Deep Brain Stimulation

OBJECTIVE

Detailed biophysical modeling of deep brain stimulation (DBS) provides a theoretical approach to quantify the cellular response to the applied electric field. However, the most accurate models for performing such analyses, patient-specific field-cable (FC) pathway-activation models (PAMs), are so technically demanding to implement that their use in clinical research is greatly limited. Predictive algorithms can simplify PAM calculations, but they generally fail to reproduce the output of FC models when evaluated over a wide range of clinically relevant stimulation parameters. Therefore, we set out to develop a novel driving-force (DF) predictive algorithm (DF-Howell), customized to the study of DBS, which can better match FC results.

METHODS

We developed the DF-Howell algorithm and compared its predictions to FC PAM results, as well as to the DF-Peterson algorithm, which is currently the most accurate and generalizable DF-based method. Comparison of the various methods was quantified within the context of subthalamic DBS using activation thresholds of axons representing the internal capsule, hyperdirect pathway, and cerebellothalamic tract for various combinations of fiber diameters, stimulus pulse widths, and electrode configurations.

RESULTS

The DF-Howell predictor estimated activation of the three axonal pathways with less than a 6.2% mean error with respect to the FC PAM for all 21 cases tested. In 15 of the 21 cases, DF-Howell outperformed DF-Peterson in estimating pathway activation, reducing mean-errors up to 22.5%.

CONCLUSIONS

DF-Howell represents an accurate predictor for estimating axonal pathway activation in patient-specific DBS models, but errors still exist relative to FC PAM calculations. Nonetheless, the tractability of DF algorithms helps to reduce the technical barriers for performing accurate biophysical modeling in clinical DBS research studies.

Vestibular heading perception in Parkinson's disease

Postural instability and falls are common causes of morbidity and mortality in the second most prevalent neurodegenerative condition, Parkinson's disease (PD). Poor understanding of balance dysfunction in PD has hampered the development of novel therapeutic measures for postural instability and balance dysfunction. We aimed to determine how the ability to perceive one's own linear motion in the absence of visual cues, i.e., vestibular heading, is affected in PD. We examined vestibular heading function using a two-alternative forced choice task performed on a six-degree-of-freedom motion platform. Sensitivity of the vestibular system to subtle variations in heading direction and systematic errors in accuracy of responses were assessed for each subject using a Gaussian cumulative distribution psychometric function. Compared to healthy subjects, PD presented with higher angular thresholds to detect vestibular heading direction. These results confirm the potential of our study to provide valuable insight to the vestibular system's role in spatial navigation deficits in PD.

Quantifying the axonal pathways directly stimulated in therapeutic subcallosal cingulate deep brain stimulation

Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) is an emerging experimental therapy for treatment-resistant depression. New developments in SCC DBS surgical targeting are focused on identifying specific axonal pathways for stimulation that are estimated from patient-specific computational models. This connectomic-based biophysical modeling strategy has proven successful in improving the clinical response to SCC DBS therapy, but the DBS models used to date have been relatively simplistic, limiting the precision of the pathway activation estimates. Therefore, we used the most detailed patient-specific foundation for DBS modeling currently available (i.e., field-cable modeling) to evaluate SCC DBS in our most recent cohort of six subjects, all of which were responders to the therapy. We quantified activation of four major pathways in the SCC region: forceps minor (FM), cingulum bundle (CB), uncinate fasciculus (UF), and subcortical connections between the frontal pole and the thalamus or ventral striatum (FP). We then used the percentage of activated axons in each pathway as regressors in a linear model to predict the time it took patients to reach a stable response, or TSR. Our analysis suggests that stimulation of the left and right CBs, as well as FM are the most likely therapeutic targets for SCC DBS. In addition, the right CB alone predicted 84% of the variation in the TSR, and the correlation was positive, suggesting that activation of the right CB beyond a critical percentage may actually protract the recovery process.

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

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

Quantifying axonal responses in patient-specific models of subthalamic deep brain stimulation

Medical imaging has played a major role in defining the general anatomical targets for deep brain stimulation (DBS) therapies. However, specifics on the underlying brain circuitry that is directly modulated by DBS electric fields remain relatively undefined. Detailed biophysical modeling of DBS provides an approach to quantify the theoretical responses to stimulation at the cellular level, and has established a key role for axonal activation in the therapeutic mechanisms of DBS. Estimates of DBS-induced axonal activation can then be coupled with advances in defining the structural connectome of the human brain to provide insight into the modulated brain circuitry and possible correlations with clinical outcomes. These pathway-activation models (PAMs) represent powerful tools for DBS research, but the theoretical predictions are highly dependent upon the underlying assumptions of the particular modeling strategy used to create the PAM. In general, three types of PAMs are used to estimate activation: 1) field-cable (FC) models, 2) driving force (DF) models, and 3) volume of tissue activated (VTA) models. FC models represent the "gold standard" for analysis but at the cost of extreme technical demands and computational resources. Consequently, DF and VTA PAMs, derived from simplified FC models, are typically used in clinical research studies, but the relative accuracy of these implementations is unknown. Therefore, we performed a head-to-head comparison of the different PAMs, specifically evaluating DBS of three different axonal pathways in the subthalamic region. The DF PAM was markedly more accurate than the VTA PAMs, but none of these simplified models were able to match the results of the patient-specific FC PAM across all pathways and combinations of stimulus parameters. These results highlight the limitations of using simplified predictors to estimate axonal stimulation and emphasize the need for novel algorithms that are both biophysically realistic and computationally simple.

Action potential initiation, propagation, and cortical invasion in the hyperdirect pathway during subthalamic deep brain stimulation

BACKGROUND

High frequency (∼130 Hz) deep brain stimulation (DBS) of the subthalamic region is an established clinical therapy for the treatment of late stage Parkinson's disease (PD). Direct modulation of the hyperdirect pathway, defined as cortical layer V pyramidal neurons that send an axon collateral to the subthalamic nucleus (STN), has emerged as a possible component of the therapeutic mechanisms. However, numerous questions remain to be addressed on the basic biophysics of hyperdirect pathway stimulation.

OBJECTIVE

Quantify action potential (AP) initiation, propagation, and cortical invasion in hyperdirect neurons during subthalamic stimulation.

METHODS

We developed an anatomically and electrically detailed computational model of hyperdirect neuron stimulation with explicit representation of the stimulating electric field, axonal response, AP propagation, and synaptic transmission.

RESULTS

We found robust AP propagation throughout the complex axonal arbor of the hyperdirect neuron. Even at therapeutic DBS frequencies, stimulation induced APs could reach all of the intracortical axon terminals with ∼100% fidelity. The functional result of this high frequency axonal driving of the thousands of synaptic connections made by each directly stimulated hyperdirect neuron is a profound synaptic suppression that would effectively disconnect the neuron from the cortical circuitry.

CONCLUSIONS

The synaptic suppression hypothesis integrates the fundamental biophysics of electrical stimulation, axonal transmission, and synaptic physiology to explain a generic mechanism of DBS.

A connectomic approach for subcallosal cingulate deep brain stimulation surgery: prospective targeting in treatment-resistant depression

Target identification and contact selection are known contributors to variability in efficacy across different clinical indications of deep brain stimulation surgery. A retrospective analysis of responders to subcallosal cingulate deep brain stimulation (SCC DBS) for depression demonstrated the common impact of the electrical stimulation on a stereotypic connectome of converging white matter bundles (forceps minor, uncinate fasciculus, cingulum and fronto-striatal fibers). To test the utility of a prospective connectomic approach for SCC DBS surgery, this pilot study used the four-bundle tractography 'connectome blueprint' to plan surgical targeting in 11 participants with treatment-resistant depression. Before surgery, targets were selected individually using deterministic tractography. Selection of contacts for chronic stimulation was made by matching the post-operative probabilistic tractography map to the pre-surgical deterministic tractography map for each subject. Intraoperative behavioral responses were used as a secondary verification of location. A probabilistic tract map of all participants demonstrated inclusion of the four bundles as intended, matching the connectome blueprint previously defined. Eight of 11 patients (72.7%) were responders and 5 were remitters after 6 months of open-label stimulation. At one year, 9 of 11 patients (81.8%) were responders, with 6 of them in remission. These results support the utility of a group probabilistic tractography map as a connectome blueprint for individualized, patient-specific, deterministic tractography targeting, confirming retrospective findings previously published. This new method represents a connectomic approach to guide future SCC DBS studies.

Characterization of the stimulus waveforms generated by implantable pulse generators for deep brain stimulation

OBJECTIVE

To determine the circuit elements required to theoretically describe the stimulus waveforms generated by an implantable pulse generator (IPG) during clinical deep brain stimulation (DBS).

METHODS

We experimentally interrogated the Medtronic Activa PC DBS IPG and defined an equivalent circuit model that accurately captured the output of the IPG. We then compared the detailed circuit model of the clinical stimulus waveforms to simplified representations commonly used in computational models of DBS. We quantified the errors associated with these simplifications using theoretical activation thresholds of myelinated axons in response to DBS.

RESULTS

We found that the detailed IPG model generated substantial differences in activation thresholds compared to simplified models. These differences were largest for bipolar stimulation with long pulse widths. Average errors were ∼3 to 24% for voltage-controlled stimulation and ∼2 to 11% for current-controlled stimulation.

CONCLUSIONS

Our results demonstrate the importance of including basic circuit elements (e.g. blocking capacitors, lead wire resistance, electrode capacitance) in model analysis of DBS.

SIGNIFICANCE

Computational models of DBS are now commonly used in academic research, industrial technology development, and in the selection of clinical stimulation parameters. Incorporating a realistic representation of the IPG output is necessary to improve the accuracy and utility of these clinical and scientific tools.

Impact of brain shift on subcallosal cingulate deep brain stimulation

BACKGROUND

Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) is an emerging experimental therapy for treatment-resistant depression. New developments in SCC DBS surgical targeting are focused on identifying specific axonal pathways for stimulation that are estimated from preoperatively collected diffusion-weighted imaging (DWI) data. However, brain shift induced by opening burr holes in the skull may alter the position of the target pathways.

OBJECTIVES

Quantify the effect of electrode location deviations on tractographic representations for stimulating the target pathways using longitudinal clinical imaging datasets.

METHODS

Preoperative MRI and DWI data (planned) were coregistered with postoperative MRI (1 day, near-term) and CT (3 weeks, long-term) data. Brain shift was measured with anatomical control points. Electrode models corresponding to the planned, near-term, and long-term locations were defined in each hemisphere of 15 patients. Tractography analyses were performed using estimated stimulation volumes as seeds centered on the different electrode positions.

RESULTS

Mean brain shift of 2.2 mm was observed in the near-term for the frontal pole, which resolved in the long-term. However, electrode displacements from the planned stereotactic target location were observed in the anterior-superior direction in both the near-term (mean left electrode shift: 0.43 mm, mean right electrode shift: 0.99 mm) and long-term (mean left electrode shift: 1.02 mm, mean right electrode shift: 1.47 mm). DBS electrodes implanted in the right hemisphere (second-side operated) were more displaced from the plan than those in the left hemisphere. These displacements resulted in 3.6% decrease in pathway activation between the electrode and the ventral striatum, but 2.7% increase in the frontal pole connection, compared to the plan. Remitters from six-month chronic stimulation had less variance in pathway activation patterns than the non-remitters.

CONCLUSIONS

Brain shift is an important concern for SCC DBS surgical targeting and can impact connectomic analyses.