ABSTRACT
Deep brain stimulation (DBS) of the internal segment of the globus pallidus (GPi) can markedly reduce muscle rigidity in people with Parkinson's disease (PD); however, the mechanisms mediating this effect are poorly understood. Computational modeling of DBS provides a method to estimate the relative contributions of neural pathway activations to changes in outcomes. In this study, we generated patient-specific biophysical models of GPi DBS (derived from individual 7T MRI) - including pallidal efferent, putamenal efferent and internal capsule pathways - to investigate how activation of neural pathways contributed to changes in forearm rigidity in PD. Ten individuals (17 arms) were tested off medication under four conditions: off stimulation, on clinically optimized stimulation, and on stimulation specifically targeting the dorsal GPi or ventral GPi. Quantitative measures of forearm rigidity, with and without a contralateral activation maneuver, were obtained using a robotic manipulandum. Clinically optimized GPi DBS settings significantly reduced forearm rigidity (p < 0.001), which aligned with GPi efferent fiber activation. The model demonstrated that GPi efferent axons could be activated at any location along the GPi dorsal-ventral axis. These results provide evidence that rigidity reduction produced by GPi DBS is mediated by preferential activation of GPi efferents to the thalamus, likely leading to a reduction in excitability of the muscle stretch reflex via overdriving pallidofugal output.
ABSTRACT
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for Parkinson's disease, but its mechanisms of action remain unclear. Detailed multicompartment computational models of STN neurons are often used to study how DBS electric fields modulate the neurons. However, currently available STN neuron models have some limitations in their biophysical realism. In turn, the goal of this study was to update a detailed rodent STN neuron model originally developed by Gillies and Willshaw in 2006. Our design requirements consisted of explicitly representing an axon connected to the neuron and updating the ion channel distributions based on the experimental literature to match established electrophysiological features of rodent STN neurons. We found that adding an axon to the STN neuron model substantially altered its firing characteristics. We then used a genetic algorithm to optimize biophysical parameters of the model. The updated model exhibited spontaneous firing, action potential shape, hyperpolarization response, and frequency-current curve that aligned well with experimental recordings from STN neurons. Subsequently, we evaluated the general compatibility of the updated biophysics by applying them to 26 different STN neuron morphologies derived from three-dimensional anatomical reconstructions. The different morphologies affected the firing behavior of the model, but the updated biophysics were robustly capable of maintaining the desired electrophysiological features. The new STN neuron model developed in this work offers a valuable tool for studying STN neuron firing properties and may find application in simulating STN local field potentials and analyzing the effects of STN DBS.NEW & NOTEWORTHY This study presents an anatomically and biophysically realistic rodent STN neuron model. The work showcases the use of a genetic algorithm to optimize the model parameters. We noted a substantial influence of the axon on the electrophysiological characteristics of STN neurons. The updated model offers a valuable tool to investigate the firing of STN neurons and their modulation by intrinsic and/or extrinsic factors.
Subject(s)
Action Potentials , Models, Neurological , Neurons , Subthalamic Nucleus , Subthalamic Nucleus/physiology , Subthalamic Nucleus/cytology , Animals , Neurons/physiology , Action Potentials/physiology , Rats , Axons/physiology , Deep Brain StimulationABSTRACT
Deep brain stimulation (DBS) is an effective treatment for Parkinson's disease (PD); however, there is limited understanding of which subthalamic pathways are recruited in response to stimulation. Here, by focusing on the polarity of the stimulus waveform (cathodic vs. anodic), our goal was to elucidate biophysical mechanisms that underlie electrical stimulation in the human brain. In clinical studies, cathodic stimulation more easily triggers behavioral responses, but anodic DBS broadens the therapeutic window. This suggests that neural pathways involved respond preferentially depending on stimulus polarity. To experimentally compare the activation of therapeutically relevant pathways during cathodic and anodic subthalamic nucleus (STN) DBS, pathway activation was quantified by measuring evoked potentials resulting from antidromic or orthodromic activation in 15 PD patients undergoing DBS implantation. Cortical evoked potentials (cEP) were recorded using subdural electrocorticography, DBS local evoked potentials (DLEP) were recorded from non-stimulating contacts and EMG activity was recorded from arm and face muscles. We measured: 1) the amplitude of short-latency cEP, previously demonstrated to reflect activation of the cortico-STN hyperdirect pathway, 2) DLEP amplitude thought to reflect activation of STN-globus pallidus (GP) pathway, and 3) amplitudes of very short-latency cEP and motor evoked potentials (mEP) for activation of cortico-spinal/bulbar tract (CSBT). We constructed recruitment and strength-duration curves for each EP/pathway to compare the excitability for different stimulation polarities. We compared experimental data with the most advanced DBS computational models. Our results provide experimental evidence that subcortical cathodic and anodic stimulation activate the same pathways in the STN region and that cathodic stimulation is in general more efficient. However, relative efficiency varies for different pathways so that anodic stimulation is the least efficient in activating CSBT, more efficient in activating the HDP and as efficient as cathodic in activating STN-GP pathway. Our experiments confirm biophysical model predictions regarding neural activations in the central nervous system and provide evidence that stimulus polarity has differential effects on passing axons, terminal synapses, and local neurons. Comparison of experimental results with clinical DBS studies provides further evidence that the hyperdirect pathway may be involved in the therapeutic mechanisms of DBS.
ABSTRACT
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.
Subject(s)
Basal Ganglia , Deep Brain Stimulation , Evoked Potentials , Parkinson Disease , Deep Brain Stimulation/methods , Humans , Basal Ganglia/physiology , Basal Ganglia/physiopathology , Evoked Potentials/physiology , Parkinson Disease/therapy , Parkinson Disease/physiopathology , Animals , Globus Pallidus/physiology , Subthalamic Nucleus/physiologyABSTRACT
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.
Subject(s)
Deep Brain Stimulation , White Matter , Humans , Deep Brain Stimulation/methods , Gyrus Cinguli/physiology , Corpus Callosum , Evoked PotentialsABSTRACT
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.
ABSTRACT
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.
Subject(s)
Deep Brain Stimulation , Essential Tremor , Parkinson Disease , Subthalamic Nucleus , Zona Incerta , Humans , Subthalamic Nucleus/physiology , Parkinson Disease/therapy , Essential Tremor/therapyABSTRACT
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.
Subject(s)
Axons , Neurons , Animals , Mice , Axons/physiology , Neurons/physiology , Electric Stimulation/methods , Models, NeurologicalABSTRACT
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.
Subject(s)
Deep Brain Stimulation , Motion Perception , Parkinson Disease , Subthalamic Nucleus , Humans , Parkinson Disease/therapy , Deep Brain Stimulation/methods , Subthalamic Nucleus/physiology , ThalamusABSTRACT
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.
Subject(s)
Deep Brain Stimulation , Parkinson Disease , Subthalamic Nucleus , Humans , Parkinson Disease/therapy , Subthalamic Nucleus/physiology , Axons , ElectrodesABSTRACT
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.
Subject(s)
Deep Brain Stimulation , Nervous System Diseases , Humans , Models, Neurological , Computer Simulation , Electrodes , Brain/physiologyABSTRACT
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.
Subject(s)
Brain-Computer Interfaces , Humans , Brain , ComputersABSTRACT
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.
Subject(s)
Deep Brain Stimulation , Mental Disorders , Humans , Prospective Studies , Deep Brain Stimulation/methods , Brain/diagnostic imaging , Mental Disorders/therapy , ElectroencephalographyABSTRACT
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.
Subject(s)
Deep Brain Stimulation , Depressive Disorder, Treatment-Resistant , Epilepsy , Humans , Epilepsy/therapy , Electroencephalography/methods , Depressive Disorder, Treatment-Resistant/therapy , Electrodes , Deep Brain Stimulation/methods , Electrodes, ImplantedABSTRACT
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.
Subject(s)
Deep Brain Stimulation , Subthalamic Nucleus , Humans , Deep Brain Stimulation/methods , Subthalamic Nucleus/physiology , Electrodes , Beta Rhythm/physiology , Models, NeurologicalABSTRACT
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.
Subject(s)
Deep Brain Stimulation , Parkinson Disease , Subthalamic Nucleus , Humans , Subthalamic Nucleus/physiology , Deep Brain Stimulation/methods , Axons/physiology , Neurons/physiology , Parkinson Disease/therapyABSTRACT
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.
Subject(s)
Deep Brain Stimulation , Parkinson Disease , Subthalamic Nucleus , Humans , Stereotaxic Techniques , Deep Brain Stimulation/methods , Parkinson Disease/diagnostic imaging , Parkinson Disease/surgery , Subthalamic Nucleus/diagnostic imaging , Subthalamic Nucleus/surgery , Subthalamic Nucleus/anatomy & histology , Electrodes, Implanted , Magnetic Resonance Imaging/methodsABSTRACT
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.
Subject(s)
Deep Brain Stimulation , Mental Disorders , Neurosurgery , Psychosurgery , Humans , United States , Neurosurgical Procedures , Mental Disorders/surgeryABSTRACT
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.