Browsing by Author "Howell, Bryan"

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    Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example.
    (PloS one, 2017-01) Gunalan, Kabilar; Chaturvedi, Ashutosh; Howell, Bryan; Duchin, Yuval; Lempka, Scott F; Patriat, Remi; Sapiro, Guillermo; Harel, Noam; McIntyre, Cameron C

    Background

    Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports.

    Objective

    Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation.

    Methods

    Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python) enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson's disease (PD). This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution.

    Results

    Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings.

    Conclusion

    Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation.
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    Design and in vivo evaluation of more efficient and selective deep brain stimulation electrodes.
    (Journal of neural engineering, 2015-08) Howell, Bryan; Huynh, Brian; Grill, Warren M

    Objective

    Deep brain stimulation (DBS) is an effective treatment for movement disorders and a promising therapy for treating epilepsy and psychiatric disorders. Despite its clinical success, the efficiency and selectivity of DBS can be improved. Our objective was to design electrode geometries that increased the efficiency and selectivity of DBS.

    Approach

    We coupled computational models of electrodes in brain tissue with cable models of axons of passage (AOPs), terminating axons (TAs), and local neurons (LNs); we used engineering optimization to design electrodes for stimulating these neural elements; and the model predictions were tested in vivo.

    Main results

    Compared with the standard electrode used in the Medtronic Model 3387 and 3389 arrays, model-optimized electrodes consumed 45-84% less power. Similar gains in selectivity were evident with the optimized electrodes: 50% of parallel AOPs could be activated while reducing activation of perpendicular AOPs from 44 to 48% with the standard electrode to 0-14% with bipolar designs; 50% of perpendicular AOPs could be activated while reducing activation of parallel AOPs from 53 to 55% with the standard electrode to 1-5% with an array of cathodes; and, 50% of TAs could be activated while reducing activation of AOPs from 43 to 100% with the standard electrode to 2-15% with a distal anode. In vivo, both the geometry and polarity of the electrode had a profound impact on the efficiency and selectivity of stimulation.

    Significance

    Model-based design is a powerful tool that can be used to improve the efficiency and selectivity of DBS electrodes.
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    Design of Electrodes for Efficient and Selective Electrical Stimulation of Nervous Tissue
    (2015) Howell, Bryan

    Modulation of neural activity with electrical stimulation is a widespread therapy for treating neurological disorders and diseases. Two notable applications that have had striking clinical success are deep brain stimulation (DBS) for the treatment of movement disorders (e.g., Parkinson's disease) and spinal cord stimulation (SCS) for the treatment of chronic low back and limb pain. In these therapies, the battery life of the stimulators is much less than the required duration of treatment, requiring patients to undergo repeated battery replacement surgeries, which are costly and obligate them to incur repeatedly the risks associated with surgery. Further, deviations in lead position of 2-3 mm can preclude some or all potential clinical benefits, and in some cases, generate side-effects by stimulation of non-target regions. Therefore, despite the success of DBS and SCS, their efficiency and ability to activate target neural elements over non-target elements, termed selectivity, are inadequate and need improvement.

    We combined computational models of volume conduction in the brain and spine with cable models of neurons to design novel electrode configurations for efficient and selective electrical stimulation of nervous tissue. We measured the efficiency and selectivity of prototype electrode designs in vitro and in vivo. Stimulation efficiency was increased by increasing electrode area and/or perimeter, but the effect of increasing perimeter was not as pronounced as increasing area. Cylindrical electrodes with aspect (height to diameter) ratios of > 5 were the most efficient for stimulating neural elements oriented perpendicular to the axis of the electrode, whereas electrodes with aspect ratios of < 2 were the most efficient for stimulating parallel neural elements.

    Stimulation selectivity was increased by combining two or more electrodes in multipolar configurations. Asymmetric bipolar configurations were optimal for activating parallel axons over perpendicular axons; arrays of cathodes with short interelectrode spacing were optimal for activating perpendicular axons over parallel axons; anodes displaced from the center of the target region were optimal for selectively activating terminating axons over passing axons; and symmetric tripolar configurations were optimal for activating neural elements based on their proximity to the electrode. The performance of the efficient and selective designs was not be explained solely by differences in their electrical properties, suggesting that field-shaping effects from changing electrode geometry and polarity can be as large as or larger than the effects of decreasing electrode impedance.

    Advancing our understanding of the features of electrode geometry that are important for increasing stimulation efficiency and selectivity facilitates the design of the next generation of stimulation electrodes for the brain and spinal cord. Increased stimulation efficiency will increase the battery life of IPGs, increase the recharge interval of rechargeable IPGs, and potentially reduce stimulator volume. Greater selectivity may improve the success rate of DBS and SCS by mitigating the sensitivity of clinical outcomes to malpositioning of the electrode.

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    Effects of frequency-dependent membrane capacitance on neural excitability.
    (Journal of neural engineering, 2015-10) Howell, Bryan; Medina, Leonel E; Grill, Warren M

    Objective

    Models of excitable cells consider the membrane specific capacitance as a ubiquitous and constant parameter. However, experimental measurements show that the membrane capacitance declines with increasing frequency, i.e., exhibits dispersion. We quantified the effects of frequency-dependent membrane capacitance, c(f), on the excitability of cells and nerve fibers across the frequency range from dc to hundreds of kilohertz.

    Approach

    We implemented a model of c(f) using linear circuit elements, and incorporated it into several models of neurons with different channel kinetics: the Hodgkin-Huxley model of an unmyelinated axon, the McIntyre-Richardson-Grill (MRG) of a mammalian myelinated axon, and a model of a cortical neuron from prefrontal cortex (PFC). We calculated thresholds for excitation and kHz frequency conduction block, the conduction velocity, recovery cycle, strength-distance relationship and firing rate.

    Main results

    The impact of c(f) on activation thresholds depended on the stimulation waveform and channel kinetics. We observed no effect using rectangular pulse stimulation, and a reduction for frequencies of 10 kHz and above using sinusoidal signals only for the MRG model. c(f) had minimal impact on the recovery cycle and the strength-distance relationship, whereas the conduction velocity increased by up to 7.9% and 1.7% for myelinated and unmyelinated fibers, respectively. Block thresholds declined moderately when incorporating c(f), the effect was greater at higher frequencies, and the maximum reduction was 11.5%. Finally, c(f) marginally altered the firing pattern of a model of a PFC cell, reducing the median interspike interval by less than 2%.

    Significance

    This is the first comprehensive analysis of the effects of dispersive capacitance on neural excitability, and as the interest on stimulation with kHz signals gains more attention, it defines the regions over which frequency-dependent membrane capacitance, c(f), should be considered.
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    Evaluation of high-perimeter electrode designs for deep brain stimulation.
    (Journal of neural engineering, 2014-08) Howell, Bryan; Grill, Warren M

    Objective

    Deep brain stimulation (DBS) is an effective treatment for movement disorders and a promising therapy for treating epilepsy and psychiatric disorders. Despite its clinical success, complications including infections and mis-programing following surgical replacement of the battery-powered implantable pulse generator adversely impact the safety profile of this therapy. We sought to decrease power consumption and extend battery life by modifying the electrode geometry to increase stimulation efficiency. The specific goal of this study was to determine whether electrode contact perimeter or area had a greater effect on increasing stimulation efficiency.

    Approach

    Finite-element method (FEM) models of eight prototype electrode designs were used to calculate the electrode access resistance, and the FEM models were coupled with cable models of passing axons to quantify stimulation efficiency. We also measured in vitro the electrical properties of the prototype electrode designs and measured in vivo the stimulation efficiency following acute implantation in anesthetized cats.

    Main results

    Area had a greater effect than perimeter on altering the electrode access resistance; electrode (access or dynamic) resistance alone did not predict stimulation efficiency because efficiency was dependent on the shape of the potential distribution in the tissue; and, quantitative assessment of stimulation efficiency required consideration of the effects of the electrode-tissue interface impedance.

    Significance

    These results advance understanding of the features of electrode geometry that are important for designing the next generation of efficient DBS electrodes.
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    Evaluation of intradural stimulation efficiency and selectivity in a computational model of spinal cord stimulation.
    (PloS one, 2014-01) Howell, Bryan; Lad, Shivanand P; Grill, Warren M
    Spinal cord stimulation (SCS) is an alternative or adjunct therapy to treat chronic pain, a prevalent and clinically challenging condition. Although SCS has substantial clinical success, the therapy is still prone to failures, including lead breakage, lead migration, and poor pain relief. The goal of this study was to develop a computational model of SCS and use the model to compare activation of neural elements during intradural and extradural electrode placement. We constructed five patient-specific models of SCS. Stimulation thresholds predicted by the model were compared to stimulation thresholds measured intraoperatively, and we used these models to quantify the efficiency and selectivity of intradural and extradural SCS. Intradural placement dramatically increased stimulation efficiency and reduced the power required to stimulate the dorsal columns by more than 90%. Intradural placement also increased selectivity, allowing activation of a greater proportion of dorsal column fibers before spread of activation to dorsal root fibers, as well as more selective activation of individual dermatomes at different lateral deviations from the midline. Further, the results suggest that current electrode designs used for extradural SCS are not optimal for intradural SCS, and a novel azimuthal tripolar design increased stimulation selectivity, even beyond that achieved with an intradural paddle array. Increased stimulation efficiency is expected to increase the battery life of implantable pulse generators, increase the recharge interval of rechargeable implantable pulse generators, and potentially reduce stimulator volume. The greater selectivity of intradural stimulation may improve the success rate of SCS by mitigating the sensitivity of pain relief to malpositioning of the electrode. The outcome of this effort is a better quantitative understanding of how intradural electrode placement can potentially increase the selectivity and efficiency of SCS, which, in turn, provides predictions that can be tested in future clinical studies assessing the potential therapeutic benefits of intradural SCS.
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    Feasibility of Interferential and Pulsed Transcranial Electrical Stimulation for Neuromodulation at the Human Scale.
    (Neuromodulation : journal of the International Neuromodulation Society, 2021-07) Howell, Bryan; McIntyre, Cameron C

    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.
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    Influences of interpolation error, electrode geometry, and the electrode-tissue interface on models of electric fields produced by deep brain stimulation.
    (IEEE transactions on bio-medical engineering, 2014-02) Howell, Bryan; Naik, Sagar; Grill, Warren M
    Deep brain stimulation (DBS) is an established therapy for movement disorders, but the fundamental mechanisms by which DBS has its effects remain unknown. Computational models can provide insights into the mechanisms of DBS, but to be useful, the models must have sufficient detail to predict accurately the electric fields produced by DBS. We used a finite-element method model of the Medtronic 3387 electrode array, coupled to cable models of myelinated axons, to quantify how interpolation errors, electrode geometry, and the electrode-tissue interface affect calculation of electrical potentials and stimulation thresholds for populations of model nerve fibers. Convergence of the potentials was not a sufficient criterion for ensuring the same degree of accuracy in subsequent determination of stimulation thresholds, because the accuracy of the stimulation thresholds depended on the order of the elements. Simplifying the 3387 electrode array by ignoring the inactive contacts and extending the terminated end of the shaft had position-dependent effects on the potentials and excitation thresholds, and these simplifications may impact correlations between DBS parameters and clinical outcomes. When the current density in the bulk tissue is uniform, the effect of the electrode-tissue interface impedance could be approximated by filtering the potentials calculated with a static lumped electrical equivalent circuit. Further, for typical DBS parameters during voltage-regulated stimulation, it was valid to approximate the electrode as an ideal polarized electrode with a nonlinear capacitance. Validation of these computational considerations enables accurate modeling of the electric field produced by DBS.
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    Stimulation Efficiency With Decaying Exponential Waveforms in a Wirelessly Powered Switched-Capacitor Discharge Stimulation System.
    (IEEE transactions on bio-medical engineering, 2018-05) Lee, Hyung-Min; Howell, Bryan; Grill, Warren M; Ghovanloo, Maysam
    The purpose of this study was to test the feasibility of using a switched-capacitor discharge stimulation (SCDS) system for electrical stimulation, and, subsequently, determine the overall energy saved compared to a conventional stimulator. We have constructed a computational model by pairing an image-based volume conductor model of the cat head with cable models of corticospinal tract (CST) axons and quantified the theoretical stimulation efficiency of rectangular and decaying exponential waveforms, produced by conventional and SCDS systems, respectively. Subsequently, the model predictions were tested in vivo by activating axons in the posterior internal capsule and recording evoked electromyography (EMG) in the contralateral upper arm muscles. Compared to rectangular waveforms, decaying exponential waveforms with time constants >500 μs were predicted to require 2%-4% less stimulus energy to activate directly models of CST axons and 0.4%-2% less stimulus energy to evoke EMG activity in vivo. Using the calculated wireless input energy of the stimulation system and the measured stimulus energies required to evoke EMG activity, we predict that an SCDS implantable pulse generator (IPG) will require 40% less input energy than a conventional IPG to activate target neural elements. A wireless SCDS IPG that is more energy efficient than a conventional IPG will reduce the size of an implant, require that less wireless energy be transmitted through the skin, and extend the lifetime of the battery in the external power transmitter.
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    StimVision v2: Examples and Applications in Subthalamic Deep Brain Stimulation for Parkinson's Disease.
    (Neuromodulation : journal of the International Neuromodulation Society, 2021-02) Noecker, Angela M; Frankemolle-Gilbert, Anneke M; Howell, Bryan; Petersen, Mikkel V; Beylergil, Sinem Balta; Shaikh, Aasef G; McIntyre, Cameron C

    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.