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Saalmann YB, Mofakham S, Mikell CB, Djuric PM. Microscale multicircuit brain stimulation: Achieving real-time brain state control for novel applications. CURRENT RESEARCH IN NEUROBIOLOGY 2022; 4:100071. [PMID: 36619175 PMCID: PMC9816916 DOI: 10.1016/j.crneur.2022.100071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 11/30/2022] [Accepted: 12/19/2022] [Indexed: 12/30/2022] Open
Abstract
Neurological and psychiatric disorders typically result from dysfunction across multiple neural circuits. Most of these disorders lack a satisfactory neuromodulation treatment. However, deep brain stimulation (DBS) has been successful in a limited number of disorders; DBS typically targets one or two brain areas with single contacts on relatively large electrodes, allowing for only coarse modulation of circuit function. Because of the dysfunction in distributed neural circuits - each requiring fine, tailored modulation - that characterizes most neuropsychiatric disorders, this approach holds limited promise. To develop the next generation of neuromodulation therapies, we will have to achieve fine-grained, closed-loop control over multiple neural circuits. Recent work has demonstrated spatial and frequency selectivity using microstimulation with many small, closely-spaced contacts, mimicking endogenous neural dynamics. Using custom electrode design and stimulation parameters, it should be possible to achieve bidirectional control over behavioral outcomes, such as increasing or decreasing arousal during central thalamic stimulation. Here, we discuss one possible approach, which we term microscale multicircuit brain stimulation (MMBS). We discuss how machine learning leverages behavioral and neural data to find optimal stimulation parameters across multiple contacts, to drive the brain towards desired states associated with behavioral goals. We expound a mathematical framework for MMBS, where behavioral and neural responses adjust the model in real-time, allowing us to adjust stimulation in real-time. These technologies will be critical to the development of the next generation of neurostimulation therapies, which will allow us to treat problems like disorders of consciousness and cognition.
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Affiliation(s)
- Yuri B. Saalmann
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA,Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI, USA,Corresponding author. Department of Psychology, University of Wisconsin-Madison, 1202 W Johnson St, Madison, WI, 53706, USA.
| | - Sima Mofakham
- Department of Neurological Surgery, Stony Brook University Hospital, Stony Brook, NY, USA,Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Charles B. Mikell
- Department of Neurological Surgery, Stony Brook University Hospital, Stony Brook, NY, USA
| | - Petar M. Djuric
- Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA
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Kang W, Ju C, Joo J, Lee J, Shon YM, Park SM. Closed-loop direct control of seizure focus in a rodent model of temporal lobe epilepsy via localized electric fields applied sequentially. Nat Commun 2022; 13:7805. [PMID: 36528681 PMCID: PMC9759546 DOI: 10.1038/s41467-022-35540-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 12/09/2022] [Indexed: 12/23/2022] Open
Abstract
Direct electrical stimulation of the seizure focus can achieve the early termination of epileptic oscillations. However, direct intervention of the hippocampus, the most prevalent seizure focus in temporal lobe epilepsy is thought to be not practicable due to its large size and elongated shape. Here, in a rat model, we report a sequential narrow-field stimulation method for terminating seizures, while focusing stimulus energy at the spatially extensive hippocampal structure. The effects and regional specificity of this method were demonstrated via electrophysiological and biological responses. Our proposed modality demonstrates spatiotemporal preciseness and selectiveness for modulating the pathological target region which may have potential for further investigation as a therapeutic approach.
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Affiliation(s)
- Wonok Kang
- grid.49100.3c0000 0001 0742 4007School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.49100.3c0000 0001 0742 4007Medical Device Innovation Center, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea
| | - Chanyang Ju
- grid.49100.3c0000 0001 0742 4007Medical Device Innovation Center, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.49100.3c0000 0001 0742 4007Department of Convergence IT Engineering, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea
| | - Jaesoon Joo
- grid.264381.a0000 0001 2181 989XBiomedical Engineering Research Center, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, 06351 South Korea
| | - Jiho Lee
- grid.49100.3c0000 0001 0742 4007Medical Device Innovation Center, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.49100.3c0000 0001 0742 4007Department of Convergence IT Engineering, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea
| | - Young-Min Shon
- grid.264381.a0000 0001 2181 989XBiomedical Engineering Research Center, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, 06351 South Korea ,grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, 06351 Republic of Korea
| | - Sung-Min Park
- grid.49100.3c0000 0001 0742 4007School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.49100.3c0000 0001 0742 4007Medical Device Innovation Center, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.49100.3c0000 0001 0742 4007Department of Convergence IT Engineering, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.49100.3c0000 0001 0742 4007Department of Electrical Engineering, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.49100.3c0000 0001 0742 4007Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.15444.300000 0004 0470 5454Institute of Convergence Science, Yonsei University, Seoul, 03722 Republic of Korea
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Aubignat M, Lefranc M, Tir M, Krystkowiak P. Deep brain stimulation programming in Parkinson's disease: Introduction of current issues and perspectives. Rev Neurol (Paris) 2020; 176:770-779. [DOI: 10.1016/j.neurol.2020.02.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Revised: 01/28/2020] [Accepted: 02/12/2020] [Indexed: 12/11/2022]
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Vorwerk J, McCann D, Krüger J, Butson CR. Interactive computation and visualization of deep brain stimulation effects using Duality. COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION 2020; 8:3-14. [PMID: 32742820 DOI: 10.1080/21681163.2018.1484817] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Deep brain stimulation (DBS) is an established treatment for movement disorders such as Parkinson's disease or essential tremor. Currently, the selection of optimal stimulation settings is performed by iteratively adjusting the stimulation parameters and is a time consuming procedure that requires multiple clinic visits of several hours. Recently, computational models to predict and visualize the effect of DBS have been developed with the goal to simplify and accelerate this procedure by providing visual guidance and such models have been made available also on mobile devices. However, currently available visualization software still either lacks mobility, i.e., it is running on desktop computers and not easily available in clinical praxis, or flexibility, as the simulations that are visualized on mobile devices have to be precomputed. The goal of the pipeline presented in this paper is to close this gap: Using Duality, a newly developed software for the interactive visualization of simulation results, we implemented a pipeline that allows to compute DBS simulations in near-real time and instantaneously visualize the result on a tablet computer. Therefore, a client-server setup is used, so that the visualization and user interaction occur on the tablet computer, while the computations are carried out on a remote server. We present two examples for the use of Duality, one for postoperative programming and one for the planning of DBS surgery in a pre- or intraoperative setting. We carry out a performance analysis and present the results of a case study in which the pipeline for postoperative programming was applied.
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Affiliation(s)
- J Vorwerk
- Scientific Computing & Imaging (SCI) Institute, Department of Bioengineering, University of Utah, Salt Lake City, UT-8f112, USA
| | - D McCann
- Scientific Computing & Imaging (SCI) Institute, Department of Bioengineering, University of Utah, Salt Lake City, UT-8f112, USA
| | - J Krüger
- Center of Visual Data Analysis and Computer Graphics (COVIDAG) & HPC Group, University of Duisburg-Essen, 47057 Duisburg, Germany.,Scientific Computing & Imaging (SCI) Institute, Department of Bioengineering, University of Utah, Salt Lake City, UT-8f112, USA
| | - C R Butson
- Scientific Computing & Imaging (SCI) Institute, Department of Bioengineering, University of Utah, Salt Lake City, UT-8f112, USA
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Bogdan ID, van Laar T, Oterdoom DM, Drost G, van Dijk JMC, Beudel M. Optimal Parameters of Deep Brain Stimulation in Essential Tremor: A Meta-Analysis and Novel Programming Strategy. J Clin Med 2020; 9:jcm9061855. [PMID: 32545887 PMCID: PMC7356338 DOI: 10.3390/jcm9061855] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 06/04/2020] [Accepted: 06/09/2020] [Indexed: 01/10/2023] Open
Abstract
The programming of deep brain stimulation (DBS) parameters for tremor is laborious and empirical. Despite extensive efforts, the end-result is often suboptimal. One reason for this is the poorly understood relationship between the stimulation parameters’ voltage, pulse width, and frequency. In this study, we aim to improve DBS programming for essential tremor (ET) by exploring a new strategy. At first, the role of the individual DBS parameters in tremor control was characterized using a meta-analysis documenting all the available parameters and tremor outcomes. In our novel programming strategy, we applied 10 random combinations of stimulation parameters in eight ET-DBS patients with suboptimal tremor control. Tremor severity was assessed using accelerometers and immediate and sustained patient-reported outcomes (PRO’s), including the occurrence of side-effects. The meta-analysis showed no substantial relationship between individual DBS parameters and tremor suppression. Nevertheless, with our novel programming strategy, a significantly improved (accelerometer p = 0.02, PRO p = 0.02) and sustained (p = 0.01) tremor suppression compared to baseline was achieved. Less side-effects were encountered compared to baseline. Our pilot data show that with this novel approach, tremor control can be improved in ET patients with suboptimal tremor control on DBS. In addition, this approach proved to have a beneficial effect on stimulation-related complications.
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Affiliation(s)
- I. Daria Bogdan
- Department of Neurology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (I.D.B.); (G.D.)
- Department of Neurosurgery, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (D.L.M.O.); (J.M.C.v.D.)
| | - Teus van Laar
- Department of Neurology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (I.D.B.); (G.D.)
- Correspondence:
| | - D.L. Marinus Oterdoom
- Department of Neurosurgery, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (D.L.M.O.); (J.M.C.v.D.)
| | - Gea Drost
- Department of Neurology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (I.D.B.); (G.D.)
- Department of Neurosurgery, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (D.L.M.O.); (J.M.C.v.D.)
| | - J. Marc C. van Dijk
- Department of Neurosurgery, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (D.L.M.O.); (J.M.C.v.D.)
| | - Martijn Beudel
- Department of Neurology, Amsterdam Neuroscience Institute, Amsterdam University Medical Center, 1007 MB Amsterdam, The Netherlands;
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Vorwerk J, Brock AA, Anderson DN, Rolston JD, Butson CR. A retrospective evaluation of automated optimization of deep brain stimulation parameters. J Neural Eng 2019; 16:064002. [PMID: 31344689 PMCID: PMC7759010 DOI: 10.1088/1741-2552/ab35b1] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
OBJECTIVE We performed a retrospective analysis of an optimization algorithm for the computation of patient-specific multipolar stimulation configurations employing multiple independent current/voltage sources. We evaluated whether the obtained stimulation configurations align with clinical data and whether the optimized stimulation configurations have the potential to lead to an equal or better stimulation of the target region as manual programming, while reducing the time required for programming sessions. APPROACH For three patients (five electrodes) diagnosed with essential tremor, we derived optimized multipolar stimulation configurations using an approach that is suitable for the application in clinical practice. To evaluate the automatically derived stimulation settings, we compared them to the results of the monopolar review. MAIN RESULTS We observe a good agreement between the findings of the monopolar review and the optimized stimulation configurations, with the algorithm assigning the maximal voltage in the optimized multipolar pattern to the contact that was found to lead to the best therapeutic effect in the clinical monopolar review in all cases. Additionally, our simulation results predict that the optimized stimulation settings lead to the activation of an equal or larger volume fraction of the target compared to the manually determined settings in all cases. SIGNIFICANCE Our results demonstrate the feasibility of an automatic determination of optimal DBS configurations and motivate a further evaluation of the applied optimization algorithm.
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Affiliation(s)
- Johannes Vorwerk
- Scientific Computing & Imaging (SCI) Institute, University of Utah, Salt Lake City, Utah, USA,Institute of Electrical and Biomedical Engineering, UMIT - Private University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
| | - Andrea A. Brock
- Scientific Computing & Imaging (SCI) Institute, University of Utah, Salt Lake City, Utah, USA,Department of Neurosurgery, University of Utah, Salt Lake City, Utah, USA
| | - Daria N. Anderson
- Scientific Computing & Imaging (SCI) Institute, University of Utah, Salt Lake City, Utah, USA,Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
| | - John D. Rolston
- Department of Neurosurgery, University of Utah, Salt Lake City, Utah, USA,Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
| | - Christopher R. Butson
- Scientific Computing & Imaging (SCI) Institute, University of Utah, Salt Lake City, Utah, USA,Department of Neurosurgery, University of Utah, Salt Lake City, Utah, USA,Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA,Departments of Psychiatry and Neurology, University of Utah, Salt Lake City, Utah, USA,Correspondig Author.
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Anderson DN, Anderson C, Lanka N, Sharma R, Butson CR, Baker BW, Dorval AD. The μDBS: Multiresolution, Directional Deep Brain Stimulation for Improved Targeting of Small Diameter Fibers. Front Neurosci 2019; 13:1152. [PMID: 31736693 PMCID: PMC6828644 DOI: 10.3389/fnins.2019.01152] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Accepted: 10/11/2019] [Indexed: 11/25/2022] Open
Abstract
Directional deep brain stimulation (DBS) leads have recently been approved and used in patients, and growing evidence suggests that directional contacts can increase the therapeutic window by redirecting stimulation to the target region while avoiding side-effect-inducing regions. We outline the design, fabrication, and testing of a novel directional DBS lead, the μDBS, which utilizes microscale contacts to increase the spatial resolution of stimulation steering and improve the selectivity in targeting small diameter fibers. We outline the steps of fabrication of the μDBS, from an integrated circuit design to post-processing and validation testing. We tested the onboard digital circuitry for programming fidelity, characterized impedance for a variety of electrode sizes, and demonstrated functionality in a saline bath. In a computational experiment, we determined that reduced electrode sizes focus the stimulation effect on small, nearby fibers. Smaller electrode sizes allow for a relative decrease in small-diameter axon thresholds compared to thresholds of large-diameter fibers, demonstrating a focusing of the stimulation effect within small, and possibly therapeutic, fibers. This principle of selectivity could be useful in further widening the window of therapy. The μDBS offers a unique, multiresolution design in which any combination of microscale contacts can be used together to function as electrodes of various shapes and sizes. Multiscale electrodes could be useful in selective neural targeting for established neurological targets and in exploring novel treatment targets for new neurological indications.
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Affiliation(s)
- Daria Nesterovich Anderson
- Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
- Department of Neurosurgery, School of Medicine, University of Utah, Salt Lake City, UT, United States
- Scientific Computing and Imaging (SCI) Institute, University of Utah, Salt Lake City, UT, United States
| | - Connor Anderson
- Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
| | - Nikhita Lanka
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, United States
| | - Rohit Sharma
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, United States
| | - Christopher R. Butson
- Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
- Department of Neurosurgery, School of Medicine, University of Utah, Salt Lake City, UT, United States
- Scientific Computing and Imaging (SCI) Institute, University of Utah, Salt Lake City, UT, United States
- Department of Neurology, School of Medicine, University of Utah, Salt Lake City, UT, United States
- Department of Psychiatry, School of Medicine, University of Utah, Salt Lake City, UT, United States
| | - Brian W. Baker
- Utah Nanofab, University of Utah, Salt Lake City, UT, United States
| | - Alan D. Dorval
- Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
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Anderson DN, Osting B, Vorwerk J, Dorval AD, Butson CR. Optimized programming algorithm for cylindrical and directional deep brain stimulation electrodes. J Neural Eng 2019; 15:026005. [PMID: 29235446 DOI: 10.1088/1741-2552/aaa14b] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Deep brain stimulation (DBS) is a growing treatment option for movement and psychiatric disorders. As DBS technology moves toward directional leads with increased numbers of smaller electrode contacts, trial-and-error methods of manual DBS programming are becoming too time-consuming for clinical feasibility. We propose an algorithm to automate DBS programming in near real-time for a wide range of DBS lead designs. APPROACH Magnetic resonance imaging and diffusion tensor imaging are used to build finite element models that include anisotropic conductivity. The algorithm maximizes activation of target tissue and utilizes the Hessian matrix of the electric potential to approximate activation of neurons in all directions. We demonstrate our algorithm's ability in an example programming case that targets the subthalamic nucleus (STN) for the treatment of Parkinson's disease for three lead designs: the Medtronic 3389 (four cylindrical contacts), the direct STNAcute (two cylindrical contacts, six directional contacts), and the Medtronic-Sapiens lead (40 directional contacts). MAIN RESULTS The optimization algorithm returns patient-specific contact configurations in near real-time-less than 10 s for even the most complex leads. When the lead was placed centrally in the target STN, the directional leads were able to activate over 50% of the region, whereas the Medtronic 3389 could activate only 40%. When the lead was placed 2 mm lateral to the target, the directional leads performed as well as they did in the central position, but the Medtronic 3389 activated only 2.9% of the STN. SIGNIFICANCE This DBS programming algorithm can be applied to cylindrical electrodes as well as novel directional leads that are too complex with modern technology to be manually programmed. This algorithm may reduce clinical programming time and encourage the use of directional leads, since they activate a larger volume of the target area than cylindrical electrodes in central and off-target lead placements.
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Affiliation(s)
- Daria Nesterovich Anderson
- Department of Bioengineering, University of Utah, Salt Lake City, UT, United States of America. Scientific Computing & Imaging (SCI) Institute, University of Utah, Salt Lake City, UT, United States of America
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Åström M, Samuelsson J, Roothans J, Fytagoridis A, Ryzhkov M, Nijlunsing R, Blomstedt P. Prediction of Electrode Contacts for Clinically Effective Deep Brain Stimulation in Essential Tremor. Stereotact Funct Neurosurg 2018; 96:281-288. [DOI: 10.1159/000492230] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2017] [Accepted: 07/18/2018] [Indexed: 11/19/2022]
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Janson AP, Butson CR. Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models. J Vis Exp 2018. [PMID: 30148495 PMCID: PMC6126786 DOI: 10.3791/57292] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Deep brain stimulation (DBS), which involves insertion of an electrode to deliver stimulation to a localized brain region, is an established therapy for movement disorders and is being applied to a growing number of disorders. Computational modeling has been successfully used to predict the clinical effects of DBS; however, there is a need for novel modeling techniques to keep pace with the growing complexity of DBS devices. These models also need to generate predictions quickly and accurately. The goal of this project is to develop an image processing pipeline to incorporate structural magnetic resonance imaging (MRI) and diffusion weighted imaging (DWI) into an interactive, patient specific model to simulate the effects of DBS. A virtual DBS lead can be placed inside of the patient model, along with active contacts and stimulation settings, where changes in lead position or orientation generate a new finite element mesh and solution of the bioelectric field problem in near real-time, a timespan of approximately 10 seconds. This system also enables the simulation of multiple leads in close proximity to allow for current steering by varying anodes and cathodes on different leads. The techniques presented in this paper reduce the burden of generating and using computational models while providing meaningful feedback about the effects of electrode position, electrode design, and stimulation configurations to researchers or clinicians who may not be modeling experts.
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Affiliation(s)
- Andrew P Janson
- Scientific Computing and Imaging (SCI) Institute, Department of Biomedical Engineering, University of Utah
| | - Christopher R Butson
- Scientific Computing and Imaging (SCI) Institute, Department of Biomedical Engineering, University of Utah;
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Teplitzky BA, Zitella LM, Xiao Y, Johnson MD. Model-Based Comparison of Deep Brain Stimulation Array Functionality with Varying Number of Radial Electrodes and Machine Learning Feature Sets. Front Comput Neurosci 2016; 10:58. [PMID: 27375470 PMCID: PMC4901081 DOI: 10.3389/fncom.2016.00058] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2016] [Accepted: 05/27/2016] [Indexed: 12/29/2022] Open
Abstract
Deep brain stimulation (DBS) leads with radially distributed electrodes have potential to improve clinical outcomes through more selective targeting of pathways and networks within the brain. However, increasing the number of electrodes on clinical DBS leads by replacing conventional cylindrical shell electrodes with radially distributed electrodes raises practical design and stimulation programming challenges. We used computational modeling to investigate: (1) how the number of radial electrodes impact the ability to steer, shift, and sculpt a region of neural activation (RoA), and (2) which RoA features are best used in combination with machine learning classifiers to predict programming settings to target a particular area near the lead. Stimulation configurations were modeled using 27 lead designs with one to nine radially distributed electrodes. The computational modeling framework consisted of a three-dimensional finite element tissue conductance model in combination with a multi-compartment biophysical axon model. For each lead design, two-dimensional threshold-dependent RoAs were calculated from the computational modeling results. The models showed more radial electrodes enabled finer resolution RoA steering; however, stimulation amplitude, and therefore spatial extent of the RoA, was limited by charge injection and charge storage capacity constraints due to the small electrode surface area for leads with more than four radially distributed electrodes. RoA shifting resolution was improved by the addition of radial electrodes when using uniform multi-cathode stimulation, but non-uniform multi-cathode stimulation produced equivalent or better resolution shifting without increasing the number of radial electrodes. Robust machine learning classification of 15 monopolar stimulation configurations was achieved using as few as three geometric features describing a RoA. The results of this study indicate that, for a clinical-scale DBS lead, more than four radial electrodes minimally improved in the ability to steer, shift, and sculpt axonal activation around a DBS lead and a simple feature set consisting of the RoA center of mass and orientation enabled robust machine learning classification. These results provide important design constraints for future development of high-density DBS arrays.
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Affiliation(s)
| | - Laura M. Zitella
- Department of Biomedical Engineering, University of MinnesotaMinneapolis, MN, USA
| | - YiZi Xiao
- Department of Biomedical Engineering, University of MinnesotaMinneapolis, MN, USA
| | - Matthew D. Johnson
- Department of Biomedical Engineering, University of MinnesotaMinneapolis, MN, USA
- Institute for Translational Neuroscience, University of MinnesotaMinneapolis, MN, USA
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Connolly AT, Vetter RJ, Hetke JF, Teplitzky BA, Kipke DR, Pellinen DS, Anderson DJ, Baker KB, Vitek JL, Johnson MD. A Novel Lead Design for Modulation and Sensing of Deep Brain Structures. IEEE Trans Biomed Eng 2015; 63:148-57. [PMID: 26529747 DOI: 10.1109/tbme.2015.2492921] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
GOAL Develop and characterize the functionality of a novel thin-film probe technology with a higher density of electrode contacts than are currently available with commercial deep brain stimulation (DBS) lead technology. Such technology has potential to enhance the spatial precision of DBS and enable a more robust approach to sensing local field potential activity in the context of adaptive DBS strategies. METHODS Thin-film planar arrays were microfabricated and then assembled on a cylindrical carrier to achieve a lead with 3-D conformation. Using an integrated and removable stylet, the arrays were chronically implanted in the subthalamic nucleus and globus pallidus in two parkinsonian nonhuman primates. RESULTS This study provides the first in vivo data from chronically implanted DBS arrays for translational nonhuman primate studies. Stimulation through the arrays induced a decrease in parkinsonian rigidity, and directing current around the lead showed an orientation dependence for eliciting motor capsule side effects. The array recordings also showed that oscillatory activity in the basal ganglia is heterogeneous at a smaller scale than detected by the current DBS lead technology. CONCLUSION These 3-D DBS arrays provide an enabling tool for future studies that seek to monitor and modulate deep brain activity through chronically implanted leads. SIGNIFICANCE DBS lead technology with a higher density of electrode contacts has potential to enable sculpting DBS current flow and sensing biomarkers of disease and therapy.
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