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Closing the Loop With Cortical Sensing: The Development of Adaptive Deep Brain Stimulation for Essential Tremor Using the Activa PC+S

Deep Brain Stimulation (DBS) is an important tool in the treatment of pharmacologically resistant neurological movement disorders such as essential tremor (ET) and Parkinson's disease (PD). However, the open-loop design of current systems may be holding back the true potential of invasive neuro...

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Autores principales: Fra̧czek, Tomasz M., Ferleger, Benjamin I., Brown, Timothy E., Thompson, Margaret C., Haddock, Andrew J., Houston, Brady C., Ojemann, Jeffrey G., Ko, Andrew L., Herron, Jeffrey A., Chizeck, Howard J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8695120/
https://www.ncbi.nlm.nih.gov/pubmed/34955714
http://dx.doi.org/10.3389/fnins.2021.749705
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author Fra̧czek, Tomasz M.
Ferleger, Benjamin I.
Brown, Timothy E.
Thompson, Margaret C.
Haddock, Andrew J.
Houston, Brady C.
Ojemann, Jeffrey G.
Ko, Andrew L.
Herron, Jeffrey A.
Chizeck, Howard J.
author_facet Fra̧czek, Tomasz M.
Ferleger, Benjamin I.
Brown, Timothy E.
Thompson, Margaret C.
Haddock, Andrew J.
Houston, Brady C.
Ojemann, Jeffrey G.
Ko, Andrew L.
Herron, Jeffrey A.
Chizeck, Howard J.
author_sort Fra̧czek, Tomasz M.
collection PubMed
description Deep Brain Stimulation (DBS) is an important tool in the treatment of pharmacologically resistant neurological movement disorders such as essential tremor (ET) and Parkinson's disease (PD). However, the open-loop design of current systems may be holding back the true potential of invasive neuromodulation. In the last decade we have seen an explosion of activity in the use of feedback to “close the loop” on neuromodulation in the form of adaptive DBS (aDBS) systems that can respond to the patient's therapeutic needs. In this paper we summarize the accomplishments of a 5-year study at the University of Washington in the use of neural feedback from an electrocorticography strip placed over the sensorimotor cortex. We document our progress from an initial proof of hardware all the way to a fully implanted adaptive stimulation system that leverages machine-learning approaches to simplify the programming process. In certain cases, our systems out-performed current open-loop approaches in both power consumption and symptom suppression. Throughout this effort, we collaborated with neuroethicists to capture patient experiences and take them into account whilst developing ethical aDBS approaches. Based on our results we identify several key areas for future work. “Graded” aDBS will allow the system to smoothly tune the stimulation level to symptom severity, and frequent automatic calibration of the algorithm will allow aDBS to adapt to the time-varying dynamics of the disease without additional input from a clinician. Additionally, robust computational models of the pathophysiology of ET will allow stimulation to be optimized to the nuances of an individual patient's symptoms. We also outline the unique advantages of using cortical electrodes for control and the remaining hardware limitations that need to be overcome to facilitate further development in this field. Over the course of this study we have verified the potential of fully-implanted, cortically driven aDBS as a feasibly translatable treatment for pharmacologically resistant ET.
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spelling pubmed-86951202021-12-23 Closing the Loop With Cortical Sensing: The Development of Adaptive Deep Brain Stimulation for Essential Tremor Using the Activa PC+S Fra̧czek, Tomasz M. Ferleger, Benjamin I. Brown, Timothy E. Thompson, Margaret C. Haddock, Andrew J. Houston, Brady C. Ojemann, Jeffrey G. Ko, Andrew L. Herron, Jeffrey A. Chizeck, Howard J. Front Neurosci Neuroscience Deep Brain Stimulation (DBS) is an important tool in the treatment of pharmacologically resistant neurological movement disorders such as essential tremor (ET) and Parkinson's disease (PD). However, the open-loop design of current systems may be holding back the true potential of invasive neuromodulation. In the last decade we have seen an explosion of activity in the use of feedback to “close the loop” on neuromodulation in the form of adaptive DBS (aDBS) systems that can respond to the patient's therapeutic needs. In this paper we summarize the accomplishments of a 5-year study at the University of Washington in the use of neural feedback from an electrocorticography strip placed over the sensorimotor cortex. We document our progress from an initial proof of hardware all the way to a fully implanted adaptive stimulation system that leverages machine-learning approaches to simplify the programming process. In certain cases, our systems out-performed current open-loop approaches in both power consumption and symptom suppression. Throughout this effort, we collaborated with neuroethicists to capture patient experiences and take them into account whilst developing ethical aDBS approaches. Based on our results we identify several key areas for future work. “Graded” aDBS will allow the system to smoothly tune the stimulation level to symptom severity, and frequent automatic calibration of the algorithm will allow aDBS to adapt to the time-varying dynamics of the disease without additional input from a clinician. Additionally, robust computational models of the pathophysiology of ET will allow stimulation to be optimized to the nuances of an individual patient's symptoms. We also outline the unique advantages of using cortical electrodes for control and the remaining hardware limitations that need to be overcome to facilitate further development in this field. Over the course of this study we have verified the potential of fully-implanted, cortically driven aDBS as a feasibly translatable treatment for pharmacologically resistant ET. Frontiers Media S.A. 2021-12-08 /pmc/articles/PMC8695120/ /pubmed/34955714 http://dx.doi.org/10.3389/fnins.2021.749705 Text en Copyright © 2021 Fra̧czek, Ferleger, Brown, Thompson, Haddock, Houston, Ojemann, Ko, Herron and Chizeck. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Fra̧czek, Tomasz M.
Ferleger, Benjamin I.
Brown, Timothy E.
Thompson, Margaret C.
Haddock, Andrew J.
Houston, Brady C.
Ojemann, Jeffrey G.
Ko, Andrew L.
Herron, Jeffrey A.
Chizeck, Howard J.
Closing the Loop With Cortical Sensing: The Development of Adaptive Deep Brain Stimulation for Essential Tremor Using the Activa PC+S
title Closing the Loop With Cortical Sensing: The Development of Adaptive Deep Brain Stimulation for Essential Tremor Using the Activa PC+S
title_full Closing the Loop With Cortical Sensing: The Development of Adaptive Deep Brain Stimulation for Essential Tremor Using the Activa PC+S
title_fullStr Closing the Loop With Cortical Sensing: The Development of Adaptive Deep Brain Stimulation for Essential Tremor Using the Activa PC+S
title_full_unstemmed Closing the Loop With Cortical Sensing: The Development of Adaptive Deep Brain Stimulation for Essential Tremor Using the Activa PC+S
title_short Closing the Loop With Cortical Sensing: The Development of Adaptive Deep Brain Stimulation for Essential Tremor Using the Activa PC+S
title_sort closing the loop with cortical sensing: the development of adaptive deep brain stimulation for essential tremor using the activa pc+s
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8695120/
https://www.ncbi.nlm.nih.gov/pubmed/34955714
http://dx.doi.org/10.3389/fnins.2021.749705
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