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A neurochemical closed-loop controller for deep brain stimulation: toward individualized smart neuromodulation therapies
Current strategies for optimizing deep brain stimulation (DBS) therapy involve multiple postoperative visits. During each visit, stimulation parameters are adjusted until desired therapeutic effects are achieved and adverse effects are minimized. However, the efficacy of these therapeutic parameters...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4070176/ https://www.ncbi.nlm.nih.gov/pubmed/25009455 http://dx.doi.org/10.3389/fnins.2014.00169 |
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author | Grahn, Peter J. Mallory, Grant W. Khurram, Obaid U. Berry, B. Michael Hachmann, Jan T. Bieber, Allan J. Bennet, Kevin E. Min, Hoon-Ki Chang, Su-Youne Lee, Kendall H. Lujan, J. L. |
author_facet | Grahn, Peter J. Mallory, Grant W. Khurram, Obaid U. Berry, B. Michael Hachmann, Jan T. Bieber, Allan J. Bennet, Kevin E. Min, Hoon-Ki Chang, Su-Youne Lee, Kendall H. Lujan, J. L. |
author_sort | Grahn, Peter J. |
collection | PubMed |
description | Current strategies for optimizing deep brain stimulation (DBS) therapy involve multiple postoperative visits. During each visit, stimulation parameters are adjusted until desired therapeutic effects are achieved and adverse effects are minimized. However, the efficacy of these therapeutic parameters may decline with time due at least in part to disease progression, interactions between the host environment and the electrode, and lead migration. As such, development of closed-loop control systems that can respond to changing neurochemical environments, tailoring DBS therapy to individual patients, is paramount for improving the therapeutic efficacy of DBS. Evidence obtained using electrophysiology and imaging techniques in both animals and humans suggests that DBS works by modulating neural network activity. Recently, animal studies have shown that stimulation-evoked changes in neurotransmitter release that mirror normal physiology are associated with the therapeutic benefits of DBS. Therefore, to fully understand the neurophysiology of DBS and optimize its efficacy, it may be necessary to look beyond conventional electrophysiological analyses and characterize the neurochemical effects of therapeutic and non-therapeutic stimulation. By combining electrochemical monitoring and mathematical modeling techniques, we can potentially replace the trial-and-error process used in clinical programming with deterministic approaches that help attain optimal and stable neurochemical profiles. In this manuscript, we summarize the current understanding of electrophysiological and electrochemical processing for control of neuromodulation therapies. Additionally, we describe a proof-of-principle closed-loop controller that characterizes DBS-evoked dopamine changes to adjust stimulation parameters in a rodent model of DBS. The work described herein represents the initial steps toward achieving a “smart” neuroprosthetic system for treatment of neurologic and psychiatric disorders. |
format | Online Article Text |
id | pubmed-4070176 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-40701762014-07-09 A neurochemical closed-loop controller for deep brain stimulation: toward individualized smart neuromodulation therapies Grahn, Peter J. Mallory, Grant W. Khurram, Obaid U. Berry, B. Michael Hachmann, Jan T. Bieber, Allan J. Bennet, Kevin E. Min, Hoon-Ki Chang, Su-Youne Lee, Kendall H. Lujan, J. L. Front Neurosci Neuroscience Current strategies for optimizing deep brain stimulation (DBS) therapy involve multiple postoperative visits. During each visit, stimulation parameters are adjusted until desired therapeutic effects are achieved and adverse effects are minimized. However, the efficacy of these therapeutic parameters may decline with time due at least in part to disease progression, interactions between the host environment and the electrode, and lead migration. As such, development of closed-loop control systems that can respond to changing neurochemical environments, tailoring DBS therapy to individual patients, is paramount for improving the therapeutic efficacy of DBS. Evidence obtained using electrophysiology and imaging techniques in both animals and humans suggests that DBS works by modulating neural network activity. Recently, animal studies have shown that stimulation-evoked changes in neurotransmitter release that mirror normal physiology are associated with the therapeutic benefits of DBS. Therefore, to fully understand the neurophysiology of DBS and optimize its efficacy, it may be necessary to look beyond conventional electrophysiological analyses and characterize the neurochemical effects of therapeutic and non-therapeutic stimulation. By combining electrochemical monitoring and mathematical modeling techniques, we can potentially replace the trial-and-error process used in clinical programming with deterministic approaches that help attain optimal and stable neurochemical profiles. In this manuscript, we summarize the current understanding of electrophysiological and electrochemical processing for control of neuromodulation therapies. Additionally, we describe a proof-of-principle closed-loop controller that characterizes DBS-evoked dopamine changes to adjust stimulation parameters in a rodent model of DBS. The work described herein represents the initial steps toward achieving a “smart” neuroprosthetic system for treatment of neurologic and psychiatric disorders. Frontiers Media S.A. 2014-06-25 /pmc/articles/PMC4070176/ /pubmed/25009455 http://dx.doi.org/10.3389/fnins.2014.00169 Text en Copyright © 2014 Grahn, Mallory, Khurram, Berry, Hachmann, Bieber, Bennet, Min, Chang, Lee and Lujan. http://creativecommons.org/licenses/by/3.0/ 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) or licensor 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 Grahn, Peter J. Mallory, Grant W. Khurram, Obaid U. Berry, B. Michael Hachmann, Jan T. Bieber, Allan J. Bennet, Kevin E. Min, Hoon-Ki Chang, Su-Youne Lee, Kendall H. Lujan, J. L. A neurochemical closed-loop controller for deep brain stimulation: toward individualized smart neuromodulation therapies |
title | A neurochemical closed-loop controller for deep brain stimulation: toward individualized smart neuromodulation therapies |
title_full | A neurochemical closed-loop controller for deep brain stimulation: toward individualized smart neuromodulation therapies |
title_fullStr | A neurochemical closed-loop controller for deep brain stimulation: toward individualized smart neuromodulation therapies |
title_full_unstemmed | A neurochemical closed-loop controller for deep brain stimulation: toward individualized smart neuromodulation therapies |
title_short | A neurochemical closed-loop controller for deep brain stimulation: toward individualized smart neuromodulation therapies |
title_sort | neurochemical closed-loop controller for deep brain stimulation: toward individualized smart neuromodulation therapies |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4070176/ https://www.ncbi.nlm.nih.gov/pubmed/25009455 http://dx.doi.org/10.3389/fnins.2014.00169 |
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