Artifact characterization and mitigation techniques during concurrent sensing and stimulation using bidirectional deep brain stimulation platforms
Bidirectional deep brain stimulation (DBS) platforms have enabled a surge in hours of recordings in naturalistic environments, allowing further insight into neurological and psychiatric disease states. However, high amplitude, high frequency stimulation generates artifacts that contaminate neural si...
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Published in | Frontiers in human neuroscience Vol. 16; p. 1016379 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers Research Foundation
19.10.2022
Frontiers Media S.A |
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Online Access | Get full text |
ISSN | 1662-5161 1662-5161 |
DOI | 10.3389/fnhum.2022.1016379 |
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Abstract | Bidirectional deep brain stimulation (DBS) platforms have enabled a surge in hours of recordings in naturalistic environments, allowing further insight into neurological and psychiatric disease states. However, high amplitude, high frequency stimulation generates artifacts that contaminate neural signals and hinder our ability to interpret the data. This is especially true in psychiatric disorders, for which high amplitude stimulation is commonly applied to deep brain structures where the native neural activity is miniscule in comparison. Here, we characterized artifact sources in recordings from a bidirectional DBS platform, the Medtronic Summit RC + S, with the goal of optimizing recording configurations to improve signal to noise ratio (SNR). Data were collected from three subjects in a clinical trial of DBS for obsessive-compulsive disorder. Stimulation was provided bilaterally to the ventral capsule/ventral striatum (VC/VS) using two independent implantable neurostimulators. We first manipulated DBS amplitude within safe limits (2–5.3 mA) to characterize the impact of stimulation artifacts on neural recordings. We found that high amplitude stimulation produces slew overflow, defined as exceeding the rate of change that the analog to digital converter can accurately measure. Overflow led to expanded spectral distortion of the stimulation artifact, with a six fold increase in the bandwidth of the 150.6 Hz stimulation artifact from 147–153 to 140–180 Hz. By increasing sense blank values during high amplitude stimulation, we reduced overflow by as much as 30% and improved artifact distortion, reducing the bandwidth from 140–180 Hz artifact to 147–153 Hz. We also identified artifacts that shifted in frequency through modulation of telemetry parameters. We found that telemetry ratio changes led to predictable shifts in the center-frequencies of the associated artifacts, allowing us to proactively shift the artifacts outside of our frequency range of interest. Overall, the artifact characterization methods and results described here enable increased data interpretability and unconstrained biomarker exploration using data collected from bidirectional DBS devices. |
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AbstractList | Bidirectional deep brain stimulation (DBS) platforms have enabled a surge in hours of recordings in naturalistic environments, allowing further insight into neurological and psychiatric disease states. However, high amplitude, high frequency stimulation generates artifacts that contaminate neural signals and hinder our ability to interpret the data. This is especially true in psychiatric disorders, for which high amplitude stimulation is commonly applied to deep brain structures where the native neural activity is miniscule in comparison. Here, we characterized artifact sources in recordings from a bidirectional DBS platform, the Medtronic Summit RC + S, with the goal of optimizing recording configurations to improve signal to noise ratio (SNR). Data were collected from three subjects in a clinical trial of DBS for obsessive-compulsive disorder. Stimulation was provided bilaterally to the ventral capsule/ventral striatum (VC/VS) using two independent implantable neurostimulators. We first manipulated DBS amplitude within safe limits (2–5.3 mA) to characterize the impact of stimulation artifacts on neural recordings. We found that high amplitude stimulation produces slew overflow, defined as exceeding the rate of change that the analog to digital converter can accurately measure. Overflow led to expanded spectral distortion of the stimulation artifact, with a six fold increase in the bandwidth of the 150.6 Hz stimulation artifact from 147–153 to 140–180 Hz. By increasing sense blank values during high amplitude stimulation, we reduced overflow by as much as 30% and improved artifact distortion, reducing the bandwidth from 140–180 Hz artifact to 147–153 Hz. We also identified artifacts that shifted in frequency through modulation of telemetry parameters. We found that telemetry ratio changes led to predictable shifts in the center-frequencies of the associated artifacts, allowing us to proactively shift the artifacts outside of our frequency range of interest. Overall, the artifact characterization methods and results described here enable increased data interpretability and unconstrained biomarker exploration using data collected from bidirectional DBS devices. Bidirectional deep brain stimulation (DBS) platforms have enabled a surge in hours of recordings in naturalistic environments, allowing further insight into neurological and psychiatric disease states. However, high amplitude, high frequency stimulation generates artifacts that contaminate neural signals and hinder our ability to interpret the data. This is especially true in psychiatric disorders, for which high amplitude stimulation is commonly applied to deep brain structures where the native neural activity is miniscule in comparison. Here, we characterized artifact sources in recordings from a bidirectional DBS platform, the Medtronic Summit RC + S, with the goal of optimizing recording configurations to improve signal to noise ratio (SNR). Data were collected from three subjects in a clinical trial of DBS for obsessive-compulsive disorder. Stimulation was provided bilaterally to the ventral capsule/ventral striatum (VC/VS) using two independent implantable neurostimulators. We first manipulated DBS amplitude within safe limits (2-5.3 mA) to characterize the impact of stimulation artifacts on neural recordings. We found that high amplitude stimulation produces slew overflow, defined as exceeding the rate of change that the analog to digital converter can accurately measure. Overflow led to expanded spectral distortion of the stimulation artifact, with a six fold increase in the bandwidth of the 150.6 Hz stimulation artifact from 147-153 to 140-180 Hz. By increasing sense blank values during high amplitude stimulation, we reduced overflow by as much as 30% and improved artifact distortion, reducing the bandwidth from 140-180 Hz artifact to 147-153 Hz. We also identified artifacts that shifted in frequency through modulation of telemetry parameters. We found that telemetry ratio changes led to predictable shifts in the center-frequencies of the associated artifacts, allowing us to proactively shift the artifacts outside of our frequency range of interest. Overall, the artifact characterization methods and results described here enable increased data interpretability and unconstrained biomarker exploration using data collected from bidirectional DBS devices.Bidirectional deep brain stimulation (DBS) platforms have enabled a surge in hours of recordings in naturalistic environments, allowing further insight into neurological and psychiatric disease states. However, high amplitude, high frequency stimulation generates artifacts that contaminate neural signals and hinder our ability to interpret the data. This is especially true in psychiatric disorders, for which high amplitude stimulation is commonly applied to deep brain structures where the native neural activity is miniscule in comparison. Here, we characterized artifact sources in recordings from a bidirectional DBS platform, the Medtronic Summit RC + S, with the goal of optimizing recording configurations to improve signal to noise ratio (SNR). Data were collected from three subjects in a clinical trial of DBS for obsessive-compulsive disorder. Stimulation was provided bilaterally to the ventral capsule/ventral striatum (VC/VS) using two independent implantable neurostimulators. We first manipulated DBS amplitude within safe limits (2-5.3 mA) to characterize the impact of stimulation artifacts on neural recordings. We found that high amplitude stimulation produces slew overflow, defined as exceeding the rate of change that the analog to digital converter can accurately measure. Overflow led to expanded spectral distortion of the stimulation artifact, with a six fold increase in the bandwidth of the 150.6 Hz stimulation artifact from 147-153 to 140-180 Hz. By increasing sense blank values during high amplitude stimulation, we reduced overflow by as much as 30% and improved artifact distortion, reducing the bandwidth from 140-180 Hz artifact to 147-153 Hz. We also identified artifacts that shifted in frequency through modulation of telemetry parameters. We found that telemetry ratio changes led to predictable shifts in the center-frequencies of the associated artifacts, allowing us to proactively shift the artifacts outside of our frequency range of interest. Overall, the artifact characterization methods and results described here enable increased data interpretability and unconstrained biomarker exploration using data collected from bidirectional DBS devices. Bidirectional deep brain stimulation (DBS) platforms have enabled a surge in hours of recordings in naturalistic environments, allowing further insight into neurological and psychiatric disease states. However, high amplitude, high frequency stimulation generates artifacts that contaminate neural signals and hinder our ability to interpret the data. This is especially true in psychiatric disorders, for which high amplitude stimulation is commonly applied to deep brain structures where the native neural activity is miniscule in comparison. Here, we characterized artifact sources in recordings from a bidirectional DBS platform, the Medtronic Summit RC+S, with the goal of optimizing recording configurations to improve signal to noise ratio (SNR). Data were collected from three subjects in a clinical trial of DBS for obsessive-compulsive disorder. Stimulation was provided bilaterally to the ventral capsule/ventral striatum (VC/VS) using two independent implantable neurostimulators. We first manipulated DBS amplitude within safe limits (2-5.3 mA) to characterize the impact of stimulation artifacts on neural recordings. We found that high amplitude stimulation produces slew overflow, defined as exceeding the rate of change that the analog to digital converter can accurately measure. Overflow led to expanded spectral distortion of the stimulation artifact, with a six fold increase in the bandwidth of the 150.6 Hz stimulation artifact from 147-153 Hz to 140-180 Hz. By increasing sense blank values during high amplitude stimulation, we reduced overflow by as much as 30% and improved artifact distortion, reducing the bandwidth from 140-180 Hz artifact to 147-153 Hz. We also identified artifacts that shifted in frequency through modulation of telemetry parameters. We found that telemetry ratio changes led to predictable shifts in the center-frequencies of the associated artifacts, allowing us to proactively shift the artifacts outside of our frequency range of interest. Overall, the artifact characterization methods and results described here enable increased data interpretability and unconstrained biomarker exploration using data collected from bidirectional DBS devices. |
Author | Provenza, Nicole R. Alarie, Michaela E. Avendano-Ortega, Michelle Goodman, Wayne K. Sheth, Sameer A. McKay, Sarah A. Mathura, Raissa K. Herron, Jeffrey A. Borton, David A. Waite, Ayan S. |
AuthorAffiliation | 5 Department of Veterans Affairs, Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service , Providence, RI , United States 1 Brown University School of Engineering , Providence, RI , United States 2 Department of Neurosurgery, Baylor College of Medicine , Houston, TX , United States 4 Department of Neurological Surgery, University of Washington , Seattle, WA , United States 3 Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine , Houston, TX , United States |
AuthorAffiliation_xml | – name: 5 Department of Veterans Affairs, Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service , Providence, RI , United States – name: 1 Brown University School of Engineering , Providence, RI , United States – name: 2 Department of Neurosurgery, Baylor College of Medicine , Houston, TX , United States – name: 4 Department of Neurological Surgery, University of Washington , Seattle, WA , United States – name: 3 Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine , Houston, TX , United States |
Author_xml | – sequence: 1 givenname: Michaela E. surname: Alarie fullname: Alarie, Michaela E. – sequence: 2 givenname: Nicole R. surname: Provenza fullname: Provenza, Nicole R. – sequence: 3 givenname: Michelle surname: Avendano-Ortega fullname: Avendano-Ortega, Michelle – sequence: 4 givenname: Sarah A. surname: McKay fullname: McKay, Sarah A. – sequence: 5 givenname: Ayan S. surname: Waite fullname: Waite, Ayan S. – sequence: 6 givenname: Raissa K. surname: Mathura fullname: Mathura, Raissa K. – sequence: 7 givenname: Jeffrey A. surname: Herron fullname: Herron, Jeffrey A. – sequence: 8 givenname: Sameer A. surname: Sheth fullname: Sheth, Sameer A. – sequence: 9 givenname: David A. surname: Borton fullname: Borton, David A. – sequence: 10 givenname: Wayne K. surname: Goodman fullname: Goodman, Wayne K. |
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Cites_doi | 10.1016/j.brs.2021.08.016 10.1016/j.brs.2022.03.002 10.1088/1741-2552/ac59a3 10.1101/2022.02.09.22270606 10.1038/s41591-021-01550-z 10.1159/000521431 10.3389/fneur.2019.00410 10.1109/TBCAS.2018.2880148 10.1109/TNSRE.2012.2183617 10.48550/arXiv.2204.03778 10.1016/j.brs.2018.11.014 10.1016/j.biopsych.2014.03.029 10.1088/1741-2552/ac1d5b 10.1016/j.brs.2021.08.010 10.1016/j.crmeth.2021.100010 10.3389/fnhum.2021.714256 10.1101/2022.05.23.493124 10.1176/appi.ajp.2020.20111601 10.1038/s41587-021-00897-5 10.1016/j.expneurol.2021.113825 10.1097/00004691-200401000-00007 10.1016/j.conb.2018.01.012 10.3389/fpsyt.2018.00302 10.3389/fneur.2021.704170 10.1111/epi.17047 10.1038/sj.npp.1301165 10.3389/fnins.2021.748165 |
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Copyright | Copyright © 2022 Alarie, Provenza, Avendano-Ortega, McKay, Waite, Mathura, Herron, Sheth, Borton and Goodman. 2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. Copyright © 2022 Alarie, Provenza, Avendano-Ortega, McKay, Waite, Mathura, Herron, Sheth, Borton and Goodman. 2022 Alarie, Provenza, Avendano-Ortega, McKay, Waite, Mathura, Herron, Sheth, Borton and Goodman |
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Keywords | implantable devices neuromodulation deep brain stimulation artifact characterization bidirectional platforms |
Language | English |
License | Copyright © 2022 Alarie, Provenza, Avendano-Ortega, McKay, Waite, Mathura, Herron, Sheth, Borton and Goodman. 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. |
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SubjectTerms | artifact characterization bidirectional platforms Biomarkers Communication Data transmission Deep brain stimulation Human Neuroscience implantable devices Mental disorders Neostriatum neuromodulation Obsessive compulsive disorder Telemetry |
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Title | Artifact characterization and mitigation techniques during concurrent sensing and stimulation using bidirectional deep brain stimulation platforms |
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