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Computational modeling and minimization of unintended neuronal excitation in a LIFU stimulation

The neuromodulation effect of low-intensity focused ultrasound (LIFU) is highly target-specific. Unintended off-target neuronal excitation can be elicited when the beam focusing accuracy and resolution are limited, whereas the resulted side effect has not been evaluated quantitatively. There is also...

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Autores principales: Fan, Boqiang, Goodman, Wayne, Cho, Raymond Y., Sheth, Sameer A., Bouchard, Richard R., Aazhang, Behnaam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10435497/
https://www.ncbi.nlm.nih.gov/pubmed/37591991
http://dx.doi.org/10.1038/s41598-023-40522-w
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author Fan, Boqiang
Goodman, Wayne
Cho, Raymond Y.
Sheth, Sameer A.
Bouchard, Richard R.
Aazhang, Behnaam
author_facet Fan, Boqiang
Goodman, Wayne
Cho, Raymond Y.
Sheth, Sameer A.
Bouchard, Richard R.
Aazhang, Behnaam
author_sort Fan, Boqiang
collection PubMed
description The neuromodulation effect of low-intensity focused ultrasound (LIFU) is highly target-specific. Unintended off-target neuronal excitation can be elicited when the beam focusing accuracy and resolution are limited, whereas the resulted side effect has not been evaluated quantitatively. There is also a lack of methods addressing the minimization of such side effects. Therefore, this work introduces a computational model of unintended neuronal excitation during LIFU neuromodulation, which evaluates the off-target activation area (OTAA) by integrating an ultrasound field model with the neuronal spiking model. In addition, a phased array beam focusing scheme called constrained optimal resolution beamforming (CORB) is proposed to minimize the off-target neuronal excitation area while ensuring effective stimulation in the target brain region. A lower bound of the OTAA is analytically approximated in a simplified homogeneous medium, which could guide the selection of transducer parameters such as aperture size and operating frequency. Simulations in a human head model using three transducer setups show that CORB markedly reduces the OTAA compared with two benchmark beam focusing methods. The high neuromodulation resolution demonstrates the capability of LIFU to effectively limit the side effects during neuromodulation, allowing future clinical applications such as treatment of neuropsychiatric disorders.
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spelling pubmed-104354972023-08-19 Computational modeling and minimization of unintended neuronal excitation in a LIFU stimulation Fan, Boqiang Goodman, Wayne Cho, Raymond Y. Sheth, Sameer A. Bouchard, Richard R. Aazhang, Behnaam Sci Rep Article The neuromodulation effect of low-intensity focused ultrasound (LIFU) is highly target-specific. Unintended off-target neuronal excitation can be elicited when the beam focusing accuracy and resolution are limited, whereas the resulted side effect has not been evaluated quantitatively. There is also a lack of methods addressing the minimization of such side effects. Therefore, this work introduces a computational model of unintended neuronal excitation during LIFU neuromodulation, which evaluates the off-target activation area (OTAA) by integrating an ultrasound field model with the neuronal spiking model. In addition, a phased array beam focusing scheme called constrained optimal resolution beamforming (CORB) is proposed to minimize the off-target neuronal excitation area while ensuring effective stimulation in the target brain region. A lower bound of the OTAA is analytically approximated in a simplified homogeneous medium, which could guide the selection of transducer parameters such as aperture size and operating frequency. Simulations in a human head model using three transducer setups show that CORB markedly reduces the OTAA compared with two benchmark beam focusing methods. The high neuromodulation resolution demonstrates the capability of LIFU to effectively limit the side effects during neuromodulation, allowing future clinical applications such as treatment of neuropsychiatric disorders. Nature Publishing Group UK 2023-08-17 /pmc/articles/PMC10435497/ /pubmed/37591991 http://dx.doi.org/10.1038/s41598-023-40522-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Fan, Boqiang
Goodman, Wayne
Cho, Raymond Y.
Sheth, Sameer A.
Bouchard, Richard R.
Aazhang, Behnaam
Computational modeling and minimization of unintended neuronal excitation in a LIFU stimulation
title Computational modeling and minimization of unintended neuronal excitation in a LIFU stimulation
title_full Computational modeling and minimization of unintended neuronal excitation in a LIFU stimulation
title_fullStr Computational modeling and minimization of unintended neuronal excitation in a LIFU stimulation
title_full_unstemmed Computational modeling and minimization of unintended neuronal excitation in a LIFU stimulation
title_short Computational modeling and minimization of unintended neuronal excitation in a LIFU stimulation
title_sort computational modeling and minimization of unintended neuronal excitation in a lifu stimulation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10435497/
https://www.ncbi.nlm.nih.gov/pubmed/37591991
http://dx.doi.org/10.1038/s41598-023-40522-w
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