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

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dc.citation.articleNumber13403en_US
dc.citation.journalTitleScientific Reportsen_US
dc.citation.volumeNumber13en_US
dc.contributor.authorFan, Boqiangen_US
dc.contributor.authorGoodman, Wayneen_US
dc.contributor.authorCho, Raymond Y.en_US
dc.contributor.authorSheth, Sameer A.en_US
dc.contributor.authorBouchard, Richard R.en_US
dc.contributor.authorAazhang, Behnaamen_US
dc.date.accessioned2024-05-03T15:51:20Zen_US
dc.date.available2024-05-03T15:51:20Zen_US
dc.date.issued2023en_US
dc.description.abstractThe 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.en_US
dc.identifier.citationFan, B., Goodman, W., Cho, R. Y., Sheth, S. A., Bouchard, R. R., & Aazhang, B. (2023). Computational modeling and minimization of unintended neuronal excitation in a LIFU stimulation. Scientific Reports, 13(1), 13403. https://doi.org/10.1038/s41598-023-40522-wen_US
dc.identifier.digitals41598-023-40522-wen_US
dc.identifier.doihttps://doi.org/10.1038/s41598-023-40522-wen_US
dc.identifier.urihttps://hdl.handle.net/1911/115624en_US
dc.language.isoengen_US
dc.publisherSpringer Natureen_US
dc.rightsExcept where otherwise noted, this work is licensed under a Creative Commons Attribution (CC BY) license. Permission to reuse, publish, or reproduce the work beyond the terms of the license or beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titleComputational modeling and minimization of unintended neuronal excitation in a LIFU stimulationen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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