Design of Multichannel Transcranial Temporal Interfering Stimulation System Using an Individual MRI

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Abstract

Transcranial temporal interfering stimulation (tTIS) is an electrical stimulation method, in which two high-frequency alternating electric fields generate interference in the deep brain. This study aimed to design and verify the performance of a system that can precisely stimulate the deep brain using a multichannel tTIS based on an MRI image of an individual’s brain. The optimization process, based on the parallel genetic algorithm with a GPU, was computationally verified using a modeled head that housed the deep brain. The hardware digitally stimulated the pre-interpreted head in a calculative manner, and the performance of the method was verified using an ideal head circuit. When four or more electrodes per frequency were used to stimulate the left thalamus, the rate of misstimulation was controlled to less than 2% on average for approximately 1 min. In the absence of deep-brain modeling, the average stimulus applied was reduced to 77.9%. The predicted signal had a 98.21% coefficient of determination for the modulations obtained by stimulating a head-type circuit using the proposed hardware. We designed a system that can stimulate the deep region of the brain through a multichannel tTIS, with due consideration for its practical application during the entire process. CCS CONCEPTS: • Theory and algorithms for application domains → Theory and algorithms for application domains; • Computing methodologies → Modeling and simulation; • Applied computing → Physical sciences and engineering
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Abstract Transcranial temporal interfering stimulation (tTIS) is an electrical stimulation method, in which two high-frequency alternating electric fields generate interference in the deep brain. This study aimed to design and verify the performance of a system that can precisely stimulate the deep brain using a multichannel tTIS based on an MRI image of an individual’s brain. The optimization process, based on the parallel genetic algorithm with a GPU, was computationally verified using a modeled head that housed the deep brain. The hardware digitally stimulated the pre-interpreted head in a calculative manner, and the performance of the method was verified using an ideal head circuit. When four or more electrodes per frequency were used to stimulate the left thalamus, the rate of misstimulation was controlled to less than 2% on average for approximately 1 min. In the absence of deep-brain modeling, the average stimulus applied was reduced to 77.9%. The predicted signal had a 98.21% coefficient of determination for the modulations obtained by stimulating a head-type circuit using the proposed hardware. We designed a system that can stimulate the deep region of the brain through a multichannel tTIS, with due consideration for its practical application during the entire process. CCS CONCEPTS: • Theory and algorithms for application domains → Theory and algorithms for application domains; • Computing methodologies → Modeling and simulation; • Applied computing → Physical sciences and engineering Competing Interest Statement The authors have declared no competing interest.

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last seen: 2026-05-20T01:45:00.602351+00:00