The effect of deep brain structure modeling on transcranial direct current stimulation-induced electric fields: An in-silico study.

Chae-Bin Song, Cheolki Lim, Jongseung Lee, Donghyeon Kim, Hyeon Seo
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Abstract

To study transcranial direct current stimulation (tDCS) and its effect on the brain, it could be useful to predict the distribution of the electric field induced in the brain with given tDCS parameters. As a solution, simulation with realistic computational models using magnetic resonance images (MRIs) have been widely used in the fields. With the recent advance of deep learning-based segmentation techniques of the brain, questions have been raised about if tDCS-induced electric field is affected by the deep brain structures. This study aimed to investigate the effect of the deep brain structure modeling on the induced electric field. To this end, we generated models with and without the deep brain structures by using an open MRI dataset comprising tDCS parameters, electric field simulation results and in-vivo intracranial recordings in the deep brain structures. We investigated the difference between the simulation results of the two models with a statistical analysis. Our results indicated that tDCS-induced electric fields and current flow in the brain are significantly different when the deep brain structures are considered.

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脑深部结构建模对经颅直流电刺激电场的影响:模拟研究
要研究经颅直流电刺激(tDCS)及其对大脑的影响,预测给定 tDCS 参数在大脑中诱发的电场分布可能很有用。作为一种解决方案,利用磁共振图像(MRI)的逼真计算模型进行模拟已被广泛应用于该领域。随着最近基于深度学习的大脑分割技术的发展,人们提出了关于 tDCS 诱导的电场是否会受到大脑深层结构影响的问题。本研究旨在研究大脑深层结构建模对诱导电场的影响。为此,我们使用一个开放的磁共振成像数据集,包括 tDCS 参数、电场模拟结果和脑深部结构的体内颅内记录,生成了有脑深部结构和无脑深部结构的模型。我们通过统计分析研究了两种模型模拟结果之间的差异。结果表明,当考虑到大脑深部结构时,tDCS 在大脑中诱导的电场和电流有显著差异。
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