利用贝叶斯优化和超宽带寻求单对经颅直流电刺激的最佳蒙太奇--可行性研究

IF 3.2 3区 医学 Q2 CLINICAL NEUROLOGY
Cheolki Im, Jongseung Lee, Donghyeon Kim, Sung Chan Jun, Hyeon Seo
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引用次数: 0

摘要

目的:经颅直流电刺激(tDCS)是一种新兴的神经调控技术。tDCS 的效果会因电极位置和电流强度的不同而有显著差异,因此找到优化的 tDCS 组合至关重要。然而,由于计算量大,大多数 tDCS 优化方法都是在有限的候选电极位置(如 10-10 或 10-20 国际通道配置)下进行的。本研究引入了贝叶斯优化和超带(BOHB)方法,在没有传统限制的情况下寻求整个人体头皮的最佳 tDCS 蒙太奇:贝叶斯优化和超宽带方法是一种概率方法,可在先前结果的基础上迭代改进最佳蒙太奇的选择。为了确定这种方法是否适用于 tDCS 模拟,我们将其与随机搜索(随机选择蒙太奇)和贪婪搜索(考虑所有候选蒙太奇)进行了比较。接下来,贪婪搜索中的条件被用作 BOHB 的初始条件,以实现快速学习。tDCS 优化的目标函数设定为最大化感兴趣区(ROI)的平均电场规范(|E|),感兴趣区为运动区(M1)和左侧背外侧前额叶皮层:在两个 ROI 中,迭代次数相同时,BOHB 方法的性能优于传统的随机搜索。对于 M1,BOHB 方法在每次试验中产生最大评价指标的迭代指数在统计学上小于随机搜索(P < 0.0001)。关于归一化|E|,在 M1 区域,BOHB 方法比随机搜索显示出更高的归一化|E|:结论:BOHB 方法的性能优于随机搜索方法。因此,BOHB 方法在 tDCS 优化中是可行的,并可通过微调一些控制参数作为最佳刺激蒙太奇搜索器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Seeking Optimal Montage for Single-Pair Transcranial Direct Current Stimulation Using Bayesian Optimization and Hyperband-A Feasibility Study.

Objectives: Transcranial direct current stimulation (tDCS) is an emerging neuromodulation technique. The effect of tDCS can vary significantly depending on electrode position and current intensity, making it crucial to find an optimized tDCS montage. However, because of the high computational load, most tDCS optimization approaches have been performed with a limited number of candidates for electrode positions, such as 10-10 or 10-20 international channel configurations. This study introduced the Bayesian optimization and hyperband (BOHB) method to seek optimal tDCS montage for the entire human scalp without conventional constraints.

Materials and methods: The BOHB method is a probabilistic approach that iteratively refines the selection of the optimal montage on the basis of previous results. To determine the suitability of this approach for tDCS simulation, we compared it with random search, which randomly selects montages, and greedy search, which, considers all candidates. Next, the conditions in the greedy search were used as the initial conditions for BOHB for fast learning. The objective function of tDCS optimization was set to maximize the average electric field norm (|E|) in the region of interest (ROI), which is the motor area (M1) and left dorsal lateral prefrontal cortex.

Results: The BOHB method performed better than the conventional random search for the same number of iterations in both ROIs. For M1, the iteration index yielding the maximum evaluation metric in each trial was statistically smaller in the BOHB method than in the random search (p < 0.0001). Regarding the normalized |E|, the BOHB method showed a higher normalized |E| than did the random search for the M1 region.

Conclusions: The BOHB method performed better than did the random search approach. Thus, the BOHB method is feasible for tDCS optimization and can be used as an optimal stimulation montage seeker by fine-tuning some control parameters.

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来源期刊
Neuromodulation
Neuromodulation 医学-临床神经学
CiteScore
6.40
自引率
3.60%
发文量
978
审稿时长
54 days
期刊介绍: Neuromodulation: Technology at the Neural Interface is the preeminent journal in the area of neuromodulation, providing our readership with the state of the art clinical, translational, and basic science research in the field. For clinicians, engineers, scientists and members of the biotechnology industry alike, Neuromodulation provides timely and rigorously peer-reviewed articles on the technology, science, and clinical application of devices that interface with the nervous system to treat disease and improve function.
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