Transcranial Electrical Neuromodulation Based on the Reciprocity Principle.
Transcranial Electrical Neuromodulation Based on the Reciprocity Principle.
复制标题
DOI：
10.3389/fpsyt.2016.00087
复制
发表时间：
2016
影响因子：
4.7
通讯作者：
Tucker D
中科院分区：
文献类型：
--
作者：
Fernández-Corazza M;Turovets S;Luu P;Anderson E;Tucker D
多电极经颅电刺激 (TES) 或经颅直流电刺激 (tDCS) 的一个关键挑战是找到一种电流注入模式，在目标处提供必要的电流密度，并在头部的其余部分最小化电流密度，这在数学上被建模为优化问题。这种使用最小二乘法 (LS) 或线性约束最小方差 (LCMV) 算法的优化通常计算成本较高，并且需要多个独立的电流源。基于脑电图 (EEG) 和 TES 中的互易原理，只要前向脑电图问题的解可用于感兴趣的大脑区域，就可以快速找到最佳的 TES 模式。在这里，我们研究了互易原理，作为在 TES 中寻找符合安全约束的最佳电流注入模式的指南。我们在详细的七组织有限元头部模型中定义了四个不同的试验皮质目标，并使用 LS 和 LCMV 解决方案作为参考标准，分析了 TES 方法互易族在电极密度、瞄准误差、焦点、强度和方向性方面的性能。结果发现，互易算法表现出与 LCMV 和 LS 解决方案相当的良好性能。比较 128 和 256 电极情况，我们发现使用更大的电极密度可以改善焦点、方向性和强度参数。结果表明，互易原理可用于快速确定 TES 中的最佳电流注入模式，并有助于简化与硬件和软件可用性以及安全约束一致的 TES 协议。
A key challenge in multi-electrode transcranial electrical stimulation (TES) or transcranial direct current stimulation (tDCS) is to find a current injection pattern that delivers the necessary current density at a target and minimizes it in the rest of the head, which is mathematically modeled as an optimization problem. Such an optimization with the Least Squares (LS) or Linearly Constrained Minimum Variance (LCMV) algorithms is generally computationally expensive and requires multiple independent current sources. Based on the reciprocity principle in electroencephalography (EEG) and TES, it could be possible to find the optimal TES patterns quickly whenever the solution of the forward EEG problem is available for a brain region of interest. Here, we investigate the reciprocity principle as a guideline for finding optimal current injection patterns in TES that comply with safety constraints. We define four different trial cortical targets in a detailed seven-tissue finite element head model, and analyze the performance of the reciprocity family of TES methods in terms of electrode density, targeting error, focality, intensity, and directionality using the LS and LCMV solutions as the reference standards. It is found that the reciprocity algorithms show good performance comparable to the LCMV and LS solutions. Comparing the 128 and 256 electrode cases, we found that use of greater electrode density improves focality, directionality, and intensity parameters. The results show that reciprocity principle can be used to quickly determine optimal current injection patterns in TES and help to simplify TES protocols that are consistent with hardware and software availability and with safety constraints.