Hori Junichi, Takasawa Shintaro
Graduate School of Science and Technology, Niigata University, Niigata 950-2181, Japan.
Graduate School of Science and Technology, Niigata University, Niigata 950-2181, Japan; Terumo Corporation, Tokyo, Japan.
Comput Intell Neurosci. 2016;2016:8404565. doi: 10.1155/2016/8404565. Epub 2016 Aug 29.
Cortical dipole imaging has been developed to visualize brain electrical activity in high spatial resolution. It is necessary to solve an inverse problem to estimate the cortical dipole distribution from the scalp potentials. In the present study, the accuracy of cortical dipole imaging was improved by focusing on filtering property of the spatial inverse filter. We proposed an inverse filter that optimizes filtering property using a sigmoid function. The ability of the proposed method was compared with the traditional inverse techniques, such as Tikhonov regularization, truncated singular value decomposition (TSVD), and truncated total least squares (TTLS), in a computer simulation. The proposed method was applied to human experimental data of visual evoked potentials. As a result, the estimation accuracy was improved and the localized dipole distribution was obtained with less noise.
皮层偶极子成像技术已被开发用于以高空间分辨率可视化脑电活动。从头皮电位估计皮层偶极子分布需要解决一个逆问题。在本研究中，通过关注空间逆滤波器的滤波特性提高了皮层偶极子成像的准确性。我们提出了一种使用 sigmoid 函数优化滤波特性的逆滤波器。在计算机模拟中，将所提出方法的能力与传统逆技术（如 Tikhonov 正则化、截断奇异值分解 (TSVD) 和截断总最小二乘法 (TTLS)）进行了比较。所提出的方法应用于视觉诱发电位的人体实验数据。结果，估计精度得到提高，并且获得了噪声较少的局部偶极子分布。
