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Computational Intelligence and Neuroscience
Volume 2016, Article ID 8404565, 10 pages
http://dx.doi.org/10.1155/2016/8404565
Research Article

High-Resolution Cortical Dipole Imaging Using Spatial Inverse Filter Based on Filtering Property

1Graduate School of Science and Technology, Niigata University, Niigata 950-2181, Japan
2Terumo Corporation, Tokyo, Japan

Received 12 April 2016; Revised 15 July 2016; Accepted 7 August 2016

Academic Editor: Joao P. Papa

Copyright © 2016 Junichi Hori and Shintaro Takasawa. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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.