Abstract
The electroencephalogram (EEG) is broadly used for research of brain activities and diagnosis of brain diseases and disorders. Although EEG provides good temporal resolution of millisecond or less, it does not provide good spatial resolution. There are two main reasons for the poor spatial resolution: the blurring effects of the head volume conductor and poor signal-to-noise ratio. We have developed a tripolar concentric ring electrode (TCRE) Laplacian sensor and now report on computer simulations comparing spatial resolution between conventional EEG disc electrode sensors and TCRE Laplacian sensors. We also performed visual evoked stimulus experiments and acquired visual evoked potentials (VEPs) from healthy human subjects. From the simulations, we found that TCRE Laplacian sensors can provide approximately a tenfold improvement in spatial resolution and pass signals from specific volumes. Placing TCRE sensors near the brain region of interest will allow passage of the wanted signals and rejection of distant interference signals. We were also able to detect VEPs on the scalp surface and show that TCREs separated VEP sources better than conventional disc electrodes.
Highlights
Electroencephalography (EEG) is widely used in diagnosis of brain-related disorders and research
Sensitivity Distribution of Conventional Electrodes and tripolar concentric ring electrode (TCRE) Based on Half-Sensitivity Volume
The average power of the 64 normalized disc potentials was equal to 0:44 ± 0:31 while the average power of the 64 normalized tripolar Laplacians was equal to 0:23 ± 0:24. These results indicate that the distribution of the power of the tripolar Laplacian is more focused on a smaller number of TCREs, while the power of the disc potential tends to be distributed over a larger number of disc electrodes
Summary
Electroencephalography (EEG) is widely used in diagnosis of brain-related disorders and research. EEG suffers from poor spatial resolution due to the blurring effects primarily from different conductivities of the volume conductor [1]. To improve the spatial resolution, the surface Laplacian has been applied to EEG [1, 2]. The surface Laplacian is a high-pass spatial filter, which sharpens the blurred potential distribution on the surface [2] and produces an image proportional to the cortical potentials [3]. Two approaches have been used to calculate the surface Laplacian. The global surface Laplacian approach is based on the potential interpolation on the surface [4,5,6]. A drawback of this approach is that building the potential interpolation equations requires a significant number of electrodes [7]
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