A Study on the Finite Difference Approach of the Surface Laplacian

摘要

Surface Laplacian map provides a better spatial resolution than surface potential distribution. Different order finite difference approximations are deduced and compared by simulations on a plane in this paper. The results show high order approximation is better than low order approximation for noiseless situation. However, low order approximation is better for noise suppression. Results also show Laplacian is more sensitive to shallow neural activities and the temporal course of neural activities can be correctly reconstructed by a finite difference Laplacian.