The above example illustrates the principle of a Laplacian transformation for a one-dimensional scenario, which is often employed in intracranial EEG studies (cf. Tenke and Kayser, 2012). For a linear penetration of tissue, Freeman and Nicholson (1975) originally proposed a local “slope-of-slope” measure as applied in Figure 4, but simplified the computation as the potential at each electrode minus half of the potentials at each of the two neighboring sites. Local smoothing can be obtained by expanding this algorithm to the four nearest neighbors and weighting the subtracted potentials by distance.5
