The attributes that provide the surface Laplacian with its advantages in sharpening a topography and eliminating redundancy may become limitations as well. These concerns have become so well known by the research community (for a concise and terse summary, see Nunez and Srinivasan, 2006a) that they are often expressed categorically, and without regard for the specific application in question. From their empirical data, Hjorth and Rodin (1988) specifically proposed the use of a local Laplacian CSD as a means of parsing the contributions of superficial from deep generators of scalp-recorded seizure activity. Although quantitatively correct, simulations readily discount the strict, qualitative dichotomy implied by this approach (Turetsky and Fein, 1991; also cf. Figures 7 and 8). Moreover, coherence estimates from scalp potentials and Laplacians have been shown to be sensitive to different spatial bandwidths, which led Srinivasan et al. (1998) to recommend using the two measures in parallel.
