A local Hjorth is a close computational analog to the simplest intracranial CSD algorithm for the scalp-recorded EEG, and has been reported to yield similar results to other Laplacian estimates (Tandonnet et al., 2005; Tenke et al., 1998). In principle, the CSD estimate may be optimized at different resolutions to focus on the different scales for different applications, components or regions (Tenke et al. 1993; Tenke and Kayser, 2005). A multiresolutional approach for scalp data could be based on multiple submontages, whereby a local Hjorth estimate may be computed at multiple resolutions (e.g., nearest-neighbor vs. next-nearest-neighbor). Alternatively, multiple smoothing parameters may be used for a given montage.
