Chunk #51 — 3. Impact of spatial scale on CSD implementations — 3.3. Empirical considerations for planar (two-dimensional) scalp-recorded EEG — 3.3.2. CSD as a conservative description of neural current generators
The redundancy and linearity that is implicit in Eq. 2 provides multiple paths to the identification of the neuronal generators underlying a scalp topography. In a number of circumstances, these solutions partially or completely converge with results obtained using other methods that vary widely in their assumptions, constraints, or underlying theoretical models. Cincotti et al. (2004) argued that a surface Laplacian and a distributed inverse model may both be useful as deblurring methods in a clinical context. Foffani et al. (2004) went even further, noting that an alternative decomposition method (independent component analysis) compared favorably with scalp Laplacians computed using realistic scalp models. This degree of convergence validates the presumption that neural processes are separable and quantifiable in multiple ways. Conversely, if results diverge, the model most parsimonious with regard to known biophysical processes must be preferred.
