I would like to implement the approximated surface Laplacian (SL) estimated using Hjorth Algorithm but I can't find an open literature on the approximation of The SL at scalp edges as suggested in "Spatial Filter Selection for EEG Based Communication" by McFarland et al.
They mention Zhou's work for edge electrodes SL approximation but I do not have access to that literature.
Does anyone have relevant literature on that?
Or Does anyone Know How To Compute The Large Laplacian also called" next nearest neighbor SL" (up to the edge of the scalp)?
Dear Yves,
I found the follwing statement in Mike X. Cohen - Analyzing Neural Time Series Data:
"A basic approximation to the surface Laplacian is to subtract from each electrode the
averaged activity of immediately surrounding electrodes (Hjorth 1975; Shepard 1968). This is not the most elegant solution, however: volume conduction does not spread only to nearest neighbors but rather to many electrodes up to tens of centimeters away, and the effect of volume conduction does not affect all neighboring electrodes equally but, rather, as a function of the distance between each electrode and the “source ” electrode (that is, the skull/surface source of the electrical activity). There are several algorithms to compute the surface Laplacian that are more accurate than nearest-neighbor subtraction."
This may not help directly with your question, but maybe you'll want to have a look at Cohen's book for some other calculations.
Hi Yves,
you might want to check out the (open-source) implementation in the FieldTrip Matlab toolbox:
http://www.fieldtriptoolbox.org/
In FieldTrip, Hjorth's method is implemented within the function ft_scalpcurrentdensity, see: http://www.fieldtriptoolbox.org/reference/ft_scalpcurrentdensity
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