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Chunk #22 — 1. Introduction — 1.2. What is a surface Laplacian transform?

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Issues and considerations for using the scalp surface Laplacian in EEG/ERP research: A tutorial review.
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the potentials measured at each site multiplied by the column weights (an analogous formalization can be easily defined in the one-dimensional case via a transformation vector). Because this transformation matrix is independent of the actual EEG signal (i.e., the values obtained for each recording site), it only needs to be defined once for a given montage, and can then be applied to any time point of any EEG data set employing this montage.