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Accurate analysis of scalp-recorded electrical activity requires the identification of electrode locations in 3D space. For example, source analysis of EEG/ERP (electroencephalogram, EEG; event-related-potentials, ERP) with realistic head models requires the identification of electrode locations on the head model derived from structural MRI recordings. Electrode systems must cover the entire scalp in sufficient density to discriminate EEG activity on the scalp and to complete accurate source analysis. The current study compares techniques for averaging electrode locations from 86 participants with the 128 channel "Geodesic Sensor Net" (GSN; EGI, Inc.), 38 participants with the 128 channel "Hydrocel Geodesic Sensor Net" (HGSN; EGI, Inc.), and 174 participants with the 81 channels in the 10-10 configurations. A point-set registration between the participants and an average MRI template resulted in an average configuration showing small standard errors, which could be transformed back accurately into the participants' original electrode space. Average electrode locations are available for the GSN (86 participants), Hydrocel-GSN (38 participants), and 10-10 and 10-5 systems (174 participants).

Evaluating Methods for Constructing Average High-Density Electrode Positions