Spline Laplacian estimate of EEG potentials over a realistic magnetic resonance-constructed scalp surface model

F. Babiloni, C. Babiloni, F. Carducci, L. Fattorini, P. Onorati, A. Urbano

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a realistic Laplacian (RL) estimator based on a tensorial formulation of the surface Laplacian (SL) that uses the 2-D thin plate spline function to obtain a mathematical description of a realistic scalp surface. Because of this tensorial formulation, the RL does not need an orthogonal reference frame placed on the realistic scalp surface. In simulation experiments the RL was estimated with an increasing number of 'electrodes' (up to 256) on a mathematical scalp model, the analytic Laplacian being used as a reference. Second and third order spherical spline Laplacian estimates were examined for comparison. Noise of increasing magnitude and spatial frequency was added to the simulated potential distributions. Movement-related potentials and somatosensory evoked potentials sampled with 128 electrodes were used to estimate the RL on a realistically shaped, MR-constructed model of the subject's scalp surface. The RL was also estimated on a mathematical spherical scalp model computed from the real scalp surface. Simulation experiments showed that the performances of the RL estimator were similar to those of the second and third order spherical spline Laplacians. Furthermore, the information content of scalp-recorded potentials was clearly better when the RL estimator computed the SL of the potential on an MR-constructed scalp surface model.

Original languageEnglish
Pages (from-to)363-373
Number of pages11
JournalElectroencephalography and Clinical Neurophysiology
Volume98
Issue number4
DOIs
Publication statusPublished - Apr 1996

Keywords

  • High resolution EEG
  • MR-constructed scalp surface model
  • Realistic spline Laplacian
  • Scalp-recorded event-related potentials
  • Simulated EEG potentials

ASJC Scopus subject areas

  • Clinical Neurology
  • Neuroscience(all)

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