title: Surface Laplacians (SL) and phase properties of EEG rhythms: Simulated generators in a volume-conduction model.
abstract: Surface Laplacian (SL) methods offer advantages in spectral analysis owing to the well-known implications of volume conduction. Although recognition of the superiority of SL over reference-dependent measures is widespread, well-reasoned cautions have precluded their universal adoption. Notably, the expected selectivity of SL for superficial rather than deep generators has relegated SL to the role of an add-on to conventional analyses, rather than as an independent area of inquiry, despite empirical findings supporting the consistency and replicability of physiological effects of interest. It has also been reasoned that the contrast-enhancing effects of SL necessarily make it insensitive to broadly distributed generators, including those suspected for oscillatory rhythms such as EEG alpha. These concerns are further exacerbated for phase-sensitive measures (e.g., phase-locking, coherence), where key features of physiological generators have yet to be evaluated. While the neuronal generators of empirically-derived EEG measures cannot be precisely known due to the inverse problem, simple dipole generator configurations can be simulated using a 4-sphere head model and linearly combined. We simulated subdural and deep generators and distributed dipole layers using sine and cosine waveforms, quantified at 67-scalp sites corresponding to those used in previous research. Reference-dependent (nose, average, mastoids reference) EEG and corresponding SL topographies were used to probe signal fidelity in the topography of the measured amplitude spectra, phase and coherence of sinusoidal stimuli at and between "active" recording sites. SL consistently outperformed the conventional EEG measures, indicating that continued reluctance by the research community is unfounded.
authors.affiliation: Division of Cognitive Neuroscience, New York State Psychiatric Institute, New York, NY, USA; Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York, NY, USA. Electronic address: cet2103@columbia.edu.
authors.forename: Craig E
authors.initials: CE
authors.lastname: Tenke
authors.affiliation: Division of Cognitive Neuroscience, New York State Psychiatric Institute, New York, NY, USA; Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York, NY, USA.
authors.forename: Jürgen
authors.initials: J
authors.lastname: Kayser
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D003198:Computer Simulation; D004569:Electroencephalography; D005583:Fourier Analysis; D006801:Humans; D008954:Models, Biological; D058067:Wavelet Analysis
keywords: Coherence; Current source density (CSD); Oscillation; Phase; Surface Laplacian; Volume conduction