2002/06/03 by Giulio Ruffini, Ruffini, Giulio, Josep Marco +3 · 1 citation
Biochemistry, Genetics and Molecular Biology · Engineering · Medicine · Neuroscience · Physics and Astronomy · #Advanced MRI Techniques and Applications #Control Systems and Identification #Data Analysis #FOS: Biological sciences #FOS: Physical sciences #Functional Brain Connectivity Studies #Medical Physics (physics.med-ph) #Neurons and Cognition (q-bio.NC) #Statistics and Probability (physics.data-an) #physics.data-an #physics.med-ph #q-bio.NC
paper · pdf · doi:10.48550/arxiv.physics/0206007
14 pages, 3 figures. This is an internal Starlab Knowledge Nugget, with public status
arxiv created 2002/06/03 · openalex publication_date 2002/06/03 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The aim in this note is to define an algorithm to carry out minimal curvature spherical harmonics interpolation, which is then used to calculate the Laplacian for multi-electrode EEG data analysis. The approach taken is to respect the data. That is, we implement a minimal curvature condition for the interpolating surface subject to the constraints determined from the multi-electrode data. We implement this approach using spherical harmonics interpolation. In this elegant example we show that minimization requirement and constraints complement each other to fix all degrees of freedom automatically, as occurs in gauge theories. That is, the constraints are respected, while only the orthogonal subspace minimization constraints are enforced. As an example, we discuss the application to interpolate control data and calculate the temporal sequence of laplacians from an EEG Mismatch Negativity (MMN) experiment (using an implementation of the algorithm in IDL).