Application of independent component analysis to remove linear dependencies in EEG recorded in hippocampus
J. Harry Blaise, Taikang Ning · 2016
Linear cross-spectral and nonlinear cross-bispectral analysis techniques were applied to EEG data recorded simultaneously in two subfields (CA1 and dentate gyrus) of the hippocampus in freely behaving neonatal rats during REM sleep. Linear dependencies between the two sites were specifically removed using independent component analysis (ICA). The cross-spectrum and the cross-bispectrum computed prior to ICA processing were compared with those after ICA processing to determine its effects. Our results indicate that ICA almost completely extracts the linear relationship in the theta frequency band between CA1 and the dentate gyrus. It is noted also that ICA processing significantly decreases the quadratic phase coupling (QPC) between the two hippocampal subfields.