Nicolas Roehri, Jean-Marc Lina, John C. Mosher, Fabrice Bartolomei, and Christian-George Bénar, Institut de Neurosciences des Systèmes & Clinical Neurophysiology, Marseille, France, École de technologie supérieure, Canada, Cleveland Clinic Neurological Institute, USA
High-frequency oscillations (HFOs) are considered to be highly representative of brain tissues capable of producing epileptic seizures. The visual review of HFOs on intracerebral electroencephalography is time consuming and tedious, and it can be improved by time-frequency (TF) analysis. The main issue is that the signal is dominated by lower frequencies that mask the HFOs. Our aim was to flatten (i.e., whiten) the frequency spectrum to enhance the fast oscillations while preserving an optimal signal to noise ratio (SNR).
We investigated eight methods of data whitening based on either prewhitening or TF normalization in order to improve the detectability of HFOs. We detected all local maxima of the TF image above a range of thresholds in the HFO band. We obtained the precision and recall curves at different SNR and for different HFO types and illustrate the added value of whitening both in the TF plane and in time domain. The normalization strategies based on a baseline and on our proposed method (the “H0 z-score”) are more precise than the others. The H0 z-score provides an optimal framework for representing and detecting HFOs, independent of a baseline and a priori frequency bands.
KEYWORDS : Epilepsy, high-frequency oscillation, stereoelectroencephalography (SEEG), wavelet transform, whitening.
Institut de Neurosciences des Systemes: http://ins.univ-amu.fr/research-teams/dynamical-brain-mapping-dynamap/dynamap-research/READ FULL ARTICLE ON IEEE XPLORE