Non-linear Analysis of Scalp EEG by Using Bispectra: The Effect of the Reference Choice.

ABSTRACT: Bispectral analysis is a signal processing technique that makes it possible to capture the non-linear and non-Gaussian properties of the EEG signals. It has found various applications in EEG research and clinical practice, including the assessment of anesthetic depth, the identification of epileptic seizures, and more recently, the evaluation of non-linear cross-frequency brain functional connectivity. However, the validity and reliability of the indices drawn from bispectral analysis of EEG signals are potentially biased by the use of a non-neutral EEG reference. The present study aims at investigating the effects of the reference choice on the analysis of the non-linear features of EEG signals through bicoherence, as well as on the estimation of cross-frequency EEG connectivity through t

SUBMITTER: Chella F 

PROVIDER: S-EPMC5432555 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature