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Studentized continuous wavelet transform (t-CWT) in the analysis of individual ERPs: real and simulated EEG data

Ruben G. L. Real,B. Kotchoubey,A. Kübler

2014 · DOI: 10.3389/fnins.2014.00279
Frontiers in Neuroscience · 16 Citations

TLDR

Results show that the t-CWT combines high sensitivity and specificity with favorable PPV and NPV and may be well suited for the assessment of weak ERPs in single-subject settings.

Abstract

This study aimed at evaluating the performance of the Studentized Continuous Wavelet Transform (t-CWT) as a method for the extraction and assessment of event-related brain potentials (ERP) in data from a single subject. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) of the t-CWT were assessed and compared to a variety of competing procedures using simulated EEG data at six low signal-to-noise ratios. Results show that the t-CWT combines high sensitivity and specificity with favorable PPV and NPV. Applying the t-CWT to authentic EEG data obtained from 14 healthy participants confirmed its high sensitivity. The t-CWT may thus be well suited for the assessment of weak ERPs in single-subject settings.