Studentized Continuous Wavelet Transform (t-CWT) in the Analysis of Individual ERPs: Real and Simulated EEG Data

• Main Authors: Ruben Gustav Leonhardt Real, Boris eKotchoubey, Andrea eKübler
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2014-09-01
• Series: Frontiers in Neuroscience
• Subjects: EEG; ERP; Wavelet; detection; Electroencephalogram; significance
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00279/full

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.