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

被引：11

作者：

Real, Ruben G. L. ^{[1
]}

Kotchoubey, Boris ^{[2
]}

Kuebler, Andrea ^{[1
]}

机构：

[1] Univ Wurzburg, Inst Psychol, Dept Psychol 1, D-97070 Wurzburg, Germany

[2] Univ Tubingen, Inst Med Psychol & Behav Neurobiol, Tubingen, Germany

来源：

FRONTIERS IN NEUROSCIENCE | 2014年 / 8卷

关键词：

electroencephalogram; EEG; wavelet; t-CWT; ERP; significance; detection; FALSE DISCOVERY RATE; VEGETATIVE STATE; BEDSIDE DETECTION; CONSCIOUSNESS; DISORDERS; AWARENESS; REANALYSIS; COMPONENTS;

D O I：

10.3389/fnins.2014.00279

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

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 (ERR) 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.

引用

页数：9