Accounting for time dependence in large-scale multiple testing of event-related potential data1

Ching Fan Sheu, Émeline Perthame, Yuh Shiow Lee, David Causeur

研究成果: Article同行評審

5 引文 斯高帕斯(Scopus)

摘要

Event-related potentials (ERPs) are recordings of electrical activity along the scalp time-locked to perceptual, motor and cognitive events. Because ERP signals are often rare and weak, relative to the large between-subject variability, establishing significant associations between ERPs and behavioral (or experimental) variables of interest poses major challenges for statistical analysis. Noting that ERP time dependence exhibits a block pattern suggesting strong local and long-range autocorrelation components, we propose a flexible factor modeling of dependence. An adaptive factor adjustment procedure is derived from a joint estimation of the signal and noise processes, given a prior knowledge of the noise-alone intervals. A simulation study is presented using known signals embedded in a real dependence structure extracted from authentic ERP measurements. The proposed procedure performs well compared with existing multiple testing procedures and is more powerful at discovering interesting ERP features.

原文English
頁(從 - 到)219-245
頁數27
期刊Annals of Applied Statistics
10
發行號1
DOIs
出版狀態Published - 2016 三月

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modelling and Simulation
  • Statistics, Probability and Uncertainty

指紋 深入研究「Accounting for time dependence in large-scale multiple testing of event-related potential data1」主題。共同形成了獨特的指紋。

引用此