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 |
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頁(從 - 到) | 219-245 |
頁數 | 27 |
期刊 | Annals of Applied Statistics |
卷 | 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