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© Research
Publication : Annals of applied statistics

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

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in Annals of applied statistics - 25 Mar 2016

Ching-Fan Sheu, Émeline Perthame, Yuh-shiow Lee, and David Causeur

Ann. Appl. Stat. Volume 10, Number 1 (2016), 219-245.

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.

https://projecteuclid.org/download/pdfview_1/euclid.aoas/1458909914