How does noise affect amplitude and latency measurement of event‐related potentials (<scp>ERPs</scp>)? A methodological critique and simulation study

TLDR

ERP amplitude and latency measurements vary considerably across studies. The study investigated how increasing background noise affects the reliability of ERP quantification methods using published data and simulations. The authors evaluated mean amplitude, adaptive mean, peak amplitude, peak latency, and centroid latency as potential measures. Mean amplitude proved most robust to noise, the adaptive mean, though biased, efficiently estimated true ERP signals for individual latency variability, peak amplitude should be avoided, and for latency measures peak latency was less biased but less efficient than centroid latency, highlighting the need to report retained trials and noise estimates when comparing ERPs.

Abstract

There is considerable variability in the quantification of event-related potential (ERP) amplitudes and latencies. We examined susceptibility of ERP quantification measures to incremental increases in background noise through published ERP data and simulations. Measures included mean amplitude, adaptive mean, peak amplitude, peak latency, and centroid latency. Results indicated mean amplitude was the most robust against increases in background noise. The adaptive mean measure was more biased, but represented an efficient estimator of the true ERP signal particularly for individual-subject latency variability. Strong evidence is provided against using peak amplitude. For latency measures, the peak latency measure was less biased and less efficient than the centroid latency measurement. Results emphasize the prudence in reporting the number of trials retained for averaging as well as noise estimates for groups and conditions when comparing ERPs.