Maximizing signal‐to‐noise ratio and statistical power in ERP measurement: Single sites versus multi‐site average clusters

Abstract

AbstractOne important decision in every event‐related potential (ERP) experiment is which electrode site(s) to use in quantifying the ERP component of interest. A common approach is to measure the ERP from a single electrode site, typically the site where the ERP component is largest. Alternatively, two or more electrode sites in a given spatial region are averaged together, and the ERP is measured from the resulting multi‐site cluster. The goal of the present study was to systematically compare these two measurement approaches across a range of outcome measures and ERP components to determine whether measuring from a single electrode site or an average of multiple sites yields consistently better results. We examined seven common ERP components from the open‐source ERP CORE dataset that span a range of neurocognitive processes: N170, mismatch negativity (MMN), N2pc, N400, P3, lateralized readiness potential (LRP), and error‐related negativity (ERN). For each component, we compared ERP amplitude, noise level, signal‐to‐noise ratio, and effect size at two single electrode sites and four multi‐site clusters. We also used a Monte Carlo approach to simulate within‐participant and between‐groups experiments with known effect magnitudes to compare statistical power at single sites and multi‐site clusters. Overall, measuring from a multi‐site cluster produced results that were as good as or better than measuring from a single electrode site across analyses and components, indicating that the cluster‐based measurement approach may be beneficial in quantifying ERPs from a range of neurocognitive domains.