Event‐related potentials data quality in young children: Standardized measurement error of ERN and Pe

Abstract

Most methods used to quantify event-related potential (ERP) data were developed for use with typical adult populations. Questions regarding how these methods apply to child ERP data remain. Here, we focused on two widely used ERP scoring methods, namely, time-window mean amplitude and peak amplitude measures, for two ERP error monitoring components, the error-related negativity (ERN) and the error positivity (Pe), collected from Kindergarteners during a child-friendly cognitive control task (N = 170). We first established the presence of error-related ERPs and examined the relations between ERP scores and children's behavioral task performance. We then assessed the data quality (precision) of mean and peak ERP amplitude scores at the level of individual participants using the standardized measurement error of ERPs.We also compared the effects of choosing baseline correction periods that were relatively distal versus proximal to responses on data quality. Across each of these analyses, we found that time-window mean amplitude scoring was comparable to, and in some cases outperformed, peak amplitude scoring. In addition, the proximal baseline provided higher data quality than the distal baseline. We conclude with specific recommendations regarding the scoring and baseline correction for ERP data collected from young children.

Variations in ERP data quality across paradigms, participants, and scoring procedures

“…It would be very helpful for researchers to provide SME benchmarks for other paradigms, participant populations, and scoring procedures. For example, a recent study by Isbell and Grammer (2022) examined the SME for the ERN in children between the ages of 5 and 7 using a child‐friendly version of the Go/NoGo task. They found that the SME values were substantially larger than those found for the ERN in the present study, which is not surprising given the challenges involved in recording the EEG from children.…”

Methods and metrics for EEG/ERP assessment of emotion and cognition in young children

“…Their work demonstrates the likely differences in ERP morphologies that are present in the extant developmental literature and the need for empirically derived gold standard editing practices for work with children. Isbell and Grammer (2022) describe an approach to quantifying ERP data quality using standardized measurement error, which can be used to consider the impact of different processing and scoring decisions on data quality and as a more objective method of deciding when to exclude participants’ data due to noise.…”

The default‐interventionist model underlies premise typicality weakening the premise diversity effect during category‐based induction: Event‐related potentials evidence

“…We conducted Independent component analysis (ICA) to decompose independent components based on all electrodes except for VEOG, HEOG, and two mastoid electrodes. By using the ICLabel plug‐in (Pion‐Tonachini, Kreutz‐Delgado & Makeig, 2019), the artifacts generated from eyes, muscle, heart, line noise, and channel noise were corrected when their artifacts probability was over 70% and associated with the “Brain” label with <5% probability (Isbell & Grammer, 2022).…”