Search

In studies of event-related brain potentials (ERPs), numerous decisions about data processing are required to extract ERP scores from continuous data. Unfortunately, the systematic impact of these choices on the data quality and psychometric reliability of ERP scores or even ERP scores themselves is virtually unknown, which is a barrier to the standardization of ERPs. The aim of the present study was to optimize processing pipelines for the error-related negativity (ERN) and error positivity (Pe) by considering a multiverse of data processing choices. A multiverse analysis of a data processing pipeline examines the impact of a large set of different reasonable choices to determine the robustness of effects, such as the impact of different decisions on between-trial standard deviations (i.e., data quality) and between-condition differences (i.e., experimental effects). ERN and Pe data from 298 healthy young adults were used to determine the impact of different methodological choices on data quality and experimental effects (correct vs. error trials) at several key stages: highpass filtering, lowpass filtering, ocular artifact correction, reference, baseline adjustment, scoring sensors, and measurement procedure. This multiverse analysis yielded 3,456 ERN scores and 576 Pe scores per person. An optimized pipeline for ERN included a 15 Hz lowpass filter, ICA-based ocular artifact correction, and a region of interest (ROI) approach to scoring. For Pe, the optimized pipeline included a 0.10 Hz highpass filter, 30 Hz lowpass filter, regression-based ocular artifact correction, a -200 to 0 ms baseline adjustment window, and an ROI approach to scoring. The multiverse approach can be used to optimize pipelines for eventual standardization, which would support efforts toward establishing normative ERP databases. The proposed process of analyzing the data-processing multiverse of ERP scores paves the way for better refinement, identification, and selection of data processing parameters, ultimately improving the precision and utility of ERPs.

Food-related inhibitory control, the ability to withhold a dominant response towards highly palatable foods, influences dietary decisions. Food-related inhibitory control abilities may increase following a bout of aerobic exercise; however, the impact of exercise intensity on both food-related inhibitory control and broader cognitive control processes is currently unclear. We used a high-powered, within-subjects, crossover design to test how relative intensity of aerobic exercise influenced behavioral (response time, accuracy) and neural (N2 and P3 components of the scalp-recorded event-related potential [ERP]) measures of food-related inhibitory and cognitive control. Two hundred and ten participants completed three separate conditions separated by approximately one week in randomized order: two exercise conditions (35% VO2max or 70% VO2max) and seated rest. Directly following exercise or rest, participants completed a food-based go/no-go task and a flanker task while electroencephalogram data were recorded. Linear mixed models showed generally faster response times (RT) and improved accuracy following 70% VO2max exercise compared to rest, but not 35% VO2max; RTs and accuracy did not differ between 35% VO2max exercise and rest conditions. N2 and P3 amplitudes were larger following 70% VO2max exercise for the food-based go/no-go task compared to rest and 35% VO2max exercise. There were no differences between exercise conditions for N2 amplitude during the flanker task; however, P3 amplitude was more positive following 70% VO2max compared to rest, but not 35% VO2max exercise. Biological sex did not moderate exercise outcomes. Results suggest improved and more efficient food-related recruitment of later inhibitory control and cognitive control processes following 70% VO2max exercise.

We suggest that a large data set for the error-related negativity (ERN) and error positivity (Pe) components of the scalp-recorded event-related brain potential (ERP) recently published as normative is not ready for such use in research and, especially, clinical application. Such efforts are challenged by an incomplete understanding of the functional significance of between-person differences in amplitudes and of nuisance factors that contribute to amplitude differences, a lack of standardization of methods, and the use of a convenience sample for the potentially normative database. To move ERPs toward standardization and useful norms, we encourage more research on the meaning of differences in ERN scores, including factors that influence between- and within-person variation, and the dissemination of protocols for data collection and processing.