Heterogeneity in pediatric resting EEG data processing and analysis: A state of the field.

Abstract

Developmental, resting electroencephalography (EEG) is gaining rapid popularity with implementation in large-scale studies as well as a recent WHO report naming resting EEG as a gold standard measure of brain health. With an increased interest in resting EEG as a potential biomarker for neurocognition, it is paramount that resting EEG findings are reliable and reproducible. One of the major threats to replicability and reproducibility stems from variations in preprocessing and analysis. One of the primary challenges facing the field of developmental EEG is that it can be challenging to acquire data from infants and children, which commonly makes data cleaning and analysis difficult and unstandardized. The goal of the present manuscript is to take a state of the field of the methods experts in resting EEG report they would use to clean and analyze a hypothetical data set. Here we report on the responses of 66 self-identified experts in developmental psychophysiology, none of which submitted identical preregistrations. As expected, there were areas of more and less consensus, but ultimately, we believe our findings highlight opportunities for core methodological work and field-level efforts to establish consensus.