Limiting data loss in infant EEG: putting hunches to the test

Abstract

EEG is a widely used tool to study the infant brain and its relationship with behavior. As infants usually have small attention spans, move at free will, and do not respond to task instructions, attrition rates are usually high. Increasing our understanding of what influences data loss is therefore vital. The current paper examines external factors to data loss in a large-scale on-going longitudinal study (the YOUth project; 1279 five-month-olds, 1024 ten-months-olds, and 109 three-year-olds). Data loss is measured for both continuous EEG and ERP tasks as the percentage data loss after artifact removal. Our results point to a wide array of external factors that contribute to data loss, some related to the child (e.g., gender; age; head shape) and some related to experimental settings (e.g., choice of research assistant; time of day; season; and course of the experiment). Data loss was also more pronounced in the ERP experiment than in the EEG experiment. Finally, evidence was found for within-subject stability in data loss characteristics over multiple sessions. We end with recommendations to limit data loss in future studies.

Development of the N400 for Word Learning in the First 2 Years of Life: A Systematic Review

“…One welcome addition to the field would be cross-sectional or ideally even longitudinal studies with the same paradigm using small consecutive age-bins, and systematically testing on- and offsets of the N400 latency, together with reports on peak latency. Yet even then infant data might be contaminated with too much noise to infer development (van der Velde and Junge, 2020 ). Large data sets, such as acquired in a large-scale replication study as is recently published with adults and EEG on semantic processing, allow for more fine-grained analyses (Nieuwland et al, 2020 ).…”

“…This method has proven increasingly popular for testing infants with the advance of neuroimaging techniques (Reid, 2012 ; Azhari et al, 2020 ). There is increasing literature explaining and improving the methodology for testing such young populations (e.g., Thierry, 2005 ; De Haan, 2007 ; Bell and Cuevas, 2012 ; Stets et al, 2012 ; van der Velde and Junge, 2020 ). One of the most commonly derived measures from the EEG is the Event-Related Potential (ERP) technique.…”

Teaming up to understand individual development

“…The paper by Onland-Moret et al (2020) describes the design, population, determinants, measures and outcomes of the YOUth cohort, which will help greatly in facilitating replication and collaboration with other cohorts. In addition, the paper by van der Velde and Junge (2020 ) addresses a number of important issues regarding how infant characteristics and the testing environment impact data loss in the EEG studies conducted in the YOUth cohort. In a separate paper, a detailed and transparent description of the MR acquisition protocols in the YOUth cohort is described, but this paper by Buimer et al (2020) also includes test-retest reliability of the included MR acquisitions in a group of adults.…”

The YOUth study: Rationale, design, and study procedures

“…At YOUth Baby & Child (‘Around 0’, ‘Around 3’, and ‘Around 6’) we use EEG (event-related potentials, more specifically) to measure whether infants can tell apart faces from houses, and whether they can discriminate between different facial epressions. The 5-months-olds passively see only neutral faces and houses while the 10-month-olds and older children in ‘Around 3’ additionally see fearful or happy faces ( van der Velde and Junge, 2020 ).…”

“…While in the MRI scanner, children are asked to passively view (emotional) faces or houses, while their brain activity is recorded. We use exactly the same stimuli and comparisons as in our EEG tasks that is used in YOUth Baby & Child (neutral faces, fearful faces, happy faces, houses) ( van der Velde and Junge, 2020 ).…”