ReviewDevelopmental cognitive neuroscience2022
Utility of linear mixed effects models for event-related potential research with infants and children.
Review in Developmental cognitive neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Experience Modulates Visuocortical Responses to Faces in 3- to 6-Year-Old Children.Journal of experimental child psychology · 2027Article
- Reliable resting-state EEG connectivity measures reveal brain network destabilization and cognitive decoupling following prolonged extreme working conditions.Cognitive neurodynamics · 2026Article
- From screens to live interactions: Considerations for naturalistic EEG paradigms in social and affective neuroscience.Developmental cognitive neuroscience · 2026Article
- Age and Social Observation Effects on Theta Synchrony and Its Role in Adolescent Post-Error Control: A Computational Approach.bioRxiv : the preprint server for biology · 2026Article
- Reduced cortical excitability is associated with head impact severity and cognitive symptoms in adolescent football players.iScience · 2026Article
- Children's and Adults' P100 and N170 Responses to Own- and Other-Race Face Categories and Identities.Developmental psychobiology · 2026Article
- Social observation influences the trajectory of performance monitoring across trials: evidence from single-trial estimates of the ERN and CRN.bioRxiv : the preprint server for biology · 2025Article
- High frequency broadband activity detected noninvasively in infants distinguishes wake from sleep states.bioRxiv : the preprint server for biology · 2025Article
- Discourse Focus and Memory Encoding: The Role of Trial-Level Alpha Power.bioRxiv : the preprint server for biology · 2025Article
- Similar Gap-Overlap Profiles in Children with Fragile X Syndrome and IQ-Matched Autism.Journal of autism and developmental disorders · 2025Article
- At-Home Stroke Neurorehabilitation: Early Findings with the NeuroExo BCI System.Sensors (Basel, Switzerland) · 2025Article
- Heterogeneity in pediatric resting EEG data processing and analysis: A state of the field.Psychophysiology · 2025Article
- Impact of emotion regulation on emotional experiences following social rejection: an ERP study.Frontiers in psychology · 2025Review
- Neural dynamics underlying the illusion of control during reward processing.Social cognitive and affective neuroscience · 2024Article
- Exploring the Activation of Target Words in Picture Naming in Children Who Stutter: Evidence From Event-Related Potentials.Journal of speech, language, and hearing research : JSLHR · 2024Article
- Measuring attentional selection of object categories using hierarchical frequency tagging.Journal of vision · 2024Article
- Optimal filters for ERP research I: A general approach for selecting filter settings.Psychophysiology · 2024Article
- Evaluating the effectiveness of artifact correction and rejection in event-related potential research.Psychophysiology · 2024Article
- Flexible multi-step hypothesis testing of human ECoG data using cluster-based permutation tests with GLMEs.NeuroImage · 2024Article
- Parental emotionality is related to preschool children's neural responses to emotional faces.Social cognitive and affective neuroscience · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Event-related potentials (ERPs) are advantageous for investigating cognitive development. However, their application in infants/children is challenging given children's difficulty in sitting through the multiple trials required in an ERP task. Thus, a large problem in developmental ERP research is high subject exclusion due to too few analyzable trials. Common analytic approaches (that involve averaging trials within subjects and excluding subjects with too few trials, as in ANOVA and linear regression) work around this problem, but do not mitigate it. Moreover, these practices can lead to inaccuracies in measuring neural signals. The greater the subject exclusion, the more problematic inaccuracies can be. We review recent developmental ERP studies to illustrate the prevalence of these issues. Critically, we demonstrate an alternative approach to ERP analysis-linear mixed effects (LME) modeling-which offers unique utility in developmental ERP research. We demonstrate with simulated and real ERP data from preschool children that commonly employed ANOVAs yield biased results that become more biased as subject exclusion increases. In contrast, LME models yield accurate, unbiased results even when subjects have low trial-counts, and are better able to detect real condition differences. We include tutorials and example code to facilitate LME analyses in future ERP research.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.