ArticlePsychophysiology2024
The effect of hair type and texture on electroencephalography and event-related potential data quality.
Article in Psychophysiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Challenges and Innovations in Equitable EEG for Patients with Coarse, Dense, and Curly Hair.Journal of child neurology · 2026Article
- Mind the Cap: Inclusivity Gaps in EEG Research.Psychophysiology · 2026Article
- Power struggles: Absolute vs. relative EEG power in developmental neuroscience.Developmental cognitive neuroscience · 2026Article
- Smartphone language and resting-state EEG indicators of self-focused attention prospectively predict major depressive disorder risk in adolescents.Journal of child psychology and psychiatry, and allied disciplines · 2026Article
- Advancing Dry Electroencephalography With Scalable, Soft, and Transcranial Magnetic Stimulation-Compatible TiAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Spectral EEG-guided adaptive neuromodulation for social anxiety disorder, performance-only subtype: a case report.Frontiers in psychiatry · 2026Article
- Modality-level obstacles and initiatives to improve representation in fetal, infant, and toddler neuroimaging research samples.Developmental cognitive neuroscience · 2025Article
- Differences in Consummatory but Not Anticipatory Reward Processing Predict Depressive Symptoms in Young Adult Women.Psychophysiology · 2025Article
- Exploring the Utility of the Muse Headset for Capturing the N400: Dependability and Single-Trial Analysis.Sensors (Basel, Switzerland) · 2024Article
- Fostering inclusion in EEG measures of pediatric brain activity.NPJ science of learning · 2024Review
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Authors and funding
4 authors.
Funding
Abstract
Research utilizing event-related potential (ERP) methods is generally biased with regard to sample representativeness. Among the myriad of factors that contribute to sample bias are researchers' assumptions about the extent to which racial differences in hair texture, volume, and style impact electrode placement, and subsequently, study eligibility. The current study examines these impacts using data collected from n = 213 individuals ages 17-19 years, and offers guidance on collection of ERP data across the full spectrum of hair types. Individual differences were quantified for hair texture using a visual scale, and for hair volume by measuring the amount of gel used in cap preparation. Electroencephalography data quality was assessed with multiple metrics at the preprocessing, post-processing, and variable generation stages. Results indicate that hair volume is associated with small, but systematic differences in signal quality and signal amplitude. Such differences are highly problematic as they could be misattributed to cognitive differences among groups. However, inclusion of gel volume as a covariate to account for individual differences in hair volume significantly reduced, and in most cases eliminated, group differences. We discuss strategies for overcoming real and perceived technical barriers for researchers seeking to achieve greater inclusivity and representativeness in ERP research.
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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.