Comparing aperiodic activity in consumer-grade and research-grade EEG: Reliability and association with mathematical ability

Electroencephalography (EEG) provides valuable insights into brain development, but collecting high-quality data can be tedious, limiting its usability with children. This study evaluates the feasibility and reliability of EEG data acquisition in children with a wireless consumer-grade EEG headset (EMOTIV EPOC X), by comparing it to a research-grade system (BioSemi ActiveTwo), with a focus on aperiodic brain activity. The portability of the EMOTIV headset allows for EEG data collection in ecologically valid, real-world settings such as schools, enabling novel insights into brain activity during learning. We recorded EEG from 93 children (aged 9-10 years) using the EMOTIV headset, beginning with a 4-min resting-state measurement, followed by assessments of mathematical ability, visuospatial working memory, and verbal working memory, in a classroom environment. Aperiodic activity, thought to reflect fundamental aspects of neural excitability and cognitive processing, was extracted and its reliability compared across the two EEG systems. We further tested whether aperiodic activity recorded with EMOTIV predicts mathematical ability, replicating earlier research using research-grade EEG equipment. Our findings reveal that, similar to earlier findings, lower aperiodic activity was associated with higher math performance, supporting its role as a neural marker of cognitive ability. These results demonstrate the feasibility and reliability of using a consumer-grade mobile EEG headset to investigate individual differences in cognitive development in naturalistic contexts. This work opens up new opportunities for large-scale, school-based neurocognitive assessments and paves the way for personalized educational approaches based on neural profiles.

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Publication Details

Journal
Behavior Research Methods
Published
2026-01-06
DOI
https://doi.org/10.3758/s13428-025-02905-x
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00

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article

Comparing aperiodic activity in consumer-grade and research-grade EEG: Reliability and association with mathematical ability

Lisa M. Jonkman, Anne H. van Hoogmoed, Shankara S. van de Ven, Nienke E. R. van Bueren
Behavior Research Methods
EEG and Brain-Computer Interfaces
article

Comparing aperiodic activity in consumer-grade and research-grade EEG: Reliability and association with mathematical ability

Lisa M. Jonkman, Anne H. van Hoogmoed, Shankara S. van de Ven, Nienke E. R. van Bueren
article en

Abstract

Electroencephalography (EEG) provides valuable insights into brain development, but collecting high-quality data can be tedious, limiting its usability with children. This study evaluates the feasibility and reliability of EEG data acquisition in children with a wireless consumer-grade EEG headset (EMOTIV EPOC X), by comparing it to a research-grade system (BioSemi ActiveTwo), with a focus on aperiodic brain activity. The portability of the EMOTIV headset allows for EEG data collection in ecologically valid, real-world settings such as schools, enabling novel insights into brain activity during learning. We recorded EEG from 93 children (aged 9-10 years) using the EMOTIV headset, beginning with a 4-min resting-state measurement, followed by assessments of mathematical ability, visuospatial working memory, and verbal working memory, in a classroom environment. Aperiodic activity, thought to reflect fundamental aspects of neural excitability and cognitive processing, was extracted and its reliability compared across the two EEG systems. We further tested whether aperiodic activity recorded with EMOTIV predicts mathematical ability, replicating earlier research using research-grade EEG equipment. Our findings reveal that, similar to earlier findings, lower aperiodic activity was associated with higher math performance, supporting its role as a neural marker of cognitive ability. These results demonstrate the feasibility and reliability of using a consumer-grade mobile EEG headset to investigate individual differences in cognitive development in naturalistic contexts. This work opens up new opportunities for large-scale, school-based neurocognitive assessments and paves the way for personalized educational approaches based on neural profiles.

Behavior Research MethodsVol. 58(1)
Radboud University Nijmegen (NL), Maastricht University (NL)
Radboud Universiteit, Universiteit Maastricht
Quality Education
Openalex Percentile: Top 96%
EEG and Brain-Computer Interfaces
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