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EEG power spectral measures of cognitive workload: A meta-analysis
Samy Chikhi1, Nadine Matton2,3, Sophie Blanchet1
1Laboratoire Mémoire, Cerveau et Cognition (MC2Lab, URP 7536), Institute of Psychology, University of Paris, Boulogne-Billancourt, France.
Psychophysiology
|February 7, 2022
Summary
This review found that theta brainwaves, particularly frontal theta, are the most sensitive indicator for measuring cognitive workload (CWL). Alpha and beta frequencies were also affected, but less consistently.
Area of Science:
- Neuroscience
- Cognitive Psychology
- Human Performance
Background:
- Cognitive workload (CWL) assessment is crucial for monitoring human performance.
- Electroencephalogram (EEG) is a common neuroimaging technique, but its findings on CWL effects on brain frequencies are inconsistent.
- Objective and continuous CWL measurement using neuroimaging is an active research area.
Purpose of the Study:
- To systematically review and quantitatively assess which brain frequency band is most sensitive to cognitive workload.
- To synthesize existing literature on EEG spectral power changes related to CWL.
- To provide a quantitative evaluation of theta, alpha, and beta frequency bands' sensitivity to CWL.
Main Methods:
- Systematic literature search adhering to PRISMA guidelines.
- Conducted three meta-analyses to quantitatively examine CWL effects on theta, alpha, and beta frequency bands.
- Analyzed 45 effect sizes from 24 studies involving 723 participants.
Main Results:
- Cognitive workload significantly impacted theta power (g = 0.68), alpha power (g = -0.25), and beta power (g = 0.50).
- Frontal theta emerged as the most sensitive index for cognitive workload.
- While alpha and beta power showed significant effects, their association with CWL was less direct.
Conclusions:
- Theta, especially frontal theta, is the most reliable EEG-based index for measuring cognitive workload.
- Further research should explore interactions between CWL and factors like emotional load.
- Combining EEG spectral power with other neurophysiological measures (e.g., functional connectivity, heart rate) is recommended for comprehensive analysis.
