Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Predictive validity of cognitive abilities for air traffic controllers selection among proficient scientific candidates.

Applied ergonomics·2025
Same author

Impact of automation level on airline pilots' flying performance and visual scanning strategies: A full flight simulator study.

Applied ergonomics·2024
Same author

Effects of one session of theta or high alpha neurofeedback on EEG activity and working memory.

Cognitive, affective & behavioral neuroscience·2024
Same author

How a pilot's brain copes with stress and mental load? Insights from the executive control network.

Behavioural brain research·2023
Same author

Mental strategies and resting state EEG: Effect on high alpha amplitude modulation by neurofeedback in healthy young adults.

Biological psychology·2023
Same author

Reconsidering conceptual knowledge: Heterogeneity of its components.

Journal of experimental child psychology·2022

Related Experiment Video

Updated: Feb 21, 2026

Estimate the Cognitive Load Using Electrocardiographic Measure: A Human-AI Collaborative Task
07:08

Estimate the Cognitive Load Using Electrocardiographic Measure: A Human-AI Collaborative Task

Published on: December 5, 2025

774

Using theta and alpha band power to assess cognitive workload in multitasking environments.

Sébastien Puma1, Nadine Matton2, Pierre-V Paubel1

  • 1University of Toulouse, CNRS (UMR5263), 5 allées Antonio Machado, 31058 Toulouse Cedex 9, France.

International Journal of Psychophysiology : Official Journal of the International Organization of Psychophysiology
|October 12, 2017
PubMed
Summary

Measuring cognitive workload using electroencephalography (EEG) shows increased theta and decreased alpha band power with task complexity. Individual performance levels significantly influence these EEG measures, impacting reliability.

Keywords:
Cognitive workloadElectroencephalographyMultitasking, spectral power

More Related Videos

Measuring the Switch Cost of Smartphone Use While Walking
07:00

Measuring the Switch Cost of Smartphone Use While Walking

Published on: April 30, 2020

2.3K
Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

12.0K

Related Experiment Videos

Last Updated: Feb 21, 2026

Estimate the Cognitive Load Using Electrocardiographic Measure: A Human-AI Collaborative Task
07:08

Estimate the Cognitive Load Using Electrocardiographic Measure: A Human-AI Collaborative Task

Published on: December 5, 2025

774
Measuring the Switch Cost of Smartphone Use While Walking
07:00

Measuring the Switch Cost of Smartphone Use While Walking

Published on: April 30, 2020

2.3K
Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

12.0K

Area of Science:

  • Human Factors and Ergonomics
  • Neuroscience
  • Cognitive Psychology

Background:

  • Cognitive workload assessment is crucial for human-machine interface design and safety.
  • Electroencephalography (EEG) is frequently used to measure cognitive workload, with studies linking increased theta and decreased alpha band power to higher workload.
  • Inconsistent findings in previous EEG studies suggest potential influences of individual differences and small sample sizes.

Purpose of the Study:

  • To investigate the relationship between cognitive workload, task performance, and EEG signals in a multitasking environment.
  • To address inconsistencies in previous research by accounting for individual differences in performance.

Main Methods:

  • Utilized electroencephalography (EEG) to record brain activity.
  • Employed a multitasking simulation task, increasing concurrent sub-tasks from one to four.
  • Collected subjective ratings, performance scores, pupil size, and EEG data from twenty participants.

Main Results:

  • Increased EEG theta and alpha band power correlated with higher cognitive resource engagement for one to three subtasks.
  • EEG measures plateaued when task performance began to decline.
  • Higher task performance was consistently associated with lower theta and alpha band power.

Conclusions:

  • EEG alpha and theta band power are sensitive indicators of cognitive workload in multitasking scenarios.
  • Individual performance levels are critical factors influencing EEG-based workload assessment.
  • Accounting for performance differences enhances the reliability of EEG for measuring cognitive workload.