How does the brain reflect mental effort, vigilance, and fatigue across different tasks — from mental arithmetic to immersive virtual reality?

Angel David Blanco
Oct 28
3 min read

EEG Spectral Power Correlates Across Cognitive Tasks: Insights from Our Latest Publication in Biological Psychology

That’s the question we explored in our latest open-access publication, “EEG spectral power correlates across cognitive tasks: Implications for VR, UXA, and Ergonomics,” recently published in Biological Psychology.

This research, led by Ángel Blanco Casares, Ph.D., Karan Chugani, Claire Braboszcz, Eleni Kroupi, and Aureli Soria-Frisch, investigates how EEG spectral features behave across multiple cognitive challenges and whether they can be used as reliable indicators of cognitive states in realistic scenarios.

Understanding Brain Dynamics Across Tasks

Electroencephalography (EEG) provides a non-invasive window into the brain’s electrical activity. In this study, we examined how spectral power — the energy of brain oscillations in specific frequency bands (Theta, Alpha, etc.) — changes with cognitive demand and vigilance.

To do this, we analyzed EEG data from three paradigms representing different types of cognitive effort:

🧮 Mental Arithmetic Task: Participants performed calculations after a resting-state baseline.
🧠 Memory Task: They memorized sets of 2, 4, 6, or 8 items before recall.
🚗 Virtual Reality Driving Task: Participants steered a simulated vehicle and corrected unexpected deviations over a 90-minute session.

Each task taxed the brain in a different way — from working memory to sustained attention — allowing us to assess whether EEG markers of mental effort remain consistent across contexts.

What We Found

Across tasks, EEG spectral features in the Theta and Alpha bands showed strong correlations with cognitive exertion and vigilance:

Increases in Theta power often reflected growing mental fatigue or reduced attention.
Decreases in Alpha power were associated with greater engagement and focus.

Interestingly, when looking at the VR driving data in detail, we found that brain activity recorded just three seconds before a lane deviation response could predict how fast a participant would react.Higher Theta and Alpha power predicted slower reactions — likely reflecting moments of mind-wandering or declining vigilance.

Participants who maintained better performance showed adaptive changes in brain activity over time, while those who struggled displayed patterns consistent with cognitive fatigue.

These findings suggest that EEG spectral features can serve as early indicators of attentional lapses, potentially even before behavioral performance starts to decline.

Implications for Real-World Applications

Our results contribute to several fields at the intersection of neuroscience and technology:

⚙️ Cognitive Ergonomics: Designing safer, more adaptive environments that respond to mental workload.
🧑‍💻 User Experience and Human–Machine Interaction: Understanding how attention fluctuates during complex interactions.
🧠 Neurotechnology and Adaptive Systems: Enabling systems that monitor brain states in real time and adjust accordingly — for example, to prevent accidents, optimize workload, or enhance learning.

By demonstrating the cross-task reliability of EEG spectral markers, this study supports the development of EEG-based monitoring tools for cognitive performance, fatigue, and vigilance — with applications in fields ranging from aviation and automotive safety to virtual reality and neuroergonomics.

Open Science: Data and Access

In line with our commitment to transparency and open science, all EEG datasets used in this work are publicly available (here, here and here). The article itself is free to read and download for a limited time through a special access link provided by the journal.