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Related Experiment Video

Updated: Sep 17, 2025

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

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

Published on: August 9, 2016

Exploring Brain Activity in Different Mental Cognitive Workloads.

Sahar Oftadeh Balani¹, Ali Fawzi Al-Hussainy², Alhan Abd Al-Hassan Shalal³

¹Department of Computer Science, Yadegar-e-Imam Khomeini (RAH), Shahre Rey Branch, Islamic Azad University, Tehran, Iran.

Iranian Journal of Psychiatry

|July 1, 2025

Summary

Electroencephalography (EEG) analysis reveals altered brain connectivity and complexity during arithmetic tasks. Increased frontoparietal connectivity and prefrontal/temporal/parietal complexity support cognitive processes like working memory and attention.

Keywords:

Brain Cognition Complexity Analysis Electroencephalography

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Area of Science:

Neuroscience
Cognitive Psychology

Background:

Understanding neural mechanisms of cognitive workload is vital for human cognition research.
Electroencephalography (EEG) offers insights into brain activity during cognitive tasks.

Purpose of the Study:

To investigate brain activity, specifically functional connectivity and complexity, associated with varying mental cognitive workloads using EEG.
To explore changes in neural patterns during an arithmetic task compared to rest.

Main Methods:

Utilized a publicly accessible EEG dataset from 36 healthy volunteers (18-26 years old).
Preprocessed EEG data to remove noise and artifacts.
Calculated functional connectivity (coherence) and complexity (permutation entropy) from EEG signals.
Applied repeated measures ANOVA to analyze differences between rest and task states across brain regions.

Main Results:

Significant within-subject effects and state-channel interactions were found for both connectivity and entropy.
Connectivity changes included decreased FP1-F7/F8/Fz and increased frontoparietal/frontooccipital connections during the arithmetic task.
Permutation entropy significantly increased in prefrontal, temporal, and parietal regions during the task.

Conclusions:

Heightened frontoparietal connectivity and regional brain complexity during arithmetic tasks reflect the integrated engagement of neural networks.
These neural changes support critical cognitive functions including numerical processing, attention, working memory, and cognitive control.
The findings elucidate the neural basis of complex problem-solving and cognitive workload.