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Updated: Dec 12, 2025

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
Published on: August 9, 2016
Activity in the fronto-parietal multiple-demand network is robustly associated with individual differences in working
Moataz Assem1, Idan A Blank2, Zachary Mineroff3
1MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
Higher activity in the brain's multiple-demand (MD) network correlates with better executive functions and fluid intelligence. This study clarifies the positive association, contrasting with prior conflicting findings.
Area of Science:
- Cognitive Neuroscience
- Neuroimaging
Background:
- Executive abilities and fluid intelligence are linked to the fronto-parietal multiple-demand (MD) network.
- Previous fMRI studies show conflicting results regarding MD network activation and executive function.
Purpose of the Study:
- To investigate the relationship between MD network activity and individual differences in executive abilities and fluid intelligence.
- To clarify conflicting findings in prior research by using a large sample size and robust methodology.
Main Methods:
- Functional magnetic resonance imaging (fMRI) on a large sample (n=216) to measure brain activity.
- Participants performed a spatial working memory task during fMRI.
- Fluid intelligence was assessed independently (n=114).
Main Results:
- Stronger MD network activity was robustly associated with more accurate and faster responses in the working memory task.
- MD network activity positively correlated with independently measured fluid intelligence.
- A weak association between language network activity and working memory performance was abolished when controlling for MD activity.
Conclusions:
- Individual differences in executive abilities and fluid intelligence are selectively and positively associated with MD network activity.
- The findings support lesion studies and highlight the importance of MD network function.
- Methodological issues like unreliable measures and small sample sizes can lead to erroneous negative associations.
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