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Updated: Sep 10, 2025
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Modeling the Functional Network for Spatial Navigation in the Human Brain
Published on: October 13, 2023
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A cognitive multiplex network approach to investigate mental navigation and predict high-level cognition
Ofir Ganor1, Gal Samuel1, Massimo Stella2
1Faculty of Data and Decision Sciences, Technion - Israel Institute of Technology, Haifa, Israel.
Behavior Research Methods
|August 25, 2025
Summary
Mental navigation, measured using verbal fluency tasks, predicts individual differences in intelligence and creativity. This research introduces a novel approach to understanding complex cognitive abilities.
Area of Science:
- Cognitive Psychology
- Computational Neuroscience
- Psychometrics
Background:
- High-level cognition, including intelligence and creativity, are key human traits.
- The underlying mechanisms of these complex abilities remain challenging to identify.
- Mental navigation is proposed as a potential unifying mechanism.
Purpose of the Study:
- To investigate the role of mental navigation in predicting individual differences in high-level cognition.
- To operationalize mental navigation using verbal fluency tasks.
- To demonstrate the predictive power of mental navigation for intelligence, creativity, and openness to experience.
Main Methods:
- Utilized verbal fluency tasks (animal fluency, synonym generation) with 479 participants.
- Modeled participant responses using a multidimensional cognitive multiplex network of the mental lexicon.
- Employed quantitative measures of mental navigation in regression models.
Main Results:
- Mental navigation measures significantly predicted individual differences in assessed high-level cognition.
- Findings were consistent across both verbal fluency tasks, demonstrating robustness.
- Developed an online tool, the High-level Cognitive Prediction tool, based on the findings.
Conclusions:
- Converging computational methods, specifically mental navigation via verbal fluency, can elucidate complex high-level cognition.
- This approach offers a novel way to understand and predict intelligence and creativity.
- The study highlights the utility of computational tools in cognitive science research.
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