Evidence map›Paper›PMID 40855212›Full record

ArticleBehavior research methods2025

A cognitive multiplex network approach to investigate mental navigation and predict high-level cognition.

Ofir Ganor, Gal Samuel, Massimo Stella, Yoed N Kenett

Abstract read
In one paragraph

Article in Behavior research methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ofir GanorFaculty of Data and Decision Sciences, Technion - Israel Institute of Technology, Haifa, Israel.
Gal SamuelFaculty of Data and Decision Sciences, Technion - Israel Institute of Technology, Haifa, Israel.
Massimo StellaCogNosco Lab, Department of Psychology and Cognitive Science, University of Trento, Trento, Italy.ORCID http://orcid.org/0000-0003-1810-9699
Yoed N KenettFaculty of Data and Decision Sciences, Technion - Israel Institute of Technology, Haifa, Israel. yoedk@technion.ac.il.ORCID http://orcid.org/0000-0003-3872-7689

Funding

United States-Israel Binational Science Foundation 2021040
6 · The paper itself

Abstract

High-level cognition, such as intelligence and creativity, are considered the hallmark of human cognition; however, their complexity hinders the identification of underlying common mechanisms. We focus on one such likely mechanism-mental navigation. We utilize converging computational methods to demonstrate how mental navigation-operationalized via verbal fluency tasks-predicts individual differences in creativity, intelligence, and openness to experience (the personality trait most closely related to them). Participants' (N = 479) responses to two tasks-a 2-min animal fluency task and a 2-min generating synonyms of the word "hot" fluency task-were modeled over a multidimensional model (a cognitive multiplex network) of the mental lexicon. Quantitative measures of their mental navigation were used to build regression models that significantly predicted their assessed high-level cognition (replicating across both fluency tasks). Finally, we developed an online tool that capitalizes on our approach-the High-level Cognitive Prediction tool. Overall, we show how converging computational tools can elucidate the complexity of high-level cognition.

Indexed as

CognitionCreativityAdultFemaleHumansIndividualityIntelligenceMaleYoung AdultCognitive multiplex networkCreativityHigh-level cognitionIntelligenceMental navigation

Identifiers

PMID40855212
PMCPMC12378698

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.