Evidence map›Paper›PMID 31354458›Full record

ArticleFrontiers in human neuroscience2019

Topological Modification of Brain Networks Organization in Children With High Intelligence Quotient: A Resting-State fMRI Study.

Ilaria Suprano, Chantal Delon-Martin, Gabriel Kocevar, Claudio Stamile, Salem Hannoun, Sophie Achard, Amanpreet Badhwar, Pierre Fourneret, Olivier Revol, Fanny Nusbaum and 1 more

Erratum issuedAbstract read
In one paragraph

Article in Frontiers in human neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Ilaria SupranoUniv. Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Étienne, CNRS, INSERM, CREATIS UMR 5220, Lyon, France.
Chantal Delon-MartinUniv. Grenoble Alpes, INSERM, U1216, Grenoble Institut Neurosciences, Grenoble, France.
Gabriel KocevarUniv. Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Étienne, CNRS, INSERM, CREATIS UMR 5220, Lyon, France.
Claudio StamileUniv. Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Étienne, CNRS, INSERM, CREATIS UMR 5220, Lyon, France.
Salem HannounNehme and Therese Tohme Multiple Sclerosis Center, Faculty of Medicine, American University of Beirut, Beirut, Lebanon.
Sophie AchardGIPSA-Lab, UMR CNRS 5216, Université Grenoble Alpes, Grenoble, France.
Amanpreet BadhwarCentre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Université de Montréal, Montreal, QC, Canada.
Pierre FourneretService de Psychopathologie du Développement de l'Enfant et de l'Adolescent, Hospices Civils de Lyon, Lyon, France.
Olivier RevolService de Psychopathologie du Développement de l'Enfant et de l'Adolescent, Hospices Civils de Lyon, Lyon, France.
Fanny NusbaumLaboratoire Parcours Santé Systémique (Equipe d'Accueil 4129), Université de Lyon, Université Claude Bernard-Lyon 1, Lyon, France.
Dominique Sappey-MarinierUniv. Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Étienne, CNRS, INSERM, CREATIS UMR 5220, Lyon, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The idea that intelligence is embedded not only in a single brain network, but instead in a complex, well-optimized system of complementary networks, has led to the development of whole brain network analysis. Using graph theory to analyze resting-state functional MRI data, we investigated the brain graph networks (or brain networks) of high intelligence quotient (HIQ) children. To this end, we computed the "hub disruption index κ," an index sensitive to graph network modifications. We found significant topological differences in the integration and segregation properties of brain networks in HIQ compared to standard IQ children, not only for the whole brain graph, but also for each hemispheric graph, and for the homotopic connectivity. Moreover, two profiles of HIQ children, homogenous and heterogeneous, based on the differences between the two main IQ subscales [verbal comprehension index (VCI) and perceptual reasoning index (PRI)], were compared. Brain network changes were more pronounced in the heterogeneous than in the homogeneous HIQ subgroups. Finally, we found significant correlations between the graph networks' changes and the full-scale IQ (FSIQ), as well as the subscales VCI and PRI. Specifically, the higher the FSIQ the greater was the brain organization modification in the whole brain, the left hemisphere, and the homotopic connectivity. These results shed new light on the relation between functional connectivity topology and high intelligence, as well as on different intelligence profiles.

Indexed as

brain networkschildrenfunctional connectivityfunctional MRIhub disruption indexintelligenceresting state

Identifiers

PMID31354458
PMCPMC6639736

What OpenQuestion holds

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LicenceCC BY
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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.