Evidence map›Paper›PMID 30420501›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2018

Subspecialization within default mode nodes characterized in 10,000 UK Biobank participants.

Julius M Kernbach, B T Thomas Yeo, Jonathan Smallwood, Daniel S Margulies, Michel Thiebaut de Schotten, Henrik Walter, Mert R Sabuncu, Avram J Holmes, Alexandre Gramfort, Gaël Varoquaux and 2 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
79citing papers in PubMed, 3 pooled it
–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

79 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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19 more citing papers are in PubMed but not listed here.

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

12 authors.

Julius M KernbachDepartment of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, 52072 Aachen, Germany.
B T Thomas YeoDepartment of Electrical and Computer Engineering, Clinical Imaging Research Centre, Singapore Institute for Neurotechnology and Memory Networks Program, National University of Singapore (NUS), 117575 Singapore, Singapore.ORCID 0000-0002-0119-3276
Jonathan SmallwoodDepartment of Psychology, York Neuroimaging Centre, University of York, York YO10 5DD, United Kingdom.
Daniel S MarguliesCentre National de la Recherche Scientifique, CNRS UMR 7225, Institut du Cerveau et de la Moelle Épinière, 75013 Paris, France.
Michel Thiebaut de SchottenBrain Connectivity and Behaviour Group, Frontlab, 75013 Paris, France.ORCID 0000-0002-0329-1814
Henrik WalterDepartment of Psychiatry and Psychotherapy at Campus Charité Mitte, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, 10117 Berlin, Germany.ORCID 0000-0002-9403-6121
Mert R SabuncuAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129.
Avram J HolmesAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129.
Alexandre GramfortParietal Team, Institut National de Recherche en Informatique et en Automatique (INRIA), Neurospin, Commissariat à l'Energie Atomique (CEA-Saclay), Université Paris-Saclay, 91191 Gif-sur-Yvette, France.
Gaël VaroquauxParietal Team, Institut National de Recherche en Informatique et en Automatique (INRIA), Neurospin, Commissariat à l'Energie Atomique (CEA-Saclay), Université Paris-Saclay, 91191 Gif-sur-Yvette, France.ORCID 0000-0003-1076-5122
Bertrand ThirionParietal Team, Institut National de Recherche en Informatique et en Automatique (INRIA), Neurospin, Commissariat à l'Energie Atomique (CEA-Saclay), Université Paris-Saclay, 91191 Gif-sur-Yvette, France.
Danilo BzdokDepartment of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, 52072 Aachen, Germany; danilo.bzdok@rwth-aachen.de.

Funding

Advanced machine learning algorithms that integrate genomewide, longitudinal MRI and demographic data to predict future cognitive decline toward dementiaR01AG053949 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI SABUNCU, MERT RORY · 2017 to 2021
$2.4M
Novel Bioinformatics Strategies to Study Associations Between Genetic Variants and Neuroanatomical ShapeR01LM012719 · NLM · CORNELL UNIVERSITY · PI SABUNCU, MERT RORY · 2017 to 2020
$1.4M
Multi-modal Prediction of Future Clinical DementiaR21AG050122 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI VAN LEEMPUT, KOEN · 2016 to 2017
$470k
Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NIA NIH HHS R01 AG053949NIA NIH HHS R21 AG050122NLM NIH HHS R01 LM012719
6 · The paper itself

Abstract

The human default mode network (DMN) is implicated in several unique mental capacities. In this study, we tested whether brain-wide interregional communication in the DMN can be derived from population variability in intrinsic activity fluctuations, gray-matter morphology, and fiber tract anatomy. In a sample of 10,000 UK Biobank participants, pattern-learning algorithms revealed functional coupling states in the DMN that are linked to connectivity profiles between other macroscopical brain networks. In addition, DMN gray matter volume was covaried with white matter microstructure of the fornix. Collectively, functional and structural patterns unmasked a possible division of labor within major DMN nodes: Subregions most critical for cortical network interplay were adjacent to subregions most predictive of fornix fibers from the hippocampus that processes memories and places.

Indexed as

AdultAgedAlgorithmsBiological Specimen BanksBrainBrain MappingFemaleGray MatterHumansLearningMagnetic Resonance ImagingMaleMiddle AgedUnited KingdomWhite Matterhigh-level cognitionmachine learningsystems neuroscience

Identifiers

PMID30420501
PMCPMC6275484

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.