Evidence map›Paper›PMID 33280008›Full record

ArticleCerebral cortex (New York, N.Y. : 1991)2021

Hierarchical Complexity of the Macro-Scale Neonatal Brain.

Manuel Blesa, Paola Galdi, Simon R Cox, Gemma Sullivan, David Q Stoye, Gillian J Lamb, Alan J Quigley, Michael J Thrippleton, Javier Escudero, Mark E Bastin and 2 more

Abstract read
In one paragraph

Article in Cerebral cortex (New York, N.Y. : 1991), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

12 authors.

Manuel BlesaMRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK.
Paola GaldiMRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK.
Simon R CoxLothian Birth Cohorts Group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK.
Gemma SullivanMRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK.
David Q StoyeMRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK.
Gillian J LambMRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK.
Alan J QuigleyDepartment of Radiology, Royal Hospital for Sick Children, Edinburgh EH9 1LF, UK.
Michael J ThrippletonCentre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK.
Javier EscuderoSchool of Engineering, Institute for Digital Communications, University of Edinburgh, Edinburgh EH9 3FG, UK.
Mark E BastinCentre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK.
Keith M SmithUsher Institute, University of Edinburgh, Edinburgh EH16 4UX, UK.
James P BoardmanMRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK.

Funding

Mapping the Human Connectome: Structure, Function, and HeritabilityU54MH091657 · NIMH · WASHINGTON UNIVERSITY · PI UGURBIL, KAMIL, VAN ESSEN, DAVID C · 2010 to 2014
$34.7M
Evaluating Longitudinal Changes in the Human Structural Connectome in Relation to Cognitive AgingR01AG054628 · NIA · UNIVERSITY OF TEXAS AT AUSTIN · PI TUCKER-DROB, ELLIOT MAX · 2017 to 2021
$2.7M
British Heart FoundationChief Scientist Office [UK]Medical Research Council G0700704Medical Research Council G1002033Medical Research Council MR/K026992/1Medical Research Council MR/N022556/1Medical Research Council MR/R024065/1Medical Research Council MR/S004122/1NIA NIH HHS R01 AG054628NIMH NIH HHS U54 MH091657The Dunhill Medical Trust R380R/1114Wellcome Trust
6 · The paper itself

Abstract

The human adult structural connectome has a rich nodal hierarchy, with highly diverse connectivity patterns aligned to the diverse range of functional specializations in the brain. The emergence of this hierarchical complexity in human development is unknown. Here, we substantiate the hierarchical tiers and hierarchical complexity of brain networks in the newborn period, assess correspondences with hierarchical complexity in adulthood, and investigate the effect of preterm birth, a leading cause of atypical brain development and later neurocognitive impairment, on hierarchical complexity. We report that neonatal and adult structural connectomes are both composed of distinct hierarchical tiers and that hierarchical complexity is greater in term born neonates than in preterms. This is due to diversity of connectivity patterns of regions within the intermediate tiers, which consist of regions that underlie sensorimotor processing and its integration with cognitive information. For neonates and adults, the highest tier (hub regions) is ordered, rather than complex, with more homogeneous connectivity patterns in structural hubs. This suggests that the brain develops first a more rigid structure in hub regions allowing for the development of greater and more diverse functional specialization in lower level regions, while connectivity underpinning this diversity is dysmature in infants born preterm.

Indexed as

AdultBrainCohort StudiesDiffusion Magnetic Resonance ImagingFemaleHumansInfant, NewbornInfant, PrematureLongitudinal StudiesMaleNerve Netdeveloping braindMRIhierarchical complexitynetwork analysisnewbornstructural connectome

Identifiers

PMID33280008
PMCPMC7945030

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Registered trials

None linked

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.