Gast ::
| Hauptseite > Publikationsdatenbank > Regional patterns of human cortex development correlate with underlying neurobiology > print |
| Hauptseite > Publikationsdatenbank > Regional patterns of human cortex development correlate with underlying neurobiology > print |
| 001 | 1031255 | ||
| 005 | 20250203133208.0 | ||
| 024 | 7 | _ | |a 10.1038/s41467-024-52366-7 |2 doi |
| 024 | 7 | _ | |a 10.34734/FZJ-2024-05633 |2 datacite_doi |
| 037 | _ | _ | |a FZJ-2024-05633 |
| 082 | _ | _ | |a 500 |
| 100 | 1 | _ | |a Lotter, Leon |0 P:(DE-Juel1)192260 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Regional patterns of human cortex development correlate with underlying neurobiology |
| 260 | _ | _ | |a [London] |c 2024 |b Nature Publishing Group UK |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1727244395_29313 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a Human brain morphology undergoes complex changes over the lifespan. Despite recent progress in tracking brain development via normative models, current knowledge of underlying biological mechanisms is highly limited. We demonstrate that human cortical thickness development and aging trajectories unfold along patterns of molecular and cellular brain organization, traceable from population-level to individual developmental trajectories. During childhood and adolescence, cortex-wide spatial distributions of dopaminergic receptors, inhibitory neurons, glial cell populations, and brain-metabolic features explain up to 50% of the variance associated with a lifespan model of regional cortical thickness trajectories. In contrast, modeled cortical thickness change patterns during adulthood are best explained by cholinergic and glutamatergic neurotransmitter receptor and transporter distributions. These relationships are supported by developmental gene expression trajectories and translate to individual longitudinal data from over 8000 adolescents, explaining up to 59% of developmental change at cohort- and 18% at single-subject level. Integrating neurobiological brain atlases with normative modeling and population neuroimaging provides a biologically meaningful path to understand brain development and aging in living humans. |
| 536 | _ | _ | |a 5253 - Neuroimaging (POF4-525) |0 G:(DE-HGF)POF4-5253 |c POF4-525 |f POF IV |x 0 |
| 536 | _ | _ | |a 5251 - Multilevel Brain Organization and Variability (POF4-525) |0 G:(DE-HGF)POF4-5251 |c POF4-525 |f POF IV |x 1 |
| 588 | _ | _ | |a Dataset connected to DataCite |
| 700 | 1 | _ | |a Saberi, Amin |0 P:(DE-Juel1)190448 |b 1 |
| 700 | 1 | _ | |a Hansen, Justine Y. |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Misic, Bratislav |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Paquola, Casey |0 P:(DE-Juel1)187055 |b 4 |
| 700 | 1 | _ | |a Barker, Gareth J. |0 P:(DE-HGF)0 |b 5 |
| 700 | 1 | _ | |a Bokde, Arun L. W. |0 P:(DE-HGF)0 |b 6 |
| 700 | 1 | _ | |a Desrivières, Sylvane |0 P:(DE-HGF)0 |b 7 |
| 700 | 1 | _ | |a Flor, Herta |0 P:(DE-HGF)0 |b 8 |
| 700 | 1 | _ | |a Grigis, Antoine |0 P:(DE-HGF)0 |b 9 |
| 700 | 1 | _ | |a Garavan, Hugh |0 P:(DE-HGF)0 |b 10 |
| 700 | 1 | _ | |a Gowland, Penny |0 P:(DE-HGF)0 |b 11 |
| 700 | 1 | _ | |a Heinz, Andreas |0 P:(DE-HGF)0 |b 12 |
| 700 | 1 | _ | |a Brühl, Rüdiger |0 P:(DE-HGF)0 |b 13 |
| 700 | 1 | _ | |a Martinot, Jean-Luc |0 P:(DE-HGF)0 |b 14 |
| 700 | 1 | _ | |a Paillère, Marie-Laure |0 P:(DE-HGF)0 |b 15 |
| 700 | 1 | _ | |a Artiges, Eric |0 P:(DE-HGF)0 |b 16 |
| 700 | 1 | _ | |a Papadopoulos Orfanos, Dimitri |0 P:(DE-HGF)0 |b 17 |
| 700 | 1 | _ | |a Paus, Tomáš |0 P:(DE-HGF)0 |b 18 |
| 700 | 1 | _ | |a Poustka, Luise |0 P:(DE-HGF)0 |b 19 |
| 700 | 1 | _ | |a Hohmann, Sarah |0 P:(DE-HGF)0 |b 20 |
| 700 | 1 | _ | |a Fröhner, Juliane H. |0 P:(DE-HGF)0 |b 21 |
| 700 | 1 | _ | |a Smolka, Michael N. |0 P:(DE-HGF)0 |b 22 |
| 700 | 1 | _ | |a Vaidya, Nilakshi |0 P:(DE-HGF)0 |b 23 |
| 700 | 1 | _ | |a Walter, Henrik |0 P:(DE-HGF)0 |b 24 |
| 700 | 1 | _ | |a Whelan, Robert |0 P:(DE-HGF)0 |b 25 |
| 700 | 1 | _ | |a Schumann, Gunter |0 P:(DE-HGF)0 |b 26 |
| 700 | 1 | _ | |a Nees, Frauke |0 P:(DE-HGF)0 |b 27 |
| 700 | 1 | _ | |a Banaschewski, Tobias |0 P:(DE-HGF)0 |b 28 |
| 700 | 1 | _ | |a Eickhoff, Simon B. |0 P:(DE-Juel1)131678 |b 29 |
| 700 | 1 | _ | |a Dukart, Juergen |0 P:(DE-Juel1)177727 |b 30 |e Corresponding author |
| 773 | _ | _ | |a 10.1038/s41467-024-52366-7 |g Vol. 15, no. 1, p. 7987 |0 PERI:(DE-600)2553671-0 |n 1 |p 7987 |t Nature Communications |v 15 |y 2024 |x 2041-1723 |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/1031255/files/s41467-024-52366-7.pdf |
| 856 | 4 | _ | |y OpenAccess |x icon |u https://juser.fz-juelich.de/record/1031255/files/s41467-024-52366-7.gif?subformat=icon |
| 856 | 4 | _ | |y OpenAccess |x icon-180 |u https://juser.fz-juelich.de/record/1031255/files/s41467-024-52366-7.jpg?subformat=icon-180 |
| 856 | 4 | _ | |y OpenAccess |x icon-640 |u https://juser.fz-juelich.de/record/1031255/files/s41467-024-52366-7.jpg?subformat=icon-640 |
| 856 | 4 | _ | |y OpenAccess |x icon-1440 |u https://juser.fz-juelich.de/record/1031255/files/s41467-024-52366-7.jpg?subformat=icon-1440 |
| 909 | C | O | |o oai:juser.fz-juelich.de:1031255 |p openaire |p open_access |p OpenAPC |p driver |p VDB |p openCost |p dnbdelivery |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)192260 |
| 910 | 1 | _ | |a Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University, Düsseldorf, Max Planck School of Cognition; Leipzig |0 I:(DE-HGF)0 |b 0 |6 P:(DE-Juel1)192260 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)190448 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 4 |6 P:(DE-Juel1)187055 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 29 |6 P:(DE-Juel1)131678 |
| 910 | 1 | _ | |a HHU Düsseldorf |0 I:(DE-HGF)0 |b 29 |6 P:(DE-Juel1)131678 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 30 |6 P:(DE-Juel1)177727 |
| 910 | 1 | _ | |a HHU Düsseldorf |0 I:(DE-HGF)0 |b 30 |6 P:(DE-Juel1)177727 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Natural, Artificial and Cognitive Information Processing |1 G:(DE-HGF)POF4-520 |0 G:(DE-HGF)POF4-525 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Decoding Brain Organization and Dysfunction |9 G:(DE-HGF)POF4-5253 |x 0 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Natural, Artificial and Cognitive Information Processing |1 G:(DE-HGF)POF4-520 |0 G:(DE-HGF)POF4-525 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Decoding Brain Organization and Dysfunction |9 G:(DE-HGF)POF4-5251 |x 1 |
| 914 | 1 | _ | |y 2024 |
| 915 | p | c | |a APC keys set |2 APC |0 PC:(DE-HGF)0000 |
| 915 | p | c | |a Local Funding |2 APC |0 PC:(DE-HGF)0001 |
| 915 | p | c | |a DFG OA Publikationskosten |2 APC |0 PC:(DE-HGF)0002 |
| 915 | p | c | |a DOAJ Journal |2 APC |0 PC:(DE-HGF)0003 |
| 915 | p | c | |a DEAL: Springer Nature 2020 |2 APC |0 PC:(DE-HGF)0113 |
| 915 | _ | _ | |a Article Processing Charges |0 StatID:(DE-HGF)0561 |2 StatID |d 2023-08-29 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2023-08-29 |
| 915 | _ | _ | |a Fees |0 StatID:(DE-HGF)0700 |2 StatID |d 2023-08-29 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1190 |2 StatID |b Biological Abstracts |d 2023-08-29 |
| 915 | _ | _ | |a Creative Commons Attribution CC BY 4.0 |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2023-08-29 |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b NAT COMMUN : 2022 |d 2025-01-02 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2025-01-02 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2025-01-02 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0501 |2 StatID |b DOAJ Seal |d 2024-01-30T07:48:07Z |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0500 |2 StatID |b DOAJ |d 2024-01-30T07:48:07Z |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b DOAJ : Peer review |d 2024-01-30T07:48:07Z |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2025-01-02 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1040 |2 StatID |b Zoological Record |d 2025-01-02 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1060 |2 StatID |b Current Contents - Agriculture, Biology and Environmental Sciences |d 2025-01-02 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1150 |2 StatID |b Current Contents - Physical, Chemical and Earth Sciences |d 2025-01-02 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |d 2025-01-02 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1030 |2 StatID |b Current Contents - Life Sciences |d 2025-01-02 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2025-01-02 |
| 915 | _ | _ | |a IF >= 15 |0 StatID:(DE-HGF)9915 |2 StatID |b NAT COMMUN : 2022 |d 2025-01-02 |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-7-20090406 |k INM-7 |l Gehirn & Verhalten |x 0 |
| 980 | 1 | _ | |a FullTexts |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)INM-7-20090406 |
| 980 | _ | _ | |a APC |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|