{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Sun H"],"funding":["NIMH NIH HHS","U.S. Department of Health & Human Services | NIH | National Institute of Mental Health","Wellcome Trust"],"pagination":["10251"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11599754"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["15(1)"],"pubmed_abstract":["Structural and functional connectomes undergo rapid changes during the third trimester and the first month of postnatal life. Despite progress, our understanding of the developmental trajectories of the connectome in the perinatal period remains incomplete. Brain age prediction uses machine learning to estimate the brain's maturity relative to normative data. The difference between the individual's predicted and chronological age-or brain age gap (BAG)-represents the deviation from these normative trajectories. Here, we assess brain age prediction and BAGs using structural and functional connectomes for infants in the first month of life. We use resting-state fMRI and DTI data from 611 infants (174 preterm; 437 term) from the Developing Human Connectome Project (dHCP) and connectome-based "],"journal":["Nature communications"],"pubmed_title":["Brain age prediction and deviations from normative trajectories in the neonatal connectome."],"pmcid":["PMC11599754"],"funding_grant_id":["R01 MH126133","K24 MH127381"],"pubmed_authors":["Scheinost D","Cheng B","Mehta S","Hao X","Sun H","Khaitova M","Spann M"],"additional_accession":[]},"is_claimable":false,"name":"Brain age prediction and deviations from normative trajectories in the neonatal connectome.","description":"Structural and functional connectomes undergo rapid changes during the third trimester and the first month of postnatal life. Despite progress, our understanding of the developmental trajectories of the connectome in the perinatal period remains incomplete. Brain age prediction uses machine learning to estimate the brain's maturity relative to normative data. The difference between the individual's predicted and chronological age-or brain age gap (BAG)-represents the deviation from these normative trajectories. Here, we assess brain age prediction and BAGs using structural and functional connectomes for infants in the first month of life. We use resting-state fMRI and DTI data from 611 infants (174 preterm; 437 term) from the Developing Human Connectome Project (dHCP) and connectome-based ","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Nov","modification":"2025-04-22T20:41:57.17Z","creation":"2025-04-06T03:15:16.055Z"},"accession":"S-EPMC11599754","cross_references":{"pubmed":["39592647"],"doi":["10.1038/s41467-024-54657-5"]}}