Fine-grained functional parcellation maps of the infant cerebral cortex.
functional connectivity
functional parcellation
human
infant brain
neuroscience
Journal
eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614
Informations de publication
Date de publication:
01 08 2023
01 08 2023
Historique:
received:
09
11
2021
accepted:
17
07
2023
medline:
2
8
2023
pubmed:
1
8
2023
entrez:
1
8
2023
Statut:
epublish
Résumé
Resting-state functional MRI (rs-fMRI) is widely used to examine the dynamic brain functional development of infants, but these studies typically require precise cortical parcellation maps, which cannot be directly borrowed from adult-based functional parcellation maps due to the substantial differences in functional brain organization between infants and adults. Creating infant-specific cortical parcellation maps is thus highly desired but remains challenging due to difficulties in acquiring and processing infant brain MRIs. In this study, we leveraged 1064 high-resolution longitudinal rs-fMRIs from 197 typically developing infants and toddlers from birth to 24 months who participated in the Baby Connectome Project to develop the first set of infant-specific, fine-grained, surface-based cortical functional parcellation maps. To establish meaningful cortical functional correspondence across individuals, we performed cortical co-registration using both the cortical folding geometric features and the local gradient of functional connectivity (FC). Then we generated both age-related and age-independent cortical parcellation maps with over 800 fine-grained parcels during infancy based on aligned and averaged local gradient maps of FC across individuals. These parcellation maps reveal complex functional developmental patterns, such as changes in local gradient, network size, and local efficiency, especially during the first 9 postnatal months. Our generated fine-grained infant cortical functional parcellation maps are publicly available at https://www.nitrc.org/projects/infantsurfatlas/ for advancing the pediatric neuroimaging field.
Identifiants
pubmed: 37526293
doi: 10.7554/eLife.75401
pii: 75401
pmc: PMC10393291
doi:
pii:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : NIMH NIH HHS
ID : MH116225
Pays : United States
Organisme : NIMH NIH HHS
ID : 1U01MH110274
Pays : United States
Organisme : NIMH NIH HHS
ID : MH117943
Pays : United States
Organisme : NIMH NIH HHS
ID : MH123202
Pays : United States
Organisme : NIMH NIH HHS
ID : MH127544
Pays : United States
Informations de copyright
© 2023, Wang et al.
Déclaration de conflit d'intérêts
FW, HZ, ZW, DH, ZZ, JG, LW, WL, GL No competing interests declared
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