Hippocampal anterior- posterior shift in childhood and adolescence
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Hippocampal-cortical networks play an important role in neurocognitive development. Applying the method of Connectivity-Based Parcellation (CBP) on hippocampal-cortical structural covariance (SC) networks computed from T1-weighted magnetic resonance images, we examined how the hippocampus differentiates into subregions during childhood and adolescence (N = 1105, 6–18 years). In late childhood, the hippocampus mainly differentiated along the anterior-posterior axis similar to previous reported functional differentiation patterns of the hippocampus. In contrast, in adolescence a differentiation along the medial-lateral axis was evident, reminiscent of the cytoarchitectonic division into cornu ammonis and subiculum. Further meta-analytical characterization of hippocampal subregions in terms of related structural co-maturation networks, behavioural and gene profiling suggested that the hippocampal head is related to higher order functions (e.g. language, theory of mind, autobiographical memory) in late childhood morphologically co-varying with almost the whole brain. In early adolescence but not in childhood, posterior subicular SC networks were associated with action-oriented and reward systems. The findings point to late childhood as an important developmental period for hippocampal head morphology and to early adolescence as a crucial period for hippocampal integration into action- and reward-oriented cognition. The latter may constitute a developmental feature that conveys increased propensity for addictive disorders.
| Originalsprog | Engelsk |
|---|---|
| Artikelnummer | 102447 |
| Tidsskrift | Progress in Neurobiology |
| Vol/bind | 225 |
| ISSN | 0301-0082 |
| DOI | |
| Status | Udgivet - 2023 |
Bibliografisk note
Funding Information:
This work was supported by the Deutsche Forschungsgemeinschaft (DFG, GE 2835/2-1 , EI 816/16-1 and EI 816/21-1 ), the National Institute of Mental Health ( R01-MH074457 ), the Helmholtz Joint Lab "Supercomputing and Modeling for the Human Brain" , the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 785907 ( HBP SGA2) , 945539 ( HBP SGA3 ), The Virtual Brain Cloud ( EU H2020 , no. 826421 ) and by Lifebrain Project Grant (grant agreement number 732592 ). AP was supported by Region Hovedstadens Forskningsfond 2021 (grant number A7118 ). HRS holds a 5-year professorship in precision medicine at the Faculty of Health Sciences and Medicine, University of Copenhagen which is sponsored by the Lundbeck Foundation (Grant Nr. R186-2015-2138 ).
Funding Information:
This work was supported by the Deutsche Forschungsgemeinschaft (DFG, GE 2835/2-1, EI 816/16-1 and EI 816/21-1), the National Institute of Mental Health (R01-MH074457), the Helmholtz Joint Lab "Supercomputing and Modeling for the Human Brain", the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement 785907 (HBP SGA2), 945539 (HBP SGA3), The Virtual Brain Cloud (EU H2020, no. 826421) and by Lifebrain Project Grant (grant agreement number 732592). AP was supported by Region Hovedstadens Forskningsfond 2021 (grant number A7118). HRS holds a 5-year professorship in precision medicine at the Faculty of Health Sciences and Medicine, University of Copenhagen which is sponsored by the Lundbeck Foundation (Grant Nr. R186-2015-2138).
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