Trajectories and Milestones of Cortical and Subcortical Development of the Marmoset Brain From Infancy to Adulthood

Abstract With increasing attention on the developmental causes of neuropsychiatric disorders, appropriate animal models are crucial to identifying causes and assessing potential interventions. The common marmoset is an ideal model as it has sophisticated social/emotional behavior, reaching adulthood...

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Veröffentlicht in:Cerebral cortex (New York, N.Y. 1991) N.Y. 1991), 2018-12, Vol.28 (12), p.4440-4453
Hauptverfasser: Sawiak, S J, Shiba, Y, Oikonomidis, L, Windle, C P, Santangelo, A M, Grydeland, H, Cockcroft, G, Bullmore, E T, Roberts, A C
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Sprache:eng
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Zusammenfassung:Abstract With increasing attention on the developmental causes of neuropsychiatric disorders, appropriate animal models are crucial to identifying causes and assessing potential interventions. The common marmoset is an ideal model as it has sophisticated social/emotional behavior, reaching adulthood within 2 years of birth. Magnetic resonance imaging was used in an accelerated longitudinal cohort (n = 41; aged 3-27 months; scanned 2-7 times over 2 years). Splines were used to model nonlinear trajectories of grey matter volume development in 53 cortical areas and 16 subcortical nuclei. Generally, volumes increased before puberty, peaked, and declined into adulthood. We identified 3 milestones of grey matter development: I) age at peak volume; II) age at onset of volume decline; and III) age at maximum rate of volume decline. These milestones differentiated growth trajectories of primary sensory/motor cortical areas from those of association cortex but also revealed distinct trajectories between association cortices. Cluster analysis of trajectories showed that prefrontal cortex was the most heterogenous of association regions, comprising areas with distinct milestones and developmental trajectories. These results highlight the potential of high-field structural MRI to define the dynamics of primate brain development and importantly to identify when specific prefrontal circuits may be most vulnerable to environmental impact.
ISSN:1047-3211
1460-2199
DOI:10.1093/cercor/bhy256