DOI 10.1016/j.neuroimage.2025.121586
Age-dependent brain neuroimaging signatures in rhesus monkeys.
Аннотация
Despite advancements in understanding macroscopic and functional brain changes in developing nonhuman primates, a comprehensive in vivo understanding of underlying quantitative microstructural and compositional tissue changes remains elusive. To address this knowledge gap, we applied a quantitative multimodal magnetic resonance imaging (MRI) approach, integrating T1 relaxation time, R2* relaxation rate, and voxel-based morphometry, alongside hematology and serum chemistry analyses, in 94 rhesus monkeys of varying ages (62 males, 32 females; mean age = 5.66±2.08 yr; age range = 1.96-10.3 yr). Our in vivo multimodal analyses revealed distinct age-dependent brain patterns: R2* sharply increased before the age of 5 in deep gray matter (globus pallidus, striatum, thalamus), indicating rapid early iron accumulation in the brain, and then plateaued, strongly supporting a 5-yr developmental age threshold. T1 increased with age in the brainstem and cerebellum, suggesting unique microstructural changes. Voxel-based morphometry revealed a significant volume increase in the deep gray matter, including the thalamus and striatum, and white matter. This study highlights advanced quantitative MRI as a precise, noninvasive developmental index for tracking age-dependent brain tissue properties and microstructural organization in rhesus monkeys during critical developmental ages. These findings provide a robust methodological framework for future research on nonhuman primates, advancing the understanding of neurodevelopment.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.