人类大脑衰老连续体的低维多重表示
bioRxiv : the preprint server for biology
|October 3, 2025
概括
大脑衰老涉及复杂的结构变化. 使用MRI数据的新型低维多元方法揭示了个体的大脑衰老模式,并确定了特定的区域变化,如男性的额头缩.
科学领域:
- 神经成像是一种神经成像.
- 老年学是指老年学的学科.
- 计算神经科学是一种神经科学.
背景情况:
- 大脑衰老呈现出复杂的结构变化,使得个体大脑健康评估具有挑战性.
- 之前的研究记录了与年龄相关的大脑变化,但由于高维度,很难整合多结构数据进行个人评估.
研究的目的:
- 开发一个透明的框架来评估个人的大脑衰老状态.
- 为了确定有助于整体大脑衰老的特定区域大脑变化.
- 研究不同亚组中大脑衰老的异质性质.
主要方法:
- 利用了来自人类连接体项目衰老数据集的结构磁共振成像 (MRI) 数据.
- 将与年龄相关的区域体积变化映射到一个代表神经解剖学约束的低维多元.
- 在多个社区内分析数据,以识别同质子组中的独特结构变化.
主要成果:
- 证明了与年龄相关的区域大脑体积变化符合低维多元.
- 开发了一个评估个体大脑衰老状况和确定推动区域变化的框架.
- 在子组内确定了明显的结构变化,包括主要在男性参与者中显著的额头缩.
结论:
- 多重表示提供了一种透明和有效的方法来理解个人的大脑衰老.
- 聚合局部模式为大脑衰老提供了全面的视图,突出了其异质性质.
- 研究结果为与年龄相关的大脑变化的性别特异性模式提供了新的见解,例如男性的额头缩.
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