儿童早期发展的大脑网络动态:模块化图表指标的洞察力
Zeyu Song1, Zhenqi Jiang1, Zhao Zhang1
1School of Medical Technology, Beijing Institute of Technology Zhengzhou Academy of Intelligent Technology, Beijing Institute of Technology, Beijing 100081, PR China.
NeuroImage
|July 24, 2024
概括
大脑网络的相互作用在幼儿时期变得更加专业化,从全球整合转向本地处理. 这一发展影响了信息传输效率,突出网络发挥了关键作用.
科学领域:
- 神经科学是一个神经科学.
- 发育神经科学的发展神经科学.
- 网络科学 网络科学
背景情况:
- 模块化动态图形理论指标捕捉大脑发育模式.
- 现有的研究缺乏了解早期儿童功能网络的跨社区变化及其对信息传输效率的影响.
研究的目的:
- 追踪早期儿童功能网络的跨社区结构变化.
- 模拟这些变化对信息传输效率的贡献.
主要方法:
- 分析了来自83名儿童 (2至8岁) 的194个功能性MRI扫描.
- 使用了滑动窗口,模块化算法和时空/中心度量.
- 采用混合效应线性模型和调解分析.
主要成果:
- 与年龄相关的时间灵活性 (DMN,ECN,SN) 和SN空间时间多样性的显著增加.
- 在语言网络中减少了社区内部的多样性,表明了专业化.
- 增加了社区间的中心性 (DMN,ECN,SN,语言,背部注意网络).
- SN动态调解了全球效率的与年龄相关的变化,而多个网络则调解了当地效率的变化.
结论:
- 儿童早期的大脑发育显示了信息处理中从全球一体化向地方隔离的转变.
- 在这种发展转型中,突出网络至关重要.
- 跨社区网络的调整在开发过程中显著影响信息传输效率.
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