Department of Psychiatry, Columbia University, New York, NY, USA; New York State Psychiatric Institute, New York, NY, USA.
Institute for the Developing Mind, Children's Hospital Los Angeles, Los Angeles, CA, USA; The Keck School of Medicine, The University of Southern California, Los Angeles, CA, USA.
Eur J Paediatr Neurol. 2018 Jul;22(4):642-651. doi: 10.1016/j.ejpn.2018.03.003. Epub 2018 Mar 24.
The development of brain circuits is coupled with changes in neurovascular coupling, which refers to the close relationship between neural activity and cerebral blood flow (CBF). Studying the characteristics of CBF during resting state in developing brain can be a complementary way to understand the functional connectivity of the developing brain. Arterial spin labeling (ASL), as a noninvasive MR technique, is particularly attractive for studying cerebral perfusion in children and even newborns. We have collected pulsed ASL data in resting state for 47 healthy subjects from young children to adolescence (aged from 6 to 20 years old). In addition to studying the developmental change of static CBF maps during resting state, we also analyzed the CBF time series to reveal the dynamic characteristics of CBF in differing age groups. We used the seed-based correlation analysis to examine the temporal relationship of CBF time series between the selected ROIs and other brain regions. We have shown the developmental patterns in both static CBF maps and dynamic characteristics of CBF. While higher CBF of default mode network (DMN) in all age groups supports that DMN is the prominent active network during the resting state, the CBF connectivity patterns of some typical resting state networks show distinct patterns of metabolic activity during the resting state in the developing brains.
脑回路的发育伴随着神经血管耦联的变化,即神经活动与脑血流(CBF)之间的密切关系。研究发育中大脑静息状态下的 CBF 特征可以作为理解发育中大脑功能连接的一种补充方式。动脉自旋标记(ASL)作为一种非侵入性的磁共振技术,特别适合研究儿童甚至新生儿的脑灌注。我们已经收集了 47 名来自幼儿到青少年(年龄 6 至 20 岁)的健康受试者在静息状态下的脉冲 ASL 数据。除了研究静息状态下静态 CBF 图的发育变化外,我们还分析了 CBF 时间序列,以揭示不同年龄组 CBF 的动态特征。我们使用基于种子的相关分析来检查选定 ROI 和其他脑区之间的 CBF 时间序列的时间关系。我们已经展示了静态 CBF 图和 CBF 动态特征的发育模式。虽然所有年龄组默认模式网络(DMN)的 CBF 较高,表明 DMN 是静息状态下的突出活动网络,但一些典型静息状态网络的 CBF 连接模式在发育中的大脑静息状态下显示出不同的代谢活动模式。