Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
Commun Biol. 2024 Sep 17;7(1):1163. doi: 10.1038/s42003-024-06876-1.
The cortical development of our brains is in a hierarchical manner and promotes the emergence of large-scale functional hierarchy. However, under interindividual heterogenicity, how the spatiotemporal features of brain networks reflect brain development and mental health remains unclear. Here we collect both resting-state electroencephalography and functional magnetic resonance imaging data from the Child Mind Institute Biobank to demonstrate that during brain growth, the global dynamic patterns of brain states become more active and the dominant networks shift from sensory to higher-level networks; the individual functional network patterns become more similar to that of adults and their spatial coupling tends to be invariable. Furthermore, the properties of multimodality brain networks are sufficiently robust to identify healthy brain age and mental disorders at specific ages. Therefore, multimodality brain networks provide new insights into the functional development of the brain and a more reliable and reasonable approach for age prediction and individual diagnosis.
我们大脑的皮质发育具有层次结构,促进了大规模功能层次结构的出现。然而,在个体间异质性下,大脑网络的时空特征如何反映大脑发育和心理健康尚不清楚。在这里,我们收集了来自儿童心理研究所生物库的静息态脑电图和功能磁共振成像数据,结果表明,在大脑生长过程中,大脑状态的全局动态模式变得更加活跃,主导网络从感觉网络转移到更高层次的网络;个体功能网络模式变得更类似于成年人,并且它们的空间耦合趋于不变。此外,多模态脑网络的特性足够稳健,可以在特定年龄识别健康的脑龄和精神障碍。因此,多模态脑网络为大脑的功能发育提供了新的视角,并为年龄预测和个体诊断提供了一种更可靠和合理的方法。