Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104, USA.
Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA.
Neuron. 2020 Apr 22;106(2):340-353.e8. doi: 10.1016/j.neuron.2020.01.029. Epub 2020 Feb 19.
The spatial distribution of large-scale functional networks on the cerebral cortex differs between individuals and is particularly variable in association networks that are responsible for higher-order cognition. However, it remains unknown how this functional topography evolves in development and supports cognition. Capitalizing on advances in machine learning and a large sample imaged with 27 min of high-quality functional MRI (fMRI) data (n = 693, ages 8-23 years), we delineate how functional topography evolves during youth. We found that the functional topography of association networks is refined with age, allowing accurate prediction of unseen individuals' brain maturity. The cortical representation of association networks predicts individual differences in executive function. Finally, variability of functional topography is associated with fundamental properties of brain organization, including evolutionary expansion, cortical myelination, and cerebral blood flow. Our results emphasize the importance of considering the plasticity and diversity of functional neuroanatomy during development and suggest advances in personalized therapeutics.
大脑皮层上大规模功能网络的空间分布在个体之间存在差异，在负责更高阶认知的关联网络中尤为多变。然而，目前尚不清楚这种功能拓扑结构如何在发育过程中发展并支持认知。利用机器学习的进展和利用 27 分钟高质量功能磁共振成像 (fMRI) 数据对 693 名年龄在 8-23 岁的个体进行的大样本成像，我们描绘了功能拓扑结构在青少年时期的发展情况。我们发现，关联网络的功能拓扑结构随着年龄的增长而变得更加精细，能够准确预测未见过的个体的大脑成熟度。关联网络的皮质代表预测了执行功能的个体差异。最后，功能拓扑的可变性与大脑组织的基本特性有关，包括进化扩展、皮质髓鞘形成和脑血流。我们的研究结果强调了在发展过程中考虑功能神经解剖结构的可塑性和多样性的重要性，并为个性化治疗提供了新的思路。
