Cao Miao, Huang Hao, Peng Yun, Dong Qi, He Yong
State Key Laboratory of Cognitive Neuroscience and Learning and International Data Group/McGovern Institute for Brain Research, Beijing Normal University Beijing, China.
Department of Radiology, Children's Hospital of PhiladelphiaPhiladelphia, PA, USA; Department of Radiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphia, PA, USA.
Front Neuroanat. 2016 Mar 31;10:25. doi: 10.3389/fnana.2016.00025. eCollection 2016.
Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying structural and functional connectivity patterns of the developing brain. Normal brain development is characterized by continuous and significant network evolution throughout infancy, childhood, and adolescence, following specific maturational patterns. Disruption of these normal changes is associated with neuropsychiatric developmental disorders, such as autism spectrum disorders or attention-deficit hyperactivity disorder. In this review, we focused on the recent progresses regarding typical and atypical development of human brain networks from birth to early adulthood, using a connectomic approach. Specifically, by the time of birth, structural networks already exhibit adult-like organization, with global efficient small-world and modular structures, as well as hub regions and rich-clubs acting as communication backbones. During development, the structure networks are fine-tuned, with increased global integration and robustness and decreased local segregation, as well as the strengthening of the hubs. In parallel, functional networks undergo more dramatic changes during maturation, with both increased integration and segregation during development, as brain hubs shift from primary regions to high order functioning regions, and the organization of modules transitions from a local anatomical emphasis to a more distributed architecture. These findings suggest that structural networks develop earlier than functional networks; meanwhile functional networks demonstrate more dramatic maturational changes with the evolution of structural networks serving as the anatomical backbone. In this review, we also highlighted topologically disorganized characteristics in structural and functional brain networks in several major developmental neuropsychiatric disorders (e.g., autism spectrum disorders, attention-deficit hyperactivity disorder and developmental dyslexia). Collectively, we showed that delineation of the brain network from a connectomics perspective offers a unique and refreshing view of both normal development and neuropsychiatric disorders.
基于图论的成像连接组学已成为研究发育中大脑结构和功能连接模式的有效且独特的方法框架。正常的大脑发育特征是在婴儿期、儿童期和青少年期整个过程中,遵循特定的成熟模式,大脑网络持续且显著地进化。这些正常变化的破坏与神经精神发育障碍相关,如自闭症谱系障碍或注意力缺陷多动障碍。在本综述中,我们使用连接组学方法,聚焦于从出生到成年早期人类大脑网络典型和非典型发育的最新进展。具体而言,在出生时,结构网络已呈现出类似成人的组织,具有全局高效的小世界和模块化结构,以及作为通信主干的枢纽区域和富俱乐部。在发育过程中,结构网络会进行微调,全局整合和稳健性增加,局部隔离减少,同时枢纽得到加强。与此同时,功能网络在成熟过程中经历更显著的变化,在发育过程中整合和隔离都增加,因为大脑枢纽从初级区域转移到高阶功能区域,模块组织从局部解剖学重点转变为更分布式的架构。这些发现表明结构网络比功能网络发育更早;同时,功能网络随着作为解剖学主干的结构网络的进化,表现出更显著的成熟变化。在本综述中,我们还强调了几种主要发育性神经精神障碍(如自闭症谱系障碍、注意力缺陷多动障碍和发育性阅读障碍)中结构和功能大脑网络的拓扑紊乱特征。总体而言,我们表明从连接组学角度描绘大脑网络为正常发育和神经精神障碍提供了独特而新颖的视角。