Annual Research Review: Growth connectomics - the organization and reorganization of brain networks during normal and abnormal development

被引:148
作者
Vertes, Petra E. [1 ,2 ]
Bullmore, Edward T. [1 ,2 ,3 ]
机构
[1] Univ Cambridge, Dept Psychiat, Behav & Clin Neurosci Inst, Cambridge, England
[2] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England
[3] GlaxoSmithKline, ImmunoPsychiat, Alternat Discovery & Dev, Cambridge, England
基金
英国医学研究理事会; 英国惠康基金;
关键词
Brain networks; connectomics; development; cognitive change; neurodevelopmental disorders; STATE FUNCTIONAL CONNECTIVITY; GRAPH-THEORETICAL ANALYSIS; HUMAN CORTICAL DEVELOPMENT; WHITE-MATTER MATURATION; RESTING HUMAN BRAIN; STRUCTURAL CONNECTIVITY; DEFAULT MODE; ANATOMICAL NETWORKS; WIRING OPTIMIZATION; BOLD FLUCTUATIONS;
D O I
10.1111/jcpp.12365
中图分类号
B844 [发展心理学(人类心理学)];
学科分类号
040202 ;
摘要
BackgroundWe first give a brief introduction to graph theoretical analysis and its application to the study of brain network topology or connectomics. Within this framework, we review the existing empirical data on developmental changes in brain network organization across a range of experimental modalities (including structural and functional MRI, diffusion tensor imaging, magnetoencephalography and electroencephalography in humans). SynthesisWe discuss preliminary evidence and current hypotheses for how the emergence of network properties correlates with concomitant cognitive and behavioural changes associated with development. We highlight some of the technical and conceptual challenges to be addressed by future developments in this rapidly moving field. Given the parallels previously discovered between neural systems across species and over a range of spatial scales, we also review some recent advances in developmental network studies at the cellular scale. We highlight the opportunities presented by such studies and how they may complement neuroimaging in advancing our understanding of brain development. Finally, we note that many brain and mind disorders are thought to be neurodevelopmental in origin and that charting the trajectory of brain network changes associated with healthy development also sets the stage for understanding abnormal network development. ConclusionsWe therefore briefly review the clinical relevance of network metrics as potential diagnostic markers and some recent efforts in computational modelling of brain networks which might contribute to a more mechanistic understanding of neurodevelopmental disorders in future. Read the Commentary on this article at doi
引用
收藏
页码:299 / 320
页数:22
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