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. 2013 Aug 1:76:216-24.
doi: 10.1016/j.neuroimage.2013.03.021. Epub 2013 Mar 21.

Development of cortical anatomical properties from early childhood to early adulthood

Affiliations

Development of cortical anatomical properties from early childhood to early adulthood

Jingxin Nie et al. Neuroimage. .

Abstract

Human brain matures in temporal and regional heterogeneity, with some areas matured at early adulthood. In this study, the relationship of cortical structural developments between different cortical sheet regions is systematically analyzed using interregional correlation coefficient and network methods. Specifically, 951 longitudinal T1 brain MR images from 445 healthy subjects with ages from 3 to 20 years old are used. The result shows that the development of cortex reaches a turning point at around 7 years of age: a) the cortical thickness reaches its highest value and also the cortical folding becomes stable at this age; b) both global and local efficiencies of anatomical correlation networks reach the lowest and highest values at this age, respectively; and c) the change of anatomical correlation networks reach the highest level at this age, and the convergence of different anatomical correlation networks starts to decrease from this age. These results might inspire more studies on why there exists a turning point at this age from different viewpoints. For example, is there any change of synaptic pruning, or is it related to the starting of school life? And how can we benefit from this in the real life?

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Conflict of interest statement

Conflict of interest statement: The authors report no biomedical financial interests or potential conflicts of interest related to this article.

Figures

Fig. 1
Fig. 1
The number of sessions at each year.
Fig. 2
Fig. 2
The development of the hemispheric symmetry between corresponding left and right ROIs from 3 to 20 years of age, using linear regression of correlation values (red: increase of symmetry; blue: decrease of symmetry). (a) Thickness correlation. (b) Curvedness correlation.
Fig. 3
Fig. 3
The parcellation of the cortex by the similarity of developmental patterns in ROIs. (a) Thickness correlation. (b) Curvedness correlation.
Fig. 4
Fig. 4
The development of global and local efficiencies on the thickness and curvedness correlation networks (sparsity = 0.234).
Fig. 5
Fig. 5
The change of percentage of convergence of the thickness and curvedness correlation networks during the development.
Fig. 6
Fig. 6
The development of hub regions in the thickness and curvedness correlation networks from 3 to 20 years of age. (a) Hub regions in the thickness correlation network, (b) hub regions in the curvedness correlation network.

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