The results of this analysis are summarized in Figure 4 Males an

The results of this analysis are summarized in Figure 4. Males and females showed strong and statistically indistinguishable positive relationships between the pace of left FPC CT change and that within widespread bilateral medial and see more lateral prefrontal, lateral temporal, angular and supramarginal, and superior parietal cortices (Figure 4A). Coupling with left FPC maturation was, however, significantly enhanced in females as compared to males in bilateral DLPFC and right VLPFC (Figure 4B). Enhanced coupling with left FPC maturation in males relative to females was restricted to small regions in the left orbitofrontal

cortex, marginal sulcus, and parieto-occipital fissure. These findings held when analyses were conducted using CT change maps in which CT had been expressed as a proportion

of starting CT (results not shown), suggesting that sex differences in maturational coupling are unlikely to be an artifact of differences in brain size between males and females. The findings generated by our study of correlated anatomical change within the developing human brain fall into three broad groups. First, we demonstrate that rates of anatomical change in different parts of the developing cortex show a highly nonrandom correlational structure, and that the magnitude of this maturational coupling varies systematically across the cortical sheet. Specifically, rates of CT change in frontal and temporal association Selleck Docetaxel cortices display the strongest and most spatially extensive correlation with CT changes in the rest of the cortex, whereas the opposite is seen in primary visual and sensorimotor cortices. These regional differences show several convergences with regional differences in cross-sectional CT correlation (Lerch et al., 2006), and we were able to rule out the possibility that these convergences solely arose as an artifact of hidden

relationship between CT and CT change Cell press in our data set. A reasonable inference therefore is that patterns of cross-sectional CT correlation arise as a result of correlated maturation over time. By extension, established characteristics of cross-sectional CT correlation including its heritability (Schmitt et al., 2009), network modularity (Chen et al., 2008), and relationship with cognitive ability (Lerch et al., 2006) are likely to apply to correlated CT change, and these hypotheses can be directly tested in future work. The factors that might contribute to the regional differences in degree of coupling with global cortical maturation remain unclear.

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