Regional gray matter growth, sexual dimorphism, and cerebral asymmetry in the neonatal brain

John H Gilmore, Weili Lin, Marcel W Prastawa, Christopher B Looney, Y Sampath K Vetsa, Rebecca C Knickmeyer, Dianne D Evans, J Keith Smith, Robert M Hamer, Jeffrey A Lieberman, Guido Gerig, John H Gilmore, Weili Lin, Marcel W Prastawa, Christopher B Looney, Y Sampath K Vetsa, Rebecca C Knickmeyer, Dianne D Evans, J Keith Smith, Robert M Hamer, Jeffrey A Lieberman, Guido Gerig

Abstract

Although there has been recent interest in the study of childhood and adolescent brain development, very little is known about normal brain development in the first few months of life. In older children, there are regional differences in cortical gray matter development, whereas cortical gray and white matter growth after birth has not been studied to a great extent. The adult human brain is also characterized by cerebral asymmetries and sexual dimorphisms, although very little is known about how these asymmetries and dimorphisms develop. We used magnetic resonance imaging and an automatic segmentation methodology to study brain structure in 74 neonates in the first few weeks after birth. We found robust cortical gray matter growth compared with white matter growth, with occipital regions growing much faster than prefrontal regions. Sexual dimorphism is present at birth, with males having larger total brain cortical gray and white matter volumes than females. In contrast to adults and older children, the left hemisphere is larger than the right hemisphere, and the normal pattern of fronto-occipital asymmetry described in older children and adults is not present. Regional differences in cortical gray matter growth are likely related to differential maturation of sensory and motor systems compared with prefrontal executive function after birth. These findings also indicate that whereas some adult patterns of sexual dimorphism and cerebral asymmetries are present at birth, others develop after birth.

Figures

Figure 1.
Figure 1.
A–C, T1-weighted (A) and T2-weighted (B) images are automatically segmented (C) into CSF (blue), gray matter (yellow), unmyelinated white matter (green), and myelinated white matter (purple). D, Template of the neonatal brain for automatic parcellation into 16 cortical regions (left and right, superior and inferior, prefrontal, frontal, and parietal and occipital regions, respectively), right and left subcortical regions, brainstem, and cerebellum.
Figure 2.
Figure 2.
Tissue-specific growth rates in whole brain (n = 74). There is a significant overall difference in slopes (inhomogeneity of slopes: F(3,288) = 16.6; p < 0.0001). There are significant differences in growth rates between gray matter (GM) and unmyelinated white matter (umWM) (F(1,288) = 28.0; p < 0.0001) and between GM and myelinated white matter (mWM) (F(1,288) = 44.9; p < 0.0001).
Figure 3.
Figure 3.
Regional growth of cortical gray matter (n = 74). There is a significant overall regional difference in slopes (inhomogeneity of slopes: F(3,288) = 8.6; p < 0.0001). There were significant differences between occipital and prefrontal (F(1,288) = 18.9; p < 0.0001), occipital and frontal (F(1,288) = 5.8; p = 0.0166), and parietal and prefrontal (F(1,288) = 17.9; p < 0.0001) matter growth rates.
Figure 4.
Figure 4.
Regional growth of cortical unmyelinated white matter (n = 74). There was not a significant regional difference in slopes for unmyelinated white matter (inhomogeneity of slopes: F(3,288) = 1.5; p = 0.2180).

Source: PubMed

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