Executive functions of six-year-old boys with normal birth weight and gestational age.

Impaired fetal development, reflected by low birth weight or prematurity, predicts an increased risk for psychopathology, especially attention deficit hyperactivity disorder (ADHD). Such effects cut across the normal range of birth weight and gestation. Despite the strength of existing epidemiological data, cognitive pathways that link fetal development to mental health are largely unknown. In this study we examined the relation of birth weight (>2500 g) and gestational age (37-41 weeks) within the normal range with specific executive functions in 195 Singaporean six-year-old boys of Chinese ethnicity. Birth weight adjusted for gestational age was used as indicator of fetal growth while gestational age was indicative of fetal maturity. Linear regression revealed that increased fetal growth within the normal range is associated with an improved ability to learn rules during the intra/extra-dimensional shift task and to retain visual information for short period of time during the delayed matching to sample task. Moreover, faster and consistent reaction times during the stop-signal task were observed among boys born at term, but with higher gestational age. Hence, even among boys born at term with normal birth weight, variations in fetal growth and maturity showed distinct effects on specific executive functions.

Birth weight and gestation influence striatal morphology and motor response in normal six-year-old boys.

The relation between fetal growth and attention deficit hyperactivity disorder (ADHD) cuts across the normal range of birth weights suggesting that subtle variations in fetal development may influence brain and cognitive function. We investigated the relation of ADHD-related endophenotypes, such as the striatum morphology, motor response and inhibition, with birth weight and gestational age in healthy children. 157 Six-year-old boys born at term (37 to 41 weeks) within the normal range for birth weight (2500 to 4630 g) underwent magnetic resonance imaging (MRI) and performed the stop signal task. Linear regression was used to examine effects of birth weight, gestational age, and their interaction on striatal volumes and shapes as well as motor response and inhibition. Interactive effects of birth weight and gestational age, even within the normal range, predicted caudate volumes and shapes. Boys with relatively low birth weight and shorter gestation had smaller caudate volumes, reflected by shape contraction in the middle body, and in addition performed worst in motor response, reflected by mean reaction time and its variability. Our results supported the idea that prenatal influences on neurocognitive and brain development are not limited to the extreme range, but occur across the entire population. Variations in brain structure and cognitive endophenotypes associated with childhood ADHD psychopathology are sensitive to subtle prenatal influences, which provides guidance for intervention research to improve mental health of children.

Quantitative evaluation of LDDMM, FreeSurfer, and CARET for cortical surface mapping.

Cortical surface mapping has been widely used to compensate for individual variability of cortical shape and topology in anatomical and functional studies. While many surface mapping methods were proposed based on landmarks, curves, spherical or native cortical coordinates, few studies have extensively and quantitatively evaluated surface mapping methods across different methodologies. In this study we compared five cortical surface mapping algorithms, including large deformation diffeomorphic metric mapping (LDDMM) for curves (LDDMM-curve), for surfaces (LDDMM-surface), multi-manifold LDDMM (MM-LDDMM), FreeSurfer, and CARET, using 40 MRI scans and 10 simulated datasets. We computed curve variation errors and surface alignment consistency for assessing the mapping accuracy of local cortical features (e.g., gyral/sulcal curves and sulcal regions) and the curvature correlation for measuring the mapping accuracy in terms of overall cortical shape. In addition, the simulated datasets facilitated the investigation of mapping error distribution over the cortical surface when the MM-LDDMM, FreeSurfer, and CARET mapping algorithms were applied. Our results revealed that the LDDMM-curve, MM-LDDMM, and CARET approaches best aligned the local curve features with their own curves. The MM-LDDMM approach was also found to be the best in aligning the local regions and cortical folding patterns (e.g., curvature) as compared to the other mapping approaches. The simulation experiment showed that the MM-LDDMM mapping yielded less local and global deformation errors than the CARET and FreeSurfer mappings.