Negative associations between corpus callosum midsagittal area and IQ in a representative sample of healthy children and adolescents.

Documented associations between corpus callosum size and cognitive ability have heretofore been inconsistent potentially owing to differences in sample characteristics, differing methodologies in measuring CC size, or the use of absolute versus relative measures. We investigated the relationship between CC size and intelligence quotient (IQ) in the NIH MRI Study of Normal Brain Development sample, a large cohort of healthy children and adolescents (aged six to 18, n = 198) recruited to be representative of the US population. CC midsagittal area was measured using an automated system that partitioned the CC into 25 subregions. IQ was measured using the Wechsler Abbreviated Scale of Intelligence (WASI). After correcting for total brain volume and age, a significant negative correlation was found between total CC midsagittal area and IQ (r = -0.147; p = 0.040). Post hoc analyses revealed a significant negative correlation in children (ag

Anxious/depressed symptoms are related to microstructural maturation of white matter in typically developing youths

AbstractThere are multiple recent reports of an association between anxious/depressed (A/D) symptomatology and the rate of cerebral cortical thickness maturation in typically developing youths. We investigated the degree to which anxious/depressed symptoms are tied to age-related microstructural changes in cerebral fiber pathways. The participants were part of the NIH MRI Study of Normal Brain Development. Child Behavior Checklist A/D scores and diffusion imaging were available for 175 youths (84 males, 91 females; 241 magnetic resonance imagings) at up to three visits. The participants ranged from 5.7 to 18.4 years of age at the time of the scan. Alignment of fractional anisotropy data was implemented using FSL/Tract-Based Spatial Statistics, and linear mixed model regression was carried out using SPSS. Child Behavior Checklist A/D was associated with the rate of microstructural development in several white matter pathways, including the bilateral anterior thalamic radiation, bilateral inferior longitudinal fasciculus, left superior longitudinal fasciculus, and right cingulum. Across these pathways, greater age-related fractional anisotropy increases were observed at lower levels of A/D. The results suggest that subclinical A/D symptoms are associated with the rate of microstructural development within several white matter pathways that have been implicated in affect regulation, as well as mood and anxiety psychopathology.</jats:p

Macrocerebellum, epilepsy, intellectual disability, and gut malrotation in a child with a 16q24.1–q24.2 contiguous gene deletion

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108054/1/ajmga36569.pd

Insecure attachment during infancy predicts greater amygdala volumes in early adulthood

Background The quality of the early environment is hypothesized to be an influence on morphological development in key neural areas related to affective responding, but direct evidence to support this possibility is limited. In a 22-year longitudinal study, we examined hippocampal and amygdala volumes in adulthood in relation to early infant attachment status, an important indicator of the quality of the early caregiving environment. Methods Participants (N = 59) were derived from a prospective longitudinal study of the impact of maternal postnatal depression on child development. Infant attachment status (24 Secure; 35 Insecure) was observed at 18 months of age, and MRI assessments were completed at 22 years. Results In line with hypotheses, insecure versus secure infant attachment status was associated with larger amygdala volumes in young adults, an effect that was not accounted for by maternal depression history. We did not find early infant attachment status to predict hippocampal volumes. Conclusions Common variations in the quality of early environment are associated with gross alterations in amygdala morphology in the adult brain. Further research is required to establish the neural changes that underpin the volumetric differences reported here, and any functional implications

Adolescent brain development

Adolescence starts with puberty and ends when individuals attain an independent role in society. Cognitive neuroscience research in the last two decades has improved our understanding of adolescent brain development. The evidence indicates a prolonged structural maturation of grey matter and white matter tracts supporting higher cognitive functions such as cognitive control and social cognition. These changes are associated with a greater strengthening and separation of brain networks, both in terms of structure and function, as well as improved cognitive skills. Adolescent-specific sub-cortical reactivity to emotions and rewards, contrasted with their developing self-control skills, are thought to account for their greater sensitivity to the socio-affective context. The present review examines these findings and their implications for training interventions and education

The higher the grey matter volume the larger the slope increase.

Adolescence is a common time for initiation of alcohol use and development of alcohol use disorders. The present study investigates neuroanatomical predictors for trajectories of future alcohol use based on a novel voxel-wise whole-brain structural equation modeling framework. In 1814 healthy adolescents of the IMAGEN sample, the Alcohol Use Disorder Identification Test (AUDIT) was acquired at three measurement occasions across five years. Based on a two-part latent growth curve model, we conducted whole-brain analyses on structural MRI data at age 14, predicting change in alcohol use score over time. Higher grey-matter volumes in the caudate nucleus and the left cerebellum at age 14 years were predictive of stronger increase in alcohol use score over 5 years. The study is the first to demonstrate the feasibility of running separate voxel-wise structural equation models thereby opening new avenues for data analysis in brain imaging.peerReviewe