Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data (http://www.brainchart.io/). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Exposure to maternal anxiety predicts offspring brain development. However, because children's brains are commonly assessed years after birth, the timing of such maternal influences in humans is unclear. This study aimed to examine the consequences of antenatal and postnatal exposure to maternal anxiety upon early infant development of the hippocampus, a key structure for stress regulation. A total of 175 neonates underwent magnetic resonance imaging (MRI) at birth and among them 35 had repeated scans at 6 months of age. Maternal anxiety was assessed using the State-Trait Anxiety Inventory (STAI) at week 26 of pregnancy and 3 months after delivery. Regression analyses showed that antenatal maternal anxiety did not influence bilateral hippocampal volume at birth. However, children of mothers reporting increased anxiety during pregnancy showed slower growth of both the left and right hippocampus over the first 6 months of life. This effect of antenatal maternal anxiety upon right hippocampal growth became statistically stronger when controlling for postnatal maternal anxiety. Furthermore, a strong positive association between postnatal maternal anxiety and right hippocampal growth was detected, whereas a strong negative association between postnatal maternal anxiety and the left hippocampal volume at 6 months of life was found. Hence, the postnatal growth of bilateral hippocampi shows distinct responses to postnatal maternal anxiety. The size of the left hippocampus during early development is likely to reflect the influence of the exposure to perinatal maternal anxiety, whereas right hippocampal growth is constrained by antenatal maternal anxiety, but enhanced in response to increased postnatal maternal anxiety.

Maternal depressive symptoms influence neurodevelopment in the offspring. Such effects may appear to be gender-dependent. The present study examined contributions of prenatal and postnatal maternal depressive symptoms to the volume and microstructure of the amygdala in 4.5-year-old boys and girls. Prenatal maternal depressive symptoms were measured using the Edinburgh Postnatal Depression Scale (EPDS) at 26 weeks of gestation. Postnatal maternal depression was assessed at 3 months using the EPDS and at 1, 2, 3 and 4.5 years using the Beck's Depression Inventory-II. Structural magnetic resonance imaging and diffusion tensor imaging were performed with 4.5-year-old children to extract the volume and fractional anisotropy (FA) values of the amygdala. Our results showed that greater prenatal maternal depressive symptoms were associated with larger right amygdala volume in girls, but not in boys. Increased postnatal maternal depressive symptoms were associated with higher right amygdala FA in the overall sample and girls, but not in boys. These results support the role of variation in right amygdala structure in transmission of maternal depression to the offspring, particularly to girls. The differential effects of prenatal and postnatal maternal depressive symptoms on the volume and FA of the right amygdala suggest the importance of the timing of exposure to maternal depressive symptoms in brain development of girls. This further underscores the need for intervention targeting both prenatal and postnatal maternal depression to girls in preventing adverse child outcomes.

Right frontal electroencephalogram (EEG) asymmetry associates with negative affect and depressed mood, which, among children, are predicted by maternal depression and poor parenting. This study examined associations of maternal depression and maternal sensitivity with infant frontal EEG asymmetry based on 111 mother-6-month-infant dyads. There were no significant effects of postnatal maternal depression or maternal sensitivity, or their interaction, on infant EEG frontal asymmetry. However, in a subsample for which the infant spent at least 50% of his/her day time hours with his/her mother, both lower maternal sensitivity and higher maternal depression predicted greater relative right frontal EEG asymmetry. Our study further showed that greater relative right frontal EEG asymmetry of 6-month-old infants predicted their greater negative emotionality at 12 months of age. Our study suggested that among infants with sufficient postnatal maternal exposure, both maternal sensitivity and mental health are important influences on early brain development.

Over the past 25 years, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, there are no reference standards against which to anchor measures of individual differences in brain morphology, in contrast to growth charts for traits such as height and weight. Here, we built an interactive online resource (www.brainchart.io) to quantify individual differences in brain structure from any current or future magnetic resonance imaging (MRI) study, against models of expected age-related trends. With the goal of basing these on the largest and most inclusive dataset, we aggregated MRI data spanning 115 days post-conception through 100 postnatal years, totaling 122,123 scans from 100,071 individuals in over 100 studies across 6 continents. When quantified as centile scores relative to the reference models, individual differences show high validity with non-MRI brain growth estimates and high stability across longitudinal assessment. Centile scores helped identify previously unreported brain developmental milestones and demonstrated increased genetic heritability compared to non-centiled MRI phenotypes. Crucially for the study of brain disorders, centile scores provide a standardised and interpretable measure of deviation that reveals new patterns of neuroanatomical differences across neurological and psychiatric disorders emerging during development and ageing. In sum, brain charts for the human lifespan are an essential first step towards robust, standardised quantification of individual variation and for characterizing deviation from age-related trends. Our global collaborative study provides such an anchorpoint for basic neuroimaging research and will facilitate implementation of research-based standards in clinical studies.

In this study, the absorption process of the aqueous DEEA solution for CO2 capture in polytetrafluoroethylene hollow-fiber membrane contactor was investigated by both experiment and simulation. Based on the finite element analysis method, a two-dimensional steady-state mathematical model was established using COMSOL Multiphysics simulation software to calculate the CO2 mass transfer flux (JCO2) of DEEA in the hollow fiber membrane contactor under non-wetting and partial wetting conditions and the distribution of CO2 concentration under corresponding conditions. The results show that the predicted JCO2 under 15% membrane wetting conditions is in good agreement with the experimental value, and the mass transfer performance is severely reduced under wetting conditions. In addition, a dimensionless equation was developed to predict the liquid phase, gas phase and membrane phase mass transfer coefficient and JCO2. The calculated JCO2 values are in good agreement with the experimental values with the average relative deviation (AARD) of 9.4%.