Application of resting state functional connectivity magnetic resonance imaging (fcMRI) to the study of prematurely born infants enables assessment of the earliest forms of cerebral connectivity and characterization of its early development in the human brain. We obtained 90 longitudinal fcMRI data sets from a cohort of preterm infants aged from 26 weeks postmenstrual age (PMA) through term equivalent age at PMA-specific time points. Utilizing seed-based correlation analysis, we identified resting state networks involving varied cortical regions, the thalamus, and cerebellum. Identified networks demonstrated a regionally variable age-specific pattern of development, with more mature forms consisting of localized interhemispheric connections between homotopic counterparts. Anatomical distance was found to play a critical role in the rate of connection development. Prominent differences were noted between networks identified in term control versus premature infants at term equivalent, including in the thalamocortical connections critical for neurodevelopment. Putative precursors of the default mode network were detected in term control infants but were not identified in preterm infants, including those at term equivalent. Identified patterns of network maturation reflect the intricate relationship of structural and functional processes present throughout this important developmental period and are consistent with prior investigations of neurodevelopment in this population.

Resting state fMRI measures spontaneous, low frequency fluctuations in the BOLD signal to investigate the functional architecture of the brain. Application of this technique has allowed for the identification of various RSNs, or spatially distinct areas of the brain that demonstrate synchronous BOLD fluctuations at rest. Various methods exist for analyzing resting state data, including seed based approaches, independent component analysis, graph methods, clustering algorithms, neural networks, and pattern classifiers. Clinical applications of resting state fMRI are at an early stage of development. However, its use in presurgical planning for brain tumor and epilepsy patients demonstrates early promise, and the technique may also have a future role in providing diagnostic and prognostic information for neurological and psychiatric diseases.

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.

Objective Although many perinatal factors have been linked to adverse neurodevelopmental outcomes in very premature infants, much of the variation in outcome remains unexplained. The impact on brain development of one potential factor, exposure to stressors in the Neonatal Intensive Care Unit, has not yet been studied in a systematic, prospective manner. Methods In this prospective cohort study of infants born at <30 weeks gestation, nurses were trained in recording procedures and cares. These recordings were used to derive Neonatal Infant Stressor Scale scores, which were employed to measure exposure to stressors. Magnetic resonance imaging (brain metrics, diffusion, and functional magnetic resonance imaging) and neurobehavioral examinations at term equivalent postmenstrual age were used to assess cerebral structure and function. Simple and partial correlations corrected for confounders including immaturity and severity of illness were used to explore these relationships. Results Exposure to stressors was highly variable, both between infants and throughout a single infant’s hospital course. Exposure to a greater number of stressors was associated with decreased frontal and parietal brain width, altered diffusion measures and functional connectivity in the temporal lobes, and abnormalities in motor behavior on neurobehavioral examination. Interpretation Exposure to stressors in the Neonatal Intensive Care Unit is associated with regional alterations in brain structure and function. Further research into interventions that may decrease or mitigate exposure to stressors in the Neonatal Intensive Care Unit is warranted.

Objective To evaluate associations between neonatal intensive care unit (NICU) room type (open ward and private room) and medical outcomes; neurobehavior, electrophysiology and brain structure at hospital discharge; and developmental outcomes at two years of age. Study design In this prospective longitudinal cohort study, we enrolled 136 preterm infants born <30 weeks gestation from an urban, 75-bed level III NICU from 2007-2010. Upon admission, each participant was assigned to a bedspace in an open ward or private room within the same hospital, based on space and staffing availability, where they remained for the duration of hospitalization. The primary outcome was developmental performance at two years of age (n=86 infants returned for testing, which was 83% of survivors) measured using the Bayley Scales of Infant and Toddler Development, 3rd Edition. Secondary outcomes were 1) medical factors throughout the hospitalization, 2) neurobehavior, and 3) cerebral injury and maturation (determined by magnetic resonance imaging and electroencephalography). Results At term equivalent age, infants in private rooms were characterized by a diminution of normal hemispheric asymmetry and a trend toward having lower amplitude integrated electroencephalography cerebral maturation scores [p= 0.02; β=−0.52 (CI −0.95, −0.10)]. At age two years, infants from private rooms had lower language scores [p= 0.006; β=−8.3 (CI −14.2, −2.4)] and a trend toward lower motor scores [p= 0.02; β=−6.3 (CI −11.7, −0.99)], which persisted after adjustment for potential confounders. Conclusion These findings raise concerns that highlight the need for further research into the potential adverse effects of different amounts of sensory exposure in the NICU environment.

Premature birth is associated with high rates of motor and cognitive disability. Investigations have described resting-state functional magnetic resonance imaging (rs-fMRI) correlates of prematurity in older children, but comparable data in the neonatal period remain scarce. We studied 25 term-born control infants within the first week of life and 25 very preterm infants (born at gestational ages ranging from 23 to 29 weeks) without evident structural injury at term equivalent postmenstrual age. Conventional resting-state network (RSN) mapping revealed only modest differences between the term and prematurely born infants, in accordance with previous work. However, clear group differences were observed in quantitative analyses based on correlation and covariance matrices representing the functional MRI time series extracted from 31 regions of interest in 7 RSNs. In addition, the maximum likelihood dimensionality estimates of the group-averaged covariance matrices in the term and preterm infants were 5 and 3, respectively, indicating that prematurity leads to a reduction in the complexity of rs-fMRI covariance structure. These findings highlight the importance of quantitative analyses of rs-fMRI data and suggest a more sensitive method for delineating the effects of preterm birth in infants without evident structural injury.

Advanced neuroimaging techniques have been increasingly applied to the study of preterm and term infants in an effort to further define the functional cerebral architecture of the developing brain. Despite improved understanding of the complex relationship between structure and function obtained through these investigations, significant questions remain regarding the nature, location, and timing of the maturational changes which occur during early development. Functional connectivity magnetic resonance imaging (fcMRI) utilizes spontaneous, low frequency (< 0.1 Hz), coherent fluctuations in blood oxygen level dependent (BOLD) signal to identify networks of functional cerebral connections. Due to the intrinsic characteristics of its image acquisition and analysis, fcMRI offers a novel neuroimaging approach well suited to investigation of infants. Recently, this methodology has been successfully applied to examine neonatal populations, defining normative patterns of large-scale neural network development in the maturing brain. The resting-state networks (RSNs) identified in these studies reflect the evolving cerebral structural architecture, presumably driven by varied genetic and environmental influences. Principal features of these investigations and their role in characterization of the tenets of neural network development during this critical developmental period are highlighted in this review. Despite these successes, optimal methods for fcMRI data acquisition and analysis for this population have not yet been defined. Further, appropriate schemes for interpretation and translation of fcMRI results remain unknown, a matter of increasing importance as functional neuroimaging findings are progressively applied in the clinical arena. Notwithstanding these concerns, fcMRI provides insight into the earliest forms of cerebral connectivity and therefore holds great promise for future neurodevelopmental investigations.

Objective Alterations in the normal developmental trajectory of amygdala resting state-functional connectivity (rs-FC) have been associated with atypical emotional processes and psychopathology. Little is known, however, regarding amygdala rs-FC at birth or its relevance to outcomes. This study examined amygdala rs-FC in healthy, full-term (FT) infants and in very preterm (VPT) infants and tested whether variability of neonatal amygdala rs-FC predicted internalizing symptoms at age 2 years. Method Resting state-fMRI data were obtained shortly after birth from 65 FT infants (gestational age [GA] ≥36 weeks) and 57 VPT infants (GA <30 weeks) at term-equivalent. Voxel-wise correlation analyses were performed using individual-specific bilateral amygdala regions of interest. Total internalizing symptoms and the behavioral inhibition, depression/withdrawal, general anxiety, and separation distress subdomains were assessed in a subset (n=44) at age 2 years using the Infant Toddler Social Emotional Assessment. Results In FT and VPT infants, the amygdala demonstrated positive correlations with subcortical and limbic structures and negative correlations with cortical regions, though magnitudes were decreased in VPT infants. Neonatal amygdala rs-FC predicted internalizing symptoms at age 2 with regional specificity consistent with known pathophysiology in older populations: connectivity with the anterior insula related to depressive symptoms, with the dorsal anterior cingulate related to generalized anxiety, and with the medial prefrontal cortex related to behavioral inhibition. Conclusion Amygdala rs-FC is well-established in neonates. Variability in regional neonatal amygdala rs-FC predicted internalizing symptoms at 2 years, suggesting that risk for internalizing symptoms may be established in neonatal amygdala functional connectivity patterns.