Functional Brain Maturation Research Articles

Greater Neighborhood Disadvantage Is Associated with Alterations in Fetal Functional Brain Network Structure

To determine the association between neighborhood disadvantage (ND) and functional brain development of in utero fetuses. We conducted an observational study using Social Vulnerability Index (SVI) scores to assess the impact of ND on a prospectively recruited sample of healthy pregnant women from Washington, DC. Using 79 functional magnetic resonance imaging scans from 68 healthy pregnancies at a mean gestational age of 33.12weeks, we characterized the overall functional brain network structure using a graph metric approach. We used linear mixed effects models to assess the relationship between SVI and gestational age on 5 graph metrics, adjusting for multiple scans. Exposure to greater ND was associated with less well integrated functional brain networks, as observed by longer characteristic path lengths and diminished global efficiency (GE), as well as diminished small world propensity (SWP). Across gestational ages, however, the association between SVI and network integration diminished to a negligible relationship in the third trimester. Conversely, SWP was significant across pregnancy, but the relationship changed such that there was a negative association with SWP earlier in the second trimester that inverted around the transition to the third trimester to a positive association. These data directly connect ND and altered functional brain maturation in fetuses. Our results suggest that, even before birth, proximity to environmental stressors in the wider neighborhood environment are associated with altered brain development.

Relationship between Brain Function and Microstructural Brain Maturation in Preterm Infants

Introduction: Preterm infants are at risk for impairment in brain maturation at term equivalent age (TEA). Diffusion tensor imaging (DTI) is a powerful magnetic resonance imaging (MRI) technique, quantitatively reflecting microstructural brain development of white matter regions with parameters such as fractional anisotropy (FA) and apparent diffusion coefficient (ADC). Amplitude-integrated electroencephalography (aEEG) assesses electrocortical activity and brain function. Methods: Aim of this study was to investigate a possible correlation between functional and microstructural brain maturation using neonatal aEEG and DTI-MRI at TEA. The study was conducted as a retrospective single-center study in 446 infants born below 32 gestational weeks. Spearman rank’s correlation coefficients were calculated between aEEG (total maturation score) and FA/ADC value. To compare aEEG and DTI-MRI to neurodevelopmental outcome at 24 months of corrected age, we performed a multivariate linear regression analysis. Results: Analysis showed an all-time significant correlation between total maturation score and FA/ADC values of the corpus callosum at TEA with the strongest correlation at day 2, day 3, week 3, and week 4. After including perinatal variables in the model, this correlation remained highly significant at day 2 and 3. When comparing the association of aEEG and DTI-MRI to outcome, both the total maturation score at day 2, day 3, and FA/ADC of the splenium of the corpus callosum showed a significant correlation. Conclusion: This study indicates that early monitoring of functional brain maturation may predict later assessment of microstructural brain development of corpus callosum in preterm infants with a relation to neurodevelopmental outcome.

Sex- and age-specific respiratory alterations induced by prenatal exposure to the cannabinoid receptor agonist WIN 55,212-2 in rats.

Cannabis legalization has risen in many countries, and its use during pregnancy has increased. The endocannabinoid system is present in the CNS at early stages of embryonic development, and regulates functional brain maturation including areas responsible for respiratory control, data on the influence of external cannabinoids on the development of the respiratory system and possible consequences during postnatal life are limited. We evaluated the effects of prenatal exposure to synthetic cannabinoid (WIN 55,212-2 [WIN], 0.5 mg·kg-1 ·day-1 ) on the respiratory control system in neonatal (P0, P6-7 and P12-13) and juvenile (P27-28) male and female rats. WIN administration to pregnant rats interfered sex-specifically with breathing regulation of offspring, promoting a greater sensitivity to CO2 at all ages in males (except P6-7) and in juvenile females. An altered hypoxic chemoreflex was observed in P0 (hyperventilation) and P6-7 (hypoventilation) males, which was absent in females. Along with breathing alterations, brainstem analysis showed an increase in the number of catecholaminergic neurons and cannabinoid receptor type 1 (CB1 ) and changes in tissue respiration in the early males. A reduction in pulmonary compliance was observed in juvenile male rats. Preexposure to WIN enhanced spontaneous apnoea and reduced the number of serotoninergic (5-HT) neurons in the raphe magnus nucleus of P0 females. These data demonstrate that excess stimulation of the endocannabinoid system during gestation has prolonged and sex-specific consequences for the respiratory control system.

Resting-state functional connectivity identifies individuals and predicts age in 8-to-26-month-olds

Resting-state functional connectivity (rsFC) measured with fMRI has been used to characterize functional brain maturation in typically and atypically developing children and adults. However, its reliability and utility for predicting development in infants and toddlers is less well understood. Here, we use fMRI data from the Baby Connectome Project study to measure the reliability and uniqueness of rsFC in infants and toddlers and predict age in this sample (8-to-26 months old; n = 170). We observed medium reliability for within-session infant rsFC in our sample, and found that individual infant and toddler’s connectomes were sufficiently distinct for successful functional connectome fingerprinting. Next, we trained and tested support vector regression models to predict age-at-scan with rsFC. Models successfully predicted novel infants’ age within ± 3.6 months error and a prediction R2 = .51. To characterize the anatomy of predictive networks, we grouped connections into 11 infant-specific resting-state functional networks defined in a data-driven manner. We found that connections between regions of the same network—i.e. within-network connections—predicted age significantly better than between-network connections. Looking ahead, these findings can help characterize changes in functional brain organization in infancy and toddlerhood and inform work predicting developmental outcome measures in this age range.

Functional brain maturation and sleep organisation in neonates with congenital heart disease.

Neonates with Congenital Heart Disease (CHD) have structural delays in brain development. To evaluate whether functional brain maturation and sleep-wake physiology is also disturbed, the Functional Brain Age (FBA) and sleep organisation on EEG during the neonatal period is investigated. We compared 15 neonates with CHD who underwent multichannel EEG with healthy term newborns of the same postmenstrual age, including subgroup analysis for d-Transposition of the Great Arteries (d-TGA) (n=8). To estimate FBA, a prediction tool using quantitative EEG features as input, was applied. Second, the EEG was automatically classified into the 4 neonatal sleep stages. Neonates with CHD underwent neurodevelopmental testing using the Bayley Scale of Infant Development-III at 24 months. Preoperatively, the FBA was delayed in CHD infants and more so in d-TGA infants. The FBA was positively correlated with motor scores. Sleep organisation was significantly altered in neonates with CHD. The duration of the sleep cycle and the proportion of Active Sleep Stage 1 was decreased, again more marked in the d-TGA infants. Neonates with d-TGA spent less time in High Voltage Slow Wave Sleep and more in Tracé Alternant compared to healthy terms. Both FBA and sleep organisation normalised postoperatively. The duration of High Voltage Slow Wave Sleep remained positively correlated with motor scores in d-TGA infants. Altered early brain function and sleep is present in neonates with CHD. These results are intruiging, as inefficient neonatal sleep has been linked with adverse long-term outcome. Identifying how these rapid alterations in brain function are mitigated through improvements in cerebral oxygenation, surgery, drugs and nutrition may have relevance for clinical practice and outcome.

Rest Functional Brain Maturation during the First Year of Life.

The first year of life is a key period of brain development, characterized by dramatic structural and functional modifications. Here, we measured rest cerebral blood flow (CBF) modifications throughout babies’ first year of life using arterial spin labeling magnetic resonance imaging sequence in 52 infants, from 3 to 12 months of age. Overall, global rest CBF significantly increased during this age span. In addition, we found marked regional differences in local functional brain maturation. While primary sensorimotor cortices and insula showed early maturation, temporal and prefrontal region presented great rest CBF increase across the first year of life. Moreover, we highlighted a late and remarkably synchronous maturation of the prefrontal and posterior superior temporal cortices. These different patterns of regional cortical rest CBF modifications reflect a timetable of local functional brain maturation and are consistent with baby’s cognitive development within the first year of life.

Deep learning for estimation of functional brain maturation from EEG of premature neonates.

EEG monitoring of early brain function and development in neonatal intensive care units may help to identify infants with high risk of serious neurological impairment and to assess brain maturation for evaluation of neurodevelopmental progress. Automated analysis of EEG data makes continuous evaluation of brain activity fast and accessible. A convolutional neural network (CNN) for regression of EEG maturational age of premature neonates from marginally preprocessed serial EEG recordings is proposed. The CNN was trained and validated using 141 EEG recordings from 43 preterm neonates born below 28 weeks of gestation with normal neurodevelop-mental outcome at 12 months of corrected age. The estimated functional brain maturation between the first and last EEG recording increased in each patient. On average over 96% of repeated measures within an infant had an increasing EEG maturational age according to the post menstrual age at EEG recording time. Our algorithm has potential to be deployed to support neonatologists for accurate estimation of functional brain maturity in premature neonates.

Influence of Intensive Care Unit Enlightenment on Premature Infants on Functional Brain Maturation Assessed by Amplitude-Integrated Electroencephalograph.

Amplitude-integrated electroencephalograph (aEEG) presents a valuable tool for functional brain maturation of preterm infants. However, the effect of enlightenment on functional brain maturation of premature infants has not been investigated. We aimed to do this with aEEG. A total of 32 infants, 30 to 35 gestational weeks, were involved in the study. They were randomly distributed into three groups in which different lighting protocols were applied. In group 1, the infants' incubators were covered for 24 hours. In group 2, the infants' incubators were open for 24 hours. In group 3, the infants' incubators were covered for 12 hours and open for another 12 hours. The infants are evaluated with aEEG recordings done on the 3rd (first measurement) and 10th days (second measurement) along with the Burdjalov scoring. Analysis of aEEG recordings was performed, based on sleep-wake cycles (SWCs), upper and lower margin amplitudes, narrowband and broadband of SWC, and bandwidth of SWC. At first, the narrowband lower amplitudes in group 1 were higher than those of the other groups (p = 0.042), but the difference was not significant in the second measurement (p = 0.110). The Burdjalov scores were higher in group 1 and group 3 on 10th day, though not statistically significant (p = 0.871). When the infants were re-evaluated according to the gestational weeks, the Burdjalov scores of the two groups less than 34 weeks (30-31 and 32-33 weeks) were similar, whereas 34 to 35 weeks were higher when compared with those of the two groups. The difference observed between groups in terms of narrowband lower amplitude in the first measurement may reflect the effect of intrauterine environment rather than enlightenment at the same gestational age because it was made on the third day. However, the fact that all groups have similar results on day 10 suggests that other factors in the intensive care setting may diminish the effect of enlightenment. Burdjalov scores are associated with maturation, and high scores found in the 34- to 35-week group suggest that the 34-week maturation might be a threshold for SWC and development in our group sample.

Increased segregation of functional networks in developing brains

A growing literature conceptualises typical brain development from a network perspective. However, largely due to technical and methodological challenges inherent in paediatric functional neuroimaging, there remains an important gap in our knowledge regarding the typical development of functional brain networks in “preschool” childhood (i.e., children younger than 6 years of age). In this study, we recorded brain oscillatory activity using age-appropriate magnetoencephalography in 24 children, including 14 preschool children aged from 4 to 6 years and 10 school children aged from 7 to 12 years. We compared the topology of the resting-state brain networks in these children, estimated using minimum spanning tree (MST) constructed from phase synchrony between beamformer-reconstructed time-series, with that of 24 adults. Our results show that during childhood the MST topology shifts from a star-like (centralised) toward a more line-like (de-centralised) configuration, indicating the functional brain networks become increasingly segregated. In addition, the increasing global network segregation is frequency-independent and accompanied by decreases in centrality (or connectedness) of cortical regions with age, especially in areas of the default mode network. We propose a heuristic MST model of “network space”, which posits a clear developmental trajectory for the emergence of complex brain networks. Our results not only revealed topological reorganisation of functional networks across multiple temporal and spatial scales in childhood, but also fill a gap in the literature regarding neurophysiological mechanisms of functional brain maturation during the preschool years of childhood.

Age-related differences in task-induced brain activation is not task specific: Multivariate pattern generalization between metacognition, cognition and perception

Adolescence is associated with widespread maturation of brain structures and functional connectivity profiles that shift from local to more distributed and better integrated networks, which are active during a variety of cognitive tasks. Nevertheless, the approach to examine task-induced developmental brain changes is function-specific, leaving the question open whether functional maturation is specific to the particular cognitive demands of the task used, or generalizes across different tasks. In the present study we examine the hypothesis that functional brain maturation is driven by global changes in how the brain handles cognitive demands. Multivariate pattern classification analysis (MVPA) was used to examine whether age discriminative task-induced activation patterns generalize across a wide range of information processing levels. 25 young (13-years old) and 22 old (17-years old) adolescents performed three conceptually different tasks of metacognition, cognition and visual processing. MVPA applied within each task indicated that task-induced brain activation is consistent and reliably different between ages 13 and 17. These age-discriminative activation patterns proved to be common across the different tasks used, despite the differences in cognitive demands and brain structures engaged by each of the three tasks. MVP classifiers trained to detect age-discriminative patterns in brain activation during one task were significantly able to decode age from brain activation maps during execution of other tasks with accuracies between 63 and 75%. The results emphasize that age-specific characteristics of task-induced brain activation have to be understood at the level of brain-wide networks that show maturational changes in their organization and processing efficacy during adolescence.

Abnormal functional activation and maturation of ventromedial prefrontal cortex and cerebellum during temporal discounting in autism spectrum disorder

People with autism spectrum disorder (ASD) have poor decision-making and temporal foresight. This may adversely impact on their everyday life, mental health, and productivity. However, the neural substrates underlying poor choice behavior in people with ASD, or its' neurofunctional development from childhood to adulthood, are unknown. Despite evidence of atypical structural brain development in ASD, investigation of functional brain maturation in people with ASD is lacking. This cross-sectional developmental fMRI study investigated the neural substrates underlying performance on a temporal discounting (TD) task in 38 healthy (11-35 years old) male adolescents and adults with ASD and 40 age, sex, and IQ-matched typically developing healthy controls. Most importantly, we assessed group differences in the neurofunctional maturation of TD across childhood and adulthood. Males with ASD had significantly poorer task performance and significantly lower brain activation in typical regions that mediate TD for delayed choices, in predominantly right hemispheric regions of ventrolateral/dorsolateral prefrontal cortices, ventromedial prefrontal cortex, striatolimbic regions, and cerebellum. Importantly, differential activation in ventromedial frontal cortex and cerebellum was associated with abnormal functional brain maturation; controls, in contrast to people with ASD, showed progressively increasing activation with increasing age in these regions; which furthermore was associated with performance measures and clinical ASD measures (stereotyped/restricted interests). Findings provide first cross-sectional evidence that reduced activation of TD mediating brain regions in people with ASD during TD is associated with abnormal functional brain development in these regions between childhood and adulthood, and this is related to poor task performance and clinical measures of ASD. Hum Brain Mapp 38:5343-5355, 2017. © 2017 Wiley Periodicals, Inc.

Impact of brain injury on functional measures of amplitude-integrated EEG at term equivalent age in premature infants.

To evaluate the association between qualitative and quantitative amplitude-integrated EEG (aEEG) measures at term equivalent age (TEA) and brain injury on magnetic resonance imaging (MRI) in preterm infants. A cohort of premature infants born at <30 weeks of gestation and with moderate-to-severe MRI injury on a TEA MRI scan was identified. A contemporaneous group of gestational age-matched control infants also born at <30 weeks of gestation with none/mild injury on MRI was also recruited. Quantitative aEEG measures, including maximum and minimum amplitudes, bandwidth span and spectral edge frequency (SEF90), were calculated using an offline software package. The aEEG recordings were qualitatively scored using the Burdjalov system. MRI scans, performed on the same day as aEEG, occurred at a mean postmenstrual age of 38.0 (range 37 to 42) weeks and were scored for abnormality in a blinded manner using an established MRI scoring system. Twenty-eight (46.7%) infants had a normal MRI or mild brain abnormality, while 32 (53.3%) infants had moderate-to-severe brain abnormality. Univariate regression analysis demonstrated an association between severity of brain abnormality and quantitative measures of left and right SEF90 and bandwidth span (β=-0.38, -0.40 and 0.30, respectively) and qualitative measures of cyclicity, continuity and total Burdjalov score (β=-0.10, -0.14 and -0.12, respectively). After correcting for confounding variables, the relationship between MRI abnormality score and aEEG measures of SEF90, bandwidth span and Burdjalov score remained significant. Brain abnormalities on MRI at TEA in premature infants are associated with abnormalities on term aEEG measures, suggesting that anatomical brain injury may contribute to delay in functional brain maturation as assessed using aEEG.

An Automated Quiet Sleep Detection Approach in Preterm Infants as a Gateway to Assess Brain Maturation.

Sleep state development in preterm neonates can provide crucial information regarding functional brain maturation and give insight into neurological well being. However, visual labeling of sleep stages from EEG requires expertise and is very time consuming, prompting the need for an automated procedure. We present a robust method for automated detection of preterm sleep from EEG, over a wide postmenstrual age (PMA = gestational age + postnatal age) range, focusing first on Quiet Sleep (QS) as an initial marker for sleep assessment. Our algorithm, CLuster-based Adaptive Sleep Staging (CLASS), detects QS if it remains relatively more discontinuous than non-QS over PMA. CLASS was optimized on a training set of 34 recordings aged 27–42 weeks PMA, and performance then assessed on a distinct test set of 55 recordings of the same age range. Results were compared to visual QS labeling from two independent raters (with inter-rater agreement Kappa = 0. 93), using Sensitivity, Specificity, Detection Factor (DF = proportion of visual QS periods correctly detected by CLASS) and Misclassification Factor (MF = proportion of CLASS-detected QS periods that are misclassified). CLASS performance proved optimal across recordings at 31–38 weeks (median DF = 1.0, median MF 0–0.25, median Sensitivity 0.93–1.0, and median Specificity 0.80–0.91 across this age range), with minimal misclassifications at 35–36 weeks (median MF = 0). To illustrate the potential of CLASS in facilitating clinical research, normal maturational trends over PMA were derived from CLASS-estimated QS periods, visual QS estimates, and nonstate specific periods (containing QS and non-QS) in the EEG recording. CLASS QS trends agreed with those from visual QS, with both showing stronger correlations than nonstate specific trends. This highlights the benefit of automated QS detection for exploring brain maturation.

Urban air pollution affects structural and functional processes of brain maturation in children

Introduction From conception to young adulthood, the human brain undergoes dynamic changes in both its structural and functional organization. This period of life is particularly vulnerable to environmental insults that may interfere with the cascade of neurodevelopmental processes. Exposure to urban air pollution has been associated with poorer cognitive performance, which is thought to be a result of direct interference with brain maturation. We aimed to assess the extent of such potential effects of urban pollution exposure during the prenatal period and the childhood. Methods A group of 263 children, aged 8 to 12 years, underwent magnetic resonance imaging to quantify regional brain volumes and functional connectivity in major neural networks and activation / deactivation dynamics during a sensory task. Prenatal NO2 exposure was estimated using both the mothers address during pregnancy and the data from an urban background monitoring station. A combined measurement of elemental carbon and NO2 in the school environment was used to assess urban air pollution exposure during the childhood period. Results While the children exposed to low prenatal NO2 levels showed an increase in white matter volume (WMV) with advancing age, no WMV progression was observed in the children exposed to higher prenatal levels. Similarly, in the opposite effect to that of age, a higher content of pollutants in the school environment was associated with lower functional integration and segregation in key brain networks relevant to both inner mental processes (the default mode network) and stimulus-driven mental operations. Conclusion Both prenatal and postnatal air pollution exposure appear to adversely affect the structural and functional brain maturation. Further research is needed to determine to what extent these disruptions in the brain maturation process are involved in the poor cognitive performance previously observed in children exposed to air pollution.

Interplay of brain structure and function in neonatal congenital heart disease.

ObjectiveTo evaluate whether structural and microstructural brain abnormalities in neonates with congenital heart disease (CHD) correlate with neuronal network dysfunction measured by analysis of EEG connectivity.MethodsWe studied a prospective cohort of 20 neonates with CHD who underwent continuous EEG monitoring before surgery to assess functional brain maturation and network connectivity, structural magnetic resonance imaging (MRI) to determine the presence of brain injury and structural brain development, and diffusion tensor MRI to assess brain microstructural development.ResultsNeonates with MRI brain injury and delayed structural and microstructural brain development demonstrated significantly stronger high‐frequency (beta and gamma frequency band) connectivity. Furthermore, neonates with delayed microstructural brain development demonstrated significantly weaker low‐frequency (delta, theta, alpha frequency band) connectivity. Neonates with brain injury also displayed delayed functional maturation of EEG background activity, characterized by greater background discontinuity.InterpretationThese data provide new evidence that early structural and microstructural developmental brain abnormalities can have immediate functional consequences that manifest as characteristic alterations of neuronal network connectivity. Such early perturbations of developing neuronal networks, if sustained, may be responsible for the persistent neurocognitive impairment prevalent in adolescent survivors of CHD. These foundational insights into the complex interplay between evolving brain structure and function may have relevance for a wide spectrum of neurological disorders manifesting early developmental brain injury.

EP 139. Cortical maturation during the first years of life as assessed by steady state flicker VEP

Cognitive and motor development are closely coupled to structural and functional brain maturation during the first years of life. During this developmental period brain maturation is dominated by the differentiation and grow of dendritic arbours, forming of synapses and the axons of the cortical neurons get isolated by the myelin shade. Children with learning disabilities often show a delayed functional and structural maturation of their brain early in life. However most of these children are diagnosed only after the clinical symptoms are apparent. In order to diagnose a delayed maturation early quantitative markers are required. Several studies in the past have shown that evoked potentials can be used to assess brain maturation. Recently it was shown (Dubois et al., 2008), that the myelinisation as measured by T2-MR imaging and the latency parameters of flash visual evoked potentials (VEP) closely correlate during early development. Therefore VEPs could function as surrogate marker for myelinisation. However flash VEPs still show a range of variability that makes a conclusive judgment difficult. Most studies so far analyze VEP in the time domain. However the analysis of the VEP in frequency space delivers stable and reproducible results (Pieh et al., 2009). The aim of the study presented her was to establish a method to use steady state flicker VEP in order to assess brain development. We recorded VEP from children aged between 0 days and 12 years. Classical VEP were calculated using time-locked grand averages and the latency of the P100 components were measured. Second, we analyzed the steady state signal of the cortex to the presented visual stimuli. In order to do so the measured signal was transferred to the frequency space using a fast Fourier transformation. We analyzed the power of the first and second harmonic in relation to different visual stimulation frequencies presented. Using this data we could derived a synchronization parameter. We could show that this parameter closely correlates to the maturation of the classical VEP and therefore -according to (Dubois et al., 2008)- also to the maturation of myelinisation in general. To conclude we have derived a technique which delivers an objective and quantitative marker for brain development in young children using VEP.

The case of late preterm birth: sliding forwards the critical window for cognitive outcome risk.

Many survivors of preterm birth experience neurodevelopmental disabilities, such as cerebral palsy, visual and hearing problems. However, even in the absence of major neurological complications, premature babies show significant neuropsychological and behavioural deficits during childhood and beyond. While the clinical tools routinely used to assess neurocognitive development in those infants have been useful in detecting major clinical complications in early infancy, they have not been equally sensitive in identifying subtle cognitive impairments emerging during childhood. These methodological concerns become even more relevant when considering the case of late preterm children (born between 34 and 36 gestational weeks). Although these children have been traditionally considered as having similar risks for developmental problems as neonates born at term, a recent line of research has provided growing evidence that even late preterm children display altered structural and functional brain maturation, with potential life-long implications for neurocognitive functioning. A recent study by Heinonen put forward the hypothesis that environmental factors, in this case educational attainment, could moderate the association between late preterm birth (LPT) and neuropsychological impairments commonly associated with aging. In this paper we bring together clinical literature and recent neuroimaging evidence in order to provide two different but complementary approaches for a better understanding of the "nature-nurture" interplay underlying the lifespan neurocognitive development of preterm babies.

Interplay between impaired brain structure and function in term newborns with congenital heart disease

Background: Term neonates with congenital heart disease (CHD) demonstrate a high incidence of white matter injury (WMI), together with increased average diffusivity and decreased fractional anisotropy (FA) on MR diffusion tensor imaging. EEG background activity is a robust measure of functional brain maturation that becomes less discontinuous, contains more fast activity and shows higher complexity of EEG patterns with increasing age. We sought to determine the association between structural brain abnormalities and functional brain maturation in term neonates with CHD. Methods: Thirteen term newborns with CHD underwent pre-operative MR imaging and continuous EEG recordings (cEEG). The proportion of cEEG with discontinuous vs. continuous background activity was quantified by visual analysis. During continuous epochs, we differentiated between two states: wakefulness/active sleep vs. quiet/transitional sleep, and applied algorithms to measure spectral power and EEG complexity. Results: Three patients had multifocal WMI which was associated with greater EEG background discontinuity (P&lt;0.05). Moreover, lower white matter diffusivity was associated with higher power of fast activity (P&lt;0.05 for wakefulness/active sleep EEG pattern), while higher white matter FA showed a trend toward being associated with increased EEG complexity (P&lt;0.1 for quiet/transitional sleep pattern). Conclusions: In this series of term neonates with CHD, structural and microstructural white matter abnormalities are associated with impaired maturation of brain function.

Developmental sex differences in resting state functional connectivity of amygdala sub-regions

During adolescence, considerable social and biological changes occur that interact with functional brain maturation, some of which are sex-specific. The amygdala is one brain area that has displayed sexual dimorphism, specifically in socio-affective (superficial amygdala [SFA]), stress (centromedial amygdala [CMA]), and learning and memory (basolateral amygdala [BLA]) processing. The amygdala has also been implicated in mood and anxiety disorders which display sex-specific features, most prominently observed during adolescence. Using functional magnetic resonance imaging (fMRI), the present study examined the interaction of age and sex on resting state functional connectivity (RSFC) of amygdala sub-regions, BLA and SFA, in a sample of healthy adolescents between the ages 10 and 16years (n=122, 71 boys). Whole-brain, voxel-wise partial correlation analyses were conducted to determine RSFC of bilateral BLA and SFA seed regions, created using the Eickhoff–Zilles maximum probability maps based on cytoarchitectonic mapping and FMRIB's Integrated Registration and Segmentation Tool (FIRST). Monte Carlo simulation was implemented to correct for multiple comparisons (threshold of 53 contiguous voxels with a z-value≥2.25). Results indicated that with increasing age, there was a corresponding decrease in RSFC between both amygdala sub-regions and parieto-occipital cortices, with a concurrent increase in RSFC with medial prefrontal cortex (mPFC). Specifically, boys and girls demonstrated increased coupling of mPFC and left and right SFA with age, respectively; however, neither sex showed increased connectivity between mPFC and BLA, which could indicate relative immaturity of fronto-limbic networks that is similar across sex. A dissociation in connectivity between BLA- and SFA-parieto-occipital RSFC emerged, in which girls had weaker negative RSFC between SFA and parieto-occipital regions and boys had weaker negative RSFC of BLA and parieto-occipital regions with increased age, both standing in contrast to adult patterns of amygdala sub-regional RSFC. The present findings suggest relative immaturity of amygdala sub-regional RSFC with parieto-occipital cortices during adolescence, with unique patterns in both sexes that may support memory and socio-affective processing in boys and girls, respectively. Understanding the underlying normative functional architecture of brain networks associated with the amygdala during adolescence may better inform future research of the neural features associated with increased risk for internalizing psychopathology.

III. The importance of physical activity and aerobic fitness for cognitive control and memory in children.

In this chapter, we review literature that examines the association among physical activity, aerobic fitness, cognition, and the brain in elementary school children (ages 7-10 years). Specifically, physical activity and higher levels of aerobic fitness in children have been found to benefit brain structure, brain function, cognition, and school achievement. For example, higher fit children have larger brain volumes in the basal ganglia and hippocampus, which relate to superior performance on tasks of cognitive control and memory, respectively, when compared to their lower fit peers. Higher fit children also show superior brain function during tasks of cognitive control, better scores on tests of academic achievement, and higher performance on a real-world street crossing task, compared to lower fit and less active children. The cross-sectional findings are strengthened by a few randomized, controlled trials, which demonstrate that children randomly assigned to a physical activity intervention group show greater brain and cognitive benefits compared to a control group. Because these findings suggest that the developing brain is plastic and sensitive to lifestyle factors, we also discuss typical structural and functional brain maturation in children to provide context in which to interpret the effects of physical activity and aerobic fitness on the developing brain. This research is important because children are becoming increasingly sedentary, physically inactive, and unfit. An important goal of this review is to emphasize the importance of physical activity and aerobic fitness for the cognitive and brain health of today's youth.