Microstate Analysis Reflects Maturation of the Preterm Brain

Preterm neonates are at risk of long-term neurodevelopmental impairments due to disruption of natural brain development. Electroencephalography (EEG) analysis can provide insights into brain development of preterm neonates. This study aims to explore the use of microstate (MS) analysis to evaluate global brain dynamics changes during maturation in preterm neonates with normal neurodevelopmental outcome.The dataset included 135 EEGs obtained from 48 neonates at varying postmenstrual ages (26.4 to 47.7 weeks), divided into four age groups. For each recording we extracted a 5-minute epoch during quiet sleep (QS) and during non-quiet sleep (NQS), resulting in eight groups (4 age group x 2 sleep states). We compared MS maps and corresponding (map-specific) MS metrics across groups using group-level maps. Additionally, we investigated individual map metrics.Four group-level MS maps accounted for approximately 70% of the global variance and showed non-random syntax. MS topographies and transitions changed significantly when neonates reached 37 weeks. For both sleep states and all MS maps, MS duration decreased and occurrence increased with age. The same relationships were found using individual maps, showing strong correlations (Pearson coefficients up to 0.74) between individual map metrics and post-menstrual age. Moreover, the Hurst exponent of the individual MS sequence decreased with age.The observed changes in MS metrics with age might reflect the development of the preterm brain, which is characterized by formation of neural networks. Therefore, MS analysis is a promising tool for monitoring preterm neonatal brain maturation, while our study can serve as a valuable reference for investigating EEGs of neonates with abnormal neurodevelopmental outcomes.

Lateralization of the cerebral network of inhibition in children before and after cognitive training

Inhibitory control (IC) plays a critical role in cognitive and socio-emotional development. IC relies on a lateralized cortico-subcortical brain network including the inferior frontal cortex, anterior parts of insula, anterior cingulate cortex, caudate nucleus and putamen. Brain asymmetries play a critical role for IC efficiency. In parallel to age-related changes, IC can be improved following training. The aim of this study was to (1) assess the lateralization of IC network in children (N = 60, 9-10 y.o.) and (2) examine possible changes in neural asymmetry of this network from anatomical (structural MRI) and functional (resting-state fMRI) levels after 5-week computerized IC vs. active control (AC) training. We observed that IC training, but not AC training, led to a leftward lateralization of the putamen anatomy, similarly to what is observed in adults, supporting that training could accelerate the maturation of this structure.

Microstructural Brain Development and Neurodevelopmental Outcome of Very Preterm Infants of Mothers with Gestational Diabetes Mellitus

INTRODUCTION

There are data linking gestational diabetes mellitus (GDM) with adverse neurodevelopmental outcome in the offspring. We investigated the effect of GDM on microstructural brain development and neurodevelopmental outcome of very preterm infants.

MATERIALS AND METHODS

Preterm infants <32 gestational weeks of mothers with GDM obtained cerebral magnetic resonance imaging (MRI) including diffusion-tensor imaging at term-equivalent age. For every infant, two gestational age-, sex-, and MRI scanner type-matched controls were included. Brain injury was assessed and fractional anisotropy (FA) and apparent diffusion coefficient (ADC) measured in 14 defined cerebral regions. Neurodevelopmental outcome was quantified at the corrected age of 24 months using the Bayley Scales of Infant Development.

RESULTS

We included 47 infants of mothers with GDM and 94 controls. There were no differences in neonatal morbidity between the groups, nor in any type of brain injury. The GDM group showed significantly higher FA values in the centrum semiovale, the posterior limb of the internal capsule and the pons bilaterally, in the corpus callosum and the right occipital white matter, as well as lower ADC values in the right centrum semiovale, the right occipital white matter and the corpus callosum. Neurodevelopmental outcome did not differ between the groups.

CONCLUSION

We found no impairment of brain development in GDM-exposed infants compared to matched controls, but differences in white matter microstructure in specific regions indicating an enhanced maturation. However, neurodevelopmental outcome was equal in both groups. Further studies are needed to better understand brain maturation in preterm infants exposed to GDM.

[A preliminary study on a new method for evaluating brain maturation in preterm infants]

OBJECTIVES

To establish a new method for evaluating the brain maturation of preterm infants based on the features of electroencephalographic activity.

METHODS

A prospective study was conducted on the video electroencephalography (vEEG) and amplitude-integrated electroencephalography (aEEG) recordings within 7 days after birth of preterm infants who had a postmenstrual age (PMA) of 25-36 weeks and met the inclusion criteria. The background activity of aEEG+conventional electroencephalography (cEEG) was scored according to the features of brain maturation as a new evaluation system and was compared with the aEEG evaluation system. The correlations of the evaluation results of the two methods with gestational age (GA), PMA, and head circumference were evaluated. The intervals of the total scores of aEEG+cEEG and aEEG were calculated for preterm infants with different PMAs and were compared between groups. The consistency of the new scoring system was evaluated among different raters.

RESULTS

A total of 52 preterm infants were included. The total scores of aEEG+cEEG and aEEG were positively correlated with GA, PMA, and head circumference (P<0.05), and the correlation coefficient between the total scores of the two systems and PMA and GA was >0.9. The normal score intervals for aEEG+cEEG and aEEG scoring systems were determined in preterm infants with different PMAs as follows: infants with a PMA of less than 28 weeks had scores of 13.0 (11.0, 14.0) points for aEEG+cEEG and 6.0 (4.0, 7.0) points for aEEG; infants with a PMA between 28 and 29+6 weeks had scores of 16.0 (14.5, 17.0) points for aEEG+cEEG and 8.0 (6.0, 8.0) points for aEEG; infants with a PMA between 30 and 31+6 weeks had scores of 18.0 (17.0, 21.0) points for aEEG+cEEG and 9.0 (8.0, 10.0) points for aEEG; infants with between 32 and 33+6 weeks had scores of 22.0 (20.0, 24.5) points for aEEG+cEEG and 10.0 (10.0, 10.8) points for aEEG; infants with a PMA between 34 and 36 weeks had scores of 26.0 (24.5, 27.5) points for aEEG+cEEG and 11.0 (10.0, 12.0) points for aEEG. There were significant differences in the total scores of aEEG+cEEG and aEEG among the different PMA groups (P<0.05). There was a high consistency between different raters when using the scoring system to evaluate the brain maturation of preterm infants (κ=0.86).

CONCLUSIONS

The aEEG+cEEG scoring system established in this study can quantitatively reflect the brain maturation of preterm infants, with a good discriminatory ability between preterm infants with different PMAs and high consistency between different raters.

Puberty differentially predicts brain maturation in male and female youth: A longitudinal ABCD Study

Research has demonstrated associations between pubertal development and brain maturation. However, existing studies have been limited by small samples, cross-sectional designs, and inconclusive findings regarding directionality of effects and sex differences. We examined the longitudinal temporal coupling of puberty status assessed using the Pubertal Development Scale (PDS) and magnetic resonance imaging (MRI)-based grey and white matter brain structure. Our sample consisted of 8896 children and adolescents at baseline (mean age = 9.9) and 6099 at follow-up (mean age = 11.9) from the Adolescent Brain and Cognitive Development (ABCD) Study cohort. Applying multigroup Bivariate Latent Change Score (BLCS) models, we found that baseline PDS predicted the rate of change in cortical thickness among females and rate of change in cortical surface area for both males and females. We also found a correlation between baseline PDS and surface area and co-occurring changes over time in males. Diffusion tensor imaging (DTI) analyses revealed correlated change between PDS and fractional anisotropy (FA) for both males and females, but no significant associations for mean diffusivity (MD). Our results suggest that pubertal status predicts cortical maturation, and that the strength of the associations differ between sex. Further research spanning the entire duration of puberty is needed to understand the extent and contribution of pubertal development on the youth brain.

Recreational Marijuana Use, Adolescent Cognitive Development, and Schizophrenia Susceptibility

Background

We investigated how low marijuana (MJ) use levels, the typical use pattern in most adolescent users, affect cognitive maturation and schizophrenia risk.

Methods

In two complementary adolescent samples where the majority reported minimal MJ use, we compared cognitive performances before and after MJ use initiation. The Iowa sample (40 first-degree relatives and 54 second-degree relatives of patients with schizophrenia and 117 control subjects with no schizophrenia family history) underwent a battery of standardized neuropsychological tests at 0, 18, and 36 months. Based on self-administered Timeline Followback interviews, 26.5% of adolescents had emergent MJ use (eMJ) during follow-up. The second sample (n = 3463), derived from a birth cohort, received substance use and sustained attention assessments between ages 10 and 15 years. Mixed linear models and regression analyses tested the effects of eMJ on longitudinal changes in cognitive performance.

Results

In the Iowa sample, longitudinal changes in 5 of 8 cognitive domains were significantly associated with eMJ. On sustained attention, visuospatial working memory, and executive sequencing, adolescents with eMJ showed less age-expected improved performance. In addition, first-degree relatives with eMJ were less improved on processing speed and executive reasoning than first-degree relatives without eMJ. In the birth cohort, greater intraindividual variability in reaction times (indicative of poorer sustained attention) was significantly associated with more frequent MJ use and with recreational use levels.

Conclusions

Nonheavy MJ use disrupts normal adolescent maturation and compounds aberrant adolescent maturation associated with familial schizophrenia risk. These findings underscore the importance of reducing adolescent MJ access in the context of increased availability to high-potency MJ.

Biochemical mechanisms in pathogenesis of infantile epileptic spasm syndrome

The molecular mechanisms leading to infantile epileptic spasm syndrome (IESS) remain obscure. The only common factor seems to be that the spasms are restricted to a limited period of infancy, during a certain maturational state. Here the current literature regarding the biochemical mechanisms of brain maturation in IESS is reviewed, and various hypotheses of the pathophysiology are put together. They include: (1) imbalance of inhibitory (NGF, IGF-1, ACTH, GABA) and excitatory factors (glutamate, nitrites) which distinguishes the different etiological subgroups, (2) abnormality of the hypothalamic pituitary adrenal (HPA) axis linking insults and early life stress, (3) inflammation (4) yet poorly known genetic and epigenetic factors, and (5) glucocorticoid and vigabatrin action on brain development, pinpointing at molecular targets of the pathophysiology from another angle. An altered maturational process may explain why so many, seemingly independent etiological factors lead to the same clinical syndrome and frequently to developmental delay. Understanding these factors can provide ideas for novel therapies.

Atypically high influence of subcortical activity on primary sensory regions in autism

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The age-dependent decrease of subcortico-cortical connectivity is attenuated in ASD.

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Primary sensory regions remain less segregated from subcortical activity in ASD.

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This could underlie an excessive amount of sensory input relayed to the cortex.

Background

Hypersensitivity, stereotyped behaviors and attentional problems in autism spectrum disorder (ASD) are compatible with inefficient filtering of undesired or irrelevant sensory information at early stages of neural processing. This could stem from the persistent overconnectivity between primary sensory regions and deep brain nuclei in both children and adults with ASD – as reported by several previous studies – which could reflect a decreased or arrested maturation of brain connectivity. However, it has not yet been investigated whether this overconnectivity can be modelled as an excessive directional influence of subcortical brain activity on primary sensory cortical regions in ASD, with respect to age-matched typically developing (TD) individuals.

Methods

To this aim, we used dynamic causal modelling to estimate (1) the directional influence of subcortical activity on cortical processing and (2) the functional segregation of primary sensory cortical regions from subcortical activity in 166 participants with ASD and 193 TD participants from the Autism Brain Imaging Data Exchange (ABIDE). We then specifically tested the hypothesis that the age-related changes of these indicators of brain connectivity would differ between the two groups.

Results

We found that in TD participants age was significantly associated with decreased influence of subcortical activity on cortical processing, paralleled by an increased functional segregation of cortical sensory processing from subcortical activity. Instead these effects were highly reduced and mostly absent in ASD participants, suggesting a delayed or arrested development of the segregation between subcortical and cortical sensory processing in ASD.

Conclusion

This atypical configuration of subcortico-cortical connectivity in ASD can result in an excessive amount of unprocessed sensory input relayed to the cortex, which is likely to impact cognitive functioning in everyday situations where it is beneficial to limit the influence of basic sensory information on cognitive processing, such as activities requiring focused attention or social interactions.

Understanding Sensitive Period Effects in Musical Training

Adult ability in complex cognitive domains, including music, is commonly thought of as the product of gene-environment interactions, where genetic predispositions influence and are modulated by experience, resulting in the final phenotypic expression. Recently, however, the important contribution of maturation to gene-environment interactions has become better understood. Thus, the timing of exposure to specific experience, such as music training, has been shown to produce long-term impacts on adult behaviour and the brain. Work from our lab and others shows that musical training before the ages of 7-9 enhances performance on musical tasks and modifies brain structure and function, sometimes in unexpected ways. The goal of this paper is to present current evidence for sensitive period effects for musical training in the context of what is known about brain maturation and to present a framework that integrates genetic, environmental and maturational influences on the development of musical skill. We believe that this framework can also be applied more broadly to understanding how predispositions, brain development and experience interact.

A systematic review and meta-analysis of the cyclic alternating pattern across the lifespan

BACKGROUND

Cyclic alternating pattern (CAP) is the electroencephalogram (EEG) pattern described as a marker of sleep instability and assessed by NREM transient episodes in sleep EEG. It has been associated with brain maturation. The aim of this review was to evaluate the normative data of CAP parameters according to the aging process in healthy subjects through a systematic review and meta-analysis.

METHODS

Two authors independently searched databases using PRISMA guidelines. Discrepancies were reconciled by a third reviewer. Subgroup analysis and tests for heterogeneity were conducted.

RESULTS

Of 286 studies, 10 submitted a total of 168 healthy individuals to CAP analysis. Scoring of CAP can begin at 3 months of life, when K-complexes, delta bursts, or spindles can be recognized. Rate of CAP increased with age, mainly during the first 2 years of life, then decreased in adolescence, and increased in the elderly. The A1 CAP subtype and CAP rate were high in school-aged children during slow-wave sleep (SWS). A1 CAP subtypes were significantly more numerous in adolescents compared with other groups, while the elderly showed the highest amounts of A2 and A3 CAP subtypes. Our meta-analysis registered the lowest CAP rate in infants younger than 2 years old and the highest in the elderly.

CONCLUSIONS

This review summarized the normative data of CAP in NREM sleep during the aging process. The CAP rate increased with age and sleep depth, especially during SWS. Parameters of CAP may reflect gender hormonal effects and neuroplasticity. More reports on CAP subtypes are needed for their reference values establishment.

In vivo biomarkers of structural and functional brain development and aging in humans

Brain aging is a major determinant of aging. Along with the aging population, prevalence of neurodegenerative diseases is increasing, therewith placing economic and social burden on individuals and society. Individual rates of brain aging are shaped by genetics, epigenetics, and prenatal environmental. Biomarkers of biological brain aging are needed to predict individual trajectories of aging and the risk for age-associated neurological impairments for developing early preventive and interventional measures. We review current advances of in vivo biomarkers predicting individual brain age. Telomere length and epigenetic clock, two important biomarkers that are closely related to the mechanistic aging process, have only poor deterministic and predictive accuracy regarding individual brain aging due to their high intra- and interindividual variability. Phenotype-related biomarkers of global cognitive function and brain structure provide a much closer correlation to age at the individual level. During fetal and perinatal life, autonomic activity is a unique functional marker of brain development. The cognitive and structural biomarkers also boast high diagnostic specificity for determining individual risks for neurodegenerative diseases.

Magnetoencephalographic signatures of conscious processing before birth

The concept of fetal consciousness is a widely discussed topic. In this study, we applied a hierarchical rule learning paradigm to investigate the possibility of fetal conscious processing during the last trimester of pregnancy. We used fetal magnetoencephalography, to assess fetal brain activity in 56 healthy fetuses between gestational week 25 and 40, during an auditory oddball paradigm containing first- and second-order regularities. The comparison of fetal brain responses towards standard and deviant tones revealed that the investigated fetuses show signs of hierarchical rule learning, and thus the formation of a memory trace for the second-order regularity. This ability develops over the course of the last trimester of gestation, in accordance with processes in physiological brain development and was only reliably present in fetuses older than week 35 of gestation. Analysis of fetal autonomic nervous system activity replicates findings in newborns, showing importance of activity state for cognitive processes. On the whole, our results support the assumption that fetuses in the last weeks of gestation are capable of consciously processing stimuli that reach them from outside the womb.

Effects of nutrition therapy on growth, inflammation and metabolism in immature infants: a study protocol of a double-blind randomized controlled trial (ImNuT)

Background

Current nutritional management of infants born very preterm results in significant deficiency of the essential fatty acids (FAs) arachidonic acid (ARA) and docosahexaenoic acid (DHA). The impact of this deficit on brain maturation and inflammation mediated neonatal morbidities are unknown. The aim of this study is to determine whether early supply of ARA and DHA improves brain maturation and neonatal outcomes in infants born before 29 weeks of gestation.

Methods

Infants born at Oslo University Hospital are eligible to participate in this double-blind randomized controlled trial. Study participants are randomized to receive an enteral FA supplement of either 0.4 ml/kg MCT-oil™ (medium chain triglycerides) or 0.4 ml/kg Formulaid™ (100 mg/kg of ARA and 50 mg/kg of DHA). The FA supplement is given from the second day of life to 36 weeks’ postmenstrual age (PMA). The primary outcome is brain maturation assessed by Magnetic Resonance Imaging (MRI) at term equivalent age. Secondary outcomes include quality of growth, incidence of neonatal morbidities, cardiovascular health and neuro-development. Target sample size is 120 infants (60 per group), this will provide 80% power to detect a 0.04 difference in mean diffusivity (MD, mm²/sec) in major white matter tracts on MRI.

Discussion

Supplementation of ARA and DHA has the potential to improve brain maturation and reduce inflammation related diseases. This study is expected to provide valuable information for future nutritional guidelines for preterm infants.

Trial registration

Clinicaltrials.gov ID: NCT03555019. Registered 4 October 2018- Retrospectively registered.

Emergence and organization of adult brain function throughout child development

Adult cognitive neuroscience has guided the study of human brain development by identifying regions associated with cognitive functions at maturity. The activity, connectivity, and structure of a region can be compared across ages to characterize the developmental trajectory of the corresponding function. However, developmental differences may reflect both the maturation of the function and also its organization across the brain. That is, a function may be present in children but supported by different brain regions, leading its maturity to be underestimated. Here we test the presence, maturity, and localization of adult functions in children using shared response modeling, a machine learning approach for functional alignment. After learning a lower-dimensional feature space from fMRI activity as adults watched a movie, we translated these shared features into the anatomical brain space of children 3–12 years old. To evaluate functional maturity, we correlated this reconstructed activity with children’s actual fMRI activity as they watched the same movie. We found reliable correlations throughout cortex, even in the youngest children. The strength of the correlation in the precuneus, inferior frontal gyrus, and lateral occipital cortex predicted chronological age. These age-related changes were driven by three types of developmental trajectories: emergence from absence to presence, consistency in anatomical expression, and reorganization from one anatomical region to another. We also found evidence that the processing of pain-related events in the movie underwent reorganization across childhood. This data-driven, naturalistic approach provides a new perspective on the development of functional neuroanatomy throughout childhood.

Postoperative Improvement of Brain Maturation in Infants With Congenital Heart Disease

Children with severe congenital heart disease are at risk for neurodevelopmental impairments. We examined brain maturation in infants undergoing neonatal cardiopulmonary bypass surgery or hybrid procedure for hypoplastic left heart syndrome compared to controls. This is a prospective cohort study on term-born infants with congenital heart disease with cerebral MRI pre- and postoperatively. Healthy infants served as controls. Brain maturation was measured using a semiquantitative scoring system. The progress of brain maturation from the preoperative to postoperative MRI within patients was compared. Neurodevelopment was assessed at 1 year with the Bayley Scales of Infant and Toddler Development III. A total of 92 patients with congenital heart disease and 46 controls were studied. Median total maturation score in patients was 12 (interquartile range 10.6-13.0) preoperatively and 14 (12.0-15.0) postoperatively, in controls it was 14 (13.0-15.0). Median time interval between scans was 19 days (interquartile range 14-26). After correction for postmenstrual age at MRI, the pre- and postoperative maturation score was lower in patients compared to controls (preoperative P = 0.01, postoperative P = 0.03) and increased between pre- and postoperative assessment (P ≤ 0.001). Brain maturation scores did not correlate with neurodevelopmental outcome at 1 year, when corrected for socioeconomic status and postmenstrual age at MRI. This study confirms delayed brain maturation in children with congenital heart disease, and despite neonatal cardiac bypass surgery followed by postoperative intensive care medicine brain maturation is ongoing. We encourage further investigation in outcome prediction in this population, potentially by combining more advanced MRI measures with clinical methods.

Behavioral-state development and sleep-state differentiation during early ontogenesis

Sleep is a key process in neurodevelopment and essential for the maturation of fundamental brain functions. Premature birth can disturb the initial steps of sleep maturation, which may contribute to the impairment of neurodevelopment. It is thus fundamental to understand the maturation of the various sleep states and the quality of cerebral function in each vigilance state, as well as the development of sleep cyclicity, in at-risk neonatal infants, particularly those born premature. The objective of this review is to provide a precise description of sleep states and cycles and their rhythmic organization in premature and term newborns according to their gestational age. Technical aspects of polysomnography, which requires a high level of expertise in neonates, are also described. Principles of the visual interpretation of polysomnography, including the simultaneous analysis of behavioral (spontaneous motricity and eye movements), polysomnographic parameters (electro-oculogram, electrocardiogram, respiration), and electroencephalography patterns are presented. The neurophysiology of sleep ontogenesis and its interaction with brain maturation are discussed, highlighting the crucial role of sleep states and their duration in premature newborns. In particular, the involvement of myoclonic twitches in functional connectivity in sensorimotor development is discussed. Indeed, sleep quality, determined by combined polysomnographic parameters, reflects either normal or pathological developmental processes during the neonatal period. The fundamental place of neurophysiological explorations in the early detection of sleep disorders is discussed, as well as their potential consequences on neurodevelopmental care to improve the prevention of neurodevelopmental impairment.

Age-Dependent Reduction in Severity and Discrete Topographical Patterns in Rasmussen Encephalitis: A Link to Cortical Maturation?

BACKGROUND

Autopsy studies in Rasmussen encephalitis reveal areas of sparing within the affected hemisphere. Clinical progression and inflammation are milder with an older onset. We sought to demonstrate radiological corroboration for these patterns.

METHODS

In our retrospective study, 38 cases were dichotomized into severe pan-hemispheric (all lobes involved) and sub-hemispheric groups (others) to identify age demographics and other severity predictors. The extent and patterns of radiological pathology in the cortex and subcortical structures were assessed by structured visual grading. Relevant clinical data were also reported.

RESULTS

Children with pan-hemispheric involvement were younger at onset (P < 0.001) and were more likely to present with status epilepticus (odds ratio 8.5, 95% confidence interval 1.5 to 50.0, P = 0.022). A history of perinatal asphyxia/hospitalization (P < 0.001) and delayed milestones (P = 0.013) were encountered exclusively in this group, and progression to a low-amplitude record background on electroencephalography, suggesting that cortical damage was identified frequently (P = 0.038, odds ratio = 5.7, 95% confidence interval 1.3 to 25.0). Visual grading revealed significant differences among both cortical (P < 0.001) and subcortical (P < 0.001) regions. On multivariate analysis, the odds for pan-hemispheric disease decreased per year of age at onset (P = 0.022, odds ratio 0.51, 95% confidence interval 0.085 to 0.725). Epilepsy surgery (n = 14) was associated with Engel Class 1 seizure control (P < 0.001). Immunosuppressive therapy (n = 20) did not demonstrate a significant seizure remission (P = 0.157, odds ratio 0.39, 95% confidence interval 0.10 to 1.55).

CONCLUSIONS

Our case series confirms the presence of specific topographical patterns of macroscopic radiological pathology over the affected hemisphere with a marked age-associated reduction in the odds for severe pan-hemispheric disease.

Microglia dynamics in adolescent traumatic brain injury

Repetitive, mild traumatic brain injuries (RmTBIs) are increasingly common in adolescents and encompass one of the largest neurological health concerns in the world. Adolescence is a critical period for brain development where RmTBIs can substantially impact neurodevelopmental trajectories and life-long neurological health. Our current understanding of RmTBI pathophysiology suggests key roles for neuroinflammation in negatively regulating neural health and function. Microglia, the brain’s resident immune population, play important roles in brain development by regulating neuronal number, and synapse formation and elimination. In response to injury, microglia activate to inflammatory phenotypes that may detract from these normal homeostatic, physiological, and developmental roles. To date, however, little is known regarding the impact of RmTBIs on microglia function during adolescent brain development. This review details key concepts surrounding RmTBI pathophysiology, adolescent brain development, and microglia dynamics in the developing brain and in response to injury, in an effort to formulate a hypothesis on how the intersection of these processes may modify long-term trajectories.

[Neurodevelopment and cannabis]

Brain development is a complex phenomenon, stretching from fetal life to adolescence, during which brain maturation proceeds through a series of ordered events including critical periods of plasticity. The brain is particularly sensitive to the environment during these changes. The endocannabinoid system participates directly and indirectly in these plasticity and maturation processes. The main psychoactive component of cannabis, the delta-9-tetrahydrocanabinol, can cross the placental barrier, is present in breastmilk and diffuses in the brain. It interacts with the endocannabinoid signaling, especially through the activation of cannabinoid receptors 1 CB1R, which can lead to abnormal neurodevelopmental processes and neuronal circuits functions. Therefore, exposure to cannabis in utero, in perinatal phase, as well as during the adolescence disrupts the brain maturation and can cause disturbances on the cognitive, psychotic and addictive levels that persist far beyond the period of exposure. Several factors modulate the risk of such complications, but studies performed in animal models as well as in human cohorts have shown that exposure during both the critical perinatal and adolescence phases is a risk factor per se. Current knowledge encourages the dissemination of objective information to young people, to prevent and limit early exposure and its consequences.

MTE-NODDI: Multi-TE NODDI for disentangling non-T2-weighted signal fractions from compartment-specific T2 relaxation times

Neurite orientation dispersion and density imaging (NODDI) has become a popular diffusion MRI technique for investigating microstructural alternations during brain development, maturation and aging in health and disease. However, the NODDI model of diffusion does not explicitly account for compartment-specific T2 relaxation and its model parameters are usually estimated from data acquired with a single echo time (TE). Thus, the NODDI-derived measures, such as the intra-neurite signal fraction, also known as the neurite density index, could be T2-weighted and TE-dependent. This may confound the interpretation of studies as one cannot disentangle differences in diffusion from those in T2 relaxation. To address this challenge, we propose a multi-TE NODDI (MTE-NODDI) technique, inspired by recent studies exploiting the synergy between diffusion and T2 relaxation. MTE-NODDI could give robust estimates of the non-T2-weighted signal fractions and compartment-specific T2 values, as demonstrated by both simulation and in vivo data experiments. Results showed that the estimated non-T2 weighted intra-neurite fraction and compartment-specific T2 values in white matter were consistent with previous studies. The T2-weighted intra-neurite fractions from the original NODDI were found to be overestimated compared to their non-T2-weighted estimates; the overestimation increases with TE, consistent with the reported intra-neurite T2 being larger than extra-neurite T2. Finally, the inclusion of the free water compartment reduces the estimation error in intra-neurite T2 in the presence of cerebrospinal fluid contamination. With the ability to disentangle non-T2-weighted signal fractions from compartment-specific T2 relaxation, MTE-NODDI could help improve the interpretability of future neuroimaging studies, especially those in brain development, maturation and aging.

Maturation of topological organization of brain networks in male adolescent rats: A longitudinal FDG-PET study

Recent studies have found developmental alterations of the brain during the adolescent period. However, maturation-related changes of the topological properties in brain networks are unexplored so far. We therefore used fluoro-d-glucose positron emission tomography (FDG PET) to explore the maturation-related topological metabolic changes in brain networks from adolescence to adulthood with a longitudinal study in rats (male, n = 6), followed by a graph theoretical analysis. Our results showed reduced normalization characteristic path length and increased small world index of brain networks. Specifically, we found that relative to adulthood, in the adolescent stage rats had significantly increased nodal centrality in right entorhinal cortex, left frontal association cortex, and cerebellum, areas relating to memory, executive function and higher cognitive control and motor control; and significantly reduced nodal centrality in left superior colliculus and left retrosplenial cortex. These findings suggest that moving from adolescence to adulthood, networks of the brain mature accompanied by reassignment of hub regions to increase network efficiency. These results provide an animal model of brain network maturation from adolescence to adulthood which are relevant for understanding of development of psychiatric disorders during adolescence or transition from adolescence to adulthood.

Examining brain maturation during adolescence using graph Laplacian learning based Fourier transform

BACKGROUND

Longitudinal neuroimaging studies have demonstrated that adolescence is a crucial developmental period of continued brain growth and change. Motivated by both achievements in graph signal processing and recent evidence that some brain areas act as hubs connecting functionally specialized systems, we propose an approach to detect these regions from a spectral analysis perspective. In particular, as the human brain undergoes substantial development throughout adolescence, we evaluate functional network difference among age groups from functional magnetic resonance imaging (fMRI) measurements.

NEW METHODS

We treated these measurements as graph signals defined on the parcellated functional brain regions and proposed a graph Laplacian learning based Fourier transform (GLFT) to transform the original graph signals into the frequency domain. Eigen-analysis was conducted afterwards to study the behaviors of the corresponding brain regions, which enabled the characterization of brain maturation.

RESULT

We first evaluated our method on the synthetic data and then applied it to resting state and task fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) dataset, comprised of normally developing adolescents from 8 to 22 years of age. The method provided an accuracy of 94.9% in distinguishing different adolescent stages and we detected 13 hubs from resting state fMRI and 16 hubs from task fMRI related to brain maturation.

COMPARISON WITH EXISTING METHODS

The proposed GLFT demonstrated its superiority over conventional graph Fourier transform and alternative graph Fourier transform with high predictive power.

CONCLUSION

The method provides a powerful approach for extracting brain connectivity patterns and identifying hub regions.

Memory: Normative development of memory systems

During the past decades, abundant behavioral, clinical, and neuroimaging data have shown several memory systems in the brain. A memory system is a type of memory that processes a particular type of information, using specific mechanisms, with distinct neural correlates. What we call memory is therefore not a unitary capacity but a collection of distinct systems. From a developmental perspective, each memory system has its own developmental course. This explains the heterogeneity of children's mnemonic competencies: for example, 3-year-olds learn many new words and concepts every day but have trouble recalling in detail an event that happened the week before. In this chapter, we sum up major findings regarding the development from infancy to early adulthood of the main memory systems. Specifically, we report recent data regarding the development of declarative memory (i.e., episodic and semantic memory), and the relationship between the maturation of their neural correlates and the phenomena of infantile and childhood amnesia. We conclude by indicating some of the possible avenues for future research.

Newborns and preterm infants at term equivalent age: A semi-quantitative assessment of cerebral maturity

BACKGROUND AND PURPOSE

Currently available MRI scoring systems of cerebral maturation in term and preterm infant at term equivalent age do not include the changes of transient fetal compartments that persist to term age. We studied the visibility and the pattern of these structures in healthy term newborns compared to preterm infants at term equivalent age in order to investigate if they can be included in a new MRI score system. We hypothesized that transient fetal compartments are different in both groups, and that these differences can be characterized using the clinical T2-weighted MRIs.

MATERIALS AND METHODS

Using 3T MRI T2-weighted brain sequences of 21 full-term and 41 preterm infants (< 32 weeks), scanned at term equivalent age, 3 raters independently scored the maturation level of 3 transient fetal compartments: the periventricular crossroads, von Monakow segments of the white matter, and the subplate compartment. These 3 new items were included in a scoring system along with validated parameters of brain maturation (germinal matrix, bands of migration, subarachnoid space and quality of gyrification). A cumulative maturity score was calculated separately for both groups of newborns by adding together each item. More mature were the brain structures, higher was the cumulative maturity score.

RESULTS

Cumulative maturity score distinguished full-term from preterm infants (mean score 41/60 ± 1.4 versus 37/60 ± 2.5 points, p < 0.001), with an increase of 0.5 points for each supplemental gestational week at birth (r = 0.5, 95% CI 0.5 - 0.85). While a majority of transient fetal compartments were less mature in preterm group at term equivalent age, von Monakow segments of the white matter and subplate compartment presented a more advanced maturational stage in the preterm group compared to the term group. No subject had all scored items in the most mature state. Except a slight intra-rater agreement for von Monakow segment II, inter- and intra-rater agreements were moderate to excellent indicating the potential of the developed scoring system in routine clinical practice.

CONCLUSION

Brain transient fetal structures can be assessed on regular T2-weighted MRI in newborns. Their appearance differs between term and preterm babies. However our results suggest a more complex situation, with both delayed and accelerated maturation pattern in preterm infants. It remains to be determined if these differences could be biomarkers of the future neurodevelopment of preterm infants.

Early Parenting Intervention and Adverse Family Environments Affect Neural Function in Middle Childhood

BACKGROUND

Growing work points to the negative impact of early adverse experiences on the developing brain. An outstanding question concerns the extent to which early intervention can normalize trajectories of brain development in at-risk children. We tested this within the context of a randomized clinical trial of an early parenting program, the Attachment and Biobehavioral Catch-up (ABC), delivered to parents and infants monitored for maltreatment by Child Protective Services.

METHODS

Families participated in the randomized clinical trial when children were 2.5 years of age or younger. Parenting and home adversity was measured at baseline. Children were followed longitudinally, and resting brain activity was measured electrophysiologically (n = 106) when children reached 8 years of age. Spectral power was quantified and compared across children assigned to the experimental intervention (ABC), a control intervention, and a low-risk comparison group (n = 76) recruited at the follow-up assessment.

RESULTS

Higher early home adversity was associated with electrophysiological profiles indicative of cortical delays/immaturity in middle childhood, based on relatively greater power in lower frequency bands (theta, 4-6 Hz, and low alpha, 6-9 Hz) and lower power in a higher frequency band (high alpha, 9-12 Hz). Children assigned to ABC showed relatively greater high-frequency power (beta, 12-20 Hz) than children assigned to the control intervention. Beta power in the ABC did not differ from that of the low-risk comparison group.

CONCLUSIONS

Maltreatment risk and home adversity can affect indicators of middle childhood brain maturation. Early parenting programs can support more normative patterns of neural function during middle childhood.

Preterm brain Injury: White matter injury

Despite the advances in neonatal intensive care, the preterm brain remains vulnerable to white matter injury (WMI) and disruption of normal brain development (i.e., dysmaturation). Compared to severe cystic WMI encountered in the past decades, contemporary cohorts of preterm neonates experience milder WMIs. More than destructive lesions, disruption of the normal developmental trajectory of cellular elements of the white and the gray matter occurs. In the acute phase, in response to hypoxia-ischemia and/or infection and inflammation, multifocal areas of necrosis within the periventricular white matter involve all cellular elements. Later, chronic WMI is characterized by diffuse WMI with aberrant regeneration of oligodendrocytes, which fail to mature to myelinating oligodendrocytes, leading to myelination disturbances. Complete neuronal degeneration classically accompanies necrotic white matter lesions, while altered neurogenesis, represented by a reduction of the dendritic arbor and synapse formation, is observed in response to diffuse WMI. Neuroimaging studies now provide more insight in assessing both injury and dysmaturation of both gray and white matter. Preterm brain injury remains an important cause of neurodevelopmental disabilities, which are still observed in up to 50% of the preterm survivors and take the form of a complex combination of motor, cognitive, and behavioral concerns.

Sleep spindles are altered in early- but not late-onset nightmare recallers

Nightmares are a common sleep disorder, defined as highly disturbing mentation which usually awakens the individual from rapid eye movement (REM) sleep. While nightmares are mainly a REM sleep phenomenon, Picard-Deland et al., (2017) recently showed an association between nightmare recall and sleep spindles, which are a non-rapid eye movement (NREM) oscillatory feature. Their results pointed to fewer slow spindles and a higher oscillatory frequency for fast spindles among frequent nightmare recallers compared with controls. To test the suggestion that nightmares stem from changes to emotional neural circuits arising in early childhood (Nielsen, 2017), including early changes in sleep spindles (Scholle et al., 2007), we investigated if the spindle features of early-onset nightmare recallers (ie, recalling nightmares since childhood) (N = 22), differed from those of late-onset nightmare recallers (ie, since adolescence or adulthood) (N = 11), or from those of controls (N = 23). A retrospective analysis of the sleep spindles of 56 participants who had undergone a polysomnographically-recorded morning nap revealed that Early starters uniquely exhibited lower slow spindle densities in five of six derivations (all p < 0.045) and higher fast spindle frequencies in all six derivations (all p < 0.015). These results add precision to previously reported findings for Nightmare recallers: spindle differences are shown to hold only for Early starters. The lifelong occurrence of nightmares may be closely tied to disruptions in the normal development of spindle generation processes occurring early in development.

Gyrification changes are related to cognitive strengths in autism

Background

Behavioral, cognitive and functional particularities in autism differ according to autism subgroups and might be associated with domain-specific cognitive strengths. It is unknown whether structural changes support this specialization. We investigated the link between cortical folding, its maturation and cognitive strengths in autism subgroups presenting verbal or visuo-spatial peaks of abilities.

Methods

We measured gyrification, a structural index related to function, in 55 autistic participants with (AS-SOD, N = 27) or without (AS-NoSOD, N = 28) a speech onset delay (SOD) with similar symptom severity but respectively perceptual and verbal cognitive strengths, and 37 typical adolescents and young adults matched for intelligence and age. We calculated the local Gyrification Index (lGI) throughout an occipito-temporal region of interest and independently modeled age and peak of ability effects for each group.

Results

Unique gyrification features in both autistic groups were detected in localized clusters. When comparing the three groups, gyrification was found lower in AS-SOD in a fusiform visual area, whereas it was higher in AS-NoSOD in a temporal language-related region. These particular areas presented age-related gyrification differences reflecting contrasting local maturation pathways in AS. As expected, peaks of ability were found in a verbal subtest for the AS-NoSOD group and in the Block Design IQ subtest for the AS-SOD group.

Conclusions

Irrespective of their direction, regional gyrification differences in visual and language processing areas respectively reflect AS-SOD perceptual and AS-NoSOD language-oriented peaks. Unique regional maturation trajectories in the autistic brain may underline specific cognitive strengths, which are key variables for understanding heterogeneity in autism.

•

Subgrouping the autism spectrum (AS) partly accounts for its heterogeneity.

•

AS individuals with a speech onset delay (SOD) show perceptual cognitive strengths.

•

AS individuals without a SOD show language-related cognitive strengths.

•

AS subgroups show unique gyrification patterns in areas related to their strengths.

•

Cortical structural maturation may be related to domain-specific strengths in AS.

Developmental trajectories of brain maturation and behavior: Relevance to major mental illnesses

Adverse events in childhood and adolescence, such as social neglect or drug abuse, are known to lead to behavioral changes in young adulthood. This is particularly true for the subset of people who are intrinsically more vulnerable to stressful conditions. Yet the underlying mechanisms for such developmental trajectory from early life insult to aberrant adult behavior remains elusive. Adolescence is a period of dynamic physiological, psychological, and behavioral changes, encompassing a distinct neurodevelopmental stage called the 'critical period'. During adolescence, the brain is uniquely susceptible to stress. Stress mediators may lead to disturbances to biological processes that can cause permanent alterations in the adult stage, even as severe as the onset of mental illness when paired with genetic risk and environmental factors. Understanding the molecular factors governing the critical period and how stress can disturb the maturation processes will allow for better treatment and prevention of late adolescent/young adult onset psychiatric disorders.

Measuring in vivo cerebral maturation using age-related T2 relaxation times at 3T

OBJECTIVE

To examine age-related changes in T₂ relaxation times during infancy and childhood in order to assess T₂ values obtained from routine MRI as a biomarker.

METHODS

From our pool of clinical pediatric MRI examinations at 3T all patients with normal conventional MRI scans were retrospectively selected. Depending on their clinical findings the identified 99 patients (0-199months) were divided into 43 healthy controls and 56 diseased children with various clinical abnormalities (developmental delay, epilepsy, prematurity, and deafness). T₂ maps based on routinely performed triple echo turbo spin echo sequences were created. T₂ values were measured in 22 brain regions to determine age-related changes. We also investigated whether such changes differ between healthy and diseased children.

RESULTS

Age significantly reduced T₂ relaxation times across all regions (p<0.05), but health status had no impact. With increasing age, T₂ values decreased continuously, with declines faster over the first 10months and slower thereafter. Early rapid and later slow decline was similar in healthy and diseased groups.

CONCLUSIONS

Using T₂ maps based on clinical MRI data we could determine age-related T₂ relaxation times in 22 brain regions during infancy and childhood. Our data have relevance for future investigator independent T₂ relaxation time measurements in determining whether T₂ values are within the normal range or should be considered as potentially pathologic.

Age-related T2 relaxation times at 3 Tesla as a biomarker of infratentorial brain maturation

PURPOSE

The purpose of this study was to examine age-related, infratentorial changes in T₂ relaxation times during infancy and childhood using routine MRI data at 3 Tesla.

METHODS

One hundred patients (0-199 months) without signal abnormalities on conventional MRI were retrospectively selected from our pool of pediatric MRI examinations. T₂ maps based on our routinely acquired triple-echo turbo spin-echo (TSE) sequence were created. Based on their clinical symptoms, the children were divided into 43 controls and 57 diseased children with different clinical diseases. T₂ relaxation times were measured in 15 infratentorial brain regions (medullary pyramid, ventral and dorsal pons, middle cerebellar peduncle, dentate nucleus, medial and lateral cerebellar hemisphere each on both sides, and in the cerebellar vermis) investigating age-related changes. Secondly, this study examined whether those changes in T₂ values differed between healthy and diseased children.

RESULTS

Age significantly reduced T₂ relaxation time in all infratentorial brain regions (p < 0.05). With increasing age, the T₂ relaxation times decreased continuously, faster in the first 9 months and slower thereafter. Overall, controls did not differ significantly from diseased children (p > 0.05) apart from the dentate nucleus and cerebellar hemispheres in terms of rapid decline (larger in controls) and the right dorsal pons and left pyramid in terms of slow decline (larger in diseased children). In both groups, the later slow decline was almost negligible.

CONCLUSIONS

Using T₂ maps, it was possible to determine age-related T₂ relaxation times in the different infratentorial brain regions in this preliminary study. Between neurologically healthy controls and diseased children, no significant differences in T₂ relaxation times could be found overall in the studied regions.

Different maturational changes of fast and slow sleep spindles in the first four years of life

OBJECTIVE/BACKGROUND

Massive changes in brain morphology and function in the first years of life reveal a postero-anterior trajectory of cortical maturation accompanied by regional modifications of NREM sleep. One of the most sensible marker of this maturation process is represented by electroencephalographic (EEG) activity within the frequency range of sleep spindles. However, direct evidence that these changes actually reflect maturational modifications of fast and slow spindles still lacks. Our study aimed at answering the following questions: 1. Do cortical changes at 11.50 Hz frequency correspond to slow spindles? 2. Do fast and slow spindles show different age trajectories and different topographical distributions? 3. Do changes in peak frequency explain age changes of slow and fast spindles?

PATIENTS/METHODS

We measured the antero-posterior changes of slow and fast spindles in the first 60 min of nightly sleep of 39 infants and children (0-48 mo.).

RESULTS

We found that (A) changes of slow spindles from birth to childhood mostly affect frontal areas (B) variations of fast and slow spindles across age groups go in opposite direction, the latter progressively increasing across ages; (C) this process is not merely reducible to changes of spindle frequency.

CONCLUSIONS

As a main finding, our cross-sectional study shows that the first form of mature spindle (i.e., corresponding to the adult phasic event of NREM sleep) is marked by the emergence of slow spindles on anterior regions around the age of 12 months.

Review of sleep-EEG in preterm and term neonates

Neonatal sleep is a crucial state that involves endogenous driven brain activity, important for neuronal survival and guidance of brain networks. Sequential EEG-sleep analysis in preterm infants provides insights into functional brain integrity and can document deviations of the biologically pre-programmed process of sleep ontogenesis during the neonatal period. Visual assessment of neonatal sleep-EEG, with integration of both cerebral and non-cerebral measures to better define neonatal state, is still considered the gold standard. Electrographic patterns evolve over time and are gradually time locked with behavioural characteristics which allow classification of quiet sleep and active sleep periods during the last 10weeks of gestation. Near term age, the neonate expresses a short ultradian sleep cycle, with two distinct active and quiet sleep, as well as brief periods of transitional or indeterminate sleep. Qualitative assessment of neonatal sleep is however challenged by biological and environmental variables that influence the expression of EEG-sleep patterns and sleep organization. Developing normative EEG-sleep data with the aid of automated analytic methods, can further improve our understanding of extra-uterine brain development and state organization under stressful or pathological conditions. Based on those developmental biomarkers of normal and abnormal brain function, research can be conducted to support and optimise sleep in the NICU, with the ultimate goal to improve therapeutic interventions and neurodevelopmental outcome.

Quantification of myelin in children using multiparametric quantitative MRI: a pilot study

PURPOSE

The purpose of this study was to evaluate the usefulness of multiparametric quantitative MRI for myelination quantification in children.

METHODS

We examined 22 children (age 0-14 years) with multiparametric quantitative MRI. The total volume of myelin partial volume (Msum), the percentage of Msum within the whole brain parenchyma (Mbpv), and the percentage of Msum within the intracranial volume (Micv) were obtained. Four developmental models of myelin maturation (the logarithmic, logistic, Gompertz, and modified Gompertz models) were examined to find the most representative model of the three parameters. We acquired myelin partial volume values in different brain regions and assessed the goodness of fit for the models.

RESULTS

The ranges of Msum, Mbpv, and Micv were 0.8-160.9 ml, 0.2-13%, and 0.0-11.6%, respectively. The Gompertz model was the best fit for the three parameters. For developmental model analysis of myelin partial volume in each brain region, the Gompertz model was the best-fit model for pons (R ² = 74.6%), middle cerebeller peduncle (R ² = 76.4%), putamen (R² = 95.8%), and centrum semiovale (R ² = 77.7%). The logistic model was the best-fit model for the genu and splenium of the corpus callosum (R ² = 79.7-93.6%), thalamus (R ² = 81.7%), and frontal, parietal, temporal, and occipital white matter (R ² = 92.5-96.5%).

CONCLUSIONS

Multiparametric quantitative MRI depicts the normal developmental pattern of myelination in children. It is a potential tool for research studies on pediatric brain development evaluation.

A review of important electroencephalogram features for the assessment of brain maturation in premature infants

This review describes the maturational features of the baseline electroencephalogram (EEG) in the neurologically healthy preterm infant. Features such as continuity, sleep state, synchrony and transient waveforms are described, even from extremely preterm infants and includes abundant illustrated examples. The physiological significance of these EEG features and their relationship to neurodevelopment are highlighted where known. This review also demonstrates the importance of multichannel conventional EEG monitoring for preterm infants as many of the features described are not apparent if limited channel EEG monitors are used.

CONCLUSION

This review aims to provide healthcare professionals in the neonatal intensive care unit with guidance on the more common normal maturational features seen in the EEG of preterm infants.

Changes in brain microstructure during infancy and childhood using clinical feasible ADC-maps

PURPOSE

The purpose of this study was to examine age-related changes in apparent diffusion coefficient (ADC) during infancy and childhood using routine MRI data.

METHODS

A total of 112 investigations of patients aged 0 to 17.2 years showing a normal degree of myelination and no signal abnormalities on conventional MRI were retrospectively selected from our pool of pediatric MRI examinations at 1.5T. ADC maps based on our routinely included axial diffusion weighted sequence were created from the scanner. ADC values were measured in 35 different brain regions investigating normal age-related changes during the maturation of the human brain in infancy and childhood using clinical feasible sequences at 1.5T.

RESULTS

The relationship between ADC values and age in infancy and childhood can be described as an exponential function. With increasing age, the ADC values decrease significantly in all brain regions, especially during the first 2 years of life. Except in the peritrigonal white matter, no significant differences were found between both hemispheres. Between 0 and 2 years of life, no significant gender differences were detected.

CONCLUSIONS

Using ADC maps based on a routinely performed axial diffusion weighted sequence, it was possible first to describe the relationship between ADC values and age in infancy and childhood as exponential function in the whole brain and second to determine normative age-related ADC values in multiple brain regions.

Multivariate dynamical modelling of structural change during development

Here we introduce a multivariate framework for characterising longitudinal changes in structural MRI using dynamical systems. The general approach enables modelling changes of states in multiple imaging biomarkers typically observed during brain development, plasticity, ageing and degeneration, e.g. regional gray matter volume of multiple regions of interest (ROIs). Structural brain states follow intrinsic dynamics according to a linear system with additional inputs accounting for potential driving forces of brain development. In particular, the inputs to the system are specified to account for known or latent developmental growth/decline factors, e.g. due to effects of growth hormones, puberty, or sudden behavioural changes etc. Because effects of developmental factors might be region-specific, the sensitivity of each ROI to contributions of each factor is explicitly modelled. In addition to the external effects of developmental factors on regional change, the framework enables modelling and inference about directed (potentially reciprocal) interactions between brain regions, due to competition for space, or structural connectivity, and suchlike. This approach accounts for repeated measures in typical MRI studies of development and aging. Model inversion and posterior distributions are obtained using earlier established variational methods enabling Bayesian evidence-based comparisons between various models of structural change. Using this approach we demonstrate dynamic cortical changes during brain maturation between 6 and 22 years of age using a large openly available longitudinal paediatric dataset with 637 scans from 289 individuals. In particular, we model volumetric changes in 26 bilateral ROIs, which cover large portions of cortical and subcortical gray matter. We account for (1) puberty-related effects on gray matter regions; (2) effects of an early transient growth process with additional time-lag parameter; (3) sexual dimorphism by modelling parameter differences between boys and girls. There is evidence that the regional pattern of sensitivity to dynamic hidden growth factors in late childhood is similar across genders and shows a consistent anterior-posterior gradient with strongest impact to prefrontal cortex (PFC) brain changes. Finally, we demonstrate the potential of the framework to explore the coupling of structural changes across a priori defined subnetworks using an example of previously established resting state functional connectivity.

Age-Dependency of Location of Epileptic Foci in "Continuous Spike-and-Waves during Sleep": A Parallel to the Posterior-Anterior Trajectory of Slow Wave Activity

BACKGROUND

Epileptic encephalopathy with continuous spike-and-waves during sleep (CSWS) occurs during childhood and is characterized by an activation of spike wave complexes during slow wave sleep. The location of epileptic foci is variable, as is etiology. A relationship between the epileptic focus and age has been shown in various focal epilepsies following a posterior-anterior trajectory, and a link to brain maturation has been proposed. We hypothesize that in CSWS, maximal spike wave activity, corresponding to the epileptic focus, is related to age and shows a posterior-anterior evolution.

FINDINGS

In a retrospective cross-sectional study on CSWS (22 EEGs of 22 patients aged 3.1–13.5 years), the location of the epileptic focus is related to age and follows a posterior-anterior course. Younger patients are more likely to have posterior foci than older ones.

CONCLUSIONS

We propose that the posterior-anterior trajectory of maximal spike waves in CSWS might reflect maturational changes of maximal expression of sleep slow waves, which follow a comparable course. Epileptic spike waves, that is, “hyper-synchronized slow waves” may occur at the place where the highest and therefore most synchronized slow waves meet brain tissue with an increased susceptibility to synchronization.

Changes of brain metabolite concentrations during maturation in different brain regions measured by chemical shift imaging

INTRODUCTION

We examined the effect of maturation on the regional distribution of brain metabolite concentrations using multivoxel chemical shift imaging.

METHODS

From our pool of pediatric MRI examinations, we retrospectively selected patients showing a normal cerebral MRI scan or no pathologic signal abnormalities at the level of the two-dimensional 1H MRS-CSI sequence and an age-appropriate global neurological development, except for focal neurological deficits. Seventy-one patients (4.5 months-20 years) were identified. Using LC Model, spectra were evaluated from voxels in the white matter, caudate head, and corpus callosum.

RESULTS

The concentration of total N-acetylaspartate increased in all regions during infancy and childhood except in the right caudate head where it remained constant. The concentration of total creatine decreased in the caudate nucleus and splenium and minimally in the frontal white matter and genu. It remained largely constant in the parietal white matter. The concentration of choline-containing compounds had the tendency to decrease in all regions except in the parietal white matter where it remained constant. The concentration of myoinositol decreased slightly in the splenium and right frontal white matter, remained constant on the left side and in the caudate nucleus, and rose slightly in the parietal white matter and genu.

CONCLUSION

CSI determined metabolite concentrations in multiple cerebral regions during routine MRI. The obtained data will be helpful in future pediatric CSI measurements deciding whether the ratios of the main metabolites are within the range of normal values or have to be considered as probably pathologic.

Awake surgery for hemispheric low-grade gliomas: oncological, functional and methodological differences between pediatric and adult populations

INTRODUCTION

Brain mapping through a direct cortical and subcortical electrical stimulation during an awake craniotomy has gained an increasing popularity as a powerful tool to prevent neurological deficit while increasing extent of resection of hemispheric diffuse low-grade gliomas in adults. However, few case reports or very limited series of awake surgery in children are currently available in the literature.

METHODS

In this paper, we review the oncological and functional differences between pediatric and adult populations, and the methodological specificities that may limit the use of awake mapping in pediatric low-grade glioma surgery.

RESULTS

This could be explained by the fact that pediatric low-grade gliomas have a different epidemiology and biologic behavior in comparison to adults, with pilocytic astrocytomas (WHO grade I glioma) as the most frequent histotype, and with WHO grade II gliomas less prone to anaplastic transformation than their adult counterparts. In addition, aside from the issue of poor collaboration of younger children under 10 years of age, some anatomical and functional peculiarities of children developing brain (cortical and subcortical myelination, maturation of neural networks and of specialized cortical areas) can influence direct electrical stimulation methodology and sensitivity, limiting its use in children.

CONCLUSIONS

Therefore, even though awake procedure with cortical and axonal stimulation mapping can be adapted in a specific subgroup of children with a diffuse glioma from the age of 10 years, only few pediatric patients are nonetheless candidates for awake brain surgery.

The suppression curve as a quantitative approach for measuring brain maturation in preterm infants

OBJECTIVES

We apply the suppression curve (SC) as an automated approach to describe the maturational change in EEG discontinuity in preterm infants. This method allows to define normative values of interburst intervals (IBIs) at different postmenstrual ages (PMA).

METHODS

Ninety-two multichannel EEG recordings from 25 preterm infants (born ⩽32weeks) with normal developmental outcome at 9months, were first analysed using the Line Length method, an established method for burst detection. Subsequently, the SC was defined as the 'level of EEG discontinuity'. The mean and the standard deviation of the SC, as well as the IBIs from each recording were calculated and correlated with PMA.

RESULTS

Over the course of development, there is a decrease in EEG discontinuity with a strong linear correlation between the mean SC and PMA till 34weeks. From 30weeks PMA, differences between discontinuous and continuous EEG become smaller, which is reflected by the decrease of the standard deviation of the SC. IBIs are found to have a significant correlation with PMA.

CONCLUSIONS

Automated detection of individual maturational changes in EEG discontinuity is possible with the SC. These changes include more continuous tracing, less amplitude differences and shorter suppression periods, reflecting development of the vigilance states.

SIGNIFICANCE

The suppression curve facilitates automated assessment of EEG maturation. Clinical applicability is straight forward since values for IBIs according to PMA are generated automatically.

Chemotherapy-induced neurotoxicity in pediatric solid non-CNS tumor patients: An update on current state of research and recommended future directions

Neurocognitive sequelae are known to be induced by cranial radiotherapy and central-nervous-system-directed chemotherapy in childhood Acute Lymphoblastic Leukemia (ALL) and brain tumor patients. However, less evidence exists for solid non-CNS-tumor patients. To get a better understanding of the potential neurotoxic mechanisms of non-CNS-directed chemotherapy during childhood, we performed a comprehensive literature review of this topic. Here, we provide an overview of preclinical and clinical studies investigating neurotoxicity associated with chemotherapy in the treatment of pediatric solid non-CNS tumors. Research to date suggests that chemotherapy has deleterious biological and psychological effects, with animal studies demonstrating histological evidence for neurotoxic effects of specific agents and human studies demonstrating acute neurotoxicity. Although the existing literature suggests potential neurotoxicity throughout neurodevelopment, research into the long-term neurocognitive sequelae in survivors of non-CNS cancers remains limited. Therefore, we stress the critical need for neurodevelopmental focused research in children who are treated for solid non-CNS tumors, since they are at risk for potential neurocognitive impairment.

MRI and (1)H-MRS in adenosine kinase deficiency

INTRODUCTION

Adenosine kinase deficiency (ADK deficiency) is a recently described disorder of methionine and adenosine metabolism resulting in a neurological phenotype with developmental delay, muscular hypotonia, and epilepsy as well as variable systemic manifestations. The underlying neuropathology is poorly understood. We have investigated MRI and (1)H-MRS changes in ADK deficiency in order to better understand the in vivo neuropathologic changes of ADK deficiency.

METHODS

Systematic evaluation of 21 MRIs from eight patients (age range 9 days-14.6 years, mean 3.9 years, median 2.7 years) including diffusion-weighted imaging in six and (1)H-MRS in five patients.

RESULTS

Brain maturation was delayed in the neonatal period and in infancy (6/6), but ultimately complete. White matter changes occurring in five of eight patients were discrete, periventricular, and unspecific (4/5), or diffuse with sparing of optic radiation, corona radiata, and pyramidal tracts (1/5). Choline was low in white matter spectra (3/3), while there was no indication of low creatine in white matter or basal ganglia (5/5), and diffusion was variably decreased or increased. Central tegmental tract hyperintensity was a common finding (6/8), as was supratentorial atrophy (6/8).

CONCLUSIONS

MRI changes in ADK deficiency consist of delayed but ultimately completed brain maturation with later onset of mostly unspecific white matter changes and potentially transient central tegmental tract hyperintensity. Immaturity on neonatal MRI is consistent with prenatal onset of disease and reduced choline with lower membrane turnover resulting in delayed myelination and deficient myelin maintenance.

Pre-hatching fluoxetine-induced neurochemical, neurodevelopmental, and immunological changes in newly hatched cuttlefish

Embryonic and early postembryonic development of the cuttlefish Sepia officinalis (a cephalopod mollusk) occurs in coastal waters, an environment subject to considerable pressure from xenobiotic pollutants such as pharmaceutical residues. Given the role of serotonin in brain development and its interaction with neurodevelopmental functions, this study focused on fluoxetine (FLX), a selective serotonin reuptake inhibitor (SSRI, antidepressant). The goal was to determine the effects of subchronic waterborne FLX exposure (1 and 10 μg L(-1)) during the last 15 days of embryonic development on neurochemical, neurodevelopmental, behavioral, and immunological endpoints at hatching. Our results showed for the first time that organic contaminants, such as FLX, could pass through the eggshell during embryonic development, leading to a substantial accumulation of this molecule in hatchlings. We also found that FLX embryonic exposure (1 and 10 μg L(-1)) (1) modulated dopaminergic but not serotonergic neurotransmission, (2) decreased cell proliferation in key brain structures for cognitive and visual processing, (3) did not induce a conspicuous change in camouflage quality, and (4) decreased lysozyme activity. In the long term, these alterations observed during a critical period of development may impair complex behaviors of the juvenile cuttlefish and thus lead to a decrease in their survival. Finally, we suggest a different mode of action by FLX between vertebrate and non-vertebrate species and raise questions regarding the vulnerability of early life stages of cuttlefish to the pharmaceutical contamination found in coastal waters.

The impact of quality assurance assessment on diffusion tensor imaging outcomes in a large-scale population-based cohort

BACKGROUND

Diffusion tensor imaging (DTI) is applied in investigation of brain biomarkers for neurodevelopmental and neurodegenerative disorders. However, the quality of DTI measurements, like other neuroimaging techniques, is susceptible to several confounding factors (e.g., motion, eddy currents), which have only recently come under scrutiny. These confounds are especially relevant in adolescent samples where data quality may be compromised in ways that confound interpretation of maturation parameters. The current study aims to leverage DTI data from the Philadelphia Neurodevelopmental Cohort (PNC), a sample of 1601 youths with ages of 8-21 who underwent neuroimaging, to: 1) establish quality assurance (QA) metrics for the automatic identification of poor DTI image quality; 2) examine the performance of these QA measures in an external validation sample; 3) document the influence of data quality on developmental patterns of typical DTI metrics.

METHODS

All diffusion-weighted images were acquired on the same scanner. Visual QA was performed on all subjects completing DTI; images were manually categorized as Poor, Good, or Excellent. Four image quality metrics were automatically computed and used to predict manual QA status: Mean voxel intensity outlier count (MEANVOX), Maximum voxel intensity outlier count (MAXVOX), mean relative motion (MOTION) and temporal signal-to-noise ratio (TSNR). Classification accuracy for each metric was calculated as the area under the receiver-operating characteristic curve (AUC). A threshold was generated for each measure that best differentiated visual QA status and applied in a validation sample. The effects of data quality on sensitivity to expected age effects in this developmental sample were then investigated using the traditional MRI diffusion metrics: fractional anisotropy (FA) and mean diffusivity (MD). Finally, our method of QA is compared with DTIPrep.

RESULTS

TSNR (AUC=0.94) best differentiated Poor data from Good and Excellent data. MAXVOX (AUC=0.88) best differentiated Good from Excellent DTI data. At the optimal threshold, 88% of Poor data and 91% Good/Excellent data were correctly identified. Use of these thresholds on a validation dataset (n=374) indicated high accuracy. In the validation sample 83% of Poor data and 94% of Excellent data was identified using thresholds derived from the training sample. Both FA and MD were affected by the inclusion of poor data in an analysis of an age, sex and race matched comparison sample. In addition, we show that the inclusion of poor data results in significant attenuation of the correlation between diffusion metrics (FA and MD) and age during a critical neurodevelopmental period. We find higher correspondence between our QA method and DTIPrep for Poor data, but we find our method to be more robust for apparently high-quality images.

CONCLUSION

Automated QA of DTI can facilitate large-scale, high-throughput quality assurance by reliably identifying both scanner and subject induced imaging artifacts. The results present a practical example of the confounding effects of artifacts on DTI analysis in a large population-based sample, and suggest that estimates of data quality should not only be reported but also accounted for in data analysis, especially in studies of development.

Amide Proton Transfer (APT) MR imaging and Magnetization Transfer (MT) MR imaging of pediatric brain development

OBJECTIVES

To quantify the brain maturation process during childhood using combined amide proton transfer (APT) and conventional magnetization transfer (MT) imaging at 3 Tesla.

METHODS

Eighty-two neurodevelopmentally normal children (44 males and 38 females; age range, 2-190 months) were imaged using an APT/MT imaging protocol with multiple saturation frequency offsets. The APT-weighted (APTW) and MT ratio (MTR) signals were quantitatively analyzed in multiple brain areas. Age-related changes in MTR and APTW were evaluated with a non-linear regression analysis.

RESULTS

The APTW signals followed a decreasing exponential curve with age in all brain regions measured (R(2) = 0.7-0.8 for the corpus callosum, frontal and occipital white matter, and centrum semiovale). The most significant changes appeared within the first year. At maturation, larger decreases in APTW and lower APTW values were found in the white matter. On the contrary, the MTR signals followed an increasing exponential curve with age in the same brain regions measured, with the most significant changes appearing within the initial 2 years. There was an inverse correlation between the MTR and APTW signal intensities during brain maturation.

CONCLUSIONS

Together with MT imaging, protein-based APT imaging can provide additional information in assessing brain myelination in the paediatric population.

KEY POINTS

• APTW signals followed a decreasing exponential curve with age. • The most significant APTW changes appeared within the first year • At maturation, larger APTW decreases and lower APTW appeared in white matter • MTR signals followed an increasing exponential curve with age.

Localized Misfolding Within Broca's Area as a Distinctive Feature of Autistic Disorder

BACKGROUND

Recent neuroimaging studies suggest that autism spectrum disorder results from abnormalities in the cortical folding pattern. Usual morphometric measurements have failed to provide reliable neuroanatomic markers. Here, we propose that sulcal pits, which are the deepest points in each fold, are suitable candidates to uncover this atypical cortical folding.

METHODS

Sulcal pits were extracted from a magnetic resonance imaging database of 102 children (1.5-10 years old) distributed in three groups: children with autistic disorder (n = 59), typically developing children (n = 22), and children with pervasive developmental disorder not otherwise specified (n = 21). The geometrical properties of sulcal pits were compared between these three groups.

RESULTS

Fold-level analyses revealed a reduced pit depth in the left ascending ramus of the Sylvian fissure in children with autistic disorder only. The depth of this central fold of Broca's area was correlated with the social communication impairments that are characteristic of the pathology.

CONCLUSIONS

Our findings support an atypical gyrogenesis of this specific fold in autistic disorder that could be used for differential diagnosis. Sulcal pits constitute valuable markers of the cortical folding dynamics and could help for the early detection of atypical brain maturation.

Family Nurture Intervention in preterm infants alters frontal cortical functional connectivity assessed by EEG coherence

AIM

To assess the impact of Family Nurture Intervention (FNI) on cortical function in preterm infants at term age.

METHODS

Family Nurture Intervention is a NICU-based intervention designed to establish emotional connection between mothers and preterm infants. Infants born at 26-34 weeks postmenstrual age (PMA) were divided into two groups, standard care (SC, N = 49) and FNI (FNI, N = 56). Infants had EEG recordings of ~one hour duration with 124 lead nets between 37 and 44 weeks PMA. Coherence was measured between all pairs of electrodes in ten frequency bands. Data were summarised both within and between 12 regions during two sleep states (active, quiet).

RESULTS

Coherence levels were negatively correlated with PMA age in both groups. As compared to SC infants, FNI infants showed significantly lower levels of EEG coherence (1-18 Hz) largely within and between frontal regions.

CONCLUSION

Coherence in FNI infants was decreased in regions where we previously found robust increases in EEG power. As coherence decreases with age, results suggest that FNI may accelerate brain maturation particularly in frontal brain regions, which have been shown in research by others to be involved in regulation of attention, cognition and emotion regulation; domains deficient in preterm infants.

Detection of hand and leg motor tract injury using novel diffusion tensor MRI tractography in children with central motor dysfunction

PURPOSE

To examine whether an objective segmenation of corticospinal tract (CST) associated with hand and leg movements can be used to detect central motor weakness in the corresponding extremities in a pediatric population.

MATERIAL AND METHODS

This retrospective study included diffusion tensor imaging (DTI) of 25 children with central paresis affecting at least one limb (age: 9.0±4.2years, 15 boys, 5/13/7 children with left/right/both hemispheric lesions including ischemia, cyst, and gliosis), as well as 42 pediatric control subjects with no motor dysfunction (age: 9.0±5.5years, 21 boys, 31 healthy/11 non-lesional epilepsy children). Leg- and hand-related CST pathways were segmented using DTI-maximum a posteriori (DTI-MAP) classification. The resulting CST volumes were then divided by total supratentorial white matter volume, resulting in a marker called "normalized streamline volume ratio (NSVR)" to quantify the degree of axonal loss in separate CST pathways associated with leg and hand motor functions. A receiver operating characteristic curve was applied to measure the accuracy of this marker to identify extremities with motor weakness.

RESULTS

NSVR values of hand/leg CST selectively achieved the following values of accuracy/sensitivity/specificity: 0.84/0.84/0.57, 0.82/0.81/0.55, 0.78/0.75/0.55, 0.79/0.81/0.54 at a cut-off of 0.03/0.03/0.03/0.02 for right hand CST, left hand CST, right leg CST, and left leg CST, respectively. Motor weakness of hand and leg was most likely present at the cut-off values of hand and leg NSVR (i.e., 0.029/0.028/0.025/0.020 for left-hand/right-hand/left-leg/right-leg). The control group showed a moderate age-related increase in absolute CST volumes and a biphasic age-related variation of the normalized CST volumes, which were lacking in the paretic children.

CONCLUSIONS

This study demonstrates that DTI-MAP classification may provide a new imaging tool to quantify axonal loss in children with central motor dysfunction. Using this technique, we found that early-life brain lesions affect the maturational trajectory of the primary motor pathway which may be used as an effective marker to facilitate evidence-based treatment of paretic children.

Prediction of brain maturity based on cortical thickness at different spatial resolutions

Several studies using magnetic resonance imaging (MRI) scans have shown developmental trajectories of cortical thickness. Cognitive milestones happen concurrently with these structural changes, and a delay in such changes has been implicated in developmental disorders such as attention-deficit/hyperactivity disorder (ADHD). Accurate estimation of individuals' brain maturity, therefore, is critical in establishing a baseline for normal brain development against which neurodevelopmental disorders can be assessed. In this study, cortical thickness derived from structural magnetic resonance imaging (MRI) scans of a large longitudinal dataset of normally growing children and adolescents (n=308), were used to build a highly accurate predictive model for estimating chronological age (cross-validated correlation up to R=0.84). Unlike previous studies which used kernelized approach in building prediction models, we used an elastic net penalized linear regression model capable of producing a spatially sparse, yet accurate predictive model of chronological age. Upon investigating different scales of cortical parcellation from 78 to 10,240 brain parcels, we observed that the accuracy in estimated age improved with increased spatial scale of brain parcellation, with the best estimations obtained for spatial resolutions consisting of 2560 and 10,240 brain parcels. The top predictors of brain maturity were found in highly localized sensorimotor and association areas. The results of our study demonstrate that cortical thickness can be used to estimate individuals' brain maturity with high accuracy, and the estimated ages relate to functional and behavioural measures, underscoring the relevance and scope of the study in the understanding of biological maturity.