Evidence on the emergence of the brain's default network from 2-week-old to 2-year-old healthy pediatric subjects

Annual research review: Growth connectomics--the organization and reorganization of brain networks during normal and abnormal development

BACKGROUND

We first give a brief introduction to graph theoretical analysis and its application to the study of brain network topology or connectomics. Within this framework, we review the existing empirical data on developmental changes in brain network organization across a range of experimental modalities (including structural and functional MRI, diffusion tensor imaging, magnetoencephalography and electroencephalography in humans).

SYNTHESIS

We discuss preliminary evidence and current hypotheses for how the emergence of network properties correlates with concomitant cognitive and behavioural changes associated with development. We highlight some of the technical and conceptual challenges to be addressed by future developments in this rapidly moving field. Given the parallels previously discovered between neural systems across species and over a range of spatial scales, we also review some recent advances in developmental network studies at the cellular scale. We highlight the opportunities presented by such studies and how they may complement neuroimaging in advancing our understanding of brain development. Finally, we note that many brain and mind disorders are thought to be neurodevelopmental in origin and that charting the trajectory of brain network changes associated with healthy development also sets the stage for understanding abnormal network development.

CONCLUSIONS

We therefore briefly review the clinical relevance of network metrics as potential diagnostic markers and some recent efforts in computational modelling of brain networks which might contribute to a more mechanistic understanding of neurodevelopmental disorders in future.

Use of resting-state functional MRI to study brain development and injury in neonates

Advances in methodology have led to expanded application of resting-state functional MRI (rs-fMRI) to the study of term and prematurely born infants during the first years of life, providing fresh insight into the earliest forms of functional cerebral development. In this review, we detail our evolving understanding of the use of rs-fMRI for studying neonates. We initially focus on the biological processes of cortical development related to resting-state network development. We then review technical issues principally affecting neonatal investigations, including the effects of subject motion during acquisition and image distortions related to magnetic susceptibility effects. We next summarize the literature in which rs-fMRI is used to study normal brain development during the early postnatal period, the effects of prematurity, and the effects of cerebral injury. Finally, we review potential future directions for the field, such as the use of complementary imaging modalities and advanced analysis techniques.

Quantitative tract-based white matter heritability in twin neonates

Studies in adults indicate that white matter microstructure, assessed with diffusion tensor imaging (DTI), has high heritability. Little is known about genetic and environmental influences on DTI parameters, measured along fiber tracts particularly, in early childhood. In the present study, we report comprehensive heritability data of white matter microstructure fractional anisotropy (FA), radial diffusion (RD), and axial diffusion (AD) along 47 fiber tracts using the quantitative tractography in a large sample of neonatal twins (n=356). We found significant genetic influences in almost all tracts with similar heritabilities for FA, RD, and AD as well as positive relationships between these parameters and heritability. In a single tract analysis, genetic influences along the length of the tract were highly variable. These findings suggest that at birth, there is marked heterogeneity of genetic influences of white matter microstructure within white matter tracts. This study provides a basis for future studies of developmental changes in genetic and environmental influences during early childhood, a period of rapid development that likely plays a major role in individual differences in white matter structure and function.

The intrahemispheric functional properties of the developing sensorimotor cortex are influenced by maturation

The investigation of the functional changes in the sensorimotor cortex has important clinical implications as deviations from normal development can anticipate developmental disorders. The functional properties of the sensorimotor cortex can be characterized through the rolandic mu rhythm, already present during infancy. However, how the sensorimotor network develops from early infancy to adulthood, and how sensorimotor processing contributes to the generation of perceptual-motor coupling remains largely unknown. Here, we analyzed magnetoencephalographic (MEG) data recorded in two groups of infants (11-24 and 26-47 weeks), two groups of children (24-34 and 36-60 months), and a control group of adults (20-39 years), during intermixed conditions of rest and prehension. The MEG sensor array was positioned over the sensorimotor cortex of the contralateral hemisphere. We characterized functional connectivity and topological properties of the sensorimotor network across ages and conditions through synchronization likelihood and segregation/integration measures in an individual mu rhythm frequency range. All functional measures remained almost unchanged during the first year of life, whereas they varied afterwards through childhood to reach adult values, demonstrating an increase of both segregation and integration properties. With age, the sensorimotor network evolved from a more random (infants) to a "small-world" organization (children and adults), more efficient both locally and globally. These findings are in line with prior studies on structural and functional brain development in infants, children and adults. We could not demonstrate any significant change in the functional properties of the sensorimotor cortex in the prehension condition with respect to rest. Our results support the view that, since early infancy, the functional properties of the developing sensorimotor cortex are modulated by maturation.

Toward a neural basis for peer-interaction: what makes peer-learning tick?

Many of the instructional practices that have been advanced as intrinsically motivating are inherent in socio-constructivist learning environments. There is now emerging scientific evidence to explain why interactive learning environments promote the intrinsic motivation to learn. The "two-body" and "second person" approaches have begun to explore the "dark matter" of social neuroscience: the intra- and inter-individual brain dynamics during social interaction. Moreover, studies indicate that when young learners are given expanded opportunities to actively and equitably participate in collaborative learning activities they experienced feelings of well-being, contentment, or even excitement. Neuroscience starts demonstrating how this naturally rewarding aspect is strongly associated with the implication of the mesolimbic dopaminergic pathway during social interaction. The production of dopamine reinforces the desire to continue the interaction, and heightens feelings of anticipation for future peer-learning activities. Here we review how cooperative learning and problem-solving interactions can bring about the "intrinsic" motivation to learn. Overall, the reported theoretical arguments and neuroscientific results have clear implications for school and organization approaches and support social constructivist perspectives.

Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data

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SVMs classified 6 versus 12 month-old infants above chance based on fcMRI data alone.

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We carefully accounted for the effects of fcMRI motion artifact.

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These results coincide with a period of dramatic change in infant development.

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Two interpretations about connections supporting this age categorization are given.

Human large-scale functional brain networks are hypothesized to undergo significant changes over development. Little is known about these functional architectural changes, particularly during the second half of the first year of life. We used multivariate pattern classification of resting-state functional connectivity magnetic resonance imaging (fcMRI) data obtained in an on-going, multi-site, longitudinal study of brain and behavioral development to explore whether fcMRI data contained information sufficient to classify infant age. Analyses carefully account for the effects of fcMRI motion artifact. Support vector machines (SVMs) classified 6 versus 12 month-old infants (128 datasets) above chance based on fcMRI data alone. Results demonstrate significant changes in measures of brain functional organization that coincide with a special period of dramatic change in infant motor, cognitive, and social development. Explorations of the most different correlations used for SVM lead to two different interpretations about functional connections that support 6 versus 12-month age categorization.

Age-related increases in long-range connectivity in fetal functional neural connectivity networks in utero

Formation of operational neural networks is one of the most significant accomplishments of human fetal brain growth. Recent advances in functional magnetic resonance imaging (fMRI) have made it possible to obtain information about brain function during fetal development. Specifically, resting-state fMRI and novel signal covariation approaches have opened up a new avenue for non-invasive assessment of neural functional connectivity (FC) before birth. Early studies in this area have unearthed new insights about principles of prenatal brain function. However, very little is known about the emergence and maturation of neural networks during fetal life. Here, we obtained cross-sectional rs-fMRI data from 39 fetuses between 24 and 38 weeks postconceptual age to examine patterns of connectivity across ten neural FC networks. We identified primitive forms of motor, visual, default mode, thalamic, and temporal networks in the human fetal brain. We discovered the first evidence of increased long-range, cerebral-cerebellar, cortical-subcortical, and intra-hemispheric FC with advancing fetal age. Continued aggregation of data about fundamental neural connectivity systems in utero is essential to establishing principles of connectomics at the beginning of human life. Normative data provides a vital context against which to compare instances of abnormal neurobiological development.

Brains for all the ages: structural neurodevelopment in infants and children from a life-span perspective

Magnetic resonance imaging (MRI) is a noninvasive method to measure brain structure and function that may be applied to human participants of all ages. This chapter reviews our recent work creating a life-span Neurodevelopmental MRI Database. It provides age-specific reference data in fine-grained age intervals from 2 weeks through 89 years. The reference data include average MRI templates, segmented tissue priors, and a common stereotaxic atlas for pediatric and adult participants. The database will be useful for neuroimaging research over a wide range of ages and may be used to make life-span comparisons. The chapter reviews the application of this database to the study of neurostructural development, including a new volumetric study of segmented brain tissue over the life span. We also show how this database could be used to create "study-specific" MRI templates for special groups and apply this to the MRIs of Chinese children. Finally, we review recent use of the database in the study of brain activity in pediatric populations.

Behavioral inhibition and developmental risk: a dual-processing perspective

Behavioral inhibition (BI) is an early-appearing temperament characterized by strong reactions to novelty. BI shows a good deal of stability over childhood and significantly increases the risk for later diagnosis of social anxiety disorder (SAD). Despite these general patterns, many children with high BI do not go on to develop clinical, or even subclinical, anxiety problems. Therefore, understanding the cognitive and neural bases of individual differences in developmental risk and resilience is of great importance. The present review is focused on the relation of BI to two types of information processing: automatic (novelty detection, attention biases to threat, and incentive processing) and controlled (attention shifting and inhibitory control). We propose three hypothetical models (Top-Down Model of Control; Risk Potentiation Model of Control; and Overgeneralized Control Model) linking these processes to variability in developmental outcomes for BI children. We argue that early BI is associated with an early bias to quickly and preferentially process information associated with motivationally salient cues. When this bias is strong and stable across development, the risk for SAD is increased. Later in development, children with a history of BI tend to display normative levels of performance on controlled attention tasks, but they demonstrate exaggerated neural responses in order to do so, which may further potentiate risk for anxiety-related problems. We conclude by discussing the reviewed studies with reference to the hypothetical models and make suggestions regarding future research and implications for treatment.

Intersubject variability of and genetic effects on the brain's functional connectivity during infancy

Infancy is a period featuring a high level of intersubject variability but the brain basis for such variability and the potential genetic/environmental contributions remain largely unexplored. The assessment of the brain's functional connectivity during infancy by the resting state functional magnetic resonance imaging (rsfMRI) technique (Biswal et al., 1995) provides a unique means to probe the brain basis of intersubject variability during infancy. In this study, an unusually large typically developing human infant sample including 58 singletons, 132 dizygotic twins, and 98 monozygotic twins with rsfMRI scans during the first 2 years of life was recruited to delineate the spatial and temporal developmental patterns of both the intersubject variability of and genetic effects on the brain's functional connectivity. Through systematic voxelwise functional connectivity analyses, our results revealed that the intersubject variability at birth features lower variability in primary functional areas but higher values in association areas. Although the relative pattern remains largely consistent, the magnitude of intersubject variability undergoes an interesting U-shaped growth during the first 2 years of life. Overall, the intersubject variability patterns during infancy show both adult-like and infant-specific characteristics (Mueller et al., 2013). On the other hand, age-dependent genetic effects were observed showing significant but bidirectional relationships with intersubject variability. The temporal and spatial patterns of the intersubject variability of and genetic contributions to the brain's functional connectivity documented in this study shed light on the largely uncharted functional development of the brain during infancy.

Frequency of spontaneous BOLD signal shifts during infancy and correlates with cognitive performance

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Peak-frequency of spontaneous BOLD signal increases during infancy.

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Increments of power at the peak-frequency showed spatially dependent patterns.

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Power at the peak-frequency in 1-year olds correlates with cognitive performance.

Numerous studies have been conducted to delineate the early development of different functional networks, based on measuring the temporal synchronization of spontaneous blood oxygenation level-dependent (BOLD) signals acquired using resting state functional MRI (rsfMRI). However, little attention has been paid to the change of the frequency properties of these signals during early brain development. Such frequency properties may reflect important physiological changes and potentially have significant cognitive consequences. In this study, leveraging a large (N = 86 subjects), longitudinal sample of human infants scanned during the first two years of life, we aimed to specifically delineate the developmental changes of the frequency characteristics of spontaneous BOLD signals. Both whole-brain and network-level examinations were carried out and the frequency–behavior relationship was explored. Our results revealed a clear right-ward shift of BOLD signal frequency during the first year of life. Moreover, the power at the peak-frequency for sensorimotor and lateral visual networks correlates with domain-specific Mullen Scales in 1-year-olds, suggesting the behavioral significance of the BOLD signal frequency during infancy. Findings from this study shed light into early functional brain development and provide a new perspective for future searches for functional developmental abnormalities.

Age effects on the default mode and control networks in typically developing children

BACKGROUND

The investigation of neurodevelopment during late childhood and pre-adolescence has recently attracted a great deal of interest in the field of neuroimaging. One promising topic in this field is the formation of brain networks in healthy subjects. The integration between neural modules characterizes the ability of the network to process information globally. Although many fMRI-based neurodevelopment studies can be found in the literature, the analyses of very large samples (on the order of hundreds of subjects) that focus on the late childhood/pre-adolescence period and resting state fMRI are scarce, and most studies have focused solely on North American and European populations.

AIMS

In this study, we present a descriptive investigation of the developmental formation of the Default Mode Network and the Control Network based on a Brazilian, cross-sectional community sample of 447 typically developing subjects aged 7-15 years old.

METHODS

Resting state fMRI data were acquired using two MRI systems from the same manufacturer using the same acquisition parameters. We estimated the age effects on the strength of the links (between brain regions) and the network features (graph descriptors: degree and eigenvector centrality).

RESULTS

Our findings showed an increase in the antero-posterior connectivity in both studied networks during brain development. The graph analyses showed an increase in centrality with age for most regions in the Default Mode Network and the dorsal anterior and posterior cingulate, the right anterior insula and the left posterior temporal cortex in the Control Network.

CONCLUSION

We conclude that the period of 7-15 years of age is crucial for the development of both the Default Mode and Control networks, with integration between the posterior and anterior neuronal modules and an increase in the centrality measures of the hub regions.

Resting-State Network Complexity and Magnitude Are Reduced in Prematurely Born Infants

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

Duration of early adversity and structural brain development in post-institutionalized adolescents

For children reared in institutions for orphaned or abandoned children, multiple aspects of the early environment deviate from species-typical experiences, which may lead to alterations in neurobehavioral development. Although the effects of early deprivation and early life stress have been studied extensively in animal models, less is known about implications for human brain development. This structural neuroimaging study examined the long-term neural correlates of early adverse rearing environments in a large sample of 12-14 year old children (N = 110) who were internationally adopted from institutional care as young children (median age at adoption = 12 months) relative to a same age, comparison group reared with their biological families in the United States. History of institutional rearing was associated with broad changes in cortical volume even after controlling for variability in head size. Results suggested that prefrontal cortex was especially susceptible to early adversity, with significant reductions in volume (driven primarily by differences in surface area rather than cortical thickness) in post-institutionalized youth. Hippocampal volumes showed an association with duration of institutional care, with later-adopted children showing the smallest volumes relative to non-adopted controls. Larger amygdala volumes were not detected in this sample of post-institutionalized children. These data suggest that this temporally discrete period of early deprivation is associated with persisting alterations in brain morphology even years after exposure. Furthermore, these alterations are not completely ameliorated by subsequent environmental enrichment by early adolescence.

Early visual attention in preterm and fullterm infants in relation to cognitive and motor outcomes at school age: an exploratory study

OBJECTIVE

Preterm infants are exposed to the visual environment earlier than fullterm infants, but whether early exposure affects later development is unclear. Our aim was to investigate whether the development of visual disengagement capacity during the first 6 months postterm was associated with cognitive and motor outcomes at school age, and whether associations differed between fullterms and low-risk preterms.

METHOD

Seventeen fullterms and ten low-risk preterms were tested in a gaze shifting task every 4 weeks until 6 months postterm. The longitudinal data were converted into single continuous variables by fitting the data with an S-shaped curve (frequencies of looks) or an inverse model (latencies of looks). Neuropsychological test results at school age were converted into composite z scores. We then performed linear regression analyses for each functional domain at school age with the variables measuring infant visual attention as separate predictors and adjusting for maternal level of education and group (fullterms versus preterms). We included an interaction term, visual attention*group, to determine whether predictive relations differed between fullterms and preterms.

RESULTS

A slower development of disengagement predicted poorer performance on attention, motor skills, and handwriting, irrespective of fullterm or preterm birth. Predictive relationships differed marginally between fullterms and preterms for inhibitory attentional control (P = 0.054) and comprehensive reading (P = 0.064).

CONCLUSION

This exploratory study yielded no indications of a clear advantage or disadvantage of the extra visual exposure in healthy preterm infants. We tentatively conclude that additional visual exposure does not interfere with the ongoing development of neuronal networks during this vulnerable period of brain development.

Multivariate longitudinal shape analysis of human lateral ventricles during the first twenty-four months of life

BACKGROUND

Little is known about the temporospatial shape characteristics of human lateral ventricles (LVs) during the first two years of life. This study aimed to delineate the morphological growth characteristics of LVs during early infancy using longitudinally acquired MR images in normal healthy infants.

METHODS

24 healthy infants were MR imaged starting from 2 weeks old every 3 months during the first and every 6 months during the second year. Bilateral LVs were segmented and longitudinal morphological and shape analysis were conducted using longitudinal mixed effect models.

RESULTS

A significant bilateral ventricular volume increase (p<0.0001) is observed in year one (Left: 126±51% and Right: 145±62%), followed by a significant reduction (p<0.02) during the second year of life (Left: -24±27% and Right: -20±18%) despite the continuing increase of intracranial volume. Morphological analysis reveals that the ventricular growth is spatially non-uniform, and that the most significant growth occurs during the first 6 months. The first 3 months of life exhibit a significant (p<0.01) bilateral lengthening of the anterior lateral ventricle and a significant increase of radius (p<0.01) and area (p<0.01) at the posterior portion of the ventricle. Shape analysis shows that the horns exhibit a faster growth rate than the mid-body. Finally, bilateral significant age effects (p<0.01) are observed for the growth of LVs whereas gender effects are more subtle and significant effects (p<0.01) only present at the left anterior and posterior horns. More importantly, both the age and gender effects are growth directionally dependent.

CONCLUSIONS

We have demonstrated the temporospatial shape growth characteristics of human LVs during the first two years of life using a unique longitudinal MR data set. A temporally and spatially non-uniform growth pattern was reported. These normative results could provide invaluable information to discern abnormal growth patterns in patients with neurodevelopmental disorders.

Development of thalamocortical connectivity during infancy and its cognitive correlations

Although commonly viewed as a sensory information relay center, the thalamus has been increasingly recognized as an essential node in various higher-order cognitive circuits, and the underlying thalamocortical interaction mechanism has attracted increasing scientific interest. However, the development of thalamocortical connections and how such development relates to cognitive processes during the earliest stages of life remain largely unknown. Leveraging a large human pediatric sample (N = 143) with longitudinal resting-state fMRI scans and cognitive data collected during the first 2 years of life, we aimed to characterize the age-dependent development of thalamocortical connectivity patterns by examining the functional relationship between the thalamus and nine cortical functional networks and determine the correlation between thalamocortical connectivity and cognitive performance at ages 1 and 2 years. Our results revealed that the thalamus-sensorimotor and thalamus-salience connectivity networks were already present in neonates, whereas the thalamus-medial visual and thalamus-default mode network connectivity emerged later, at 1 year of age. More importantly, brain-behavior analyses based on the Mullen Early Learning Composite Score and visual-spatial working memory performance measured at 1 and 2 years of age highlighted significant correlations with the thalamus-salience network connectivity. These results provide new insights into the understudied early functional brain development process and shed light on the behavioral importance of the emerging thalamocortical connectivity during infancy.

Early metabolic development of posteromedial cortex and thalamus in humans analyzed via in vivo quantitative magnetic resonance spectroscopy

The posteromedial cortex (PMC) including the posterior cingulate, retrosplenial cortex, and medial parietal cortex/precuneus is an epicenter of cortical interactions in a wide spectrum of neural activity. Anatomic connections between PMC and thalamic components have been established in animal studies, but similar studies do not exist for the fetal and neonatal period. Magnetic resonance spectroscopy (MRS) allows for noninvasive measurement of metabolites in early development. Using single-voxel 3-T MRS, healthy term neonates (n = 31, mean postconception age 41.5 weeks ± 3.8 weeks) were compared with control children (n = 23, mean age 9.4 years ± 5.1 years) and young adults (n = 10, mean age 24.1 years ± 2.6 years). LCModel-based calculations compared metabolites within medial parietal gray matter (colocalizing to the PMC), posterior thalamus, and parietal white matter voxels. Common metabolic changes existed for neuronal-axonal maturation and structural markers in the PMC, thalamus, and parietal white matter with increasing NAA and glutamate and decreasing myoinositol and choline with age. Key differences in creatine and glucose metabolism were noted in the PMC, in contrast to the thalamic and parietal white matter locations, suggesting a unique role of energy metabolism. Significant parallel metabolite developmental changes of multiple other metabolites including aspartate, glutamine, and glutathione with age were present between PMC and parietal white matter but not between PMC and thalamus. These findings offer insight into the metabolic architecture of the interface between structural and functional topology of brain networks. Further investigation unifying metabolic changes with functional and anatomic pathways may further enhance the understanding of the PMC in posterior default mode network development.

Resting State fMRI in the moving fetus: a robust framework for motion, bias field and spin history correction

There is growing interest in exploring fetal functional brain development, particularly with Resting State fMRI. However, during a typical fMRI acquisition, the womb moves due to maternal respiration and the fetus may perform large-scale and unpredictable movements. Conventional fMRI processing pipelines, which assume that brain movements are infrequent or at least small, are not suitable. Previous published studies have tackled this problem by adopting conventional methods and discarding as much as 40% or more of the acquired data. In this work, we developed and tested a processing framework for fetal Resting State fMRI, capable of correcting gross motion. The method comprises bias field and spin history corrections in the scanner frame of reference, combined with slice to volume registration and scattered data interpolation to place all data into a consistent anatomical space. The aim is to recover an ordered set of samples suitable for further analysis using standard tools such as Group Independent Component Analysis (Group ICA). We have tested the approach using simulations and in vivo data acquired at 1.5 T. After full motion correction, Group ICA performed on a population of 8 fetuses extracted 20 networks, 6 of which were identified as matching those previously observed in preterm babies.

Prenatal cocaine effects on brain structure in early infancy

Prenatal cocaine exposure (PCE) is related to subtle deficits in cognitive and behavioral function in infancy, childhood and adolescence. Very little is known about the effects of in utero PCE on early brain development that may contribute to these impairments. The purpose of this study was to examine brain structural differences in infants with and without PCE. We conducted MRI scans of newborns (mean age = 5 weeks) to determine cocaine's impact on early brain structural development. Subjects were three groups of infants: 33 with PCE co-morbid with other drugs, 46 drug-free controls and 40 with prenatal exposure to other drugs (nicotine, alcohol, marijuana, opiates, SSRIs) but without cocaine. Infants with PCE exhibited lesser total gray matter (GM) volume and greater total cerebral spinal fluid (CSF) volume compared with controls and infants with non-cocaine drug exposure. Analysis of regional volumes revealed that whole brain GM differences were driven primarily by lesser GM in prefrontal and frontal brain regions in infants with PCE, while more posterior regions (parietal, occipital) did not differ across groups. Greater CSF volumes in PCE infants were present in prefrontal, frontal and parietal but not occipital regions. Greatest differences (GM reduction, CSF enlargement) in PCE infants were observed in dorsal prefrontal cortex. Results suggest that PCE is associated with structural deficits in neonatal cortical gray matter, specifically in prefrontal and frontal regions involved in executive function and inhibitory control. Longitudinal study is required to determine whether these early differences persist and contribute to deficits in cognitive functions and enhanced risk for drug abuse seen at school age and in later life.

Learning to remember: the early ontogeny of episodic memory

Over the past 60 years the neural correlates of human episodic memory have been the focus of intense neuroscientific scrutiny. By contrast, neuroscience has paid substantially less attention to understanding the emergence of this neurocognitive system. In this review we consider how the study of memory development has evolved. In doing so, we concentrate primarily on the first postnatal year because it is within this time window that the most dramatic shifts in scientific opinion have occurred. Moreover, this time frame includes the critical age (∼9 months) at which human infants purportedly first begin to demonstrate rudimentary hippocampal-dependent memory. We review the evidence for and against this assertion, note the lack of direct neurocognitive data speaking to this issue, and question how demonstrations of exuberant relational learning and memory in infants as young as 3-months old can be accommodated within extant models. Finally, we discuss whether current impasses in the infant memory literature could be leveraged by making greater use of neuroimaging techniques, such as magnetic resonance imaging (MRI), which have been deployed so successfully in adults.

Mapping longitudinal development of local cortical gyrification in infants from birth to 2 years of age

Human cortical folding is believed to correlate with cognitive functions. This likely correlation may have something to do with why abnormalities of cortical folding have been found in many neurodevelopmental disorders. However, little is known about how cortical gyrification, the cortical folding process, develops in the first 2 years of life, a period of dynamic and regionally heterogeneous cortex growth. In this article, we show how we developed a novel infant-specific method for mapping longitudinal development of local cortical gyrification in infants. By using this method, via 219 longitudinal 3T magnetic resonance imaging scans from 73 healthy infants, we systemically and quantitatively characterized for the first time the longitudinal cortical global gyrification index (GI) and local GI (LGI) development in the first 2 years of life. We found that the cortical GI had age-related and marked development, with 16.1% increase in the first year and 6.6% increase in the second year. We also found marked and regionally heterogeneous cortical LGI development in the first 2 years of life, with the high-growth regions located in the association cortex, whereas the low-growth regions located in sensorimotor, auditory, and visual cortices. Meanwhile, we also showed that LGI growth in most cortical regions was positively correlated with the brain volume growth, which is particularly significant in the prefrontal cortex in the first year. In addition, we observed gender differences in both cortical GIs and LGIs in the first 2 years, with the males having larger GIs than females at 2 years of age. This study provides valuable information on normal cortical folding development in infancy and early childhood.

Developing Attention: Behavioral and Brain Mechanisms

Brain networks underlying attention are present even during infancy and are critical for the developing ability of children to control their emotions and thoughts. For adults, individual differences in the efficiency of attentional networks have been related to neuromodulators and to genetic variations. We have examined the development of attentional networks and child temperament in a longitudinal study from infancy (7 months) to middle childhood (7 years). Early temperamental differences among infants, including smiling and laughter and vocal reactivity, are related to self-regulation abilities at 7 years. However, genetic variations related to adult executive attention, while present in childhood, are poor predictors of later control, in part because individual genetic variationmay have many small effects and in part because their influence occurs in interaction with caregiver behavior and other environmental influences. While brain areas involved in attention are present during infancy, their connectivity changes and leads to improvement in control of behavior. It is also possible to influence control mechanisms through training later in life. The relation between maturation and learning may allow advances in our understanding of human brain development.

Functional Network Development During the First Year: Relative Sequence and Socioeconomic Correlations

The first postnatal year is characterized by the most dramatic functional network development of the human lifespan. Yet, the relative sequence of the maturation of different networks and the impact of socioeconomic status (SES) on their development during this critical period remains poorly characterized. Leveraging a large, normally developing infant sample with multiple longitudinal resting-state functional magnetic resonance imaging scans during the first year (N = 65, scanned every 3 months), we aimed to delineate the relative maturation sequence of 9 key brain functional networks and examine their SES correlations. Our results revealed a maturation sequence from primary sensorimotor/auditory to visual to attention/default-mode, and finally to executive control networks. Network-specific critical growth periods were also identified. Finally, marginally significant positive SES-brain correlations were observed at 6 months of age for both the sensorimotor and default-mode networks, indicating interesting SES effects on functional brain maturation. To the best of our knowledge, this is the first study delineating detailed longitudinal growth trajectories of all major functional networks during the first year of life and their SES correlations. Insights from this study not only improve our understanding of early brain development, but may also inform the critical periods for SES expression during infancy.

Intrinsic functional brain architecture derived from graph theoretical analysis in the human fetus

The human brain undergoes dramatic maturational changes during late stages of fetal and early postnatal life. The importance of this period to the establishment of healthy neural connectivity is apparent in the high incidence of neural injury in preterm infants, in whom untimely exposure to ex-uterine factors interrupts neural connectivity. Though the relevance of this period to human neuroscience is apparent, little is known about functional neural networks in human fetal life. Here, we apply graph theoretical analysis to examine human fetal brain connectivity. Utilizing resting state functional magnetic resonance imaging (fMRI) data from 33 healthy human fetuses, 19 to 39 weeks gestational age (GA), our analyses reveal that the human fetal brain has modular organization and modules overlap functional systems observed postnatally. Age-related differences between younger (GA <31 weeks) and older (GA≥31 weeks) fetuses demonstrate that brain modularity decreases, and connectivity of the posterior cingulate to other brain networks becomes more negative, with advancing GA. By mimicking functional principles observed postnatally, these results support early emerging capacity for information processing in the human fetal brain. Current technical limitations, as well as the potential for fetal fMRI to one day produce major discoveries about fetal origins or antecedents of neural injury or disease are discussed.

Default mode network alterations during language task performance in children with benign epilepsy with centrotemporal spikes (BECTS)

Benign epilepsy with centrotemporal spikes (BECTS) is the most common idiopathic epileptic disorder in children. Besides reported cognitive deficits, functional alterations mostly in the reorganization of language areas have also been described. In several publications, it has been reported that activation of the default mode network (DMN) can be reduced or altered in different neuropsychiatric and neurological disorders in adults. Whether this also holds true for children with epilepsy has so far not been clarified. To determine the functional activation of the DMN in children with BECTS, 20 patients and 16 healthy controls were examined using functional magnetic resonance imaging (fMRI), while a sentence generation task and a reading task were applied in a block design manner. To study the default mode network and the functional alterations between groups, an independent component analysis (ICA) was computed and further analyzed using SPM5. Compared with controls, children with BECTS showed not only significantly less activation of the DMN during the rest condition but also less deactivation during cognitive effort. This was most apparent in the precuneus, a key region of the DMN, while subjects were generating sentences. From these findings, we hypothesize that children with BECTS show a functional deficit that is reflected by alterations in the DMN.

Eighteen-month-olds' ability to make gaze predictions following distraction or a long delay

The abilities to flexibly allocate attention, select between conflicting stimuli, and make anticipatory gaze movements are important for young children's exploration and learning about their environment. These abilities constitute voluntary control of attention and show marked improvements in the second year of a child's life. Here we investigate the effects of visual distraction and delay on 18-month-olds' ability to predict the location of an occluded target in an experiment that requires switching of attention, and compare their performance to that of adults. Our results demonstrate that by 18 months of age children can readily overcome a previously learned response, even under a condition that involves visual distraction, but have difficulties with correctly updating their prediction when presented with a longer time delay. Further, the experiment shows that, overall, the 18-month-olds' allocation of visual attention is similar to that of adults, the primary difference being that adults demonstrate a superior ability to maintain attention on task and update their predictions over a longer time period.

Development of Human Somatosensory Cortical Functions - What have We Learned from Magnetoencephalography: A Review

The mysteries of early development of cortical processing in humans have started to unravel with the help of new non-invasive brain research tools like multichannel magnetoencephalography (MEG). In this review, we evaluate, within a wider neuroscientific and clinical context, the value of MEG in studying normal and disturbed functional development of the human somatosensory system. The combination of excellent temporal resolution and good localization accuracy provided by MEG has, in the case of somatosensory studies, enabled the differentiation of activation patterns from the newborn’s primary (SI) and secondary somatosensory (SII) areas. Furthermore, MEG has shown that the functioning of both SI and SII in newborns has particular immature features in comparison with adults. In extremely preterm infants, the neonatal MEG response from SII also seems to potentially predict developmental outcome: those lacking SII responses at term show worse motor performance at age 2 years than those with normal SII responses at term. In older children with unilateral early brain lesions, bilateral alterations in somatosensory cortical activation detected in MEG imply that the impact of a localized insult may have an unexpectedly wide effect on cortical somatosensory networks. The achievements over the last decade show that MEG provides a unique approach for studying the development of the somatosensory system and its disturbances in childhood. MEG well complements other neuroimaging methods in studies of cortical processes in the developing brain.

Strengthening connections: functional connectivity and brain plasticity

The ascendancy of functional neuroimaging has facilitated the addition of network-based approaches to the neuropsychologist's toolbox for evaluating the sequelae of brain insult. In particular, intrinsic functional connectivity (iFC) mapping of resting state fMRI (R-fMRI) data constitutes an ideal approach to measuring macro-scale networks in the human brain. Beyond the value of iFC mapping for charting how the functional topography of the brain is altered by insult and injury, iFC analyses can provide insights into experience-dependent plasticity at the macro level of large-scale functional networks. Such insights are foundational to the design of training and remediation interventions that will best facilitate recovery of function. In this review, we consider what is currently known about the origin and function of iFC in the brain, and how this knowledge is informative in neuropsychological settings. We then summarize studies that have examined experience-driven plasticity of iFC in healthy control participants, and frame these findings in terms of a schema that may aid in the interpretation of results and the generation of hypotheses for rehabilitative studies. Finally, we outline some caveats to the R-fMRI approach, as well as some current developments that are likely to bolster the utility of the iFC paradigm for neuropsychology.

The entropic brain: a theory of conscious states informed by neuroimaging research with psychedelic drugs

Entropy is a dimensionless quantity that is used for measuring uncertainty about the state of a system but it can also imply physical qualities, where high entropy is synonymous with high disorder. Entropy is applied here in the context of states of consciousness and their associated neurodynamics, with a particular focus on the psychedelic state. The psychedelic state is considered an exemplar of a primitive or primary state of consciousness that preceded the development of modern, adult, human, normal waking consciousness. Based on neuroimaging data with psilocybin, a classic psychedelic drug, it is argued that the defining feature of "primary states" is elevated entropy in certain aspects of brain function, such as the repertoire of functional connectivity motifs that form and fragment across time. Indeed, since there is a greater repertoire of connectivity motifs in the psychedelic state than in normal waking consciousness, this implies that primary states may exhibit "criticality," i.e., the property of being poised at a "critical" point in a transition zone between order and disorder where certain phenomena such as power-law scaling appear. Moreover, if primary states are critical, then this suggests that entropy is suppressed in normal waking consciousness, meaning that the brain operates just below criticality. It is argued that this entropy suppression furnishes normal waking consciousness with a constrained quality and associated metacognitive functions, including reality-testing and self-awareness. It is also proposed that entry into primary states depends on a collapse of the normally highly organized activity within the default-mode network (DMN) and a decoupling between the DMN and the medial temporal lobes (which are normally significantly coupled). These hypotheses can be tested by examining brain activity and associated cognition in other candidate primary states such as rapid eye movement (REM) sleep and early psychosis and comparing these with non-primary states such as normal waking consciousness and the anaesthetized state.

Reprint of: Mapping connectivity in the developing brain

Recently, there has been a wealth of research into structural and functional brain connectivity, and how they change over development. While we are far from a complete understanding, these studies have yielded important insights into human brain development. There is an ever growing variety of methods for assessing connectivity, each with its own advantages. Here we review research on the development of structural and/or functional brain connectivity in both typically developing subjects and subjects with neurodevelopmental disorders. Space limitations preclude an exhaustive review of brain connectivity across all developmental disorders, so we review a representative selection of recent findings on brain connectivity in autism, Fragile X, 22q11.2 deletion syndrome, Williams syndrome, Turner syndrome, and ADHD. Major strides have been made in understanding the developmental trajectory of the human connectome, offering insight into characteristic features of brain development and biological processes involved in developmental brain disorders. We also discuss some common themes, including hemispheric specialization - or asymmetry - and sex differences. We conclude by discussing some promising future directions in connectomics, including the merger of imaging and genetics, and a deeper investigation of the relationships between structural and functional connectivity.

Development of human brain cortical network architecture during infancy

The brain's mature functional network architecture has been extensively studied but the early emergence of the brain's network organization remains largely unknown. In this study, leveraging a large sample (143 subjects) with longitudinal rsfMRI scans (333 datasets), we aimed to characterize the important developmental process of the brain's functional network architecture during the first 2 years of life. Based on spatial independent component analysis and longitudinal linear mixed effect modeling, our results unveiled the detailed topology and growth trajectories of nine cortical functional networks. Within networks, our findings clearly separated the brains networks into two categories: primary networks were topologically adult-like in neonates while higher-order networks were topologically incomplete and isolated in neonates but demonstrated consistent synchronization during the first 2 years of life (connectivity increases 0.13-0.35). Between networks, our results demonstrated both network-level connectivity decreases (-0.02 to -0.64) and increases (0.05-0.18) but decreasing connections (n = 14) dominated increasing ones (n = 5). Finally, significant sex differences were observed with boys demonstrating faster network-level connectivity increases among the two frontoparietal networks (growth rate was 1.63e-4 per day for girls and 2.69e-4 per day for boys, p < 1e-4). Overall, our study delineated the development of the whole brain functional architecture during the first 2 years of life featuring significant changes of both within- and between-network interactions.

Resting-state functional connectivity MRI reveals active processes central to cognition

Analysis of spontaneously correlated low-frequency activity fluctuations across the brain using functional magnetic resonance imaging (MRI)-commonly referred to as resting-state functional connectivity (RSFC) MRI-was initially seen as a useful tool for mapping functional-anatomic networks in the living human brain, characterizing brain changes and differences in clinical populations, and studying comparative anatomy across species. However, little was known about the potential relevance of RSFC to cognitive processes. Indeed, there has been considerable controversy and debate as to the utility of studying the resting-state in cognitive neuroscience. However, recent work has shown that RSFC, rather than merely reflecting passive or epiphenomenal activity within underlying functional-anatomic networks, reveals important dynamic processes that play an active role in cognition. RSFC has been associated with individual differences in a number of behavioral and cognitive domains, including perception, language, learning and memory, and the organization of conceptual knowledge. In this article, we review and integrate the latest research demonstrating that RSFC is functionally relevant to human behavior and higher-level cognition, and propose a hypothesis regarding its mechanism of action on functional network dynamics and cognition. We conclude that RSFC MRI will be an invaluable tool for future discovery of the fundamental neurocognitive interactions that underlie cognition. WIREs Cogn Sci 2014, 5:233-245. doi: 10.1002/wcs.1275 CONFLICT OF INTEREST: The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.

Reduced brain resting-state network specificity in infants compared with adults

PURPOSE

Infant resting-state networks do not exhibit the same connectivity patterns as those of young children and adults. Current theories of brain development emphasize developmental progression in regional and network specialization. We compared infant and adult functional connectivity, predicting that infants would exhibit less regional specificity and greater internetwork communication compared with adults.

PATIENTS AND METHODS

Functional magnetic resonance imaging at rest was acquired in 12 healthy, term infants and 17 adults. Resting-state networks were extracted, using independent components analysis, and the resulting components were then compared between the adult and infant groups.

RESULTS

Adults exhibited stronger connectivity in the posterior cingulate cortex node of the default mode network, but infants had higher connectivity in medial prefrontal cortex/anterior cingulate cortex than adults. Adult connectivity was typically higher than infant connectivity within structures previously associated with the various networks, whereas infant connectivity was frequently higher outside of these structures. Internetwork communication was significantly higher in infants than in adults.

CONCLUSION

We interpret these findings as consistent with evidence suggesting that resting-state network development is associated with increasing spatial specificity, possibly reflecting the corresponding functional specialization of regions and their interconnections through experience.

Measuring the dynamic longitudinal cortex development in infants by reconstruction of temporally consistent cortical surfaces

Quantitative measurement of the dynamic longitudinal cortex development during early postnatal stages is of great importance to understand the early cortical structural and functional development. Conventional methods usually reconstruct the cortical surfaces of longitudinal images from the same subject independently, which often generate longitudinally-inconsistent cortical surfaces and thus lead to inaccurate measurement of cortical changes, especially for vertex-wise mapping of cortical development. This paper aims to address this problem by presenting a method to reconstruct temporally-consistent cortical surfaces from longitudinal infant brain MR images, for accurate and consistent measurement of the dynamic cortex development in infants. Specifically, the longitudinal development of the inner cortical surface is first modeled by a deformable growth sheet with elasto-plasticity property to establish longitudinally smooth correspondences of the inner cortical surfaces. Then, the modeled longitudinal inner cortical surfaces are jointly deformed to locate both inner and outer cortical surfaces with a spatial-temporal deformable surface method. The method has been applied to 13 healthy infants, each with 6 serial MR scans acquired at 2 weeks, 3 months, 6 months, 9 months, 12 months and 18 months of age. Experimental results showed that our method with the incorporated longitudinal constraints can reconstruct the longitudinally-dynamic cortical surfaces from serial infant MR images more consistently and accurately than the previously published methods. By using our method, for the first time, we can characterize the vertex-wise longitudinal cortical thickness development trajectory at multiple time points in the first 18 months of life. Specifically, we found the highly age-related and regionally-heterogeneous developmental trajectories of the cortical thickness during this period, with the cortical thickness increased most from 3 to 6 months (16.2%) and least from 9 to 12 months (less than 0.1%). Specifically, the central sulcus only underwent significant increase of cortical thickness from 6 to 9 months and the occipital cortex underwent significant increase from 0 to 9 months, while the frontal, temporal and parietal cortices grew continuously in this first 18 months of life. The adult-like spatial patterns of cortical thickness were generally present at 18 months of age. These results provided detailed insights into the dynamic trajectory of the cortical thickness development in infants.

Development of human brain structural networks through infancy and childhood

During human brain development through infancy and childhood, microstructural and macrostructural changes take place to reshape the brain's structural networks and better adapt them to sophisticated functional and cognitive requirements. However, structural topological configuration of the human brain during this specific development period is not well understood. In this study, diffusion magnetic resonance image (dMRI) of 25 neonates, 13 toddlers, and 25 preadolescents were acquired to characterize network dynamics at these 3 landmark cross-sectional ages during early childhood. dMRI tractography was used to construct human brain structural networks, and the underlying topological properties were quantified by graph-theory approaches. Modular organization and small-world attributes are evident at birth with several important topological metrics increasing monotonically during development. Most significant increases of regional nodes occur in the posterior cingulate cortex, which plays a pivotal role in the functional default mode network. Positive correlations exist between nodal efficiencies and fractional anisotropy of the white matter traced from these nodes, while correlation slopes vary among the brain regions. These results reveal substantial topological reorganization of human brain structural networks through infancy and childhood, which is likely to be the outcome of both heterogeneous strengthening of the major white matter tracts and pruning of other axonal fibers.

Functional brain imaging across development

The developmental cognitive neuroscience literature has grown exponentially over the last decade. This paper reviews the functional magnetic resonance imaging (fMRI) literature on brain function development of typically late developing functions of cognitive and motivation control, timing and attention as well as of resting state neural networks. Evidence shows that between childhood and adulthood, concomitant with cognitive maturation, there is progressively increased functional activation in task-relevant lateral and medial frontal, striatal and parieto-temporal brain regions that mediate these higher level control functions. This is accompanied by progressively stronger functional inter-regional connectivity within task-relevant fronto-striatal and fronto-parieto-temporal networks. Negative age associations are observed in earlier developing posterior and limbic regions, suggesting a shift with age from the recruitment of "bottom-up" processing regions towards "top-down" fronto-cortical and fronto-subcortical connections, leading to a more mature, supervised cognition. The resting state fMRI literature further complements this evidence by showing progressively stronger deactivation with age in anti-correlated task-negative resting state networks, which is associated with better task performance. Furthermore, connectivity analyses during the resting state show that with development increasingly stronger long-range connections are being formed, for example, between fronto-parietal and fronto-cerebellar connections, in both task-positive networks and in task-negative default mode networks, together with progressively lesser short-range connections, suggesting progressive functional integration and segregation with age. Overall, evidence suggests that throughout development between childhood and adulthood, there is progressive refinement and integration of both task-positive fronto-cortical and fronto-subcortical activation and task-negative deactivation, leading to a more mature and controlled cognition.

Consistent anterior-posterior segregation of the insula during the first 2 years of life

The human insula is a complex region characterized by heterogeneous cytoarchitecture, connectivity, and function. Subregional parcellation of the insula in adults has revealed an interesting anterior-posterior subdivision pattern that is highly consistent with its functional differentiation. However, the development of the insula's subregional segregation during the first 2 years of life remains unknown. The aim of this study was to test the hypothesis that similar segregation of the insula exists during this critical time period based on the resting-state functional magnetic resonance imaging study of a large cohort of infants (n = 143) with longitudinal scans. Our results confirmed a consistent anterior-posterior subdivision of the insula during the first 2 years of life with dissociable connectivity patterns associated with each cluster. Specifically, the anterior insula coupled more with frontal association areas, whereas the posterior insula integrated more with sensorimotor-related regions. More importantly, dramatic development of each subregion's functional network was observed, providing important neuronal correlates for the rapid advancement of its related functions during this time period.

Selective development of anticorrelated networks in the intrinsic functional organization of the human brain

We examined the normal development of intrinsic functional connectivity of the default network (brain regions typically deactivated for attention-demanding tasks) as measured by resting-state fMRI in children, adolescents, and young adults ages 8-24 years. We investigated both positive and negative correlations and employed analysis methods that allowed for valid interpretation of negative correlations and that also minimized the influence of motion artifacts that are often confounds in developmental neuroimaging. As age increased, there were robust developmental increases in negative correlations, including those between medial pFC (MPFC) and dorsolateral pFC (DLPFC) and between lateral parietal cortices and brain regions associated with the dorsal attention network. Between multiple regions, these correlations reversed from being positive in children to negative in adults. Age-related changes in positive correlations within the default network were below statistical threshold after controlling for motion. Given evidence in adults that greater negative correlation between MPFC and DLPFC is associated with superior cognitive performance, the development of an intrinsic anticorrelation between MPFC and DLPFC may be a marker of the large growth of working memory and executive functions that occurs from childhood to young adulthood.

Mapping connectivity in the developing brain

Recently, there has been a wealth of research into structural and functional brain connectivity, and how they change over development. While we are far from a complete understanding, these studies have yielded important insights into human brain development. There is an ever growing variety of methods for assessing connectivity, each with its own advantages. Here we review research on the development of structural and/or functional brain connectivity in both typically developing subjects and subjects with neurodevelopmental disorders. Space limitations preclude an exhaustive review of brain connectivity across all developmental disorders, so we review a representative selection of recent findings on brain connectivity in autism, Fragile X, 22q11.2 deletion syndrome, Williams syndrome, Turner syndrome, and ADHD. Major strides have been made in understanding the developmental trajectory of the human connectome, offering insight into characteristic features of brain development and biological processes involved in developmental brain disorders. We also discuss some common themes, including hemispheric specialization - or asymmetry - and sex differences. We conclude by discussing some promising future directions in connectomics, including the merger of imaging and genetics, and a deeper investigation of the relationships between structural and functional connectivity.

Clinical applications of the functional connectome

Central to the development of clinical applications of functional connectomics for neurology and psychiatry is the discovery and validation of biomarkers. Resting state fMRI (R-fMRI) is emerging as a mainstream approach for imaging-based biomarker identification, detecting variations in the functional connectome that can be attributed to clinical variables (e.g., diagnostic status). Despite growing enthusiasm, many challenges remain. Here, we assess evidence of the readiness of R-fMRI based functional connectomics to lead to clinically meaningful biomarker identification through the lens of the criteria used to evaluate clinical tests (i.e., validity, reliability, sensitivity, specificity, and applicability). We focus on current R-fMRI-based prediction efforts, and survey R-fMRI used for neurosurgical planning. We identify gaps and needs for R-fMRI-based biomarker identification, highlighting the potential of emerging conceptual, analytical and cultural innovations (e.g., the Research Domain Criteria Project (RDoC), open science initiatives, and Big Data) to address them. Additionally, we note the need to expand future efforts beyond identification of biomarkers for disease status alone to include clinical variables related to risk, expected treatment response and prognosis.

On development of functional brain connectivity in the young brain

Our brain is a complex network of structurally and functionally interconnected regions, shaped to efficiently process and integrate information. The development from a brain equipped with basic functionalities to an efficient network facilitating complex behavior starts during gestation and continues into adulthood. Resting-state functional MRI (rs-fMRI) enables the examination of developmental aspects of functional connectivity (FC) and functional brain networks. This review will discuss changes observed in the developing brain on the level of network FC from a gestational age of 20 weeks onwards. We discuss findings of resting-state fMRI studies showing that functional network development starts during gestation, creating a foundation for each of the resting-state networks (RSNs) to be established. Visual and sensorimotor areas are reported to develop first, with other networks, at different rates, increasing both in network connectivity and size over time. Reaching childhood, marked fine-tuning and specialization takes place in the regions necessary for higher-order cognitive functions.

Developing self-regulation in early childhood

Studies using fMRI at rest and during task performance have revealed a set of brain areas and their connections that can be linked to the ability of children to regulate their thoughts, actions and emotions. Higher self-regulation has also been related favorable outcomes in adulthood. These findings have set the occasion for methods of improving self-regulation via training. A tool kit of such methods is now available. It remains to be seen if educators will use these new findings and tools to forge practical methods for improving the lives of the world's children.

Functional connectivity in the developing brain: a longitudinal study from 4 to 9months of age

We characterize the development of intrinsic connectivity networks (ICNs) from 4 to 9months of age with resting state magnetic resonance imaging performed on sleeping infants without sedative medication. Data is analyzed with independent component analysis (ICA). Using both low (30 components) and high (100 components) ICA model order decompositions, we find that the functional network connectivity (FNC) map is largely similar at both 4 and 9months. However at 9months the connectivity strength decreases within local networks and increases between more distant networks. The connectivity within the default-mode network, which contains both local and more distant nodes, also increases in strength with age. The low frequency power spectrum increases with age only in the posterior cingulate cortex and posterior default mode network. These findings are consistent with a general developmental pattern of increasing longer distance functional connectivity over the first year of life and raise questions regarding the developmental importance of the posterior cingulate at this age.

Neuroimaging, a new tool for investigating the effects of early diet on cognitive and brain development

Nutrition is crucial to the initial development of the central nervous system (CNS), and then to its maintenance, because both depend on dietary intake to supply the elements required to develop and fuel the system. Diet in early life is often seen in the context of "programming" where a stimulus occurring during a vulnerable period can have long-lasting or even lifetime effects on some aspect of the organism's structure or function. Nutrition was first shown to be a programming stimulus for growth, and then for cognitive behavior, in animal studies that were able to employ methods that allowed the demonstration of neural effects of early nutrition. Such research raised the question of whether nutrition could also programme cognition/brain structure in humans. Initial studies of cognitive effects were observational, usually conducted in developing countries where the presence of confounding factors made it difficult to interpret the role of nutrition in the cognitive deficits that were seen. Attributing causality to nutrition required randomized controlled trials (RCTs) and these, often in developed countries, started to appear around 30 years ago. Most demonstrated convincingly that early nutrition could affect subsequent cognition. Until the advent of neuroimaging techniques that allowed in vivo examination of the brain, however, we could determine very little about the neural effects of early diet in humans. The combination of well-designed trials with neuroimaging tools means that we are now able to pose and answer questions that would have seemed impossible only recently. This review discusses various neuroimaging methods that are suitable for use in nutrition studies, while pointing out some of the limitations that they may have. The existing literature is small, but examples of studies that have used these methods are presented. Finally, some considerations that have arisen from previous studies, as well as suggestions for future research, are discussed.

The dynamic reorganization of the default-mode network during a visual classification task

The default-mode network has been reported to possess highly versatile and even contrasting functions but the underlying functioning mechanism remains elusive. In this study, we adopt a dynamic view of the default-mode network structure and hypothesize that it could potentially contribute to different functions through dynamic reorganization of its functional interaction pattern within and across network boundaries depending on the ongoing cognitive demands. With four experimental states and functional connectivity magnetic resonance imaging, we show that the default-mode network is characterized by within-network desynchronization and outside-network integration during the transition from resting state to an external visual classification task. Such default-mode network dynamics are task demand-dependent and return to their original status during the transition back to resting. More importantly, the degree of within-network desynchronization correlates with reaction time while the level of outside-network integration indexes task performance accuracy. Overall, the documented dynamic reorganization of the default-mode network and the significant behavioral correlations provide new insights into our understanding of this complex network and emphasize a dynamic view in future studies of its functioning mechanism.