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

Early microstructure of white matter associated with infant attention

Early infancy is characterized by rapid brain development that occurs alongside, and in response to, the development of cognitive and behavioral functions, including attention. Infants' ability to orient and sustain attention to stimuli develops in concert with refinement of the orienting network in frontoparietal regions of the brain. Infants (n = 97) underwent magnetic resonance imaging at one-month of age and data were fit to a diffusion tensor imaging model to calculate fractional anisotropy (FA) and radial diffusivity (RD), as well as to a neurite orientation dispersion and density imaging model to calculate intracellular volume fraction (νic). Infant attention was assessed at six months of age using a dynamic puppet task (Cuevas and Bell, 2014). Infants with higher FA in the corpus callosum and anterior cingulum showed increased orienting behaviors. Our findings indicate that increased microstructure of the white matter tracts in the orienting network may play a role in the early neurodevelopment of attentional orienting behaviors.

Developing attention in typical children related to disabilities

We define attention by three basic functions. The first is obtaining and maintaining the alert state. The second is orienting overtly or covertly to sensory stimuli. The third is selection among competing responses. These three functions correspond to three separable brain networks. Control of the alert state develops in infancy but continues to change till adulthood. During childhood, the orienting network provides a means of controlling affective responses, e.g., by looking away from negative events and toward positive or novel events. The executive network mediates between competing voluntary responses by resolving conflicts. Executive control improves rapidly over the first 7 years of life. Autistic spectrum disorders and attention deficit hyperactivity disorder are two disorders that have been shown to involve deficits in attention networks. We examine connections between developing attention networks and these disorders.

The Subgrouping Structure of Newborns with Heterogenous Brain-Behavior Relationships

The presence of heterogeneity/subgroups in infants and older populations against single-domain brain or behavioral measures has been previously characterized. However, few attempts have been made to explore heterogeneity at the brain-behavior relationship level. Such a hypothesis posits that different subgroups of infants may possess qualitatively different brain-behavior relationships that could ultimately contribute to divergent developmental outcomes even with relatively similar brain phenotypes. In this study, we aimed to explore such relationship-level heterogeneity and delineate the subgrouping structure of newborns with differential brain-behavior associations based on a typically developing sample of 81 infants with 3-week resting-state functional magnetic resonance imaging scans and 4-year intelligence quotient (IQ) measures. Our results not only confirmed the existence of relationship-level heterogeneity in newborns but also revealed divergent developmental outcomes associated with two subgroups showing similar brain functional connectivity but contrasting brain-behavior relationships. Importantly, further analyses unveiled an intriguing pattern that the subgroup with higher 4-year IQ outcomes possessed brain-behavior relationships that were congruent to their functional connectivity pattern in neonates while the subgroup with lower 4-year IQ not, providing potential explanations for the observed IQ differences. The characterization of heterogeneity at the brain-behavior relationship level may not only improve our understanding of the patterned intersubject variability during infancy but could also pave the way for future development of heterogeneity-inspired, personalized, subgroup-specific models for better prediction.

The longitudinal associations between temperament and sleep during the first year of life

Temperament and sleep in infants are related but also distinct concepts. The longitudinal effects of temperament on sleep in infancy remain unclear, although this information is potentially important for the prevention and treatment of early sleep problems. We examined how various temperament features influence sleep development during the first year of life in a large birth cohort. This study comprised mother-infant dyads with complete longitudinal data on sleep, temperament and sociodemographic measurements at six and 12 months (N = 1436). We observed that higher infant Negative Affectivity was related to several sleep problems, and that many subscales of Negative Affectivity and Orienting/Regulation predicted worse sleep and deterioration in sleep problems from six to 12 months. Few associations between Surgency and sleep were found. Our findings highlight especially Negative Affectivity as a risk factor for persistent and increasing sleep problems, and also the specific importance of the fine-grained aspects of temperament in predicting infant sleep development.

Functional neural network configuration in late childhood varies by age and cognitive state

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fMRI data from 60 children aged 9–12 during resting and tasks involving decision making, visual perception, and working memory were examined.

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At rest, the child brain exhibited network organization similar to adults though the degree of similarity was age- and network-dependent.

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During tasks, brain network configurations showed task-induced and age-related changes in integration.

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Frontoparietal network showed flexible connectivity pattern across states while networks for sensory and motor processing remained stable.

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Findings demonstrate that network connectivity characteristics may serve as markers for neural and cognitive maturation.

Late childhood and early adolescence is characterized by substantial brain maturation which contributes to both adult-like and age-dependent resting-state network connectivity patterns. However, it remains unclear whether these functional network characteristics in children are subject to differential modulation by distinct cognitive demands as previously found in adults. We conducted network analyses on fMRI data from 60 children (aged 9–12) during resting and during three distinct tasks involving decision making, visual perception, and spatial working memory. Graph measures of network architecture, functional integration, and flexibility were calculated for each of the four states. During resting state, the children’s network architecture was similar to that in young adults (N = 60, aged 20–23) but the degree of similarity was age- and network-dependent. During the task states, the children's whole-brain network exhibited enhanced integration in response to increased cognitive demand. Additionally, the frontoparietal network showed flexibility in connectivity patterns across states while networks implicated in motor and visual processing remained relatively stable. Exploratory analyses suggest different relationships between behavioral performance and connectivity profiles for the working memory and perceptual tasks. Together, our findings demonstrate state- and age-dependent features in functional network connectivity during late childhood, potentially providing markers for brain and cognitive development.

The emergence of a functionally flexible brain during early infancy

While adult brains are known to be functionally flexible, the emergence of a functionally flexible brain during early infancy is largely uncharted due the lack of approaches to assess neural flexibility in infants. Using recent advances of multilayer network approaches and a cohort of typically developing children who underwent longitudinal MRI during the first 2 y of life, we investigated the developmental characteristics of brain neural flexibility. The temporal and spatial emergence of a functionally flexible brain was revealed. Brain regions with high neural flexibility appear consistent with the core regions supporting cognitive flexibility processing in adults, whereas brain regions governing basic brain functions exhibit lower neural flexibility, demonstrating the emergence of functionally flexible brain during early infancy.

Adult brains are functionally flexible, a unique characteristic that is thought to contribute to cognitive flexibility. While tools to assess cognitive flexibility during early infancy are lacking, we aimed to assess the spatiotemporal developmental features of “neural flexibility” during the first 2 y of life. Fifty-two typically developing children 0 to 2 y old were longitudinally imaged up to seven times during natural sleep using resting-state functional MRI. Using a sliding window approach, MR-derived neural flexibility, a quantitative measure of the frequency at which brain regions change their allegiance from one functional module to another during a given time period, was used to evaluate the temporal emergence of neural flexibility during early infancy. Results showed that neural flexibility of whole brain, motor, and high-order brain functional networks/regions increased significantly with age, while visual regions exhibited a temporally stable pattern, suggesting spatially and temporally nonuniform developmental features of neural flexibility. Additionally, the neural flexibility of the primary visual network at 3 mo of age was significantly and negatively associated with cognitive ability evaluated at 5/6 y of age. The “flexible club,” comprising brain regions with neural flexibility significantly higher than whole-brain neural flexibility, were consistent with brain regions known to govern cognitive flexibility in adults and exhibited unique characteristics when compared to the functional hub and diverse club regions. Thus, MR-derived neural flexibility has the potential to reveal the underlying neural substrates for developing a cognitively flexible brain during early infancy.

Regularized-Ncut: Robust and homogeneous functional parcellation of neonate and adult brain networks

Brain network parcellation based on resting-state functional MRI (rs-fMRI) is affected by noise, resulting in spurious small patches and decreased functional homogeneity within each network. Obtaining robust and homogeneous parcellation of neonate brain is more difficult, because neonate rs-fMRI is associated with relatively higher level of noise and no prior knowledge from a functional neonate atlas is available as spatial constraints. To meet these challenges, we developed a novel data-driven Regularized Normalized-cut (RNcut) method. RNcut is formulated by adding two regularization terms, a smoothing term using Markov random fields and a small-patch removal term, to conventional normalized-cut (Ncut) method. The RNcut and competing methods were tested with simulated datasets with known ground truth and then applied to both adult and neonate rs-fMRI datasets. Based on the parcellated networks generated by RNcut, intra-network connectivity was quantified. The test results from simulated datasets demonstrated that the RNcut method is more robust (p < 0.01) to noise and can delineate parcellated functional networks with significantly better (p < 0.01) spatial contiguity and significantly higher (p < 0.01) functional homogeneity than competing methods. Application of RNcut to neonate and adult rs-fMRI dataset revealed distinctive functional brain organization of neonate brains from that of adult brains. Collectively, we developed a novel data-driven RNcut method by integrating conventional Ncut with two regularization terms, generating robust and homogeneous functional parcellation without imposing spatial constraints. A broad range of brain network applications and analyses, especially neonate and infant brain parcellation with noisy and large sample of datasets, can potentially benefit from this RNcut method.

Development of Brain Networks In Utero: Relevance for Common Neural Disorders

Magnetic resonance imaging, histological, and gene analysis approaches in living and nonliving human fetuses and in prematurely born neonates have provided insight into the staged processes of prenatal brain development. Increased understanding of micro- and macroscale brain network development before birth has spurred interest in understanding the relevance of prenatal brain development to common neurological diseases. Questions abound as to the sensitivity of the intrauterine brain to environmental programming, to windows of plasticity, and to the prenatal origin of disorders of childhood that involve disruptions in large-scale network connectivity. Much of the available literature on human prenatal neural development comes from cross-sectional or case studies that are not able to resolve the longitudinal consequences of individual variation in brain development before birth. This review will 1) detail specific methodologies for studying the human prenatal brain, 2) summarize large-scale human prenatal neural network development, integrating findings from across a variety of experimental approaches, 3) explore the plasticity of the early developing brain as well as potential sex differences in prenatal susceptibility, and 4) evaluate opportunities to link specific prenatal brain developmental processes to the forms of aberrant neural connectivity that underlie common neurological disorders of childhood.

Autism Spectrum Disorders: Multiple Routes to, and Multiple Consequences of, Abnormal Synaptic Function and Connectivity

Autism spectrum disorders (ASDs) are a heterogeneous group of neurodevelopmental disorders of genetic and environmental etiologies. Some ASD cases are syndromic: associated with clinically defined patterns of somatic abnormalities and a neurobehavioral phenotype (e.g., Fragile X syndrome). Many cases, however, are idiopathic or non-syndromic. Such disorders present themselves during the early postnatal period when language, speech, and personality start to develop. ASDs manifest by deficits in social communication and interaction, restricted and repetitive patterns of behavior across multiple contexts, sensory abnormalities across multiple modalities and comorbidities, such as epilepsy among many others. ASDs are disorders of connectivity, as synaptic dysfunction is common to both syndromic and idiopathic forms. While multiple theories have been proposed, particularly in idiopathic ASDs, none address why certain brain areas (e.g., frontotemporal) appear more vulnerable than others or identify factors that may affect phenotypic specificity. In this hypothesis article, we identify possible routes leading to, and the consequences of, altered connectivity and review the evidence of central and peripheral synaptic dysfunction in ASDs. We postulate that phenotypic specificity could arise from aberrant experience-dependent plasticity mechanisms in frontal brain areas and peripheral sensory networks and propose why the vulnerability of these areas could be part of a model to unify preexisting pathophysiological theories.

Does the child brain rest?: An examination and interpretation of resting cognition in developmental cognitive neuroscience

In cognitive neuroscience, measurements of "resting baseline" are often considered stable across age and used as a reference point against which to judge cognitive state. The task-based approach-comparing resting baseline to task conditions-implies that resting baseline is an equalizer across participants and-in the case of studies of developmental changes in cognition-across age groups. In contrast, network neuroscience explicitly examines the development of "resting state" networks across age, at odds with the idea of a consistent resting baseline. Little attention has been paid to how cognition during rest may shift across development, particularly in children under the age of eight. Childhood is marked by striking maturation of neural systems, including a protracted developmental period for cognitive control systems. To grow and shape these cognitive systems, children have a developmental imperative to engage their neural circuitry at every possible opportunity. Thus, periods of "rest" without specific instructions may require additional control for children as they fight against developmental expectation to move, speak, or otherwise engage. We therefore theorize that the child brain does not rest in a manner consistent with the adult brain as longer rest periods may represent increased cognitive control. To shape this theory, we first review the extant literature on neurodevelopment across early childhood within the context of cognitive development. Next, we present nascent evidence for a destabilized baseline for comparisons across age. Finally, we present recommendations for designing, analyzing, and interpreting tasks conducted with young children as well as for resting state. Future work must aim to tease apart the cognitive context under which we examine functional brain development in young children and take considerations into account unique to each age.

Resting-state abnormalities of posterior cingulate in autism spectrum disorder

The posterior cingulate cortex (PCC) plays pivotal roles in cognitive, social and emotional processing, as well as early neural development that supports complex interactions among different neural networks. Alterations in its local and long-range connectivity during resting state are often implicated in neuropathology of neurodevelopmental disorders such as autism spectrum disorder (ASD). ASD is characterized by social and communication deficits, as well as restricted and repetitive behaviors and interests. Individuals with ASD demonstrate persistent disturbances in cognitive and social-emotional functioning, and their PCC exhibits both local and long-range resting state abnormalities compared to typically developing healthy controls. In terms of regional metrics, only the dorsal part of the PCC showed local underconnectivity. As to long-range connectivity measures, the most replicated finding in ASD studies is the reduced functional coupling between the PCC and medial prefrontal cortex (MPFC), which may represent a core neuropathology of ASD unrelated to medication effects. Functional importance of these resting state abnormalities to ASD and directions of future study are discussed at the end of this chapter.

Resting-state networks of the neonate brain identified using independent component analysis

Resting-state functional magnetic resonance imaging (rs-fMRI) has been successfully used to probe the intrinsic functional organization of the brain and to study brain development. Here, we implemented a combination of individual and group independent component analysis (ICA) of FSL on a 6-min resting-state data set acquired from 21 naturally sleeping term-born (age 26 ± 6.7 d), healthy neonates to investigate the emerging functional resting-state networks (RSNs). In line with the previous literature, we found evidence of sensorimotor, auditory/language, visual, cerebellar, thalmic, parietal, prefrontal, anterior cingulate as well as dorsal and ventral aspects of the default-mode-network. Additionally, we identified RSNs in frontal, parietal, and temporal regions that have not been previously described in this age group and correspond to the canonical RSNs established in adults. Importantly, we found that careful ICA-based denoising of fMRI data increased the number of networks identified with group-ICA, whereas the degree of spatial smoothing did not change the number of identified networks. Our results show that the infant brain has an established set of RSNs soon after birth.

The developmental trajectory of fronto-temporoparietal connectivity as a proxy of the default mode network: a longitudinal fNIRS investigation

The default mode network (DMN) is a network of brain regions that is activated while we are not engaged in any particular task. While there is a large volume of research documenting functional connectivity within the DMN in adults, knowledge of the development of this network is still limited. There is some evidence for a gradual increase in the functional connections within the DMN during the first 2 years of life, in contrast to other functional resting‐state networks that support primary sensorimotor functions, which are online from very early in life. Previous studies that investigated the development of the DMN acquired data from sleeping infants using fMRI. However, sleep stages are known to affect functional connectivity. In the current longitudinal study, fNIRS was used to measure spontaneous fluctuations in connectivity within fronto‐temporoparietal areas—as a proxy for the DMN—in awake participants every 6 months from 11 months till 36 months. This study validates a method for recording resting‐state data from awake infants, and presents a data analysis pipeline for the investigation of functional connections with infant fNIRS data, which will be beneficial for researchers in this field. A gradual development of fronto‐temporoparietal connectivity was found, supporting the idea that the DMN develops over the first years of life. Functional connectivity reached its maximum peak at about 24 months, which is consistent with previous findings showing that, by 2 years of age, DMN connectivity is similar to that observed in adults.

Multiscale Structure-Function Gradients in the Neonatal Connectome

The adult functional connectome is well characterized by a macroscale spatial gradient of connectivity traversing from unimodal toward higher-order transmodal cortices that recapitulates known principles of hierarchical organization and myelination patterns. Despite an emerging literature assessing connectome properties in neonates, the presence of connectome gradients and particularly their correspondence to microstructure remains largely unknown. We derived connectome gradients using unsupervised techniques applied to functional connectivity data from 40 term-born neonates. A series of cortex-wide analysis examined associations to magnetic resonance imaging-derived morphological parameters (cortical thickness, sulcal depth, curvature), measures of tissue microstructure (intracortical T1w/T2w intensity, superficial white matter diffusion parameters), and subcortico-cortical functional connectivity. Our findings indicate that the primary neonatal connectome gradient runs between sensorimotor and visual anchors and captures specific associations to cortical and superficial white matter microstructure as well as thalamo-cortical connectivity. A second gradient indicated an anterior-to-posterior asymmetry in macroscale connectivity alongside an immature differentiation between unimodal and transmodal areas, indicating a connectome-level circuitry en route to an adult-like organization. Our findings reveal an important coordination of structural and functional interactions in the neonatal connectome across spatial scales. Observed associations were replicable across individual neonates, suggesting consistency and generalizability.

Twin MRI studies on genetic and environmental determinants of brain morphology and function in the early lifespan

Neurodevelopment represents a period of increased opportunity and vulnerability, during which a complex confluence of genetic and environmental factors influences brain growth trajectories, cognitive and mental health outcomes. Recently, magnetic resonance imaging (MRI) studies on twins have increased our knowledge of the extent to which genes, the environment and their interactions shape inter-individual brain variability. The present review draws from highly salient MRI studies in young twin samples to provide a robust assessment of the heritability of structural and functional brain changes during development. The available studies suggest that (as with many other traits), global brain morphology and network organization are highly heritable from early childhood to young adulthood. Conversely, genetic correlations among brain regions exhibit heterogeneous trajectories, and this heterogeneity reflects the progressive, experience-related increase in brain network complexity. Studies also support the key role of environment in mediating brain network differentiation via changes of genetic expression and hormonal levels. Thus, rest- and task-related functional brain circuits seem to result from a contextual and dynamic expression of heritability.

Functional Connectome of the Fetal Brain

Large-scale functional connectome formation and reorganization is apparent in the second trimester of pregnancy, making it a crucial and vulnerable time window in connectome development. Here we identified which architectural principles of functional connectome organization are initiated before birth, and contrast those with topological characteristics observed in the mature adult brain. A sample of 105 pregnant women participated in human fetal resting-state fMRI studies (fetal gestational age between 20 and 40 weeks). Connectome analysis was used to analyze weighted network characteristics of fetal macroscale brain wiring. We identified efficient network attributes, common functional modules, and high overlap between the fetal and adult brain network. Our results indicate that key features of the functional connectome are present in the second and third trimesters of pregnancy. Understanding the organizational principles of fetal connectome organization may bring opportunities to develop markers for early detection of alterations of brain function.SIGNIFICANCE STATEMENT The fetal to neonatal period is well known as a critical stage in brain development. Rapid neurodevelopmental processes establish key functional neural circuits of the human brain. Prenatal risk factors may interfere with early trajectories of connectome formation and thereby shape future health outcomes. Recent advances in MRI have made it possible to examine fetal brain functional connectivity. In this study, we evaluate the network topography of normative functional network development during connectome genesis in utero Understanding the developmental trajectory of brain connectivity provides a basis for understanding how the prenatal period shapes future brain function and disease dysfunction.

Association between spontaneous activity of the default mode network hubs and leukocyte telomere length in late childhood and early adolescence

The impact of early life stress on mental health and telomere length shortening have been reported. Changes in brain default mode network (DMN) were found to be related to a myriad of psychiatric conditions in which stress may play a role. In this context, family environment and adverse childhood experiences (ACEs) are potential causes of stress. This is a hypothesis-driven study focused on testing two hypotheses: (i) there is an association between telomere length and the function of two main hubs of DMN: the posterior cingulate cortex (PCC) and the medial prefrontal cortex (mPFC); (ii) this association is modulated by family environment and/or ACEs. To the best of our knowledge, this is the first study investigating these hypotheses. Resting-state functional magnetic resonance imaging data and blood sample were collected from 389 subjects (6-15 age range). We assessed DMN fractional amplitude of low-frequency fluctuations (fALFF) and leukocyte telomere length (LTL). We fitted general linear models to test the main effects of LTL on DMN hubs and the interaction effects with Family Environment Scale (FES) and ACEs. The results did not survive a strict Bonferroni correction. However, uncorrected p-values suggest that LTL was positively correlated with fALFF in PCC and a FES interaction between FES and LTL at mPFC. Although marginal, our results encourage further research on the interaction between DMN hubs, telomere length and family environment, which may play a role on the biological embedding of stress.

I know that I know nothing: Cortical thickness and functional connectivity underlying meta-ignorance ability in pre-schoolers

Metacognition plays a pivotal role in human development. The ability to realize that we do not know something, or meta-ignorance, emerges after approximately five years of age. We sought for the brain systems that underlie the developmental emergence of this ability in a preschool sample. Twenty-four children aged between five and six years answered questions under three conditions. In the critical partial knowledge condition, an experimenter first showed two toys to a child, then announced that she would place one of them in a box, out of sight from the child. The experimenter then asked the child whether she knew which toy was in the box. Children who gave consistently correct answers to this question (n = 9) showed greater cortical thickness in a cluster within left medial orbitofrontal cortex than children who did not (n = 15). Further, seed-based functional connectivity analyses of the brain during resting state revealed that this region is functionally connected to the medial orbitofrontal gyrus, posterior cingulate gyrus and precuneus, and mid- and inferior temporal gyri. This finding suggests that the default mode network, critically through its prefrontal regions, supports introspective processing. It leads to the emergence of metacognitive monitoring allowing children to explicitly report their own ignorance.

Psychopathy is associated with shifts in the organization of neural networks in a large incarcerated male sample

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Psychopathy is linked to disruptions in neural information processing.

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Graph analysis revealed that psychopathy impacts neural network organization.

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Psychopathy is linked to a hyper-efficiently organized dorsal attention network.

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Subcortical structures are less central to neural communication in psychopathy.

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No psychopathy differences were found in default or salience network graph metrics.

Psychopathy is a personality disorder defined by antisocial behavior paired with callousness, low empathy, and low interpersonal emotions. Psychopathic individuals reliably display complex atypicalities in emotion and attention processing that are evident when examining task performance, activation within specific neural regions, and connections between regions. Recent advances in neuroimaging methods, namely graph analysis, attempt to unpack this type of processing complexity by evaluating the overall organization of neural networks. Graph analysis has been used to better understand neural functioning in several clinical disorders but has not yet been used in the study of psychopathy. The present study applies a minimum spanning tree graph analysis to resting-state fMRI data collected from male inmates assessed for psychopathy with the Hare Psychopathy Checklist-Revised (n = 847). Minimum spanning tree analysis provides several metrics of neural organization optimality (i.e., the effectiveness, efficiency, and robustness of neural network organization). Results show that inmates higher in psychopathy exhibit a more efficiently organized dorsal attention network (β = =0.101, p_corrected = =0.018). Additionally, subcortical structures (e.g., amygdala, caudate, and hippocampus) act as less of a central hub in the global flow of information in inmates higher in psychopathy (β = =−0.104, p_corrected = =0.048). There were no significant effects of psychopathy on neural network organization in the default or salience networks. Together, these shifts in neural organization suggest that the brains of inmates higher in psychopathy are organized in a fundamentally different way than other individuals.

Altered Functional Brain Network Integration, Segregation, and Modularity in Infants Born Very Preterm at Term-Equivalent Age

OBJECTIVES

To determine the functional network organization of the brain in infants born very preterm at term-equivalent age and to relate network alterations to known clinical risk factors for poor neurologic outcomes in prematurity.

STUDY DESIGN

Resting-state functional magnetic resonance imaging data from 66 infants born very preterm (gestational age <32 weeks and birth weight <1500 g) and 66 healthy neonates born at full term, acquired as part of a prospective, cross-sectional study, were compared at term age using graph theory. Features of resting-state networks, including integration, segregation, and modularity, were derived from correlated hemodynamic activity arising from 93 cortical and subcortical regions of interest and compared between groups.

RESULTS

Despite preserved small-world topology and modular organization, resting-state networks of infants born very preterm at term-equivalent age were less segregated and less integrated than those of infants born full term. Chronic respiratory illness (ie, bronchopulmonary dysplasia and the length of oxygen support) was associated with decreased global efficiency and increased path lengths (P < .05). In both cohorts, 4 functional modules with similar composition were observed (parietal/temporal, frontal, subcortical/limbic, and occipital). The density of connections in 3 of the 4 modules was decreased in the very preterm network (P < .01); however, in the occipital/visual cortex module, connectivity was increased in infants born very preterm relative to control infants (P < .0001).

CONCLUSIONS

Early exposure to the ex utero environment is associated with altered resting-state network functional organization in infants born very preterm at term-equivalent age, likely reflecting disrupted brain maturational processes.

Neonatal functional brain maturation in the context of perioperative critical care and pain management: A case report

INTRODUCTION

Remarkable plasticity during the first year of life imparts heighted vulnerability of the developing infant brain. Application of resting-state functional magnetic resonance imaging (rs-fMRI) in infants may contribute to our understanding of neuroplastic changes associated with therapeutic interventions and/or brain insults. In addition to showing clinically relevant incidental brain MRI findings, the objective of our pilot study was to test feasibility of rs-fMRI methods at this early age in the context of pediatric perioperative critical care.

METHODS

We report the case of a former 33-week premature infant born with long-gap esophageal atresia that underwent complex perioperative critical care (Foker process) requiring prolonged post-operative sedation and whom presented with incidental subdural hematoma. Rs-fMRI data was acquired before (at 1-month corrected age) and after (at 2.25-months corrected age) complex perioperative care. We evaluated resting-state functional connectivity (RSFC) using graph theory to explore the complex structure of brain networks.

RESULTS

A transient increase in head circumference coincided temporally with lifting of sedation and initiation of sedation drugs weaning, and qualified for hydrocephalus (93%) but not macrocephaly (>95%). RSFC analysis identified networks spatially consistent with those previously described in the literature, with notable pre-post-treatment qualitative differences in correlated and anticorrelated spontaneous brain activity.

DISCUSSION

Current definitions of macrocephaly may require lower threshold criteria for monitoring of critically ill infants. Although we demonstrate that available rs-fMRI could be effectively applied in a critically ill infant in the setting of brain pathology, future group-level studies should investigate RSFC to evaluate maintenance of network homeostasis during development of both healthy and critically ill infants.

Fronto-temporoparietal connectivity and self-awareness in 18-month-olds: A resting state fNIRS study

How and when a concept of the 'self' emerges has been the topic of much interest in developmental psychology. Self-awareness has been proposed to emerge at around 18 months, when toddlers start to show evidence of physical self-recognition. However, to what extent physical self-recognition is a valid indicator of being able to think about oneself, is debated. Research in adult cognitive neuroscience has suggested that a common network of brain regions called Default Mode Network (DMN), including the temporo-parietal junction (TPJ) and the medial prefrontal cortex (mPFC), is recruited when we are reflecting on the self. We hypothesized that if mirror self-recognition involves self-awareness, toddlers who exhibit mirror self-recognition might show increased functional connectivity between frontal and temporoparietal regions of the brain, relative to those toddlers who do not yet show mirror self-recognition. Using fNIRS, we collected resting-state data from 18 Recognizers and 22 Non-Recognizers at 18 months of age. We found significantly stronger fronto-temporoparietal connectivity in Recognizers compared to Non-Recognizers, a finding which might support the hypothesized relationship between mirror-self recognition and self-awareness in infancy.

Early Developmental Trajectories of Functional Connectivity Along the Visual Pathways in Rhesus Monkeys

Early social interactions shape the development of social behavior, although the critical periods or the underlying neurodevelopmental processes are not completely understood. Here, we studied the developmental changes in neural pathways underlying visual social engagement in the translational rhesus monkey model. Changes in functional connectivity (FC) along the ventral object and motion pathways and the dorsal attention/visuo-spatial pathways were studied longitudinally using resting-state functional MRI in infant rhesus monkeys, from birth through early weaning (3 months), given the socioemotional changes experienced during this period. Our results revealed that (1) maturation along the visual pathways proceeds in a caudo-rostral progression with primary visual areas (V1-V3) showing strong FC as early as 2 weeks of age, whereas higher-order visual and attentional areas (e.g., MT-AST, LIP-FEF) show weak FC; (2) functional changes were pathway-specific (e.g., robust FC increases detected in the most anterior aspect of the object pathway (TE-AMY), but FC remained weak in the other pathways (e.g., AST-AMY)); (3) FC matures similarly in both right and left hemispheres. Our findings suggest that visual pathways in infant macaques undergo selective remodeling during the first 3 months of life, likely regulated by early social interactions and supporting the transition to independence from the mother.

Functional Brain Parcellations of the Infant Brain and the Associated Developmental Trends

Resting-state functional connectivity studies have dramatically improved our understanding of the early human brain functional development during the past decade. However, one emerging problem that could potentially impede future progresses in the field is the definition of regions of interest (ROI), since it is well known that functional connectivity estimation can be seriously contaminated by within-ROI signal heterogeneity. In this study, based on a large-scale rsfMRI data set in human infants (230 neonates, 143 1-year olds, and 107 2-year olds), we aimed to derive a set of anatomically constrained, infant-specific functional brain parcellations using functional connectivity-based clustering. Our results revealed significantly higher levels of signal homogeneity within the newly defined functional parcellations compared with other schemes. Importantly, the global functional connectivity patterns associated with the newly defined functional subunits demonstrated significantly increasing levels of differentiation with age, confirming increasing levels of local specialization. Subsequent whole brain connectivity analysis revealed intriguing patterns of regional-level functional connectivity developments and system-level hub redistribution during infancy. Overall, the newly derived infant-specific functional brain parcellations and the associated novel developmental patterns will likely prove valuable for future early developmental studies using the functional connectivity technique.

Adverse childhood experiences and the onset of chronic disease in young adulthood

This study examined the association of adverse childhood experiences (ACEs) with early-onset chronic conditions. We analyzed data from the 2011-2012 Behavioral Risk Factor Surveillance System (BRFSS), which included 86,968 respondents representing a nine-state adult population of 32 million. ACE questions included physical, emotional, and sexual abuse; substance use, mental illness or incarceration of a household member; domestic violence, and parental separation. Outcomes included chronic conditions (cardiovascular disease, chronic obstructive pulmonary disease, cancer, depression, diabetes, and prediabetes); overall health status; and days of poor mental or physical health in the past month. We estimated Poisson regression models of the likelihood of chronic conditions and poor health status comparing adults reporting ≥4 ACEs to respondents with no ACEs within three age strata: 18-34, 35-54 and ≥55 years. The prevalence of ≥4 ACEs was highest among youngest respondents (19%). There was a dose-response gradient between ACE scores and outcomes except for cancer in older adults. Among younger respondents, those reporting ≥4 ACEs had two to four times the risk for each chronic condition and poor health status compared to respondents reporting no ACEs. With few exceptions (depression, poor mental and physical health in the past month), incidence rate ratios were highest in young adults and successively decreased among older adults. This study is among the first to analyze patterns of association between ACEs and adult health disaggregated by age. Young adults with high ACE scores are at increased risk of early-onset chronic disease. Trauma-informed care and ACEs prevention are crucial public health priorities.

Neural substrates of early executive function development

In the last decade, advances in neuroimaging technologies have given rise to a large number of research studies that investigate the neural underpinnings of executive function (EF). EF has long been associated with the prefrontal cortex (PFC) and involves both a unified, general element, as well as the distinct, separable elements of working memory, inhibitory control and set shifting. We will highlight the value of utilising advances in neuroimaging techniques to uncover answers to some of the most pressing questions in the field of early EF development. First, this review will explore the development and neural substrates of each element of EF. Second, the structural, anatomical and biochemical changes that occur in the PFC during infancy and throughout childhood will be examined, in order to address the importance of these changes for the development of EF. Third, the importance of connectivity between regions of the PFC and other brain areas in EF development is reviewed. Finally, throughout this review more recent developments in neuroimaging techniques will be addressed, alongside the implications for further elucidating the neural substrates of early EF development in the future.

Gut microbiome and brain functional connectivity in infants-a preliminary study focusing on the amygdala

Recently, there has been a surge of interest in the possibility that microbial communities inhabiting the human gut could affect cognitive development and increase risk for mental illness via the "microbiome-gut-brain axis." Infancy likely represents a critical period for the establishment of these relationships, as it is the most dynamic stage of postnatal brain development and a key period in the maturation of the microbiome. Indeed, recent reports indicate that characteristics of the infant gut microbiome are associated with both temperament and cognitive performance. The neural circuits underlying these relationships have not yet been delineated. To address this gap, resting-state fMRI scans were acquired from 39 1-year-old human infants who had provided fecal samples for identification and relative quantification of bacterial taxa. Measures of alpha diversity were generated and tested for associations with measures of functional connectivity. Primary analyses focused on the amygdala as manipulation of the gut microbiota in animal models alters the structure and neurochemistry of this brain region. Secondary analyses explored functional connectivity of nine canonical resting-state functional networks. Alpha diversity was significantly associated with functional connectivity between the amygdala and thalamus and between the anterior cingulate cortex and anterior insula. These regions play an important role in processing/responding to threat. Alpha diversity was also associated with functional connectivity between the supplementary motor area (SMA, representing the sensorimotor network) and the inferior parietal lobule (IPL). Importantly, SMA-IPL connectivity also related to cognitive outcomes at 2 years of age, suggesting a potential pathway linking gut microbiome diversity and cognitive outcomes during infancy. These results provide exciting new insights into the gut-brain axis during early human development and should stimulate further studies into whether microbiome-associated changes in brain circuitry influence later risk for psychopathology.

MR Imaging of Normal Brain Development

Normal brain development is best evaluated by MR imaging in the fetal and pediatric patient. As the developing brain grows, myelinates, and sulcates rapidly, understanding the normal appearance of the brain throughout development is critical. The fetal brain can be evaluated by MR imaging after 16 weeks gestational age, both morphologically and biometrically. Sulcation of the fetal brain lags behind premature neonates of equivalent gestational age. Sensory axons generally myelinate before motor axons with central to peripheral and dorsal to ventral myelination gradients. By 2 years of age, the brain has a near adult appearance by conventional anatomic MR imaging.

Increased Functional Connectivity Within and Between Cognitive-Control Networks from Early Infancy to Nine Years During Story Listening

The cingulo-opercular (CO) and frontoparietal (FP) networks are part of the cognitive-control system of the brain. Evidence suggests that over the course of development, brain regions supporting cognitive-control functions become more integrated within their networks (i.e., have increased within-network connectivity), more separated from other networks, and, due to increased maturation along development, are more functionally connected between the networks. The focus of this study was to characterize the developmental trajectory of the CO and FP networks from early infancy (17 months) to 9 years of age in typically developing children while listening to stories, using functional connectivity analyses. Seventy-four children underwent a functional magnetic resonance imaging session while listening to stories inside the scanner. Within- and between-network functional connectivity and graph theory measures were compared during development. Developmental increase in functional connectivity within the CO network and between the CO and FP networks, as well as global efficiency of the CO network from 17 months to 9 years of age, was observed. These findings highlight the involvement of the CO and FP networks in story listening from early infancy, which increases along development. Future studies examining failures in language acquisition to further explore the role of these networks in story listening are warranted.

Sex differences in functional connectivity during fetal brain development

Sex-related differences in brain and behavior are apparent across the life course, but the exact set of processes that guide their emergence in utero remains a topic of vigorous scientific inquiry. Here, we evaluate sex and gestational age (GA)-related change in functional connectivity (FC) within and between brain wide networks. Using resting-state functional magnetic resonance imaging we examined FC in 118 human fetuses between 25.9 and 39.6 weeks GA (70 male; 48 female). Infomap was applied to the functional connectome to identify discrete prenatal brain networks in utero. A consensus procedure produced an optimal model comprised of 16 distinct fetal neural networks distributed throughout the cortex and subcortical regions. We used enrichment analysis to assess network-level clustering of strong FC-GA correlations separately in each sex group, and to identify network pairs exhibiting distinct patterns of GA-related change in FC between males and females. We discovered both within and between network FC-GA associations that varied with sex. Specifically, associations between GA and posterior cingulate-temporal pole and fronto-cerebellar FC were observed in females only, whereas the association between GA and increased intracerebellar FC was stronger in males. These observations confirm that sexual dimorphism in functional brain systems emerges during human gestation.

Resting-state abnormalities in Autism Spectrum Disorders: A meta-analysis

The gold standard for clinical assessment of Autism Spectrum Disorders (ASD) relies on assessing behavior via semi-structured play-based interviews and parent interviews. Although these methods show good sensitivity and specificity in diagnosing ASD cases, behavioral assessments alone may hinder the identification of asymptomatic at-risk group. Resting-state functional magnetic resonance imaging (rs-fMRI) could be an appropriate approach to produce objective neural markers to supplement behavioral assessments due to its non-invasive and task-free nature. Previous neuroimaging studies reported inconsistent resting-state abnormalities in ASD, which may be explained by small sample sizes and phenotypic heterogeneity in ASD subjects, and/or the use of different analytical methods across studies. The current study aims to investigate the local resting-state abnormalities of ASD regardless of subject age, IQ, gender, disease severity and methodological differences, using activation likelihood estimation (ALE). MEDLINE/PubMed databases were searched for whole-brain rs-fMRI studies on ASD published until Feb 2018. Eight experiments involving 424 subjects were included in the ALE meta-analysis. We demonstrate two ASD-related resting-state findings: local underconnectivity in the dorsal posterior cingulate cortex (PCC) and in the right medial paracentral lobule. This study contributes to uncovering a consistent pattern of resting-state local abnormalities that may serve as potential neurobiological markers for ASD.

Threat-related Attention Bias in Socioemotional Development: A Critical Review and Methodological Considerations

Cross-sectional evidence suggests that attention bias to threat is linked to anxiety disorders and anxiety vulnerability in both children and adults. However, there is a lack of developmental evidence regarding the causal mechanisms through which attention bias to threat might convey risks for socioemotional problems, such as anxiety. Gaining insights into this question demands longitudinal research to track the complex interplay between threat-related attention and socioemotional functioning. Developing and implementing reliable and valid assessments tools is essential to this line of work. This review presents theoretical accounts and empirical evidence from behavioral, eye-tracking, and neural assessments of attention to discuss our current understanding of the development of normative threat-related attention in infancy, as well as maladaptive threat-related attention patterns that may be associated with the development of anxiety. This review highlights the importance of measuring threat-related attention using multiple attention paradigms at multiple levels of analysis. In order to understand if and how threat-related attention bias in real-life, social interactive contexts can predict socioemotional development outcomes, this review proposes that future research cannot solely rely on screen-based paradigms but needs to extend the assessment of threat-related attention to naturalistic settings. Mobile eye-tracking technology provides an effective tool for capturing threat-related attention processes in vivo as children navigate fear-eliciting environments and may help us uncover more proximal bio-psycho-behavioral markers of anxiety.

Resting-state functional MRI studies on infant brains: A decade of gap-filling efforts

Resting-state functional MRI (rs-fMRI) is one of the most prevalent brain functional imaging modalities. Previous rs-fMRI studies have mainly focused on adults and elderly subjects. Recently, infant rs-fMRI studies have become an area of active research. After a decade of gap filling studies, many facets of the brain functional development from early infancy to toddler has been uncovered. However, infant rs-fMRI is still in its infancy. The image analysis tools for neonates and young infants can be quite different from those for adults. From data analysis to result interpretation, more questions and issues have been raised, and new hypotheses have been formed. With the anticipated availability of unprecedented high-resolution rs-fMRI and dedicated analysis pipelines from the Baby Connectome Project (BCP), it is important now to revisit previous findings and hypotheses, discuss and comment existing issues and problems, and make a "to-do-list" for the future studies. This review article aims to comprehensively review a decade of the findings, unveiling hidden jewels of the fields of developmental neuroscience and neuroimage computing. Emphases will be given to early infancy, particularly the first few years of life. In this review, an end-to-end summary, from infant rs-fMRI experimental design to data processing, and from the development of individual functional systems to large-scale brain functional networks, is provided. A comprehensive summary of the rs-fMRI findings in developmental patterns is highlighted. Furthermore, an extensive summary of the neurodevelopmental disorders and the effects of other hazardous factors is provided. Finally, future research trends focusing on emerging dynamic functional connectivity and state-of-the-art functional connectome analysis are summarized. In next decade, early infant rs-fMRI and developmental connectome study could be one of the shining research topics.

A review on neuroimaging studies of genetic and environmental influences on early brain development

The past decades witnessed a surge of interest in neuroimaging study of normal and abnormal early brain development. Structural and functional studies of normal early brain development revealed massive structural maturation as well as sequential, coordinated, and hierarchical emergence of functional networks during the infancy period, providing a great foundation for the investigation of abnormal early brain development mechanisms. Indeed, studies of altered brain development associated with either genetic or environmental risks emerged and thrived. In this paper, we will review selected studies of genetic and environmental risks that have been relatively more extensively investigated-familial risks, candidate risk genes, and genome-wide association studies (GWAS) on the genetic side; maternal mood disorders and prenatal drug exposures on the environmental side. Emerging studies on environment-gene interactions will also be reviewed. Our goal was not to perform an exhaustive review of all studies in the field but to leverage some representative ones to summarize the current state, point out potential limitations, and elicit discussions on important future directions.

First-year development of modules and hubs in infant brain functional networks

The human brain develops rapidly in the first postnatal year, in which rewired functional brain networks could shape later behavioral and cognitive performance. Resting-state functional magnetic resonances imaging (rs-fMRI) and complex network analysis have been widely used for characterizing the developmental brain functional connectome. Yet, such studies focusing on the first year of postnatal life are still very limited. Leveraging normally developing longitudinal infant rs-fMRI scans from neonate to one year of age, we investigated how brain functional networks develop at a fine temporal scale (every 3 months). Considering challenges in the infant fMRI-based network analysis, we developed a novel algorithm to construct the robust, temporally consistent and modular structure augmented group-level network based on which functional modules were detected at each age. Our study reveals that the brain functional network is gradually subdivided into an increasing number of functional modules accompanied by the strengthened intra- and inter-modular connectivities. Based on the developing modules, we found connector hubs (the high-centrality regions connecting different modules) emerging and increasing, while provincial hubs (the high-centrality regions connecting regions in the same module) diminishing. Further region-wise longitudinal analysis validates that different hubs have distinct developmental trajectories of the intra- and inter-modular connections suggesting different types of role transitions in network, such as non-hubs to hubs or provincial hubs to connector hubs et al. All findings indicate that functional segregation and integration are both increased in the first year of postnatal life. The module reorganization and hub transition lead to more efficient brain networks, featuring increasingly segregated modular structure and more connector hubs. This study provides the first comprehensive report of the development of functional brain networks at a 3-month interval throughout the first postnatal year of life, which provides essential information to the future neurodevelopmental and developmental disorder studies.

Neonatal brain injury and aberrant connectivity

Brain injury sustained during the neonatal period may disrupt development of critical structural and functional connectivity networks leading to subsequent neurodevelopmental impairment in affected children. These networks can be characterized using structural (via diffusion MRI) and functional (via resting state-functional MRI) neuroimaging techniques. Advances in neuroimaging have led to expanded application of these approaches to study term- and prematurely-born infants, providing improved understanding of cerebral development and the deleterious effects of early brain injury. Across both modalities, neuroimaging data are conducive to analyses ranging from characterization of individual white matter tracts and/or resting state networks through advanced 'connectome-style' approaches capable of identifying highly connected network hubs and investigating metrics of network topology such as modularity and small-worldness. We begin this review by summarizing the literature detailing structural and functional connectivity findings in healthy term and preterm infants without brain injury during the postnatal period, including discussion of early connectome development. We then detail common forms of brain injury in term- and prematurely-born infants. In this context, we next review the emerging body of literature detailing studies employing diffusion MRI, resting state-functional MRI and other complementary neuroimaging modalities to characterize structural and functional connectivity development in infants with brain injury. We conclude by reviewing technical challenges associated with neonatal neuroimaging, highlighting those most relevant to studying infants with brain injury and emphasizing the need for further targeted study in this high-risk population.

Brain functional development separates into three distinct time periods in the first two years of life

Recently, resting functional MRI has provided invaluable insight into the brain developmental processes of early infancy and childhood. A common feature of previous functional development studies is the use of age to separate subjects into different cohorts for group comparisons. However, functional maturation paces vary tremendously from subject to subject. Since this is particularly true for the first years of life, an alternative to physical age alone is needed for cluster analysis. Here, a data-driven approach based on individual brain functional connectivity was employed to cluster typically developing children who were longitudinally imaged using MRI without sedation for the first two years of life. Specifically, three time periods were determined based on the distinction of brain functional connectivity patterns, including 0-1 month (group 1), 2-7 months (group 2), and 8-24 (group 3) of age, respectively. From groups 1 to 2, connection density increased by almost two-fold, local efficacy (LE) is significantly improved, and there was no change in global efficiency (GE). From groups 2 to 3, connection density increased slightly, LE showed no change, and a significant increase in GE were observed. Furthermore, 27 core brain regions were identified which yielded clustering results that resemble those obtained using all brain regions. These core regions were largely associated with the motor, visual and language functional domains as well as regions associated with higher order cognitive functional domains. Both visual and language functional domains exhibited a persistent and significant increase within domain connection from groups 1 to 3, while no changes were observed for the motor domain. In contrast, while a reduction of inter-domain connection was the general developmental pattern, the motor domain exhibited an interesting "V" shape pattern in its relationship to visual and language associated areas, showing a decrease from groups 1 to 2, followed by an increase from groups 2 to 3. In summary, our results offer new insights into functional brain development and identify 27 core brain regions critically important for early brain development.

The development of brain functional connectivity networks revealed by resting-state functional magnetic resonance imaging

Previous studies on brain functional connectivity networks in children have mainly focused on changes in function in specific brain regions, as opposed to whole brain connectivity in healthy children. By analyzing the independent components of activation and network connectivity between brain regions, we examined brain activity status and development trends in children aged 3 and 5 years. These data could provide a reference for brain function rehabilitation in children with illness or abnormal function. We acquired functional magnetic resonance images from 15 3-year-old children and 15 5-year-old children under natural sleep conditions. The participants were recruited from five kindergartens in the Nanshan District of Shenzhen City, China. The parents of the participants signed an informed consent form with the premise that they had been fully informed regarding the experimental protocol. We used masked independent component analysis and BrainNet Viewer software to explore the independent components of the brain and correlation connections between brain regions. We identified seven independent components in the two groups of children, including the executive control network, the dorsal attention network, the default mode network, the left frontoparietal network, the right frontoparietal network, the salience network, and the motor network. In the default mode network, the posterior cingulate cortex, medial frontal gyrus, and inferior parietal lobule were activated in both 3- and 5-year-old children, supporting the “three-brain region theory” of the default mode network. In the frontoparietal network, the frontal and parietal gyri were activated in the two groups of children, and functional connectivity was strengthened in 5-year-olds compared with 3-year-olds, although the nodes and network connections were not yet mature. The high-correlation network connections in the default mode networks and dorsal attention networks had been significantly strengthened in 5-year-olds vs. 3-year-olds. Further, the salience network in the 3-year-old children included an activated insula/inferior frontal gyrus-anterior cingulate cortex network circuit and an activated thalamus-parahippocampal-posterior cingulate cortex-subcortical regions network circuit. By the age of 5 years, nodes and high-correlation network connections (edges) were reduced in the salience network. Overall, activation of the dorsal attention network, default mode network, left frontoparietal network, and right frontoparietal network increased (the volume of activation increased, the signals strengthened, and the high-correlation connections increased and strengthened) in 5-year-olds compared with 3-year-olds, but activation in some brain nodes weakened or disappeared in the salience network, and the network connections (edges) were reduced. Between the ages of 3 and 5 years, we observed a tendency for function in some brain regions to be strengthened and for the generalization of activation to be reduced, indicating that specialization begins to develop at this time. The study protocol was approved by the local ethics committee of the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences in China with approval No. SIAT-IRB-131115-H0075 on November 15, 2013.

Neural histology and neurogenesis of the human fetal and infant brain

The human brain develops slowly and over a long period of time which lasts for almost three decades. This enables good spatio-temporal resolution of histogenetic and neurogenetic events as well as an appropriate and clinically relevant timing of these events. In order to successfully apply in vivo neuroimaging data, in analyzing both the normal brain development and the neurodevelopmental origin of major neurological and mental disorders, it is important to correlate these neuroimaging data with the existing data on morphogenetic, histogenetic and neurogenetic events. Furthermore, when performing such correlation, the genetic, genomic, and molecular biology data on phenotypic specification of developing brain regions, areas and neurons should also be included. In this review, we focus on early developmental periods (form 8 postconceptional weeks to the second postnatal year) and describe the microstructural organization and neural circuitry elements of the fetal and early postnatal human cerebrum.

Default Mode Network Maturation and Environmental Adversities During Childhood

Default mode network (DMN) plays a central role in cognition and brain disorders. It has been shown that adverse environmental conditions impact neurodevelopment, but how these conditions impact in DMN maturation is still poorly understood. This article reviews representative neuroimaging functional studies addressing the interactions between DMN development and environmental factors, focusing on early life adversities, a critical period for brain changes. Studies focused on this period of life offer a special challenge: to disentangle the neurodevelopmental connectivity changes from those related to environmental conditions. We first summarized the literature on DMN maturation, providing an overview of both typical and atypical development patterns in childhood and early adolescence. Afterward, we focused on DMN changes associated with chronic exposure to environmental adversities during childhood. This summary suggests that changes in DMN development could be a potential allostatic neural feature associated with an embodiment of environmental circumstances. Finally, we discuss about some key methodological issues that should be considered in paradigms addressing environmental adversities and open questions for future investigations.

Rapid Eye Movements in Sleep Furnish a Unique Probe Into Consciousness

The neural correlates of rapid eye movements (REMs) in sleep are extraordinarily robust; including REM-locked multisensory-motor integration and accompanying activation in the retrosplenial cortex, the supplementary eye field and areas encompassing cholinergic basal nucleus (Hong et al., 2009). The phenomenology of REMs speaks to the notion that perceptual experience in both sleep and wakefulness is a constructive process - in which we generate predictions of sensory inputs and then test those predictions through actively sampling the sensorium with eye movements. On this view, REMs during sleep may index an internalized active sampling or 'scanning' of self-generated visual constructs that are released from the constraints of visual input. If this view is correct, it renders REMs an ideal probe to study consciousness as "an exclusively internal affair" (Metzinger, 2009). In other words, REMs offer a probe of active inference - in the sense of predictive coding - when the brain is isolated from the sensorium in virtue of the natural blockade of sensory afferents during REM sleep. Crucially, REMs are temporally precise events that enable powerful inferences based on time series analyses. As a natural, task-free probe, (REMs) could be used in non-compliant subjects, including infants and animals. In short, REMs constitute a promising probe to study the ontogenetic and phylogenetic development of consciousness and perhaps the psychopathology of schizophrenia and autism, which have been considered in terms of aberrant predictive coding.

Functional connectivity of intrinsic cognitive networks during resting state and task performance in preadolescent children

Earlier studies on adults have shown that functional connectivity (FC) of brain networks can vary depending on the brain state and cognitive challenge. Network connectivity has been investigated quite extensively in children in resting state, much less during tasks and is largely unexplored between these brain states. Here we used functional magnetic resonance imaging and independent component analysis to investigate the functional architecture of large-scale brain networks in 16 children (aged 7–11 years, 11 males) and 16 young adults (aged 22–29 years, 10 males) during resting state and visual working memory tasks. We identified the major neurocognitive intrinsic connectivity networks (ICNs) in both groups. Children had stronger FC than adults within the cingulo-opercular network in resting state, during task performance, and after controlling for performance differences. During tasks, children had stronger FC than adults also within the default mode (DMN) and right frontoparietal (rFPN) networks, and between the anterior DMN and the frontopolar network, whereas adults had stronger coupling between the anterior DMN and rFPN. Furthermore, children compared to adults modulated the FC strength regarding the rFPN differently between the brain states. The FC within the anterior DMN correlated with age and performance in children so that the younger they were, the stronger was the FC, and the stronger the FC within this network, the slower they performed the tasks. The group differences in the network connectivity reported here, and the observed correlations with task performance, provide insight into the normative development of the preadolescent brain and link maturation of functional connectivity with improving cognitive performance.

The Impact of Caregiving on the Association Between Infant Emotional Behavior and Resting State Neural Network Functional Topology

The extent to which neural networks underlying emotional behavior in infancy serve as precursors of later behavioral and emotional problems is unclear. Even less is known about caregiving influences on these early brain-behavior relationships. To study brain-emotional behavior relationships in infants, we examined resting-state functional network metrics and infant emotional behavior in the context of early maternal caregiving. We assessed 46 3-month-old infants and their mothers from a community sample. Infants underwent functional MRI during sleep. Resting-state data were processed using graph theory techniques to examine specific nodal metrics as indicators of network functionality. Infant positive and negative emotional behaviors, and positive, negative and mental-state talk (MST) indices of maternal caregiving were coded independently from filmed interactions. Regression analyses tested associations among nodal metrics and infant emotionality, and the moderating effects of maternal behavior on these relationships. All results were FDR corrected at alpha = 0.05. While relationships between infant emotional behavior or maternal caregiving, and nodal metrics were weak, higher levels of maternal MST strengthened associations between infant positive emotionality and nodal metrics within prefrontal (p < 0.0001), and occipital (p < 0.0001) cortices more generally. Positive and negative aspects of maternal caregiving had little effect. Our findings suggest that maternal MST may play an important role in strengthening links between emotion regulation neural circuitry and early infant positive behavior. They also provide objective neural markers that could inform and monitor caregiving-based interventions designed to improve the health and well-being of vulnerable infants at-risk for behavioral and emotional problems.

The Lifespan Trajectory of the Encoding-Retrieval Flip: A Multimodal Examination of Medial Parietal Cortex Contributions to Episodic Memory

The formation of episodic memories is associated with deactivation during encoding and activation during retrieval in the posteromedial cortex (PMC). We hypothesized that the encoding/retrieval (E/R) flip is a critical component of episodic memory across the lifespan because structural and metabolic changes in the PMC coincide with the fine tuning of the episodic memory system in development and the reductions of memory performance in aging. The aims of the present study were, first, to describe lifespan trajectories of PMC encoding and retrieval activity in 270 human participants (167 females) from 6 to 80 years of age. Our second goal was to construct a model for episodic memory development in which contributions from brain activity, cortical thickness (CT), and structural connectivity are accounted for. We found that modulation of neural activity in response to memory encoding and retrieval demands was not fully developed until adolescence and decreased from adulthood through old age. The magnitude of the E/R flip was related to source memory and 55% of the age-related variance in source memory performance during childhood and adolescence could be accounted for by the E/R flip, CT, and mean diffusivity together. However, only CT and the E/R flip provided unique contributions with which to explain memory performance. The results suggest that neural dynamics in the PMC is related to the development of episodic memory during childhood and adolescence. The similar trajectories of the E/R flip and episodic memory emergence and decline through development and aging further suggests that a lifelong relationship exists.SIGNIFICANCE STATEMENT Modulation of neural activity in the posteromedial cortex (PMC) in response to memory encoding/retrieval (E/R) demands (E/R flip) does not reach its peak until adolescence and decreases from adulthood through old age. The magnitude of the E/R flip is related to source memory and 55% of the age-related variance in source memory performance during childhood and adolescence can be accounted for by the E/R flip and brain structure together. The results suggest that neural dynamics in the PMC is related to the development of episodic memory function during childhood and adolescence and the similar trajectories of the E/R flip and episodic memory performance through development and aging suggests that a lifelong relationship exists.

Methodological challenges in the comparison of infant fMRI across age groups

Functional MRI (fMRI) in infants is rapidly growing and providing fundamental insights into the origins of brain functions. Comparing brain development at different ages is particularly powerful, but there are a number of methodological challenges that must be addressed if confounds are to be avoided. With development, brains change in composition in a way that alters their tissue contrast, and in size, shape, and gyrification, requiring careful image processing strategies and age-specific standard templates. The hemodynamic response and other aspects of physiology change with age, requiring careful paradigm design and analysis methods. Infants move more, particularly around the second year of age, and move in a different way to adults. This movement can lead to distortion in fMRI images, and requires tailored techniques during acquisition and post-processing. Infants have different sleep patterns, and their sensory periphery is changing macroscopically and in its neural pathways. Finally, once data have been acquired and analyzed, there are important considerations during mapping of brain processes and cognitive functions across age groups. In summary, new methods are critical to the comparison across age groups, and key to maximizing the rate at which infant fMRI can provide insight into the fascinating questions about the origin of cognition.

Mind wandering perspective on attention-deficit/hyperactivity disorder

Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder associated with a range of mental health, neurocognitive and functional problems. Although the diagnosis is based on descriptions of behaviour, individuals with ADHD characteristically describe excessive spontaneous mind wandering (MW). MW in individuals with ADHD reflects constant mental activity which lacks topic stability and content consistency. Based on this review of the neural correlates of ADHD and MW, we outline a new perspective on ADHD: the MW hypothesis. We propose that altered deactivation of the default mode network, and dysfunctional interaction with the executive control network, leads to excessive and spontaneous MW, which underpins symptoms and impairments of ADHD. We highlight that processes linked to the normal neural regulation of MW (context regulation, sensory decoupling, salience thresholds) are deficient in ADHD. MW-related measures could serve as markers of the disease process, as MW can be experimentally manipulated, as well as measured using rating scales, and experience sampling during both cognitive tasks and daily life. MW may therefore be a potential endophenotype.

Alterations in hub organization in the white matter structural network in toddlers with autism spectrum disorder: A 2-year follow-up study

Little is currently known about the longitudinal developmental patterns of hubs in the whole-brain white matter (WM) structural networks among toddlers with autism spectrum disorder (ASD). This study utilized diffusion tensor imaging (DTI) and deterministic tractography to map the WM structural networks in 37 ASD toddlers and 27 age-, gender- and developmental quotient-matched controls with developmental delay (DD) toddlers aged 2-3 years old at baseline (Time 1) and at 2-year follow-up (Time 2). Furthermore, graph-theoretical methods were applied to investigate alterations in the network hubs in these patients at the two time points. The results showed that after 2 years, 17 hubs were identified in the ASD subjects compared to the controls, including 13 hubs that had not changed from baseline and 4 hubs that were newly identified. In addition, alterations in the properties of the hubs of the right middle frontal gyrus, right insula, left median cingulate gyri, and bilateral precuneus were significantly correlated with alterations in the behavioral data for ASD patients. These results indicated that at the stage of 2-5 years of age, ASD children showed distributions of network hubs that were relatively stable, with minor differences. Abnormal developmental patterns in the five areas mentioned above in ASD may contribute to abnormalities in the social and nonsocial characteristics of this disorder. Autism Res 2018, 11: 1218-1228. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: This work studied the longitudinal developmental patterns of hubs in the whole-brain white matter (WM) structural network among toddlers with autism spectrum disorder (ASD). The findings of this study could have implications for understanding how the abnormalities in hub organization in ASD account for behavioral deficits in patients and may provide potential biomarkers for disease diagnosis and the subsequent monitoring of progression and treatment effects for patients with ASD.