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

Individual Brain Morphological Connectome Indicator Based on Jensen-Shannon Divergence Similarity Estimation for Autism Spectrum Disorder Identification

Background

Structural magnetic resonance imaging (sMRI) reveals abnormalities in patients with autism spectrum syndrome (ASD). Previous connectome studies of ASD have failed to identify the individual neuroanatomical details in preschool-age individuals. This paper aims to establish an individual morphological connectome method to characterize the connectivity patterns and topological alterations of the individual-level brain connectome and their diagnostic value in patients with ASD.

Methods

Brain sMRI data from 24 patients with ASD and 17 normal controls (NCs) were collected; participants in both groups were aged 24-47 months. By using the Jensen-Shannon Divergence Similarity Estimation (JSSE) method, all participants's morphological brain network were ascertained. Student's t-tests were used to extract the most significant features in morphological connection values, global graph measurement, and node graph measurement.

Results

The results of global metrics' analysis showed no statistical significance in the difference between two groups. Brain regions with meaningful properties for consensus connections and nodal metric features are mostly distributed in are predominantly distributed in the basal ganglia, thalamus, and cortical regions spanning the frontal, temporal, and parietal lobes. Consensus connectivity results showed an increase in most of the consensus connections in the frontal, parietal, and thalamic regions of patients with ASD, while there was a decrease in consensus connectivity in the occipital, prefrontal lobe, temporal lobe, and pale regions. The model that combined morphological connectivity, global metrics, and node metric features had optimal performance in identifying patients with ASD, with an accuracy rate of 94.59%.

Conclusion

The individual brain network indicator based on the JSSE method is an effective indicator for identifying individual-level brain network abnormalities in patients with ASD. The proposed classification method can contribute to the early clinical diagnosis of ASD.

NeoRS: A Neonatal Resting State fMRI Data Preprocessing Pipeline

Resting state functional MRI (rsfMRI) has been shown to be a promising tool to study intrinsic brain functional connectivity and assess its integrity in cerebral development. In neonates, where functional MRI is limited to very few paradigms, rsfMRI was shown to be a relevant tool to explore regional interactions of brain networks. However, to identify the resting state networks, data needs to be carefully processed to reduce artifacts compromising the interpretation of results. Because of the non-collaborative nature of the neonates, the differences in brain size and the reversed contrast compared to adults due to myelination, neonates can’t be processed with the existing adult pipelines, as they are not adapted. Therefore, we developed NeoRS, a rsfMRI pipeline for neonates. The pipeline relies on popular neuroimaging tools (FSL, AFNI, and SPM) and is optimized for the neonatal brain. The main processing steps include image registration to an atlas, skull stripping, tissue segmentation, slice timing and head motion correction and regression of confounds which compromise functional data interpretation. To address the specificity of neonatal brain imaging, particular attention was given to registration including neonatal atlas type and parameters, such as brain size variations, and contrast differences compared to adults. Furthermore, head motion was scrutinized, and motion management optimized, as it is a major issue when processing neonatal rsfMRI data. The pipeline includes quality control using visual assessment checkpoints. To assess the effectiveness of NeoRS processing steps we used the neonatal data from the Baby Connectome Project dataset including a total of 10 neonates. NeoRS was designed to work on both multi-band and single-band acquisitions and is applicable on smaller datasets. NeoRS also includes popular functional connectivity analysis features such as seed-to-seed or seed-to-voxel correlations. Language, default mode, dorsal attention, visual, ventral attention, motor and fronto-parietal networks were evaluated. Topology found the different analyzed networks were in agreement with previously published studies in the neonate. NeoRS is coded in Matlab and allows parallel computing to reduce computational times; it is open-source and available on GitHub (https://github.com/venguix/NeoRS). NeoRS allows robust image processing of the neonatal rsfMRI data that can be readily customized to different datasets.

Memory for the Future: Psychodynamic Approach to Time and Self Through the Default Network

Time exists in us, and our self exists in time. Our self is affected and shaped by time to the point that a better understanding of the former can aid the understanding of the latter. Psychoanalysis works through self and time, where the self is composed of the biopsychosocial history (the past) of the individual and able to map a trajectory for the future. The psychoanalytic relationship starts from a "measurement": an active process able to alter the system being measured-the self-continuously built over time. This manuscript, starts from the philosophical and scientific tradition of a proximity between time and self, suggesting a neural overlapping at the Default Network. A historical and scientific background will be introduced, proposing a multidisciplinary dimension that has characterized the birth of psychoanalysis (its past), influencing its present and future in the dialogue with physics and neuroscience. After a historical scientific introduction, a neural entanglement between past and future at the Default Network level will be proposed, tracing a link with the self at the level of this network. This hypothesis will be supported by studies in cognitive neurosciences and functional neuroimaging which have used the resting state functional Magnetic Resonance Imaging. The ontogenetic development of time perception will be discussed, consistent with self-development and the Default Network's function. The most common form of dementia, the Alzheimer's Disease, in which the perception of time is brutally impaired together with a loss of the self's functions will be proposed to support this idea. Finally, the potential theoretical and clinical significance for psychoanalysis and psychodynamic neurosciences, will be discussed.

Examining the Role of Socioeconomic Status and Maternal Sensitivity in Predicting Functional Brain Network Connectivity in 5-Month-Old Infants

Infancy is a sensitive period of human brain development that is plastically shaped by environmental factors. Both proximal factors, such as sensitive parenting, and distal factors, such as socioeconomic status (SES), are known predictors of individual differences in structural and functional brain systems across the lifespan, yet it is unclear how these familial and contextual factors work together to shape functional brain development during infancy, particularly during the first months of life. In the current study, we examined pre-registered hypotheses regarding the interplay between these factors to assess how maternal sensitivity, within the broader context of socioeconomic variation, relates to the development of functional connectivity in long-range cortical brain networks. Specifically, we measured resting-state functional connectivity in three cortical brain networks (fronto-parietal network, default mode network, homologous-interhemispheric connectivity) using functional near-infrared spectroscopy (fNIRS), and examined the associations between maternal sensitivity, SES, and functional connectivity in a sample of 5-month-old infants and their mothers (N = 50 dyads). Results showed that all three networks were detectable during a passive viewing task, and that maternal sensitivity was positively associated with functional connectivity in the default mode network, such that infants with more sensitive mothers exhibited enhanced functional connectivity in this network. Contrary to hypotheses, we did not observe any associations of SES with functional connectivity in the brain networks assessed in this study. This suggests that at 5 months of age, maternal sensitivity is an important proximal environmental factor associated with individual differences in functional connectivity in a long-range cortical brain network implicated in a host of emotional and social-cognitive brain processes.

Evidence for the Normalization Effects of Medication for Opioid Use Disorder on Functional Connectivity in Neonates with Prenatal Opioid Exposure

Altered functional connectivity has been reported in infants with prenatal exposure to opioids, which significantly interrupts and influences endogenous neurotransmitter/receptor signaling during fetal programming. Better birth outcomes and long-term developmental outcomes are associated with medication for opioid use disorder (MOUD) during pregnancy, but the neural mechanisms underlying these benefits are largely unknown. We aimed to characterize effects of prenatal opioid/other drug exposure (PODE) and the neural basis for the reported beneficial effects of MOUD by examining neonatal brain functional organization. A cohort of 109 human newborns, 42 PODE, 39 with prenatal exposure to drugs excluding opioids (PDE), 28 drug-free controls (males and females) underwent resting-state fMRI at 2 weeks of age. To examine neural effects of MOUD, PODE infants were separated into subgroups based on whether mothers received MOUD (n = 31) or no treatment (n = 11). A novel heatmap analysis was designed to characterize PODE-associated functional connectivity alterations and MOUD-related effects, and permutation testing identified regions of interest with significant effects. PODE neonates showed alterations beyond those associated with PDE, particularly in reward-related frontal-sensory connectivity. MOUD was associated with a significant reduction of PODE-related alterations in key regions of endogenous opioid pathways including limbic and frontal connections. However, significant residual effects in limbic and subcortical circuitry were observed. These findings confirm altered brain functional organization associated with PODE. Importantly, widespread normalization effects associated with MOUD reveal, for the first time, the potential brain basis of the beneficial effects of MOUD on the developing brain and underscore the importance of this treatment intervention for better developmental outcomes.SIGNIFICANCE STATEMENT This is the first study to reveal the potential neural mechanisms underlying the beneficial effects on the neonate brain associated with MOUD during pregnancy. We identified both normalization and residual effects of MOUD on brain functional architecture by directly comparing neonates prenatally exposed to opioids with MOUD and those exposed to opioids but without MOUD. Our findings confirm altered brain functional organization associated with prenatal opioid exposure and demonstrate that although significant residual effects remain in reward circuitry, MOUD confers significant normalization effects on functional connectivity of regions associated with socioemotional development and reward processing. Together, our results highlight the importance of MOUD intervention for better neurodevelopmental outcomes.

Neonatal encephalopathy prediction of poor outcome with diffusion-weighted imaging connectome and fixel-based analysis

BACKGROUND

Better biomarkers of eventual outcome are needed for neonatal encephalopathy. To identify the most potent neonatal imaging marker associated with 2-year outcomes, we retrospectively performed diffusion-weighted imaging connectome (DWIC) and fixel-based analysis (FBA) on magnetic resonance imaging (MRI) obtained in the first 4 weeks of life in term neonatal encephalopathy newborns.

METHODS

Diffusion tractography was available in 15 out of 24 babies with MRI, five each with normal, abnormal motor outcome, or death. All 15 except one underwent hypothermia as initial treatment. In abnormal motor and death groups, DWIC found 19 white matter pathways with severely disrupted fiber orientation distributions.

RESULTS

Using random forest classification, these disruptions predicted the follow-up outcomes with 89-99% accuracy. These pathways showed reduced integrity in abnormal motor and death vs. normal tone groups (p < 10^-6). Using ranked supervised multi-view canonical correlation and depicting just three of the five dimensions of the analysis, the abnormal motor and death were clearly differentiated from each other and the normal tone group.

CONCLUSIONS

This study suggests that a machine-learning model for prediction using early DWIC and FBA could be a possible way of developing biomarkers in large MRI datasets having clinical outcomes.

IMPACT

Early connectome and FBA of clinically acquired DWI provide a new noninvasive imaging tool to predict the long-term motor outcomes after birth, based on the severity of white matter injury. Disrupted white matter connectivity as a novel neonatal marker achieves high accuracy of 89-99% to predict 2-year motor outcomes using conventional machine-learning classification. The proposed neonatal marker may allow better prognostication that is important to elucidate neural repair mechanisms and evaluate treatment modalities in neonatal encephalopathy.

Individual variability in the nonlinear development of the corpus callosum during infancy and toddlerhood: a longitudinal MRI analysis

The human brain spends several years bootstrapping itself through intrinsic and extrinsic modulation, thus gradually developing both spatial organization and functions. Based on previous studies on developmental patterns and inter-individual variability of the corpus callosum (CC), we hypothesized that inherent variations of CC shape among infants emerge, depending on the position within the CC, along the developmental timeline. Here we used longitudinal magnetic resonance imaging data from infancy to toddlerhood and investigated the area, thickness, and shape of the midsagittal plane of the CC by applying multilevel modeling. The shape characteristics were extracted using the Procrustes method. We found nonlinearity, region-dependency, and inter-individual variability, as well as intra-individual consistencies, in CC development. Overall, the growth rate is faster in the first year than in the second year, and the trajectory differs between infants; the direction of CC formation in individual infants was determined within six months and maintained to two years. The anterior and posterior subregions increase in area and thickness faster than other subregions. Moreover, we clarified that the growth rate of the middle part of the CC is faster in the second year than in the first year in some individuals. Since the division of regions exhibiting different tendencies coincides with previously reported divisions based on the diameter of axons that make up the region, our results suggest that subregion-dependent individual variability occurs due to the increase in the diameter of the axon caliber, myelination partly due to experience and axon elimination during the early developmental period.

An ode to fetal, infant, and toddler neuroimaging: Chronicling early clinical to research applications with MRI, and an introduction to an academic society connecting the field

Fetal, infant, and toddler neuroimaging is commonly thought of as a development of modern times (last two decades). Yet, this field mobilized shortly after the discovery and implementation of MRI technology. Here, we provide a review of the parallel advancements in the fields of fetal, infant, and toddler neuroimaging, noting the shifts from clinical to research use, and the ongoing challenges in this fast-growing field. We chronicle the pioneering science of fetal, infant, and toddler neuroimaging, highlighting the early studies that set the stage for modern advances in imaging during this developmental period, and the large-scale multi-site efforts which ultimately led to the explosion of interest in the field today. Lastly, we consider the growing pains of the community and the need for an academic society that bridges expertise in developmental neuroscience, clinical science, as well as computational and biomedical engineering, to ensure special consideration of the vulnerable mother-offspring dyad (especially during pregnancy), data quality, and image processing tools that are created, rather than adapted, for the young brain.

Sinful pleasures and pious woes? Using fMRI to examine evaluative and hedonic emotion knowledge

Traditionally, lust and pride have been considered pleasurable, yet sinful in the West. Conversely, guilt is often considered aversive, yet valuable. These emotions illustrate how evaluations about specific emotions and beliefs about their hedonic properties may often diverge. Evaluations about specific emotions may shape important aspects of emotional life (e.g. in emotion regulation, emotion experience and acquisition of emotion concepts). Yet these evaluations are often understudied in affective neuroscience. Prior work in emotion regulation, affective experience, evaluation/attitudes and decision-making point to anterior prefrontal areas as candidates for supporting evaluative emotion knowledge. Thus, we examined the brain areas associated with evaluative and hedonic emotion knowledge, with a focus on the anterior prefrontal cortex. Participants (N = 25) made evaluative and hedonic ratings about emotion knowledge during functional magnetic resonance imaging (fMRI). We found that greater activity in the medial prefrontal cortex (mPFC), ventromedial PFC (vmPFC) and precuneus was associated with an evaluative (vs hedonic) focus on emotion knowledge. Our results suggest that the mPFC and vmPFC, in particular, may play a role in evaluating discrete emotions.

Individual variability in functional organization of the neonatal brain

The adult brain is organized into distinct functional networks, forming the basis of information processing and determining individual differences in behavior. Is this network organization genetically determined and present at birth? And what is the individual variability in this organization in neonates? Here, we use unsupervised learning to uncover intrinsic functional brain organization using resting-state connectivity from a large cohort of neonates (Developing Human Connectome Project). We identified a set of symmetric, hierarchical, and replicable networks: sensorimotor, visual, default mode, ventral attention, and high-level vision. We quantified individual variability across neonates, and found the most individual variability in the ventral attention networks. Crucially, the variability of these networks was not driven by SNR differences or differences from adult networks (Yeo et al., 2011). Finally, differential gene expression provided a potential explanation for the emergence of these distinct networks and identified potential genes of interest for future developmental and individual variability research. Overall, we found neonatal connectomes (even at the voxel-level) can reveal broad individual-specific information processing units. The presence of individual differences in neonates and the framework for personalized parcellations demonstrated here has the potential to improve prediction of behavior and future outcomes from neonatal and infant brain data.

Atypical Intrinsic Hemispheric Interaction Associated with Autism Spectrum Disorder Is Present within the First Year of Life

Autism spectrum disorder (ASD) is characterized by atypical connectivity lateralization of functional networks. However, previous studies have not directly investigated if differences in specialization between ASD and typically developing (TD) peers are present in infancy, leaving the timing of onset of these differences relatively unknown. We studied the hemispheric asymmetries of connectivity in children with ASD and infants later meeting the diagnostic criteria for ASD. Analyses were performed in 733 children with ASD and TD peers and in 71 infants at high risk (HR) or normal risk (NR) for ASD, with data collected at 1 month and 9 months of age. Comparing children with ASD (n = 301) to TDs (n = 432), four regions demonstrated group differences in connectivity: posterior cingulate cortex (PCC), posterior superior temporal gyrus, extrastriate cortex, and anterior prefrontal cortex. At 1 month, none of these regions exhibited group differences between ASD (n = 10), HR-nonASD (n = 15), or NR (n = 18) infants. However, by 9 months, the PCC and extrastriate exhibited atypical connectivity in ASD (n = 11) and HR-nonASD infants (n = 24) compared to NR infants (n = 22). Connectivity did not correlate with symptoms in either sample. Our results demonstrate that differences in network asymmetries associated with ASD risk are observable prior to the age of a reliable clinical diagnosis.

Early development of sleep and brain functional connectivity in term-born and preterm infants

The proper development of sleep and sleep-wake rhythms during early neonatal life is crucial to lifelong neurological well-being. Recent data suggests that infants who have poor quality sleep demonstrate a risk for impaired neurocognitive outcomes. Sleep ontogenesis is a complex process, whereby alternations between rudimentary brain states-active vs. wake and active sleep vs. quiet sleep-mature during the last trimester of pregnancy. If the infant is born preterm, much of this process occurs in the neonatal intensive care unit, where environmental conditions might interfere with sleep. Functional brain connectivity (FC), which reflects the brain's ability to process and integrate information, may become impaired, with ensuing risks of compromised neurodevelopment. However, the specific mechanisms linking sleep ontogenesis to the emergence of FC are poorly understood and have received little investigation, mainly due to the challenges of studying causal links between developmental phenomena and assessing FC in newborn infants. Recent advancements in infant neuromonitoring and neuroimaging strategies will allow for the design of interventions to improve infant sleep quality and quantity. This review discusses how sleep and FC develop in early life, the dynamic relationship between sleep, preterm birth, and FC, and the challenges associated with understanding these processes. IMPACT: Sleep in early life is essential for proper functional brain development, which is essential for the brain to integrate and process information. This process may be impaired in infants born preterm. The connection between preterm birth, early development of brain functional connectivity, and sleep is poorly understood. This review discusses how sleep and brain functional connectivity develop in early life, how these processes might become impaired, and the challenges associated with understanding these processes. Potential solutions to these challenges are presented to provide direction for future research.

Functional brain network community structure in childhood: Unfinished territories and fuzzy boundaries

Adult cortex is organized into distributed functional communities. Yet, little is known about community architecture of children's brains. Here, we uncovered the community structure of cortex in childhood using fMRI data from 670 children aged 9-11 years (48% female, replication sample n=544, 56% female) from the Adolescent Brain and Cognitive Development study. We first applied a data-driven community detection approach to cluster cortical regions into communities, then employed a generative model-based approach called the weighted stochastic block model to further probe community interactions. Children showed similar community structure to adults, as defined by Yeo and colleagues in 2011, in early-developing sensory and motor communities, but differences emerged in transmodal areas. Children have more cortical territory in the limbic community, which is involved in emotion processing, than adults. Regions in association cortex interact more flexibly across communities, creating uncertainty for the model-based assignment algorithm, and perhaps reflecting cortical boundaries that are not yet solidified. Uncertainty was highest for cingulo-opercular areas involved in flexible deployment of cognitive control. Activation and deactivation patterns during a working memory task showed that both the data-driven approach and a set of adult communities statistically capture functional organization in middle childhood. Collectively, our findings suggest that community boundaries are not solidified by middle childhood.

Filtering respiratory motion artifact from resting state fMRI data in infant and toddler populations

The importance of motion correction when processing resting state functional magnetic resonance imaging (rs-fMRI) data is well-established in adult cohorts. This includes adjustments based on self-limited, large amplitude subject head motion, as well as factitious rhythmic motion induced by respiration. In adults, such respiration artifact can be effectively removed by applying a notch filter to the motion trace, resulting in higher amounts of data retained after frame censoring (e.g., "scrubbing") and more reliable correlation values. Due to the unique physiological and behavioral characteristics of infants and toddlers, rs-fMRI processing pipelines, including methods to identify and remove colored noise due to subject motion, must be appropriately modified to accurately reflect true neuronal signal. These younger cohorts are characterized by higher respiration rates and lower-amplitude head movements than adults; thus, the presence and significance of comparable respiratory artifact and the subsequent necessity of applying similar techniques remain unknown. Herein, we identify and characterize the consistent presence of respiratory artifact in rs-fMRI data collected during natural sleep in infants and toddlers across two independent cohorts (aged 8-24 months) analyzed using different pipelines. We further demonstrate how removing this artifact using an age-specific notch filter allows for both improved data quality and data retention in measured results. Importantly, this work reveals the critical need to identify and address respiratory-driven head motion in fMRI data acquired in young populations through the use of age-specific motion filters as a mechanism to optimize the accuracy of measured results in this population.

Executive Functions in Alzheimer’s Disease: A Systematic Review

Background: In Alzheimer’s disease, in addition to memory, attention has been given to cognitive testing due to its interface and connection with memory. Objective: The aim of this study is to take a global view of executive functions and place the concept within the theoretical framework of Alzheimer’s disease dementia, verifying their role in the cognitive functioning of the human mind, as well as how they are compromised in this pathology. Methods: An initial search was carried out in databases such as PubMed, ScienceDirect, and Web of Science. The guiding question presented at the end of the introduction was elaborated from the PICO/PIO/PEO strategy. The selected articles, therefore, answered the guiding question, were made available in full, and published in the period from 2000 to 2020. Studies without specific methodology and which correlated with other diseases or other types of dementia were excluded. To meet the objective, an integrative literature review was adopted. Results: The results indicate that, although the tests to verify the performance of cognitive functions have their limitations, they bring some evidence that they have been compromised, especially when analyzed periodically during the development of dementia. Conclusion: It is concluded that there is an interference of executive functions in function of Alzheimer’s and that memory and attention are the most evident in this type of dementia.

Alterations in motor functional connectivity in Neonatal Hypoxic Ischemic Encephalopathy

BACKGROUND

Neonatal hypoxic-ischemic encephalopathy (HIE) is the result of global hypoxic-ischemic brain injury in neonates due to asphyxia during birth and is one of the most common causes of severe, long-term neurologic deficits in children. Methods: Resting state fMRI (rs-fMRI) was used to assess potential functional disruptions in the primary and association motor areas in HIE neonates (n = 16) compared to healthy controls (n = 11).

RESULTS

Results demonstrate reduced intra-hemispheric resting state functional connectivity (rs-FC) between primary motor regions (upper extremity and facial motor regions) as well as reduced inter-hemispheric rs-FC in the HIE group. In addition, HIE neonates demonstrated increased rs-FC between motor regions and frontal, temporal and parietal cortices but decreased rs-FC with the cerebellum.

DISCUSSION

These preliminary results provide initial evidence for the disruption of functional communication with the motor network in neonates with HIE. Further studies are necessary to both validate these findings in a larger dataset as well as to determine if rs-fMRI measurements collected at birth may have the potential to serve as a prognostic marker in addition to the traditional combination of clinical measurements and conventional MRI.

Altered Functional Network in Infants With Profound Bilateral Congenital Sensorineural Hearing Loss: A Graph Theory Analysis

Functional magnetic resonance imaging (fMRI) studies have suggested that there is a functional reorganization of brain areas in patients with sensorineural hearing loss (SNHL). Recently, graph theory analysis has brought a new understanding of the functional connectome and topological features in central neural system diseases. However, little is known about the functional network topology changes in SNHL patients, especially in infants. In this study, 34 infants with profound bilateral congenital SNHL and 28 infants with normal hearing aged 11–36 months were recruited. No difference was found in small-world parameters and network efficiency parameters. Differences in global and nodal topologic organization, hub distribution, and whole-brain functional connectivity were explored using graph theory analysis. Both normal-hearing infants and SNHL infants exhibited small-world topology. Furthermore, the SNHL group showed a decreased nodal degree in the bilateral thalamus. Six hubs in the SNHL group and seven hubs in the normal-hearing group were identified. The left middle temporal gyrus was a hub only in the SNHL group, while the right parahippocampal gyrus and bilateral temporal pole were hubs only in the normal-hearing group. Functional connectivity between auditory regions and motor regions, between auditory regions and default-mode-network (DMN) regions, and within DMN regions was found to be decreased in the SNHL group. These results indicate a functional reorganization of brain functional networks as a result of hearing loss. This study provides evidence that functional reorganization occurs in the early stage of life in infants with profound bilateral congenital SNHL from the perspective of complex networks.

OUP accepted manuscript

One of the great frontiers of consciousness science is understanding how early consciousness arises in the development of the human infant. The reciprocal relationship between the default mode network and fronto-parietal networks—the dorsal attention and executive control network—is thought to facilitate integration of information across the brain and its availability for a wide set of conscious mental operations. It remains unknown whether the brain mechanism of conscious awareness is instantiated in infants from birth. To address this gap, we investigated the development of the default mode and fronto-parietal networks and of their reciprocal relationship in neonates. To understand the effect of early neonate age on these networks, we also assessed neonates born prematurely or before term-equivalent age. We used the Developing Human Connectome Project, a unique Open Science dataset which provides a large sample of neonatal functional MRI data with high temporal and spatial resolution. Resting state functional MRI data for full-term neonates (n = 282, age 41.2 weeks ± 12 days) and preterm neonates scanned at term-equivalent age (n = 73, 40.9 weeks ± 14.5 days), or before term-equivalent age (n = 73, 34.6 weeks ± 13.4 days), were obtained from the Developing Human Connectome Project, and for a reference adult group (n = 176, 22–36 years), from the Human Connectome Project. For the first time, we show that the reciprocal relationship between the default mode and dorsal attention network was present at full-term birth or term-equivalent age. Although different from the adult networks, the default mode, dorsal attention and executive control networks were present as distinct networks at full-term birth or term-equivalent age, but premature birth was associated with network disruption. By contrast, neonates before term-equivalent age showed dramatic underdevelopment of high-order networks. Only the dorsal attention network was present as a distinct network and the reciprocal network relationship was not yet formed. Our results suggest that, at full-term birth or by term-equivalent age, infants possess key features of the neural circuitry that enables integration of information across diverse sensory and high-order functional modules, giving rise to conscious awareness. Conversely, they suggest that this brain infrastructure is not present before infants reach term-equivalent age. These findings improve understanding of the ontogeny of high-order network dynamics that support conscious awareness and of their disruption by premature birth.

How prenatal exposures shape the infant brain: Insights from infant neuroimaging studies

Brain development during the prenatal period is rapid and unparalleled by any other time during development. Biological systems undergoing rapid development are at higher risk for disorganizing influences. Therefore, certain prenatal exposures impact brain development, increasing risk for negative neurodevelopmental outcome. While prenatal exposures have been associated with cognitive and behavioral outcomes later in life, the underlying macroscopic brain pathways remain unclear. Here, we review magnetic resonance imaging (MRI) studies investigating the association between prenatal exposures and infant brain development focusing on prenatal exposures via maternal physical health factors, maternal mental health factors, and maternal drug and medication use. Further, we discuss the need for studies to consider multiple prenatal exposures in parallel and suggest future directions for this body of research.

fMRI Evidence for Default Mode Network Deactivation Associated with Rapid Eye Movements in Sleep

System-specific brain responses—time-locked to rapid eye movements (REMs) in sleep—are characteristically widespread, with robust and clear activation in the primary visual cortex and other structures involved in multisensory integration. This pattern suggests that REMs underwrite hierarchical processing of visual information in a time-locked manner, where REMs index the generation and scanning of virtual-world models, through multisensory integration in dreaming—as in awake states. Default mode network (DMN) activity increases during rest and reduces during various tasks including visual perception. The implicit anticorrelation between the DMN and task-positive network (TPN)—that persists in REM sleep—prompted us to focus on DMN responses to temporally-precise REM events. We timed REMs during sleep from the video recordings and quantified the neural correlates of REMs—using functional MRI (fMRI)—in 24 independent studies of 11 healthy participants. A reanalysis of these data revealed that the cortical areas exempt from widespread REM-locked brain activation were restricted to the DMN. Furthermore, our analysis revealed a modest temporally-precise REM-locked decrease—phasic deactivation—in key DMN nodes, in a subset of independent studies. These results are consistent with hierarchical predictive coding; namely, permissive deactivation of DMN at the top of the hierarchy (leading to the widespread cortical activation at lower levels; especially the primary visual cortex). Additional findings indicate REM-locked cerebral vasodilation and suggest putative mechanisms for dream forgetting.

Integrated structural and functional atlases of Asian children from infancy to childhood

The developing brain grows exponentially in the first few years of life. There is a need to have age-appropriate brain atlases that coherently characterize the geometry of the cerebral cortex, white matter tracts, and functional organization. This study employed multi-modal brain images of an Asian cohort and constructed brain structural and functional atlases for 6-month-old infants, 4.5-, 6-, and 7.5-year-old children. We exploited large deformation diffeomorphic metric mapping and probabilistic atlas generation approaches to integrate structural MRI and diffusion weighted images (DWIs) and to create the atlas where white matter tracts well fit into the cortical folding pattern. Based on this structural atlas, we then employed spectral clustering to parcellate the brain into functional networks from resting-state fMRI (rs-fMRI). Our results provided the atlas that characterizes the cortical folding geometry, subcortical regions, deep white matter tracts, as well as functional networks in a stereotaxic coordinate space for the four different age groups. The functional networks consisting of the primary cortex were well established in infancy and remained stable to childhood, while specific higher-order functional networks showed specific patterns of hemispherical, subcortical-cerebellar, and cortical-cortical integration and segregation from infancy to childhood. Our multi-modal fusion analysis demonstrated the use of the integrated structural and functional atlas for understanding coherent patterns of brain anatomical and functional development during childhood. Hence, our atlases can be potentially used to study coherent patterns of brain anatomical and functional development.

Patterns of Infant Amygdala Connectivity Mediate the Impact of High Caregiver Affect on Reducing Infant Smiling: Discovery and Replication

BACKGROUND

Behavioral research indicates that caregiver mood disorders and emotional instability in the early months following childbirth are associated with lower positive emotionality and higher negative emotionality in infants, but the neural mechanisms remain understudied.

METHODS

Using resting-state functional connectivity as a measure of the functional architecture of the early infant brain, we aimed to determine the extent to which connectivity between the amygdala, a key region supporting emotional learning and perception, and large-scale neural networks mediated the association between caregiver affect and anxiety and early infant negative emotionality and positive emotionality. Two samples of infants (first sample: n = 58; second sample: n = 31) 3 months of age underwent magnetic resonance imaging during natural sleep.

RESULTS

During infancy, greater resting-state functional connectivity between the amygdala and the salience network and, to a lesser extent, lower amygdala and executive control network resting-state functional connectivity mediated the effect of greater caregiver postpartum depression and trait anxiety on reducing infant smiling (familywise error-corrected p < .05). Furthermore, results from the first sample were replicated in the second, independent sample, to a greater extent for caregiver depression than for caregiver anxiety.

CONCLUSIONS

We provide evidence of early objective neural markers that can help identify infants who are more likely to be at risk from, versus those who might be protected against, the deleterious effects of caregiver depression and anxiety and reduced positive emotionality.

Maternal trait anxiety symptoms, frontolimbic resting-state functional connectivity, and cognitive development in infancy

Exposure to maternal anxiety symptoms during infancy has been associated with difficulties in development and greater risk for developing anxiety later in life. Although previous studies have examined associations between prenatal maternal distress, infant brain development, and developmental outcomes, it is still largely unclear if there are associations between postnatal anxiety, infant brain development, and cognitive development in infancy. In this study, we used resting-state functional magnetic resonance imaging to examine the association between maternal anxiety symptoms and resting-state functional connectivity in the first year of life. We also examine the association between frontolimbic functional connectivity and infant cognitive development. The sample consisted of 21 infants (mean age = 24.15 months, SD = 4.17) that were scanned during their natural sleep using. We test the associations between maternal trait anxiety symptoms and amygdala-anterior cingulate cortex (ACC) functional connectivity, a neural circuit implicated in early life stress exposure. We also test the associations between amygdala-ACC connectivity and cognitive development. We found a significant negative association between maternal trait anxiety symptoms and left amygdala-right ACC functional connectivity (p < .05, false discovery rate corrected). We found a significant negative association between left amygdala-right ACC functional connectivity and infant cognitive development (p < .05). These findings have potential implications for understanding the role of postpartum maternal anxiety symptoms in functional brain and cognitive development in infancy.

What have we really learned from functional connectivity in clinical populations?

Functional connectivity (FC), or the statistical interdependence of blood-oxygen dependent level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool for probing functional abnormalities in clinical populations due to the promise of the approach across conceptual, technical, and practical levels. With an already vast and steadily accumulating neuroimaging literature on neurodevelopmental, psychiatric, and neurological diseases and disorders in which FC is a primary measure, we aim here to provide a high-level synthesis of major concepts that have arisen from FC findings in a manner that cuts across different clinical conditions and sheds light on overarching principles. We highlight that FC has allowed us to discover the ubiquity of intrinsic functional networks across virtually all brains and clarify typical patterns of neurodevelopment over the lifespan. This understanding of typical FC maturation with age has provided important benchmarks against which to evaluate divergent maturation in early life and degeneration in late life. This in turn has led to the important insight that many clinical conditions are associated with complex, distributed, network-level changes in the brain, as opposed to solely focal abnormalities. We further emphasize the important role that FC studies have played in supporting a dimensional approach to studying transdiagnostic clinical symptoms and in enhancing the multimodal characterization and prediction of the trajectory of symptom progression across conditions. We highlight the unprecedented opportunity offered by FC to probe functional abnormalities in clinical conditions where brain function could not be easily studied otherwise, such as in disorders of consciousness. Lastly, we suggest high priority areas for future research and acknowledge critical barriers associated with the use of FC methods, particularly those related to artifact removal, data denoising and feasibility in clinical contexts.

Resting state functional networks in 1-to-3-year-old typically developing children

Brain functional networks undergo substantial development and refinement during the first years of life. Yet, the maturational pathways of functional network development remain poorly understood. Using resting-state fMRI data acquired during natural sleep from 24 typically developing toddlers, ages 1.5-3.5 years, we aimed to examine the large-scale resting-state functional networks and their relationship with age and developmental skills. Specifically, two network organization indices reflecting network connectivity and spatial variability were derived. Our results revealed that reduced spatial variability or increased network homogeneity in one of the default mode network components was associated with age, with older children displaying less spatially variable posterior DMN subcomponent, consistent with the notion of increased spatial and functional specialization. Further, greater network homogeneity in higher-order functional networks, including the posterior default mode, salience, and language networks, was associated with more advanced developmental skills measured with a standardized assessment of early learning, regardless of age. These results not only improve our understanding of brain functional network development during toddler years, but also inform the relationship between brain network organization and emerging cognitive and behavioral skills.

Developmental heatmaps of brain functional connectivity from newborns to 6-year-olds

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Heatmaps quantify degrees of developmental changes in functional connectivity.

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More changes are observed in the first than second postnatal year, driven by girls.

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Most change is observed from ages 2–4 compared with any other age span.

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Limbic and subcortical areas show more changes than primary sensory regions.

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Consistent trajectories of functional connectivity are found across validations.

Different functional networks exhibit distinct longitudinal trajectories throughout development, but the timeline of the dynamics of functional connectivity across the whole brain remains to be elucidated. Here we used resting-state fMRI to investigate the development of voxel-level changes in functional connectivity across the first six years of life. Globally, we found that developmental changes in functional connectivity are nonlinear with more changes during the first postnatal year than the second, followed by most significant changes from ages 2–4 and from ages 4–6. However, the overall global difference observed between the first and second year appears to have been driven by girls. Limbic and subcortical areas consistently demonstrated the most substantial changes, whereas primary sensory areas were the most stable. These patterns were consistent in full-term and preterm subgroups. Validation on randomly divided subsamples as well as in an independent cross-sectional sample revealed global patterns consistent with the main results. Overall, the derived developmental heatmaps reveal novel dynamics underlying functional circuit development during the first 6 years of life.

Variability in Infants' Functional Brain Network Connectivity Is Associated With Differences in Affect and Behavior

Variability in functional brain network connectivity has been linked to individual differences in cognitive, affective, and behavioral traits in adults. However, little is known about the developmental origins of such brain-behavior correlations. The current study examined functional brain network connectivity and its link to behavioral temperament in typically developing newborn and 1-month-old infants (M [age] = 25 days; N = 75) using functional near-infrared spectroscopy (fNIRS). Specifically, we measured long-range connectivity between cortical regions approximating fronto-parietal, default mode, and homologous-interhemispheric networks. Our results show that connectivity in these functional brain networks varies across infants and maps onto individual differences in behavioral temperament. Specifically, connectivity in the fronto-parietal network was positively associated with regulation and orienting behaviors, whereas connectivity in the default mode network showed the opposite effect on these behaviors. Our analysis also revealed a significant positive association between the homologous-interhemispheric network and infants' negative affect. The current results suggest that variability in long-range intra-hemispheric and cross-hemispheric functional connectivity between frontal, parietal, and temporal cortex is associated with individual differences in affect and behavior. These findings shed new light on the brain origins of individual differences in early-emerging behavioral traits and thus represent a viable novel approach for investigating developmental trajectories in typical and atypical neurodevelopment.

Adverse childhood experiences and future self-rated health: a prospective cohort study

BACKGROUND

Negative life events (re) occurring during childhood is often described as adverse childhood experiences (ACEs) and may have long-lasting negative effects on health. Previous studies on the association between ACEs and self-rated health (SRH) have primarily been focusing on chronic diseases in elderly, non-Scandinavian populations using a cross-sectional design. The aim of the study was to examine the associations between ACEs and SRH in early adulthood and to investigate if disadvantageous health-behavioral strategies explain the association between ACEs and SRH.

METHODS

A prospective cohort study using data from The West Jutland Cohort Study (N = 2.255). Baseline data on exposure to ACEs were collected from surveys at the age of 15 and 18 and respondents were categorized into having experienced 0, 1-2, 3 or > 4 ACEs. The outcome SRH stems from surveys at the age of 21 and 28 and was dichotomized into moderate and good SRH. The association between ACE-categories and SRH at age 21 and 28 were analyzed separately by logistic regression with a two-step adjustment model, adjusting for potential confounders and disadvantageous health-behavioral strategies.

RESULTS

More than half of the participants reported at least one ACE (56.3%) with "bullying" and "loss of parent, parental separation or divorce" being the most prevalent. Participants who reported > 4 ACEs, compared to those with 0 ACEs, had a 2.6-fold increased odds (95% CI 1.3; 5.1) of having moderate SRH at the age of 21, and a 2.7-fold increased odds (95% CI 1.4; 5.4) of moderate SRH at the age of 28 years, when adjusted for potential confounders. Further, small attenuations of the estimates were seen when adjusting for disadvantageous health-behavioral strategies. A significant exposure response relationship between the ACE-categories and moderate SRH were seen both at age 21 and 28.

CONCLUSION

The study showed an association between ACEs and moderate SRH in young adulthood, and experiencing multiple ACEs increased the odds of reporting moderate SRH. Information on ACEs could help identifying people with a higher risk of future health problems and accentuates a growing need for early prevention in homes with children who has experienced adverse events.

Annual Research Review: Anterior Modifiers in the Emergence of Neurodevelopmental Disorders (AMEND)-a systems neuroscience approach to common developmental disorders

We present the Anterior Modifiers in the Emergence of Neurodevelopmental Disorders (AMEND) framework, designed to reframe the field of prospective studies of neurodevelopmental disorders. In AMEND we propose conceptual, statistical and methodological approaches to separating markers of early-stage perturbations from later developmental modifiers. We describe the evidence for, and features of, these interacting components before outlining analytical approaches to studying how different profiles of early perturbations and later modifiers interact to produce phenotypic outcomes. We suggest this approach could both advance our theoretical understanding and clinical approach to the emergence of developmental psychopathology in early childhood.

MRI of the Neonatal Brain: A Review of Methodological Challenges and Neuroscientific Advances

In recent years, exploration of the developing brain has become a major focus for researchers and clinicians in an attempt to understand what allows children to acquire amazing and unique abilities, as well as the impact of early disruptions (eg, prematurity, neonatal insults) that can lead to a wide range of neurodevelopmental disorders. Noninvasive neuroimaging methods such as MRI are essential to establish links between the brain and behavioral changes in newborns and infants. In this review article, we aim to highlight recent and representative studies using the various techniques available: anatomical MRI, quantitative MRI (relaxometry, diffusion MRI), multiparametric approaches, and functional MRI. Today, protocols use 1.5 or 3T MRI scanners, and specialized methodologies have been put in place for data acquisition and processing to address the methodological challenges specific to this population, such as sensitivity to motion. MR sequences must be adapted to the brains of newborns and infants to obtain relevant good soft-tissue contrast, given the small size of the cerebral structures and the incomplete maturation of tissues. The use of age-specific image postprocessing tools is also essential, as signal and contrast differ from the adult brain. Appropriate methodologies then make it possible to explore multiple neurodevelopmental mechanisms in a precise way, and assess changes with age or differences between groups of subjects, particularly through large-scale projects. Although MRI measurements only indirectly reflect the complex series of dynamic processes observed throughout development at the molecular and cellular levels, this technique can provide information on brain morphology, structural connectivity, microstructural properties of gray and white matter, and on the functional architecture. Finally, MRI measures related to clinical, behavioral, and electrophysiological markers have a key role to play from a diagnostic and prognostic perspective in the implementation of early interventions to avoid long-term disabilities in children. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 1.

Hippocampal functional connectivity development during the first two years indexes 4-year working memory performance

The hippocampus is a key limbic region involved in higher-order cognitive processes including learning and memory. Although both typical and atypical functional connectivity patterns of the hippocampus have been well-studied in adults, the developmental trajectory of hippocampal connectivity during infancy and how it relates to later working memory performance remains to be elucidated. Here we used resting state fMRI (rsfMRI) during natural sleep to examine the longitudinal development of hippocampal functional connectivity using a large cohort (N = 202) of infants at 3 weeks (neonate), 1 year, and 2 years of age. Next, we used multivariate modeling to investigate the relationship between both cross-sectional and longitudinal growth in hippocampal connectivity and 4-year working memory outcome. Results showed robust local functional connectivity of the hippocampus in neonates with nearby limbic and subcortical regions, with dramatic maturation and increasing connectivity with key default mode network (DMN) regions resulting in adult-like topology of the hippocampal functional connectivity by the end of the first year. This pattern was stabilized and further consolidated by 2 years of age. Importantly, cross-sectional and longitudinal measures of hippocampal connectivity in the first year predicted subsequent behavioral measures of working memory at 4 years of age. Taken together, our findings provide insight into the development of hippocampal functional circuits underlying working memory during this early critical period.

Functional difficulties mediate the association between exposure to adverse childhood experiences and headaches among children: Findings from a population-based study

BACKGROUND

Adverse childhood experiences (ACEs) are commonly observed in the general population and often have lasting neurological and physiological effects. Previous studies have found links between exposure to ACEs, headaches, and functional difficulties in adults. However, little is known about the mechanisms through which exposure to ACEs is associated with headaches among children.

OBJECTIVE

To examine the association between exposure to ACEs and headaches in children, and whether functional difficulties mediate this association.

METHODS

Data for this cross-sectional secondary analysis study came from the 2017-2018 National Survey of Children's Health. The sample analyzed in this study was 40,953 children who were between ages 3 and 17 years. We adjusted for the complexity of the sampling design and used structural equation modeling to examine the mediating effect of functional difficulties in the association between exposure to ACEs and headaches.

RESULTS

Based on parent reports, we found that 4.1% (1697/40,953) of the children reported frequent or severe headaches, and 9.5% (3906/40,953) were exposed to three or more ACEs. About one in four children (23.4%; 9601/40,953) had at least one functional difficulty. The results show that exposure to ACEs was directly positively associated with functional difficulties (β = 0.16, p < 0.001, 95% CI = 0.15-0.17), and functional difficulties were in turn positively associated with headaches (β = 0.17, p < 0.001, 95% CI = 0.12-0.22). The Sobel test of indirect effect showed that functional difficulties partially mediated the association between exposure to ACEs and headaches (β = 0.027, p < 0.001, 95% CI = 0.022-0.029). Also, older children and children with brain injury were more likely to report experiencing headaches.

CONCLUSIONS

The findings from this study suggest an association between exposure to ACEs and headaches among children, and functional difficulties partially mediate this association.

A Dynamic Systems Framework for Gender/Sex Development: From Sensory Input in Infancy to Subjective Certainty in Toddlerhood

From birth to 15 months infants and caregivers form a fundamentally intersubjective, dyadic unit within which the infant's ability to recognize gender/sex in the world develops. Between about 18 and 36 months the infant accumulates an increasingly clear and subjective sense of self as female or male. We know little about how the precursors to gender/sex identity form during the intersubjective period, nor how they transform into an independent sense of self by 3 years of age. In this Theory and Hypothesis article I offer a general framework for thinking about this problem. I propose that through repetition and patterning, the dyadic interactions in which infants and caregivers engage imbue the infant with an embodied, i.e., sensori-motor understanding of gender/sex. During this developmental period (which I label Phase 1) gender/sex is primarily an intersubjective project. From 15 to 18 months (which I label Phase 2) there are few reports of newly appearing gender/sex behavioral differences, and I hypothesize that this absence reflects a period of developmental instability during which there is a transition from gender/sex as primarily inter-subjective to gender/sex as primarily subjective. Beginning at 18 months (i.e., the start of Phase 3), a toddler's subjective sense of self as having a gender/sex emerges, and it solidifies by 3 years of age. I propose a dynamic systems perspective to track how infants first assimilate gender/sex information during the intersubjective period (birth to 15 months); then explore what changes might occur during a hypothesized phase transition (15 to 18 months), and finally, review the emergence and initial stabilization of individual subjectivity-the period from 18 to 36 months. The critical questions explored focus on how to model and translate data from very different experimental disciplines, especially neuroscience, physiology, developmental psychology and cognitive development. I close by proposing the formation of a research consortium on gender/sex development during the first 3 years after birth.

Structural development of cortical lobes during the first 6 months of life in infant macaques

This study mapped the developmental trajectories of cortical regions in comparison to overall brain growth in typically developing, socially-housed infant macaques. Volumetric changes of cortical brain regions were examined longitudinally between 2-24 weeks of age (equivalent to the first 2 years in humans) in 21 male rhesus macaques. Growth of the prefrontal, frontal, parietal, occipital, and temporal cortices (visual and auditory) was examined using MRI and age-specific infant macaque brain atlases developed by our group. Results indicate that cortical volumetric development follows a cubic growth curve, but maturational timelines and growth rates are region-specific. Total intracranial volume (ICV) increased significantly during the first 5 months of life, leveling off thereafter. Prefrontal and temporal visual cortices showed fast volume increases during the first 16 weeks, followed by a plateau, and significant growth again between 20-24 weeks. Volume of the frontal and temporal auditory cortices increased substantially between 2-24 weeks. The parietal cortex showed a significant volume increase during the first 4 months, whereas the volume of the occipital lobe increased between 2-12 weeks and plateaued thereafter. These developmental trajectories show similarities to cortical growth in human infants, providing foundational information necessary to build nonhuman primate (NHP) models of human neurodevelopmental disorders.

Group-level cortical functional connectivity patterns using fNIRS: assessing the effect of bilingualism in young infants

Significance: Early monolingual versus bilingual experience induces adaptations in the development of linguistic and cognitive processes, and it modulates functional activation patterns during the first months of life. Resting-state functional connectivity (RSFC) is a convenient approach to study the functional organization of the infant brain. RSFC can be measured in infants during natural sleep, and it allows to simultaneously investigate various functional systems. Adaptations have been observed in RSFC due to a lifelong bilingual experience. Investigating whether bilingualism-induced adaptations in RSFC begin to emerge early in development has important implications for our understanding of how the infant brain's organization can be shaped by early environmental factors. Aims: We attempt to describe RSFC using functional near-infrared spectroscopy (fNIRS) and to examine whether it adapts to early monolingual versus bilingual environments. We also present an fNIRS data preprocessing and analysis pipeline that can be used to reliably characterize RSFC in development and to reduce false positives and flawed results interpretations. Methods: We measured spontaneous hemodynamic brain activity in a large cohort ( N = 99 ) of 4-month-old monolingual and bilingual infants using fNIRS. We implemented group-level approaches based on independent component analysis to examine RSFC, while providing proper control for physiological confounds and multiple comparisons. Results: At the group level, we describe the functional organization of the 4-month-old infant brain in large-scale cortical networks. Unbiased group-level comparisons revealed no differences in RSFC between monolingual and bilingual infants at this age. Conclusions: High-quality fNIRS data provide a means to reliably describe RSFC patterns in the infant brain. The proposed group-level RSFC analyses allow to assess differences in RSFC across experimental conditions. An effect of early bilingual experience in RSFC was not observed, suggesting that adaptations might only emerge during explicit linguistic tasks, or at a later point in development.

Attention recruits frontal cortex in human infants

Young infants learn about the world by overtly shifting their attention to perceptually salient events. In adults, attention recruits several brain regions spanning the frontal and parietal lobes. However, it is unclear whether these regions are sufficiently mature in infancy to support attention and, more generally, how infant attention is supported by the brain. We used event-related functional magnetic resonance imaging (fMRI) in 24 sessions from 20 awake behaving infants 3 mo to 12 mo old while they performed a child-friendly attentional cuing task. A target was presented to either the left or right of the infant's fixation, and offline gaze coding was used to measure the latency with which they saccaded to the target. To manipulate attention, a brief cue was presented before the target in three conditions: on the same side as the upcoming target (valid), on the other side (invalid), or on both sides (neutral). All infants were faster to look at the target on valid versus invalid trials, with valid faster than neutral and invalid slower than neutral, indicating that the cues effectively captured attention. We then compared the fMRI activity evoked by these trial types. Regions of adult attention networks activated more strongly for invalid than valid trials, particularly frontal regions. Neither behavioral nor neural effects varied by infant age within the first year, suggesting that these regions may function early in development to support the orienting of attention. Together, this furthers our mechanistic understanding of how the infant brain controls the allocation of attention.

The Developing Human Connectome Project: typical and disrupted perinatal functional connectivity

The Developing Human Connectome Project is an Open Science project that provides the first large sample of neonatal functional MRI data with high temporal and spatial resolution. These data enable mapping of intrinsic functional connectivity between spatially distributed brain regions under normal and adverse perinatal circumstances, offering a framework to study the ontogeny of large-scale brain organization in humans. Here, we characterize in unprecedented detail the maturation and integrity of resting state networks (RSNs) at term-equivalent age in 337 infants (including 65 born preterm). First, we applied group independent component analysis to define 11 RSNs in term-born infants scanned at 43.5–44.5 weeks postmenstrual age (PMA). Adult-like topography was observed in RSNs encompassing primary sensorimotor, visual and auditory cortices. Among six higher-order, association RSNs, analogues of the adult networks for language and ocular control were identified, but a complete default mode network precursor was not. Next, we regressed the subject-level datasets from an independent cohort of infants scanned at 37–43.5 weeks PMA against the group-level RSNs to test for the effects of age, sex and preterm birth. Brain mapping in term-born infants revealed areas of positive association with age across four of six association RSNs, indicating active maturation in functional connectivity from 37 to 43.5 weeks PMA. Female infants showed increased connectivity in inferotemporal regions of the visual association network. Preterm birth was associated with striking impairments of functional connectivity across all RSNs in a dose-dependent manner; conversely, connectivity of the superior parietal lobules within the lateral motor network was abnormally increased in preterm infants, suggesting a possible mechanism for specific difficulties such as developmental coordination disorder, which occur frequently in preterm children. Overall, we found a robust, modular, symmetrical functional brain organization at normal term age. A complete set of adult-equivalent primary RSNs is already instated, alongside emerging connectivity in immature association RSNs, consistent with a primary-to-higher order ontogenetic sequence of brain development. The early developmental disruption imposed by preterm birth is associated with extensive alterations in functional connectivity.

Fundamental functional differences between gyri and sulci: implications for brain function, cognition, and behavior

Folding of the cerebral cortex is a prominent characteristic of mammalian brains. Alterations or deficits in cortical folding are strongly correlated with abnormal brain function, cognition, and behavior. Therefore, a precise mapping between the anatomy and function of the brain is critical to our understanding of the mechanisms of brain structural architecture in both health and diseases. Gyri and sulci, the standard nomenclature for cortical anatomy, serve as building blocks to make up complex folding patterns, providing a window to decipher cortical anatomy and its relation with brain functions. Huge efforts have been devoted to this research topic from a variety of disciplines including genetics, cell biology, anatomy, neuroimaging, and neurology, as well as involving computational approaches based on machine learning and artificial intelligence algorithms. However, despite increasing progress, our understanding of the functional anatomy of gyro-sulcal patterns is still in its infancy. In this review, we present the current state of this field and provide our perspectives of the methodologies and conclusions concerning functional differentiation between gyri and sulci, as well as the supporting information from genetic, cell biology, and brain structure research. In particular, we will further present a proposed framework for attempting to interpret the dynamic mechanisms of the functional interplay between gyri and sulci. Hopefully, this review will provide a comprehensive summary of anatomo-functional relationships in the cortical gyro-sulcal system together with a consideration of how these contribute to brain function, cognition, and behavior, as well as to mental disorders.

Imaging the rapidly developing brain: Current challenges for MRI studies in the first five years of life

Rapid and widespread changes in brain anatomy and physiology in the first five years of life present substantial challenges for developmental structural, functional, and diffusion MRI studies. One persistent challenge is that methods best suited to earlier developmental stages are suboptimal for later stages, which engenders a trade-off between using different, but age-appropriate, methods for different developmental stages or identical methods across stages. Both options have potential benefits, but also biases, as pipelines for each developmental stage can be matched on methods or the age-appropriateness of methods, but not both. This review describes the data acquisition, processing, and analysis challenges that introduce these potential biases and attempts to elucidate decisions and make recommendations that would optimize developmental comparisons.

Spontaneous synchronous network activity in the neonatal development of mPFC in mice

Spontaneous Synchronous Network Activity (SSA) is a hallmark of neurodevelopment found in numerous central nervous system structures, including neocortex. SSA occurs during restricted developmental time‐windows, commonly referred to as critical periods in sensory neocortex. Although part of the neocortex, the critical period for SSA in the medial prefrontal cortex (mPFC) and the underlying mechanisms for generation and propagation are unknown. Using Ca²⁺ imaging and whole‐cell patch‐clamp in an acute mPFC slice mouse model, the development of spontaneous activity and SSA was investigated at cellular and network levels during the two first postnatal weeks. The data revealed that developing mPFC neuronal networks are spontaneously active and exhibit SSA in the first two postnatal weeks, with peak synchronous activity at postnatal days (P)8–9. Networks remain active but are desynchronized by the end of this 2‐week period. SSA was driven by excitatory ionotropic glutamatergic transmission with a small contribution of excitatory GABAergic transmission at early time points. The neurohormone oxytocin desynchronized SSA in the first postnatal week only without affecting concurrent spontaneous activity. By the end of the second postnatal week, inhibiting GABA_A receptors restored SSA. These findings point to the emergence of GABA_A receptor‐mediated inhibition as a major factor in the termination of SSA in mouse mPFC.

Clinical and Preclinical Evidence for Adverse Neurodevelopment after Postnatal Zika Virus Infection

Although the Zika virus (ZIKV) typically causes mild or no symptoms in adults, during the 2015−2016 outbreak, ZIKV infection in pregnancy resulted in a spectrum of diseases in infants, including birth defects and neurodevelopmental disorders identified in childhood. While intense clinical and basic science research has focused on the neurodevelopmental outcomes of prenatal ZIKV infection, less is known about the consequences of infection during early life. Considering the neurotropism of ZIKV and the rapidly-developing postnatal brain, it is important to understand how infection during infancy may disrupt neurodevelopment. This paper reviews the current knowledge regarding early postnatal ZIKV infection. Emerging clinical evidence supports the hypothesis that ZIKV infection during infancy can result in negative neurologic consequences. However, clinical data regarding postnatal ZIKV infection in children are limited; as such, animal models play an important role in understanding the potential complications of ZIKV infection related to the vulnerable developing brain. Preclinical data provide insight into the potential behavioral, cognitive, and motor domains that clinical studies should examine in pediatric populations exposed to ZIKV during infancy.

Premature Birth and Developmental Programming: Mechanisms of Resilience and Vulnerability

The third trimester of pregnancy represents a sensitive phase for infant brain plasticity when a series of fast-developing cellular events (synaptogenesis, neuronal migration, and myelination) regulates the development of neural circuits. Throughout this dynamic period of growth and development, the human brain is susceptible to stress. Preterm infants are born with an immature brain and are, while admitted to the neonatal intensive care unit, precociously exposed to stressful procedures. Postnatal stress may contribute to altered programming of the brain, including key systems such as the hypothalamic-pituitary-adrenal axis and the autonomic nervous system. These neurobiological systems are promising markers for the etiology of several affective and social psychopathologies. As preterm birth interferes with early development of stress-regulatory systems, early interventions might strengthen resilience factors and might help reduce the detrimental effects of chronic stress exposure. Here we will review the impact of stress following premature birth on the programming of neurobiological systems and discuss possible stress-related neural circuits and pathways involved in resilience and vulnerability. Finally, we discuss opportunities for early intervention and future studies.

Hypofunctional connectivity between the posterior cingulate cortex and ventromedial prefrontal cortex in autism: Evidence from coordinate-based imaging meta-analysis

BACKGROUND

Underconnectivity in the posterior cingulate cortex (PCC) may be associated with a weakened ability to interpret social signals in autism spectrum disorder (ASD) and result in cognitive inflexibility - a hallmark feature of ASD. However, previous neuroimaging studies using resting-state functional magnetic resonance imaging in ASD reported inconsistent findings on functional connectivity of the PCC. This study investigated the aberrant resting-state functional connectivity of the PCC in ASD using multilevel kernel density analysis.

METHODS

Online databases (MEDLINE/PubMed) were searched for PCC-based functional connectivity in ASD. Ten studies (501 subjects; 161 reported foci) met the inclusion criteria of this meta-analysis.

RESULTS

We found one consistent and strong abnormal functional connectivity of ASD during the resting state, which was the hypoconnectivity between the PCC and ventromedial prefrontal cortex (VMPFC). Importantly, the Jackknife sensitivity analysis revealed that the VMPFC cluster was stably hypoconnected with the PCC in ASD (maximum spatial overlap rate: 100%).

CONCLUSIONS

The reduced PCC-VMPFC functional coupling may provide an early insight into the effects of ASD on multiple dimensions of functioning, including higher-order cognitive and complex social functions.

Neonatal brain connectivity outliers identify over forty percent of IQ outliers at 4 years of age

BACKGROUND

Defining reliable brain markers for the prediction of abnormal behavioral outcomes remains an urgent but extremely challenging task in neuroscience research. This is particularly important for infant studies given the most dramatic brain and behavioral growth during infancy.

METHODS

In this study, we proposed a novel prediction scheme through abstracting individual newborn's whole-brain functional connectivity pattern to three outlier measures (Triple O) and tested the hypothesis that neonates identified as "brain outliers" based on Triple O were more likely to develop as IQ outliers at 4 years of age. Without need for training with behavioral data, Triple O represents a novel proof-of-concept approach to predict later IQ outcomes based on neonatal brain data.

RESULTS

Triple O correctly identified 42.1% true IQ outliers among a mixed cohort of 175 newborns with different term, twin, and maternal disorder statuses. Triple O also reached a high level of specificity (96.2%) and overall accuracy (90.3%). Further incorporating a demographic information indicator, the enhanced Triple O+ could further differentiate between high and low 4YR IQ outliers. Validation tests against seven independent reference samples revealed highly consistent results and a minimum sample size of ~50 for robust performance.

CONCLUSIONS

Considering that postnatal brain growth and various environmental factors likely also contribute to 4YR IQ, the fact that Triple O, based purely on neonatal functional connectivity data, could identify >40% of 4YR IQ outliers is striking. Together with the very high level of specificity, each outlier predicted by Triple O represents a meaningful risk but future efforts are needed to explore ways to identify the rest of outliers. Overall, with no need for training, a high level of robustness, and a minimal requirement on sample size, the proposed Triple O approach demonstrates great potential to predict later outlying IQ performances using neonatal functional connectivity data.

The intrinsic neonatal hippocampal network: rsfMRI findings

Although both animal data and human data suggest that the hippocampus is immature at birth, to date, there are no direct assessments of human hippocampal functional connectivity (FC) very early in life. Our study explores the FC of the hippocampus to the cortex at birth, allowing insight into the development of human memory systems. In particular, we find that adults and neonates exhibit vastly different hippocampal connectivity profiles—a finding that likely has large developmental implications.

Development and Emergence of Individual Variability in the Functional Connectivity Architecture of the Preterm Human Brain

Individual variability in human brain networks underlies individual differences in cognition and behaviors. However, researchers have not conclusively determined when individual variability patterns of the brain networks emerge and how they develop in the early phase. Here, we employed resting-state functional MRI data and whole-brain functional connectivity analyses in 40 neonates aged around 31-42 postmenstrual weeks to characterize the spatial distribution and development modes of individual variability in the functional network architecture. We observed lower individual variability in primary sensorimotor and visual areas and higher variability in association regions at the third trimester, and these patterns are generally similar to those of adult brains. Different functional systems showed dramatic differences in the development of individual variability, with significant decreases in the sensorimotor network; decreasing trends in the visual, subcortical, and dorsal and ventral attention networks, and limited change in the default mode, frontoparietal and limbic networks. The patterns of individual variability were negatively correlated with the short- to middle-range connection strength/number and this distance constraint was significantly strengthened throughout development. Our findings highlight the development and emergence of individual variability in the functional architecture of the prenatal brain, which may lay network foundations for individual behavioral differences later in life.

Neonatal brain volume as a marker of differential susceptibility to parenting quality and its association with neurodevelopment across early childhood

Parenting quality is associated with child cognitive and executive functions (EF), which are important predictors of social and academic development. However, children vary in their susceptibility to parenting behaviors, and the neurobiological underpinnings of this susceptibility are poorly understood. In a prospective longitudinal study, we examined whether neonatal total brain volume (TBV) and subregions of interest (i.e., hippocampus (HC) and anterior cingulate gyrus (ACG)) moderate the association between maternal sensitivity and cognitive/EF development across early childhood. Neonates underwent a brain magnetic resonance imaging scan. Their cognitive performance and EF was characterized at 2.0 ± 0.1 years (N = 53) and at 4.9 ± 0.8 years (N = 36) of age. Maternal sensitivity was coded based on observation of a standardized play situation at 6-mo postpartum. Neonatal TBV moderated the association between maternal sensitivity and 2-year working memory as well as all 5-year cognitive outcomes, suggesting that the positive association between maternal sensitivity and child cognition was observed only among children with large or average but not small TBV as neonates. Similar patterns were observed for TBV-corrected HC and ACG volumes. The findings suggest that larger neonatal TBV, HC and ACG may underlie susceptibility to the environment and affect the degree to which parenting quality shapes long-term cognitive development.

Exploring functional brain activity in neonates: A resting-state fMRI study

The human brain is born with a certain maturity, but quantitatively measuring the maturation and development of functional brain activity in neonates remains a topic of vigorous scientific research, especially the dynamic characteristics. To address this, T1w, T2w, and resting-state functional magnetic resonance imaging (rs-fMRI) data from 40 full-term healthy neonates and 38 adults were adopted in this study. Group differences of local brain activity and functional connectivity between neonates and adults from both static and dynamic perspectives were explored. We found that the neonatal brain is largely immature in general. Sensorimotor areas were the most active, well-connected, and temporally dynamic. Compared with adults, visual and primary auditory areas in neonates showed higher or similar local activity but lower static and dynamic connections with other brain regions. Our findings provide new references and valuable insights for time-varying and local brain functional activity in neonates.