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

Functional connectome through the human life span

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimer's disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.

Why did my seizures start now? Influences of lesion connectivity and genetic etiology on age at seizure onset in focal epilepsy

OBJECTIVE

Patients with focal, lesional epilepsy present with seizures at variable ages. Larger lesion size and overlap with sensorimotor or default mode network (DMN) have been associated with younger age at seizure onset in cohorts with mixed types of focal cortical dysplasia (FCD). Here, we studied determinants of age at seizure onset in patients with bottom-of-sulcus dysplasia (BOSD), a discrete type of FCD with highly localized epileptogenicity.

METHODS

Eighty-four patients (77% operated) with BOSD were studied. Demographic, histopathologic, and genetic findings were recorded. BOSD volume and anatomical, primary versus association, rostral versus caudal, and functional network locations were determined. Normative functional connectivity analyses were performed using each BOSD as a region of interest in resting-state functional magnetic resonance imaging data of healthy children. Variables were correlated with age at seizure onset.

RESULTS

Median age at seizure onset was 5.4 (interquartile range = 2-7.9) years. Of 50 tested patients, 22 had somatic and nine had germline pathogenic mammalian target of rapamycin (mTOR) pathway variants. Younger age at seizure onset was associated with greater BOSD volume (p = .002), presence of a germline pathogenic variant (p = .04), DMN overlap (p = .04), and increased functional connectivity with the DMN (p < .05, false discovery rate corrected). Location within sensorimotor cortex and networks was not associated with younger age at seizure onset in our relatively small but homogenous cohort.

SIGNIFICANCE

Greater lesion size, pathogenic mTOR pathway germline variants, and DMN connectivity are associated with younger age at seizure onset in small FCD. Our findings strengthen the suggested role of DMN connectivity in the onset of FCD-related focal epilepsy and reveal novel contributions of genetic etiology.

Constructing fine-grained spatiotemporal neonatal functional atlases with spectral functional network learning

The early stages of human development are increasingly acknowledged as pivotal in laying the groundwork for subsequent behavioral and cognitive development. Spatiotemporal (4D) brain functional atlases are important in elucidating the development of human brain functions. However, the scarcity of such atlases for early life stages stems from two primary challenges: (1) the significant noise in functional magnetic resonance imaging (fMRI) that complicates the generation of high-quality atlases for each age group, and (2) the rapid and complex changes in the early human brain that hinder the maintenance of temporal consistency in 4D atlases. This study tackles these challenges by integrating low-rank tensor learning with spectral embedding, thereby proposing a novel, data-driven 4D functional atlas generation framework based on spectral functional network learning (SFNL). This method utilizes low-rank tensor learning to capture common functional connectivity (FC) patterns across different ages, thus optimizing FCs for each age group to improve the temporal consistency of functional networks. Incorporating spectral embedding aids in mitigating potential noise in FC networks derived from fMRI data by reconstructing networks in the spectral space. Utilizing SFNL-generated functional networks enables the creation of consistent and highly qualified spatiotemporal functional atlases. The framework was applied to the developing Human Connectome Project (dHCP) dataset, generating the first neonatal 4D functional atlases with fine-grained temporal and spatial resolutions. Experimental evaluations focusing on functional homogeneity, reliability, and temporal consistency demonstrated the superiority of our framework compared to existing methods for constructing 4D atlases. Additionally, network analysis experiments, including individual identification, functional systems development, and local efficiency assessments, further corroborate the efficacy and robustness of the generated atlases. The 4D atlases and related codes will be made publicly accessible (https://github.com/zhaoyunxi/neonate-atlases).

A Systematic Review over the Effect of Early Infant Diet on Neurodevelopment: Insights from Neuroimaging

The optimization of infant neuronal development through nutrition is an increasingly studied area. While human milk consumption during infancy is thought to give a slight cognitive advantage throughout early childhood in comparison to commercial formula, the biological underpinnings of this process are less well-known and debated in the literature. This systematic review seeks to quantitatively analyze whether early diet affects infant neurodevelopment as measured by various neuroimaging modalities and techniques. Results presented suggest that human milk does have a slight positive impact on the structural development of the infant brain-and that this impact is larger in preterm infants. Other diets with distinct macronutrient compositions were also considered, although these had more conflicting results.

Development of segregation and integration of functional connectomes during the first 1,000 days

The first 1,000 days of human life lay the foundation for brain development and later cognitive growth. However, the developmental rules of the functional connectome during this critical period remain unclear. Using high-resolution, longitudinal, task-free functional magnetic resonance imaging data from 930 scans of 665 infants aged 28 postmenstrual weeks to 3 years, we report the early maturational process of connectome segregation and integration. We show the dominant development of local connections alongside a few global connections, the shift of brain hubs from primary regions to high-order association cortices, the developmental divergence of network segregation and integration along the anterior-posterior axis, the prediction of neurocognitive outcomes, and their associations with gene expression signatures of microstructural development and neuronal metabolic pathways. These findings advance our understanding of the principles of connectome remodeling during early life and its neurobiological underpinnings and have implications for studying typical and atypical development.

Rest to Promote Learning: A Brain Default Mode Network Perspective

The brain often switches freely between focused attention and divergent thinking, and the Default Mode Network (DMN) is activated during brain rest. Since its discovery, the DMN, together with its function and characteristics, indicates that learning does not stop when the brain "rests". Therefore, DMN plays an important role in learning. Neural activities such as beta wave rhythm regulation, "subconscious" divergence thinking mode initiation, hippocampal function, and neural replay occur during default mode, all of which explains that "rest" promotes learning. This paper summarized the function and neural mechanism of DMN in learning and proposed that the DMN plays an essential role in learning, which is that it enables rest to promote learning.

Spatiotemporal cerebral blood flow dynamics underlies emergence of the limbic-sensorimotor-association cortical gradient in human infancy

Infant cerebral blood flow (CBF) delivers nutrients and oxygen to fulfill brain energy consumption requirements for the fastest period of postnatal brain development across lifespan. However, organizing principle of whole-brain CBF dynamics during infancy remains obscure. Leveraging a unique cohort of 100+ infants with high-resolution arterial spin labeled MRI, we found the emergence of the cortical hierarchy revealed by highest-resolution infant CBF maps available to date. Infant CBF across cortical regions increased in a biphasic pattern with initial rapid and sequentially slower rate, with break-point ages increasing along the limbic-sensorimotor-association cortical gradient. Increases in CBF in sensorimotor cortices were associated with enhanced language and motor skills, and frontoparietal association cortices for cognitive skills. The study discovered emergence of the hierarchical limbic-sensorimotor-association cortical gradient in infancy, and offers standardized reference of infant brain CBF and insight into the physiological basis of cortical specialization and real-world infant developmental functioning.

Brain Structural Connectivity Guided Vision Transformers for Identification of Functional Connectivity Characteristics in Preterm Neonates

Preterm birth is the leading cause of death in children under five years old, and is associated with a wide sequence of complications in both short and long term. In view of rapid neurodevelopment during the neonatal period, preterm neonates may exhibit considerable functional alterations compared to term ones. However, the identified functional alterations in previous studies merely achieve moderate classification performance, while more accurate functional characteristics with satisfying discrimination ability for better diagnosis and therapeutic treatment is underexplored. To address this problem, we propose a novel brain structural connectivity (SC) guided Vision Transformer (SCG-ViT) to identify functional connectivity (FC) differences among three neonatal groups: preterm, preterm with early postnatal experience, and term. Particularly, inspired by the neuroscience-derived information, a novel patch token of SC/FC matrix is defined, and the SC matrix is then adopted as an effective mask into the ViT model to screen out input FC patch embeddings with weaker SC, and to focus on stronger ones for better classification and identification of FC differences among the three groups. The experimental results on multi-modal MRI data of 437 neonatal brains from publicly released Developing Human Connectome Project (dHCP) demonstrate that SCG-ViT achieves superior classification ability compared to baseline models, and successfully identifies holistically different FC patterns among the three groups. Moreover, these different FCs are significantly correlated with the differential gene expressions of the three groups. In summary, SCG-ViT provides a powerfully brain-guided pipeline of adopting large-scale and data-intensive deep learning models for medical imaging-based diagnosis.

Multi-level fMRI analysis applied to hemispheric specialization in the language network, functional areas, and their behavioral correlations in the ABCD sample

Prior research suggests that the organization of the language network in the brain is left-dominant and becomes more lateralized with age and increasing language skill. The age at which specific components of the language network become adult-like varies depending on the abilities they subserve. So far, a large, developmental study has not included a language task paradigm, so we introduce a method to study resting-state laterality in the Adolescent Brain Cognitive Development (ABCD) study. Our approach mixes source timeseries between left and right homotopes of the (1) inferior frontal and (2) middle temporal gyri and (3) a region we term "Wernicke's area" near the supramarginal gyrus. Our large subset sample size of ABCD (n = 6153) allows improved reliability and validity compared to previous, smaller studies of brain-behavior associations. We show that behavioral metrics from the NIH Youth Toolbox and other resources are differentially related to tasks with a larger linguistic component over ones with less (e.g., executive function-dominant tasks). These baseline characteristics of hemispheric specialization in youth are critical for future work determining the correspondence of lateralization with language onset in earlier stages of development.

Association of Breastfeeding and Neonatal Jaundice With Infant Neurodevelopment

INTRODUCTION

Exclusive breastfeeding is advantageous for infant neurodevelopment. Nevertheless, insufficient human milk supply in exclusively breastfed infants may elevate the risk of neonatal jaundice, which can potentially result in neurological harm. Whether mothers should adhere to exclusive breastfeeding in infants with neonatal jaundice remains unclear.

METHODS

Data comes from the Jiangsu Birth Cohort (JBC), a prospective and longitudinal birth cohort study in China. A total of 2,577 infants born from November 2017 to March 2021 were included in the analysis. Multivariate linear regression models were used to analyze the associations between breastfeeding status, neonatal jaundice, and their interaction with infant neurodevelopment. Analysis was performed in 2022.

RESULTS

Compared with "exclusive breastfeeding," fine motor scores of infants were lower for "mixed feeding" (βadj, -0.16; 95% CI, -0.29 to -0.03; p=0.016) and "no breastfeeding" (βadj, -0.41; 95% CI, -0.79 to -0.03; p=0.034). Compared with "no neonatal jaundice," infants with "severe neonatal jaundice" had lower scores for cognition (βadj, -0.44; 95% CI, -0.66 to -0.23; p<0.001) and fine motor (βadj, -0.19; 95% CI, -0.35 to -0.03; p=0.024). In infants with severe neonatal jaundice, the termination of exclusive breastfeeding before 6 months was associated with worse cognition (βadj, -0.28; 95% CI, -0.57 to 0.01), while this association was not observed in those without neonatal jaundice (βadj, 0.09; 95% CI, -0.26 to 0.43).

CONCLUSIONS

Exclusive breastfeeding for the first 6 months is beneficial to the neurodevelopment of infants, especially in those with severe neonatal jaundice.

Childhood adversities characterize the heterogeneity in the brain pattern of individuals during neurodevelopment

BACKGROUND

Several factors shape the neurodevelopmental trajectory. A key area of focus in neurodevelopmental research is to estimate the factors that have maximal influence on the brain and can tip the balance from typical to atypical development.

METHODS

Utilizing a dissimilarity maximization algorithm on the dynamic mode decomposition (DMD) of the resting state functional MRI data, we classified subjects from the cVEDA neurodevelopmental cohort (n = 987, aged 6-23 years) into homogeneously patterned DMD (representing typical development in 809 subjects) and heterogeneously patterned DMD (indicative of atypical development in 178 subjects).

RESULTS

Significant DMD differences were primarily identified in the default mode network (DMN) regions across these groups (p < 0.05, Bonferroni corrected). While the groups were comparable in cognitive performance, the atypical group had more frequent exposure to adversities and faced higher abuses (p < 0.05, Bonferroni corrected). Upon evaluating brain-behavior correlations, we found that correlation patterns between adversity and DMN dynamic modes exhibited age-dependent variations for atypical subjects, hinting at differential utilization of the DMN due to chronic adversities.

CONCLUSION

Adversities (particularly abuse) maximally influence the DMN during neurodevelopment and lead to the failure in the development of a coherent DMN system. While DMN's integrity is preserved in typical development, the age-dependent variability in atypically developing individuals is contrasting. The flexibility of DMN might be a compensatory mechanism to protect an individual in an abusive environment. However, such adaptability might deprive the neural system of the faculties of normal functioning and may incur long-term effects on the psyche.

The dorsomedial prefrontal cortex prioritizes social learning during rest

Sociality is a defining feature of the human experience: We rely on others to ensure survival and cooperate in complex social networks to thrive. Are there brain mechanisms that help ensure we quickly learn about our social world to optimally navigate it? We tested whether portions of the brain's default network engage "by default" to quickly prioritize social learning during the memory consolidation process. To test this possibility, participants underwent functional MRI (fMRI) while viewing scenes from the documentary film, Samsara. This film shows footage of real people and places from around the world. We normed the footage to select scenes that differed along the dimension of sociality, while matched on valence, arousal, interestingness, and familiarity. During fMRI, participants watched the "social" and "nonsocial" scenes, completed a rest scan, and a surprise recognition memory test. Participants showed superior social (vs. nonsocial) memory performance, and the social memory advantage was associated with neural pattern reinstatement during rest in the dorsomedial prefrontal cortex (DMPFC), a key node of the default network. Moreover, it was during early rest that DMPFC social pattern reinstatement was greatest and predicted subsequent social memory performance most strongly, consistent with the "prioritization" account. Results simultaneously update 1) theories of memory consolidation, which have not addressed how social information may be prioritized in the learning process, and 2) understanding of default network function, which remains to be fully characterized. More broadly, the results underscore the inherent human drive to understand our vastly social world.

Differences in the amplitude of low-frequency fluctuations of spontaneous brain activity between preterm and term infants

Objectives

To date, the majority of research on resting-state functional magnetic resonance imaging (rs-fMRI) in the developing brain has primarily centered on adolescents and adults, leaving a gap in understanding variations in spontaneous brain activity at rest in preterm infants. This study aimed to uncover and comprehend the distinctions in spontaneous brain activity between preterm and term infants, with the goal of establishing a foundation for assessing the condition of preterm infants.

Methods

In this study, 14 term infants and 15 preterm infants with equivalent gestational age were carefully chosen from the neonatal unit of Anhui Provincial Children's Hospital. The amplitude of low-frequency fluctuations (ALFF) intensity was assessed using resting-state functional magnetic resonance imaging (rs-fMRI) to examine brain activity in both groups. Subsequently, the differences between the term and preterm infants were statistically analyzed using a two-sample t-test. A p-value of <0.05, corrected for the REST Gaussian Random Fields, was deemed to be statistically significant.

Results

In comparison to the term infant group, the preterm infant group exhibited a significant increase in the ALFF value in the left precuneus, left frontal superior orbital gyrus, and left calcarine cortex.

Conclusion

Significant variances in spontaneous brain activity have been observed in various regions between term infants and preterm infants of equivalent gestational age. These variations could potentially impact the emotional and cognitive development of preterm infants in the long term.

Attention network training promotes selective attention of children with low socioeconomic status

The objectives of this study were to evaluate the difference of selective attention efficiency between children with low and high socioeconomic status (SES) and the promotional effect of attention network training (an attention network test was used as the training task) on selective attention in children with the low SES. A total of 139 10- to 12-year-old children participated in two experiments (71 in Experiment 1 and 68 in Experiment 2). The results suggest that selective attention and switch ability of children with high SES are better than those of children with low SES. After attention network training, selective attention, switch ability, and working memory of low-SES children improved significantly. The findings provide evidence that attention network training could enhance selective attention in low-SES children and that the beneficial training effect could also transfer to switch ability and working memory. The research may provide a promising method to compensate cognitive delay of low-SES children.

Atypical local brain connectivity in pediatric autism spectrum disorder? A coordinate-based meta-analysis of regional homogeneity studies

Despite decades of massive neuroimaging research, the comprehensive characterization of short-range functional connectivity in autism spectrum disorder (ASD) remains a major challenge for scientific advances and clinical translation. From the theoretical point of view, it has been suggested a generalized local over-connectivity that would characterize ASD. This stance is known as the general local over-connectivity theory. However, there is little empirical evidence supporting such hypothesis, especially with regard to pediatric individuals with ASD (age [Formula: see text] 18 years old). To explore this issue, we performed a coordinate-based meta-analysis of regional homogeneity studies to identify significant changes of local connectivity. Our analyses revealed local functional under-connectivity patterns in the bilateral posterior cingulate cortex and superior frontal gyrus (key components of the default mode network) and in the bilateral paracentral lobule (a part of the sensorimotor network). We also performed a functional association analysis of the identified areas, whose dysfunction is clinically consistent with the well-known deficits affecting individuals with ASD. Importantly, we did not find relevant clusters of local hyper-connectivity, which is contrary to the hypothesis that ASD may be characterized by generalized local over-connectivity. If confirmed, our result will provide a valuable insight into the understanding of the complex ASD pathophysiology.

Functional parcellation of the neonatal cortical surface

The cerebral cortex is organized into distinct but interconnected cortical areas, which can be defined by abrupt differences in patterns of resting state functional connectivity (FC) across the cortical surface. Such parcellations of the cortex have been derived in adults and older infants, but there is no widely used surface parcellation available for the neonatal brain. Here, we first demonstrate that existing parcellations, including surface-based parcels derived from older samples as well as volume-based neonatal parcels, are a poor fit for neonatal surface data. We next derive a set of 283 cortical surface parcels from a sample of n = 261 neonates. These parcels have highly homogenous FC patterns and are validated using three external neonatal datasets. The Infomap algorithm is used to assign functional network identities to each parcel, and derived networks are consistent with prior work in neonates. The proposed parcellation may represent neonatal cortical areas and provides a powerful tool for neonatal neuroimaging studies.

Growth in early infancy drives optimal brain functional connectivity which predicts cognitive flexibility in later childhood

Functional brain network organization, measured by functional connectivity (FC), reflects key neurodevelopmental processes for healthy development. Early exposure to adversity, e.g. undernutrition, affects neurodevelopment, observable via disrupted FC, and leads to poorer outcomes from preschool age onward. We assessed longitudinally the impact of early growth trajectories on developmental FC in a rural Gambian population from age 5 to 24 months. To investigate how these early trajectories relate to later childhood outcomes, we assessed cognitive flexibility at 3-5 years. We observed that early physical growth before the fifth month of life drove optimal developmental trajectories of FC that in turn predicted cognitive flexibility at pre-school age. In contrast to previously studied developmental populations, this Gambian sample exhibited long-range interhemispheric FC that decreased with age. Our results highlight the measurable effects that poor growth in early infancy has on brain development and the subsequent impact on pre-school age cognitive development, underscoring the need for early life interventions throughout global settings of adversity.

Resting-State Functional MRI and PET Imaging as Noninvasive Tools to Study (Ab)Normal Neurodevelopment in Humans and Rodents

Neurodevelopmental disorders (NDDs) are a group of complex neurologic and psychiatric disorders. Functional and molecular imaging techniques, such as resting-state functional magnetic resonance imaging (rs-fMRI) and positron emission tomography (PET), can be used to measure network activity noninvasively and longitudinally during maturation in both humans and rodent models. Here, we review the current knowledge on rs-fMRI and PET biomarkers in the study of normal and abnormal neurodevelopment, including intellectual disability (ID; with/without epilepsy), autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD), in humans and rodent models from birth until adulthood, and evaluate the cross-species translational value of the imaging biomarkers. To date, only a few isolated studies have used rs-fMRI or PET to study (abnormal) neurodevelopment in rodents during infancy, the critical period of neurodevelopment. Further work to explore the feasibility of performing functional imaging studies in infant rodent models is essential, as rs-fMRI and PET imaging in transgenic rodent models of NDDs are powerful techniques for studying disease pathogenesis, developing noninvasive preclinical imaging biomarkers of neurodevelopmental dysfunction, and evaluating treatment-response in disease-specific models.

Developmental coupling of brain iron and intrinsic activity in infants during the first 150 days

Brain iron is vital for core neurodevelopmental processes including myelination and neurotransmitter synthesis and, accordingly, iron accumulates in the brain with age. However, little is known about the association between brain iron and neural functioning and how they evolve with age in early infancy. This study investigated brain iron in 48 healthy infants (22 females) aged 64.00 ± 33.28 days by estimating R2 * relaxometry from multi-echo functional MRI (fMRI). Linked independent component analysis was performed to examine the association between iron deposition and spontaneous neural activity, as measured by the amplitude of low frequency fluctuations (ALFF) by interrogating shared component loadings across modalities. Further, findings were validated in an independent dataset (n = 45, 24 females, 77.93 ± 26.18 days). The analysis revealed developmental coupling between the global R2 * and ALFF within the default mode network (DMN). Furthermore, we observed that this coupling effect significantly increased with age (r = 0.78, p = 9.2e-11). Our results highlight the importance of iron-neural coupling during early development and suggest that the neural maturation of the DMN may correspond to growth in distributed brain iron.

Learning during sleep in humans - A historical review

Sleep helps to consolidate previously acquired memories. Whether new information such as languages and other useful skills can also be learned during sleep has been debated for over a century, however, the sporadic studies' different objectives and varied methodologies make it difficult to draw definitive conclusions. This review provides a comprehensive overview of the history of sleep learning research conducted in humans, from its empirical beginnings in the 1940s to the present day. Synthesizing the findings from 51 research papers, we show that several studies support the notion that simpler forms of learning, such as habituation and conditioning, are possible during sleep. In contrast, the findings for more complex, applied learning (e.g., learning a new language during sleep) are more divergent. While there is often an indication of processing and learning during sleep when looking at neural markers, behavioral evidence for the transfer of new knowledge to wake remains inconclusive. We close by critically examining the limitations and assumptions that have contributed to the discrepancies in the literature and highlight promising new directions in the field.

Structural and functional connectome relationships in early childhood

There is strong evidence that the functional connectome is highly related to the white matter connectome in older children and adults, though little is known about structure-function relationships in early childhood. We investigated the development of cortical structure-function coupling in children longitudinally scanned at 1, 2, 4, and 6 years of age (N = 360) and in a comparison sample of adults (N = 89). We also applied a novel graph convolutional neural network-based deep learning model with a new loss function to better capture inter-subject heterogeneity and predict an individual's functional connectivity from the corresponding structural connectivity. We found regional patterns of structure-function coupling in early childhood that were consistent with adult patterns. In addition, our deep learning model improved the prediction of individual functional connectivity from its structural counterpart compared to existing models.

Functional parcellation of the neonatal brain

The cerebral cortex is organized into distinct but interconnected cortical areas, which can be defined by abrupt differences in patterns of resting state functional connectivity (FC) across the cortical surface. Such parcellations of the cortex have been derived in adults and older infants, but there is no widely used surface parcellation available for the neonatal brain. Here, we first demonstrate that adult- and older infant-derived parcels are a poor fit with neonatal data, emphasizing the need for neonatal-specific parcels. We next derive a set of 283 cortical surface parcels from a sample of n=261 neonates. These parcels have highly homogenous FC patterns and are validated using three external neonatal datasets. The Infomap algorithm is used to assign functional network identities to each parcel, and derived networks are consistent with prior work in neonates. The proposed parcellation may represent neonatal cortical areas and provides a powerful tool for neonatal neuroimaging studies.

Concurrent and prospective associations between infant frontoparietal and default mode network connectivity and negative affectivity

Emotion dysregulation is linked to differences in frontoparietal (FPN) and default mode (DMN) brain network functioning. These differences may be identifiable early in development. Temperamental negative affectivity has been identified as a precursor to later emotion dysregulation, though the underlying neurodevelopmental mechanism is unknown. The present study explores concurrent and prospective associations between FPN and DMN connectivity in infants and measures of negative affectivity. 72 infants underwent 5.03-13.28 min of resting state fMRI during natural sleep (M±SD age=4.90 ± 0.84 weeks; 54% male; usable data=9.92 ± 2.15 min). FPN and DMN intra- and internetwork connectivity were computed using adult network assignments. Crying was obtained from both parent-report and day-long audio recordings. Temperamental negative affectivity was obtained from a parent-report questionnaire. In this preregistered study, based on analyses conducted with a subset of this data (N = 32), we hypothesized that greater functional connectivity within and between FPN and DMN would be associated with greater negative affectivity. In the full sample we did not find support for these hypotheses. Instead, greater DMN intranetwork connectivity at age one month was associated with lower concurrent parent-reported crying and temperamental negative affectivity at age six months (ßs>-0.35, ps<.025), but not crying at age six months. DMN intranetwork connectivity was also negatively associated with internalizing symptoms at age eighteen-months (ß=-0.58, p = .012). FPN intra- and internetwork connectivity was not associated with negative affectivity measures after accounting for covariates. This work furthers a neurodevelopmental model of emotion dysregulation by suggesting that infant functional connectivity at rest is associated with later emotional functioning.

Alterations in the topological organization of the default-mode network in Tourette syndrome

BACKGROUND

The exact pathophysiology of TS is still elusive. Previous studies have identified default mode networks (DMN) abnormalities in patients with TS. However, these literatures investigated the neural activity during the tic suppression, not a true resting-state. Therefore, this study aimed to reveal the neural mechanism of Tourette's syndrome (TS) from the perspective of topological organization and functional connectivity within the DMN by electroencephalography (EEG) in resting-state.

METHODS

The study was conducted by analyzing the EEG data of TS patients with graph theory approaches. Thirty children with TS and thirty healthy controls (HCs) were recruited, and all subjects underwent resting-state EEG data acquisition. Functional connectivity within the DMN was calculated, and network properties were measured.

RESULTS

A significantly lower connectivity in the neural activity of the TS patients in the β band was found between the bilateral posterior cingulate cortex/retrosplenial cortex (t = -3.02, p < 0.05). Compared to HCs, the TS patients' local topological properties (degree centrality) in the left temporal lobe in the γ band were changed, while the global topological properties (global efficiency and local efficiency) in DMN exhibited no significant differences. It was also demonstrated that the degree centrality of the left temporal lobe in the γ band was positively related to the Yale Global Tic Severity Scale scores (r = 0.369, p = 0.045).

CONCLUSIONS

The functional connectivity and topological properties of the DMN of TS patients were disrupted, and abnormal DMN topological property alterations might affect the severity of tic in TS patients. The abnormal topological properties of the DMN in TS patients may be due to abnormal functional connectivity alterations. The findings provide novel insight into the neural mechanism of TS patients.

Mapping the evolution of regional brain network efficiency and its association with cognitive abilities during the first twenty-eight months of life

Human brain undergoes rapid growth during the first few years of life. While previous research has employed graph theory to study early brain development, it has mostly focused on the topological attributes of the whole brain. However, examining regional graph-theory features may provide unique insights into the development of cognitive abilities. Utilizing a large and longitudinal rsfMRI dataset from the UNC/UMN Baby Connectome Project, we investigated the developmental trajectories of regional efficiency and evaluated the relationships between these changes and cognitive abilities using Mullen Scales of Early Learning during the first twenty-eight months of life. Our results revealed a complex and spatiotemporally heterogeneous development pattern of regional global and local efficiency during this age period. Furthermore, we found that the trajectories of the regional global efficiency at the left temporal occipital fusiform and bilateral occipital fusiform gyri were positively associated with cognitive abilities, including visual reception, expressive language, receptive language, and early learning composite scores (P < 0.05, FDR corrected). However, these associations were weakened with age. These findings offered new insights into the regional developmental features of brain topologies and their associations with cognition and provided evidence of ongoing optimization of brain networks at both whole-brain and regional levels.

Longitudinal developmental trajectories of functional connectivity reveal regional distribution of distinct age effects in infancy

Prior work has shown that different functional brain networks exhibit different maturation rates, but little is known about whether and how different brain areas may differ in the exact shape of longitudinal functional connectivity growth trajectories during infancy. We used resting-state functional magnetic resonance imaging (fMRI) during natural sleep to characterize developmental trajectories of different regions using a longitudinal cohort of infants at 3 weeks (neonate), 1 year, and 2 years of age (n = 90; all with usable data at three time points). A novel whole brain heatmap analysis was performed with four mixed-effect models to determine the best fit of age-related changes for each functional connection: (i) growth effects: positive-linear-age, (ii) emergent effects: positive-log-age, (iii) pruning effects: negative-quadratic-age, and (iv) transient effects: positive-quadratic-age. Our results revealed that emergent (logarithmic) effects dominated developmental trajectory patterns, but significant pruning and transient effects were also observed, particularly in connections centered on inferior frontal and anterior cingulate areas that support social learning and conflict monitoring. Overall, unique global distribution patterns were observed for each growth model indicating that developmental trajectories for different connections are heterogeneous. All models showed significant effects concentrated in association areas, highlighting the dominance of higher-order social/cognitive development during the first 2 years of life.

Visual experience shapes functional connectivity between occipital and non-visual networks

Comparisons across adults with different sensory histories (blind vs. sighted) have uncovered effects of experience on human brain function. In people born blind visual cortices are responsive to non-visual tasks and show altered functional connectivity at rest. Since almost all research has been done with adults, little is known about the developmental origins of this plasticity. Are infant visual cortices initially functionally like those of sighted adults and blindness causes reorganization? Alternatively, do infants start like blind adults, with vision required to set up the sighted pattern? To distinguish between these possibilities, we compare resting state functional connectivity across blind (n = 30) and blindfolded sighted (n = 50) adults to a large cohort of sighted infants (Developing Human Connectome Project, n = 475). Remarkably, we find that infant secondary visual cortices functionally resemble those of blind more than sighted adults, consistent with the idea that visual experience is required to set up long-range functional connectivity. Primary visual cortices show a mixture of instructive effects of vision and reorganizing effects of blindness. Specifically, in sighted adults, visual cortices show stronger functional coupling with nonvisual sensory-motor networks (i.e., auditory, somatosensory/motor) than with higher-cognitive prefrontal cortices (PFC). In blind adults, visual cortices show stronger coupling with PFC. In infants, connectivity of secondary visual cortices is stronger with PFC, while V1 shows equal sensory-motor/PFC connectivity. In contrast, lateralization of occipital-to-frontal connectivity resembles the sighted adults at birth and is reorganized by blindness, possibly due to recruitment of occipital networks for lateralized cognitive functions, such as language.

When shapes are more than shapes: perceptual, developmental, and neurophysiological basis for attributions of animacy and theory of mind

Among a variety of entities in their environment, what do humans consider alive or animate and how does this attribution of animacy promote development of more abstract levels of mentalizing? By decontextualizing the environment of bodily features, we review how physical movements give rise to perceived animacy in Heider-Simmel style animations. We discuss the developmental course of how perceived animacy shapes our interpretation of the social world, and specifically discuss when and how children transition from perceiving actions as goal-directed to attributing behaviors to unobservable mental states. This transition from a teleological stance, asserting a goal-oriented interpretation to an agent's actions, to a mentalistic stance allows older children to reason about more complex actions guided by hidden beliefs. The acquisition of these more complex cognitive behaviors happens developmentally at the same time neural systems for social cognition are coming online in young children. We review perceptual, developmental, and neural evidence to identify the joint cognitive and neural changes associated with when children begin to mentalize and how this ability is instantiated in the brain.

Prenatal environment is associated with the pace of cortical network development over the first three years of life

Environmental influences on brain structure and function during early development have been well-characterized. In pre-registered analyses, we test the theory that socioeconomic status (SES) is associated with differences in trajectories of intrinsic brain network development from birth to three years (n = 261). Prenatal SES is associated with developmental increases in cortical network segregation, with neonates and toddlers from lower-SES backgrounds showing a steeper increase in cortical network segregation with age, consistent with accelerated network development. Associations between SES and cortical network segregation occur at the local scale and conform to a sensorimotor-association hierarchy of cortical organization. SES-associated differences in cortical network segregation are associated with language abilities at two years, such that lower segregation is associated with improved language abilities. These results yield key insight into the timing and directionality of associations between the early environment and trajectories of cortical development.

Fine-grained functional parcellation maps of the infant cerebral cortex

Resting-state functional MRI (rs-fMRI) is widely used to examine the dynamic brain functional development of infants, but these studies typically require precise cortical parcellation maps, which cannot be directly borrowed from adult-based functional parcellation maps due to the substantial differences in functional brain organization between infants and adults. Creating infant-specific cortical parcellation maps is thus highly desired but remains challenging due to difficulties in acquiring and processing infant brain MRIs. In this study, we leveraged 1064 high-resolution longitudinal rs-fMRIs from 197 typically developing infants and toddlers from birth to 24 months who participated in the Baby Connectome Project to develop the first set of infant-specific, fine-grained, surface-based cortical functional parcellation maps. To establish meaningful cortical functional correspondence across individuals, we performed cortical co-registration using both the cortical folding geometric features and the local gradient of functional connectivity (FC). Then we generated both age-related and age-independent cortical parcellation maps with over 800 fine-grained parcels during infancy based on aligned and averaged local gradient maps of FC across individuals. These parcellation maps reveal complex functional developmental patterns, such as changes in local gradient, network size, and local efficiency, especially during the first 9 postnatal months. Our generated fine-grained infant cortical functional parcellation maps are publicly available at https://www.nitrc.org/projects/infantsurfatlas/ for advancing the pediatric neuroimaging field.

Functional neural network connectivity at 3 months predicts infant-mother dyadic flexibility during play at 6 months

Early functioning of neural networks likely underlies the flexible switching between internal and external orientation and may be key to the infant's ability to effectively engage in social interactions. To test this hypothesis, we examined the association between infants' neural networks at 3 months and infant-mother dyadic flexibility (denoting the structural variability of their interaction dynamics) at 3, 6, and 9 months. Participants included thirty-five infants (37% girls) and their mothers (87% White). At 3 months, infants participated in a resting-state functional magnetic resonance imaging session, and functional connectivity (FC) within the default mode (DMN) and salience (SN) networks, as well as DMN-SN internetwork FC, were derived using a seed-based approach. When infants were 3, 6, and 9 months, infant-mother dyads completed the Still-Face Paradigm where their individual engagement behaviors were observed and used to quantify dyadic flexibility using state space analysis. Results revealed that greater within-DMN FC, within-SN FC, and DMN-SN anticorrelation at 3 months predicted greater dyadic flexibility at 6 months, but not at 3 and 9 months. Findings suggest that early synchronization and interaction between neural networks underlying introspection and salience detection may support infants' flexible social interactions as they become increasingly active and engaged social partners.

Toward a more informative representation of the fetal-neonatal brain connectome using variational autoencoder

Recent advances in functional magnetic resonance imaging (fMRI) have helped elucidate previously inaccessible trajectories of early-life prenatal and neonatal brain development. To date, the interpretation of fetal-neonatal fMRI data has relied on linear analytic models, akin to adult neuroimaging data. However, unlike the adult brain, the fetal and newborn brain develops extraordinarily rapidly, far outpacing any other brain development period across the life span. Consequently, conventional linear computational models may not adequately capture these accelerated and complex neurodevelopmental trajectories during this critical period of brain development along the prenatal-neonatal continuum. To obtain a nuanced understanding of fetal-neonatal brain development, including nonlinear growth, for the first time, we developed quantitative, systems-wide representations of brain activity in a large sample (>500) of fetuses, preterm, and full-term neonates using an unsupervised deep generative model called variational autoencoder (VAE), a model previously shown to be superior to linear models in representing complex resting-state data in healthy adults. Here, we demonstrated that nonlinear brain features, that is, latent variables, derived with the VAE pretrained on rsfMRI of human adults, carried important individual neural signatures, leading to improved representation of prenatal-neonatal brain maturational patterns and more accurate and stable age prediction in the neonate cohort compared to linear models. Using the VAE decoder, we also revealed distinct functional brain networks spanning the sensory and default mode networks. Using the VAE, we are able to reliably capture and quantify complex, nonlinear fetal-neonatal functional neural connectivity. This will lay the critical foundation for detailed mapping of healthy and aberrant functional brain signatures that have their origins in fetal life.

Posterior superior temporal cortex connectivity is related to social communication in toddlers

The second year of life is a time when social communication skills typically develop, but this growth may be slower in toddlers with language delay. In the current study, we examined how brain functional connectivity is related to social communication abilities in a sample of 12-24 month-old toddlers including those with typical development (TD) and those with language delays (LD). We used an a-priori, seed-based approach to identify regions forming a functional network with the left posterior superior temporal cortex (LpSTC), a region associated with language and social communication in older children and adults. Social communication and language abilities were assessed using the Communication and Symbolic Behavior Scales (CSBS) and Mullen Scales of Early Learning. We found a significant association between concurrent CSBS scores and functional connectivity between the LpSTC and the right posterior superior temporal cortex (RpSTC), with greater connectivity between these regions associated with better social communication abilities. However, functional connectivity was not related to rate of change or language outcomes at 36 months of age. These data suggest an early marker of low communication abilities may be decreased connectivity between the left and right pSTC. Future longitudinal studies should test whether this neurobiological feature is predictive of later social or communication impairments.

Genetic and environmental factors influencing neonatal resting-state functional connectivity

Functional magnetic resonance imaging has been used to identify complex brain networks by examining the correlation of blood-oxygen-level-dependent signals between brain regions during the resting state. Many of the brain networks identified in adults are detectable at birth, but genetic and environmental influences governing connectivity within and between these networks in early infancy have yet to be explored. We investigated genetic influences on neonatal resting-state connectivity phenotypes by generating intraclass correlations and performing mixed effects modeling to estimate narrow-sense heritability on measures of within network and between-network connectivity in a large cohort of neonate twins. We also used backwards elimination regression and mixed linear modeling to identify specific demographic and medical history variables influencing within and between network connectivity in a large cohort of typically developing twins and singletons. Of the 36 connectivity phenotypes examined, only 6 showed narrow-sense heritability estimates greater than 0.10, with none being statistically significant. Demographic and obstetric history variables contributed to between- and within-network connectivity. Our results suggest that in early infancy, genetic factors minimally influence brain connectivity. However, specific demographic and medical history variables, such as gestational age at birth and maternal psychiatric history, may influence resting-state connectivity measures.

Sex differences in resting state functional connectivity across the first two years of life

Sex differences in behavior have been reported from infancy through adulthood, but little is known about sex effects on functional circuitry in early infancy. Moreover, the relationship between early sex effects on the functional architecture of the brain and later behavioral performance remains to be elucidated. In this study, we used resting-state fMRI and a novel heatmap analysis to examine sex differences in functional connectivity with cross-sectional and longitudinal mixed models in a large cohort of infants (n = 319 neonates, 1-, and 2-year-olds). An adult dataset (n = 92) was also included for comparison. We investigated the relationship between sex differences in functional circuitry and later measures of language (collected in 1- and 2-year-olds) as well as indices of anxiety, executive function, and intelligence (collected in 4-year-olds). Brain areas showing the most significant sex differences were age-specific across infancy, with two temporal regions demonstrating consistent differences. Measures of functional connectivity showing sex differences in infancy were significantly associated with subsequent behavioral scores of language, executive function, and intelligence. Our findings provide insights into the effects of sex on dynamic neurodevelopmental trajectories during infancy and lay an important foundation for understanding the mechanisms underlying sex differences in health and disease.

Maturation of large-scale brain systems over the first month of life

The period immediately after birth is a critical developmental window, capturing rapid maturation of brain structure and a child's earliest experiences. Large-scale brain systems are present at delivery, but how these brain systems mature during this narrow window (i.e. first weeks of life) marked by heightened neuroplasticity remains uncharted. Using multivariate pattern classification techniques and functional connectivity magnetic resonance imaging, we detected robust differences in brain systems related to age in newborns (n = 262; R2 = 0.51). Development over the first month of life occurred brain-wide, but differed and was more pronounced in brain systems previously characterized as developing early (i.e. sensorimotor networks) than in those characterized as developing late (i.e. association networks). The cingulo-opercular network was the only exception to this organizing principle, illuminating its early role in brain development. This study represents a step towards a normative brain "growth curve" that could be used to identify atypical brain maturation in infancy.

The parcellation of cingulate cortex in neonatal period based on resting-state functional MRI

The human cingulate cortex (CC) is a complex region that is characterized by heterogeneous cytoarchitecture, connectivity, and function, and it is associated with various cognitive functions. The adult CC has been divided into various subregions, and this subdivision is highly consistent with its functional differentiation. However, only a few studies have focused on the function of neonatal CC. The aim of this study was to describe the cingulate segregation and the functional connectivity of each subdivision in full-term neonates (n = 60) based on resting-state functional magnetic resonance imaging. The neonatal CC was divided into three subregions, and each subregion showed specific connectivity patterns. The anterior cingulate cortex was mainly correlated with brain regions related to the salience (affected) network and default mode network (DMN), the midcingulate cortex was related to motor areas, and the posterior cingulate cortex was coupled with DMN. Moreover, we found that the cingulate subregions showed distinct functional profiles with major brain networks, which were defined using independent component analysis, and exhibited functional lateralization. This study provided new insights into the understanding of the functional specialization of neonatal CC, and these findings may have significant clinical implications, especially in predicting neurological disorder.

Not with a “zap” but with a “beep”: measuring the origins of perinatal experience

When does the mind begin? Infant psychology is mysterious in part because we cannot remember our first months of life, nor can we directly communicate with infants. Even more speculative is the possibility of mental life prior to birth. The question of when consciousness, or subjective experience, begins in human development thus remains incompletely answered, though boundaries can be set using current knowledge from developmental neurobiology and recent investigations of the perinatal brain. Here, we offer our perspective on how the development of a sensory perturbational complexity index (sPCI) based on auditory ("beep-and-zip"), visual ("flash-and-zip"), or even olfactory ("sniff-and-zip") cortical perturbations in place of electromagnetic perturbations ("zap-and-zip") might be used to address this question. First, we discuss recent studies of perinatal cognition and consciousness using techniques such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and, in particular, magnetoencephalography (MEG). While newborn infants are the archetypal subjects for studying early human development, researchers may also benefit from fetal studies, as the womb is, in many respects, a more controlled environment than the cradle. The earliest possible timepoint when subjective experience might begin is likely the establishment of thalamocortical connectivity at 26 weeks gestation, as the thalamocortical system is necessary for consciousness according to most theoretical frameworks. To infer at what age and in which behavioral states consciousness might emerge following the initiation of thalamocortical pathways, we advocate for the development of the sPCI and similar techniques, based on EEG, MEG, and fMRI, to estimate the perinatal brain's state of consciousness.

Network-specific selectivity of functional connections in the neonatal brain

The adult human brain is organized into functional brain networks, groups of functionally connected segregated brain regions. A key feature of adult functional networks is long-range selectivity, the property that spatially distant regions from the same network have higher functional connectivity than spatially distant regions from different networks. Although it is critical to establish the status of functional networks and long-range selectivity during the neonatal period as a foundation for typical and atypical brain development, prior work in this area has been mixed. Although some studies report distributed adult-like networks, other studies suggest that neonatal networks are immature and consist primarily of spatially isolated regions. Using a large sample of neonates (n = 262), we demonstrate that neonates have long-range selective functional connections for the default mode, fronto-parietal, and dorsal attention networks. An adult-like pattern of functional brain networks is evident in neonates when network-detection algorithms are tuned to these long-range connections, when using surface-based registration (versus volume-based registration), and as per-subject data quantity increases. These results help clarify factors that have led to prior mixed results, establish that key adult-like functional network features are evident in neonates, and provide a foundation for studies of typical and atypical brain development.

Infant brain regional cerebral blood flow increases supporting emergence of the default-mode network

Human infancy is characterized by most rapid regional cerebral blood flow (rCBF) increases across lifespan and emergence of a fundamental brain system default-mode network (DMN). However, how infant rCBF changes spatiotemporally across the brain and how the rCBF increase supports emergence of functional networks such as DMN remains unknown. Here, by acquiring cutting-edge multi-modal MRI including pseudo-continuous arterial-spin-labeled perfusion MRI and resting-state functional MRI of 48 infants cross-sectionally, we elucidated unprecedented 4D spatiotemporal infant rCBF framework and region-specific physiology-function coupling across infancy. We found that faster rCBF increases in the DMN than visual and sensorimotor networks. We also found strongly coupled increases of rCBF and network strength specifically in the DMN, suggesting faster local blood flow increase to meet extraneuronal metabolic demands in the DMN maturation. These results offer insights into the physiological mechanism of brain functional network emergence and have important implications in altered network maturation in brain disorders.

Maternal psychological distress associates with alterations in resting-state low-frequency fluctuations and distal functional connectivity of the neonate medial prefrontal cortex

Prenatal stress exposure (PSE) has been observed to exert a programming effect on the developing infant brain, possibly with long-lasting consequences on temperament, cognitive functions and the risk for developing psychiatric disorders. Several prior studies have revealed that PSE associates with alterations in neonate functional connectivity in the prefrontal regions and amygdala. In this study, we explored whether maternal psychological symptoms measured during the 24th gestational week had associations with neonate resting-state network metrics. Twenty-one neonates (nine female) underwent resting-state fMRI scanning (mean gestation-corrected age at scan 26.95 days) to assess fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo). The ReHo/fALFF maps were used in multiple regression analysis to investigate whether maternal self-reported anxiety and/or depressive symptoms associate with neonate functional brain features. Maternal psychological distress (composite score of depressive and anxiety symptoms) was positively associated with fALFF in the neonate medial prefrontal cortex (mPFC). Anxiety and depressive symptoms, assessed separately, exhibited similar but weaker associations. Post hoc seed-based connectivity analyses further showed that distal connectivity of mPFC covaried with PSE. No associations were found between neonate ReHo and PSE. These results offer preliminary evidence that PSE may affect functional features of the developing brain during gestation.

Prenatal Stress and the Developing Brain: Postnatal Environments Promoting Resilience

Heightened maternal stress during pregnancy is associated with atypical brain development and an elevated risk for psychopathology in offspring. Supportive environments during early postnatal life may promote brain development and reverse atypical developmental trajectories induced by prenatal stress. We reviewed studies focused on the role of key early environmental factors in moderating associations between prenatal stress exposure and infant brain and neurocognitive outcomes. Specifically, we focused on the associations between parental caregiving quality, environmental enrichment, social support, and socioeconomic status with infant brain and neurocognitive outcomes. We examined the evidence that these factors may moderate the effects of prenatal stress on the developing brain. Complementing findings from translational models, human research suggests that high-quality early postnatal environments are associated with indices of infant neurodevelopment that have also been associated with prenatal stress, such as hippocampal volume and frontolimbic connectivity. Human studies also suggest that maternal sensitivity and higher socioeconomic status may attenuate the effects of prenatal stress on established neurocognitive and neuroendocrine mediators of risk for psychopathology, such as hypothalamic-pituitary-adrenal axis functioning. Biological pathways that may underlie the effects of positive early environments on the infant brain, including the epigenome, oxytocin, and inflammation, are also discussed. Future research in humans should examine resilience-promoting processes in relation to infant brain development using large sample sizes and longitudinal designs. The findings from this review could be incorporated into clinical models of risk and resilience during the perinatal period and used to design more effective early programs that reduce risk for psychopathology.

The Age of Reason: Functional Brain Network Development during Childhood

Human childhood is characterized by dramatic changes in the mind and brain. However, little is known about the large-scale intrinsic cortical network changes that occur during childhood because of methodological challenges in scanning young children. Here, we overcome this barrier by using sophisticated acquisition and analysis tools to investigate functional network development in children between the ages of 4 and 10 years ([Formula: see text]; 50 female, 42 male). At multiple spatial scales, age is positively associated with brain network segregation. At the system level, age was associated with segregation of systems involved in attention from those involved in abstract cognition, and with integration among attentional and perceptual systems. Associations between age and functional connectivity are most pronounced in visual and medial prefrontal cortex, the two ends of a gradient from perceptual, externally oriented cortex to abstract, internally oriented cortex. These findings suggest that both ends of the sensory-association gradient may develop early, in contrast to the classical theories that cortical maturation proceeds from back to front, with sensory areas developing first and association areas developing last. More mature patterns of brain network architecture, controlling for age, were associated with better visuospatial reasoning abilities. Our results suggest that as cortical architecture becomes more specialized, children become more able to reason about the world and their place in it.SIGNIFICANCE STATEMENT Anthropologists have called the transition from early to middle childhood the "age of reason", when children across cultures become more independent. We employ cutting-edge neuroimaging acquisition and analysis approaches to investigate associations between age and functional brain architecture in childhood. Age was positively associated with segregation between cortical systems that process the external world and those that process abstract phenomena like the past, future, and minds of others. Surprisingly, we observed pronounced development at both ends of the sensory-association gradient, challenging the theory that sensory areas develop first and association areas develop last. Our results open new directions for research into how brains reorganize to support rapid gains in cognitive and socioemotional skills as children reach the age of reason.

The development of cortical functional hierarchy is associated with the molecular organization of prenatal/postnatal periods

The human cerebral cortex conforms to specific functional hierarchies facilitating information processing and higher-order cognition. Prior studies in adults have unveiled a dominant functional hierarchy spanning from sensorimotor regions to transmodal regions, which is also present in younger cohorts. However, how the functional hierarchy develops and the underlying molecular mechanisms remain to be investigated. Here, we set out to investigate the developmental patterns of the functional hierarchy for preschool children (#scans = 141, age = 2.41-6.90 years) using a parsimonious general linear model and the underlying biological mechanisms by combining the neuroimaging developmental pattern with two separate transcriptomic datasets (i.e. Allen Human Brain Atlas and BrainSpan Atlas). Our results indicated that transmodal regions were further segregated from sensorimotor regions and that such changes were potentially driven by two gene clusters with distinct enrichment profiles, namely prenatal gene cluster and postnatal gene cluster. Additionally, we found similar developmental profiles manifested in subsequent developmental periods by conducting identical analyses on the Human Connectome Projects in Development (#scans = 638, age = 5.58-21.92 years) and Philadelphia Neurodevelopment Cohort datasets (#scans = 795, age = 8-21 years), driven by concordant two gene clusters. Together, these findings illuminate a comprehensive developmental principle of the functional hierarchy and the underpinning molecular factors, and thus may shed light on the potential pathobiology of neurodevelopmental disorders.

Adolescent development of multiscale structural wiring and functional interactions in the human connectome

Adolescence is a time of profound changes in the physical wiring and function of the brain. Here, we analyzed structural and functional brain network development in an accelerated longitudinal cohort spanning 14 to 25 y (n = 199). Core to our work was an advanced in vivo model of cortical wiring incorporating MRI features of corticocortical proximity, microstructural similarity, and white matter tractography. Longitudinal analyses assessing age-related changes in cortical wiring identified a continued differentiation of multiple corticocortical structural networks in youth. We then assessed structure-function coupling using resting-state functional MRI measures in the same participants both via cross-sectional analysis at baseline and by studying longitudinal change between baseline and follow-up scans. At baseline, regions with more similar structural wiring were more likely to be functionally coupled. Moreover, correlating longitudinal structural wiring changes with longitudinal functional connectivity reconfigurations, we found that increased structural differentiation, particularly between sensory/unimodal and default mode networks, was reflected by reduced functional interactions. These findings provide insights into adolescent development of human brain structure and function, illustrating how structural wiring interacts with the maturation of macroscale functional hierarchies.

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.

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.

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.