Developmental pathways to functional brain networks: emerging principles

Developmental patterns of white matter functional networks in neonates

In recent years, the development of neonatal brain networks has become a research focus, with traditional studies primarily emphasizing gray matter (GM) functional networks. This study systematically explores the developmental characteristics of white matter (WM) functional networks in neonates. Utilizing data from the third release of the Developing Human Connectome Project (dHCP), we analyzed resting-state functional magnetic resonance imaging (rs-fMRI) data from 730 full-term and 157 preterm neonates. We successfully identified ten large-scale WM functional networks and validated their correspondence with established WM fiber tracts using diffusion tensor imaging (DTI). We examined WM functional networks from two dimensions: network functional connectivity and spontaneous activity, incorporating four factors: preterm birth status, age, sex, and hemispheric differences. The results indicate that WM network functional connectivity significantly increases with age, with preterm infants exhibiting lower connectivity than full-term infants, whereas no significant differences were observed between sexes or hemispheres. Regarding spontaneous activity, preterm infants showed lower amplitude in the low-frequency range, whereas in the high-frequency range, their amplitude distribution was more unstable and dispersed. Additionally, certain differences in spontaneous activity were observed between hemispheres and sexes. These findings provide novel insights into the early development of neonatal brain networks and hold significant implications for clinical interventions and treatment strategies for preterm infants.

Influence of binge drinking on the resting state functional connectivity of university Students: A follow-up study

Binge Drinking (BD) is characterized by consuming large amounts of alcohol on one occasion, posing risks to brain function. Nonetheless, it remains the most prevalent consumption pattern among students. Cross-sectional studies have explored the relationship between BD and anomalies in resting-state functional connectivity (RS-FC), but the medium/long-term consequences of BD on RS-FC during developmental periods remain relatively unexplored. In this two-year follow-up study, the impact of sustained BD on RS-FC was investigated in 44 college students (16 binge-drinkers) via two fMRI sessions at ages 18-19 and 20-21. Using a seed-to-voxel approach, RS-FC differences were examined in nodes of the main brain functional networks vulnerable to alcohol misuse, according to previous studies. Group differences in RS-FC were observed in four of the explored brain regions. Binge drinkers, compared to the control group, exhibited, at the second assessment, decreased connectivity between the right SFG (executive control network) and right precentral gyrus, the ACC (salience network) and right postcentral gyrus, and the left amygdala (emotional network) and medial frontal gyrus/dorsal ACC. Conversely, binge drinkers showed increased connectivity between the right Nacc (reward network) and four clusters comprising bilateral middle frontal gyrus (MFG), right middle cingulate cortex, and right MFG extending to SFG. Maintaining a BD pattern during critical neurodevelopmental years impacts RS-FC, indicating mid-to-long-term alterations in functional brain organization. This study provides new insights into the neurotoxic effects of adolescent alcohol misuse, emphasizing the need for longitudinal studies addressing the lasting consequences on brain functional connectivity.

Neuropsychological outcome after surgery of frontal lobe epilepsy in children with good seizure outcome

One third of children with drug-resistant epilepsy included in surgical programmes have frontal lobe epilepsy. Frontal lobe epilepsy in itself constitutes a high risk of impacting neurocognitive and behavioral development. In this study, we characterized the long-term neuropsychological and behavioral outcomes of children with pharmacoresistant structural focal epilepsy who underwent frontal neurosurgery. The clinical variables that may influence these outcomes were also investigated. A comprehensive neuropsychological evaluation - including a behavioral questionnaire - was administered to 37 children on long-term postoperative follow-up (5.1 years ± 2.9) using the Wechsler Intelligence Scale for Children, Fluency task, Rey-Osterrieth Complex Figure, Trail Making Test, Tower of London, Wisconsin Sorting Card Test and Achenbach Child Behaviour Inventory. To assess executive functions in the youngest children, we administered the junior version of EpiTrack. The clinical characteristics were as follows (mean in years ± standard deviation): Engel I (78 % with among them 96 % without anti-seizure medication), age of onset of seizures (3.5 ± 2.9), preoperative delay (3.9 ± 2.5), neurosurgical age (7.5 ± 3.6), FCD (n = 25) versus LEAT (n = 12) aetiologies. In our series, the children had an average FSIQ (92 ± 17) with a significant difference between VCI which was higher than WMI and PSI. About a third of the children experienced weakness of the executive functions with some difficulties in phonemic verbal fluency and slowness in attentional tasks, and a long execution time in planning, as well as impaired conceptualization and organization capacities. Mild to severe alteration on the Epitrack Junior was found in the majority of the youngest patients although they had a mean FSIQ of 96. At the behavioral level, around a quarter of children reached a pathological score in the attentional, social and anxiety/depression domains. Regarding the effects of clinical variables, we demonstrated that early age at surgery, shorter disease duration and LEAT etiology, were good prognosis factors for neuropsychological outcomes. Early frontal lobe resection followed by good seizure outcome efficiently determines intellectual and neuropsychological trajectory in selected patients. Our results help to better understand the cognitive and behavioral outcomes of this pediatric population, who may benefit from cognitive follow-up and adapted intervention when weaknesses are identified.

Growing together: Dynamic connectivity between developmentally sensitive regions serving verbal working memory in children and adolescents

The neural network serving verbal working memory processes undergoes dramatic changes during the transition from childhood to adolescence, including changes in cortical thickness, activation levels, connectivity and inherent dynamics. Of all these neural properties, maturational changes in dynamic functional connectivity among developmentally sensitive regions within this network are among the least understood. To address this, we examined 75 typically developing youth (age range 6-14 years), who completed a verbal working memory task during magnetoencephalography (MEG). All MEG data were imaged and the phase-locking value was computed as an index of functional connectivity between regions exhibiting significant relationships with chronological age. Our results suggested developmental differences in functional connectivity during specific phases of working memory processing. During encoding, connectivity increased with age between left prefrontal and inferior parietal, with such age-related increases varying by sex between right frontal and left occipitotemporal regions. During the maintenance period, connectivity increased with age between left occipitotemporal and right posterior parietal areas and decreased with age between left frontal and right occipital cortices. These findings suggest that neural oscillations within regions serving working memory processing, as well as functional connectivity among these regions, are modulated by development during the transition from childhood to adolescence. KEY POINTS: With development from childhood to adolescence, verbal working memory processing becomes increasingly left lateralized in the prefrontal, parietal and temporal cortices. Several electrophysiological studies have shown that alpha oscillations within these brain regions become stronger with increasing chronological age during the transition from childhood to adolescence. Although such oscillatory power differences are well established, age-related changes in functional connectivity among these brain regions is far less understood. Here, we report novel findings suggesting that functional connectivity between developmentally sensitive cortical regions supporting verbal working memory scales with age among visual, language and attention-related brain systems. These results help to refine models of functional neural development supporting verbal working memory ability for future application in both basic research and clinical studies of typical and atypical cognitive development.

The multiscale brain structural re-organization that occurs from childhood to adolescence correlates with cortical morphology maturation and functional specialization

From childhood to adolescence, the structural organization of the human brain undergoes dynamic and regionally heterogeneous changes across multiple scales, from synapses to macroscale white matter pathways. However, during this period, the developmental process of multiscale structural architecture, its association with cortical morphological changes, and its role in the maturation of functional organization remain largely unknown. Here, using two independent multimodal imaging developmental datasets aged 6-14 years, we investigated developmental process of multiscale cortical organization by constructing an in vivo multiscale structural connectome model incorporating white matter tractography, cortico-cortical proximity, and microstructural similarity. By employing the gradient mapping method, the principal gradient derived from the multiscale structural connectome effectively recapitulated the sensory-association axis. Our findings revealed a continuous expansion of the multiscale structural gradient space during development, characterized by enhanced differentiation between primary sensory and higher-order transmodal regions along the principal gradient. This age-related differentiation paralleled regionally heterogeneous changes in cortical morphology. Furthermore, the developmental changes in coupling between multiscale structural and functional connectivity were correlated with functional specialization refinement, as evidenced by changes in the participation coefficient. Notably, the differentiation of the principal multiscale structural gradient was associated with improved cognitive abilities, such as enhanced working memory and attention performance, and potentially underpinned by synaptic and hormone-related biological processes. These findings advance our understanding of the intricate maturation process of brain structural organization and its implications for cognitive performance.

Synaptic-dependent developmental dysconnectivity in 22q11.2 deletion syndrome

Chromosome 22q11.2 deletion increases the risk of neuropsychiatric disorders like autism and schizophrenia. Disruption of large-scale functional connectivity in 22q11 deletion syndrome (22q11DS) has been widely reported, but the biological factors driving these changes remain unclear. We used a cross-species design to uncover the developmental trajectory and neural underpinnings of brain dysconnectivity in 22q11DS. In LgDel mice, a model for 22q11DS, we found age-specific patterns of brain dysconnectivity, with widespread fMRI hyperconnectivity in juvenile mice reconfiguring to hippocampal hypoconnectivity over puberty. These changes correlated with developmental alterations in dendritic spine density, and both were transiently normalized by GSK3β inhibition, suggesting a synaptic origin for this phenomenon. Notably, analogous pubertal hyperconnectivity-to-hypoconnectivity reconfiguration occurs in human 22q11DS, affecting cortical regions enriched for GSK3β-associated synaptic genes and autism-relevant transcripts. This dysconnectivity also predicts age-dependent social alterations in 22q11DS individuals. These results suggest that synaptic mechanisms underlie developmental brain dysconnectivity in 22q11DS.

Oxytocin enhances creativity specifically in approach-motivated individuals

Oxytocin (OT), a neuropeptide pivotal in social and reproductive behaviors, has recently gained attention for its potential impact on cognitive processes relevant to creativity. Yet, the direct intricate interplay between OT and creativity, particularly in the context of individual differences in motivational orientations, remains poorly understood. Here, we investigated the effects of intranasal OT on creative thinking in individuals characterized by varying levels of approach and avoidance motivations. The initial study, involving participants with high approach or avoidance motivation, employed the Alternative Uses Task to assess creativity under OT administration. Subsequently, the second study induced different motivational states through a recall task, aiming to validate and extend observed effects. Results revealed a significant enhancement of creativity in individuals with approach motivation following OT administration, while no parallel effect was discerned in those with avoidance motivation. Aligning with behavioral findings, functional connectivity and graph theory analyses of neural data illuminated the coordinated effects of OT on creativity-related neural networks. These outcomes collectively suggest that OT exerts a dissociable influence on creativity contingent upon an individual's motivational tendencies, providing insights into the intricate relationship between OT and human creative behavior.

Fiber length distribution characterizes the brain network maturation during early school-age

Environmental and social changes during early school age have a profound impact on brain development. However, it remains unclear how the brains of typically-developing children adjust white matter to optimize network topology during this period. This study proposes fiber length distribution as a novel nodal metric to capture the continuous maturation of brain network. We acquired dMRI data from N = 30 typically developing children in their first year of primary school and a one-year follow-up. We assessed the longitudinal changes in fiber length distribution, characterized by the median length of connected fibers for each brain region. The length median was positively correlated with degree and betweenness centrality, while negatively correlated with clustering coefficient and local efficiency. From ages 7 to 8, we observed significant decreases in length median in the temporal, superior parietal, anterior cingulate, and medial prefrontal cortices, accompanied by a reduction in long-range connections and an increase in short-range connections. Meta-analytic decoding revealed that the widespread decrease in length median occurred in regions responsible for sensory processing, whereas a more localized increase in length median was observed in regions involved in memory and cognitive control. Finally, simulation tests on healthy adults further supported that the decrease in long-range connections and increase in short-range connections contributed to enhanced network segregation and integration, respectively. Our results suggest that the dual process of short- and long-range fiber changes reflects a cost-efficient strategy for optimizing network organization during this critical developmental stage.

Functional Hierarchy of the Human Neocortex from Cradle to Grave

Recent evidence indicates that the organization of the human neocortex is underpinned by smooth spatial gradients of functional connectivity (FC). These gradients provide crucial insight into the relationship between the brain's topographic organization and the texture of human cognition. However, no studies to date have charted how intrinsic FC gradient architecture develops across the entire human lifespan. In this work, we model developmental trajectories of the three primary gradients of FC using a large, high-quality, and temporally-dense functional MRI dataset spanning from birth to 100 years of age. The gradient axes, denoted as sensorimotor-association (SA), visual-somatosensory (VS), and modulation-representation (MR), encode crucial hierarchical organizing principles of the brain in development and aging. By tracking their development throughout the human lifespan, we provide the first ever comprehensive low-dimensional normative reference of global FC hierarchical architecture. We observe significant age-related changes in global network features, with global markers of hierarchical organization increasing from birth to early adulthood and decreasing thereafter. During infancy and early childhood, FC organization is shaped by primary sensory processing, dense short-range connectivity, and immature association and control hierarchies. Functional differentiation of transmodal systems supported by long-range coupling drives a convergence toward adult-like FC organization during late childhood, while adolescence and early adulthood are marked by the expansion and refinement of SA and MR hierarchies. While gradient topographies remain stable during late adulthood and aging, we observe decreases in global gradient measures of FC differentiation and complexity from 30 to 100 years. Examining cortical microstructure gradients alongside our functional gradients, we observed that structure-function gradient coupling undergoes differential lifespan trajectories across multiple gradient axes.

Reproducible Brain Charts: An open data resource for mapping brain development and its associations with mental health

Major mental disorders are increasingly understood as disorders of brain development. Large and heterogeneous samples are required to define generalizable links between brain development and psychopathology. To this end, we introduce the Reproducible Brain Charts (RBC), an open data resource that integrates data from 5 large studies of brain development in youth from three continents (N=6,346; 45% Female). Confirmatory bifactor models were used to create harmonized psychiatric phenotypes that capture major dimensions of psychopathology. Following rigorous quality assurance, neuroimaging data were carefully curated and processed using consistent pipelines in a reproducible manner with DataLad, the Configurable Pipeline for the Analysis of Connectomes (C-PAC), and FreeSurfer. Initial analyses of RBC data emphasize the benefit of careful quality assurance and data harmonization in delineating developmental effects and associations with psychopathology. Critically, all RBC data - including harmonized psychiatric phenotypes, unprocessed images, and fully processed imaging derivatives - are openly shared without a data use agreement via the International Neuroimaging Data-sharing Initiative. Together, RBC facilitates large-scale, reproducible, and generalizable research in developmental and psychiatric neuroscience.

A case of severe TBI: Recovery?

Chronic stage neuropsychological assessments of children with severe TBI typically center around a referral question and focus on assessing cognitive, behavioral, and emotional functioning, making differential diagnoses, and planning treatment. When severe TBI-related neurological deficits are subtle and fall outside commonly assessed behavioral indicators, as can happen with theory of mind and social information processing, they can go unobserved and subsequently fail to be assessed. Additionally, should chronic stage cognitive, behavioral, and emotional assessment findings fall within the average to above average range, a child experiencing ongoing significant unassessed severe TBI-related subtle deficits could be mistakenly judged to have "recovered" from their injury; and to be experiencing no significant ongoing residual neurological deficits. To illustrate how this could happen, and how subacute neuroimaging and brain network theory might be early indicators of emergent chronic stage neuropsychological deficits, we present a child with a severe TBI and average to above average cognitive, behavioral, and emotional assessment findings who has comorbid significant deficits in theory of mind and social functioning.

State-dependent inter-network functional connectivity development in neonatal brain from the developing human connectome project

Although recent studies have consistently reported the emergence of resting-state networks in early infancy, the changes in inter-network functional connectivity with age are controversial and the alterations in its dynamics remain unclear at this stage. This study aimed to investigate dynamic functional network connectivity (dFNC) using resting-state functional MRI in 244 full-term (age: 37-44 weeks) and 36 preterm infants (age: 37-43 weeks) from the dHCP dataset. We evaluated whether early dFNC exhibits age-dependent changes and is influenced by preterm birth. Gestational age (GA) and postnatal age (PNA) showed different effects on variance of FNC change over time during fMRI scan in resting-state networks, especially among high-order association networks. These variances were significantly reduced by preterm birth. Moreover, two states of weakly-connected (State Ⅰ) and strongly-connected (State Ⅱ) FNC were identified. The fraction window and dwell time in State Ⅰ, and the transition from State Ⅱ to State Ⅰ, all showed significantly negative correlations with both GA and PNA. Preterm-born infants spent a longer time in the weakly-connected state compared to term-born infants. These findings suggest a state-dependent development of dynamic FNC across brain networks in the early stages, gradually reconfiguring towards a more flexible and dynamic system with stronger connections.

Early Infant Prefrontal Cortical Microstructure Predicts Present and Future Emotionality

BACKGROUND

High levels of infant negative emotionality (NE) and low positive emotionality (PE) predict future emotional and behavioral problems. The prefrontal cortex (PFC) supports emotional regulation, with each PFC subregion specializing in specific emotional processes. Neurite orientation dispersion and density imaging estimates microstructural integrity and myelination via the neurite density index (NDI) and dispersion via the orientation dispersion index (ODI), with potential to more accurately evaluate microstructural alterations in the developing brain. Yet, no study has used these indices to examine associations between PFC microstructure and concurrent or developing infant emotionality.

METHODS

We modeled PFC subregional NDI and ODI at 3 months with caregiver-reported infant NE and PE at 3 months (n = 61) and at 9 months (n = 50), using multivariable and subsequent bivariate regression models.

RESULTS

The most robust statistically significant findings were positive associations among 3-month rostral anterior cingulate cortex (ACC) ODI and caudal ACC NDI and concurrent NE, a positive association between 3-month lateral orbitofrontal cortex ODI and prospective NE, and a negative association between 3-month dorsolateral PFC ODI and concurrent PE. Multivariate models also revealed that other PFC subregional microstructure measures, as well as infant and caregiver sociodemographic and clinical factors, predicted infant 3- and 9-month NE and PE.

CONCLUSIONS

Greater NDI and ODI, reflecting greater microstructural complexity, in PFC regions supporting salience perception (rostral ACC), decision making (lateral orbitofrontal cortex), action selection (caudal ACC), and attentional processes (dorsolateral PFC) might result in greater integration of these subregions with other neural networks and greater attention to salient negative external cues, thus higher NE and/or lower PE. These findings provide potential infant cortical markers of future psychopathology risk.

The importance of sleep for the developing brain

Purpose of review

This paper summarizes recent research regarding the possible contribution of sleep to brain development. Major milestones in brain development and the methods used to track these changes are reviewed. Changes in sleep, at both behavioral and neural levels, that take place during the same developmental periods are discussed. Finally, a few empirical examples that have contributed new knowledge regarding how sleep contributes to brain development are highlighted.

Recent findings

Empirical examples demonstrating associations between development of sleep and the brain include: predictive associations between SWA topography and myelin development, associations between SWS and hippocampal development, and links between sleep duration and both white matter volume and whole-brain functional connectivity in developing populations.

Summary

There is evidence that sleep is important for the developing brain. However, studies utilizing longitudinal, objective measures of sleep, high-resolution brain imaging, and behavioral measures across developmental are critical for understanding sleep function.

Segregation of the regional radiomics similarity network exhibited an increase from late childhood to early adolescence: A developmental investigation

Brain development is characterized by an increase in structural and functional segregation, which supports the specialization of cognitive processes within the context of network neuroscience. In this study, we investigated age-related changes in morphological segregation using individual Regional Radiomics Similarity Networks (R2SNs) constructed with a longitudinal dataset of 494 T1-weighted MR scans from 309 typically developing children aged 6.2 to 13 years at baseline. Segertation indices were defined as the relative difference in connectivity strengths within and between modules and cacluated at the global, system and local levels. Linear mixed-effect models revealed longitudinal increases in both global and system segregation indices, particularly within the limbic and dorsal attention network, and decreases within the ventral attention network. Superior performance in working memory and inhibitory control was associated with higher system-level segregation indices in default, frontoparietal, ventral attention, somatomotor and subcortical systems, and lower local segregation indices in visual network regions, regardless of age. Furthermore, gene enrichment analysis revealed correlations between age-related changes in local segregation indices and regional expression levels of genes related to developmental processes. These findings provide novel insights into typical brain developmental changes using R2SN-derived segregation indices, offering a valuable tool for understanding human brain structural and cognitive maturation.

Resting state functional brain connectivity in child and adolescent psychiatry: where are we now?

Approaching the 30th anniversary of the discovery of resting state functional magnetic resonance imaging (rsfMRI) functional connectivity, we reflect on the impact of this neuroimaging breakthrough on the field of child and adolescent psychiatry. The study of intrinsic functional brain architecture that rsfMRI affords across a wide range of ages and abilities has yielded numerous key insights. For example, we now know that many neurodevelopmental conditions are associated with more widespread circuit alterations across multiple large-scale brain networks than previously suspected. The emergence of population neuroscience and effective data-sharing initiatives have made large rsfMRI datasets publicly available, providing sufficient power to begin to identify brain-based subtypes within heterogeneous clinical conditions. Nevertheless, several methodological and theoretical challenges must still be addressed to fulfill the promises of personalized child and adolescent psychiatry. In particular, incomplete understanding of the physiological mechanisms driving developmental changes in intrinsic functional connectivity remains an obstacle to further progress. Future directions include cross-species and multimodal neuroimaging investigations to illuminate such mechanisms. Data collection and harmonization efforts that span multiple countries and diverse cohorts are urgently needed. Finally, incorporating naturalistic fMRI paradigms such as movie watching should be a priority for future research efforts.

MADE-for-ASD: A multi-atlas deep ensemble network for diagnosing Autism Spectrum Disorder

In response to the global need for efficient early diagnosis of Autism Spectrum Disorder (ASD), this paper bridges the gap between traditional, time-consuming diagnostic methods and potential automated solutions. We propose a multi-atlas deep ensemble network, MADE-for-ASD, that integrates multiple atlases of the brain's functional magnetic resonance imaging (fMRI) data through a weighted deep ensemble network. Our approach integrates demographic information into the prediction workflow, which enhances ASD diagnosis performance and offers a more holistic perspective on patient profiling. We experiment with the well-known publicly available ABIDE (Autism Brain Imaging Data Exchange) I dataset, consisting of resting state fMRI data from 17 different laboratories around the globe. Our proposed system achieves 75.20% accuracy on the entire dataset and 96.40% on a specific subset - both surpassing reported ASD diagnosis accuracy in ABIDE I fMRI studies. Specifically, our model improves by 4.4 percentage points over prior works on the same amount of data. The model exhibits a sensitivity of 82.90% and a specificity of 69.70% on the entire dataset, and 91.00% and 99.50%, respectively, on the specific subset. We leverage the F-score to pinpoint the top 10 ROI in ASD diagnosis, such as precuneus and anterior cingulate/ventromedial. The proposed system can potentially pave the way for more cost-effective, efficient and scalable strategies in ASD diagnosis. Codes and evaluations are publicly available at https://github.com/hasan-rakibul/MADE-for-ASD.

Consequences of vestibular hypofunction in children with ADHD/DCD

BACKGROUND

Children with Attention Deficit Hyperactivity Disorder (ADHD) demonstrate a heterogeneous sensorimotor, emotional, and cognitive profile. Comorbid sensorimotor imbalance, anxiety, and spatial disorientation are particularly prevalent among their non-core symptoms. Studies in other populations presented these three comorbid dysfunctions in the context of vestibular hypofunction.

OBJECTIVE

To test whether there is a subgroup of children with ADHD who have vestibular hypofunction presenting with concomitant imbalance, anxiety, and spatial disorientation.

METHODS

Children with ADHD-only (n = 28), ADHD + Developmental Coordination Disorder (ADHD + DCD; n = 38), and Typical Development (TD; n = 19) were evaluated for vestibular function by the Dynamic Visual Acuity test (DVA-t), balance by the Bruininks-Oseretsky Test of motor proficiency (BOT-2), panic anxiety by the Screen for Child Anxiety Related Emotional Disorders questionnaire-Child version (SCARED-C), and spatial navigation by the Triangular Completion test (TC-t).

RESULTS

Children with ADHD vs. TD presented with a high rate of vestibular hypofunction (65 vs. 0 %), imbalance (42 vs. 0 %), panic anxiety (27 vs. 11 %), and spatial disorientation (30 vs. 5 %). Children with ADHD + DCD contributed more frequent and severe vestibular hypofunction and imbalance than children with ADHD-only (74 vs. 54 %; 58 vs. 21 %, respectively). A concomitant presence of imbalance, anxiety, and spatial disorientation was observed in 33 % of children with ADHD, all sharing vestibular hypofunction.

CONCLUSIONS

Vestibular hypofunction may be the common pathophysiology of imbalance, anxiety, and spatial disorientation in children. These comorbidities are preferentially present in children with ADHD + DCD rather than ADHD-only, thus likely related to DCD rather than to ADHD disorder. Children with this profile may benefit from a vestibular rehabilitation intervention.

Towards a neurodevelopmental cognitive perspective of temporal processing

The ability to organize and memorize the unfolding of events over time is a fundamental feature of cognition, which develops concurrently with the maturation of the brain. Nonetheless, how temporal processing evolves across the lifetime as well as the links with the underlying neural substrates remains unclear. Here, we intend to retrace the main developmental stages of brain structure, function, and cognition linked to the emergence of timing abilities. This neurodevelopmental perspective aims to untangle the puzzling trajectory of temporal processing aspects across the lifetime, paving the way to novel neuropsychological assessments and cognitive rehabilitation strategies.

Microinstrumentation for Brain Organoids

Brain organoids are three-dimensional aggregates of self-organized differentiated stem cells that mimic the structure and function of human brain regions. Organoids bridge the gaps between conventional drug screening models such as planar mammalian cell culture, animal studies, and clinical trials. They can revolutionize the fields of developmental biology, neuroscience, toxicology, and computer engineering. Conventional microinstrumentation for conventional cellular engineering, such as planar microfluidic chips; microelectrode arrays (MEAs); and optical, magnetic, and acoustic techniques, has limitations when applied to three-dimensional (3D) organoids, primarily due to their limits with inherently two-dimensional geometry and interfacing. Hence, there is an urgent need to develop new instrumentation compatible with live cell culture techniques and with scalable 3D formats relevant to organoids. This review discusses conventional planar approaches and emerging 3D microinstrumentation necessary for advanced organoid-machine interfaces. Specifically, this article surveys recently developed microinstrumentation, including 3D printed and curved microfluidics, 3D and fast-scan optical techniques, buckling and self-folding MEAs, 3D interfaces for electrochemical measurements, and 3D spatially controllable magnetic and acoustic technologies relevant to two-way information transfer with brain organoids. This article highlights key challenges that must be addressed for robust organoid culture and reliable 3D spatiotemporal information transfer.

Screen time, brain network development and socio-emotional competence in childhood: moderation of associations by parent-child reading

BACKGROUND

Screen time in infancy is linked to changes in social-emotional development but the pathway underlying this association remains unknown. We aim to provide mechanistic insights into this association using brain network topology and to examine the potential role of parent-child reading in mitigating the effects of screen time.

METHODS

We examined the association of screen time on brain network topology using linear regression analysis and tested if the network topology mediated the association between screen time and later socio-emotional competence. Lastly, we tested if parent-child reading time was a moderator of the link between screen time and brain network topology.

RESULTS

Infant screen time was significantly associated with the emotion processing-cognitive control network integration (p = 0.005). This network integration also significantly mediated the association between screen time and both measures of socio-emotional competence (BRIEF-2 Emotion Regulation Index, p = 0.04; SEARS total score, p = 0.04). Parent-child reading time significantly moderated the association between screen time and emotion processing-cognitive control network integration (β = -0.640, p = 0.005).

CONCLUSION

Our study identified emotion processing-cognitive control network integration as a plausible biological pathway linking screen time in infancy and later socio-emotional competence. We also provided novel evidence for the role of parent-child reading in moderating the association between screen time and topological brain restructuring in early childhood.

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.

Neurodevelopment of children exposed to prolonged anesthesia in infancy: GABA study interim analysis of resting-state brain networks at 2, 4, and 10-months old

BACKGROUND

Previous studies have raised concerns regarding neurodevelopmental impacts of early exposures to general anesthesia and surgery. Electroencephalography (EEG) can be used to study ontogeny of brain networks during infancy. As a substudy of an ongoing study, we examined measures of functional connectivity in awake infants with prior early and prolonged anesthetic exposures and in control infants.

METHODS

EEG functional connectivity was assessed using debiased weighted phase lag index at source and sensor levels and graph theoretical measures for resting state activity in awake infants in the early anesthesia (n = 26 at 10 month visit, median duration of anesthesia = 4 [2, 7 h]) and control (n = 38 at 10 month visit) groups at ages approximately 2, 4 and 10 months. Theta and low alpha frequency bands were of primary interest. Linear mixed models incorporated impact of age and cumulative hours of general anesthesia exposure.

RESULTS

Models showed no significant impact of cumulative hours of general anesthesia exposure on debiased weighted phase lag index, characteristic path length, clustering coefficient or small-worldness (conditional R2 0.05-0.34). An effect of age was apparent in many of these measures.

CONCLUSIONS

We could not demonstrate significant impact of general anesthesia in the first months of life on early development of resting state brain networks over the first postnatal year. Future studies will explore these networks as these infants grow older.

Evoked oscillatory cortical activity during acute pain: Probing brain in pain by transcranial magnetic stimulation combined with electroencephalogram

Temporal dynamics of local cortical rhythms during acute pain remain largely unknown. The current study used a novel approach based on transcranial magnetic stimulation combined with electroencephalogram (TMS-EEG) to investigate evoked-oscillatory cortical activity during acute pain. Motor (M1) and dorsolateral prefrontal cortex (DLPFC) were probed by TMS, respectively, to record oscillatory power (event-related spectral perturbation and relative spectral power) and phase synchronization (inter-trial coherence) by 63 EEG channels during experimentally induced acute heat pain in 24 healthy participants. TMS-EEG was recorded before, during, and after noxious heat (acute pain condition) and non-noxious warm (Control condition), delivered in a randomized sequence. The main frequency bands (α, β1, and β2) of TMS-evoked potentials after M1 and DLPFC stimulation were recorded close to the TMS coil and remotely. Cold and heat pain thresholds were measured before TMS-EEG. Over M1, acute pain decreased α-band oscillatory power locally and α-band phase synchronization remotely in parietal-occipital clusters compared with non-noxious warm (all p < .05). The remote (parietal-occipital) decrease in α-band phase synchronization during acute pain correlated with the cold (p = .001) and heat pain thresholds (p = .023) and to local (M1) α-band oscillatory power decrease (p = .024). Over DLPFC, acute pain only decreased β1-band power locally compared with non-noxious warm (p = .015). Thus, evoked-oscillatory cortical activity to M1 stimulation is reduced by acute pain in central and parietal-occipital regions and correlated with pain sensitivity, in contrast to DLPFC, which had only local effects. This finding expands the significance of α and β band oscillations and may have relevance for pain therapies.

The maternal-fetal neurodevelopmental groundings of preterm birth risk

Background

Altered neurodevelopment is a major clinical sequela of Preterm Birth (PTB) being currently unexplored in-utero.

Aims

To study the link between fetal brain functional (FbF) connectivity and preterm birth, using resting-state functional magnetic resonance imaging (rs-fMRI).

Study design

Prospective single-centre cohort study.

Subjects

A sample of 31 singleton pregnancies at 28-34 weeks assigned to a low PTB risk (LR) (n = 19) or high PTB risk (HR) (n = 12) group based on a) the Maternal Frailty Inventory (MaFra) for PTB risk; b) a case-specific PTB risk gradient.

Methods

Fetal brain rs-fMRI was performed on 1.5T MRI scanner. First, directed causal relations representing fetal brain functional connectivity measurements were estimated using the Greedy Equivalence Search (GES) algorithm. HR vs. LR group differences were then tested with a novel ad-hoc developed Monte Carlo permutation test. Second, a MaFra-only random forest (RF) was compared against a MaFra-Neuro RF, trained by including also the most important fetal brain functional connections. Third, correlation and regression analyses were performed between MaFra-Neuro class probabilities and i) the GA at birth; ii) PTB risk gradient, iii) perinatal clinical conditions and iv) PTB below 37 weeks.

Results

First, fewer fetal brain functional connections were evident in the HR group. Second, the MaFra-Neuro RF improved PTB risk prediction. Third, MaFra-Neuro class probabilities showed a significant association with: i) GA at birth; ii) PTB risk gradient, iii) perinatal clinical conditions and iv) PTB below 37 weeks.

Conclusion

Fetal brain functional connectivity is a novel promising predictor of PTB, linked to maternal risk profiles, ahead of birth, and clinical markers of neurodevelopmental risk, at birth, thus potentially "connecting" different PTB phenotypes.

Synaptic-dependent developmental dysconnectivity in 22q11.2 deletion syndrome

Chromosome 22q11.2 deletion is among the strongest known genetic risk factors for neuropsychiatric disorders, including autism and schizophrenia. Brain imaging studies have reported disrupted large-scale functional connectivity in people with 22q11 deletion syndrome (22q11DS). However, the significance and biological determinants of these functional alterations remain unclear. Here, we use a cross-species design to investigate the developmental trajectory and neural underpinnings of brain dysconnectivity in 22q11DS. We find that LgDel mice, an established mouse model of 22q11DS, exhibit age-specific patterns of functional MRI (fMRI) dysconnectivity, with widespread fMRI hyper-connectivity in juvenile mice reverting to focal hippocampal hypoconnectivity over puberty. These fMRI connectivity alterations are mirrored by co-occurring developmental alterations in dendritic spine density, and are both transiently normalized by developmental GSK3β inhibition, suggesting a synaptic origin for this phenomenon. Notably, analogous hyper- to hypoconnectivity reconfiguration occurs also in human 22q11DS, where it affects hippocampal and cortical regions spatially enriched for synaptic genes that interact with GSK3β, and autism-relevant transcripts. Functional dysconnectivity in somatomotor components of this network is predictive of age-dependent social alterations in 22q11.2 deletion carriers. Taken together, these findings suggest that synaptic-related mechanisms underlie developmentally mediated functional dysconnectivity in 22q11DS.

Multivariate Assessment of Inhibitory Control in Youth: Links With Psychopathology and Brain Function

Inhibitory control is central to many theories of cognitive and brain development, and impairments in inhibitory control are posited to underlie developmental psychopathology. In this study, we tested the possibility of shared versus unique associations between inhibitory control and three common symptom dimensions in youth psychopathology: attention-deficit/hyperactivity disorder (ADHD), anxiety, and irritability. We quantified inhibitory control using four different experimental tasks to estimate a latent variable in 246 youth (8-18 years old) with varying symptom types and levels. Participants were recruited from the Washington, D.C., metro region. Results of structural equation modeling integrating a bifactor model of psychopathology revealed that inhibitory control predicted a shared or general psychopathology dimension, but not ADHD-specific, anxiety-specific, or irritability-specific dimensions. Inhibitory control also showed a significant, selective association with global efficiency in a frontoparietal control network delineated during resting-state functional magnetic resonance imaging. These results support performance-based inhibitory control linked to resting-state brain function as an important predictor of comorbidity in youth psychopathology.

Community detection in the human connectome: Method types, differences and their impact on inference

Community structure is a fundamental topological characteristic of optimally organized brain networks. Currently, there is no clear standard or systematic approach for selecting the most appropriate community detection method. Furthermore, the impact of method choice on the accuracy and robustness of estimated communities (and network modularity), as well as method-dependent relationships between network communities and cognitive and other individual measures, are not well understood. This study analyzed large datasets of real brain networks (estimated from resting-state fMRI fromn $$ n $$ = 5251 pre/early adolescents in the adolescent brain cognitive development [ABCD] study), andn $$ n $$ = 5338 synthetic networks with heterogeneous, data-inspired topologies, with the goal to investigate and compare three classes of community detection methods: (i) modularity maximization-based (Newman and Louvain), (ii) probabilistic (Bayesian inference within the framework of stochastic block modeling (SBM)), and (iii) geometric (based on graph Ricci flow). Extensive comparisons between methods and their individual accuracy (relative to the ground truth in synthetic networks), and reliability (when applied to multiple fMRI runs from the same brains) suggest that the underlying brain network topology plays a critical role in the accuracy, reliability and agreement of community detection methods. Consistent method (dis)similarities, and their correlations with topological properties, were estimated across fMRI runs. Based on synthetic graphs, most methods performed similarly and had comparable high accuracy only in some topological regimes, specifically those corresponding to developed connectomes with at least quasi-optimal community organization. In contrast, in densely and/or weakly connected networks with difficult to detect communities, the methods yielded highly dissimilar results, with Bayesian inference within SBM having significantly higher accuracy compared to all others. Associations between method-specific modularity and demographic, anthropometric, physiological and cognitive parameters showed mostly method invariance but some method dependence as well. Although method sensitivity to different levels of community structure may in part explain method-dependent associations between modularity estimates and parameters of interest, method dependence also highlights potential issues of reliability and reproducibility. These findings suggest that a probabilistic approach, such as Bayesian inference in the framework of SBM, may provide consistently reliable estimates of community structure across network topologies. In addition, to maximize robustness of biological inferences, identified network communities and their cognitive, behavioral and other correlates should be confirmed with multiple reliable detection methods.

Epilepsy-related functional brain network alterations are already present at an early age in the GAERS rat model of genetic absence epilepsy

Introduction

Genetic Absence Epilepsy Rats from Strasbourg (GAERS) represent a model of genetic generalized epilepsy. The present longitudinal study in GAERS and age-matched non-epileptic controls (NEC) aimed to characterize the epileptic brain network using two functional measures, resting state-functional magnetic resonance imaging (rs-fMRI) and manganese-enhanced MRI (MEMRI) combined with morphometry, and to investigate potential brain network alterations, following long-term seizure activity.

Methods

Repeated rs-fMRI measurements at 9.4 T between 3 and 8 months of age were combined with MEMRI at the final time point of the study. We used graph theory analysis to infer community structure and global and local network parameters from rs-fMRI data and compared them to brain region-wise manganese accumulation patterns and deformation-based morphometry (DBM).

Results

Functional connectivity (FC) was generally higher in GAERS when compared to NEC. Global network parameters and community structure were similar in NEC and GAERS, suggesting efficiently functioning networks in both strains. No progressive FC changes were observed in epileptic animals. Network-based statistics (NBS) revealed stronger FC within the cortical community, including regions of association and sensorimotor cortex, and with basal ganglia and limbic regions in GAERS, irrespective of age. Higher manganese accumulation in GAERS than in NEC was observed at 8 months of age, consistent with higher overall rs-FC, particularly in sensorimotor cortex and association cortex regions. Functional measures showed less similarity in subcortical regions. Whole brain volumes of 8 months-old GAERS were higher when compared to age-matched NEC, and DBM revealed increased volumes of several association and sensorimotor cortex regions and of the thalamus.

Discussion

rs-fMRI, MEMRI, and volumetric data collectively suggest the significance of cortical networks in GAERS, which correlates with an increased fronto-central connectivity in childhood absence epilepsy (CAE). Our findings also verify involvement of basal ganglia and limbic regions. Epilepsy-related network alterations are already present in juvenile animals. Consequently, this early condition seems to play a greater role in dynamic brain function than chronic absence seizures.

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.

Reduced Cortico-Cortical Resting-State Connectivity in Sensory Systems Related to Bodily Pain in Juvenile Fibromyalgia

OBJECTIVE

Juvenile-onset fibromyalgia (JFM) is a paradigmatic chronic pain condition for which the underlying neurobiological substrates are poorly understood. This study examined, for the first time, data-driven resting-state functional connectivity (rsFC) alterations in 37 female adolescents with JFM compared with 43 healthy female adolescents and identified associations with bodily pain.

METHODS

Whole-brain voxel-wise rsFC alterations were assessed using the intrinsic connectivity contrast, a measure of node centrality at each voxel, and seed-based analyses for interpretability. We studied the relationship between rsFC alterations in somatosensory systems and the location and extension of bodily pain.

RESULTS

Adolescents with JFM had voxel-wise rsFC reductions in the paracentral lobule (PCL)/primary somatosensory cortex (S1) (T = 4.89, family-wise error corrected p-value (pFWE) < 0.001) and left midcingulate cortex (T = 4.67, pFWE = 0.043). Post hoc analyses revealed reduced rsFC spanning major cortical sensory hubs (T > 4.4, pFWE < 0.030). Cortico-cortical rsFC reductions within PCL/S1 in JFM occurred in locations innervated by bodily areas where the pain was most frequent (F = 3.15; positive false discovery rate = 0.029) and predicted widespread pain (T > 4.4, pFWE < 0.045). Conversely, adolescents with JFM had increases in PCL/S1-thalamus (T = 4.75, pFWE = 0.046) and PCL/S1-anterior insula rsFC (T = 5.13, pFWE = 0.039).

CONCLUSION

Reduced cortico-cortical sensory integration involving PCL/S1 and spanning the sensory systems may underly critical pain sensory features in youth with JFM. Reduced sensory integration is paralleled by augmented cross-talk between sensory and affective/salience-processing regions, potentially indicating a shift toward more affectively colored sensory experiences to the detriment of specific sensory discrimination.

Air pollution and age-dependent changes in emotional behavior across early adolescence in the U.S

Recent studies have linked air pollution to increased risk for behavioral problems during development, albeit with inconsistent findings. Additional longitudinal studies are needed that consider how emotional behaviors may be affected when exposure coincides with the transition to adolescence - a vulnerable time for developing mental health difficulties. This study investigates if annual average PM2.5 and NO2 exposure at ages 9-10 years moderates age-related changes in internalizing and externalizing behaviors over a 2-year follow-up period in a large, nationwide U.S. sample of participants from the Adolescent Brain Cognitive Development (ABCD) Study®. Air pollution exposure was estimated based on the residential address of each participant using an ensemble-based modeling approach. Caregivers answered questions from the Child Behavior Checklist (CBCL) at the baseline, 1-year follow-up, and 2-year follow-up visits, for a total of 3 waves of data; from the CBCL we obtained scores on internalizing and externalizing problems plus 5 syndrome scales (anxious/depressed, withdrawn/depressed, rule-breaking behavior, aggressive behavior, and attention problems). Zero-inflated negative binomial models were used to examine both the main effect of age as well as the interaction of age with each pollutant on behavior while adjusting for various socioeconomic and demographic characteristics. Against our hypothesis, there was no evidence that greater air pollution exposure was related to more behavioral problems with age over time.

Differences in Brain Network Topology Based on Alcohol Use History in Adolescents

Approximately 6 million youth aged 12 to 20 consume alcohol monthly in the United States. The effect of alcohol consumption in adolescence on behavior and cognition is heavily researched; however, little is known about how alcohol consumption in adolescence may alter brain function, leading to long-term developmental detriments. In order to investigate differences in brain connectivity associated with alcohol use in adolescents, brain networks were constructed using resting-state functional magnetic resonance imaging data collected by the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) from 698 youth (12-21 years; 117 hazardous drinkers and 581 no/low drinkers). Analyses assessed differences in brain network topology based on alcohol consumption in eight predefined brain networks, as well as in whole-brain connectivity. Within the central executive network (CEN), basal ganglia network (BGN), and sensorimotor network (SMN), no/low drinkers demonstrated stronger and more frequent connections between highly globally efficient nodes, with fewer and weaker connections between highly clustered nodes. Inverse results were observed within the dorsal attention network (DAN), visual network (VN), and frontotemporal network (FTN), with no/low drinkers demonstrating weaker connections between nodes with high efficiency and increased frequency of clustered nodes compared to hazardous drinkers. Cross-sectional results from this study show clear organizational differences between adolescents with no/low or hazardous alcohol use, suggesting that aberrant connectivity in these brain networks is associated with risky drinking behaviors.

Hippocampal Resting State Functional Connectivity Associated with Physical Activity in Periadolescent Children

Periadolescence is a neurodevelopmental period characterized by structural and functional brain changes that are associated with cognitive maturation. The development of the functional connectivity of the hippocampus contributes to cognitive maturation, especially memory processes. Notably, hippocampal development is influenced by lifestyle factors, including physical activity. Physical activity has been associated with individual variability in hippocampal functional connectivity. However, this relationship has not been characterized in a developmental cohort. In this study, we aimed to fill this gap by investigating the relationship between physical activity and the functional connectivity of the hippocampus in a cohort of periadolescents aged 8-13 years (N = 117). The participants completed a physical activity questionnaire, reporting the number of days per week they performed 60 min of physical activity; then, they completed a resting-state functional MRI scan. We observed that greater physical activity was significantly associated with differences in hippocampal functional connectivity in frontal and temporal regions. Greater physical activity was associated with decreased connectivity between the hippocampus and the right superior frontal gyrus and increased connectivity between the hippocampus and the left superior temporal sulcus. Capturing changes in hippocampal functional connectivity during key developmental periods may elucidate how lifestyle factors including physical activity influence brain network connectivity trajectories, cognitive development, and future disease risk.

Parcellation-Based Connectivity Model of the Judgement Core

Judgement is a higher-order brain function utilized in the evaluation process of problem solving. However, heterogeneity in the task methodology based on the many definitions of judgement and its expansive and nuanced applications have prevented the identification of a unified cortical model at a level of granularity necessary for clinical translation. Forty-six task-based fMRI studies were used to generate activation-likelihood estimations (ALE) across moral, social, risky, and interpersonal judgement paradigms. Cortical parcellations overlapping these ALEs were used to delineate patterns in neurocognitive network engagement for the four judgement tasks. Moral judgement involved the bilateral superior frontal gyri, right temporal gyri, and left parietal lobe. Social judgement demonstrated a left-dominant frontoparietal network with engagement of right-sided temporal limbic regions. Moral and social judgement tasks evoked mutual engagement of the bilateral DMN. Both interpersonal and risk judgement were shown to involve a right-sided frontoparietal network with accompanying engagement of the left insular cortex, converging at the right-sided CEN. Cortical activation in normophysiological judgement function followed two separable patterns involving the large-scale neurocognitive networks. Specifically, the DMN was found to subserve judgement centered around social inferences and moral cognition, while the CEN subserved tasks involving probabilistic reasoning, risk estimation, and strategic contemplation.

Different patterns of intrinsic functional connectivity at the default mode and attentional networks predict crystalized and fluid abilities in childhood

Crystallized abilities are skills used to solve problems based on experience, while fluid abilities are linked to reasoning without evoke prior knowledge. To what extent crystallized and fluid abilities involve dissociated or overlapping neural systems is debatable. Due to often deployed small sample sizes or different study settings in prior work, the neural basis of crystallized and fluid abilities in childhood remains largely unknown. Here we analyzed within and between network connectivity patterns from resting-state functional MRI of 2707 children between 9 and 10 years from the ABCD study. We hypothesized that differences in functional connectivity at the default mode network (DMN), ventral, and dorsal attentional networks (VAN, DAN) explain differences in fluid and crystallized abilities. We found that stronger between-network connectivity of the DMN and VAN, DMN and DAN, and VAN and DAN predicted crystallized abilities. Within-network connectivity of the DAN predicted both crystallized and fluid abilities. Our findings reveal that crystallized abilities rely on the functional coupling between attentional networks and the DMN, whereas fluid abilities are associated with a focal connectivity configuration at the DAN. Our study provides new evidence into the neural basis of child intelligence and calls for future comparative research in adulthood during neuropsychiatric diseases.

Current Evidence for Biological Biomarkers and Mechanisms Underlying Acute to Chronic Pain Transition across the Pediatric Age Spectrum

Chronic pain is highly prevalent in the pediatric population. Many factors are involved in the transition from acute to chronic pain. Currently, there are conceptual models proposed, but they lack a mechanistically sound integrated theory considering the stages of child development. Objective biomarkers are critically needed for the diagnosis, risk stratification, and prognosis of the pathological stages of pain chronification. In this article, we summarize the current evidence on mechanisms and biomarkers of acute to chronic pain transitions in infants and children through the developmental lens. The goal is to identify gaps and outline future directions for basic and clinical research toward a developmentally informed theory of pain chronification in the pediatric population. At the outset, the importance of objective biomarkers for chronification of pain in children is outlined, followed by a summary of the current evidence on the mechanisms of acute to chronic pain transition in adults, in order to contrast with the developmental mechanisms of pain chronification in the pediatric population. Evidence is presented to show that chronic pain may have its origin from insults early in life, which prime the child for the development of chronic pain in later life. Furthermore, available genetic, epigenetic, psychophysical, electrophysiological, neuroimaging, neuroimmune, and sex mechanisms are described in infants and older children. In conclusion, future directions are discussed with a focus on research gaps, translational and clinical implications. Utilization of developmental mechanisms framework to inform clinical decision-making and strategies for prevention and management of acute to chronic pain transitions in children, is highlighted.

Visual Perception Is Highly Flexible and Context Dependent in Young Infants: A Case of Top-Down-Modulated Motion Perception

Top-down modulation is an essential cognitive component in human perception. Despite mounting evidence of top-down perceptual modulation in adults, it is largely unknown whether infants can engage in this cognitive function. Here, we examined top-down modulation of motion perception in 6- to 8-month-old infants (recruited in North America) via their smooth-pursuit eye movements. In four experiments, we demonstrated that infants' perception of motion direction can be flexibly shaped by briefly learned predictive cues when no coherent motion is available. The current findings present a novel insight into infant perception and its development: Infant perceptual systems respond to predictive signals engendered from higher-level learning systems, leading to a flexible and context-dependent modulation of perception. This work also suggests that the infant brain is sophisticated, interconnected, and active when placed in a context in which it can learn and predict.

Neural Network Functional Interactions Mediate or Suppress White Matter-Emotional Behavior Relationships in Infants

BACKGROUND

Elucidating the neural basis of infant positive emotionality and negative emotionality can identify biomarkers of pathophysiological risk. Our goal was to determine how functional interactions among large-scale networks supporting emotional regulation influence white matter (WM) microstructural-emotional behavior relationships in 3-month-old infants. We hypothesized that microstructural-emotional behavior relationships would be differentially mediated or suppressed by underlying resting-state functional connectivity (rsFC), particularly between default mode network and central executive network structures.

METHODS

The analytic sample comprised primary caregiver-infant dyads (52 infants [42% female, mean age at scan = 15.10 weeks]), with infant neuroimaging and emotional behavior assessments conducted at 3 months. Infant WM and rsFC were assessed by diffusion-weighted imaging/tractography and resting-state magnetic resonance imaging during natural, nonsedated sleep. The Infant Behavior Questionnaire-Revised provided measures of infant positive emotionality and negative emotionality.

RESULTS

After significant WM-emotional behavior relationships were observed, multimodal analyses were performed using whole-brain voxelwise mediation. Results revealed that greater cingulum bundle volume was significantly associated with lower infant positive emotionality (β = -0.263, p = .031); however, a pattern of lower rsFC between central executive network and default mode network structures suppressed this otherwise negative relationship. Greater uncinate fasciculus volume was significantly associated with lower infant negative emotionality (β = -0.296, p = .022); however, lower orbitofrontal cortex-amygdala rsFC suppressed this otherwise negative relationship, while greater orbitofrontal cortex-central executive network rsFC mediated this relationship.

CONCLUSIONS

Functional interactions among neural networks have an important influence on WM microstructural-emotional behavior relationships in infancy. These relationships can elucidate neural mechanisms that contribute to future behavioral and emotional problems in childhood.

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.

Age-related differences in resting-state functional connectivity from childhood to adolescence

The human brain is active at rest, and spontaneous fluctuations in functional MRI BOLD signals reveal an intrinsic functional architecture. During childhood and adolescence, functional networks undergo varying patterns of maturation, and measures of functional connectivity within and between networks differ as a function of age. However, many aspects of these developmental patterns (e.g. trajectory shape and directionality) remain unresolved. In the present study, we characterised age-related differences in within- and between-network resting-state functional connectivity (rsFC) and integration (i.e. participation coefficient, PC) in a large cross-sectional sample of children and adolescents (n = 628) aged 8-21 years from the Lifespan Human Connectome Project in Development. We found evidence for both linear and non-linear differences in cortical, subcortical, and cerebellar rsFC, as well as integration, that varied by age. Additionally, we found that sex moderated the relationship between age and putamen integration where males displayed significant age-related increases in putamen PC compared with females. Taken together, these results provide evidence for complex, non-linear differences in some brain systems during development.

How past trauma impacts emotional intelligence: Examining the connection

Backed by both research and practice, the organizational psychology field has come to value emotional intelligence (EI) as being vital for leader and employee effectiveness. While this field values EI, it has paid little attention to the antecedents of emotional intelligence, leaving the EI domain without clarity on (1) why EI might vary across individuals, and (2) how to best develop EI. In this article, we rely on neuroscience and psychology research to make the case that past psychological trauma impacts later EI capabilities. Specifically, we present evidence that psychological trauma impairs the brain areas and functions that support EI. Establishing psychological trauma has valuable theoretical and practical implications that include providing an explanation of why EI might vary across individuals and providing a focus for improving EI: healing from past trauma. Further theoretical and practical implications for the field of organizational psychology are provided.

Air pollution and emotional behavior in adolescents across the U.S

Recent studies have linked air pollution to increased risk for behavioral problems during development, albeit with inconsistent findings. Additional longitudinal studies are needed that consider how emotional behaviors may be affected when exposure coincides with the transition to adolescence - a vulnerable time for developing mental health difficulties. This study examines how annual average PM2.5 and NO2 exposure at ages 9-10 years relates to internalizing and externalizing behaviors over a 2-year follow-up period in a large, nationwide U.S. sample of participants from the Adolescent Brain Cognitive Development (ABCD) Study®. Air pollution exposure was estimated based on the residential address of each participant using an ensemble-based modeling approach. Caregivers answered questions from the Child Behavior Checklist (CBCL) at baseline and annually for two follow-up sessions for a total of 3 waves of data; from the CBCL we obtained scores on internalizing and externalizing problems plus 5 syndrome scales (anxious/depressed, withdrawn/depressed, rule-breaking behavior, aggressive behavior, and attention problems). Zero-inflated negative binomial models were used to examine both the main effect of age as well as the interaction of age with each pollutant on behavior while adjusting for various socioeconomic and demographic characteristics. Overall, the pollution effects moderated the main effects of age with higher levels of PM2.5 and NO2 leading to an even greater likelihood of having no behavioral problems (i.e., score of zero) with age over time, as well as fewer problems when problems are present as the child ages. Albeit this was on the order equal to or less than a 1-point change. Thus, one year of annual exposure at 9-10 years is linked with very small change in emotional behaviors in early adolescence, which may be of little clinical relevance.

Early infant prefrontal gray matter volume is associated with concurrent and future infant emotionality

High levels of infant negative emotionality (NE) are associated with emotional and behavioral problems later in childhood. Identifying neural markers of high NE as well as low positive emotionality (PE) in infancy can provide neural markers to aid early identification of vulnerability, and inform interventions to help delay or even prevent psychiatric disorders before the manifestation of symptoms. Prefrontal cortical (PFC) subregions support the regulation of NE and PE, with each PFC subregion differentially specializing in distinct emotional regulation processes. Gray matter (GM) volume measures show good test-retest reliability, and thus have potential use as neural markers of NE and PE. Yet, while studies showed PFC GM structural abnormalities in adolescents and young adults with affective disorders, few studies examined how PFC subregional GM measures are associated with NE and PE in infancy. We aimed to identify relationships among GM in prefrontal cortical subregions at 3 months and caregiver report of infant NE and PE, covarying for infant age and gender and caregiver sociodemographic and clinical variables, in two independent samples at 3 months (Primary: n = 75; Replication sample: n = 40) and at 9 months (Primary: n = 44; Replication sample: n = 40). In the primary sample, greater 3-month medial superior frontal cortical volume was associated with higher infant 3-month NE (p < 0.05); greater 3-month ventrolateral prefrontal cortical volume predicted lower infant 9-month PE (p < 0.05), even after controlling for 3-month NE and PE. GM volume in other PFC subregions also predicted infant 3- and 9-month NE and PE, together with infant demographic factors, caregiver age, and/or caregiver affective instability and anxiety. These findings were replicated in the independent sample. To our knowledge, this is the first study to determine in primary and replication samples associations among infant PFC GM volumes and concurrent and prospective NE and PE, and identify promising, early markers of future psychopathology risk.

Developmental and aging resting functional magnetic resonance imaging brain state adaptations in adolescents and adults: A large N (>47K) study

The brain's functional architecture and organization undergo continual development and modification throughout adolescence. While it is well known that multiple factors govern brain maturation, the constantly evolving patterns of time-resolved functional connectivity are still unclear and understudied. We systematically evaluated over 47,000 youth and adult brains to bridge this gap, highlighting replicable time-resolved developmental and aging functional brain patterns. The largest difference between the two life stages was captured in a brain state that indicated coherent strengthening and modularization of functional coupling within the auditory, visual, and motor subdomains, supplemented by anticorrelation with other subdomains in adults. This distinctive pattern, which we replicated in independent data, was consistently less modular or absent in children and presented a negative association with age in adults, thus indicating an overall inverted U-shaped trajectory. This indicates greater synchrony, strengthening, modularization, and integration of the brain's functional connections beyond adolescence, and gradual decline of this pattern during the healthy aging process. We also found evidence that the developmental changes may also bring along a departure from the canonical static functional connectivity pattern in favor of more efficient and modularized utilization of the vast brain interconnections. State-based statistical summary measures presented robust and significant group differences that also showed significant age-related associations. The findings reported in this article support the idea of gradual developmental and aging brain state adaptation processes in different phases of life and warrant future research via lifespan studies to further authenticate the projected time-resolved brain state trajectories.

Molecular and network-level mechanisms explaining individual differences in autism spectrum disorder

The mechanisms underlying phenotypic heterogeneity in autism spectrum disorder (ASD) are not well understood. Using a large neuroimaging dataset, we identified three latent dimensions of functional brain network connectivity that predicted individual differences in ASD behaviors and were stable in cross-validation. Clustering along these three dimensions revealed four reproducible ASD subgroups with distinct functional connectivity alterations in ASD-related networks and clinical symptom profiles that were reproducible in an independent sample. By integrating neuroimaging data with normative gene expression data from two independent transcriptomic atlases, we found that within each subgroup, ASD-related functional connectivity was explained by regional differences in the expression of distinct ASD-related gene sets. These gene sets were differentially associated with distinct molecular signaling pathways involving immune and synapse function, G-protein-coupled receptor signaling, protein synthesis and other processes. Collectively, our findings delineate atypical connectivity patterns underlying different forms of ASD that implicate distinct molecular signaling mechanisms.

Examining resting-state network connectivity in children exposed to perinatal maternal adversity using anatomically weighted functional connectivity (awFC) analyses; A preliminary report

Introduction

Environmental perturbations during critical periods can have pervasive, organizational effects on neurodevelopment. To date, the literature examining the long-term impact of early life adversity has largely investigated structural and functional imaging data outcomes independently. However, emerging research points to a relationship between functional connectivity and the brain’s underlying structural architecture. For instance, functional connectivity can be mediated by the presence of direct or indirect anatomical pathways. Such evidence warrants the use of structural and functional imaging in tandem to study network maturation. Accordingly, this study examines the impact of poor maternal mental health and socioeconomic context during the perinatal period on network connectivity in middle childhood using an anatomically weighted functional connectivity (awFC) approach. awFC is a statistical model that identifies neural networks by incorporating information from both structural and functional imaging data.

Methods

Resting-state fMRI and DTI scans were acquired from children aged 7–9 years old.

Results

Our results indicate that maternal adversity during the perinatal period can affect offspring’s resting-state network connectivity during middle childhood. Specifically, in comparison to controls, children of mothers who had poor perinatal maternal mental health and/or low socioeconomic status exhibited greater awFC in the ventral attention network.

Discussion

These group differences were discussed in terms of the role this network plays in attention processing and maturational changes that may accompany the consolidation of a more adult-like functional cortical organization. Furthermore, our results suggest that there is value in using an awFC approach as it may be more sensitive in highlighting connectivity differences in developmental networks associated with higher-order cognitive and emotional processing, as compared to stand-alone FC or SC analyses.

First Organoid Intelligence (OI) workshop to form an OI community

The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22-24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.

Neuronal dynamics of the default mode network and anterior insular cortex: Intrinsic properties and modulation by salient stimuli

The default mode network (DMN) is critical for self-referential mental processes, and its dysfunction is implicated in many neuropsychiatric disorders. However, the neurophysiological properties and task-based functional organization of the rodent DMN are poorly understood, limiting its translational utility. Here, we combine fiber photometry with functional magnetic resonance imaging (fMRI) and computational modeling to characterize dynamics of putative rat DMN nodes and their interactions with the anterior insular cortex (AI) of the salience network. Our analysis revealed neuronal activity changes in AI and DMN nodes preceding fMRI-derived DMN activations and cyclical transitions between brain network states. Furthermore, we demonstrate that salient oddball stimuli suppress the DMN and enhance AI neuronal activity and that the AI causally inhibits the retrosplenial cortex, a prominent DMN node. These findings elucidate the neurophysiological foundations of the rodent DMN, its spatiotemporal dynamical properties, and modulation by salient stimuli, paving the way for future translational studies.

Emerging functional connectivity patterns during sevoflurane anaesthesia in the developing human brain

BACKGROUND

Spectral-based EEG is used to monitor anaesthetic state during surgical procedures in adults. Spectral EEG features that can resemble the patterns seen in adults emerge in children after the age of 10 months and cannot distinguish wakefulness and anaesthesia in the youngest children. There is a need to explore alternative EEG measures. We hypothesise that functional connectivity is one of the measures that can help distinguish between consciousness states in children.

METHODS

An EEG data set of children undergoing sevoflurane general anaesthesia (age 0-3 yr) was reanalysed using debiased weighted phase lag index as a measure of functional connectivity in wakefulness (n=38) and anaesthesia (n=73). Network topology measures were compared between states in 0- to 6-, 6- to 10-, and >10-month-old children.

RESULTS

Functional connectivity was reduced in anaesthesia vs wakefulness in delta band (n=cluster of 17 significant connections; P=0.013; 58% connections surviving thresholding in wakefulness and 49% in anaesthesia). Network density and node degree were lower in anaesthesia even in the youngest children (0.57 in wakefulness; 0.48 in anaesthesia; t [9]=3.39; P=0.029; G=0.98; confidence interval [CI] [0.25-1.77]). Modularity was higher in anaesthesia (0-6 months: 0.16 in wakefulness and 0.19 in anaesthesia, t [9]=-2.95, P=0.04, G=-0.85, CI [-1.60 to -0.16]; >10 months: 0.16 vs 0.21, t [13]=-6.45, P<0.001, G=-1.62, CI [-2.49 to -0.85]) and decreased with age (ρ [73]=-0.456; P<0.001).

CONCLUSIONS

Anaesthesia modulates functional connectivity. Increased segregation into a more modular structure in anaesthesia decreases with age as adult-like features develop. These findings advance our understanding of the network architecture underlying the effects of anaesthesia on the developing brain.