A Network Neuroscience Approach to Typical and Atypical Brain Development.

Human brain networks based on neuroimaging data have already proven useful in characterizing both normal and abnormal brain structure and function. However, many brain disorders are neurodevelopmental in origin, highlighting the need to go beyond characterizing brain organization in terms of static networks. Here, we review the fast-growing literature shedding light on developmental changes in network phenotypes. We begin with an overview of recent large-scale efforts to map healthy brain development, and we describe the key role played by longitudinal data including repeated measurements over a long period of follow-up. We also discuss the subtle ways in which healthy brain network development can inform our understanding of disorders, including work bridging the gap between macroscopic neuroimaging results and the microscopic level. Finally, we turn to studies of three specific neurodevelopmental disorders that first manifest primarily in childhood and adolescence/early adulthood, namely psychotic disorders, attention-deficit/hyperactivity disorder, and autism spectrum disorder. In each case we discuss recent progress in understanding the atypical features of brain network development associated with the disorder, and we conclude the review with some suggestions for future directions

Autism as the Early Closure of a Neuroplastic Critical Period Normally Seen in Adolescence

The most severe cases of autism are diagnosed by extreme social dysfunction and other behavioral abnormalities. A number of genetic studies have been conducted to correlate behavioral phenotypes to genetic dysfunctions, but no “autism gene” has yet been discovered. In addition, environmental factors have been found to influence the development of autistic traits with high probability. This review will examine the role of a shortened period of neuroplasticity as a unifying feature of the autistic phenotype. The neuroplastic period of interest normally extends into adolescence, allowing for neural integration and the development of language and social skills. Early closure of this period may result in a shortened period of development, forcing the brain to rely on underdeveloped structures

Comparative analysis of US and European preschool social and emotional learning programs

Social-emotional skills are crucial for preschool children’s mental health and later school success. Most school-based SEL programs originate in the United States, reflecting a robust interest in SEL curricula from preschool through secondary school. While EU Member States are increasingly integrating social and emotional skills programs into school curricula, there is a lack of uniform terminologies, frameworks, and assessment criteria, necessitating the introduction of standardized practices. This study aims to offer an overview of US and European preschool SEL programs, utilizing content analysis to showcase the diversity of these programs. The analysis focuses on programs from the “EU-Self Programs for Social and Emotional Skills Development for Early and Preschool Children Applied in European Countries" by Koltcheva et al. (2022), including impact evaluations of nine programs in total. The study analysed the programs in relation to goals and outcomes, and findings reveal that there are no remarkable differences between US and European preschool SEL programs, although certain trends highlight distinctions among programs of different origins. The study will be useful for practitioners who are interested in introducing a preschool SEL program in their institution.peer-reviewe

The modular organization of brain cortical connectivity across the human lifespan

The network architecture of the human brain contributes in shaping neural activity, influencing cognitive and behavioral processes. The availability of neuroimaging data across the lifespan allows us to monitor how this architecture reorganizes, influenced by processes like learning, adaptation, maturation, and senescence. Changing patterns in brain connectivity can be analyzed with the tools of network science, which can be used to reveal organizational principles such as modular network topology. The identification of network modules is fundamental, as they parse the brain into coherent sub-systems and allow for both functional integration and segregation among different brain areas. In this work we examined the brain's modular organization by developing an ensemble-based multilayer network approach, allowing us to link changes of structural connectivity patterns to development and aging. We show that modular structure exhibits both linear and nonlinear age-related trends. In the early and late lifespan, communities are more modular, and we track the origins of this high modularity to two different substrates in brain connectivity, linked to the number and the weights of the intra-clusters edges. We also demonstrate that aging leads to a progressive and increasing reconfiguration of modules and a redistribution across hemispheres. Finally, we identify those brain regions that most contribute to network reconfiguration and those that remain more stable across the lifespan

A multisample study of longitudinal changes in brain network architecture in 4-13-year-old children

Pathways through Adolescenc

Meta-Network Analysis of Structural Correlation Networks Provides Insights Into Brain Network Development

Analysis of developmental brain networks is fundamentally important for basic developmental neuroscience. In this paper, we focus on the temporally-covarying connection patterns, called meta-networks, and develop a new mathematical model for meta-network decomposition. With the proposed model, we decompose the developmental structural correlation networks of cortical thickness into five meta-networks. Each meta-network exhibits a distinctive spatial connection pattern, and its covarying trajectory highlights the temporal contribution of the meta-network along development. Systematic analysis of the meta-networks and covarying trajectories provides insights into three important aspects of brain network development

Sex differences in brain plasticity: a new hypothesis for sex ratio bias in autism.

Several observations support the hypothesis that differences in synaptic and regional cerebral plasticity between the sexes account for the high ratio of males to females in autism. First, males are more susceptible than females to perturbations in genes involved in synaptic plasticity. Second, sex-related differences in non-autistic brain structure and function are observed in highly variable regions, namely, the heteromodal associative cortices, and overlap with structural particularities and enhanced activity of perceptual associative regions in autistic individuals. Finally, functional cortical reallocations following brain lesions in non-autistic adults (for example, traumatic brain injury, multiple sclerosis) are sex-dependent. Interactions between genetic sex and hormones may therefore result in higher synaptic and consecutively regional plasticity in perceptual brain areas in males than in females. The onset of autism may largely involve mutations altering synaptic plasticity that create a plastic reaction affecting the most variable and sexually dimorphic brain regions. The sex ratio bias in autism may arise because males have a lower threshold than females for the development of this plastic reaction following a genetic or environmental event

Development of brain structural connectivity between ages 12 and 30: a 4-tesla diffusion imaging study in 439 adolescents and adults

Understanding how the brain matures in healthy individuals is critical for evaluating deviations from normal development in psychiatric and neurodevelopmental disorders. The brain's anatomical networks are profoundly re-modeled between childhood and adulthood, and diffusion tractography offers unprecedented power to reconstruct these networks and neural pathways in vivo. Here we tracked changes in structural connectivity and network efficiency in 439 right-handed individuals aged 12 to 30 (211 female/126 male adults, mean age = 23.6, SD= 2.19; 31 female/24 male 12 year olds, mean age = 12.3, SD= 0.18; and 25 female/22 male 16 year olds, mean age = 16.2, SD= 0.37). All participants were scanned with high angular resolution diffusion imaging (HARDI) at 4 T. After we performed whole brain tractography, 70 cortical gyral-based regions of interest were extracted from each participant's co-registered anatomical scans. The proportion of fiber connections between all pairs of cortical regions, or nodes, was found to create symmetric fiber density matrices, reflecting the structural brain network. From those 70 x 70 matrices we computed graph theory metrics characterizing structural connectivity. Several key global and nodal metrics changed across development, showing increased network integration, with some connections pruned and others strengthened. The increases and decreases in fiber density, however, were not distributed proportionally across the brain. The frontal cortex had a disproportionate number of decreases in fiber density while the temporal cortex had a disproportionate number of increases in fiber density. This large-scale analysis of the developing structural connectome offers a foundation to develop statistical criteria for aberrant brain connectivity as the human brain matures. (C) 2012 Elsevier Inc. All rights reserved