Development of cortical anatomical properties from early childhood to early adulthood

Human brain matures in temporal and regional heterogeneity, with some areas matured at early adulthood. In this study, the relationship of cortical structural developments between different cortical sheet regions is systematically analyzed using interregional correlation coefficient and network methods. Specifically, 951 longitudinal T1 brain MR images from 445 healthy subjects with ages from 3 to 20 years old are used. The result shows that the development of cortex reaches a turning point at around 7 years of age: a) the cortical thickness reaches its highest value and also the cortical folding becomes stable at this age; b) both global and local efficiencies of anatomical correlation networks reach the lowest and highest values at this age, respectively; and c) the change of anatomical correlation networks reach the highest level at this age, and the convergence of different anatomical correlation networks starts to decrease from this age. These results might inspire more studies on why there exists a turning point at this age from different viewpoints. For example, is there any change of synaptic pruning, or is it related to the starting of school life? And how can we benefit from this in the real life

Adolescent brain maturation and cortical folding: evidence for reductions in gyrification

Evidence from anatomical and functional imaging studies have highlighted major modifications of cortical circuits during adolescence. These include reductions of gray matter (GM), increases in the myelination of cortico-cortical connections and changes in the architecture of large-scale cortical networks. It is currently unclear, however, how the ongoing developmental processes impact upon the folding of the cerebral cortex and how changes in gyrification relate to maturation of GM/WM-volume, thickness and surface area. In the current study, we acquired high-resolution (3 Tesla) magnetic resonance imaging (MRI) data from 79 healthy subjects (34 males and 45 females) between the ages of 12 and 23 years and performed whole brain analysis of cortical folding patterns with the gyrification index (GI). In addition to GI-values, we obtained estimates of cortical thickness, surface area, GM and white matter (WM) volume which permitted correlations with changes in gyrification. Our data show pronounced and widespread reductions in GI-values during adolescence in several cortical regions which include precentral, temporal and frontal areas. Decreases in gyrification overlap only partially with changes in the thickness, volume and surface of GM and were characterized overall by a linear developmental trajectory. Our data suggest that the observed reductions in GI-values represent an additional, important modification of the cerebral cortex during late brain maturation which may be related to cognitive development

The envirome and the connectome: exploring the structural noise in the human brain associated with socioeconomic deprivation

Complex cognitive functions are widely recognized to be the result of a number of brain regions working together as large-scale networks. Recently, complex network analysis has been used to characterize various structural properties of the large scale network organization of the brain. For example, the human brain has been found to have a modular architecture i.e. regions within the network form communities (modules) with more connections between regions within the community compared to regions outside it. The aim of this study was to examine the modular and overlapping modular architecture of the brain networks using complex network analysis. We also examined the association between neighborhood level deprivation and brain network structure – modularity and grey nodes. We compared network structure derived from anatomical MRI scans of 42 middle-aged neurologically healthy men from the least (LD) and the most deprived (MD) neighborhoods of Glasgow with their corresponding random networks. Cortical morphological covariance networks were constructed from the cortical thickness derived from the MRI scans of the brain. For a given modularity threshold, networks derived from the MD group showed similar number of modules compared to their corresponding random networks, while networks derived from the LD group had more modules compared to their corresponding random networks. The MD group also had fewer grey nodes – a measure of overlapping modular structure. These results suggest that apparent structural difference in brain networks may be driven by differences in cortical thicknesses between groups. This demonstrates a structural organization that is consistent with a system that is less robust and less efficient in information processing. These findings provide some evidence of the relationship between socioeconomic deprivation and brain network topology

History of early life adversity is associated with increased food addiction and sex-specific alterations in reward network connectivity in obesity.

Background:Neuroimaging studies have identified obesity-related differences in the brain's resting state activity. An imbalance between homeostatic and reward aspects of ingestive behaviour may contribute to obesity and food addiction. The interactions between early life adversity (ELA), the reward network and food addiction were investigated to identify obesity and sex-related differences, which may drive obesity and food addiction. Methods:Functional resting state magnetic resonance imaging was acquired in 186 participants (high body mass index [BMI]: ≥25: 53 women and 54 men; normal BMI: 18.50-24.99: 49 women and 30 men). Participants completed questionnaires to assess ELA (Early Traumatic Inventory) and food addiction (Yale Food Addiction Scale). A tripartite network analysis based on graph theory was used to investigate the interaction between ELA, brain connectivity and food addiction. Interactions were determined by computing Spearman rank correlations, thresholded at q < 0.05 corrected for multiple comparisons. Results:Participants with high BMI demonstrate an association between ELA and food addiction, with reward regions playing a role in this interaction. Among women with high BMI, increased ELA was associated with increased centrality of reward and emotion regulation regions. Men with high BMI showed associations between ELA and food addiction with somatosensory regions playing a role in this interaction. Conclusions:The findings suggest that ELA may alter brain networks, leading to increased vulnerability for food addiction and obesity later in life. These alterations are sex specific and involve brain regions influenced by dopaminergic or serotonergic signalling

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

Apparent thinning of human visual cortex during childhood is associated with myelination

Human cortex appears to thin during childhood development. However, the underlying microstructural mechanisms are unknown. Using functional magnetic resonance imaging (fMRI), quantitative MRI (qMRI), and diffusion MRI (dMRI) in children and adults, we tested what quantitative changes occur to gray and white matter in ventral temporal cortex (VTC) from childhood to adulthood, and how these changes relate to cortical thinning. T1 relaxation time from qMRI and mean diffusivity (MD) from dMRI provide independent and complementary measurements of microstructural properties of gray and white matter tissue. In face- and character-selective regions in lateral VTC, T1 and MD decreased from age 5 to adulthood in mid and deep cortex, as well as in their adjacent white matter. T1 reduction also occurred longitudinally in children’s brain regions. T1 and MD decreases 1) were consistent with tissue growth related to myelination, which we verified with adult histological myelin stains, and 2) were correlated with apparent cortical thinning. In contrast, in place-selective cortex in medial VTC, we found no development of T1 or MD after age 5, and thickness was related to cortical morphology. These findings suggest that lateral VTC likely becomes more myelinated from childhood to adulthood, affecting the contrast of MR images and, in turn, the apparent gray–white boundary. These findings are important because they suggest that VTC does not thin during childhood but instead gets more myelinated. Our data have broad ramifications for understanding both typical and atypical brain development using advanced in vivo quantitative measurements and clinical conditions implicating myelin

Human neuromaturation, juvenile extreme energy liability, and adult cognition/cooperation

Human childhood and adolescence is the period in which adult cognitive competences (including those that create the unique cooperativeness of humans) are acquired. It is also a period when neural development puts a juvenile’s survival at risk due to the high vulnerability of their brain to energy shortage. The brain of a 4 year-old human uses ≈50% of its total energy expenditure (TEE) (cf. adult ≈12%). This brain expensiveness is due to (1) the brain making up ≈6% of a 4 year-old body compared to 2% in an adult, and (2) increased energy metabolism that is ≈100% greater in the gray matter of a child than in an adult (a result of the extra costs of synaptic neuromaturation). The high absolute number of neurons in the human brain requires as part of learning a prolonged neurodevelopment. This refines inter- and intraarea neural networks so they become structured with economical “small world” connectivity attributes (such as hub organization and high cross-brain differentiation/integration). Once acquired, this connectivity enables highly complex adult cognitive capacities. Humans evolved as hunter-gatherers. Contemporary hunter-gatherers (and it is also likely Middle Paleolithic ones) pool high energy foods in an egalitarian manner that reliably supported mothers and juveniles with high energy intake. This type of sharing unique to humans protects against energy shortage happening to the immature brain. This cooperation that protects neuromaturation arises from adults having the capacity to communicate and evaluate social reputation, cognitive skills that exist as a result of extended neuromaturation. Human biology is therefore characterized by a presently overlooked bioenergetic-cognition loop (called here the “HEBE ring”) by which extended neuromaturation creates the cooperative abilities in adults that support juveniles through the potentially vulnerable period of the neurodevelopment needed to become such adults