The development of brain network architecture

Abstract

Brain connectivity shows protracted development throughout childhood and adolescence, and, as such, the topology of brain networks changes during this period. The complexity of these changes with development is reflected by regional differences in maturation. This study explored age-related changes in network topology and regional developmental patterns during childhood and adolescence. We acquired two sets of Diffusion Weighted Imaging-scans and anatomical T1-weighted scans. The first dataset included 85 typically developing individuals (53 males; 32 females), aged between 7 and 23 years and was acquired on a Philips Achieva 1.5 Tesla scanner. A second dataset (N = 38) was acquired on a different (but identical) 1.5 T scanner and was used for independent replication of our results. We reconstructed whole brain networks using tractography. We operationalized fiber tract development as changes in mean diffusivity and radial diffusivity with age. Most fibers showed maturational changes in mean and radial diffusivity values throughout childhood and adolescence, likely reflecting increasing white matter integrity. The largest age-related changes were observed in association fibers within and between the frontal and parietal lobes. Furthermore, there was a simultaneous age-related decrease in average path length (P < 0.0001), increase in node strength (P < 0.0001) as well as network clustering (P = 0.001), which may reflect fine-tuning of topological organization. These results suggest a sequential maturational model where connections between unimodal regions strengthen in childhood, followed by connections from these unimodal regions to association regions, while adolescence is characterized by the strengthening of connections between association regions within the frontal and parietal cortex. Hum Brain Mapp 37:717-729, 2016. © 2015 Wiley Periodicals, Inc.

Exploring the role of white matter connectivity in cortex maturation

“…It is realistic to think that during early development, the callow brain network mainly conveys coherent sensory information to higher processing areas, which would promote the maturation of related axonal pathways and connected GM regions. In line with this, connections between lower level unimodal regions strengthen before connections towards association areas, and further on to higher order processing regions [80]. Altogether, the progression of maturation from lower order areas to higher processing regions simulated with our model resembles the evolution of GM density measures between 5 and 20 years reported by Gogtay [81].…”

The role of the structural connectome in literacy and numeracy development in children

“…It quantifies the degree of local connectivity between neighbouring nodes. Reports about age-related changes in clustering coefficient are mixed with some studies reporting decreases in clustering (Hagmann et al 2010, Dennis et al 2013, Tymofiyeva et al 2013, while other studies find increases (Wierenga et al 2015, Huang et al 2013. Discrepancies may be explained by methodological differences between the studies, specifically the metric used to express connection strength.…”

“…Graph theory provides a mathematical framework for the analysis of the resulting network Sporns 2009, Rubinov and, which describes organisational principles related to ease of information exchange and wiring cost. Typical childhood is characterised by increases in global efficiency between preschool years and adulthood (Hagmann et al 2010, Yap et al 2011, Dennis et al 2013, Huang et al 2013, Khundrakpam et al 2012, Wierenga et al 2015, Hagmann et al 2010, Dennis et al 2013, Huang et al 2013. In contrast, structural brain networks in atypically developing groups, including autism, premature birth, hypoxic-ischaemic injury, and attention-deficit hyperactivity disorder (ADHD), were found to deviate from this organisation (Pandit et al 2013, Pannek et al 2013, Shi et al 2013, Konrad and Eickhoff 2010.…”

Transcending as a driver of development

“…In early childhood, myelin increases around axons in sensory regions, including ventral visual pathways, and in motor regions, including the internal capsule, basal ganglia, and thalamic pathways. In adolescence, myelin increases in axons that connect sensorimotor regions with frontal and parietal association cortices . White matter density continues to change throughout the life span—a process that is driven by experience and that supports further cognitive development and learning .…”