Association between structural brain network efficiency and intelligence increases during adolescence

Abstract

Adolescence represents an important period during which considerable changes in the brain take place, including increases in integrity of white matter bundles, and increasing efficiency of the structural brain network. A more efficient structural brain network has been associated with higher intelligence. Whether development of structural network efficiency is related to intelligence, and if so to which extent genetic and environmental influences are implicated in their association, is not known. In a longitudinal study, we mapped FA-weighted efficiency of the structural brain network in 310 twins and their older siblings at an average age of 10, 13, and 18 years. Age-trajectories of global and local FA-weighted efficiency were related to intelligence. Contributions of genes and environment were estimated using structural equation modeling. Efficiency of brain networks changed in a non-linear fashion from childhood to early adulthood, increasing between 10 and 13 years, and leveling off between 13 and 18 years. Adolescents with higher intelligence had higher global and local network efficiency. The dependency of FA-weighted global efficiency on IQ increased during adolescence (r =0.007 at age 10; 0.23 at age 18). Global efficiency was significantly heritable during adolescence (47% at age 18). The genetic correlation between intelligence and global and local efficiency increased with age; genes explained up to 87% of the observed correlation at age 18. In conclusion, the brain's structural network differentiates depending on IQ during adolescence, and is under increasing influence of genes that are also associated with intelligence as it develops from late childhood to adulthood.

Neurocognitive reorganization between crystallized intelligence, fluid intelligence and white matter microstructure in two age-heterogeneous developmental cohorts

“…Interestingly, preliminary evidence suggests that the associations between brain structure and cognitive performance may not be static during development. For instance, Koenis et al, 2018 observed increased correlation between cognitive performance and FA-derived metric changes over adolescence.…”

“…Both cross-sectional and longitudinal research in children and adolescents using fractional anisotropy (FA), a commonly used estimate of white matter integrity, have consistently revealed strong correlations between FA and cognitive ability using tests of working memory, verbal and nonverbal performance (Koenis et al, 2015;Krogsrud et al, 2018;Peters et al, 2014;Tamnes et al, 2010;Urger et al, 2015). There is also some evidence that the correlation between cognitive performance and FA-derived metrics increases over adolescence (Koenis et al, 2018). Moreover, recent research has also found associations between the corpus callosum (Navas-Sánchez et al, 2014;Westerhausen et al, 2018) association fibers (e.g.…”

Evidence for genetic correlation between human cerebral white matter microstructure and inflammation

“…The human brain is composed of structural networks that support brain function via white matter fiber connections (Kanai & Rees, 2011), making white matter microstructure essential to complex cognition (Kennedy & Raz, 2009;Madden et al, 2008), development (Barnea-Goraly et al, 2005;Giedd et al, 1999;Koenis et al, 2018;Nagy, Westerberg, & Klingberg, 2004), plasticity (Hofstetter, Tavor, Moryosef, & Assaf, 2013;Zatorre, Fields, & Johansen-Berg, 2012), and successful aging (Gunning-Dixon, Brickman, Cheng, & Alexopoulos, 2009;Gunning-Dixon & Raz, 2000). White matter microstructure is influenced by several factors, especially those associated with increased innate inflammatory activity (Porter, Leckie, & Verstynen, 2018).…”

It’s About Time: Towards a Longitudinal Cognitive Neuroscience of Intelligence

“…Using a twin analysis, the authors showed that the phenotypic covariance between IQ and cortical thickness and cortical thickness change was effectively entirely genetic. Koenis et al (2018) showed (in the same sample as Koenis et al, 2015 above) age-dependent correlations between brain measures and IQ: Weak or absent correlations early in childhood (r=0 at age 10) became pronounced by middle to late adolescence (age 18, r=.23). Notably, the previous steep changes in efficiency between age 10 and 13 had levelled off by age 18, suggesting a slowing down of cortical development.…”