Children's intellectual ability is associated with structural network integrity

Highlights

• Structural brain network of 99 typically developing children was examined.

• Higher intellectual ability was associated with higher network integration.

• Visuo-spatial ability was most strongly associated with network properties.

• Motor-related regions were strongly associated with visuo-spatial processing.

• Higher intellectual ability was associated with enhanced rich-club connectivity.

Abstract

Recent structural and functional neuroimaging studies of adults suggest that efficient patterns of brain connectivity are fundamental to human intelligence. Specifically, whole brain networks with an efficient small-world organization, along with specific brain regions (i.e., Parieto-Frontal Integration Theory, P-FIT) appear related to intellectual ability. However, these relationships have not been studied in children using structural network measures. This cross-sectional study examined the relation between non-verbal intellectual ability and structural network organization in 99 typically developing healthy preadolescent children. We showed a strong positive association between the network's global efficiency and intelligence, in which a subtest for visuo-spatial motor processing (Block Design, BD) was prominent in both global brain structure and local regions included within P-FIT as well as temporal regions involved with pattern and form processing. BD was also associated with rich club organization, which encompassed frontal, occipital, temporal, hippocampal, and neostriatal regions. This suggests that children's visual construction ability is significantly related to how efficiently children's brains are globally and locally integrated. Our findings indicate that visual construction and reasoning may make general demands on globally integrated processing by the brain.

Introduction

The inter-relationship among localized and distributed brain regions has been conceptualized as an integrated network organized into many segregated subregions linked by axonal white matter tracts (Sporns et al., 2005). A robust finding from the network perspective is that the human brain is organized in a highly efficient way for integrated information transfer, in so called small-world topology (for a review, see Bullmore and Sporns, 2009). Moreover, recent neuroimaging studies have suggested that some brain regions including the precuneus, posterior cingulate, and medial prefrontal cortex play a pivotal role as hubs or part of a structural core in the brain (Hagmann et al., 2008, Sporns et al., 2007) supporting fast communication between distributed regions. These key cortical hubs also are likely to be preferentially connected to each other forming a rich club (van den Heuvel and Sporns, 2011). Network organization undergoes rapid alterations in development with changes in axonal synaptic connectivity, white matter volume, and the thickness of corresponding cortical regions; see Vertes and Bullmore (2015) for a summary of developmental changes in network organization. In particular, structural maturation of white matter as well as cortical and subcortical areas is strongly associated with intellectual abilities from early childhood throughout adolescence (Shaw et al., 2006, Tamnes et al., 2010). However, the relationship of network properties derived from axonal white matter tracts such as network efficiency with intelligence during childhood has received little investigation.

Intelligence can be defined as the individual's capacity for mental functioning across a variety of domains including reasoning, executive function, information processing speed, memory and spatial manipulation — so called, general intelligence (g). Efficient and economical information processing among the distributed brain regions along white matter fibers is thought to contribute to general intelligence capacity (Deary et al., 2010, Gray and Thompson, 2004). The parieto-frontal integration theory (P-FIT) postulates that the dorsolateral prefrontal cortex and the parietal cortex, including the arcuate fasciculus connecting those two regions, comprise an important neuronal network associated with efficient intellectual functioning (Jung and Haier, 2007). The P-FIT of intelligence has been supported by neuroimaging findings including studies of gray matter volumes (Colom et al., 2009), cortical thickness (Narr et al., 2007) and white matter tracts (Van Beek et al., 2014). A brain network perspective provides a quantitative model for elucidating the association between the efficiency of brain networks and intelligence (Cole et al., 2012, van den Heuvel et al., 2009). Network approaches to understanding adult intelligence reveal consistent positive associations between intellectual performance and network integrity characterized by diffusion tensor imaging (DTI; Fischer et al., 2014, Li et al., 2009), resting-state functional MRI (van den Heuvel et al., 2009), and the electroencephalogram (EEG; Langer et al., 2012). Since brain development in childhood is associated with large-scale changes in synaptic connectivity, gray matter thickness and myelination, these relationships could be quite different than those observed in the adult brain. For example, there is evidence that the association between cortical regions and intelligence must include consideration of the trajectory of brain development, in which the relations between brain systems and function are dynamic and are altered as a function of age (Shaw et al., 2006). While one imaging study for children showed no relation of functional brain networks with IQ (Wu et al., 2013), no neuroimaging studies have been performed to date to investigate the relations between children's intellectual ability and whole-brain structural network properties.

In this study, we applied a graph theoretic network analysis to structural neuroimaging data acquired in typically developing children. This approach enabled characterization of global network associations with children's intelligence scores, including the role of hub regions and specific local regions in brain network architecture. We tested the hypothesis that the perceptual reasoning index (PRI), representing individual's nonverbal fluid reasoning skills, was associated with individual's structural network organization. Based on network studies on adults, higher structural network integration was predicted to be significantly associated with higher perceptual reasoning abilities. In addition to this, we particularly focused on domain-specific associations derived from three PRI subtests (Block Design, Picture Concepts, and Matrix Reasoning), and examined the association between cortical network architecture and specific intellectual performance of preadolescent children.