White matter microstructural variability linked to differential attentional skills and impulsive behavior in a pediatric population

Abstract

Structural and functional magnetic resonance imaging (MRI) studies have suggested a neuroanatomical basis that may underly attention-deficit-hyperactivity disorder (ADHD), but the anatomical ground truth remains unknown. In addition, the role of the white matter (WM) microstructure related to attention and impulsivity in a general pediatric population is still not well understood. Using a state-of-the-art structural connectivity pipeline based on the Brainnetome atlas extracting WM connections and its subsections, we applied dimensionality reduction techniques to obtain biologically interpretable WM measures. We selected the top 10 connections-of-interests (located in frontal, parietal, occipital, and basal ganglia regions) with robust anatomical and statistical criteria. We correlated WM measures with psychometric test metrics (Conner's Continuous Performance Test 3) in 171 children (27 Dx ADHD, 3Dx ASD, 9-13 years old) from the population-based GESTation and Environment cohort. We found that children with lower microstructural complexity and lower axonal density show a higher impulsive behavior on these connections. When segmenting each connection in subsections, we report WM alterations localized in one or both endpoints reflecting a specific localization of WM alterations along each connection. These results provide new insight in understanding the neurophysiology of attention and impulsivity in a general population.

Keywords: child & adolescent; cognitive functions; diffusion MRI; tractography; white matter connectivity.

Fig. 1

Flowchart of total population with exclusion reasons.

Fig. 2

Overview of the preprocessing and processing steps.

Fig. 3

Top-10 connections-of-interest that survived the filtering steps from the group comparison analysis (20% higher score vs 20% lower scores). These connections present significant difference on at least 1 DTI metrics (FA, MD, RD, AD) and AFD_fixel, AFD_total, and NuFo as well as being present in every subject from our population. Orange box identifies connections significant for impulsivity and brown box for attention. A) CLG–OPC, B) DC–PFT, C) M6–CD6, D) M6–PPT, E) A46–LA10, F) A41/42–RA40, G) MOG–IOG, H) CCG–MSOG, I) FG37–IOG, J) NA–OT. Color represents connections’ sub-sections.

Fig. 4

Results from dimensionality reduction analysis using in A) complete connection PCs (whole connection metrics) and B) sub-section PCs (based on the sub-sections specific metrics). Connections are colored from anatomy-based metric.

Fig. 5

Connection profiles comparison between the 20% higher performance and 20% lowest performance group. *: represent sub-sections were both groups are significantly different. Black rectangles represent clusters of significantly different sub-sections (defined as 5 or more closely localize significantly different sub-sections). Analysis was performed using the component extracted from the sub-sections specific metrics (results from tractometry). Axonal density is inverse scored, lower values = higher axonal density while higher values = lower axonal density. A) M6–CD6, B) A46–LA10, C) DC–PFT, D) FG37–IOG. Connection are colored based on P-values for each sub-sections.

Fig. 6

Visual representation of connections overlapping with “classical” WM bundles. A) M6–CD6, B) M6–PPT, C) A46–LA10, D) A41/42–RA40, E) FG37–IOG, F) CLG-OPC, G) CCG–MSOG, H) MOG–IOG, I) NA–OT, J) DC–PFT.