White matter microstructure is associated with cognitive control in children☆
Introduction
Recent advances in neuroimaging enable us to study how brain regions are integrated into networks to support cognitive function. Here we apply diffusion tensor imaging (DTI) to a child population to investigate how the microstructural organization of white matter tracts is related to cognitive control. Individual differences in cognition during childhood have been associated with variations in brain structure and brain function, including gray matter volumes and functional brain networks (Bunge and Crone, 2009, Shaw et al., 2006). Clearly, maturation of white matter tracts also plays a critical role in the development of cognitive functions. Yet, the white matter tracts most important to cognitive control during childhood are not well known. The present study examined the relationship between white matter microstructure and performance on a task of cognitive control in 7–9-year-old children. Cognitive control (also known as ‘executive control’) refers to the ability to guide behavior toward specific goals, formulate decisions, and control action (Bunge & Crone, 2009), processes that involve the ability to selectively attend to relevant information and filter distracting information.
DTI enables an in vivo characterization of microstructural properties of white matter based on properties of diffusion, and the information is represented mathematically in a diffusion ellipsoid (Johansen-Berg and Behrens, 2009, Jones, 2011, Mori, 2007, Rykhlevskaia et al., 2008). Different DTI measures are hypothesized to reflect specific biological properties of white matter microstructure. High levels of fractional anisotropy (FA) (i.e., increased directionality of diffusion) are said to occur in tightly bundled, structurally compact fibers with high integrity (Basser, 1995, Beaulieu, 2002, Rykhlevskaia et al., 2008, Sen and Basser, 2005). One component of FA is mean diffusivity (MD), calculated as the mean of all three axes of the diffusion ellipsoid, and considered an estimation of membrane density (Schmithorst & Yuan, 2010). Diffusion along the major axis/eigenvector of the ellipsoid is termed axial diffusivity (AD), which may reflect the pathology of axonal fibers including axonal diameter, loss or damage (Budde et al., 2007, Song et al., 2003). Radial diffusivity (RD) is the average of the second and third minor axes (Basser, 1995, Pierpaoli and Basser, 1996, Pierpaoli et al., 1996, Song et al., 2002) and is considered to reflect insulated, myelinated tracts (Budde et al., 2007, Nair et al., 2005, Rykhlevskaia et al., 2008, Song et al., 2002, Song et al., 2003, Song et al., 2005). Investigating patterns of diffusivity across the brain permits the characterization of microstructural white matter properties that are important for paying attention and inhibiting distractions, skills important in and out of the school environment (Bull and Scerif, 2001, DeStefano and LeFevre, 2004, St. Clair-Thompson and Gathercole, 2006).
A number of studies have reported a positive relationship between various cognitive abilities (e.g., reading, IQ, information processing, visual-spatial working memory, attention, interference suppression, response inhibition) and different measures of white matter microstructure across a variety of fiber tracts throughout the lifespan (see Madden et al., 2012, Schmithorst and Yuan, 2010 for reviews of literature on young and older populations). Most research has focused on the relationship between white matter structure and cognition in late life (Madden et al., 2012). Only a few investigations have examined the relationship between estimates of white matter integrity and cognitive control in healthy, typically developing children. Cognitive control is supported by a network of frontal, parietal, striatal and motor regions (Banich et al., 2000). For example, in terms of attentional control and interference control, one voxel-wise DTI study examined flanker task performance consistency (i.e., trial-to-trial intraindividual variability of reaction time [RT]) in 8–19-year-olds and found that less response time variability was associated with better estimates of white matter integrity (e.g., FA) in frontal (e.g., corpus callosum), parietal, and corticospinal tracts, independent of age (Tamnes, Fjell, Westlye, Ostby, & Walhovd, 2012). However, no significant associations between diffusion measures (FA, MD, AD, RD) and mean RT were reported (Tamnes et al., 2012). Here, we limit our age range to 7–9-year-old children to focus on the tracts important during this period of preadolescent childhood. In addition, we focus on the relationship between white matter microstructure and performance in terms of both accuracy and RT, because individual differences in accuracy may be as or even more informative in a childhood population (Davidson et al., 2006, Tamnes et al., 2012).
In terms of inhibitory control, one study used tractography to examine the relationship between connectivity in specific white matter tracts between the frontal cortex and striatum and performance on a Go/NoGo task in a sample of 7–31-year-olds (Liston et al., 2006). The researchers reported that more restricted radial diffusivity (RD) in frontostriatal fibers, but not corticospinal tracts, predicted individual differences in cognitive control, independent of age. Additionally, in a sample of children aged 7–13, faster response inhibition during a stop signal task was associated with higher FA and lower perpendicular diffusivity in fiber tracts within frontal and motor cortex regions (i.e., inferior frontal gyrus, supplementary motor cortex), independent of age (Madsen et al., 2010). Clearly, additional research is needed to understand how white matter structure relates to cognitive control during childhood.
We extend this literature in several important ways in our current study. We predicted that white matter microstructure would be associated with cognitive control in children. We made a priori hypotheses about specific white matter fibers involved in cognitive control given that certain tracts have been found to relate to cognitive and motor abilities across the lifespan (Liston et al., 2006, Madden et al., 2012, Schmithorst and Yuan, 2010, Tamnes et al., 2012). Firstly, we investigated the corpus callosum, a tract that connects the left and right cerebral hemispheres and facilitates interhemispheric communication. Secondly, we made a region of interest (ROI) of the corona radiata, a tract that carries ascending and descending information from the cerebral cortex and has been found to relate to different elements of cognitive control across the lifespan, including attention, working memory, visual-spatial memory, and processing speed (Bendlin et al., 2010, Niogi et al., 2010, Olesen et al., 2003). Thirdly, we examined the superior longitudinal fasciculus, a tract providing the bidirectional information transfer between the frontal and parietal cortex (Petrides and Pandya, 1984, Schmahmann and Pandya, 2006) which plays a role in working memory in children (Nagy, Westerberg, & Klingberg, 2004) and older adults (Burzynska et al., 2011). Fourthly, we created an ROI of the posterior thalamic radiation, nerve fibers connecting thalamus with the cerebral cortex by way of internal capsule (which separates the caudate nucleus and the thalamus from the lenticular nucleus). Fifthly, we investigated the cerebral peduncle, part of the brainstem, which includes corticospinal tract, corticobulbar tract, and other nerve tracts conveying motor information to and from the brain to the rest of the body. In general, we predicted that higher FA and lower overall diffusivity of these tracts would relate to higher performance, and less interference, during a task measuring cognitive control in 7–9-year-olds.
Section snippets
Participants
Sixty-one prepubescent (Taylor et al., 2001) children (33 girls, 28 boys), ages 7–9 years (M = 8.7 years, SD = 0.6), from East-Central Illinois were included in the analysis. To be eligible for the study, children had to have a Kaufman Brief Intelligence Test (KBIT) score greater than 85 (Kaufman & Kaufman, 1990) and qualify as prepubescent (Tanner puberty score ≤ 2; Taylor et al., 2001). Children were also screened for the presence of attentional disorders using the Attention Deficit Hyperactivity
Task performance
Children showed shorter RT (F(1, 60) = 81.566, p < 0.001) for neutral trials (M = 857.397 ms, SE = 16.888 ms) compared to incongruent trials (M = 935.829 ms, SE = 18.587 ms), as well as higher accuracy (F(1, 60) = 51.648, p < 0.001) during neutral trials (M = 87.100%, SE = 1.400%) compared to incongruent trials (M = 78.900%, SE = 2.000%).
Diffusion tensor imaging and task performance
MANOVAs with all bilateral FA, MD, AD, and RD values as the dependent measures and task performance as individual fixed factors yielded marginal, yet non-significant, results (i.e.,
Discussion
The present investigation used DTI to explore the extent to which white matter microstructure is related to cognitive control in 7–9-year-old children. Cognitive control is said to be supported by a network of frontal, parietal, striatal and motor regions (Banich et al., 2000), and the present study examined tracts that travel throughout these brain regions to try to locate the specific white matter fibers important for attentional and interference control. Our results suggest that 7–9-year-old
Acknowledgments
Thank you to Holly Tracy and Nancy Dodge for their help with data collection. This work was supported by a grant (HD055352) from the National Institute of Child Health and Human Development to Dr. Charles Hillman.
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Funding was provided by a grant from the National Institute of Child Health and Human Development (392 NIH 1 R01 HD069381).