Grey and white matter metrics demonstrate distinct and complementary prediction of differences in cognitive performance in children: Findings from ABCD (N= 11 876)

Abstract

Individual differences in cognitive performance in childhood are a key predictor of significant life outcomes such as educational attainment and physical and mental health. Differences in cognitive ability are governed at least in part by variations in brain structure. However, studies commonly focus on either grey or white matter metrics, leaving open the key question as to whether grey or white matter microstructure play distinct roles supporting cognitive performance or if they are two ways to look at the same system complementary. To compare the role of grey and white matter in supporting cognitive performance, we used regularized structural equation models to predict cognitive performance with grey and white matter measures. Specifically, we compared how morphometric grey matter measures (volume, cortical thickness and surface area) and indices of white matter microstructure (volume, fractional anisotropy and mean diffusivity) predicted individual differences in general cognitive performance. The models were tested in a large cohort of children (ABCD Study, N=11876) at 10 years old. We found that grey and white matter metrics bring partly different information to predict cognitive performance. Indeed, model selection approaches consistently demonstrated both tissues were needed, compared to simpler models with only grey or only white that explained respectively 12.3% and 10.9% of the variance in cognitive performance, the combined models explained 15.4% of the variance. Zooming in we additionally found different metrics within grey and white matter had different predictive power, and different regions for grey and white matter had the strongest association with cognitive performance differences. These results show that studies focusing on a single metric in either grey or white matter to study the link between brain structure and cognitive performance are missing a key part of the equation.

Structural brain correlates of non‐verbal cognitive ability in 5‐year‐old children: Findings from the FinnBrain birth cohort study

“…The cortical structural correlates of non‐verbal ability were similar for volume and surface area measurements but completely different for cortical thickness. This is in line with recent findings in both the similarity of volume and surface area metrics, and that they were more strongly associated with cognitive abilities than cortical thickness was (Michel et al, 2023 ). Volume is a combination of the two surface‐based measurements, cortical thickness and surface area, that reflect different biological features of the cortex.…”

How should we model the effect of "change" - or should we?

“…Development study (ABCD, Casey et al, 2018), including a measure of cognitive performance (verbal intellect and language, Luciana et al, 2018) and cortical surface area from the prefrontal cortex (for a description of the relevant measures in this sample, see Michel et al, 2023). Here we will use the cognitive measure as the outcome (y t ) and cortical surface area as the timevarying predictor (x t ).…”

“…For the first example, we can return to the two-wave data from the Adolescent Brain and Cognition Development study (ABCD, Casey et al, 2018), but this time draw a measure of reading comprehension (Luciana et al, 2018) and mean diffusivity of the forceps minor white matter tract (Michel et al, 2023). Here we will use reading comprehension as the outcome (y t ) and mean diffusivity as the time-varying predictor (x t ).…”

Sex Differences in White Matter Diffusivity in Children with Developmental Dyslexia

“…Neuroimaging research has been able to identify key areas in the brain that help connect these phonemic, orthographic, and semantic lexicons (mental representation of words) together, including the frontal, tempo-parietal, and the occipito-temporal regions in the left hemisphere of the brain [ 4 ]. The brain communicates and processes information through the complimentary functioning of gray matter, neuron cell bodies where the processing of information takes place, and white matter, myelinated axon bundles that connect neurons in different brain regions into functional units [ 5 , 6 ]. Efficient reading skills require adequate development and utilization of not only brain areas that are important for reading, but also the white matter tracts that subserve the reading network, working to communicate effectively between the brain regions and networks that specialize in language processing and reading.…”