Structural brain correlates of non-verbal cognitive ability in 5-year-old children: findings from the FinnBrain Birth Cohort study

Abstract

Non-verbal cognitive ability predicts multiple important life outcomes, e.g., school and job performance. It has been associated with parieto-frontal cortical anatomy in prior studies in adult and adolescent populations, while young children have received relatively little attention. We explored the associations between cortical anatomy and non-verbal cognitive ability in 165 5-year-old participants (mean scan age 5.40 years, SD 0.13; 90 males) from the FinnBrain Birth Cohort study. T1-weighted brain magnetic resonance images were processed using FreeSurfer. Non-verbal cognitive ability was measured using the Performance Intelligence Quotient (PIQ) estimated from the Block Design and Matrix Reasoning subtests from the Wechsler Preschool And Primary Scale Of Intelligence (WPPSI-III). In vertex-wise general linear models, PIQ scores associated positively with volumes in left caudal middle frontal and right pericalcarine regions, as well as surface area in left caudal middle frontal, left inferior temporal, and right lingual regions. There were no associations between PIQ and cortical thickness. To the best of our knowledge, this is the first study to examine structural correlates of non-verbal cognitive ability in a large sample of typically developing 5-year-olds. The findings are generally in line with prior findings from older age groups.

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

“…For grey matter, surface area and volume show the best predictive power compared to cortical thickness, a surprising finding given the prevalence of studies which (only) use cortical thickness as a structural predictor of cognitive performance. However, this result is consistent with several studies reporting that surface area is more related to cognitive performance than cortical thickness (Borgeest et al, 2021; Pulli et al, 2023). Moreover, recent evidence within the same sample suggests that cortical thickness has lower reliability than surface area or volume, which may differentially attenuate the effects a given study observes (Parsons et al, 2023).…”

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

“…For gray matter, SA and volume show the best predictive power compared with CT, a surprising finding given the prevalence of studies which (only) use CT as a structural predictor of cognitive performance. However, this result is consistent with several studies reporting that SA is more related to cognitive performance than CT ( Borgeest et al, 2021 ; Fürtjes et al, 2023 ; Pulli et al, 2023 ). Moreover, recent evidence within the same sample suggests that CT has lower reliability than SA or volume, which may differentially attenuate the effects a given study observes ( Parsons et al, 2023 ).…”