A morphometric double dissociation: cortical thickness is more related to aging; surface area is more related to cognition

Abstract

The thickness and surface area of cortex are genetically distinct aspects of brain structure, and may be affected differently by age. However, their potential to differentially predict age and cognitive abilities has been largely overlooked, likely because they are typically aggregated into the commonly used measure of volume. In a large sample of healthy adults (N=647, aged 18-88), we investigated the brain-age and brain-cognition relationships of thickness, surface area, and volume, plus five additional morphological shape metrics. Cortical thickness was the metric most strongly associated with age cross-sectionally, as well as exhibiting the steepest longitudinal change over time (subsample N=261, aged 25-84). In contrast, surface area was the best single predictor of age-residualized cognitive abilities (fluid intelligence), and changes in surface area were most strongly associated with cognitive change over time. These findings were replicated in an independent dataset (N=1345, aged 18-93). Our results suggest that cortical thickness and surface area make complementary contributions the age-brain-cognition triangle, and highlight the importance of considering these volumetric components separately.

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).…”

rsfMRI-based Brain Entropy is negatively correlated with Gray Matter Volume and Surface Area

“…In this work, we showed that the BEN of the same regions is also inversely related to the SA. A number of prior findings suggest that general cognitive ability might be correlated to SA rather than CT (28)(29)(30)(31). For instance, it has been shown that the genetic association between GMV and general intelligence, as well as that the relationship between regional GMV and cognitive aging differences, are predominantly driven by SA (29,31).…”

Individual differences in brain aging: heterogeneity in cortico-hippocampal but not caudate atrophy rates

“…Although we argue that this selection captured the relevant and aging-sensitive parts of the cerebrum, it cannot be ruled out that the analyses of other or additional regions, possibly with a whole-brain high-dimensional coverage, would yield different outcomes. Also, investigating the cortical thickness or surface area instead of volumes could potentially lead to different outcomes in relation to the magnitude of age changes and cognition ( Borgeest et al. 2021 ).…”