| Literature DB >> 26827810 |
Eero Vuoksimaa1, Matthew S Panizzon2, Chi-Hua Chen3, Mark Fiecas2, Lisa T Eyler4, Christine Fennema-Notestine5, Donald J Hagler6, Carol E Franz2, Amy J Jak7, Michael J Lyons8, Michael C Neale9, Daniel A Rinker10, Wesley K Thompson11, Ming T Tsuang2, Anders M Dale12, William S Kremen13.
Abstract
General cognitive ability (GCA) has substantial explanatory power for behavioral and health outcomes, but its cortical substrate is still not fully established. GCA is highly polygenic and research to date strongly suggests that its cortical substrate is highly polyregional. We show in map-based and region-of-interest-based analyses of adult twins that a complex cortical configuration underlies GCA. Having relatively greater surface area in evolutionary and developmentally high-expanded prefrontal, lateral temporal, and inferior parietal regions is positively correlated with GCA, whereas relatively greater surface area in low-expanded occipital, medial temporal, and motor cortices is negatively correlated with GCA. Essentially the opposite pattern holds for relative cortical thickness. The phenotypic positive-to-negative gradients in our cortical-GCA association maps were largely driven by a similar pattern of genetic associations. The patterns are consistent with regional cortical stretching whereby relatively greater surface area is related to relatively thinner cortex in high-expanded regions. Thus, the typical "bigger is better" view does not adequately capture cortical-GCA associations. Rather, cognitive ability is influenced by complex configurations of cortical development patterns that are strongly influenced by genetic factors. Optimal cognitive ability appears to be driven both by the absolute size and the polyregional configuration of the entire cortex rather than by small, circumscribed regions.Entities:
Keywords: Cortical surface area; Cortical thickness; General cognitive ability; Neurodevelopment; Twin research
Mesh:
Year: 2016 PMID: 26827810 PMCID: PMC4838639 DOI: 10.1016/j.neuroimage.2016.01.049
Source DB: PubMed Journal: Neuroimage ISSN: 1053-8119 Impact factor: 6.556