Time-lagged associations between cognitive and cortical development from childhood to early adulthood
Throughout childhood and adolescence, humans experience marked changes in cortical structure and cognitive ability. Cortical thickness and surface area, in particular, have been associated with cognitive ability. Here we ask the question: What are the time related associations between cognitive chan...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universidad Autónoma de Madrid |
| Repositorio: | Biblos-e Archivo. Repositorio Institucional de la UAM |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.uam.es:10486/709431 |
| Acceso en línea: | http://hdl.handle.net/10486/709431 https://dx.doi.org/10.1037/dev0000716 |
| Access Level: | acceso abierto |
| Palabra clave: | cortical thickness cortical surface area structural brain imaging intelligence cognitive development latent change score models Psicología |
| Sumario: | Throughout childhood and adolescence, humans experience marked changes in cortical structure and cognitive ability. Cortical thickness and surface area, in particular, have been associated with cognitive ability. Here we ask the question: What are the time related associations between cognitive changes and cortical structure maturation. Identifying a developmental sequence requires multiple measurements of these variables from the same individuals across time. This allows capturing relations among the variables and, thus, finding whether: (a) developmental cognitive changes follow cortical structure maturation, (b) cortical structure maturation follows cognitive changes, or (c) both processes influence each other over time. 430 children and adolescents (age range = 6.01 22.28 years) completed the WASI battery and were MRI scanned at three time points separated by ≈ 2 years (mean age t1 = 10.60, SD = 3.58, mean age t2=12.63, SD=3.62, mean age t3=14.49, SD=3.55). Latent Change Score (LCS) models were applied to quantify age related relationships among the variables of interest. Our results indicate that cortical and cognitive changes related to each other reciprocally. Specifically, the magnitude or rate of the change in each variable at any occasion and not the previous level was predictive of later changes. These results were replicated for brain regions selected according to the coordinates identified in the Basten et al.’s (2015) meta analysis, to the Parieto Frontal Integration Theory (P FIT, Jung & Haier, 2007) and to the whole cortex. Potential implications regarding brain plasticity and cognitive enhancement are discussed |
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