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Beyond a bigger brain: Multivariable structural brain imaging and intelligence

People with larger brains tend to score higher on tests of general intelligence (g). It is unclear, however, how much variance in intelligence other brain measurements would account for if included together with brain volume in a multivariable model. We examined a large sample of individuals in thei...

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Autores principales: Ritchie, Stuart J., Booth, Tom, Valdés Hernández, Maria del C., Corley, Janie, Maniega, Susana Muñoz, Gow, Alan J., Royle, Natalie A., Pattie, Alison, Karama, Sherif, Starr, John M., Bastin, Mark E., Wardlaw, Joanna M., Deary, Ian J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4518535/
https://www.ncbi.nlm.nih.gov/pubmed/26240470
http://dx.doi.org/10.1016/j.intell.2015.05.001
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author Ritchie, Stuart J.
Booth, Tom
Valdés Hernández, Maria del C.
Corley, Janie
Maniega, Susana Muñoz
Gow, Alan J.
Royle, Natalie A.
Pattie, Alison
Karama, Sherif
Starr, John M.
Bastin, Mark E.
Wardlaw, Joanna M.
Deary, Ian J.
author_facet Ritchie, Stuart J.
Booth, Tom
Valdés Hernández, Maria del C.
Corley, Janie
Maniega, Susana Muñoz
Gow, Alan J.
Royle, Natalie A.
Pattie, Alison
Karama, Sherif
Starr, John M.
Bastin, Mark E.
Wardlaw, Joanna M.
Deary, Ian J.
author_sort Ritchie, Stuart J.
collection PubMed
description People with larger brains tend to score higher on tests of general intelligence (g). It is unclear, however, how much variance in intelligence other brain measurements would account for if included together with brain volume in a multivariable model. We examined a large sample of individuals in their seventies (n = 672) who were administered a comprehensive cognitive test battery. Using structural equation modelling, we related six common magnetic resonance imaging-derived brain variables that represent normal and abnormal features—brain volume, cortical thickness, white matter structure, white matter hyperintensity load, iron deposits, and microbleeds—to g and to fluid intelligence. As expected, brain volume accounted for the largest portion of variance (~ 12%, depending on modelling choices). Adding the additional variables, especially cortical thickness (+~ 5%) and white matter hyperintensity load (+~ 2%), increased the predictive value of the model. Depending on modelling choices, all neuroimaging variables together accounted for 18–21% of the variance in intelligence. These results reveal which structural brain imaging measures relate to g over and above the largest contributor, total brain volume. They raise questions regarding which other neuroimaging measures might account for even more of the variance in intelligence.
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spelling pubmed-45185352015-08-01 Beyond a bigger brain: Multivariable structural brain imaging and intelligence Ritchie, Stuart J. Booth, Tom Valdés Hernández, Maria del C. Corley, Janie Maniega, Susana Muñoz Gow, Alan J. Royle, Natalie A. Pattie, Alison Karama, Sherif Starr, John M. Bastin, Mark E. Wardlaw, Joanna M. Deary, Ian J. Intelligence Article People with larger brains tend to score higher on tests of general intelligence (g). It is unclear, however, how much variance in intelligence other brain measurements would account for if included together with brain volume in a multivariable model. We examined a large sample of individuals in their seventies (n = 672) who were administered a comprehensive cognitive test battery. Using structural equation modelling, we related six common magnetic resonance imaging-derived brain variables that represent normal and abnormal features—brain volume, cortical thickness, white matter structure, white matter hyperintensity load, iron deposits, and microbleeds—to g and to fluid intelligence. As expected, brain volume accounted for the largest portion of variance (~ 12%, depending on modelling choices). Adding the additional variables, especially cortical thickness (+~ 5%) and white matter hyperintensity load (+~ 2%), increased the predictive value of the model. Depending on modelling choices, all neuroimaging variables together accounted for 18–21% of the variance in intelligence. These results reveal which structural brain imaging measures relate to g over and above the largest contributor, total brain volume. They raise questions regarding which other neuroimaging measures might account for even more of the variance in intelligence. Elsevier 2015 /pmc/articles/PMC4518535/ /pubmed/26240470 http://dx.doi.org/10.1016/j.intell.2015.05.001 Text en © 2015 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ritchie, Stuart J.
Booth, Tom
Valdés Hernández, Maria del C.
Corley, Janie
Maniega, Susana Muñoz
Gow, Alan J.
Royle, Natalie A.
Pattie, Alison
Karama, Sherif
Starr, John M.
Bastin, Mark E.
Wardlaw, Joanna M.
Deary, Ian J.
Beyond a bigger brain: Multivariable structural brain imaging and intelligence
title Beyond a bigger brain: Multivariable structural brain imaging and intelligence
title_full Beyond a bigger brain: Multivariable structural brain imaging and intelligence
title_fullStr Beyond a bigger brain: Multivariable structural brain imaging and intelligence
title_full_unstemmed Beyond a bigger brain: Multivariable structural brain imaging and intelligence
title_short Beyond a bigger brain: Multivariable structural brain imaging and intelligence
title_sort beyond a bigger brain: multivariable structural brain imaging and intelligence
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4518535/
https://www.ncbi.nlm.nih.gov/pubmed/26240470
http://dx.doi.org/10.1016/j.intell.2015.05.001
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