IDEAS home Printed from https://ideas.repec.org/a/eee/intell/v76y2019ic9.html
   My bibliography  Save this article

Structural brain imaging correlates of general intelligence in UK Biobank

Author

Listed:
  • Cox, S.R.
  • Ritchie, S.J.
  • Fawns-Ritchie, C.
  • Tucker-Drob, E.M.
  • Deary, I.J.

Abstract

The associations between indices of brain structure and measured intelligence are unclear. This is partly because the evidence to-date comes from mostly small and heterogeneous studies. Here, we report brain structure-intelligence associations on a large sample from the UK Biobank study. The overall N = 29,004, with N = 18,426 participants providing both brain MRI and at least one cognitive test, and a complete four-test battery with MRI data available in a minimum N = 7201, depending upon the MRI measure. Participants' age range was 44–81 years (M = 63.13, SD = 7.48). A general factor of intelligence (g) was derived from four varied cognitive tests, accounting for one third of the variance in the cognitive test scores. The association between (age- and sex- corrected) total brain volume and a latent factor of general intelligence is r = 0.276, 95% C.I. = [0.252, 0.300]. A model that incorporated multiple global measures of grey and white matter macro- and microstructure accounted for more than double the g variance in older participants compared to those in middle-age (13.6% and 5. 4%, respectively). There were no sex differences in the magnitude of associations between g and total brain volume or other global aspects of brain structure. The largest brain regional correlates of g were volumes of the insula, frontal, anterior/superior and medial temporal, posterior and paracingulate, lateral occipital cortices, thalamic volume, and the white matter microstructure of thalamic and association fibres, and of the forceps minor. Many of these regions exhibited unique contributions to intelligence, and showed highly stable out of sample prediction.

Suggested Citation

  • Cox, S.R. & Ritchie, S.J. & Fawns-Ritchie, C. & Tucker-Drob, E.M. & Deary, I.J., 2019. "Structural brain imaging correlates of general intelligence in UK Biobank," Intelligence, Elsevier, vol. 76(C), pages 1-1.
    • Handle: RePEc:eee:intell:v:76:y:2019:i:c:9
    DOI: 10.1016/j.intell.2019.101376
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160289619300789
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.intell.2019.101376?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rogier A. Kievit & Simon W. Davis & Daniel J. Mitchell & Jason R. Taylor & John Duncan & Richard N.A. Henson, 2014. "Distinct aspects of frontal lobe structure mediate age-related differences in fluid intelligence and multitasking," Nature Communications, Nature, vol. 5(1), pages 1-10, December.
    2. Donald M Lyall & Breda Cullen & Mike Allerhand & Daniel J Smith & Daniel Mackay & Jonathan Evans & Jana Anderson & Chloe Fawns-Ritchie & Andrew M McIntosh & Ian J Deary & Jill P Pell, 2016. "Cognitive Test Scores in UK Biobank: Data Reduction in 480,416 Participants and Longitudinal Stability in 20,346 Participants," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-10, April.
    3. MacPherson, Sarah E. & Allerhand, Michael & Cox, Simon R. & Deary, Ian J., 2019. "Individual differences in cognitive processes underlying Trail Making Test-B performance in old age: The Lothian Birth Cohort 1936," Intelligence, Elsevier, vol. 75(C), pages 23-32.
    4. Gignac, Gilles E. & Bates, Timothy C., 2017. "Brain volume and intelligence: The moderating role of intelligence measurement quality," Intelligence, Elsevier, vol. 64(C), pages 18-29.
    5. Joseph Henrich & Steven J. Heine & Ara Norenzayan, 2010. "Most people are not WEIRD," Nature, Nature, vol. 466(7302), pages 29-29, July.
    6. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. de Souza, Erick Almeida & Silva, Stéphanie Andrade & Vieira, Bruno Hebling & Salmon, Carlos Ernesto Garrido, 2023. "fMRI functional connectivity is a better predictor of general intelligence than cortical morphometric features and ICA parcellation order affects predictive performance," Intelligence, Elsevier, vol. 97(C).
    2. Bruton, Oliver J., 2021. "Is there a “g-neuron”? Establishing a systematic link between general intelligence (g) and the von Economo neuron," Intelligence, Elsevier, vol. 86(C).
    3. Hilger, Kirsten & Spinath, Frank M. & Troche, Stefan & Schubert, Anna-Lena, 2022. "The biological basis of intelligence: Benchmark findings," Intelligence, Elsevier, vol. 93(C).
    4. Vieira, Bruno Hebling & Pamplona, Gustavo Santo Pedro & Fachinello, Karim & Silva, Alice Kamensek & Foss, Maria Paula & Salmon, Carlos Ernesto Garrido, 2022. "On the prediction of human intelligence from neuroimaging: A systematic review of methods and reporting," Intelligence, Elsevier, vol. 93(C).
    5. Danni A. Gadd & Robert F. Hillary & Daniel L. McCartney & Liu Shi & Aleks Stolicyn & Neil A. Robertson & Rosie M. Walker & Robert I. McGeachan & Archie Campbell & Shen Xueyi & Miruna C. Barbu & Claire, 2022. "Integrated methylome and phenome study of the circulating proteome reveals markers pertinent to brain health," Nature Communications, Nature, vol. 13(1), pages 1-14, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ingo S. Seifert & Julia M. Rohrer & Boris Egloff & Stefan C. Schmukle, 2021. "The Development of the Rank-Order Stability of the Big Five across the Life Span," SOEPpapers on Multidisciplinary Panel Data Research 1156, DIW Berlin, The German Socio-Economic Panel (SOEP).
    2. Gignac, Gilles E. & Stevens, Elizabeth M., 2024. "Attitude toward numbers: A better predictor of financial literacy and intelligence than need for cognition," Intelligence, Elsevier, vol. 103(C).
    3. Sonia Nawrocka & Hans De Witte & Margherita Pasini & Margherita Brondino, 2023. "A Person-Centered Approach to Job Insecurity: Is There a Reciprocal Relationship between the Quantitative and Qualitative Dimensions of Job Insecurity?," IJERPH, MDPI, vol. 20(7), pages 1-27, March.
    4. Md. Mominur Rahman & Bilkis Akhter, 2021. "The impact of investment in human capital on bank performance: evidence from Bangladesh," Future Business Journal, Springer, vol. 7(1), pages 1-13, December.
    5. Masashi Soga & Kevin J. Gaston & Yuichi Yamaura & Kiyo Kurisu & Keisuke Hanaki, 2016. "Both Direct and Vicarious Experiences of Nature Affect Children’s Willingness to Conserve Biodiversity," IJERPH, MDPI, vol. 13(6), pages 1-12, May.
    6. César Merino-Soto & Gina Chávez-Ventura & Verónica López-Fernández & Guillermo M. Chans & Filiberto Toledano-Toledano, 2022. "Learning Self-Regulation Questionnaire (SRQ-L): Psychometric and Measurement Invariance Evidence in Peruvian Undergraduate Students," Sustainability, MDPI, vol. 14(18), pages 1-17, September.
    7. Nathaniel Oliver Iotti & Damiano Menin & Tomas Jungert, 2022. "Early Adolescents’ Motivations to Defend Victims of Cyberbullying," IJERPH, MDPI, vol. 19(14), pages 1-9, July.
    8. AJ Golio, 2024. "Whose Neighborhood Now? Gentrification and Community Life in Low-Income Urban Neighborhoods," Working Papers 24-29, Center for Economic Studies, U.S. Census Bureau.
    9. Peter Tavel & Bibiana Jozefiakova & Peter Telicak & Jana Furstova & Michal Puza & Natalia Kascakova, 2022. "Psychometric Analysis of the Shortened Version of the Spiritual Well-Being Scale on the Slovak Population (SWBS-Sk)," IJERPH, MDPI, vol. 19(1), pages 1-12, January.
    10. Allen, Jaime & Eboli, Laura & Forciniti, Carmen & Mazzulla, Gabriella & Ortúzar, Juan de Dios, 2019. "The role of critical incidents and involvement in transit satisfaction and loyalty," Transport Policy, Elsevier, vol. 75(C), pages 57-69.
    11. John A. List, 2024. "Optimally generate policy-based evidence before scaling," Nature, Nature, vol. 626(7999), pages 491-499, February.
    12. Christoph Dworschak, 2024. "Bias mitigation in empirical peace and conflict studies: A short primer on posttreatment variables," Journal of Peace Research, Peace Research Institute Oslo, vol. 61(3), pages 462-476, May.
    13. Andreea-Ionela Puiu & Anca Monica Ardeleanu & Camelia Cojocaru & Anca Bratu, 2021. "Exploring the Effect of Status Quo, Innovativeness, and Involvement Tendencies on Luxury Fashion Innovations: The Mediation Role of Status Consumption," Mathematics, MDPI, vol. 9(9), pages 1-18, May.
    14. Slupphaug, KJell & Mehmetoglu, Mehmet & Mittner, Matthias, 2024. "modsem: An R package for estimating latent interactions and quadratic effects," OSF Preprints h3rpw, Center for Open Science.
    15. Andres Trujillo-Barrera & Joost M. E. Pennings & Dianne Hofenk, 2016. "Understanding producers' motives for adopting sustainable practices: the role of expected rewards, risk perception and risk tolerance," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 43(3), pages 359-382.
    16. Bouma, J.A. & Nguyen, Binh & van der Heijden, Eline & Dijk, J.J., 2018. "Analysing Group Contract Design Using a Lab and a Lab-in-the-Field Threshold Public Good Experiment," Discussion Paper 2018-049, Tilburg University, Center for Economic Research.
    17. Daria J. Kuss & Lydia Harkin & Eiman Kanjo & Joel Billieux, 2018. "Problematic Smartphone Use: Investigating Contemporary Experiences Using a Convergent Design," IJERPH, MDPI, vol. 15(1), pages 1-16, January.
    18. Allen, Jaime & Muñoz, Juan Carlos & Ortúzar, Juan de Dios, 2019. "On evasion behaviour in public transport: Dissatisfaction or contagion?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 626-651.
    19. Cloarec, Julien, 2022. "Privacy controls as an information source to reduce data poisoning in artificial intelligence-powered personalization," Journal of Business Research, Elsevier, vol. 152(C), pages 144-153.
    20. Merkle, Edgar C. & Steyvers, Mark & Mellers, Barbara & Tetlock, Philip E., 2017. "A neglected dimension of good forecasting judgment: The questions we choose also matter," International Journal of Forecasting, Elsevier, vol. 33(4), pages 817-832.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:intell:v:76:y:2019:i:c:9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.