Robust prediction of individual creative ability from brain functional connectivity

Roger E. Beaty, Yoed N. Kenett, Alexander P. Christensen, Monica D. Rosenberg, Mathias Benedek, Qunlin Chen, Andreas Fink, Jiang Qiu, Thomas R. Kwapil, Michael J. Kane, Paul J. Silvia

Research output: Contribution to journalArticle

79 Citations (Scopus)

Abstract

People’s ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis—connectome-based predictive modeling—to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences (r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems—intrinsic functional networks that tend to work in opposition—suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks.

Original languageEnglish (US)
Pages (from-to)1087-1092
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume115
Issue number5
DOIs
StatePublished - Jan 30 2018

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Creativity
Brain
Aptitude
Magnetic Resonance Imaging
Parietal Lobe
Functional Neuroimaging
Art

All Science Journal Classification (ASJC) codes

  • General

Cite this

Beaty, Roger E. ; Kenett, Yoed N. ; Christensen, Alexander P. ; Rosenberg, Monica D. ; Benedek, Mathias ; Chen, Qunlin ; Fink, Andreas ; Qiu, Jiang ; Kwapil, Thomas R. ; Kane, Michael J. ; Silvia, Paul J. / Robust prediction of individual creative ability from brain functional connectivity. In: Proceedings of the National Academy of Sciences of the United States of America. 2018 ; Vol. 115, No. 5. pp. 1087-1092.
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Beaty, RE, Kenett, YN, Christensen, AP, Rosenberg, MD, Benedek, M, Chen, Q, Fink, A, Qiu, J, Kwapil, TR, Kane, MJ & Silvia, PJ 2018, 'Robust prediction of individual creative ability from brain functional connectivity', Proceedings of the National Academy of Sciences of the United States of America, vol. 115, no. 5, pp. 1087-1092. https://doi.org/10.1073/pnas.1713532115

Robust prediction of individual creative ability from brain functional connectivity. / Beaty, Roger E.; Kenett, Yoed N.; Christensen, Alexander P.; Rosenberg, Monica D.; Benedek, Mathias; Chen, Qunlin; Fink, Andreas; Qiu, Jiang; Kwapil, Thomas R.; Kane, Michael J.; Silvia, Paul J.

In: Proceedings of the National Academy of Sciences of the United States of America, Vol. 115, No. 5, 30.01.2018, p. 1087-1092.

Research output: Contribution to journalArticle

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