4.7 Article

Neural and genetic determinants of creativity

Journal

NEUROIMAGE
Volume 174, Issue -, Pages 164-176

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2018.02.067

Keywords

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Funding

  1. key project of Shanghai Science & Technology Innovation Plan [15JC1400101, 16JC1420402]
  2. National Natural Science Foundation of China [71661167002, 91630314, NSFC 31571137, 31771231]
  3. Shanghai AI Platform for Diagnosis and Treatment of Brain Diseases [2016-17]
  4. Base for Introducing Talents of Discipline to Universities [B18015]
  5. National Science Foundation of China [NSFC 11674352, 61571341, NSFC 61573107]
  6. Fundamental Research Funds for the Central Universities of China [JBZ170301]
  7. special Funds for Major State Basic Research Projects of China [2015CB856003]
  8. Project of the National Defense Science and Technology Innovation Special Zone
  9. Chang Jiang Scholars Program
  10. National Outstanding Young People Plan
  11. Program for the Top Young Talents by Chongqing
  12. Natural Science Foundation of Chongqing [cstc2015jcyjA10106]
  13. Fok Ying Tung Education Foundation [151023]
  14. Research Program Funds of the Collaborative Innovation Center of Assessment toward Basic Education Quality at Beijing Normal University

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Creative thinking plays a vital role in almost all aspects of human life. However, little is known about the neural and genetic mechanisms underlying creative thinking. Based on a cross-validation based predictive framework, we searched from the whole-brain connectome (34,716 functional connectivities) and whole genome data (309,996 SNPs) in two datasets (all collected by Southwest University, Chongqing) consisting of altogether 236 subjects, for a better understanding of the brain and genetic underpinning of creativity. Using the Torrance Tests of Creative Thinking score, we found that high figural creativity is mainly related to high functional connectivity between the executive control, attention, and memory retrieval networks (strong top-down effects); and to low functional connectivity between the default mode network, the ventral attention network, and the subcortical and primary sensory networks (weak bottom-up processing) in the first dataset (consisting of 138 subjects). High creativity also correlates significantly with mutations of genes coding for both excitatory and inhibitory neurotransmitters. Combining the brain connectome and the genomic data we can predict individuals' creativity scores with an accuracy of 78.4%, which is significantly better than prediction using single modality data (gene or functional connectivity), indicating the importance of combining multi-modality data. Our neuroimaging prediction model built upon the first dataset was cross-validated by a completely new dataset of 98 subjects (r = 0.267, p = 0.0078) with an accuracy of 64.6%. In addition, the creativity-related functional connectivity network we identified in the first dataset was still significantly correlated with the creativity score in the new dataset (p<10(-3)). In summary, our research demonstrates that strong top-down control versus weak bottom-up processes underlie creativity, which is modulated by competition between the glutamate and GABA neurotransmitter systems. Our work provides the first insights into both the neural and the genetic bases of creativity.

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