aSchool of Computer Science and Technology, Xidian University, Xi'an 710071, Shannxi, PR ChinabInstitute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, PR ChinacDepartment of Computer Science, University of Warwick, Coventry CV4 7AL, UKdOxford Centre for Computational Neuroscience, Oxford UKeKey Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, PR ChinafSchool of Psychology, Southwest University (SWU), Chongqing, PR ChinagDepartment of Computer and Information Sciences, Temple University, 1801 North Broad Street, Philadelphia, PA 19122, USAhCollaborative Innovation Center for Brain Science, Fudan University, Shanghai, 200433, PR ChinaiShanghai Center for Mathematical Sciences, Shanghai, 200433, PR ChinajSouthwest University Branch, Collaborative Innovation Center of Assessment Toward Basic Education Quality, Beijing Normal University, Beijing 100875, PR ChinakZhongshan Hospital, Fudan University, Shanghai, 200433, PR China
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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<Symbol). 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.HIGHLIGHTSThe neural correlates and genetic determinates of creativity remain largely unclear.We developed a prediction-based approach in identifying the functional connectivity and SNPs closely related to creativity.High figural creativity is associated with brain networks with strong top-down control versus weak bottom-up processes.Genes correlated with figural creativity were involved in glutamate and GABA functionality.Our neuroimaging prediction model was cross-validated by a completely new dataset.