Big-C creativity in artists and scientists is associated with more random global but less random local fMRI functional connectivity.

Brain mechanisms underlying creativity are largely unknown and few studies have involved exceptionally creative individuals. We examined functional MRI (fMRI) connectivity in a “smart comparison group” (SCG; n = 24), and in exceptionally creative (“Big C”) visual artists (VIS; n = 21) and scientists (SCI; n = 21). Groups were matched on age, sex, and estimated IQ. FMRI scans were acquired during the resting-state and performance of two tasks: (a) alternative uses test (AUT), putatively measuring divergent thinking; and (b) remote associates test (RAT), putatively engaging convergent thinking. Graph theory measures of functional connectivity were compared across groups using generalized linear mixed models. Global connectivity measures included small-worldness (indexing efficiency), clustering coefficient, and characteristic path length. Local connectivity measures included local efficiency and clustering coefficients within default mode, dorsal attention, frontoparietal, salience, ventral attention, and visual networks. During the resting-state, global small-worldness was lower for SCI than SCG; VIS had intermediate values. Relative to SCG, the Big C groups had higher local clustering coefficients during the resting-state conditions but lower local clustering during the AUT condition. No significant differences were found during the convergent thinking test (RAT). These findings suggest that Big C creativity is associated with more “random” rather than more “efficient” global network functional architecture, with condition-dependent variations in local clustering and efficiency.

Large condition-dependent correlations between global and local clustering measures deserve further examination in exceptionally creative and other groups to more fully characterize the functional topology of brain networks most relevant to creativity. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

https://doi.apa.org/doiLanding?doi=10.1037%2Faca0000463