Abstract

Recent empirical evidence reveals that creative idea generation builds upon an interplay of multiple neural networks. Measures of temporal complexity yield important information about the underlying mechanisms of these co-activated neural networks. A few neurophysiological studies investigated brain signal complexity (BSC) during the production of creative verbal associations and resting states, aiming to relate it with creative task performance. However, it is unknown whether the complexity of brain signals can distinguish between productions of typical and original verbal associations. In the present study, we investigated verbal creativity with multiscale entropy (MSE) of electroencephalography (EEG) signals, which quantifies complexity over multiple timescales, capturing unique dynamic features of neural networks. MSE was measured in verbal divergent thinking (DT) states while emphasizing on producing either typical verbal associations or original verbal associations. We hypothesized that MSE differentiates between brain states characterizing the production of typical and original associations and is a sensitive neural marker of individual differences in producing original associations. Results from a sample of N = 92 young adults revealed slightly higher average MSE for original as compared with typical association production in small and medium timescales at frontal electrodes and slightly higher average MSE for typical association production in higher timescales at parietal electrodes. However, measurement models failed to uncover specificity of individual differences as MSE in typical vs. original associations was perfectly correlated. Hence, individuals with higher MSE in original association condition also exhibit higher MSE during the production of typical associations. The difference between typical and original association MSE was not significantly associated with human-rated originality of the verbal associations. In sum, we conclude that MSE is a potential marker of creative verbal association states, but replications and extensions are needed, especially with respect to the brain-behavior relationships.

Highlights

  • IntroductionCreativity is a complex construct, defined as the process of producing an original and appropriate outcome (Mumford et al, 2003; Runco and Jaeger, 2012; Gabora, 2019)

  • Creativity as a Complex TraitCreativity is a complex construct, defined as the process of producing an original and appropriate outcome (Mumford et al, 2003; Runco and Jaeger, 2012; Gabora, 2019)

  • Following a similar line of theorizing, in the present research, we propose that the concepts of Honing theory (HT) can be applied to understand the temporal complexity of EEG signals during creative verbal associations

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Summary

Introduction

Creativity is a complex construct, defined as the process of producing an original and appropriate outcome (Mumford et al, 2003; Runco and Jaeger, 2012; Gabora, 2019). Creative solutions require complex thinking processes, such as divergent thinking (DT; Guilford, 1950). The creative process includes various aspects, such as fluent idea production, flexibility of thought, degree of elaboration, and originality of ideas (Guilford, 1956; Guilford and Merrifield, 1960). The answers given in DT tasks are mainly evaluated by humans (Silvia et al, 2008), especially when it comes to judging the product of a creative thought process in terms of its originality. Human ratings of task outcomes are customary in neuroscience (see Fink and Neubauer, 2008)

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