What Does Temporal Brain Signal Complexity Reveal About Verbal Creativity?

Frontiers in Behavioral Neuroscience
Yadwinder KaurAndrea Hildebrandt

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...Continue Reading

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Software Mentioned

Brain Vision Recorder
EEGLAB
R Software for Statistical Computing R Core Team
PsychoPy
LAtent VAriable Analysis
SASICA
SampEn

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