bioRxivNeurosciencePreprint
Creativity Potential Networks: Brain Markers for Novelty and Feasibility of Upcoming Divergent Thinking Solutions
Abstract
The brains resting-state activity can serve as an indicator of cognitive flexibility and predict the likelihood of an upcoming Aha experience. This suggests that spontaneous neural dynamics reflect a persons readiness for creative insight and underscore the potential of resting-state measures as biomarkers for anticipating creative breakthroughs. However, solutions accompanied by an Aha experience are not always truly creative, so it may be more valuable to identify biomarkers specifically linked to novelty and usefulness--two key dimensions of creative performance. To achieve this, we recruit 49 participants to complete the Alternative Uses Test, in which unconventional uses for everyday items are generated. We evaluate the responses for both novelty and feasibility using automated GPT-based methods and analyze resting-state EEG prior to the test. We find that creative performance is better predicted by interactions between different brain areas than by the activation of individual regions. Specifically, the degree centrality of theta-band functional connectivity in the right parietal and occipital areas correlates with novelty, while connectivity in the right middle and inferior frontal areas is associated with more feasible answers. These findings highlight distinct resting-state brain networks underlying the "creative potential" for novelty and feasibility, which could be leveraged to monitor and enhance brain flexibility. Significance statementOur study introduces the Creativity Potential Network (CPN), a resting-state brain network that can predict the novelty and feasibility of the upcoming solution in creative problem-solving. We show that the CPN is represented by communication between brain areas, and that the networks for novelty and feasibility are spatially distinct. This work provides a potential method to assess the potential to be creative without relying on behavioral measures and could be combined with neurofeedback to monitor and enhance brain flexibility.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 0
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