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The question of what type of attention is associated with creative potential has predominantly been examined using divergent thinking tasks and without the benefits of cognitive neuroscience methods. To address this gap, we rely on a neural approach by indexing attention using the P50 ERP component. The P50 measures sensory gating, which is the brain's ability to filter out or inhibit responses to repeated stimuli. We analyze the relationships between neural responses to P50 and performance on two tasks designed to measure creative potential: a convergent task and a divergent task. While we did not find evidence of a relationship between attention and the originality component of divergent thinking, our results show that leaky attention was positively associated with the fluency component of divergent thinking but negatively associated with performance on the convergent thinking task. This result highlights that the relationship between attention and performance on creative tasks may depend on the type of task. [ABSTRACT FROM AUTHOR]

Creativity is commonly assessed using divergent thinking tasks, which measure the fluency, flexibility, originality, and elaboration of participant output on a variety of different tasks. This study assesses the degree to which creativity can be identified based on linguistic features of participants’ language while completing collaborative divergent thinking tasks. To this end, 78 participants’ conversational dialogs (i.e., 39 dyads) within a chat environment were collected while completing three open-ended problem-solving tasks. Expert raters scored the dialogs in terms of fluency, flexibility, elaboration, and originality, as well as three types of creative language (metaphor and simile, humor, and word play). Factor analyses indicated that these scores captured two main constructs (creativity and elaboration). The linguistic features of the participants’ language (captured computationally using natural language processing tools) accounted for significant amounts of variation in both the creativity (R2 = .640) and elaboration (R2 = .550) scores within linear mixed effect (LME) models. These results highlight specific linguistic features that can be used to explain large amounts of variance in constructs related to creativity. [ABSTRACT FROM AUTHOR]