Transcranial direct current stimulation (tDCS) over the dorsolateral prefrontal cortex (DLPFC) has been shown to enhance divergent and convergent creative thinking. Yet, how stimulation impacts creative performance over time, and what cognitive mechanisms underlie any such enhancement, remain largely unanswered questions. In the present research, we aimed to (1) verify the impact of DLPFC tDCS on both convergent and divergent thinking, and further investigated (2) the temporal dynamics of divergent thinking, focusing on the serial order effect (i.e., the tendency for ideas to become more original and less frequent over time), and (3) any role that cognitive inhibition may play in mediating any effect of stimulation on creative thinking (considering the DLPFC's involvement in driving inhibitory processes that are also relevant for creative thinking). In a within-subjects design, twenty-six participants received three types of cross-hemispheric tDCS stimulation over the DLPFC (left cathodal and right anodal, L-R+; left anodal and right cathodal, L+R-; and sham). Before stimulation, they completed a pre-flanker task measuring cognitive inhibition; during stimulation, they completed the Alternate Uses Task (AUT), Remote Associates Test (RAT), and post-flanker task. Results showed that, compared with the sham stimulation, originality of responses in the AUT was significantly enhanced in the L+R- condition, while no tDCS effect was observed for the RAT. Additionally, compared with the other stimulation conditions, we found a diminished serial order effect in the L+R- condition characterized by an accelerated production of more original ideas. Critically, the L+R- condition was accompanied by better performance on the flanker task. Our findings thus verify that L+R- tDCS over the DLPFC accelerates idea originality also providing tentative clues that inhibition may act as a cognitive mechanism underlying enhancements in divergent thinking resulting from frontal lobe neuromodulation.

The associative theory of creativity has long held that creative thinking involves connecting remote concepts in semantic memory. Network science tools have recently been applied to map the organization of concepts in semantic memory, and to study the link between semantic memory and creativity. Yet such work has largely overlooked the domain of convergent thinking, despite the theoretical importance of semantic memory networks for facilitating associative processes relevant for convergent problem solving (e.g., spreading activation). Convergent thinking problems, such as the Compound Remote Associates (CRA) test, can be solved with insight (the sudden aha experience) or analysis (deliberately and incrementally working towards the solution). In a sample of 477 participants, we adopted network science methods to compare semantic memory structure across two grouping variables: 1) convergent thinking ability (i.e., CRA accuracy), and 2) the self-reported tendency to solve problems with insight or analysis. Semantic memory networks were constructed from a semantic fluency task, and problem solving style (insight or analysis) was determined from judgments provided during solving of CRAs. We found that, compared to the low-convergent thinking group, the high-convergent thinking group exhibited a more flexible and interconnected semantic network-with short paths and many connections between concepts. Moreover, participants who primarily solved problems with insight (compared to analysis) showed shorter average path distances between concepts, even after controlling for accuracy. Our results extend the literature on semantic memory and creativity, and suggest that the organization of semantic memory plays a key role in convergent thinking, including insight problem solving.

Existing research has consistently supported a relationship between creative achievement and specific personality traits (e.g. openness to experience). However, such work has largely focused on univariate associations, potentially obscuring complex interactions among multiple personality factors, rendering an incomplete picture of the creative personality. We applied a psychometric network approach to characterize the multidimensional personality structure of highly creative individuals in the arts (artists) and sciences (scientists), using data from three samples (N = 4,015): college students, a representative adult sample, and the Big-C project of eminent creative professionals. Replicating past work, we found that artists showed reliably higher levels of openness to experience compared to scientists and a control group of less creative people. Psychometric network analysis revealed that artists were characterized by higher connectivity (i.e. co-occurrence) with other personality traits for openness, indicating that openness may be more heterogeneous in how it co-occurs with other personality traits in highly creative people. Across all three samples, we found that the scientists' personality network structure was more cohesive than the personality network of artists and the control group, indicating greater homogeneity in the personality characteristics of scientists. Our findings uncover a constellation of traits that give rise to creative achievement in the arts and sciences.

For decades, researchers have struggled with measurement problems related to the construct validity of divergent and convergent thinking in creativity assessments. In response, some have called for battery-based approaches. Recently, digital games have emerged as a potential alternative, offering increased scalability and improved ecological validity. This article presents CREA: a new, scalable, game-based assessment suite. CREA includes crea.tiles and crea.blender, non-verbal games featuring both divergent and convergent thinking modes, as well as crea.ideas - the Alternative Uses Task, a standard test of divergent thinking, and crea.logic - a test of abstract reasoning. The novel convergent and divergent thinking game modes are constructed within the same contextual environment and with theoretically motivated differences in game-prompts to understand and generalize from the emerging elicited behaviors. In this study, 408 participants completed the CREA suite and selected validation measures, representing the largest game-based validation study to date. Both convergent and discriminant validity is demonstrated for crea.tiles with respect to standard tests, with correlations ranging from r = .1-.4. Having CREA freely accessible, we aim to broaden the accessibility of creativity assessment to researchers, educators, and the general public and through this scaleup validate the rich creative behavioral patterns observed in this study. Plain Language SummaryCreative thinking is an essential attribute for success in the 21st century, yet it is difficult to measure because it is complex and contextual. Traditional pen and paper tests of creative thinking are the status quo and are backed up by years of research; however, there are well-known issues with these tests such as (1) they are difficult to scale up, as they require expert human-raters to evaluate the responses; (2) many of them are verbal, which is not necessarily fair within a culturally and linguistically diverse population; and (3) there are still fundamental open questions about what they actually measure. Digital, game-based creativity assessments represent an emerging alternative to conventional creativity tests, presenting the potential for increasing scalability and improving the quality of the results. This article presents CREA: a new, scalable, suite of game-based assessments. CREA includes crea.tiles and crea.blender - non-verbal games featuring several game modes, as well as crea.ideas - a standard test of divergent thinking, and crea.logic - a test of abstract reasoning. Participants (n=408) were university students from North America. They completed the CREA suite and a series of validation measures. The results from the study indicate that the current, freely accessible, version of the CREA suite demonstrated sufficient validity to be used by researchers and practitioners as a scalable, creativity assessment instrument for automated figural assessment of divergent and convergent thinking.

Scoring divergent thinking tasks opens multiple avenues and possibilities-decisions researchers have to make. While some scholars postulate that scoring should focus on the best ideas provided, the measurement of the best responses (e.g., top scoring) comes along with challenges. More specifically, compared to the average quality across all responses, top scoring uses less information-the bad ideas are thrown away-which decreases reliability. To resolve this issue, this article introduces a multidimensional top-scoring approach analogous to linear growth modeling which retains information provided by all responses (best ideas and bad ideas). Across two studies, using both subjective human ratings and semantic distance originality scoring of responses to over a dozen divergent thinking tasks, we demonstrated that Maximum (the best idea) and Top2 Scoring (two best ideas) could surpass typically applied average scoring in measurement precision when the bad ideas' originality is used as auxiliary information (i.e., additional information in the analysis). We thus recommend retaining all ideas when scoring divergent thinking tasks, and we discuss the potential this new approach holds for creativity research and practice.

Empathy research has long emphasized accuracy when imagining other minds. We explore whether empathy can be a creative process, where people think of multiple diverging possibilities of others' experiences. We developed two tasks to measure creative empathy. First, we adapted forward flow to measure the dynamic unfolding of creativity while imagining other minds, quantified as semantic distance between mental state concepts when freely associating the contents of other minds. Second, we developed a divergent thinking task where participants reflect on others' mental states and responses are scored using subjective and automated methods. In Studies 1-3, participants instructed to be creative showed higher scores than those instructed to be accurate and a no-instruction control, demonstrating that people vary in how creatively they approach empathy. In Study 4, participants instructed to be empathic (vs. objective) toward a target showed greater creativity on the divergent thinking task, demonstrating that empathy can produce creativity. Creativity on these tasks were inconsistently associated with trait and state empathy measures, suggesting complex relationships between creative empathy and empathic outcomes. Overall, these findings support a novel approach to measuring empathy that accounts for creative processes, broadening the scope of empathy and creativity research.

Human ratings are ubiquitous in creativity research. Yet, the process of rating responses to creativity tasks - typically several hundred or thousands of responses, per rater - is often time-consuming and expensive. Planned missing data designs, where raters only rate a subset of the total number of responses, have been recently proposed as one possible solution to decrease overall rating time and monetary costs. However, researchers also need ratings that adhere to psychometric standards, such as a certain degree of reliability, and psychometric work with planned missing designs is currently lacking in the literature. In this work, we introduce how judge response theory and simulations can be used to fine-tune planning of missing data designs. We provide open code for the community and illustrate our proposed approach by a cost-effectiveness calculation based on a realistic example. We clearly show that fine-tuning helps to save time (to perform the ratings) and monetary costs, while simultaneously targeting expected levels of reliability.

The associative theory posits that creativity relates to people's ability to connect remote associations to form new ideas, based on the structure of their semantic memory. This theory has spurred several recent studies connecting semantic memory structure and associative thinking to creativity, capitalizing on advances in computational methods. To date, however, this research has almost exclusively focused on assessing creativity in the general population (e.g., assessed via divergent thinking tests), with far less work examining the role of associative thinking in eminently-creative individuals across the arts and sciences. Leveraging data collected as part of the Big-C Project-a sample of world-renowned visual artists (VIS) and scientists, and an intelligence-matched comparison group-we tested whether the ability to generate remote word associations differs as a function of creative expertise. Specifically, we used distributional semantic models to calculate the semantic distance of word associations across three conditions: a free association condition and two goal-directed conditions (common association and uncommon association). We found an interaction between domain expertise and association condition: while artists generated more distant associations overall, this effect was driven by substantially more distant responses in the free association condition. Our findings indicate that VIS spontaneously produce more remote associations-potentially due to a more interconnected semantic memory network structure-but that creative expertise is less relevant for producing associations that require goal-directed cognitive search. The findings are interpreted in the context of the ongoing debate on the domain-generality and domain-specificity of creativity.

Semantic distance scoring provides an attractive alternative to other scoring approaches for responses in creative thinking tasks. In addition, evidence in support of semantic distance scoring has increased over the last few years. In one recent approach, it has been proposed to combine multiple semantic spaces to better balance the idiosyncratic influences of each space. Thereby, final semantic distance scores for each response are represented by a composite or factor score. However, semantic spaces are not necessarily equally weighted in mean scores, and the usage of factor scores requires high levels of factor determinacy (i.e., the correlation between estimates and true factor scores). Hence, in this work, we examined the weighting underlying mean scores, mean scores of standardized variables, factor loadings, weights that maximize reliability, and equally effective weights on common verbal creative thinking tasks. Both empirical and simulated factor determinacy, as well as Gilmer-Feldt's composite reliability, were mostly good to excellent (i.e., > .80) across two task types (Alternate Uses and Creative Word Association), eight samples of data, and all weighting approaches. Person-level validity findings were further highly comparable across weighting approaches. Observed nuances and challenges of different weightings and the question of using composites vs. factor scores are thoroughly provided.