Are intelligence and creativity distinct abilities, or do they rely on the same cognitive and neural systems? We sought to quantify the extent to which intelligence and creative cognition overlap in brain and behavior by combining machine learning of fMRI data and latent variable modeling of cognitive ability data in a sample of young adults (N = 186) who completed a battery of intelligence and creative thinking tasks. The study had 3 analytic goals: (a) to assess contributions of specific facets of intelligence (e.g., fluid and crystallized intelligence) and general intelligence to creative ability (i. e., divergent thinking originality), (b) to model whole-brain functional connectivity networks that predict intelligence facets and creative ability, and ( c) to quantify the degree to which these predictive networks overlap in the brain. Using structural equation modeling, we found moderate to large correlations between intelligence facets and creative ability, as well as a large correlation between general intelligence and creative ability (r = .63). Using connectome-based predictive modeling, we found that functional brain networks that predict intelligence facets overlap to varying degrees with a network that predicts creative ability, particularly within the prefrontal cortex of the executive control network. Notably, a network that predicted general intelligence shared 46% of its functional connections with a network that predicted creative ability-including connections linking executive control and salience/ventral attention networks-suggesting that intelligence and creative thinking rely on similar neural and cognitive systems.

Generating creative ideas involves flexibly combining concepts stored in memory. Although memory provides a foundation for creative thought, existing associations can also constrain idea generation by acting as a source of interference, particularly when salient and unoriginal information becomes activated. Overcoming fixating effects of salient associations is therefore required to generate novel associations. Although previous research has explored fixation effects in verbal creativity, less is known about how it affects the generation of visual associations. In the present research, we investigated the impact of priming salient associations on the generation of creative visual ideas. In an initial pilot study, participants were shown ambiguous images and asked to provide labels describing them; from these labels, 2 subsets were selected based on their relative frequency in the sample (i.e., high- and low-frequency labels). In 2 experiments, we then tested whether priming participants with these high- and low-frequency labels impacted the subsequent generation of new creative labels. Across both experiments, we found that high-frequency labels had a constraining effect on idea generation: Participants took significantly longer to generate their first response and generated fewer total responses in the high-frequency condition. Moreover, visuospatial intelligence (Gv) reduced susceptibility to this constraining effect, with high-Gv participants generating more creative labels in the high-frequency condition, pointing to a potential inhibitory benefit of Gv. The findings indicate that salient associations have a constraining effect on visual idea generation-even when these associations are linked to ambiguous images-and that Gv may support creative thinking via increased inhibitory control.

While a recent upsurge in the application of neuroimaging methods to creative cognition has yielded encouraging progress toward understanding the neural underpinnings of creativity, the neural basis of barriers to creativity are as yet unexplored. Here, we report the first investigation into the neural correlates of one such recently identified barrier to creativity: anxiety specific to creative thinking, or creativity anxiety (Daker et al., 2019). We employed a machine-learning technique for exploring relations between functional connectivity and behavior (connectome-based predictive modeling; CPM) to investigate the functional connections underlying creativity anxiety. Using whole-brain resting-state functional connectivity data, we identified a network of connections or edges that predicted individual differences in creativity anxiety, largely comprising connections within and between regions of the executive and default networks and the limbic system. We then found that the edges related to creativity anxiety identified in one sample generalize to predict creativity anxiety in an independent sample. We additionally found evidence that the network of edges related to creativity anxiety were largely distinct from those found in previous work to be related to divergent creative ability (Beaty et al., 2018). In addition to being the first work on the neural correlates of creativity anxiety, this research also included the development of a new Chinese-language version of the Creativity Anxiety Scale, and demonstrated that key behavioral findings from the initial work on creativity anxiety are replicable across cultures and languages.

Creative thinking is thought to be supported by both spontaneous associative and controlled executive processes. Recently, a new measure of associative cognition has been developed-forward flow-which uses computational semantic models (e.g., latent semantic analysis; LSA) to capture how far people travel in semantic space during a chained free association task. The present research aims to extend the psychometrics of forward flow by 1) leveraging multiple computational semantic models for forward flow computation (reliability) and 2) testing how this metric of associative ability relates to divergent creative thinking (validity). In addition, using structural equation modeling, we test dual-process theories of creative cognition by examining the relative contribution of associative and executive abilities to divergent thinking. Study 1 (n = 151) finds moderately improved reliability of forward flow using the new multi-model approach (compared to LSA only), as well as positive effects of both forward flow (beta = .48) and general intelligence (beta = .36) on divergent thinking (human creativity ratings) in the same structural regression model. This pattern of results was replicated in Study 2 (n = 150), which showed large effects of forward flow (beta = .42) and general intelligence (beta = .46) on divergent thinking. The results expand the psychometrics of forward flow and provide new evidence for dual process models of creative cognition.

Cognitive and neuroimaging evidence suggests that episodic and semantic memory-memory for autobiographical events and conceptual knowledge, respectively-support different aspects of creative thinking, with a growing number of studies reporting activation of brain regions within the default network during performance on creative thinking tasks. The present research sought to dissociate neural contributions of these memory processes by inducing episodic or semantic retrieval orientations prior to performance on a divergent thinking task during fMRI. We conducted a representational similarity analysis (RSA) to identify multivoxel patterns of neural activity that were similar across induction (episodic and semantic) and idea generation. At the behavioral level, we found that semantic induction was associated with increased idea originality, assessed via computational estimates of semantic distance between concepts. RSA revealed that multivoxel patterns during semantic induction and subsequent idea generation were more similar (compared to episodic induction) within the left angular gyrus (AG), posterior cingulate cortex (PCC), and left anterior inferior parietal lobe (IPL). Conversely, activity patterns during episodic induction and subsequent generation were more similar within left parahippocampal gyrus and right anterior IPL. Together, the findings point to dissociable contributions of episodic and semantic memory processes to creative cognition and suggest that distinct regions within the default network support specific memory-related processes during divergent thinking.

A central challenge for creativity research-as for all areas of experimental psychology and cognitive neuroscience-is to establish a mapping between constructs and measures (i.e., identifying a set of tasks that best captures a set of creative abilities). A related challenge is to achieve greater consistency in the measures used by different researchers; inconsistent measurement hinders progress toward shared understanding of cognitive and neural components of creativity. New resources for aggregating neuroimaging data, and the emergence of methods for identifying structure in multivariate data, present the potential for new approaches to address these challenges. Identifying meta-analytic structure (i.e., similarity) in neural activity associated with creativity tasks might help identify subsets of these tasks that best reflect the similarity structure of creativity-relevant constructs. Here, we demonstrated initial proof-of-concept for such an approach. To build a model of similarity between creativity-relevant constructs, we first surveyed creativity researchers. Next, we used NeuroSynth meta-analytic software to generate maps of neural activity robustly associated with tasks intended to measure the same set of creativity-relevant constructs. A representational similarity analysis-based approach identified particular constructs-and particular tasks intended to measure those constructs-that positively or negatively impacted the model fit. This approach points the way to identifying optimal sets of tasks to capture elements of creativity (i.e., dimensions of similarity space among creativity constructs), and has long-term potential to meaningfully advance the ontological development of creativity research with the rapid growth of creativity neuroscience. Because it relies on neuroimaging meta-analysis, this approach has more immediate potential to inform longer-established fields for which more extensive sets of neuroimaging data are already available.

Whether creativity is a domain-general or domain-specific ability has been a topic of intense speculation. Although previous studies have examined domain-specific mechanisms of creative performance, little is known about commonalities and distinctions in neural correlates across different domains. We applied activation likelihood estimation (ALE) meta-analysis to identify the brain activation of domain-mechanisms by synthesizing functional neuroimaging studies across three forms of artistic creativity: music improvisation, drawing, and literary creativity. ALE meta-analysis yielded a domain-general pattern across three artistic forms, with overlapping clusters in the presupplementary motor area (pre-SMA), left dorsolateral prefrontal cortex, and right inferior frontal gyrus (IFG). Regarding domain-specificity, musical creativity was associated with recruitment of the SMA-proper, bilateral IFG, left precentral gyrus, and left middle frontal gyrus (MFG) compared to the other two artistic forms; drawing creativity recruited the left fusiform gyrus, left precuneus, right parahippocampal gyrus, and right MFG compared to musical creativity; and literary creativity recruited the left angular gyrus and right lingual gyrus compared to musical creativity. Contrasting drawing and literary creativity revealed no significant differences in neural activation, suggesting that these domains may rely on a common neurocognitive system. Overall, these findings reveal a central, domain-general system for artistic creativity, but with each domain relying to some degree on domain-specific neural circuits.