Women reliably perform worse than men on measures of spatial ability, particularly those involving mental rotation. At the same time, females also report higher levels of spatial anxiety than males. What remains unclear, however, is whether and in what ways gender differences in these cognitive and affective aspects of spatial processing may be interrelated. Here, we tested for robust gender differences across six different datasets in spatial ability and spatial anxiety (N = 1257, 830 females). Further, we tested for bidirectional mediation effects. We identified indirect relations between gender and spatial skills through spatial anxiety, as well as between gender and spatial anxiety through spatial skills. In the gender → spatial anxiety → spatial ability direction, spatial anxiety explained an average of 22.4% of gender differences in spatial ability. In the gender → spatial ability → spatial anxiety direction, spatial ability explained an average of 25.9% of gender differences in spatial anxiety. Broadly, these results support a strong relation between cognitive and affective factors when explaining gender differences in the spatial domain. However, the nature of this relation may be more complex than has been assumed in previous literature. On a practical level, the results of this study caution the development of interventions to address gender differences in spatial processing which focus primarily on either spatial anxiety or spatial ability until such further research can be conducted. Our results also speak to the need for future longitudinal work to determine the precise mechanisms linking cognitive and affective factors in spatial processing.

The standard definition of creativity as novel and useful describes creative products, but creativity is constituted by processes. This misalignment contributes to the oft-noted challenges of operationalizing creativity. Here, we distinguish creativity as a process from creativity as an attribute (i.e. creative-ness). Operating from a priori premises of creativity theory, we develop a process definition of creativity. Specifically, creativity is defined as internal attention constrained by a generative goal. This definition comprises three criteria: 1) attention is directed internally (toward mental representations); 2) attentional operations (e.g. search, manipulation) are constrained to fit parameters of a to-be-achieved goal state (whether or not a goal is actually achieved); and 3) the goal state is generative (not already precisely held in memory). We illustrate how these three definitional process elements align with insights yielded by creativity neuroscience, clarify ontological distinctions (e.g. from mind-wandering and retrieval), and relate the process definition to process-based models. The process definition provides minimal necessity and sufficiency criteria for whether a process should be considered creativity, but does not exclude the many other perceptual, emotional, etc. elements that can contribute to creativity processes. Researchers should specify whether they are studying creativity-as-process vs. creative-ness, and consider including process-focused assessments.

Identifying ways to enable people to reach their creative potential is a core goal of creativity research with implications for education and professional attainment. Recently, we identified a potential barrier to creative achievement: creativity anxiety (i.e., anxiety specific to creative thinking). Initial work found that creativity anxiety is associated with fewer real-world creative achievements. However, the more proximal impacts of creativity anxiety remain unexplored. In particular, understanding how to overcome creativity anxiety requires understanding how creativity anxiety may or may not impact creative cognitive performance, and how it may relate to state-level anxiety and effort while completing creative tasks. The present study sought to address this gap by measuring creativity anxiety alongside several measures of creative performance, while concurrently surveying state-level anxiety and effort. Results indicated that creativity anxiety was, indeed, predictive of poor creative performance, but only on some of the tasks included. We also found that creativity anxiety predicted both state anxiety and effort during creative performance. Interestingly, state anxiety and effort did not explain the associations between creativity anxiety and creative performance. Together, this work suggests that creativity anxiety can often be overcome in the performance of creative tasks, but likewise points to increased state anxiety and effort as factors that may make creative performance and achievement fragile in more demanding real-world contexts.

Introduction: Reasoning is a complex form of human cognition whose nature has long been debated. While a number of neurocognitive mechanisms for deductive reasoning have been offered, one of the most prominent accounts is Mental Model Theory (MMT). According to MMT, humans are able to manipulate and represent information for reasoning and problem solving by leveraging the brain's evolved visuospatial resources. Thus, when solving deductive reasoning problems, reasoners build mental models of the essential pieces of information conveyed in the premises, with their relations to each other represented spatially-even when the information contained within a reasoning problem is not intrinsically spatial. Crucially, taking a spatially-based approach, such as building mental models, supports higher accuracy on deductive reasoning problems. However, no study has empirically tested whether explicitly training this mental modeling ability leads to improved deductive reasoning performance.Method: Therefore, we designed the Mental Models Training App, a cognitive training mobile application which requires participants to complete increasingly difficult reasoning problems while using an external mental modeling tool. In this preregistered study (https://osf.io/4b7kn), we conducted a between-subjects experiment (N = 301) which compared the Mental Models Training App to 3 distinct control conditions in order to examine which specific components (if any) of the training were causally responsible for improved reasoning performance.Results: Results demonstrate that, when compared to a passive control condition, the Mental Models Training App led to improvements in adults' verbal deductive reasoning performance both during and after the training intervention. However, contrary to our preregistered hypotheses, the training-induced improvements were not significantly larger than the effects of the active control conditions- one which included adaptive practice of the reasoning problems, and one which included adaptive practice as well as a spatial alphabetization control task.Discussion: Therefore, while the present results demonstrate the ability of the Mental Models Training App to enhance verbal deductive reasoning, they do not support the hypothesis that directly training participants mental modeling ability yields improved performance beyond the effects of adaptive practice of reasoning. Future research should examine the long-term effects of repeated usage of the Mental Models Training App, as well as transfer effects to other forms of reasoning. Finally, we present the Mental Models Training App as a free mobile application available on the Apple App store (https://apps.apple.com/us/ app/mental-models-training/id1664939931), in the hope that this translational research may be utilized by the general public to improve their reasoning ability.

Implicit learning refers to learning without conscious awareness of the content acquired. Theoretical frameworks of human cognition suggest that intuitions develop based on incomplete perceptions of regularity during implicit learning and, in turn, lead to the development of more explicit, consciously-accessible knowledge. Surprisingly, however, this putative information processing pathway (i.e., implicit learning. intuition. explicit knowledge) has yet to be empirically demonstrated. The present study investigated the relationship between implicit learning, intuitions, and explicit knowledge using a modified Serial Reaction Time Task. Results indicate that intuitions of implicitly-learned patterns emerge prior to the development of explicit knowledge. Moreover, intuition timing and accuracy were significantly associated with accuracy of explicit reports. We did not, however, find that stronger implicit learners developed more accurate intuitions. Our findings suggest a crucial role of intuition in the formation of explicit knowledge from implicit learning.

Analogy is a central component of human cognition. Analogical mapping of similarities between pieces of information present in our experiences supports cognitive and social development, classroom learning, and creative insights and innovation. To date, analogical mapping has primarily been studied within separate modalities of information (e.g., verbal analogies between words, visuo-spatial analogies between objects). However, human experience, in development and adulthood, includes highly variegated information (e.g., words, sounds, objects) received via multiple sensory and information-processing pathways (e.g., visual vs. auditory pathways). Whereas cross-modal correspondences (e.g., between pitch and height) have been observed, the correspondences were between individual items, rather than between relations. Thus, analogical mapping (characterized by second-order relations between relations) has not been directly tested as a basis for cross-modal correspondence. Here, we devised novel cross-modality analogical stimuli (lines-to-sounds, lines-to-words, words-to-sounds) that explicated second-order comparisons between relations. In four samples across three studies-participants demonstrated well-above-chance identification of cross-modal second-order relations, providing robust evidence of analogy across modalities. Further, performance across all analogy types was explained by a single factor, indicating a modality-general analogical ability (i.e., an analo-g factor). Analo-g explained performance overand-above fluid intelligence as well as verbal and spatial abilities, though a stronger relationship to verbal than visuo-spatial ability emerged, consistent with verbal/semantic contributions to analogy. The present data suggests novel questions about our ability to find/learn second-order relations among the diverse information sources that populate human experience, and about cross-modal human and AI analogical mapping in developmental, educational, and creative contexts.

Current debate surrounds the promise of neuroscience for education, including whether learning-related neural changes can predict learning transfer better than traditional performance-based learning assessments. Long-standing debate in philosophy and psychology concerns the proposition that spatial processes underlie seemingly nonspatial/verbal reasoning (mental model theory). If so, education that fosters spatial cognition might improve verbal reasoning. Here, in a quasi-experimental design in real-world STEM classrooms, a curriculum devised to foster spatial cognition yielded transfer to improved verbal reasoning. Further indicating a spatial basis for verbal transfer, students' spatial cognition gains predicted and mediated their reasoning improvement. Longitudinal fMRI detected learning-related changes in neural activity, connectivity, and representational similarity in spatial cognition-implicated regions. Neural changes predicted and mediated learning transfer. Ensemble modeling demonstrated better prediction of transfer from neural change than from traditional measures (tests and grades). Results support in-school spatial education and suggest that neural change can inform future development of transferable curricula.

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 cognition has been consistently associated with functional connectivity between frontoparietal control and default networks. However, recent research identified distinct connectivity dynamics for subnetworks within the larger frontoparietal system-one subnetwork (FPCNa) shows positive coupling with the default network and another subnetwork (FPCNb) shows negative default coupling-raising questions about how these networks interact during creative cognition. Here we examine frontoparietal subnetwork functional connectivity in a large sample of participants (n=171) who completed a divergent creative thinking task and a resting-state scan during fMRI. We replicated recent findings on functional connectivity of frontoparietal subnetworks at rest: FPCNa positively correlated with the default network and FPCNb negatively correlated with the default network. Critically, we found that divergent thinking evoked functional connectivity between both frontoparietal subnetworks and the default network, but in different ways. Using community detection, we found that FPCNa regions showed greater co-assignment to a default network community. However, FPCNb showed overall stronger functional connectivity with the default network-reflecting a reversal of negative connectivity at rest-and the strength of FPCNb-default network connectivity correlated with individual creative ability. These findings provide novel evidence of a behavioral benefit to the cooperation of typically anticorrelated brain networks.