Semantic associative abilities and executive control functions predict novelty and appropriateness of idea generation.

Novelty and appropriateness are two fundamental components of creativity. However, the way in which novelty and appropriateness are separated at behavioral and neural levels remains poorly understood. In the present study, we aim to distinguish behavioral and neural bases of novelty and appropriateness of creative idea generation. In alignment with two established theories of creative thinking, which respectively, emphasize semantic association and executive control, behavioral results indicate that novelty relies more on associative abilities, while appropriateness relies more on executive functions. Next, employing a connectome predictive modeling (CPM) approach in resting-state fMRI data, we define two functional network-based models-dominated by interactions within the default network and by interactions within the limbic network-that respectively, predict novelty and appropriateness (i.e., cross-brain prediction). Furthermore, the generalizability and specificity of the two functional connectivity patterns are verified in additional resting-state fMRI and task fMRI. Finally, the two functional connectivity patterns, respectively mediate the relationship between semantic association/executive control and novelty/appropriateness. These findings provide global and predictive distinctions between novelty and appropriateness in creative idea generation.

The Mental Models Training App: Enhancing verbal reasoning through a cognitive training mobile application.

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.

Transfer from spatial education to verbal reasoning and prediction of transfer from learning-related neural change.

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. Longstanding 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.

Fine motor skills during early childhood predict visuospatial deductive reasoning in adolescence.

Extensive evidence and theory suggest that the development of motor skills during infancy and early childhood initiates a "developmental cascade" for cognitive abilities, such as reading and math. Motor skills are closely connected with the development of spatial cognition, an ability that supports deductive reasoning. Despite the linkage between motor skills and spatial cognition, and spatial cognition with deductive reasoning, no research has explored the developmental connection between early motor skills and reasoning ability, a plausible pathway through which the developmental cascade operates. Drawing data from the 1970 British Cohort Study (N = 1,233; 95% British, 5% other race/ethnicity; 54% male, 46% female; 7% low income, 80% middle income, 12% high income), this study investigated whether there was a relationship between gross and fine motor skills in infancy (22 months of age) and early childhood (42 months of age) and visuospatial deductive reasoning in adolescence (at 10 and 16 years of age). Results indicated that fine but not gross motor skills during early childhood positively predicted reasoning in adolescence. Critically, the fine motor-reasoning association mediated the previously observed link between early fine motor skills and adolescent reading and math ability. These results deepen our understanding of developmental cascade theory and mental model theory by identifying visuospatial reasoning (i.e., mental modeling) as a potential mechanism through which motor skills initiate cognitive development and academic success in reading and math. These findings also highlight the importance of early intervention programs targeting motor skills and illuminate the impact of those interventions on later cognitive and academic skills. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

What Makes Mental Modeling Difficult? Normative Data for the Multidimensional Relational Reasoning Task.

Relational reasoning is a complex form of human cognition involving the evaluation of relations between mental representations of information. Prior studies have modified stimulus properties of relational reasoning problems and examined differences in difficulty between different problem types. While subsets of these stimulus properties have been addressed in separate studies, there has not been a comprehensive study, to our knowledge, which investigates all of these properties in the same set of stimuli. This investigative gap has resulted in different findings across studies which vary in task design, making it challenging to determine what stimulus properties make relational reasoning-and the putative formation of mental models underlying reasoning-difficult. In this article, we present the Multidimensional Relational Reasoning Task (MRRT), a task which systematically varied an array of stimulus properties within a single set of relational reasoning problems. Using a mixed-effects framework, we demonstrate that reasoning problems containing a greater number of the premises as well as multidimensional relations led to greater task difficulty. The MRRT has been made publicly available for use in future research, along with normative data regarding the relative difficulty of each problem.

Functional Realignment of Frontoparietal Subnetworks during Divergent Creative Thinking.

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 coassignment 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.

Developing a neurally informed ontology of creativity measurement.

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.

Creativity anxiety: Evidence for anxiety that is specific to creative thinking, from STEM to the arts.

Creative thinking drives progress not only in the arts but also, and perhaps especially, in the fields of science, technology, engineering, and mathematics, and it is expected to become even more valuable than technical skill as artificial intelligence outpaces human cognition. Fostering creative thinkers has become a primary focus of educators. Educationally relevant anxieties, like math anxiety, have been shown to substantially impact specific forms of achievement and engagement, both in school and in career pursuits. Identifying these anxieties has led to promising interventions to enable affected individuals to reach their potential. Somewhat surprisingly, however, the possibility of anxiety specific to creative thinking is, to our knowledge, unexplored. In this article, across multiple samples, we tested the viability of creativity anxiety as a construct. We first created a new measure, the Creativity Anxiety Scale (CAS), demonstrating validity, internal reliability, and specificity. Applying the CAS revealed that creativity-specific anxiety predicted individual differences in creative achievement and attitudes toward creativity over and above effects of general anxiety. Moreover, across diverse content domains, from science to arts, anxiety was greater for situations that required creativity than similar situations that did not. Notably, this effect was especially pronounced in women. These findings suggest that creativity anxiety may have wide-reaching impacts and distinguish creativity anxiety from anxiety about noncreative aspects of performance. Establishing creativity anxiety as a novel construct, and the CAS as a valid measurement instrument, opens a new avenue of research that promises to deepen basic understanding of creative cognition and inform development of interventions to enable greater achievement of creative potential. (PsycINFO Database Record (c) 2019 APA, all rights reserved).