Differences in brain activity patterns during creative idea generation between eminent and non-eminent thinkers

Creative connections: the neural correlates of semantic relatedness are associated with creativity

The associative theory of creativity proposes that creative ideas result from connecting remotely related concepts in memory. Previous research found that higher creative individuals exhibit a more flexible organization of semantic memory, generate more uncommon word associations, and judge remote concepts as more related. In this study (N = 93), we used fMRI to investigate brain regions involved in judging the relatedness of concepts that vary in their semantic distance, and how such neural involvement relates to individual differences in creativity. Brain regions where activity increased with semantic relatedness mainly overlapped with default, control, salience, semantic control, and multiple demand networks. The default and semantic control networks exhibited increased involvement when evaluating more remote associations. Finally, higher creative people, who provided higher relatedness judgements on average, exhibited lower activity in those regions, possibly reflecting higher neural efficiency. We discuss these findings in the context of the neurocognitive processing underlying creativity. Overall, our findings indicate that judging remote concepts as related reflects a cognitive mechanism underlying creativity and shed light on the neural correlates of this mechanism.

"Non-Eloquent" brain regions predict neuropsychological outcome in tumor patients undergoing awake craniotomy

Supratotal resection of primary brain tumors is being advocated especially when involving "non-eloquent" tissue. However, there is extensive neuropsychological data implicating functions critical to higher cognition in areas considered "non-eloquent" by most surgeons. The goal of the study was to determine pre-surgical brain regions that would be predictive of cognitive outcome at 4-6 months post-surgery. Cortical reconstruction and volumetric segmentation were performed with the FreeSurfer-v6.0 image analysis suite. Linear regression models were used to regress cortical volumes from both hemispheres, against the total cognitive z-score to determine the relationship between brain structure and broad cognitive functioning while controlling for age, sex, and total segmented brain volume. We identified 62 consecutive patients who underwent planned awake resections of primary (n = 55, 88%) and metastatic at the University of New Mexico Hospital between 2015 and 2019. Of those, 42 (23 males, 25 left hemispheric lesions) had complete pre and post-op neuropsychological data available and were included in this study. Overall, total neuropsychological functioning was somewhat worse (p = 0.09) at post-operative neuropsychological outcome (Mean = -.20) than at baseline (Mean = .00). Patients with radiation following resection (n = 32) performed marginally worse (p = .036). We found that several discrete brain volumes obtained pre-surgery predicted neuropsychological outcome post-resection. For the total sample, these volumes included: left fusiform, right lateral orbital frontal, right post central, and right paracentral regions. Regardless of lesion lateralization, volumes within the right frontal lobe, and specifically right orbitofrontal cortex, predicted neuropsychological difference scores. The current study highlights the gaps in our current understanding of brain eloquence. We hypothesize that the volume of tissue within the right lateral orbital frontal lobe represents important cognitive reserve capacity in patients undergoing tumor surgery. Our data also cautions the neurosurgeon when considering supratotal resections of tumors that do not extend into areas considered "non-eloquent" by current standards.

Creativity at rest: Exploring functional network connectivity of creative experts

The neuroscience of creativity seeks to disentangle the complex brain processes that underpin the generation of novel ideas. Neuroimaging studies of functional connectivity, particularly functional magnetic resonance imaging (fMRI), have revealed individual differences in brain network organization associated with creative ability; however, much of the extant research is limited to laboratory-based divergent thinking measures. To overcome these limitations, we compare functional brain connectivity in a cohort of creative experts (n = 27) and controls (n = 26) and examine links with creative behavior. First, we replicate prior findings showing reduced connectivity in visual cortex related to higher creative performance. Second, we examine whether this result is driven by integrated or segregated connectivity. Third, we examine associations between functional connectivity and vivid distal simulation separately in creative experts and controls. In accordance with past work, our results show reduced connectivity to the primary visual cortex in creative experts at rest. Additionally, we observe a negative association between distal simulation vividness and connectivity to the lateral visual cortex in creative experts. Taken together, these results highlight connectivity profiles of highly creative people and suggest that creative thinking may be related to, though not fully redundant with, the ability to vividly imagine the future.

Everyday Creativity is Associated with Increased Frontal Electroencephalography Alpha Activity During Creative Ideation

Everyday creativity is the basic ability of human survival and penetrates every aspect of life. Nevertheless, the neural mechanisms underlying everyday creativity was largely unexplored. In this study, seventy-five participants completed the creative behaviour inventory, a tool for assessing creative behaviour in daily life. The participants also completed the alternate uses task (AUT) during an electroencephalography (EEG) assessment to evaluate creative thinking. Alpha power was used to quantify neural oscillations during the creative process, while alpha coherence was used to quantify information communication between frontal regions and other sites during creative ideation. Moreover, these two task-related quantitative measures were combined to investigate the relationship between individual differences in everyday creativity and EEG alpha activity during creative idea generation. Compared with the reference period, increased alpha power was observed in the frontal cortex of the right hemisphere and increased functional coupling was observed between frontal and parietal/temporal regions during the activation period. Interestingly, individual differences in everyday creativity were associated with distinct patterns of EEG alpha activity. Specifically, individuals with higher everyday creativity had increased alpha power in the frontal cortex, and increased changes in coherence in frontal-temporal regions of the right hemisphere while performing the AUT. It might indicate that individuals with higher everyday creativity had an enhanced ability to focus on internal information processing and control bottom-up stimuli, as well as better selection of novel semantic information when performing creative ideation tasks.

The time course of creativity: multivariate classification of default and executive network contributions to creative cognition over time

Research indicates that creative cognition depends on both associative and controlled processes, corresponding to the brain's default mode network (DMN) and executive control network (ECN) networks. However, outstanding questions include how the DMN and ECN operate over time during creative task performance, and whether creative cognition involves distinct generative and evaluative stages. To address these questions, we used multivariate pattern analysis (MVPA) to assess how the DMN and ECN contribute to creative cognition over three successive time phases during the production of a single creative idea. Training classifiers to predict trial condition (creative vs non-creative), we used classification accuracy as a measure of the extent of creative activity in each brain network and time phase. Across both networks, classification accuracy was highest in early phases, decreased in mid phases, and increased again in later phases, following a U-shaped curve. Notably, classification accuracy was significantly greater in the ECN than the DMN during early phases, while differences between networks at later time phases were non-significant. We also computed correlations between classification accuracy and human-rated creative performance, to assess how relevant the creative activity in each network was to the creative quality of ideas. In line with expectations, classification accuracy in the DMN was most related to creative quality in early phases, decreasing in later phases, while classification accuracy in the ECN was least related to creative quality in early phases, increasing in later phases. Given the theorized roles of the DMN in generation and the ECN in evaluation, we interpret these results as tentative evidence for the existence of separate generative and evaluative stages in creative cognition that depend on distinct neural substrates.

Brain connectivity-based prediction of real-life creativity is mediated by semantic memory structure

Associative theories of creativity argue that creative cognition involves the abilities to generate remote associations and make useful connections between unrelated concepts in one's semantic memory. Yet, whether and how real-life creative behavior relies on semantic memory structure and its neural substrates remains unclear. We acquired multi-echo functional magnetic resonance imaging data while participants underwent a semantic relatedness judgment task. These ratings were used to estimate their individual semantic memory networks, whose properties significantly predicted their real-life creativity. Using a connectome predictive modeling approach, we identified patterns of task-based functional connectivity that predicted creativity-related semantic memory network properties. Furthermore, these properties mediated the relationship between functional connectivity and real-life creativity. These results provide new insights into how brain connectivity patterns support real-life creative behavior via the structure of semantic memory. We also show how computational network science can be used to couple behavioral, cognitive, and neural levels of analysis.