Default mode network electrophysiological dynamics and causal role in creative thinking.

The default mode network (DMN) is a widely distributed, intrinsic brain network thought to play a crucial role in internally-directed cognition. The present study employs stereo-electroencephalography in 13 human patients, obtaining high resolution neural recordings across multiple canonical DMN regions during two processes that have been associated with creative thinking: spontaneous and divergent thought. We probe these two DMN-associated higher cognitive functions through mind wandering and alternate uses tasks, respectively. Our results reveal DMN recruitment during both tasks, as well as a task-specific dissociation in spatiotemporal response dynamics. When compared to the fronto-parietal network, DMN activity was characterized by a stronger increase in gamma band power (30-70 Hz) coupled with lower theta band power (4-8 Hz). The difference in activity between the two networks was especially strong during the mind wandering task. Within the DMN, we found that the tasks showed different dynamics, with the alternate uses task engaging the DMN more during the initial stage of the task, and mind wandering in the later stage. Gamma power changes were mainly driven by lateral DMN sites, while theta power displayed task-specific effects. During alternate uses task, theta changes did not show spatial differences within the DMN, while mind wandering was associated to an early lateral and late dorsomedial DMN engagement. Furthermore, causal manipulations of DMN regions using direct cortical stimulation preferentially decreased the originality of responses in the alternative uses task, without affecting fluency or mind wandering. Our results suggest that DMN activity is flexibly modulated as a function of specific cognitive processes and supports its causal role in divergent thinking. These findings shed light on the neural constructs supporting different forms of cognition and provide causal evidence for the role of DMN in the generation of original connections among concepts.

Recognizing ideas generated in a creative task: the roles of the hippocampus and medial prefrontal cortex in facilitating self-generated learning.

Creative idea generation plays an important role in promoting successful memory formation. Yet, its underlying neural correlates remain unclear. We investigated the self-generated learning of creative ideas motivated by the schema-linked interactions between medial prefrontal and medial temporal regions framework. This was achieved by having participants generate ideas in the alternative uses task, self-evaluating their ideas based on novelty and source (i.e. new or old), and then later being tested on the recognition performance of the generated ideas. At the behavioral level, our results indicated superior performances in discriminating novel ideas, highlighting the novelty effect on memory. At the neural level, the regions-of-interest analyses revealed that successful recognition of novel ideas was associated with greater activations in the hippocampus (HPC) and medial prefrontal cortex (mPFC) during ideation. However, only activation in the right HPC was positively related to the successful recognition of novel ideas. Importantly, the weaker the connection between the right HPC and left mPFC, the higher the recognition accuracy of novel ideas. Moreover, activations in the right HPC and left mPFC were both effective predictors of successful recognition of novel ideas. These findings uniquely highlight the role of novelty in promoting self-generated learning of creative ideas.

The role of alpha oscillations in free- and goal-directed semantic associations.

Alpha oscillations are known to play a central role in several higher-order cognitive functions, especially selective attention, working memory, semantic memory, and creative thinking. Nonetheless, we still know very little about the role of alpha in the generation of more remote semantic associations, which is key to creative and semantic cognition. Furthermore, it remains unclear how these oscillations are shaped by the intention to "be creative," which is the case in most creativity tasks. We aimed to address these gaps in two experiments. In Experiment 1, we compared alpha oscillatory activity (using a method which distinguishes genuine oscillatory activity from transient events) during the generation of free associations which were more vs. less distant from a given concept. In Experiment 2, we replicated these findings and also compared alpha oscillatory activity when people were generating free associations versus associations with the instruction to be creative (i.e. goal-directed). We found that alpha was consistently higher during the generation of more distant semantic associations, in both experiments. This effect was widespread, involving areas in both left and right hemispheres. Importantly, the instruction to be creative seems to increase alpha phase synchronisation from left to right temporal brain areas, suggesting that intention to be creative changed the flux of information in the brain, likely reflecting an increase in top-down control of semantic search processes. We conclude that goal-directed generation of remote associations relies on top-down mechanisms compared to when associations are freely generated.

Question-asking as a mechanism of information seeking.

Ivancovsky et al. explore the relationship between curiosity and creativity, by suggesting they align through novelty-seeking mechanisms. We argue that a general mechanism linking both capacities together is question-asking: Curiosity drives question-asking that leads to creative problem solving. Yet, current findings from our lab suggest that question complexity relates to creativity, but not necessarily to curiosity, warranting further investigation.

Noninvasive brain stimulation to lateral prefrontal cortex alters the novelty of creative idea generation.

Theories of the processes involved in creative cognition posit that cognitive control has a negative effect on creative idea generation but a positive effect on creative idea evaluation. Brain stimulation research has started to examine empirically the effects of cognitive control, with several reports of decreased cognitive control facilitating creative ideation. Such studies have shown how decreased cognitive control mechanisms facilitate creative idea generation, potentially by allowing participants access to less inhibited weaker-related associations, thereby increasing novelty. In the current study, we advance this line of work by investigating how cognitive control affects creative thinking, potentially inhibiting or facilitating novel idea generation based on task demands. Participants read sentences with the final word missing and were instructed to complete the sentence with an uncommon (but appropriate) ending. Participants performed this task while undergoing either anodal (excitatory), cathodal (inhibitory), or sham (control) transcranial direct current stimulation over their left prefrontal cortex. These responses were then rated for their novelty and appropriateness by an independent sample of raters. We found that anodal stimulation increased the appropriateness and decreased the novelty of participants' responses. Contrary to previous studies, we did not find that cathodal stimulation increased the novelty of participants' responses, which may be due to the nature of our task. Overall, we demonstrate how cognitive control mechanisms may inhibit novel idea generation.

Flexibility of thought in high creative individuals represented by percolation analysis.

Flexibility of thought is theorized to play a critical role in the ability of high creative individuals to generate novel and innovative ideas. However, this has been examined only through indirect behavioral measures. Here we use network percolation analysis (removal of links in a network whose strength is below an increasing threshold) to computationally examine the robustness of the semantic memory networks of low and high creative individuals. Robustness of a network indicates its flexibility and thus can be used to quantify flexibility of thought as related to creativity. This is based on the assumption that the higher the robustness of the semantic network, the higher its flexibility. Our analysis reveals that the semantic network of high creative individuals is more robust to network percolation compared with the network of low creative individuals and that this higher robustness is related to differences in the structure of the networks. Specifically, we find that this higher robustness is related to stronger links connecting between different components of similar semantic words in the network, which may also help to facilitate spread of activation over their network. Thus, we directly and quantitatively examine the relation between flexibility of thought and creative ability. Our findings support the associative theory of creativity, which posits that high creative ability is related to a flexible structure of semantic memory. Finally, this approach may have further implications, by enabling a quantitative examination of flexibility of thought, in both healthy and clinical populations.

Robust prediction of individual creative ability from brain functional connectivity.

People's ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis-connectome-based predictive modeling-to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences (r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems-intrinsic functional networks that tend to work in opposition-suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks.

The role of the motor system in generating creative thoughts.

Neurocognitive research is pertinent to developing mechanistic models of how humans generate creative thoughts. Such models usually overlook the role of the motor cortex in creative thinking. The framework of embodied or grounded cognition suggests that creative thoughts (e.g. using a shoe as a hammer, improvising a piano solo) are partially served by simulations of motor activity associated with tools and their use. The major hypothesis stemming from the embodied or grounded account is that, while the motor system is used to execute actions, simulations within this system also support higher-order cognition, creativity included. That is, the cognitive process of generating creative output, not just executing it, is deeply embedded in motor processes. Here, we highlight a collection of neuroimaging research that implicates the motor system in generating creative thoughts, including some evidence for its functionally necessary role in generating creative output. Specifically, the grounded or embodied framework suggests that generating creative output may, in part, rely on motor simulations of possible actions, and that these simulations may by partially implemented in the motor regions themselves. In such cases, action simulations (i.e. reactivating or re-using the motor system), do not result in overt action but instead are used to support higher-order cognitive goals like generating creative uses or improvising.

The effect of semantic memory degeneration on creative thinking: A voxel-based morphometry analysis.

Increasing attention is being directed towards explicating the neurocognitive mechanisms of divergent thinking. While neuroimaging studies have tended to dominate the contemporary creativity literature, lesion studies provide important converging evidence by revealing the regions that are not only implicated in, but essential for, task performance. Here we explored the capacity for divergent thinking in semantic dementia (SD), a neurodegenerative disorder characterised by the progressive degeneration of the conceptual knowledge base. The performance of 10 SD patients on a divergent thinking task was contrasted with that of 15 patients with the behavioural variant of frontotemporal dementia (bvFTD) and 20 healthy control participants. In addition, all participants underwent neuropsychological testing and structural MRI. Relative to controls, both patient groups generated significantly fewer responses on the divergent thinking task, with disproportionate impairment in the SD group. Further, the responses generated by patient groups were less original and reflected less flexible thinking when compared with controls. For SD patients, fluency of responses correlated with performance on a measure of semantic association, and originality of responses correlated with semantic naming and comprehension ability. In bvFTD, originality of ideas correlated with letter fluency and response inhibition. Voxel-based morphometry analyses revealed two grey matter clusters consistently associated with diminished Fluency of ideas, namely a left medial temporal lobe cluster centred on the left anterior hippocampus, and a left middle frontal gyrus cluster. Our study highlights the importance of distinct temporal and prefrontal contributions to divergent thinking via a lesion approach, and underscores the pivotal role of semantic processes in creative cognition.

Community structure of the creative brain at rest.

Recent studies have provided insight into inter-individual differences in creative thinking, focusing on characterizations of distributed large-scale brain networks both at the local level of regions and their pairwise interactions and at the global level of the brain as a whole. However, it remains unclear how creative thinking relates to mesoscale network features, e.g. community and hub organization. We applied a data-driven approach to examine community and hub structure in resting-state functional imaging data from a large sample of participants, and how they relate to individual differences in creative thinking. First, we computed for every participant the co-assignment probability of brain regions to the same community. We found that greater capacity for creative thinking was related to increased and decreased co-assignment of medial-temporal and subcortical regions to the same community, respectively, suggesting that creative capacity may be reflected in inter-individual differences in the meso-scale organization of brain networks. We then used participant-specific communities to identify network hubs-nodes whose connections form bridges across the boundaries of different communities-quantified based on their participation coefficients. We found that increased hubness of DMN and medial-temporal regions were positively and negatively related with creative ability, respectively. These findings suggest that creative capacity may be reflected in inter-individual differences in community interactions of DMN and medial-temporal structures. Collectively, these results demonstrate the fruitfulness of investigating mesoscale brain network features in relation to creative thinking.

Context matters: Novel metaphors in supportive and non-supportive contexts.

Creative language is defined as linguistic output that is both novel and appropriate. Metaphors are one such example of creative language in which one concept is used to express another by highlighting relevant semantic features. While novelty is an inherent property of unfamiliar metaphors, appropriateness depends on the context. The current study tests the hypothesis that the context in which metaphors are encountered affects their processing. We examined the neural effects of comprehending metaphors in context by comparing neural activations in response to novel metaphors and literal sentences that were either embedded in a meaningful narrative or in matched jabberwocky contexts. We found that the neural correlates of processing metaphoric sentences and their literal counterparts are indistinguishable when embedded in a narrative: both conditions activate bilateral areas along the anterior temporal poles, middle temporal gyri, superior temporal sulci, and the angular gyri. Metaphors embedded in a narrative as compared to their identical counterparts embedded in jabberwocky show increased responses in sensorimotor areas that correspond to the modality of the literal meaning of the target word, perhaps reflecting deeper semantic processing. Our results confirm that context affects neural mechanisms for understanding creative ideas.

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.

Default network contributions to episodic and semantic processing during divergent creative thinking: A representational similarity analysis.

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.

Network structure of the Wisconsin Schizotypy Scales-Short Forms: Examining psychometric network filtering approaches.

Schizotypy is a multidimensional construct that provides a useful framework for understanding the etiology, development, and risk for schizophrenia-spectrum disorders. Past research has applied traditional methods, such as factor analysis, to uncovering common dimensions of schizotypy. In the present study, we aimed to advance the construct of schizotypy, measured by the Wisconsin Schizotypy Scales-Short Forms (WSS-SF), beyond this general scope by applying two different psychometric network filtering approaches-the state-of-the-art approach (lasso), which has been employed in previous studies, and an alternative approach (information-filtering networks; IFNs). First, we applied both filtering approaches to two large, independent samples of WSS-SF data (ns = 5,831 and 2,171) and assessed each approach's representation of the WSS-SF's schizotypy construct. Both filtering approaches produced results similar to those from traditional methods, with the IFN approach producing results more consistent with previous theoretical interpretations of schizotypy. Then we evaluated how well both filtering approaches reproduced the global and local network characteristics of the two samples. We found that the IFN approach produced more consistent results for both global and local network characteristics. Finally, we sought to evaluate the predictability of the network centrality measures for each filtering approach, by determining the core, intermediate, and peripheral items on the WSS-SF and using them to predict interview reports of schizophrenia-spectrum symptoms. We found some similarities and differences in their effectiveness, with the IFN approach's network structure providing better overall predictive distinctions. We discuss the implications of our findings for schizotypy and for psychometric network analysis more generally.

Personality and complex brain networks: The role of openness to experience in default network efficiency.

The brain's default network (DN) has been a topic of considerable empirical interest. In fMRI research, DN activity is associated with spontaneous and self-generated cognition, such as mind-wandering, episodic memory retrieval, future thinking, mental simulation, theory of mind reasoning, and creative cognition. Despite large literatures on developmental and disease-related influences on the DN, surprisingly little is known about the factors that impact normal variation in DN functioning. Using structural equation modeling and graph theoretical analysis of resting-state fMRI data, we provide evidence that Openness to Experience-a normally distributed personality trait reflecting a tendency to engage in imaginative, creative, and abstract cognitive processes-underlies efficiency of information processing within the DN. Across two studies, Openness predicted the global efficiency of a functional network comprised of DN nodes and corresponding edges. In Study 2, Openness remained a robust predictor-even after controlling for intelligence, age, gender, and other personality variables-explaining 18% of the variance in DN functioning. These findings point to a biological basis of Openness to Experience, and suggest that normally distributed personality traits affect the intrinsic architecture of large-scale brain systems. Hum Brain Mapp 37:773-779, 2016. © 2015 Wiley Periodicals, Inc.

The Hyper-Modular Associative Mind: A Computational Analysis of Associative Responses of Persons with Asperger Syndrome.

Rigidity of thought is considered a main characteristic of persons with Asperger syndrome (AS). This rigidity may explain the poor comprehension of unusual semantic relations, frequently exhibited by persons with AS. Research indicates that such deficiency is related to altered mental lexicon organization, but has never been directly examined. The present study used computational network science tools to compare the mental lexicon structure of persons with AS and matched controls. Persons with AS and matched controls generated free associations, and network tools were used to extract and compare the mental lexicon structure of the two groups. The analysis revealed that persons with AS exhibit a hyper-modular semantic organization: their mental lexicon is more compartmentalized compared to matched controls. We argue that this hyper-modularity may be related to the rigidity of thought which characterizes persons with AS and discuss the clinical and more general cognitive implications of our findings.

Enhanced creative thinking under dopaminergic therapy in Parkinson disease.

OBJECTIVE: Creative thinking requires a combination of originality, flexibility, and usefulness. Several reports described enhanced artistic creativity in Parkinson disease (PD) patients treated with dopaminergic agents. We aimed to examine PD patients' ability to perform creativity tasks compared to healthy controls and to verify whether creativity is related to an impulse control disorder (ICD) as a complication of dopaminergic therapy. METHODS: Right-handed PD patients treated with dopamine agonists and/or levodopa, and age- and education- matched neurologically healthy controls were assessed using the Montreal Cognitive Assessment, semantic verbal fluency, Beck Depression Inventory, and Questionnaire for Impulsive-Compulsive Disorders in Parkinson Disease Rating Scale (QUIP-RS). Creativity assessment included Comprehension of Novel Metaphors (CNM), Remote Association Test, and Tel Aviv Creativity Test (TACT). Groups were compared using analyses of variance, t tests, and correlation analyses. RESULTS: Twenty-seven PD patients (age, mean ± standard deviation = 62 ± 7 years; education = 16 ± 3 years; disease duration = 5.8 ± 3.9 years) and 27 controls (age = 59 ± 9 years; education 17 ± 3 years) participated. PD patients performed significantly better than controls in divergent thinking tasks; specifically, the TACT-Visual for both fluency (33.48 ± 11.83 vs 25.59 ± 10.27, p = 0.034) and quality (15.78 ± 7.6 vs 11.19 ± 6.22, p = 0.025). Comprehension of Novel Metaphors was better in PD patients vs controls (0.71 ± 0.23 vs 0.55 ± 0.29, p = 0.04). QUIP-RS scores did not correlate with creativity measures. INTERPRETATION: PD patients treated with dopaminergic drugs demonstrated enhanced verbal and visual creativity as compared to neurologically healthy controls. This feature was unrelated to ICD. Dopaminergic agents might act through the reduction of latent inhibition, resulting in widening of the associative network and enriched divergent thinking.

Mapping the Memory Structure of High-Knowledge Students: A Longitudinal Semantic Network Analysis.

Standard learning assessments like multiple-choice questions measure what students know but not how their knowledge is organized. Recent advances in cognitive network science provide quantitative tools for modeling the structure of semantic memory, revealing key learning mechanisms. In two studies, we examined the semantic memory networks of undergraduate students enrolled in an introductory psychology course. In Study 1, we administered a cumulative multiple-choice test of psychology knowledge, the Intro Psych Test, at the end of the course. To estimate semantic memory networks, we administered two verbal fluency tasks: domain-specific fluency (naming psychology concepts) and domain-general fluency (naming animals). Based on their performance on the Intro Psych Test, we categorized students into a high-knowledge or low-knowledge group, and compared their semantic memory networks. Study 1 (N = 213) found that the high-knowledge group had semantic memory networks that were more clustered, with shorter distances between concepts-across both the domain-specific (psychology) and domain-general (animal) categories-compared to the low-knowledge group. In Study 2 (N = 145), we replicated and extended these findings in a longitudinal study, collecting data near the start and end of the semester. In addition to replicating Study 1, we found the semantic memory networks of high-knowledge students became more interconnected over time, across both domain-general and domain-specific categories. These findings suggest that successful learners show a distinct semantic memory organization-characterized by high connectivity and short path distances between concepts-highlighting the utility of cognitive network science for studying variation in student learning.

Cognitive modelling of concepts in the mental lexicon with multilayer networks: Insights, advancements, and future challenges.

The mental lexicon is a complex cognitive system representing information about the words/concepts that one knows. Over decades psychological experiments have shown that conceptual associations across multiple, interactive cognitive levels can greatly influence word acquisition, storage, and processing. How can semantic, phonological, syntactic, and other types of conceptual associations be mapped within a coherent mathematical framework to study how the mental lexicon works? Here we review cognitive multilayer networks as a promising quantitative and interpretative framework for investigating the mental lexicon. Cognitive multilayer networks can map multiple types of information at once, thus capturing how different layers of associations might co-exist within the mental lexicon and influence cognitive processing. This review starts with a gentle introduction to the structure and formalism of multilayer networks. We then discuss quantitative mechanisms of psychological phenomena that could not be observed in single-layer networks and were only unveiled by combining multiple layers of the lexicon: (i) multiplex viability highlights language kernels and facilitative effects of knowledge processing in healthy and clinical populations; (ii) multilayer community detection enables contextual meaning reconstruction depending on psycholinguistic features; (iii) layer analysis can mediate latent interactions of mediation, suppression, and facilitation for lexical access. By outlining novel quantitative perspectives where multilayer networks can shed light on cognitive knowledge representations, including in next-generation brain/mind models, we discuss key limitations and promising directions for cutting-edge future research.