Robust prediction of individual creative ability from brain functional connectivity

Multivariate approaches improve the reliability and validity of functional connectivity and prediction of individual behaviors

Brain functional connectivity features can predict cognition and behavior at the level of the individual. Most studies measure univariate signals, correlating timecourses from the average of constituent voxels in each node. While straightforward, this approach overlooks the spatial patterns of voxel-wise signals within individual nodes. Given that multivariate spatial activity patterns across voxels can improve fMRI measures of mental representations, here we asked whether using voxel-wise timecourses can better characterize region-by-region interactions relative to univariate approaches. Using two fMRI datasets, the Human Connectome Project sample and a local test-retest sample, we measured multivariate functional connectivity with multivariate distance correlation and univariate connectivity with Pearson's correlation. We compared multivariate and univariate connectivity estimates, demonstrating that relative to univariate estimates, multivariate estimates exhibited higher reliability at both the edge-level and connectome-level, stronger prediction of individual differences, and greater sensitivity to brain states within individuals. Our findings suggest that multivariate estimates reliably provide more powerful information about an individual's functional brain organization and its relation to cognitive skills.

Brain hemispheric involvement in visuospatial and verbal divergent thinking

Hemispheric lateralization for creative thinking remains a controversial topic. Early behavioral and neuroimaging research supported right hemisphere dominance in creative thinking, but more recent evidence suggests the left hemisphere plays an equally important role. In addition, the extent to which hemispheric lateralization in specific brain regions relates to individual creative ability, and whether hemispheric dominance relates to distinct task performance, remain poorly understood. Here, using multivariate predictive modeling of resting-state functional MRI data in a large sample of adults (N = 502), we estimated hemispheric segregation and integration for each brain region and investigated these lateralization indices with respect to individual differences in visuospatial and verbal divergent thinking. Our analyses revealed that individual visuospatial divergent thinking performance could be predicted by right-hemispheric segregation within the visual network, sensorimotor network, and some regions within the default mode network. High visuospatial divergent thinking was related to stronger functional connectivity between the visual network, fronto-parietal network, and default mode network within the right hemisphere. In contrast, high verbal divergent thinking performance could be predicted by inter-hemispheric balance within regions mainly involved in complex semantic processing (e.g., lateral temporal cortex and inferior frontal gyrus) and cognitive control processing (e.g., inferior frontal gyrus, middle frontal cortex, and superior parietal lobule). The current study suggests that two distinct forms of functional lateralization support individual differences in visuospatial and verbal divergent thinking. These findings have important implications for our understanding of hemispheric interaction mechanisms of creative thinking.

Predicting human inhibitory control from brain structural MRI

The anatomical structure of the human brain varies widely, as does individual cognitive behavior. It is important and interesting to study the relationship between brain structure and cognitive behavior. There has however been little previous work on the relationship between inhibitory control and brain structure. The goal of this study was to elucidate possible cortical markers related to inhibitory control using structural magnetic resonance imaging (sMRI) data. In this study, we analyzed sMRI data and inhibitory control behavior measurement values from 361 healthy adults from the Human Connectome Project (HCP). The data of all participants were divided into two datasets. In the first dataset, we first constructed individual brain morphometric similarity networks by calculating the inter-regional statistical similarity relationship of nine cortical characteristic measures (such as volume) for each brain area obtained from sMRI data. Areas that covary in their morphology are termed 'connected'. After that, we used a brain connectome-based predictive model (CPM) to search for 'connected' brain areas that were significantly related to inhibitory control. This is a purely data-driven method with built-in cross-validation. Two different 'connected' patterns were observed for high and low inhibitory control networks. The high inhibitory control network comprised 25 'connections' (edges between nodes), mostly involving nodes in the prefrontal and especially orbitofrontal cortex and inferior frontal gyrus. In the low inhibitory control network, nodes were scattered between parietal, occipital and limbic areas. Furthermore, these 'connections' were verified as reliable and generalizable in a cross-validation dataset. Two regions of interest, the right ventromedial prefrontal cortex including a part of medial area 10 (R.OFCmed) and left middle temporal gyrus (L.MTG) were crucial nodes in the two networks, respectively, which suggests that these two regions may be fundamentally involved in inhibitory control. Our findings potentially help to understand the relationship between areas with a correlated cortical structure and inhibitory control, and further help to reveal the brain systems related to inhibition and its disorders.

Identifying inter-individual differences in pain threshold using brain connectome: a test-retest reproducible study

Individuals are unique in terms of brain and behavior. Some are very sensitive to pain, while others have a high tolerance. However, how inter-individual intrinsic differences in the brain are related to pain is unknown. Here, we performed longitudinal test-retest analyses to investigate pain threshold variability among individuals using a resting-state fMRI brain connectome. Twenty-four healthy subjects who received four MRI sessions separated by at least 7 days were included in the data analysis. Subjects' pain thresholds were measured using two modalities of experimental pain (heat and pressure) on two different locations (heat pain: leg and arm; pressure pain: leg and thumbnail). Behavioral results showed strong inter-individual variability and strong within-individual stability in pain threshold. Resting state fMRI data analyses showed that functional connectivity profiles can accurately identify subjects across four sessions, indicating that an individual's connectivity profile may be intrinsic and unique. By using multivariate pattern analyses, we found that connectivity profiles could be used to predict an individual's pain threshold at both within-session and between-session levels, with the most predictive contribution from medial-frontal and frontal-parietal networks. These results demonstrate the potential of using a resting-state fMRI brain connectome to build a 'neural trait' for characterizing an individual's pain-related behavior, and such a 'neural trait' may eventually be used to personalize clinical assessments.

Reconstruction of behavior-relevant individual brain activity: an individualized fMRI study

Different patterns of brain activity are observed in various subjects across a wide functional domain. However, these individual differences, which are often neglected through the group average, are not yet completely understood. Based on the fundamental assumption that human behavior is rooted in the underlying brain function, we speculated that the individual differences in brain activity are reflected in the individual differences in behavior. Adopting 98 behavioral measures and assessing the brain activity induced at seven task functional magnetic resonance imaging states, we demonstrated that the individual differences in brain activity can be used to predict behavioral measures of individual subjects with high accuracy using the partial least square regression model. In addition, we revealed that behavior-relevant individual differences in brain activity transferred between different task states and can be used to reconstruct individual brain activity. Reconstructed individual brain activity retained certain individual differences which were lost in the group average and could serve as an individual functional localizer. Therefore, our results suggest that the individual differences in brain activity contain behavior-relevant information and should be included in group averaging. Moreover, reconstructed individual brain activity shows a potential use in precise and personalized medicine.

The creative thinking cognitive process influenced by acute stress in humans: an electroencephalography study

This study examined the underlying neural mechanism of acute stress affecting creative thinking. Twenty-six male participants underwent the Alternative Uses Test before and after acute stress test (Montreal Imaging Stress Task). Compared to before stress, stressed participants responded with higher salivary cortisol and salivary alpha-amylase. The electroencephalogram results indicated a general decrease in upper-frequency alpha power after stress, compared with that of before stress. The decrease in upper-frequency alpha power observed in the first stage after exposure to stress was related to memory and attention. Additionally, stress also reduced the differences between individuals with different creative abilities. In summary, these findings indicated that acute stress impaired creative thinking and primarily affected the earlier phase of the process of creative cognition. This study provides some practical implications for educational practice and corporate innovation in that a more relaxed environment promotes creative output. Lay Summary Acute stress impaired creative thinking performance and mainly affects the earlier phase of the process of creative cognition. Additionally, stress seems to reduce the differences between individuals with different creative abilities.

The Ubiquity of Cross-Domain Thinking in the Early Phase of the Creative Process

To what extent are creative processes in one domain (e.g., technology) affected by information from other domains (e.g., music)? While some studies of professional creators suggest that creative abilities are domain-specific, other studies suggest that creative avocations stimulate creativity. The latter is consistent with the predictions of the honing theory of creativity, according to which the iterative process culminating in a creative work is made possible by the self-organizing nature of a conceptual network, or worldview, and its innate holistic tendency to minimize inconsistency. As such, the creative process is not restricted to the creative domain; influences from domains other than that of the final product are predicted to impact the creative process and its outcome. To assess the prevalence of cross-domain influences on creativity we conducted two studies: one with creative experts, and one with undergraduate students from diverse academic backgrounds. Participants listed both their creative outputs, and the influences (sources of inspiration) associated with each of these outputs. In both studies, cross-domain influences on creativity were found to be widespread, and indeed more frequent than within-domain sources of inspiration. Thus, examination of the inputs to, rather than the outputs of, creative tasks supported the prediction of honing theory that cross-domain influences are a ubiquitous component of the creative process.

A Manifold Regularized Multi-Task Learning Model for IQ Prediction From Two fMRI Paradigms

OBJECTIVE

Multi-modal brain functional connectivity (FC) data have shown great potential for providing insights into individual variations in behavioral and cognitive traits. The joint learning of multi-modal data can utilize intrinsic association, and thus can boost learning performance. Although several multi-task based learning models have already been proposed by viewing feature learning on each modality as one task, most of them ignore the structural information inherent across the modalities, which may play an important role in extracting discriminative features.

METHODS

In this paper, we propose a new manifold regularized multi-task learning model by simultaneously considering between-subject and between-modality relationships. Specifically, the l_2,1-norm (i.e., group-sparsity) regularizer is enforced to jointly select a few common features across different modalities. A novelly designed manifold regularizer is further imposed as a crucial underpinning to preserve the structural information both within and between modalities. Such designed regularizers will make our model more adaptive to realistic neuroimaging data, which are usually of small sample size but high dimensional features.

RESULTS

Our model is validated on the Philadelphia Neurodevelopmental Cohort dataset, where our modalities are regarded as two types of functional MRI (fMRI) data collected under two paradigms. We conduct experimental studies on fMRI-based FC network data in two task conditions for intelligence quotient (IQ) prediction. The results show that our proposed model can not only achieve improved prediction performance, but also yield a set of IQ-relevant biomarkers.

CONCLUSION AND SIGNIFICANCE

This paper develops a new multi-task learning model, enabling the discovery of significant biomarkers that may account for a proportion of the variance in human intelligence.

Microstructural and functional gradients are increasingly dissociated in transmodal cortices

While the role of cortical microstructure in organising neural function is well established, it remains unclear how structural constraints can give rise to more flexible elements of cognition. While nonhuman primate research has demonstrated a close structure-function correspondence, the relationship between microstructure and function remains poorly understood in humans, in part because of the reliance on post mortem analyses, which cannot be directly related to functional data. To overcome this barrier, we developed a novel approach to model the similarity of microstructural profiles sampled in the direction of cortical columns. Our approach was initially formulated based on an ultra-high-resolution 3D histological reconstruction of an entire human brain and then translated to myelin-sensitive magnetic resonance imaging (MRI) data in a large cohort of healthy adults. This novel method identified a system-level gradient of microstructural differentiation traversing from primary sensory to limbic regions that followed shifts in laminar differentiation and cytoarchitectural complexity. Importantly, while microstructural and functional gradients described a similar hierarchy, they became increasingly dissociated in transmodal default mode and fronto-parietal networks. Meta-analytic decoding of these topographic dissociations highlighted involvement in higher-level aspects of cognition, such as cognitive control and social cognition. Our findings demonstrate a relative decoupling of macroscale functional from microstructural gradients in transmodal regions, which likely contributes to the flexible role these regions play in human cognition.

Connectome-based model predicts individual differences in propensity to trust

Trust constitutes a fundamental basis of human society and plays a pivotal role in almost every aspect of human relationships. Although enormous interest exists in determining the neuropsychological underpinnings of a person's propensity to trust utilizing task-based fMRI; however, little progress has been made in predicting its variations by task-free fMRI based on whole-brain resting-state functional connectivity (RSFC). Here, we combined a one-shot trust game with a connectome-based predictive modeling approach to predict propensity to trust from whole-brain RSFC. We demonstrated that individual variations in the propensity to trust were primarily predicted by RSFC rooted in the functional integration of distributed key nodes-caudate, amygdala, lateral prefrontal cortex, temporal-parietal junction, and the temporal pole-which are part of domain-general large-scale networks essential for the motivational, affective, and cognitive aspects of trust. We showed, further, that the identified brain-behavior associations were only evident for trust but not altruistic preferences and that propensity to trust (and its underlying neural underpinnings) were modulated according to the extent to which a person emphasizes general social preferences (i.e., horizontal collectivism) rather than general risk preferences (i.e., trait impulsiveness). In conclusion, the employed data-driven approach enables to predict propensity to trust from RSFC and highlights its potential use as an objective neuromarker of trust impairment in mental disorders.

Intrinsic default-executive coupling of the creative aging brain

Creativity refers to the ability to generate novel associations and has been linked to better problem-solving and real-world functional abilities. In younger adults, creative cognition has been associated with functional connectivity among brain networks implicated in executive control [fronto-parietal network (FPN) and salience network (SN)] and associative or elaborative processing default network (DN). Here, we investigate whether creativity is associated with the intrinsic network architecture of the brain and how these associations may differ for younger and older adults. Young (mean age: 24.76, n = 22) and older (mean age: 70.03, n = 44) adults underwent multi-echo functional magnetic resonance image scanning at rest and completed a divergent-thinking task to assess creative cognition outside the scanner. Divergent thinking in older adults, compared to young adults, was associated with functional connectivity between the default and both executive control networks (FPN and SN) as well as more widespread default-executive coupling. Finally, the ventromedial prefrontal cortex appears to be a critical node involved in within- and between-network connectivity associated with creative cognition in older adulthood. Patterns of intrinsic network coupling revealed here suggest a putative neural mechanism underlying a greater role for mnemonic processes in creative cognition in older adulthood.

Basic Units of Inter-Individual Variation in Resting State Connectomes

Resting state functional connectomes are massive and complex. It is an open question, however, whether connectomes differ across individuals in a correspondingly massive number of ways, or whether most differences take a small number of characteristic forms. We systematically investigated this question and found clear evidence of low-rank structure in which a modest number of connectomic components, around 50-150, account for a sizable portion of inter-individual connectomic variation. This number was convergently arrived at with multiple methods including estimation of intrinsic dimensionality and assessment of reconstruction of out-of-sample data. In addition, we show that these connectomic components enable prediction of a broad array of neurocognitive and clinical symptom variables at levels comparable to a leading method that is trained on the whole connectome. Qualitative observation reveals that these connectomic components exhibit extensive community structure reflecting interrelationships between intrinsic connectivity networks. We provide quantitative validation of this observation using novel stochastic block model-based methods. We propose that these connectivity components form an effective basis set for quantifying and interpreting inter-individual connectomic differences, and for predicting behavioral/clinical phenotypes.

Gender differences in parieto-frontal brain functional connectivity correlates of creativity

INTRODUCTION

Creativity is a complex construct that lies at the core of what has made human civilizations possible. One frequently used measure of creativity is the Abbreviated Torrance Test for Adults that yields an overall creativity score. In this study, we examine the relationship between the task-related differences in brain functional connectivity and the creativity score in a male and female group of participants.

METHODS

Brain functional connectivity was estimated from the steady-state visual evoked potential (SSVEP) event-related partial coherence in a group of 27 females and 27 males while they performed a low-demand visual vigilance task and the A-X version of the Continuous Performance Task. Task-related differences in brain functional connectivity (ΔFC) were correlated with the creativity score separately in the female and male groups.

RESULTS

We found that the creativity score was correlated with a parieto-frontal ΔFC component for both the female and male groups. However, significant gender differences were observed in both the timing and the laterality of the parietal component. Females exhibited a left parietal to bilateral frontal ΔFC component correlated with creativity score and this peaked on the appearance of a target in both tasks. By contrast, males demonstrated a right parietal to bilateral frontal ΔFC component correlated with creativity score which peaked on the appearance of the letter following the targets.

CONCLUSION

These findings are discussed in the context of the role of the Default Mode Network in creativity, and the role of gender-related differences in cortical networks that mediate creativity.

Long-term Chinese calligraphic handwriting training has a positive effect on brain network efficiency

As a visual art form, Chinese calligraphic handwriting (CCH) has been found to correlate with certain brain activity and to induce functional connectivity reorganization of the brain. This study investigated the effect of long-term CCH training on brain functional plasticity as assessed with network measures. With the resting-state fMRI data from 31 participants with at least five years of CCH training and 40 controls, we constructed brain functional networks, examined group differences at both the whole brain and modular levels, and correlated the topological characteristics with calligraphy skills. We found that, compared to the control group, the CCH group showed shorter characteristic path lengths and higher local efficiency in certain brain areas in the frontal and parietal cortices, limbic system, basal ganglia, and thalamus. Moreover, these network measures in the cingulate cortex, caudate nucleus, and thalamus were associated with CCH performance (i.e., copying and creating skills). These results suggest that long-term CCH training has a positive effect on the topological characteristics of brain networks.

Schizophrenia and Bipolar Illness in the Relatives of University Scientists: An Epidemiological Report on the Creativity-Psychopathology Relationship

A potential link between creativity and mental illness has been a longstanding topic for human studies and empirical research. The major problem is defining creativity and establishing its measurable indicators. A few high-quality epidemiological studies have been undertaken and point to a link between creativity and vulnerability to mental illness. Demonstrating such a shared vulnerability could expand our understanding of mental illnesses and open up new avenues of empirical research. In this epidemiological study, we defined scientists (academics) at the universities as individuals assumed to exhibit "more creativity" than the background population. In a register coupling with a population of 588,532 people, we examined successful university academics' first- and second-degree relatives for diagnosed mental disorders and compared those figures with controls from the background population controlling for educational level. The relatives of the academics had significantly increased risk of suffering from schizophrenia or bipolar disorder. For bipolar disorder, it is perhaps temperamental features and high energy levels that contribute to this association. In the case of schizophrenia, the mediating bridge may involve an amplification of human tendency to question the obvious and "taken-for-granted." Creativity and an increased risk for mental disorders seem to be linked by a shared vulnerability that is not manifested by clinical mental disorders in the academics.

Creative exploration as a scale-invariant search on a meaning landscape

Can knowledge accumulated in systems biology on mechanisms governing cell behavior help us to elucidate cognitive processes, such as human creative search? To address this, we focus on the property of scale invariance, which allows sensory systems to adapt to environmental signals spanning orders of magnitude. For example, bacteria search for nutrients, by responding to relative changes in nutrient concentration rather than absolute levels, via a sensory mechanism termed fold-change detection (FCD). Scale invariance is prevalent in cognition, yet the specific mechanisms are mostly unknown. Here, we screen many possible dynamic equation topologies, to find that an FCD model best describes creative search dynamics. The model further predicts robustness to variations in meaning perception, in agreement with behavioral data. We thus suggest FCD as a specific mechanism for scale invariant search, connecting sensory processes of cells and cognitive processes in human.

Right temporal alpha oscillations as a neural mechanism for inhibiting obvious associations

Creative cognition requires mental exploration of remotely connected concepts while suppressing dominant ones. Across four experiments using different samples of participants, we provide evidence that right temporal alpha oscillations play a crucial role in inhibiting habitual thinking modes, thereby paving the way for accessing more remote ideas. In the first experiment, participants completed the compound remote associate task (RAT) in three separate sessions: during right temporal alpha (10 Hz) transcranial alternating current brain stimulation (tACS), left temporal alpha tACS, and sham tACS. Participants performed better under right tACS only on RAT items in which two of the three words shared misleading semantic associations. In the second experiment, we measured EEG while the participants solved RAT items with or without shared misleading associations. We observed an increase in right temporal alpha power when participants correctly solved RAT items with misleading semantic associations. The third experiment demonstrated that while solving divergent thinking tasks participants came up with more remote ideas when stimulated by right temporal alpha tACS. In the fourth experiment, we found that participants showed higher right temporal alpha power when generating more remote uses for common objects. These studies altogether indicate that right temporal alpha oscillations may support creativity by acting as a neural mechanism for an active inhibition of obvious semantic associations.

Use or Consequences: Probing the Cognitive Difference Between Two Measures of Divergent Thinking

Recent studies have highlighted both similarities and differences between the cognitive processing that underpins memory retrieval and that which underpins creative thinking. To date, studies have focused more heavily on the Alternative Uses task, but fewer studies have investigated the processing underpinning other idea generation tasks. This study examines both Alternative Uses and Consequences idea generation with a methods pulled from cognitive psychology, and a novel method for evaluating the creativity of such responses. Participants were recruited from Amazon Mechanical Turk using a custom interface allowing for requisite experimental control. Results showed that both Alternative Uses and Consequences generation are well approximated by an exponential cumulative response time model, consistent with studies of memory retrieval. Participants were also slower to generate their first consequence compared with first responses to Alternative Uses, but inter-response time was negatively related to pairwise similarity on both tasks. Finally, the serial order effect is exhibited for both tasks, with Consequences earning more creative evaluations than Uses. The results have implications for burgeoning neuroscience research on creative thinking, and suggestions are made for future areas of inquiry. In addition, the experimental apparatus described provides an equitable way for researchers to obtain good quality cognitive data for divergent thinking tasks.

Creative aging: functional brain networks associated with divergent thinking in older and younger adults

Creative thinking is associated with connectivity between the default and executive control networks in the young brain. In aging, this pattern of functional coupling has been observed across multiple tasks. We have described this as the Default-Executive Coupling Hypothesis of Aging and suggest that this connectivity pattern may also be associated with creativity in older adulthood. However, age differences in brain networks implicated in creativity have yet to be investigated. The overarching goal of the present study was to examine age-related changes to functional brain networks associated with creativity. Specifically, we explored functional connectivity patterns among default and executive control brain regions associated with creative thoughts in older and younger adults. In a cross-sectional design, young (mean age = 21 y; n = 30) and older (mean age = 70 y; n = 25) participants completed a divergent thinking task during fMRI, which was examined using region of interest functional connectivity analyses. Consistent with predictions, analyses demonstrated that default and executive networks are more functionally coupled during creative thinking for older than younger adults. Critically, despite similar performance on an in-scanner creativity task, increased network efficiency was associated with creative ability for older adults only. These findings provide novel evidence of default-executive coupling as a putative mechanism associated with creative ability in later life.

Intersubject similarity of personality is associated with intersubject similarity of brain connectivity patterns

Personality is a central high-level psychological concept that defines individual human beings and has been associated with a variety of real-world outcomes (e.g., mental health and academic performance). Using 2 h, high resolution, functional magnetic resonance imaging (fMRI) resting state data of 984 (primary dataset N = 801, hold-out dataset N = 183) participants from the Human Connectome Project (HCP), we investigated the relationship between personality (five-factor model, FFM) and intrinsic whole-brain functional connectome. We found a pattern of functional brain connectivity ("global personality network") related to personality traits. Consistent with the heritability of personality traits, the connectivity strength of this global personality network is also heritable (more similar between monozygotic twin pairs compared to the dizygotic twin pairs). Validated by both the repeated family-based 10-fold cross-validation and hold-out dataset, our intersubject network similarity analysis allowed us to identify participants' pairs with similar personality profiles. Across all the identified pairs of participants, we found a positive correlation between the network similarity and personality similarity, supporting our "similar brain, similar personality" hypothesis. Furthermore, the global personality network can be used to predict the individual subject's responses in the personality questionnaire on an item level. In sum, based on individual brain connectivity pattern, we could predict different facets of personality, and this prediction is not based on localized regions, but rather relies on the individual connectivity pattern in large-scale brain networks.

Connectome-based models predict attentional control in aging adults

There are well-characterized age-related differences in behavioral and neural responses to tasks of attentional control. However, there is also increasing recognition of individual variability in the process of neurocognitive aging. Using connectome-based predictive modeling, a method for predicting individual-level behaviors from whole-brain functional connectivity, a sustained attention connectome-based prediction model (saCPM) has been derived in young adults. The saCPM consists of two large-scale functional networks: a high-attention network whose strength predicts better attention and a low-attention network whose strength predicts worse attention. Here we examined the generalizability of the saCPM for predicting inhibitory control in an aging sample. Forty-two healthy young adults (n = 21, ages 18-30) and older adults (n = 21, ages 60-80) performed a modified Stroop task, on which older adults exhibited poorer performance, indexed by higher reaction time cost between incongruent and congruent trials. The saCPM generalized to predict reaction time cost across age groups, but did not account for age-related differences in performance. Exploratory analyses were conducted to characterize the effects of age on functional connectivity and behavior. We identified subnetworks of the saCPM that exhibited age-related differences in strength. The strength of two low-attention subnetworks, consisting of frontoparietal, medial frontal, default mode, and motor nodes that were more strongly connected in older adults, mediated the effect of age group on performance. These results support the saCPM's ability to capture attention-related patterns reflected in each individual's functional connectivity signature across both task context and age. However, older and younger adults exhibit functional connectivity differences within components of the saCPM networks, and it is these connections that better account for age-related deficits in attentional control.

Exploring the Creative Process: Integrating Psychometric and Eye-Tracking Approaches

This exploratory study aims at integrating the psychometric approach to studying creativity with an eye-tracking methodology and thinking-aloud protocols to potentially untangle the nuances of the creative process. Wearing eye-tracking glasses, one hundred adults solved a drawing creativity test - The Test of Creative Thinking-Drawing Production (TCT-DP) - and provided spontaneous comments during this process. Indices of visual activity collected during the eye-tracking phase explained a substantial amount of variance in psychometric scores obtained in the test. More importantly, however, clear signs of methodological synergy were observed when all three sources (psychometrics, eye-tracking, and coded thinking-aloud statements) were integrated. The findings illustrate benefits of using a blended methodology for a more insightful analysis of creative processes, including creative learning and creative problem-solving.

The ebb and flow of attention: Between-subject variation in intrinsic connectivity and cognition associated with the dynamics of ongoing experience

Cognition is dynamic, allowing us the flexibility to shift focus from different aspects of the environment, or between internally- and externally-oriented trains of thought. Although we understand how individuals switch attention across different tasks, the neurocognitive processes that underpin the dynamics of less constrained elements of cognition are less well understood. To explore this issue, we developed a paradigm in which participants intermittently responded to external events across two conditions that systematically vary in their need for updating working memory based on information in the external environment. This paradigm distinguishes the influences on cognition that emerge because of demands placed by the task (sustained) from changes that result from the time elapsed since the last task response (transient). We used experience sampling to identify dynamic changes in ongoing cognition in this paradigm, and related between subject variation in these measures to variations in the intrinsic organisation of large-scale brain networks. We found systems important for attention were involved in the regulation of off-task thought. Coupling between the ventral attention network and regions of primary motor cortex was stronger for individuals who were able to regulate off-task thought in line with the demands of the task. This pattern of coupling was linked to greater task-related thought when environmental demands were high and elevated off-task thought when demands were low. In contrast, the coupling of the dorsal attention network with a region of lateral visual cortex was stronger for individuals for whom off-task thoughts transiently increased with the time since responding to the external world . This pattern is consistent with a role for this system in the time-limited top-down biasing of visual processing to increase behavioural efficiency. Unlike the attention networks, coupling between regions of the default mode network and dorsal occipital cortex was weaker for individuals for whom the level of detail decreased with the passage of time when the external task did not require continuous monitoring of external information. These data provide novel evidence for how neural systems vary across subjects and may underpin individual variation in the dynamics of thought, linking attention systems to the maintenance of task-relevant information, and the default mode network to supporting experiences with vivid detail.

Openness to experience and psychophysiological interaction patterns during divergent thinking

Creativity is the ability to produce something novel and useful. Various tasks have been used to explore the neural bases of creativity. However, studies exploring the relationship between the brain regions during divergent thinking are still rare. Given that the brain works in networks, exploring the functional connectivity (FC) patterns during divergent thinking is important. The present study explored the FC patterns during alternative uses task and its relationship with openness to experience. Psychophysiological interaction results corroborated that the inferior parietal lobule was positively connected to the precuneus and middle temporal gyrus. Middle frontal gyrus/superior frontal gyrus was positively connected to the precuneus and supramarginal gyrus. Individual difference analysis revealed that openness to experience was positively related to the strength of FCs between some key regions of default mode, cognitive control and salience networks. Findings confirmed the network-based mechanisms underlying creativity and the neural basis of individual differences of openness to experience.

Network Neuroscience of Creative Cognition: Mapping Cognitive Mechanisms and Individual Differences in the Creative Brain

Network neuroscience research is providing increasing specificity on the contribution of large-scale brain networks to creative cognition. Here, we summarize recent experimental work examining cognitive mechanisms of network interactions and correlational studies assessing network dynamics associated with individual creative abilities. Our review identifies three cognitive processes related to network interactions during creative performance: goal-directed memory retrieval, prepotent-response inhibition, and internally-focused attention. Correlational work using prediction modeling indicates that functional connectivity between networks-particularly the executive control and default networks-can reliably predict an individual's creative thinking ability. We discuss potential directions for future network neuroscience, including assessing creative performance in specific domains and using brain stimulation to test causal hypotheses regarding network interactions and cognitive mechanisms of creative thought.

Connectome-based individualized prediction of temperament trait scores

Temperament consists of multi-dimensional traits that affect various domains of human life. Evidence has shown functional connectome-based predictive models are powerful predictors of cognitive abilities. Putatively, individuals' innate temperament traits may be predictable by unique patterns of brain functional connectivity (FC) as well. However, quantitative prediction for multiple temperament traits at the individual level has not yet been studied. Therefore, we were motivated to realize the individualized prediction of four temperament traits (novelty seeking [NS], harm avoidance [HA], reward dependence [RD] and persistence [PS]) using whole-brain FC. Specifically, a multivariate prediction framework integrating feature selection and sparse regression was applied to resting-state fMRI data from 360 college students, resulting in 4 connectome-based predictive models that enabled prediction of temperament scores for unseen subjects in cross-validation. More importantly, predictive models for HA and NS could be successfully generalized to two relevant personality traits for unseen individuals, i.e., neuroticism and extraversion, in an independent dataset. In four temperament trait predictions, brain connectivities that show top contributing power commonly concentrated on the hippocampus, prefrontal cortex, basal ganglia, amygdala, and cingulate gyrus. Finally, across independent datasets and multiple traits, we show person's temperament traits can be reliably predicted using functional connectivity strength within frontal-subcortical circuits, indicating that human social and behavioral performance can be characterized by specific brain connectivity profile.

Reliable individual differences in fine-grained cortical functional architecture

Fine-grained functional organization of cortex is not well-conserved across individuals. As a result, individual differences in cortical functional architecture are confounded by topographic idiosyncrasies-i.e., differences in functional-anatomical correspondence. In this study, we used hyperalignment to align information encoded in topographically variable patterns to study individual differences in fine-grained cortical functional architecture in a common representational space. We characterized the structure of individual differences using three common functional indices, and assessed the reliability of this structure across independent samples of data in a natural vision paradigm. Hyperalignment markedly improved the reliability of individual differences across all three indices by resolving topographic idiosyncrasies and accommodating information encoded in spatially fine-grained response patterns. Our results demonstrate that substantial individual differences in cortical functional architecture exist at fine spatial scales, but are inaccessible with anatomical normalization alone.

On the Dependability and Feasibility of Layperson Ratings of Divergent Thinking

A new system for subjective rating of responses to divergent thinking tasks was tested using raters recruited from Amazon Mechanical Turk. The rationale for the study was to determine if such raters could provide reliable (aka generalizable) ratings from the perspective of generalizability theory. To promote reliability across the Alternative Uses and Consequence task prompts often used by researchers as measures of Divergent Thinking, two parallel scales were developed to facilitate feasibility and validity of ratings performed by laypeople. Generalizability and dependability studies were conducted separately for two scoring systems: the average-rating system and the snapshot system. Results showed that it is difficult to achieve adequate reliability using the snapshot system, while good reliability can be achieved on both task families using the average-rating system and a specific number of items and raters. Additionally, the construct validity of the average-rating system is generally good, with less validity for certain Consequences items. Recommendations for researchers wishing to adopt the new scales are discussed, along with broader issues of generalizability of subjective creativity ratings.

Individual differences in aesthetic engagement are reflected in resting-state fMRI connectivity: Implications for stress resilience

OBJECTIVE

Individual differences in aesthetic engagement-the propensity to be moved by art, nature, and beauty-are associated with positive health outcomes, as well as stress resilience. The purpose of the current study was to identify potential neural substrate mechanisms underlying individual differences in aesthetic engagement and reported proneness to aesthetic chill.

METHODS

Data from the Human Connectome Project (HCP) 1200 Subjects Release were utilized. Resting-state fMRI connectivity was extracted for 361 regions in the brain including cortical, subcortical and cerebellar regions for each participant, using participant-specific segmentation and parcellation of subcortical gray matter nuclei and a network-based statistics analytical approach. The Aesthetic Interests subcluster of the Openness to Experience scale (NEO-Five Factor Inventory; NEO-FFI) was used to characterize individual differences in aesthetic engagement and chill.

RESULTS

Participants reporting higher aesthetic engagement, particularly proneness to aesthetic chill responses, exhibited significantly higher connectivity between the default network and sensory and motor cortices, higher connectivity between the ventral default and salience networks, and decreased connectivity between the cerebellum and somatomotor cortex.

CONCLUSIONS

Current findings suggest that greater integration of the default mode network, involving processing of internal narrative, with neural representations of sensory perception and salience detection may be a mechanism underlying individual differences in aesthetic engagement. Thus, these individual differences may reflect general integration of environmental perception with internal emotional experience, which in turn may facilitate comfort with novelty, self-regulation, and positive adaptation to potentially stressful experiences.

Social Learning Strategies: Bridge-Building between Fields

While social learning is widespread, indiscriminate copying of others is rarely beneficial. Theory suggests that individuals should be selective in what, when, and whom they copy, by following 'social learning strategies' (SLSs). The SLS concept has stimulated extensive experimental work, integrated theory, and empirical findings, and created impetus to the social learning and cultural evolution fields. However, the SLS concept needs updating to accommodate recent findings that individuals switch between strategies flexibly, that multiple strategies are deployed simultaneously, and that there is no one-to-one correspondence between psychological heuristics deployed and resulting population-level patterns. The field would also benefit from the simultaneous study of mechanism and function. SLSs provide a useful vehicle for bridge-building between cognitive psychology, neuroscience, and evolutionary biology.

Individualized prediction of trait narcissism from whole-brain resting-state functional connectivity

Narcissism is one of the most fundamental personality traits in which individuals in general population exhibit a large heterogeneity. Despite a surge of interest in examining behavioral characteristics of narcissism in the past decades, the neurobiological substrates underlying narcissism remain poorly understood. Here, we addressed this issue by applying a machine learning approach to decode trait narcissism from whole-brain resting-state functional connectivity (RSFC). Resting-state functional MRI (fMRI) data were acquired for a large sample comprising 155 healthy adults, each of whom was assessed for trait narcissism. Using a linear prediction model, we examined the relationship between whole-brain RSFC and trait narcissism. We demonstrated that the machine-learning model was able to decode individual trait narcissism from RSFC across multiple neural systems, including functional connectivity between and within limbic and prefrontal systems as well as their connectivity with other networks. Key nodes that contributed to the prediction model included the amygdala, prefrontal and anterior cingulate regions that have been linked to trait narcissism. These findings remained robust using different validation procedures. Our findings thus demonstrate that RSFC among multiple neural systems predicts trait narcissism at the individual level.

Exploring collective experience in watching dance through intersubject correlation and functional connectivity of fMRI brain activity

How the brain contends with naturalistic viewing conditions when it must cope with concurrent streams of diverse sensory inputs and internally generated thoughts is still largely an open question. In this study, we used fMRI to record brain activity while a group of 18 participants watched an edited dance duet accompanied by a soundtrack. After scanning, participants performed a short behavioral task to identify neural correlates of dance segments that could later be recalled. Intersubject correlation (ISC) analysis was used to identify the brain regions correlated among observers, and the results of this ISC map were used to define a set of regions for subsequent analysis of functional connectivity. The resulting network was found to be composed of eight subnetworks and the significance of these subnetworks is discussed. While most subnetworks could be explained by sensory and motor processes, two subnetworks appeared related more to complex cognition. These results inform our understanding of the neural basis of common experience in watching dance and open new directions for the study of complex cognition.