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

Disentangling periodic and aperiodic resting EEG correlates of personality

Previous studies of resting electroencephalography (EEG) correlates of personality traits have conflated periodic and aperiodic sources of EEG signals. Because these are associated with different underlying neural dynamics, disentangling them can avoid measurement confounds and clarify findings. In a large sample (n = 300), we investigated how disentangling these activities impacts findings related to two research programs within personality neuroscience. In Study 1 we examined associations between Extraversion and two putative markers of reward sensitivity-Left Frontal Alpha asymmetry (LFA) and Frontal-Posterior Theta (FPT). In Study 2 we used machine learning to predict personality trait scores from resting EEG. In both studies, power within each EEG frequency bin was quantified as both total power and separate contributions of periodic and aperiodic activity. In Study 1, total power LFA and FPT correlated negatively with Extraversion (r ∼ -0.14), but there was no relation when LFA and FPT were derived only from periodic activity. In Study 2, all Big Five traits could be decoded from periodic power (r ∼ 0.20), and Agreeableness could also be decoded from total power and from aperiodic indices. Taken together, these results show how separation of periodic and aperiodic activity in resting EEG may clarify findings in personality neuroscience. Disentangling these signals allows for more reliable findings relating to periodic EEG markers of personality, and highlights novel aperiodic markers to be explored in future research.

The light side of gaming: creativity and brain plasticity

Could gaming enhance brain plasticity and executive functions (EFs) by fostering creativity? We identify vital benefits from further research exploring the relationship between games, brain plasticity, and creativity. The ongoing progress in neuroscience research in these three disciplines offers many possibilities and prospects for impactful therapy. Therefore, we emphasize the significance of investigating the untapped potentials of using games in creative therapy-our perspective on the often-overlooked neuroscientific aspect of creativity concerning health and wellbeing. One of these potentials is examining games as a therapeutic tool, focusing on their capacity to inspire and engage the imagination and other mental operators shared with creativity. Using a game as a therapeutic approach may boost brain plasticity, which may help them reduce their cognitive impairments by improving their EFs. This review offers a comprehensive outline of the latest advancements in the literature on games that tie to creativity through enhancing brain plasticity and EFs. Communicating this knowledge can furnish countless possibilities to improve our overall health and wellbeing and foster a positive perspective in individuals affected by anxiety.

The Experience of Meaningful Coincidences Is Associated with Stronger Alpha Power Increases during an Eyes-closed Resting Condition: A Bayesian Replication Approach

Recognizing and perceiving meaningful patterns in an ever-changing environment is fundamental to (human) beings. Apophenia, patternicity, and the propensity to perceive meaningful coincidences might result from the human brain working as a prediction machine that constantly matches sensory information to prior expectations. The propensity for Type I errors varies between people and, at its extreme, is associated with symptoms of schizophrenia. However, on a nonclinical level seeing meaning in randomness might be benevolent and was found to be associated with creativity and openness. However, hardly any neuroscientific investigation has examined EEG patterns of the propensity to experience meaningful coincidences in this manner. We hypothesized deviations in brain functions as one potential reason why some people experience more meaning in random arrangements than others. The gating by inhibition theory suggests that alpha power increases represent basic control mechanisms of sensory processes during varying task requirements. We found that people perceiving more meaningful coincidences had higher alpha power during an eyes-closed versus eyes-opened condition compared with people experiencing less meaningful coincidences. This indicates deviations in the sensory inhibition mechanism of the brain, which are critically relevant for higher cognitive functions. Applying Bayesian statistics, we replicated this finding in another independent sample.

Openness to Experience is associated with neural and performance measures of memory in older adults

Age-related decline in episodic memory performance is a well-replicated finding across numerous studies. Recent studies focusing on aging and individual differences found that the Big Five personality trait Openness to Experience (hereafter: Openness) is associated with better episodic memory performance in older adults, but the associated neural mechanisms are largely unclear. Here, we investigated the relationship between Openness and memory network function in a sample of 352 participants (143 older adults, 50-80 years; 209 young adults, 18-35 years). Participants underwent functional magnetic resonance imaging (fMRI) during a visual memory encoding task. Functional memory brain-network integrity was assessed using the similarity of activations during memory encoding (SAME) scores, which reflect the similarity of a participant's memory network activity compared to prototypical fMRI activity patterns of young adults. Openness was assessed using the NEO Five-Factor Inventory. Older vs young adults showed lower memory performance and higher deviation of fMRI activity patterns (i.e. lower SAME scores). Specifically in older adults, high Openness was associated with better memory performance, and mediation analysis showed that this relationship was partially mediated by higher SAME scores. Our results suggest that trait Openness may constitute a protective factor in cognitive aging by better preservation of the brain's memory network.

A shared novelty-seeking basis for creativity and curiosity

Curiosity and creativity are central pillars of human growth and invention. Although they have been studied extensively in isolation, the relationship between them has not yet been established. We propose that both curiosity and creativity emanate from the same mechanism of novelty seeking. We first present a synthesis showing that curiosity and creativity are affected similarly by a number of key cognitive faculties such as memory, cognitive control, attention, and reward. We then review empirical evidence from neuroscience research, indicating that the same brain regions are involved in both curiosity and creativity, focusing on the interplay between three major brain networks: the default mode network, the salience network, and the executive control network. After substantiating the link between curiosity and creativity, we propose a novelty-seeking model (NSM) that underlies them and suggests that the manifestation of the NSM is governed by one's state of mind.

Stability of specific personality network features corresponding to openness trait across different adult age periods: A machine learning analysis

The functional connectivity patterns of the brain during resting state are closely related to an individual's cognition, emotion, behavior, and social interactions, making it an important research method to measure personality traits in an unbiased way, replacing traditional paper-and-pencil tests. However, due to the dynamic nature of the brain, whether the changes in functional connectivity caused by age can stably map onto personality traits has not been previously investigated. This study focuses on whether network features that are significantly related to personality traits can effectively distinguish subjects with different personality traits, and whether these network features vary across different periods of adulthood. The study included 343 healthy adult participants, divided into early adulthood and middle adulthood groups according to the age threshold of 35. Resting-state functional magnetic resonance imaging (fMRI) and the Big Five personality questionnaire were collected. we investigated the relationship between personality traits and intrinsic whole-brain functional connectome. We then used support vector machine (SVM) to evaluate the performance of personality network features in distinguishing subjects with high and low scores in the early-adulthood sample, and cross-validated in the mid-adulthood sample. Additionally, edge-based analysis (NBS) was used to explore the stability of personality networks across the two age samples. Our results show that the network features corresponding to openness personality trait are stable and can effectively differentiate subjects with different scores in both age samples. Furthermore, this study found that these network features vary to some extent across different periods of adulthood. These findings provide new evidence and insights into the application of resting-state functional connectivity patterns in measuring personality traits and help us better understand the dynamic characteristics of the human brain.

Exploring the behavioral and neural correlates of semantic distance in creative writing

Creativity is critical to economic growth and societal progress. However, assessing creativity using objective approaches remains a challenge. To address this, we employ three objective indicators based on semantic distance to quantify the originality and appropriateness of creativity by analyzing long texts in a story-writing experiment. Global and local distances were generated separately by computing the mean distance of the whole text and the distance between adjacent sentences, and they were positively correlated with story originality in writing. Global cohesion was positively correlated with story rationality in writing, as generated by computing the semantic coherence between the text and story context. At the behavioral level, three semantic indicators were used to measure originality and appropriateness of creativity and reflected individual differences, including creative achievement and creative personality. At the neural level, global distance was best predicted by the features of the salience and default networks, whereas global cohesion corresponded to the control and salience networks. These findings point to a stable neural basis for semantic indicators and verify the idea of separating different dimensions of creativity. Taken together, our results demonstrate the significance of semantic indicators in assessing creativity and provide insights into analyzing long texts in natural paradigm.

Integration of structural brain networks is related to openness to experience: A diffusion MRI study with CSD-based tractography

Openness to experience is one of the big five traits of personality which recently has been the subject of several studies in neuroscience due to its importance in understanding various cognitive functions. However, the neural basis of openness to experience is still unclear. Previous studies have found largely heterogeneous results, suggesting that various brain regions may be involved in openness to experience. Here we suggested that performing structural connectome analysis may shed light on the neural underpinnings of openness to experience as it provides a more comprehensive look at the brain regions that are involved in this trait. Hence, we investigated the involvement of brain network structural features in openness to experience which has not yet been explored to date. The magnetic resonance imaging (MRI) data along with the openness to experience trait score from the self-reported NEO Five-Factor Inventory of 100 healthy subjects were evaluated from Human Connectome Project (HCP). CSD-based whole-brain probabilistic tractography was performed using diffusion-weighted images as well as segmented T1-weighted images to create an adjacency matrix for each subject. Using graph theoretical analysis, we computed global efficiency (GE) and clustering coefficient (CC) which are measures of two important aspects of network organization in the brain: functional integration and functional segregation respectively. Results revealed a significant negative correlation between GE and openness to experience which means that the higher capacity of the brain in combining information from different regions may be related to lower openness to experience.

Dream Recall Frequency, Lucid Dream Frequency, and Personality During the Covid-19 Pandemic

Dream recall frequency and lucid dream frequency showed large inter-individual differences that are partly related to personality dimensions. However, as dream research is a small field, independent studies are necessary to build a solid empirical foundation. The present online survey included 1,537 participants (1150 women, 387 men) with a mean age of 35.1 ± 15.8 years. Whereas the relationship between openness to experience and dream recall frequency was in line with previous research - supporting the life-style hypothesis of dream recall, the associations between the Big Five personality factors and lucid dream frequency are less homogenous; for example, the negative relationship between neuroticism and lucid dream frequency. Even though the effect sizes of these associations are small, the findings can help in identifying links between waking and dreaming. Moreover, it was found that lucid dream frequency was related to Covid-19-related worries, whereas dream recall frequency was not.

Functional connectivity of the central autonomic and default mode networks represent neural correlates and predictors of individual personality

There is solid evidence for the prominent involvement of the central autonomic and default mode systems in shaping personality. However, whether functional connectivity of these systems can represent neural correlates and predictors of individual variation in personality traits is largely unknown. Resting-state functional magnetic resonance imaging data of 215 healthy young adults were used to construct the sympathetic (SN), parasympathetic (PN), and default mode (DMN) networks, with intra- and internetwork functional connectivity measured. Personality factors were assessed using the five-factor model. We examined the associations between personality factors and functional network connectivity, followed by performance of personality prediction based on functional connectivity using connectome-based predictive modeling (CPM), a recently developed machine learning approach. All personality factors (neuroticism, extraversion, conscientiousness, and agreeableness) other than openness were significantly correlated with intra- and internetwork functional connectivity of the SN, PN, and DMN. Moreover, the CPM models successfully predicted conscientiousness and agreeableness at the individual level using functional network connectivity. Our findings may expand existing knowledge regarding the neural substrates underlying personality.

Retrieval flexibility links to creativity: evidence from computational linguistic measure

Creativity, the ability to generate original and valuable products, has long been linked to semantic retrieval processes. The associative theory of creativity posits flexible retrieval ability as an important basis for creative idea generation. However, there is insufficient research on how flexible memory retrieval acts on creative activities. This study aimed to capture different dynamic aspects of retrieval processes and examine the behavioral and neural associations between retrieval flexibility and creativity. We developed 5 metrics to quantify retrieval flexibility based on previous studies, which confirmed the important role of creativity. Our findings showed that retrieval flexibility was positively correlated with multiple creativity-related behavior constructs and can promote distinct search patterns in different creative groups. Moreover, high flexibility was associated with the lifetime of a specific brain state during rest, characterized by interactions among large-scale cognitive brain systems. The flexible functional connectivity within and between default mode, executive control, and salience provides further evidence on brain dynamics of creativity. Retrieval flexibility mediated the links between the lifetime of the related brain state and creativity. This new approach is expected to enhance our knowledge of the role of retrieval flexibility in creativity from a dynamic perspective.

Classification of Contrasting Discrete Emotional States Indicated by EEG Based Graph Theoretical Network Measures

The present study shows new findings that reveal the high association between emotional arousal and neuro-functional brain connectivity measures. For this purpose, contrasting discrete emotional states (happiness vs sadness, amusement vs disgust, calmness vs excitement, calmness vs anger, fear vs anger) are classified by using Support Vector Machines (SVMs) driven by Graph Theoretical segregation (clustering coefficients, transitivity, modularity) and integration (global efficiency, local efficiency) measures of the brain network. Emotional EEG data mediated by short duration video film clips is downloaded from publicly available database called DREAMER. Pearson Correlation (PC) and Spearman Correlation have been examined to estimate statistical dependencies between relatively shorter (6 sec) and longer (12 sec) non-overlapped EEG segments across the cortex. Then the corresponding brain connectivity encoded as a graph is transformed into binary numbers with respect to two different thresholds (60%max and mean). Statistical differences between contrasting emotions are obtained by using both one-way Anova tests and step-wise logistic regression modelling in accordance with variables (dependency estimation, segment length, threshold, network measure). Combined integration measures provided the highest classification accuracies (CAs) (75.00% 80.65%) when PC is applied to longer segments in accordance with particular threshold as the mean. The segregation measures also provided useful CAs (74.13% 80.00%), while the combination of both measures did not. The results reveal that discrete emotional states are characterized by balanced network measures even if both segregation and integration measures vary depending on arousal scores of audio-visual stimuli due to neurotransmitter release during video watching.

Intentionality of Self-Generated Thought: Contributions of Mind Wandering to Creativity

Studies suggest that internally oriented cognitive processes are central to creativity. Here, we distinguish between intentional and unintentional forms of mind wandering and explore their behavioral and neural correlates. We used a sample of 155 healthy adults from the mind-brain-body dataset, all of whom completed resting-state fMRI scans and trait-level measures of mind wandering. We analyzed intentional and unintentional mind wandering tendencies using self-report measures. Next, we explored the relationship between mind wandering tendencies and creativity, as measured by a divergent thinking task. Finally, we describe patterns of resting-state network connectivity associated with mind wandering, using graph theory analysis. At the behavioral level, results showed a significant positive association between creativity and both intentional and unintentional mind wandering. Neuroimaging analysis revealed higher weighted degree connectivity associated with both forms of mind wandering, implicating core regions of the default network and the left temporal pole. We observed topological connectivity differences within the default network: intentional mind wandering was associated with degree connectivity in posterior regions, whereas unintentional mind wandering showed greater involvement of prefrontal areas. Overall, the findings highlight patterns of resting-state network connectivity associated with intentional and unintentional mind wandering, and provide novel evidence of a link between mind wandering and creativity.

Reward enhances connectivity between the ventral striatum and the default mode network

The default mode network (DMN) has been theorized to participate in a range of social, cognitive, and affective functions. Yet, previous accounts do not consider how the DMN contributes to other brain regions depending on psychological context, thus rendering our understanding of DMN function incomplete. We addressed this gap by applying a novel network-based psychophysiological interaction (nPPI) analysis to the reward task within the Human Connectome Project. We first focused on the task-evoked responses of the DMN and other networks involving the prefrontal cortex, including the executive control network (salience network) and the left and right frontoparietal networks. Consistent with a host of prior studies, the DMN exhibited a relative decrease in activation during the task, while the other networks exhibited a relative increase during the task. Next, we used nPPI analyses to assess whether these networks exhibit task-dependent changes in connectivity with other brain regions. Strikingly, we found that the experience of reward enhances task-dependent connectivity between the DMN and the ventral striatum, an effect that was specific to the DMN. Surprisingly, the strength of DMN-VS connectivity was correlated with personality characteristics relating to openness. Taken together, these results advance models of DMN by demonstrating how it contributes to other brain systems during task performance and how those contributions relate to individual differences.

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.

On the Importance of Being Flexible: Dynamic Brain Networks and Their Potential Functional Significances

In this theoretical review, we begin by discussing brains and minds from a dynamical systems perspective, and then go on to describe methods for characterizing the flexibility of dynamic networks. We discuss how varying degrees and kinds of flexibility may be adaptive (or maladaptive) in different contexts, specifically focusing on measures related to either more disjoint or cohesive dynamics. While disjointed flexibility may be useful for assessing neural entropy, cohesive flexibility may potentially serve as a proxy for self-organized criticality as a fundamental property enabling adaptive behavior in complex systems. Particular attention is given to recent studies in which flexibility methods have been used to investigate neurological and cognitive maturation, as well as the breakdown of conscious processing under varying levels of anesthesia. We further discuss how these findings and methods might be contextualized within the Free Energy Principle with respect to the fundamentals of brain organization and biological functioning more generally, and describe potential methodological advances from this paradigm. Finally, with relevance to computational psychiatry, we propose a research program for obtaining a better understanding of ways that dynamic networks may relate to different forms of psychological flexibility, which may be the single most important factor for ensuring human flourishing.

Impact of Personality Traits on Knowledge Hiding: A Comparative Study on Technology-Based Online and Physical Education

Knowledge hiding has been a variable of interest that has led to major intangible losses to organizations, especially in this pandemic era when everything has shifted to online platforms and social media. Knowledge hiding has taken a new turn into the field of knowledge management. Moreover, the major players in knowledge hiding are the personality characteristics of individuals that have now found a way of expression without coming into the spotlight. This study is a necessary one in this time of online working environments where the role of personality traits and psychological ownership has been explored to understand their impact on the knowledge hiding within the organizations of China, and furthermore, to understand what role social status plays in moderating these relationships. The sampling design used is convenient random sampling with a sample size of 298 managers. This study has used the software Smart-PLS 3.3.3 for analyzing the data. The data relied on and was validated using preliminary tests of reliability and discriminant and convergent validities using the measurement model algorithm. Further, the partial least square technique was used to find the equation modeling for the variables, with the help of a structural model algorithm using 500 iterations for bootstrapping. The findings of the current study show that the personality traits of the "BIG FIVE" model positively predict knowledge hiding, except for openness to experience. At the same time, psychological ownership plays a partial mediating role.

The functional connectivity basis of creative achievement linked with openness to experience and divergent thinking

Openness to experience and divergent thinking are considered to be critical in real-life creative achievement. However, there is still a lack of neural evidence to explain how creative achievement is related to openness to experience and divergent thinking. Here, a structural equation model and resting-state functional connectivity were used to investigate their relationships in college students. The structural equation model results repeatedly showed that openness to experience and divergent thinking are positively associated with creative achievement, and the resting-state functional connectivity results showed that openness to experience and divergent thinking were both correlated with the attention network and default mode network. However, openness to experience was also correlated with the primary sensorimotor network and frontoparietal control network. Mediation models further corroborated this result. Collectively, these findings support previous works and further indicate that different neural bases may underlie the associations of creative achievement with openness to experience and divergent thinking.

Brain Knows Who Is on the Same Wavelength: Resting-State Connectivity Can Predict Compatibility of a Female-Male Relationship

Prediction of the initial compatibility of heterosexual individuals based on self-reported traits and preferences has not been successful, even with significantly developed information technology. To overcome the limitations of self-reported measures and predict compatibility, we used functional connectivity profiles from resting-state functional magnetic resonance imaging (fMRI) data that carry rich individual-specific information sufficient to predict psychological constructs and activation patterns during social cognitive tasks. Several days after collecting data from resting-state fMRIs, participants undertook a speed-dating experiment in which they had a 3-min speed date with every other opposite-sex participant. Our machine learning algorithm successfully predicted whether pairs in the experiment were compatible or not using (dis)similarity of functional connectivity profiles obtained before the experiment. The similarity and dissimilarity of functional connectivity between individuals and these multivariate relationships contributed to the prediction, hence suggesting the importance of complementarity (observed as dissimilarity) as well as the similarity between an individual and a potential partner during the initial attraction phase. The result indicates that the salience network, limbic areas, and cerebellum are especially important for the feeling of compatibility. This research emphasizes the utility of neural information to predict complex phenomena in a social environment that behavioral measures alone cannot predict.

Decomposition of individual-specific and individual-shared components from resting-state functional connectivity using a multi-task machine learning method

Resting-state functional connectivity (RSFC) can be used for mapping large-scale human brain networks during rest. There is considerable interest in distinguishing the individual-shared and individual-specific components in RSFC for the better identification of individuals and prediction of behavior. Therefore, we propose a multi-task learning based sparse convex alternating structure optimization (MTL-sCASO) method to decompose RSFC into individual-specific connectivity and individual-shared connectivity. We used synthetic data to validate the efficacy of the MTL-sCASO method. In addition, we verified that individual-specific connectivity achieves higher identification rates than the Pearson correlation (PC) method, and the individual-specific components observed in 886 individuals from the Human Connectome Project (HCP) examined in two sessions over two consecutive days might serve as individual fingerprints. Individual-specific connectivity has low inter-subject similarity (-0.005±0.023), while individual-shared connectivity has high inter-subject similarity (0.822±0.061). We also determined the anatomical locations (region or subsystem) related to individual attributes and common features. We find that individual-specific connectivity exhibits low degree centrality in the sensorimotor processing system but high degree centrality in the control system. Importantly, the individual-specific connectivity estimated by the MTL-sCASO method accurately predicts behavioral scores (improved by 9.4% compared to the PC method) in the cognitive dimension. The decomposition of individual-specific and individual-shared components from RSFC provides a new approach for tracing individual traits and group analysis using functional brain networks.

Semantic memory: A review of methods, models, and current challenges

Adult semantic memory has been traditionally conceptualized as a relatively static memory system that consists of knowledge about the world, concepts, and symbols. Considerable work in the past few decades has challenged this static view of semantic memory, and instead proposed a more fluid and flexible system that is sensitive to context, task demands, and perceptual and sensorimotor information from the environment. This paper (1) reviews traditional and modern computational models of semantic memory, within the umbrella of network (free association-based), feature (property generation norms-based), and distributional semantic (natural language corpora-based) models, (2) discusses the contribution of these models to important debates in the literature regarding knowledge representation (localist vs. distributed representations) and learning (error-free/Hebbian learning vs. error-driven/predictive learning), and (3) evaluates how modern computational models (neural network, retrieval-based, and topic models) are revisiting the traditional "static" conceptualization of semantic memory and tackling important challenges in semantic modeling such as addressing temporal, contextual, and attentional influences, as well as incorporating grounding and compositionality into semantic representations. The review also identifies new challenges regarding the abundance and availability of data, the generalization of semantic models to other languages, and the role of social interaction and collaboration in language learning and development. The concluding section advocates the need for integrating representational accounts of semantic memory with process-based accounts of cognitive behavior, as well as the need for explicit comparisons of computational models to human baselines in semantic tasks to adequately assess their psychological plausibility as models of human semantic memory.

Behavioral and Neural Signatures of Visual Imagery Vividness Extremes: Aphantasia versus Hyperphantasia

Although Galton recognized in the 1880s that some individuals lack visual imagery, this phenomenon was mostly neglected over the following century. We recently coined the terms "aphantasia" and "hyperphantasia" to describe visual imagery vividness extremes, unlocking a sustained surge of public interest. Aphantasia is associated with subjective impairment of face recognition and autobiographical memory. Here we report the first systematic, wide-ranging neuropsychological and brain imaging study of people with aphantasia (n = 24), hyperphantasia (n = 25), and midrange imagery vividness (n = 20). Despite equivalent performance on standard memory tests, marked group differences were measured in autobiographical memory and imagination, participants with hyperphantasia outperforming controls who outperformed participants with aphantasia. Face recognition difficulties and autistic spectrum traits were reported more commonly in aphantasia. The Revised NEO Personality Inventory highlighted reduced extraversion in the aphantasia group and increased openness in the hyperphantasia group. Resting state fMRI revealed stronger connectivity between prefrontal cortices and the visual network among hyperphantasic than aphantasic participants. In an active fMRI paradigm, there was greater anterior parietal activation among hyperphantasic and control than aphantasic participants when comparing visualization of famous faces and places with perception. These behavioral and neural signatures of visual imagery vividness extremes validate and illuminate this significant but neglected dimension of individual difference.

How the Immune System Deploys Creativity: Why We Can Learn From Astronauts and Cosmonauts

In this interdisciplinary article, we investigate the relationship between creativity and the immune system; the creative features of the immune system and how the immune system and its role in regulating homeostasis might be related to creative cognition. We argue that within a multivariate approach of creativity, the immune system is a contributing factor. New directions for research are also discussed. When astronauts and cosmonauts venture into the new and extreme environment of outer space, their immune system needs to instantly adapt and find new answers to survive biologically and psychologically. Many astronauts report interest in creative activities and therefore represent an interesting group to investigate creativity in relation with the immune system. Little is known regarding (1) how the immune system interacts with and supports creative cognition and behavior, (2) if an individual's immune system, interacting with cognition, adapts more originally to a new environment compared to another's; in other words, if there is creativity in the domain of the immune system, and (3) the creative properties and functions of the immune system itself.

Default Mode Network Functional Connectivity Negatively Associated with Trait Openness to Experience

Evaluating associations between the five-factor personality domains and resting-state functional connectivity networks (e.g., default mode network, DMN) highlights distributed neurobiological systems linked to behaviorally relevant phenotypes. Establishing these associations can highlight a potential underlying role for these neural pathways in related clinical illness and treatment response. Here we examined associations between within- and between-network resting-state functional connectivity with functional magnetic resonance imaging (fMRI) and the five-factor personality domains: Openness to experience (Openness), Extraversion, Neuroticism, Agreeableness and Conscientiousness. We included data from 470 resting-state scan sessions and personality assessments in 295 healthy participants. Within- and between-network functional connectivity from 32 a priori defined regions was computed across seven resting-state networks. The association between functional connectivity and personality traits was assessed using generalized least squares. Within-network DMN functional connectivity was significantly negatively associated with trait Openness (regression coefficient= -0.0010; [95% CI] = [-0.0017, -0.0003]; pFWER = 0.033), seemingly driven by association with the Fantasy subfacet. Trait Extraversion was significantly negatively associated with functional connectivity between the visual and dorsal attention networks and positively associated with functional connectivity between the frontoparietal and language networks. Our findings provide evidence that resting-state DMN is associated with trait Openness and gives insight into personality neuroscience.

Reliability modelling of resting-state functional connectivity

Resting-state functional magnetic resonance imaging (rs-fMRI) has an inherently low signal-to-noise ratio largely due to thermal and physiological noise that attenuates the functional connectivity (FC) estimates. Such attenuation limits the reliability of FC and may bias its association with other traits. Low reliability also limits heritability estimates. Classical test theory can be used to obtain a true correlation estimate free of random measurement error from parallel tests, such as split-half sessions of a rs-fMRI scan. We applied a measurement model to split-half FC estimates from the resting-state fMRI data of 1003 participants from the Human Connectome Project (HCP) to examine the benefit of reliability modelling of FC in association with traits from various domains. We evaluated the efficiency of the measurement model on extracting a stable and reliable component of FC and its association with several traits for various sample sizes and scan durations. In addition, we aimed to replicate our previous findings of increased heritability estimates when using a measurement model in a longitudinal adolescent twin cohort. The split-half measurement model improved test-retest reliability of FC on average with +0.33 points (from +0.49 to +0.82), improved strength of associations between FC and various traits on average 1.2-fold (range 1.09-1.35), and increased heritability estimates on average with +20% points (from 39% to 59%) for the full HCP dataset. On average, about half of the variance in split-session FC estimates was attributed to the stable and reliable component of FC. Shorter scan durations showed greater benefit of reliability modelling (up to 1.6-fold improvement), with an additional gain for smaller sample sizes (up to 1.8-fold improvement). Reliability modelling of FC based on a split-half using a measurement model can benefit genetic and behavioral studies by extracting a stable and reliable component of FC that is free from random measurement error and improves genetic and behavioral associations.

Effects of the Openness to Experience Polygenic Score on Cortical Thickness and Functional Connectivity

Openness to experience (OTE) has relatively stable and heritable characteristics. Previous studies have used candidate gene approaches to explore the genetic mechanisms of OTE, but genome-wide polygenic scores have a greater genetic effect than other genetic analysis methods, and previous studies have never examined the potential effect of OTE on this cumulative effect at the level of the brain mechanism. In the present study, we aim to explore the associations between polygenic scores (PGSs) of OTE and brain structure and functions. First, the results of PGSs of OTE at seven different thresholds were calculated in a large Chinese sample (N = 586). Then, we determined the associations between PGSs of OTE and cortical thickness and functional connectivity. The results showed that PGSs of OTE was negatively correlated with the thickness of the fusiform gyrus, and PGSs of OTE were negatively associated with the functional connectivity between the left intraparietal sulcus (IPS) and the right posterior occipital lobe. These findings may suggest that the brain structure of fusiform gyrus and brain functions of IPS and posterior occipital lobe are partly regulated by OTE-related genetic factors.

Testing the Information‐Seeking Theory of Openness/Intellect

Why are open people open? A recent theory suggests that openness/intellect reflects sensitivity to the reward value of information, but so far, this has undergone few direct tests. To assess preferences for information, we constructed a novel task, adapted from information‐seeking paradigms within decision science, in which participants could choose to see information related to a guessing game they had just completed. Across two studies (one exploratory, n = 151; one confirmatory, n = 301), openness/intellect did not predict information seeking. Our results thus do not support a straightforward version of the theory, whereby open individuals display a general‐purpose sensitivity to any sort of new information. However, trait curiosity (arguably a facet of openness/intellect) predicted information seeking in both studies, and uncertainty intolerance (inversely related to openness/intellect) predicted information seeking in Study 2. Thus, it is possible that the domain‐level null association masks two divergent information‐seeking pathways: one approach motivated (curiosity) and one avoidance motivated (uncertainty intolerance). It remains to be seen whether these conflicting motivations can be isolated and if doing so reveals any association between information‐seeking and the broader openness/intellect domain.

The Multilayer Network Approach in the Study of Personality Neuroscience

It has long been understood that a multitude of biological systems, from genetics, to brain networks, to psychological factors, all play a role in personality. Understanding how these systems interact with each other to form both relatively stable patterns of behaviour, cognition and emotion, but also vast individual differences and psychiatric disorders, however, requires new methodological insight. This article explores a way in which to integrate multiple levels of personality simultaneously, with particular focus on its neural and psychological constituents. It does so first by reviewing the current methodology of studies used to relate the two levels, where psychological traits, often defined with a latent variable model are used as higher-level concepts to identify the neural correlates of personality (NCPs). This is known as a top-down approach, which though useful in revealing correlations, is not able to include the fine-grained interactions that occur at both levels. As an alternative, we discuss the use of a novel complex system approach known as a multilayer network, a technique that has recently proved successful in revealing veracious interactions between networks at more than one level. The benefits of the multilayer approach to the study of personality neuroscience follow from its well-founded theoretical basis in network science. Its predictive and descriptive power may surpass that of statistical top-down and latent variable models alone, potentially allowing the discernment of more complete descriptions of individual differences, and psychiatric and neurological changes that accompany disease. Though in its infancy, and subject to a number of methodological unknowns, we argue that the multilayer network approach may contribute to an understanding of personality as a complex system comprised of interrelated psychological and neural features.

Structural equation modeling of the associations between amygdala activation, personality, and internalizing, externalizing symptoms of psychopathology

There is an expanding literature on the theoretical and empirical connections between personality and psychopathology, and their shared neurobiological correlates. Recent cybernetic theories of personality and psychopathology, as well as affective neuroscience theory, provide grounding for understanding neurobiological-personality-psychopathology (NPP) associations. With the emergence of large sample datasets (e.g., Human Connectome Project) advanced quantitative modeling can be used to rigorously test dynamic statistical representations of NPP connections. Also, research suggests that these connections are influenced by sex, and large samples provide the opportunity to examine how NPP associations might be moderated by sex. The current study used a large sample from the Duke Neurogenetics Study (DNS) to examine how amygdala activation to facial expressions was linked with self-report of personality traits and clinical interviews of internalizing and externalizing symptoms of psychopathology. Structural equation modeling results revealed direct associations of amygdala activation with personality trait expression, as well as indirect associations (though personality) with symptoms of psychopathology. Moreover, the NPP links were moderated by sex. The current results are in line with research that identifies a broader role played by the amygdala in personality and provide potential insights for continued research in personality neuroscience and recent theories on the neurobiology of personality.

Decoding personality trait measures from resting EEG: An exploratory report

Can personality be predicted from oscillatory patterns produced by the brain at rest? To date, relatively few studies using electroencephalography (EEG) have yielded consistent relations between personality trait measures and spectral power. Thus, new exploratory research may help develop targeted hypotheses about how neural processes associated with EEG activity may relate to personality differences. We used multivariate pattern analysis to decode personality scores (i.e., Big Five traits) from resting EEG frequency power spectra. Up to 8 minutes of EEG data was recorded per participant prior to completing an unrelated task (N = 168, M_age = 23.51, 57% female) and, in a subset of participants, after task completion (N = 96, M_age = 23.22, 52% female). In each recording, participants alternated between open and closed eyes. Linear support vector regression with 10-fold cross validation was performed using the power from 62 scalp electrodes within 1 Hz frequency bins from 1 to 30 Hz. One Big Five trait, agreeableness, could be decoded from EEG power ranging from 8 to 19 Hz, and this was consistent across all four recording periods. Neuroticism was decodable using data within the 3-6 Hz range, albeit less consistently. Posterior alpha power negatively correlated with agreeableness, whereas parietal beta power positively correlated with agreeableness. We suggest methods to draw from our results and develop targeted future hypotheses, such as linking to individual alpha frequency and incorporating self-reported emotional states. Our open dataset can be harnessed to reproduce results or investigate new research questions concerning the biological basis of personality.

Resting-state functional brain connectivity in a predominantly African-American sample of older adults: exploring links among personality traits, cognitive performance, and the default mode network

The personality traits of neuroticism, openness, and conscientiousness are relevant factors for cognitive aging outcomes. The present study examined how these traits were associated with cognitive abilities and corresponding resting-state functional connectivity (RSFC) of the default mode network (DMN) in an older and predominantly minority sample. A sample of 58 cognitively unimpaired, largely African-American, older adults (M age = 68.28 ± 8.33) completed a standard RSFC magnetic resonance imaging sequence, a Big Five measure of personality, and delayed memory, Stroop, and verbal fluency tasks. Personality trait associations of within-network connectivity of the posterior cingulate cortex (PCC), a hub of the DMN, were examined using a seed-based approach. Trait scores were regressed on cognitive performance (delayed memory for neuroticism, Stroop for conscientiousness, and verbal fluency for openness). Greater openness predicted greater verbal fluency and greater RSFC between the PCC and eight clusters, including the medial prefrontal cortex, left middle frontal gyrus, and precuneus. Greater PCC–precuneus connectivity predicted greater verbal fluency. Neuroticism and conscientiousness did not significantly predict either cognitive performance or RSFC. Although requiring replication and elaboration, the results implicate openness as a contributing factor to cognitive aging via concomitant cognitive performance and connectivity within cortical hubs of the DMN and add to the sparse literature on these variables in a diverse group of older adults.

Robust prediction of individual personality from brain functional connectome

Neuroimaging studies have linked inter-individual variability in the brain to individualized personality traits. However, only one or several aspects of personality have been effectively predicted based on brain imaging features. The objective of this study was to construct a reliable prediction model of personality in a large sample by using connectome-based predictive modeling (CPM), a recently developed machine learning approach. High-quality resting-state functional magnetic resonance imaging data of 810 healthy young participants from the Human Connectome Project dataset were used to construct large-scale brain networks. Personality traits of the five-factor model (FFM) were assessed by the NEO Five Factor Inventory. We found that CPM successfully and reliably predicted all the FFM personality factors (agreeableness, openness, conscientiousness and neuroticism) other than extraversion in novel individuals. At the neural level, we found that the personality-associated functional networks mainly included brain regions within default mode, frontoparietal executive control, visual and cerebellar systems. Although different feature selection thresholds and parcellation strategies did not significantly influence the prediction results, some findings lost significance after controlling for confounds including age, gender, intelligence and head motion. Our finding of robust personality prediction from an individual's unique functional connectome may help advance the translation of 'brain connectivity fingerprinting' into real-world personality psychological settings.

Resting state functional connectivity underlying musical creativity

While the behavior of "being musically creative"- improvising, composing, songwriting, etc.-is undoubtedly a complex and highly variable one, recent neuroscientific investigation has offered significant insight into the neural underpinnings of many of the creative processes contributing to such behavior. A previous study from our research group (Bashwiner et al., 2016), which examined two aspects of brain structure as a function of creative musical experience, found significantly increased cortical surface area or subcortical volume in regions of the default-mode network, a motor planning network, and a "limbic" network. The present study sought to determine how these regions coordinate with one another and with other regions of the brain in a large number of participants (n ​= ​218) during a task-neutral period, i.e., during the "resting state." Deriving from the previous study's results a set of eleven regions of interest (ROIs), the present study analyzed the resting-state functional connectivity (RSFC) from each of these seed regions as a function of creative musical experience (assessed via our Musical Creativity Questionnaire). Of the eleven ROIs investigated, nine showed significant correlations with a total of 22 clusters throughout the brain, the most significant being located in bilateral cerebellum, right inferior frontal gyrus, midline thalamus (particularly the mediodorsal nucleus), and medial premotor regions. These results support prior reports (by ourselves and others) implicating regions of the default-mode, executive, and motor-planning networks in musical creativity, while additionally-and somewhat unanticipatedly-including a potentially much larger role for the salience network than has been previously reported in studies of musical creativity.

Toward a Neural Model of the Openness-Psychoticism Dimension: Functional Connectivity in the Default and Frontoparietal Control Networks

Psychosis proneness has been linked to heightened Openness to Experience and to cognitive deficits. Openness and psychotic disorders are associated with the default and frontoparietal networks, and the latter network is also robustly associated with intelligence. We tested the hypothesis that functional connectivity of the default and frontoparietal networks is a neural correlate of the openness-psychoticism dimension. Participants in the Human Connectome Project (N = 1003) completed measures of psychoticism, openness, and intelligence. Resting state functional magnetic resonance imaging was used to identify intrinsic connectivity networks. Structural equation modeling revealed relations among personality, intelligence, and network coherence. Psychoticism, openness, and especially their shared variance were related positively to default network coherence and negatively to frontoparietal coherence. These associations remained after controlling for intelligence. Intelligence was positively related to frontoparietal coherence. Research suggests that psychoticism and openness are linked in part through their association with connectivity in networks involving experiential simulation and cognitive control. We propose a model of psychosis risk that highlights roles of the default and frontoparietal networks. Findings echo research on functional connectivity in psychosis patients, suggesting shared mechanisms across the personality-psychopathology continuum.

Role of rs454214 in Personality mediated Depression and Subjective Well-being

Happiness and depression are interlinked and both heritable, while personality, as an important predictor of them, shares the genetic basis with them. We conjecture that genetic factors of depression can affect both depressive symptoms (DS) and subjective well-being (SWB), while personality traits play important roles in mediating this process. In this study, 878 Han Chinese college freshmen and 384 Han Chinese patients with the major depressive disorder (MDD) were included. SNPs were genotyped using AGENA MassARRAY iPLEX technology and we investigated an important MDD variant rs454214. Correlation, association and mediation analysis were employed, aiming to decipher the complex relationship between SWB, DS, personality traits and the genetic variant. Association study indicated that rs454214 was not only associated with both SWB and DS (P < 0.05), but also possibly linked to MDD. Mediational analysis showed that rs454214 had no direct effect on SWB and DS, but had a significant indirect effect through personality traits, i.e., Extraversion, Neuroticism, Agreeableness and Openness to Experience or SWB, Extraversion, Neuroticism and Agreeableness for DS. This study found a shared genetic basis for happiness and depression; the causal process could be better explained if personality traits are taken as mediating factors.

The function of the hippocampus and middle temporal gyrus in forming new associations and concepts during the processing of novelty and usefulness features in creative designs

Creative thought relies on the reorganization of existing knowledge to generate novel and useful concepts. However, how these new concepts are formed, especially through the processing of novelty and usefulness (which are usually regarded as the key properties of creativity), is not clear. Taking familiar and useful (FU) objects/designs as the starting point or fundamental baseline, we modified them into novel and useless (NS) objects/designs or novel and useful (NU) ones (i.e., truly creative ones) to investigate how the features of novelty and usefulness are processed (processing of novelty: NU minus FU; processing of usefulness: NU minus NS). Specifically, we predicted that the creative integration of novelty and usefulness entails not only the formation of new associations, which could be critically mediated by the hippocampus and adjacent medial temporal lobe (MTL) areas, but also the formation of new concepts or categories, which is supported by the middle temporal gyrus (MTG). We found that both the MTL and the MTG were involved in the processing of novelty and usefulness. The MTG showed distinctive patterns of information processing, reflected by strengthened functional connectivity with the hippocampus to construct new concepts and strengthened functional connectivity with the executive control system to break the boundaries of old concepts. Additionally, participants' subjective evaluations of concept distance showed that the distance between the familiar concept (FU) and the successfully constructed concept (NU) was larger than that between the FU and the unsuccessfully constructed concept (NS), and this pattern was found to correspond to the patterns of their neural representations in the MTG. These findings demonstrate the critical mechanism by which new associations and concepts are formed during novelty and usefulness processing in creative design; this mechanism may be critically mediated by the hippocampus-MTG connection.

Associations between personality and whole-brain functional connectivity at rest: Evidence across the adult lifespan

INTRODUCTION

Personality is associated with cognitive, emotional, and social functioning, and can play a role in age-related cognitive decline and dementia risk; however, little is known about the brain dynamics underlying personality characteristics, and whether they are moderated by age.

METHODS

We investigated the associations between personality and resting-state functional MRI data from 365 individuals across the adult lifespan (20-80 years). Participants completed the 50-item International Personality Item Pool and a resting-state imaging protocol on a 3T MRI scanner. Within-network connectivity values were computed based on predefined networks. Regression analyzes were conducted in order to investigate personality-connectivity associations, as well as moderation by age. All models controlled for potential confounders (such as age, sex, education, IQ, and the other personality traits).

RESULTS

We found that openness was positively associated with connectivity in the default-mode network, neuroticism was negatively associated with both the ventral and dorsal attention networks, and agreeableness was negatively associated with the dorsal attention network. In addition, age moderated the association between conscientiousness and the frontoparietal network, indicating that this association become stronger in older age.

CONCLUSIONS

Our findings demonstrate that personality is associated with brain connectivity, which may contribute to identifying personality profiles that play a role in protection against or risk for age-related brain changes and dementia.

Personality Factors' Impact on the Structural Integrity of Mentalizing Network in Old Age: A Combined PET-MRI Study

The mentalizing network (MN) treats social interactions based on our understanding of other people's intentions and includes the medial prefrontal cortex (mPFC), temporoparietal junction (TPJ), posterior cingulate cortex (PCC), precuneus (PC), and amygdala. Not all elders are equally affected by the aging-related decrease of mentalizing abilities. Personality has recently emerged as a strong determinant of functional connectivity in MN areas. However, its impact on volumetric changes across the MN in brain aging is still unknown. To address this issue, we explored the determinants of volume decrease in MN components including amyloid burden, personality, and APOE genotyping in a previously established cohort of 130 healthy elders with a mean follow-up of 54 months. Personality was assessed with the Neuroticism Extraversion Openness Personality Inventory-Revised. Regression models corrected for multiple comparisons were used to identify predictors of volume loss including time, age, sex, personality, amyloid load, presence of APOE epsilon 4 allele, and cognitive evolution. In cases with higher Agreeableness scores, there were lower volume losses in PCC, PC, and amygdala bilaterally. This was also the case for the right mPFC in elders displaying lower Agreeableness and Conscientiousness. In multiple regression models, the effect of Agreeableness was still observed in left PC and right amygdala and that of Conscientiousness was still observed in right mPFC volume loss (26.3% of variability, significant age and sex). Several Agreeableness (Modesty) and Conscientiousness (order, dutifulness, achievement striving, and self-discipline) facets were positively related to increased volume loss in cortical components of the MN. In conclusion, these data challenge the beneficial role of higher levels of Agreeableness and Conscientiousness in old age, showing that they are associated with an increased rate of volume loss within the MN.

Functional coupling of brain networks during creative idea generation and elaboration in the figural domain

The neuroscientific investigation of creative cognition has advanced by considering the functional connectivity between brain regions and its dynamic changes over time, which are consistent with stages in the ideation process. Surprisingly, although the communication between neuronal networks takes place in a time-scale of milliseconds, EEG studies investigating a time-course in cortico-cortical communication during creative ideation are rare and findings are typically restricted to the verbal domain. Therefore, this study examined functional coupling using EEG (task-related phase-locking in the upper-alpha range) during creative thinking in the figural domain. Using an innovative computerized experimental paradigm, we specifically investigated the stage of idea generation and the stage of idea elaboration in an adapted picture completion task. The findings confirmed a hypothesized increase of functional coupling from idea generation to elaboration, which was most pronounced in frontal-central as well as frontal-temporal networks. The connectivity in the frontal-parietal/occipital network already increased during idea generation and remained constant during elaboration. Importantly, more original participants generally showed higher functional connectivity in all brain networks. This elevated functional coupling with frontal brain regions might reflect increased executive processes related to internal attention, motor planning, and semantic selection processes supporting highly original thought in the figural domain.

The relationship among resting-state brain activity and connectivity, agreeableness and displaced aggression: Two possible mediation models

BACKGROUND

Displaced aggression is a specific form of attack prompted by rumination on anger experiences and revenge thought which might lead to expression of anger on innocent people. There is sufficient evidence demonstrating the potential role of agreeableness in reducing displaced aggression in theory. However, little is known about the neural basis of displaced aggression and how agreeableness and the underlying neural mechanisms link to displaced aggression.

METHODS

In this investigation, we examined these issues on 123 college students by assessing resting-state brain activity (i.e. amplitude of low-frequency fluctuation, ALFF) and connectivity (i.e. resting-state functional connectivity, RSFC).

RESULTS

Whole-brain correlation analysis revealed that a higher level of displaced aggression was linked with decreased ALFF in the left dorsomedial prefrontal cortex (dmPFC) and decreased RSFC between the left dmPFC and left ventromedial prefrontal cortex (vmPFC). Mediation analysis further revealed that left dmPFC activity and the left dmPFC-vmPFC connectivity mediated the relationship between agreeableness and displaced aggression, as well as agreeableness mediated the relation between left dmPFC activity and the left dmPFC-vmPFC connectivity and displaced aggression.

LIMITATIONS

Only ALFF and RSFC were used as indicators of brain function in this study. The two mediation models need to be further tested by longitudinal design or experimental methods in further studies.

CONCLUSIONS

This study suggested that dmPFC and vmPFC might be the functional neural markers of displaced aggression and provided two possible mediation models regarding the relationship among the resting-state brain activity and connectivity, agreeableness and displaced aggression.

Intra-cortical myelin mediates personality differences

OBJECTIVE

Differences in myelination in the cortical mantle are important neurobiological mediators of variability in cognitive, emotional, and behavioral functioning. Past studies have found that personality traits reflecting such variability are linked to neuroanatomical and functional changes in prefrontal and temporo-parietal cortices. Whether these effects are partially mediated by the differences in intra-cortical myelin remains to be established.

METHOD

To test this hypothesis, we employed vertex-wise intra-cortical myelin maps in n = 1,003 people from the Human Connectome Project. Multivariate regression analyses were used to test for the relationship between intra-cortical myelin and each of the five-factor model's personality traits, while accounting for age, sex, intelligence quotient, total intracranial volume, and the remaining personality traits.

RESULTS

Neuroticism negatively related to frontal-pole myelin and positively to occipital cortex myelin. Extraversion positively related to superior parietal myelin. Openness negatively related to anterior cingulate myelin, while Agreeableness positively related to orbitofrontal myelin. Conscientiousness positively related to frontal-pole myelin and negatively to myelin content in the dorsal anterior cingulate cortex.

CONCLUSIONS

Intra-cortical myelin levels in brain regions with prolonged myelination are positively associated with personality traits linked to favorable outcome measures. These findings improve our understanding of the neurobiological underpinnings of variability in common behavioral dispositions.