Temporal variability-based alternations in dynamic functional networks in internet gaming disorder

BACKGROUND

Previous studies on resting-state functional connectivity (FC) in internet gaming disorder (IGD) have typically assumed that FC is static during the entire scan, neglecting the dynamic reorganization of brain networks. However, understanding the dynamic changes in functional networks is crucial for a comprehensive understanding of IGD, a complex and evolving disorder.

METHODS

Resting-state fMRI data were collected from 269 participants (132 IGD subjects, male/female: 72/60, and 137 recreational game users (RGUs), male/female: 85/52). At the network level (within-network and between-network), temporal variability indices were calculated for each group and subjected to independent samples t-tests.

RESULTS

Compared to RGUs, IGD individuals exhibited decreased within-network variability in the default mode network (DMN), increased within-network temporal variability in the ventral attention network (VAN), and increased between-network temporal variability in sensorimotor network (SMN) and VAN, SMN and limbic network (LN), VAN and LN.

CONCLUSIONS

Changes in temporal variability at the network level occur in participants with IGD, indicating impaired executive inhibitory functions and attention, as well as imbalances between sensory-attention, sensory-emotion, and emotion-motivation functions. These findings provide new insights into the dynamic functional organization of the brain in IGD, contributing to our understanding the neural basis of pathological gaming behaviors.

Resting-state EEG network variability predicts individual working memory behavior

Even during periods of rest, the brain exhibits spontaneous activity that dynamically fluctuates across spatially distributed regions in a globally coordinated manner, which has significant cognitive implications. However, the relationship between the temporal variability of resting-state networks and working memory (WM) remains largely unexplored. This study aims to address this gap by employing an EEG-based protocol combined with fuzzy entropy. First, we identified both flexible and robust patterns of dynamic resting-state networks. Subsequently, we observed a significant positive correlation between WM performance and network variability, particularly in connections associated with the frontal, right central, and right parietal lobes. Moreover, we found that the temporal variability of network properties was positively and significantly associated with WM performance. Additionally, distinct patterns of network variability were delineated, contributing to inter-individual differences in WM abilities, with these distinctions becoming more pronounced as task demands increased. Finally, using a multivariable predictive model based on these variability metrics, we effectively predicted individual WM performances. Notably, analogous analyses conducted in the source space validated the reproducibility of the temporal variability of resting-state networks in predicting individual WM behavior at higher spatial resolution, providing more precise anatomical localization of key brain regions. These results suggest that the temporal variability of resting-state networks reflects intrinsic dynamic changes in brain organization supporting WM and can serve as an objective predictor for individual WM behaviors.

Functional differentiation of the default and frontoparietal control networks predicts individual differences in creative achievement: evidence from macroscale cortical gradients

Much of the research on the neural correlates of creativity has emphasized creative cognition, and growing evidence suggests that creativity is related to functional properties of the default and frontoparietal control networks. The present work expands on this body of evidence by testing associations of creative achievement with connectivity profiles of brain networks assessed using macroscale cortical gradients. Using resting-state connectivity functional magnetic resonance imaging in 2 community samples (N's = 236 and 234), we found evidence that creative achievement is positively associated with greater functional dissimilarity between core regions of the default and frontoparietal control networks. These results suggest that creative achievement is supported by the ability of these 2 networks to carry out distinct cognitive roles. This research provides further evidence, using a cortical gradient approach, that individual differences in creative achievement can be predicted from functional properties of brain networks involved in higher-order cognition, and it aligns with past research on the functional connectivity correlates of creative task performance.

Changes on Cognition and Brain Network Temporal Variability After Pediatric Neurosurgery

BACKGROUND AND OBJECTIVES

Pediatric intracranial space-occupying lesions are common, with prognoses improving markedly in recent years, significantly extending survival. As such, there is an imperative to pay increased attention to the postoperative cognitive functions and brain network alterations in these children because these factors significantly influence their quality of life. Temporal variability (TV) analysis of brain networks captures the full extent of resting-state activities, reflecting cognitive functions and rehabilitation potential. However, previous research rarely uses TV analyses and most focus on adults or children after multidisciplinary treatments, not reflecting the combined effect caused by neurosurgery only and self-repair. This study gives our insights into this field from a holistic perspective.

METHODS

We studied 35 children with intracranial space-occupying lesions, analyzing pre- and postsurgery MRI and cognitive tests. We used TV analysis to assess changes and correlated imaging indicators with cognitive performance.

RESULTS

We observed a tendency for cognitive recovery after about 3 months postsurgery, primarily in the domains of social cognition and nonverbal reasoning. TV analysis of brain networks indicated increased nodal variability within systems such as the visual and sensorimotor networks, which are integral to external interactions. Correlative analysis showed that alterations in certain occipital regions were associated with changes in social cognition and nonverbal reasoning.

CONCLUSION

These findings suggest significant intrinsic repair in cognitive functions and brain networks at around 3 months postneurosurgery in children. This study not only enriches our comprehension of postoperative cognitive and brain network self-repair processes in children but also furnishes potential therapeutic targets for rehabilitation interventions and establishes a theoretical foundation for proactive surgical interventions.

Dynamic alterations in spontaneous neural activity in patients with attention-deficit/hyperactivity disorder: A resting-state fMRI study

BACKGROUND

To investigate the change of dynamic amplitude of low-frequency fluctuation (dALFF) and dynamic fractional amplitude of low-frequency fluctuation (dfALFF) in patients with attention-deficit/hyperactivity disorder (ADHD), and to explore whether dALFF/dfALFF can be used to distinguish ADHD from health controls (HCs).

METHODS

Forty-eight cases of clinically confirmed ADHD and forty-four cases of HCs were included in the present study. It was compared to the amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF), as well as the dynamic indicators dALFF and dfALFF. We investigated the relationship between clinical and dynamic indicators, and additionally performed voxel-based functional connectivity (FC) analysis. Finally, we developed an auxiliary diagnosis model.

RESULTS

Brain regions with increased dALFF variability of ADHD were located in right middle frontal gyrus (MFG), left inferior parietal lobe (IPL) and superior parietal gyrus (SPG) compared with HCs. Meanwhile, increased dfALFF variability was also observed in left lingual gyrus (LING), right MFG and left middle occipital gyrus (MOG) in ADHD compared to HCs. Neuropsychological scale scores correlated with some dALFF and dfALFF indicators. Reduced FC was found between the left IPL and right cerebellum crus II in ADHD compared with HCs. With dALFF and dfALFF variability as features, we achieved a good area under the curve and an accurate classification.

CONCLUSION

This study offers new valuable insights into the cerebral dysfunction associated with ADHD from the standpoint of dynamic local brain activity. The understanding of dALFF/dfALFF variability can contribute to the comprehension of neurophysiological mechanisms and potentially aid in the diagnosis of ADHD.

Dynamic cycles between brain states during creative storytelling

Many theories suggest that creative thinking involves a dynamic transition between different mental states, yet empirical evidence supporting this notion remains scarce. The dual process model proposes that spontaneous thinking and deliberate thinking drive the dwell in and the transitions between different mental states during creative thinking, but there is a debate over whether the two types of thinking operate in parallel or in sequence. To address these gaps, we conducted a functional magnetic resonance imaging (fMRI) study in 41 college students during a creative storytelling task. We then compared the dynamic brain states in creative versus uncreative storytelling to identify key brain states associated with creative thinking. And we further performed correlation analysis between these key brain states with performance of various creative tasks, trying to link the key brain states with different cognitive processes. The results showed that two key brain states are associated with creative thinking, with one involving whole-brain synchronization and the other involving the synchronization of four networks, including the default mode network and the control network. The transition patterns between the key brain states provide tentative evidence for dynamic circulation between different mental states during creative storytelling. Using a deep learning approach, we demonstrate an alternating interaction between spontaneous and deliberate thinking, driving dwelling in and the transitions between different brain states. These findings deepen our understanding of the cognitive and neural mechanisms underlying creative thinking.

Mapping Neuroimaging Findings of Creativity and Brain Disease Onto a Common Brain Circuit

Importance

Creativity is important for problem solving, adaptation to a changing environment, and innovation. Neuroimaging studies seeking to map creativity have yielded conflicting results, and studies of patients with brain disease have reported both decreases and paradoxical increases in creativity, leaving the neural basis of creativity unclear.

Objective

To investigate the brain circuit underlying creativity and assess its association with brain injury and neurodegenerative disease.

Design, Setting, and Participants

This study examined neuroimaging coordinates from a meta-analysis of 36 studies published between 2004 and 2019 associated with increased activity during creative tasks in healthy participants. A validated method termed coordinate network mapping and a database of resting-state functional connectivity from 1000 healthy individuals were used to test whether these coordinates mapped to a common brain circuit. Specificity was assessed through comparison to random coordinates and coordinates from working memory tasks in healthy participants. Reproducibility was assessed using an independent dataset of coordinates from additional studies of creativity in healthy participants. Finally, alignment with effects of focal brain damage on creativity was tested using data from patients with brain lesions and coordinates of brain atrophy from 7 different neurodegenerative disorders.

Main Outcomes and Measures

The primary outcomes were creativity or no creativity and alignment with a creativity circuit or no alignment.

Results

Creativity tasks activated heterogenous locations, with coordinates scattered across many different brain regions (415 coordinates derived from 857 healthy participants; pooled mean [SD] age, 24.1 [6.91] years; 461 [54%] female). However, these activation coordinates were part of a common brain circuit, defined by negative connectivity to the right frontal pole. This result was consistent across creative domains, reproducible in an independent dataset (383 coordinates derived from 691 participants) and specific to creativity when compared with random gray matter coordinates (n = 415) or coordinates activated by working memory tasks (3072 coordinates derived from 2900 healthy participants). Damage to this creativity circuit by lesions (n = 56 patients) or neurodegenerative disease (2262 coordinates derived from 4804 patients) aligned with both decreases and increases in creativity observed in these disorders.

Conclusions and Relevance

Findings from this study suggest that brain regions activated by creativity tasks map to a brain circuit defined by negative functional connectivity to the right frontal pole. Damage to this circuit aligned with changes in creativity observed in individuals with certain brain diseases, including paradoxical creativity increases.

Dynamic switching between brain networks predicts creative ability

Creativity is hypothesized to arise from a mental state which balances spontaneous thought and cognitive control, corresponding to functional connectivity between the brain's Default Mode (DMN) and Executive Control (ECN) Networks. Here, we conduct a large-scale, multi-center examination of this hypothesis. Employing a meta-analytic network neuroscience approach, we analyze resting-state fMRI and creative task performance across 10 independent samples from Austria, Canada, China, Japan, and the United States (N = 2433)-constituting the largest and most ethnically diverse creativity neuroscience study to date. Using time-resolved network analysis, we investigate the relationship between creativity (i.e., divergent thinking ability) and dynamic switching between DMN and ECN. We find that creativity, but not general intelligence, can be reliably predicted by the number of DMN-ECN switches. Importantly, we identify an inverted-U relationship between creativity and the degree of balance between DMN-ECN switching, suggesting that optimal creative performance requires balanced brain network dynamics. Furthermore, an independent task-fMRI validation study (N = 31) demonstrates higher DMN-ECN switching during creative idea generation (compared to a control condition) and replicates the inverted-U relationship. Therefore, we provide robust evidence across multi-center datasets that creativity is tied to the capacity to dynamically switch between brain networks supporting spontaneous and controlled cognition.

From brain connectivity to cognitive function: Dissecting the salience network in pediatric BECTS-ESES

BACKGROUND

Benign childhood epilepsy with centrotemporal spikes (BECTS), a common pediatric epilepsy, may lead to cognitive decline when compounded by Electrical Status Epilepticus during Sleep (ESES). Emerging evidence suggests that disruptions in the Salience Network (SN) contribute significantly to the cognitive deficits observed in BECTS-ESES. Our study rigorously investigates the dynamic functional connectivity (dFC) within the SN and its correlation with cognitive impairments in BECTS-ESES, employing advanced neuroimaging and neuropsychological assessments.

METHODS

In this research, 45 patients diagnosed with BECTS-ESES and 55 age-matched healthy controls (HCs) participated. We utilized resting-state functional magnetic resonance imaging (fMRI) and Independent Component Analysis (ICA) to identify three fundamental SN nodes: the right Anterior Insula (rAI), left Anterior Insula (lAI), and the Anterior Cingulate Cortex (ACC). A two-sample t-test facilitated the comparison of dFC between these pivotal regions and other brain areas.

RESULTS

Significantly, the BECTS-ESES group demonstrated increased dFC, particularly between the ACC and the right Middle Occipital Gyrus, and from the rAI to the right Superior Parietal Gyrus and Cerebellum, and from the lAI to the left Postcentral Gyrus. Such dFC augmentations provide neural insights potentially explaining the neuropsychological deficits in BECTS-ESES children. Employing comprehensive neuropsychological evaluations, we mapped these dFC disruptions to specific cognitive impairments encompassing memory, executive functioning, language, and attention. Through multiple regression analysis and path analysis, a preliminary but compelling association was discovered linking dFC disturbances directly to cognitive impairments. These findings underscore the critical role of SN disruptions in BECTS-ESES cognitive dysfunctions.

LIMITATION

Our cross-sectional design and analytic methods preclude definitive mediation models and causal inferences, leaving the precise nature of dFC's mediating role and its direct impact by BECTS-ESES partially unresolved. Future longitudinal and confirmatory studies are needed to comprehensively delineate these associations.

CONCLUSION

Our study heralds dFC within the SN as a vital biomarker for cognitive impairment in pediatric epilepsy, advocating for targeted cognitive-specific interventions in managing BECTS-ESES. The preliminary nature of our findings invites further studies to substantiate these associations, offering profound implications for the prognosis and therapeutic strategies in BECTS-ESES, thereby underlining the importance of this research in the field of pediatric neurology and epilepsy management.

A theory of hippocampal function: New developments

We develop further here the only quantitative theory of the storage of information in the hippocampal episodic memory system and its recall back to the neocortex. The theory is upgraded to account for a revolution in understanding of spatial representations in the primate, including human, hippocampus, that go beyond the place where the individual is located, to the location being viewed in a scene. This is fundamental to much primate episodic memory and navigation: functions supported in humans by pathways that build 'where' spatial view representations by feature combinations in a ventromedial visual cortical stream, separate from those for 'what' object and face information to the inferior temporal visual cortex, and for reward information from the orbitofrontal cortex. Key new computational developments include the capacity of the CA3 attractor network for storing whole charts of space; how the correlations inherent in self-organizing continuous spatial representations impact the storage capacity; how the CA3 network can combine continuous spatial and discrete object and reward representations; the roles of the rewards that reach the hippocampus in the later consolidation into long-term memory in part via cholinergic pathways from the orbitofrontal cortex; and new ways of analysing neocortical information storage using Potts networks.

The memory systems of the human brain and generative artificial intelligence

Generative Artificial Intelligence foundation models (for example Generative Pre-trained Transformer - GPT - models) can generate the next token given a sequence of tokens. How can this 'generative AI' be compared with the 'real' intelligence of the human brain, when for example a human generates a whole memory in response to an incomplete retrieval cue, and then generates further prospective thoughts? Here these two types of generative intelligence, artificial in machines and real in the human brain are compared, and it is shown how when whole memories are generated by hippocampal recall in response to an incomplete retrieval cue, what the human brain computes, and how it computes it, are very different from generative AI. Key differences are the use of local associative learning rules in the hippocampal memory system, and of non-local backpropagation of error learning in AI. Indeed, it is argued that the whole operation of the human brain is performed computationally very differently to what is implemented in generative AI. Moreover, it is emphasized that the primate including human hippocampal system includes computations about spatial view and where objects and people are in scenes, whereas in rodents the emphasis is on place cells and path integration by movements between places. This comparison with generative memory and processing in the human brain has interesting implications for the further development of generative AI and for neuroscience research.

Neural Dynamics During the Generation and Evaluation of Creative and Non-Creative Ideas

What are the neural dynamics that drive creative thinking? Recent studies have provided much insight into the neural mechanisms of creative thought. Specifically, the interaction between the executive control, default mode, and salience brain networks has been shown to be an important marker of individual differences in creative ability. However, how these different brain systems might be recruited dynamically during the two key components of the creative process-generation and evaluation of ideas-remains far from understood. In the current study we applied state-of-the-art network neuroscience methodologies to examine the neural dynamics related to the generation and evaluation of creative and non-creative ideas using a novel within-subjects design. Participants completed two functional magnetic resonance imaging sessions, taking place a week apart. In the first imaging session, participants generated either creative (alternative uses) or non-creative (common characteristics) responses to common objects. In the second imaging session, participants evaluated their own creative and non-creative responses to the same objects. Network neuroscience methods were applied to examine and directly compare reconfiguration, integration, and recruitment of brain networks during these four conditions. We found that generating creative ideas led to significantly higher network reconfiguration than generating non-creative ideas, whereas evaluating creative and non-creative ideas led to similar levels of network integration. Furthermore, we found that these differences were attributable to different dynamic patterns of neural activity across the executive control, default mode, and salience networks. This study is the first to show within-subject differences in neural dynamics related to generating and evaluating creative and non-creative ideas.

Psychological resilience-related functional connectomes predict creative personality

Both psychological resilience and creativity are complex concepts that have positive effects on individual adaptation. Previous studies have shown overlaps between the key brain regions or brain functional networks related to psychological resilience and creativity. However, no direct experimental evidence has been provided to support the assumption that psychological resilience and creativity share a common brain basis. Therefore, the present study investigated the relationship between psychological resilience and creativity using neural imaging method with a machine learning approach. At the behavioral level, we found that psychological resilience was positively related to creative personality. Predictive analysis based on static functional connectivity (FC) and dynamic FC demonstrated that FCs related to psychological resilience could effectively predict an individual's creative personality score. Both the static FC and dynamic FC were mainly located in the default mode network. These results prove that psychological resilience and creativity share a common brain functional basis. These findings also provide insights into the possibility of promoting individual positive adaptation from negative events or situations in a creative way.

Computer gaming alters resting-state brain networks, enhancing cognitive and fluid intelligence in players: evidence from brain imaging-derived phenotypes-wide Mendelian randomization

The debate on whether computer gaming enhances players' cognitive function is an ongoing and contentious issue. Aiming to delve into the potential impacts of computer gaming on the players' cognitive function, we embarked on a brain imaging-derived phenotypes (IDPs)-wide Mendelian randomization (MR) study, utilizing publicly available data from a European population. Our findings indicate that computer gaming has a positive impact on fluid intelligence (odds ratio [OR] = 6.264, P = 4.361 × 10-10, 95% confidence interval [CI] 3.520-11.147) and cognitive function (OR = 3.322, P = 0.002, 95% CI 1.563-7.062). Out of the 3062 brain IDPs analyzed, only one phenotype, IDP NET100 0378, was significantly influenced by computer gaming (OR = 4.697, P = 1.10 × 10-5, 95% CI 2.357-9.361). Further MR analysis suggested that alterations in the IDP NET100 0378 caused by computer gaming may be a potential factor affecting fluid intelligence (OR = 1.076, P = 0.041, 95% CI 1.003-1.153). Our MR study lends support to the notion that computer gaming can facilitate the development of players' fluid intelligence by enhancing the connectivity between the motor cortex in the resting-state brain and key regions such as the left dorsolateral prefrontal cortex and the language center.

EEG brain network variability is correlated with other pathophysiological indicators of critical patients in neurology intensive care unit

Continuous electroencephalogram (cEEG) plays a crucial role in monitoring and postoperative evaluation of critical patients with extensive EEG abnormalities. Recently, the temporal variability of dynamic resting-state functional connectivity has emerged as a novel approach to understanding the pathophysiological mechanisms underlying diseases. However, little is known about the underlying temporal variability of functional connections in critical patients admitted to neurology intensive care unit (NICU). Furthermore, considering the emerging field of network physiology that emphasizes the integrated nature of human organisms, we hypothesize that this temporal variability in brain activity may be potentially linked to other physiological functions. Therefore, this study aimed to investigate network variability using fuzzy entropy in 24-hour dynamic resting-state networks of critical patients in NICU, with an emphasis on exploring spatial topology changes over time. Our findings revealed both atypical flexible and robust architectures in critical patients. Specifically, the former exhibited denser functional connectivity across the left frontal and left parietal lobes, while the latter showed predominantly short-range connections within anterior regions. These patterns of network variability deviating from normality may underlie the altered network integrity leading to loss of consciousness and cognitive impairment observed in these patients. Additionally, we explored changes in 24-hour network properties and found simultaneous decreases in brain efficiency, heart rate, and blood pressure between approximately 1 pm and 5 pm. Moreover, we observed a close relationship between temporal variability of resting-state network properties and other physiological indicators including heart rate as well as liver and kidney function. These findings suggest that the application of a temporal variability-based cEEG analysis method offers valuable insights into underlying pathophysiological mechanisms of critical patients in NICU, and may present novel avenues for their condition monitoring, intervention, and treatment.

The unity and diversity of verbal and visuospatial creativity: Dynamic changes in hemispheric lateralisation

The investigation of similarities and differences in the mechanisms of verbal and visuospatial creative thinking has long been a controversial topic. Prior studies found that visuospatial creativity was primarily supported by the right hemisphere, whereas verbal creativity relied on the interaction between both hemispheres. However, creative thinking also involves abundant dynamic features that may have been ignored in the previous static view. Recently, a new method has been developed that measures hemispheric laterality from a dynamic perspective, providing new insight into the exploration of creative thinking. In the present study, dynamic lateralisation index was calculated with resting-state fMRI data. We combined the dynamic lateralisation index with sparse canonical correlation analysis to examine similarities and differences in the mechanisms of verbal and visuospatial creativity. Our results showed that the laterality reversal of the default mode network, fronto-parietal network, cingulo-opercular network and visual network contributed significantly to both verbal and visuospatial creativity and consequently could be considered the common neural mechanisms shared by these creative modes. In addition, we found that verbal creativity relied more on the language network, while visuospatial creativity relied more on the somatomotor network, which can be considered a difference in their mechanism. Collectively, these findings indicated that verbal and visuospatial creativity may have similar mechanisms to support the basic creative thinking process and different mechanisms to adapt to the specific task conditions. These findings may have significant implications for our understanding of the neural mechanisms of different types of creative thinking.

Resting-state network predicts the decision-making behaviors of the proposer during the ultimatum game

Objective. The decision-making behavior of the proposer is a key factor in achieving effective and equitable maintenance of social resources, particularly in economic interactions, and thus understanding the neurocognitive basis of the proposer's decision-making is a crucial issue. Yet the neural substrate of the proposer's decision behavior, especially from the resting-state network perspective, remains unclear.Approach. In this study, we investigated the relationship between the resting-state network and decision proposals and further established a multivariable model to predict the proposers' unfair offer rates in the ultimatum game.Main results.The results indicated the unfair offer rates of proposers are significantly related to the resting-state frontal-occipital and frontal-parietal connectivity in the delta band, as well as the network properties. And compared to the conservative decision group (low unfair offer rate), the risk decision group (high unfair offer rate) exhibited stronger resting-state long-range linkages. Finally, the established multivariable model did accurately predict the unfair offer rates of the proposers, along with a correlation coefficient of 0.466 between the actual and predicted behaviors.Significance. Together, these findings demonstrated that related resting-state frontal-occipital and frontal-parietal connectivity may serve as a dispositional indicator of the risky behaviors for the proposers and subsequently predict a highly complex decision-making behavior, which contributed to the development of artificial intelligence decision-making system with biological characteristics as well.

The body mass index is associated with increased temporal variability of functional connectivity in brain reward system

The reward system has been proven to be contributed to the vulnerability of obesity. Previous fMRI studies have shown abnormal functional connectivity of the reward system in obesity. However, most studies were based on static index such as resting-state functional connectivity (FC), ignoring the dynamic changes over time. To investigate the dynamic neural correlates of obesity susceptibility, we used a large, demographically well-characterized sample from the Human Connectome Project (HCP) to determine the relationship of body mass index (BMI) with the temporal variability of FC from integrated multilevel perspectives, i.e., regional and within- and between-network levels. Linear regression analysis was used to investigate the association between BMI and temporal variability of FC, adjusting for covariates of no interest. We found that BMI was positively associated with regional FC variability in reward regions, such as the ventral orbitofrontal cortex and visual regions. At the intra-network level, BMI was positively related to the variability of FC within the limbic network (LN) and default mode network (DMN). At the inter-network level, variability of connectivity of LN with DMN, frontoparietal, sensorimotor, and ventral attention networks showed positive correlations with BMI. These findings provided novel evidence for abnormal dynamic functional interaction between the reward network and the rest of the brain in obesity, suggesting a more unstable state and over-frequent interaction of the reward network and other attention and cognitive networks. These findings, thus, provide novel insight into obesity interventions that need to decrease the dynamic interaction between reward networks and other brain networks through behavioral treatment and neural modulation.

Altered resting-state network connectivity patterns for predicting attentional function in deaf individuals: An EEG study

Multiple aspects of brain development are influenced by early sensory loss such as deafness. Despite growing evidence of changes in attentional functions for prelingual profoundly deaf, the brain mechanisms underlying these attentional changes remain unclear. This study investigated the relationships between differential attention and the resting-state brain network difference in deaf individuals from the perspective of brain network connectivity. We recruited 36 deaf individuals and 34 healthy controls (HC). We recorded each participant's resting-state electroencephalogram (EEG) and the event-related potential (ERP) data from the Attention Network Test (ANT). The coherence (COH) method and graph theory were used to build brain networks and analyze network connectivity. First, the ERPs of analysis in task states were investigated. Then, we correlated the topological properties of the network functional connectivity with the ERPs. The results revealed a significant correlation between frontal-occipital connection in the resting state and the amplitude of alert N1 amplitude in the alpha band. Specifically, clustering coefficients and global and local efficiency correlate negatively with alert N1 amplitude, whereas the characteristic path length positively correlates with alert N1 amplitude. In addition, deaf individuals exhibited weaker frontal-occipital connections compared to the HC group. In executive control, the deaf group had longer reaction times and larger P3 amplitudes. However, the orienting function did not significantly differ from the HC group. Finally, the alert N1 amplitude in the ANT task for deaf individuals was predicted using a multiple linear regression model based on resting-state EEG network properties. Our results suggest that deafness affects the performance of alerting and executive control while orienting functions develop similarly to hearing individuals. Furthermore, weakened frontal-occipital connections in the deaf brain are a fundamental cause of altered alerting functions in the deaf. These results reveal important effects of brain networks on attentional function from the perspective of brain connections and provide potential physiological biomarkers to predicting attention.

Temporal Stability of the Dynamic Resting-State Functional Brain Network: Current Measures, Clinical Research Progress, and Future Perspectives

Based on functional magnetic resonance imaging and multilayer dynamic network model, the brain network's quantified temporal stability has shown potential in predicting altered brain functions. This manuscript aims to summarize current knowledge, clinical research progress, and future perspectives on brain network's temporal stability. There are a variety of widely used measures of temporal stability such as the variance/standard deviation of dynamic functional connectivity strengths, the temporal variability, the flexibility (switching rate), and the temporal clustering coefficient, while there is no consensus to date which measure is the best. The temporal stability of brain networks may be associated with several factors such as sex, age, cognitive functions, head motion, circadian rhythm, and data preprocessing/analyzing strategies, which should be considered in clinical studies. Multiple common psychiatric disorders such as schizophrenia, major depressive disorder, and bipolar disorder have been found to be related to altered temporal stability, especially during the resting state; generally, both excessively decreased and increased temporal stabilities were thought to reflect disorder-related brain dysfunctions. However, the measures of temporal stability are still far from applications in clinical diagnoses for neuropsychiatric disorders partly because of the divergent results. Further studies with larger samples and in transdiagnostic (including schizoaffective disorder) subjects are warranted.

The optimal balance of controlled and spontaneous processing in insight problem solving: fMRI evidence from Chinese idiom guessing

Cognitive control is a key factor in insight generation. However, the neurocognitive mechanisms underlying the generation of insight for different cognitive control remain poorly understood. This study developed a parametric fMRI design, wherein hints for solving Chinese idiom riddles were gradually provided in a stepwise manner (from the first hint, H1, to the final hint, H4). By classifying the step-specific items solved in different hint-uncovering steps/conditions, we could identify insightful responses for different levels of spontaneous or controlled processing. At the behavioral level, the number of insightful problem solving trials reached the maximum at a intermediate level of the cognitively controlled processing and the spontaneously idea generating in H3, while the bilateral insular cortex and thalamus showed the robust engagement, implying the function of these regions in making the optimal balance between external hint processing and internal generated ideas. In addition, we identified brain areas, including the dorsolateral prefrontal cortex (dlPFC), angular gyrus (AG), dorsal anterior cingulate cortex (dACC), and precuneus (PreC), whose activities were parametrically increased with the levels of controlled (from H1 to H4) insightful processing which were increasingly produced by the sequentially revealed hints. Further representational similarity analysis (RSA) found that spontaneous processing in insight featured greater within-condition representational variabilities in widely distributed regions in the executive, salience, and default networks. Altogether, the present study provided new evidence for the relationship between the process of cognitive control and that of spontaneous idea generation in insight problem solving and demystified the function of the insula and thalamus as an interactive interface for the optimal balance of these two processes.

The relationships between dynamic resting-state networks and social behavior in autism spectrum disorder revealed by fuzzy entropy-based temporal variability analysis of large-scale network

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized by a core deficit in social processes. However, it is still unclear whether the core clinical symptoms of the disorder can be reflected by the temporal variability of resting-state network functional connectivity (FC). In this article, we examined the large-scale network FC temporal variability at the local region, within-network, and between-network levels using the fuzzy entropy technique. Then, we correlated the network FC temporal variability to social-related scores. We found that the social behavior correlated with the FC temporal variability of the precuneus, parietal, occipital, temporal, and precentral. Our results also showed that social behavior was significantly negatively correlated with the temporal variability of FC within the default mode network, between the frontoparietal network and cingulo-opercular task control network, and the dorsal attention network. In contrast, social behavior correlated significantly positively with the temporal variability of FC within the subcortical network. Finally, using temporal variability as a feature, we construct a model to predict the social score of ASD. These findings suggest that the network FC temporal variability has a close relationship with social behavioral inflexibility in ASD and may serve as a potential biomarker for predicting ASD symptom severity.

Chronic Mild Traumatic Brain Injury: Aberrant Static and Dynamic Connectomic Features Identified Through Machine Learning Model Fusion

Traumatic Brain Injury (TBI) is a frequently occurring condition and approximately 90% of TBI cases are classified as mild (mTBI). However, conventional MRI has limited diagnostic and prognostic value, thus warranting the utilization of additional imaging modalities and analysis procedures. The functional connectomic approach using resting-state functional MRI (rs-fMRI) has shown great potential and promising diagnostic capabilities across multiple clinical scenarios, including mTBI. Additionally, there is increasing recognition of a fundamental role of brain dynamics in healthy and pathological cognition. Here, we undertake an in-depth investigation of mTBI-related connectomic disturbances and their emotional and cognitive correlates. We leveraged machine learning and graph theory to combine static and dynamic functional connectivity (FC) with regional entropy values, achieving classification accuracy up to 75% (77, 74 and 76% precision, sensitivity and specificity, respectively). As compared to healthy controls, the mTBI group displayed hypoconnectivity in the temporal poles, which correlated positively with semantic (r = 0.43, p < 0.008) and phonemic verbal fluency (r = 0.46, p < 0.004), while hypoconnectivity in the right dorsal posterior cingulate correlated positively with depression symptom severity (r = 0.54, p < 0.0006). These results highlight the importance of residual FC in these regions for preserved cognitive and emotional function in mTBI. Conversely, hyperconnectivity was observed in the right precentral and supramarginal gyri, which correlated negatively with semantic verbal fluency (r=-0.47, p < 0.003), indicating a potential ineffective compensatory mechanism. These novel results are promising toward understanding the pathophysiology of mTBI and explaining some of its most lingering emotional and cognitive symptoms.

Dissociation of categorical and coordinate spatial relations on dynamic network organization states

Humans can flexibly represent both categorical and coordinate spatial relations. Previous research has mainly focused on hemisphere lateralization in representing these two types of spatial relations, but little is known about how distinct network organization states support representations of the two. Here we used dynamic resting-state functional connectivity (FC) to explore this question. To do this, we separated a meta-identified navigation network into a ventral and two other subnetworks. We revealed a Weak State and a Strong State within the ventral subnetwork and a Negative State and a Positive State between the ventral and other subnetworks. Further, we found the Weak State (i.e., weak but positive FC) within the ventral subnetwork was related to the ability of categorical relation recognition, suggesting that the representation of categorical spatial relations was related to weak integration among focal regions in the navigation network. In contrast, the Negative State (i.e., negative FC) between the ventral and other subnetworks was associated with the ability of coordinate relation processing, suggesting that the representation of coordinate spatial relations may require competitive interactions among widely distributed regions. In sum, our study provides the first empirical evidence revealing different focal and distributed organizations of the navigation network in representing different types of spatial information.

Comparing transcranial direct current stimulation and transcranial random noise stimulation over left dorsolateral prefrontal cortex and left inferior frontal gyrus: Effects on divergent and convergent thinking

The essential role of creativity has been highlighted in several human knowledge areas. Regarding the neural underpinnings of creativity, there is evidence about the role of left dorsolateral prefrontal cortex (DLPFC) and left inferior frontal gyrus (IFG) on divergent thinking (DT) and convergent thinking (CT). Transcranial stimulation studies suggest that the left DLPFC is associated with both DT and CT, whereas left IFG is more related to DT. However, none of the previous studies have targeted both hubs simultaneously and compared transcranial direct current stimulation (tDCS) and random noise stimulation (tRNS). Additionally, given the relationship between cognitive flexibility and creativity, we included it in order to check if the improvement in creativity may be mediated by cognitive flexibility. In this double-blind, between-subjects study, 66 healthy participants were randomly assigned to one of three groups (N = 22) that received a transcranial direct current stimulation (tDCS), transcranial random noise stimulation (tRNS), or sham for 20 min. The tDCS group received 1.5 mA with the anode over the left DLPFC and cathode over the left IFG. Locations in tRNS group were the same and they received 1.5 mA of high frequency tRNS (100-500 Hz). Divergent thinking was assessed before (baseline) and during stimulation with unusual uses (UU) and picture completion (PC) subtests from Torrance Creative thinking Test, whereas convergent thinking was evaluated with the remote association test (RAT). Stroop test was included to assess cognitive flexibility. ANCOVA results of performance under stimulation (controlling for baseline performance) showed that there were significant differences in PC (F = 3.35, p = 0.042, n p 2 = 0.10) but not in UU (F = 0.61, p = 0.546) and RAT (F = 2.65, p = 0.079) scores. Post-hoc analyses showed that tRNS group had significantly higher scores compared to sham (p = 0.004) in PC. More specifically, tRNS showed higher performance in fluency (p = 0.012) and originality (p = 0.021) dimensions of PC compared to sham. Regarding cognitive flexibility, we did not find any significant effect of any of the stimulation groups (F = 0.34, p = 0.711). Therefore, no further mediation analyses were performed. Finally, the group that received tDCS reported more adverse effects than sham group (F = 3.46, p = 0.035). Altogether, these results suggest that tRNS may have some advantages over tDCS in DT.

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.

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

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

Creative problem solving in knowledge-rich contexts

Creative problem solving (CPS) in real-world contexts often relies on reorganization of existing knowledge to serve new, problem-relevant functions. However, classic creativity paradigms that minimize knowledge content are generally used to investigate creativity, including CPS. We argue that CPS research should expand consideration of knowledge-rich problem contexts, both in novices and experts within specific domains. In particular, paradigms focusing on creative analogical transfer of knowledge may reflect CPS skills that are applicable to real-world problem solving. Such paradigms have begun to provide process-level insights into cognitive and neural characteristics of knowledge-rich CPS and point to multiple avenues for fruitfully expanding inquiry into the role of crystalized knowledge in creativity.

Abnormal dynamic functional connectivity after sleep deprivation from temporal variability perspective

Sleep deprivation (SD) is very common in modern society and regarded as a potential causal mechanism of several clinical disorders. Previous neuroimaging studies have explored the neural mechanisms of SD using magnetic resonance imaging (MRI) from static (comparing two MRI sessions [one after SD and one after resting wakefulness]) and dynamic (using repeated MRI during one night of SD) perspectives. Recent SD researches have focused on the dynamic functional brain organization during the resting-state scan. Our present study adopted a novel metric (temporal variability), which has been successfully applied to many clinical diseases, to examine the dynamic functional connectivity after SD in 55 normal young subjects. We found that sleep-deprived subjects showed increased regional-level temporal variability in large-scale brain regions, and decreased regional-level temporal variability in several thalamus subregions. After SD, participants exhibited enhanced intra-network temporal variability in the default mode network (DMN) and increased inter-network temporal variability in numerous subnetwork pairs. Furthermore, we found that the inter-network temporal variability between visual network and DMN was negative related with the slowest 10% respond speed (β = -.42, p = 5.57 × 10^-4 ) of the psychomotor vigilance test after SD following the stepwise regression analysis. In conclusion, our findings suggested that sleep-deprived subjects showed abnormal dynamic brain functional configuration, which provides new insights into the neural underpinnings of SD and contributes to our understanding of the pathophysiology of clinical disorders.

Brain Structural Correlates of Dispositional Insight and the Mediation Role of Neuroticism in Young Adults

Studies on the neural correlates of episodic insight have made significant progress in the past decades. However, the neural mechanisms underlying dispositional insight are largely unknown. In the present study, we recruited forty-four young, healthy adults and performed several analyses to reveal the neural mechanisms of dispositional insight. Firstly, a voxel-based morphometry (VBM) technique was used to explore the structural brain mechanisms of dispositional insight. We found that dispositional insight was significantly and negatively correlated with the regional gray matter volume (rGMV) in the left thalamus (TLM.L), right temporoparietal junction (TPJ.R), and left dorsal medial prefrontal cortex (DMPFC.L). Secondly, we performed a seed-based resting-state functional connectivity (RSFC) analysis to complement the findings of VBM analysis further. The brain regions of TLM.L, DMPFC.L, and TPJ.R were selected as seed regions. We found that dispositional insight was associated with altered RSFC between the DMPFC.L and bilateral TPJ, between the TPJ.R and left dorsolateral prefrontal cortex, left ventrolateral prefrontal cortex, DMPFC.L, TPJ.L, right insula, and right cerebellum. Finally, a mediation analysis found that the personality of neuroticism partially mediated the relationship between the brain region of TLM.L and dispositional insight. These findings imply that dispositional insight has a specific functional and structural neural mechanism. The personality of neuroticism may play a pivotal role in the processes of dispositional insight.

Altered temporal variability in brain functional connectivity identified by fuzzy entropy underlines schizophrenia deficits

Investigation of the temporal variability of resting-state brain networks informs our understanding of how neural connectivity aggregates and disassociates over time, further shedding light on the aberrant neural interactions that underlie symptomatology and psychosis development. In the current work, an electroencephalogram-based sliding window analysis was utilized for the first time to measure the nonlinear complexity of dynamic resting-state brain networks of schizophrenia (SZ) patients by applying fuzzy entropy. The results of this study demonstrated the attenuated temporal variability among multiple electrodes that were distributed in the frontal and right parietal lobes for SZ patients when compared with healthy controls (HCs). Meanwhile, a concomitant strengthening of the posterior and peripheral flexible connections that may be attributed to the excessive alertness or sensitivity of SZ patients to the external environment was also revealed. These temporal fluctuation distortions combined reflect an abnormality in the coordination of functional network switching in SZ, which is further the source of worse task performance (i.e., P300 amplitude) and the negative relationship between individual complexity metrics and P300 amplitude. Notably, when using the network metrics as features, multiple linear regressions of P300 amplitudes were also exactly achieved for both the SZ and HC groups. These findings shed light on the pathophysiological mechanisms of SZ from a temporal variability perspective and provide potential biomarkers for quantifying SZ's progressive neurophysiological deterioration.

The trait and state negative affect can be separately predicted by stable and variable resting-state functional connectivity

BACKGROUND

Many emotional experiences such as anxiety and depression are influenced by negative affect (NA). NA has both trait and state features, which play different roles in physiological and mental health. Attending to NA common to various emotional experiences and their trait-state features might help deepen the understanding of the shared foundation of related emotional disorders.

METHODS

The principal component of five measures was calculated to indicate individuals' NA level. Applying the connectivity-based correlation analysis, we first identified resting-state functional connectives (FCs) relating to NA in sample 1 (n = 367), which were validated through an independent sample (n = 232; sample 2). Next, based on the variability of FCs across large timescale, we further divided the NA-related FCs into high- and low-variability groups. Finally, FCs in different variability groups were separately applied to predict individuals' neuroticism level (which is assumed to be the core trait-related factor underlying NA), and the change of NA level (which represents the state-related fluctuation of NA).

RESULTS

The low-variability FCs were primarily within the default mode network (DMN) and between the DMN and dorsal attention network/sensory system and significantly predicted trait rather than state NA. The high-variability FCs were primarily between the DMN and ventral attention network, the fronto-parietal network and DMN/sensory system, and significantly predicted the change of NA level.

CONCLUSIONS

The trait and state NA can be separately predicted by stable and variable spontaneous FCs with different attentional processes and emotion regulatory mechanisms, which could deepen our understanding of NA.

Sleep Quality Modulates the Association between Dynamic Functional Network Connectivity and Cognitive Function in Healthy Older Adults

Aging is associated with changes in sleep, brain activity, and cognitive function, as well as the association among these factors; however, the precise nature of these changes has not been elucidated. This study systematically investigated the modulatory effect of sleep on the relationship between brain functional network connectivity (FNC) and cognitive function in older adults. In total, 107 community-dwelling healthy older adults were recruited and assigned into poor sleep and good sleep groups based on the Pittsburgh Sleep Quality Index. The static functional network connectivity (sFNC), the temporal variability of dynamic FNC (dFNC) from variance (dFNC-var), and the dFNC from clustering state (dFNC-state) were calculated. Corresponding cognition-predictive models were constructed for each sleep group. dFNC but not sFNC, was able to significantly predict the cognitive function in older adults. Specifically, sleep played a modulatory role in the association between dFNC and cognitive function, with sleep-specific variations at both microscopic (i.e., specific edges) and macroscopic levels (i.e., specific states) of dFNC.

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.

The bright side and dark side of daydreaming predict creativity together through brain functional connectivity

Daydreaming and creativity have similar cognitive processes and neural basis. However, few empirical studies have examined the relationship between daydreaming and creativity using cognitive neuroscience methods. The present study explored the relationship between different types of daydreaming and creativity and their common neural basis. The behavioral results revealed that positive constructive daydreaming is positively related to creativity, while poor attentional control is negatively related to it. Machine learning framework was adopted to examine the predictive effect of daydreaming-related brain functional connectivity (FC) on creativity. The results demonstrated that task FCs related to positive constructive daydreaming and task FCs related to poor attentional control both predicted an individual's creativity score successfully. In addition, task FCs combining the positive constructive daydreaming and poor attentional control also had significant predictive effect on creativity score. Furthermore, predictive analysis based on resting-state FCs showed similar patterns. Both of the subscale-related FCs and combined FCs had significant predictive effect on creativity score. Further analysis showed the task and the resting-state FCs both mainly located in the default mode network, central executive network, salience network, and attention network. These results showed that daydreaming was closely related to creativity, as they shared common FC basis.

Mind Causality: A Computational Neuroscience Approach

A neuroscience-based approach has recently been proposed for the relation between the mind and the brain. The proposal is that events at the sub-neuronal, neuronal, and neuronal network levels take place simultaneously to perform a computation that can be described at a high level as a mental state, with content about the world. It is argued that as the processes at the different levels of explanation take place at the same time, they are linked by a non-causal supervenient relationship: causality can best be described in brains as operating within but not between levels. This mind-brain theory allows mental events to be different in kind from the mechanistic events that underlie them; but does not lead one to argue that mental events cause brain events, or vice versa: they are different levels of explanation of the operation of the computational system. Here, some implications are developed. It is proposed that causality, at least as it applies to the brain, should satisfy three conditions. First, interventionist tests for causality must be satisfied. Second, the causally related events should be at the same level of explanation. Third, a temporal order condition must be satisfied, with a suitable time scale in the order of 10 ms (to exclude application to quantum physics; and a cause cannot follow an effect). Next, although it may be useful for different purposes to describe causality involving the mind and brain at the mental level, or at the brain level, it is argued that the brain level may sometimes be more accurate, for sometimes causal accounts at the mental level may arise from confabulation by the mentalee, whereas understanding exactly what computations have occurred in the brain that result in a choice or action will provide the correct causal account for why a choice or action was made. Next, it is argued that possible cases of "downward causation" can be accounted for by a within-levels-of-explanation account of causality. This computational neuroscience approach provides an opportunity to proceed beyond Cartesian dualism and physical reductionism in considering the relations between the mind and the brain.

Brain variability in dynamic resting-state networks identified by fuzzy entropy: a scalp EEG study

Objective.Exploring the temporal variability in spatial topology during the resting state attracts growing interest and becomes increasingly useful to tackle the cognitive process of brain networks. In particular, the temporal brain dynamics during the resting state may be delineated and quantified aligning with cognitive performance, but few studies investigated the temporal variability in the electroencephalogram (EEG) network as well as its relationship with cognitive performance.Approach.In this study, we proposed an EEG-based protocol to measure the nonlinear complexity of the dynamic resting-state network by applying the fuzzy entropy. To further validate its applicability, the fuzzy entropy was applied into simulated and two independent datasets (i.e. decision-making and P300).Main results.The simulation study first proved that compared to the existing methods, this approach could not only exactly capture the pattern dynamics in time series but also overcame the magnitude effect of time series. Concerning the two EEG datasets, the flexible and robust network architectures of the brain cortex at rest were identified and distributed at the bilateral temporal lobe and frontal/occipital lobe, respectively, whose variability metrics were found to accurately classify different groups. Moreover, the temporal variability of resting-state network property was also either positively or negatively related to individual cognitive performance.Significance.This outcome suggested the potential of fuzzy entropy for evaluating the temporal variability of the dynamic resting-state brain networks, and the fuzzy entropy is also helpful for uncovering the fluctuating network variability that accounts for the individual decision differences.

Brain Entropy is Associated with Divergent Thinking

Creativity is the ability to generate original and useful products, and it is considered central to the progression of human civilization. As a noninherited emerging process, creativity may stem from temporally dynamic brain activity, which, however, has not been well studied. The purpose of this study was to measure brain dynamics using entropy and to examine the associations between brain entropy (BEN) and divergent thinking in a large healthy sample. The results showed that divergent thinking was consistently positively correlated with regional BEN in the left dorsal anterior cingulate cortex/pre-supplementary motor area and left dorsolateral prefrontal cortex, suggesting that creativity is closely related to the functional dynamics of the control networks involved in cognitive flexibility and inhibitory control. Importantly, our main results were cross-validated in two independent cohorts from two different cultures. Additionally, three dimensions of divergent thinking (fluency, flexibility, and originality) were positively correlated with regional BEN in the left inferior frontal gyrus and left middle temporal gyrus, suggesting that more highly creative individuals possess more flexible semantic associative networks. Taken together, our findings provide the first evidence of the associations of regional BEN with individual variations in divergent thinking and show that BEN is sensitive to detecting variations in important cognitive abilities in healthy subjects.

Plasticity of the resting-state brain: static and dynamic functional connectivity change induced by divergent thinking training

Creativity is very important and is linked to almost all areas of our everyday life. Improving creativity brings great benefits. Various strategies and training paradigms have been used to stimulate creative thinking. These training approaches have been confirmed to be effective. However, whether or not training can reshape the resting-state brain is still unclear. The present study examined whether or not the divergent thinking training intervention can reshape the resting-state brain functional connectivity (FC). Static seed-based and dynamic approaches were used to explore this problem. Results demonstrate significant changes in static and dynamic FCs. FCs, such as dorsal anterior cingulate cortex-inferior parietal lobule, dorsal anterior cingulate cortex-precuneus and left and right dorsolateral prefrontal cortex, was significantly improved through the training. Furthermore, the temporal variability of the supplementary motor area and middle temporal gyrus was improved. These results indicate that divergent thinking training may lead to resting-state brain plasticity. Considering the role of these regions in brain networks, the present study further confirms the close relationship between the brain networks' dynamic interactions and divergent thinking processes.

Understanding neural flexibility from a multifaceted definition

Flexibility is a hallmark of human intelligence. Emerging studies have proposed several flexibility measurements at the level of individual regions, to produce a brain map of neural flexibility. However, flexibility is usually inferred from separate components of brain activity (i.e., intrinsic/task-evoked), and different definitions are used. Moreover, recent studies have argued that neural processing may be more than a task-driven and intrinsic dichotomy. Therefore, the understanding to neural flexibility is still incomplete. To address this issue, we propose a multifaceted definition of neural flexibility according to three key features: broad cognitive engagement, distributed connectivity, and adaptive connectome dynamics. For these three features, we first review the advances in computational approaches, their functional relevance, and their potential pitfalls. We then suggest a set of metrics that can help us assign a flexibility rating to each region. Subsequently, we present an emergent probabilistic view for further understanding the functional operation of individual regions in the unified framework of intrinsic and task-driven states. Finally, we highlight several areas related to the multifaceted definition of neural flexibility for future research. This review not only strengthens our understanding of flexible human brain, but also suggests that the measure of neural flexibility could bridge the gap between understanding intrinsic and task-driven brain function dynamics.

Brain dynamics: Synchronous peaks, functional connectivity, and its temporal variability

We describe advances in the understanding of brain dynamics that are important for understanding the operation of the cerebral cortex in health and disease. Peaks in the resting state fMRI BOLD signal in many different brain areas can become synchronized. In data from 1,017 participants from the Human Connectome Project, we show that early visual and connected areas have the highest probability of synchronized peaks. We show that these cortical areas also have low temporal variability of their functional connectivity. We show that there is an approximately reciprocal relation between the probability that a brain region will be involved in synchronized peaks and the temporal variability of the connectivity of a brain region. We show that a high probability of synchronized peaks and a low temporal variability of the connectivity of cortical areas are related to high mean functional connectivity, and provide an account of how these dynamics with some of the properties of avalanches arise. These discoveries help to advance our understanding of cortical operation in health, and in some mental disorders including schizophrenia.

Dissecting the default mode network: direct structural evidence on the morphology and axonal connectivity of the fifth component of the cingulum bundle

OBJECTIVE

Although a growing body of data support the functional connectivity between the precuneus and the medial temporal lobe during states of resting consciousness as well as during a diverse array of higher-order functions, direct structural evidence on this subcortical circuitry is scarce. Here, the authors investigate the very existence, anatomical consistency, morphology, and spatial relationships of the cingulum bundle V (CB-V), a fiber tract that has been reported to reside close to the inferior arm of the cingulum (CingI).

METHODS

Fifteen normal, formalin-fixed cerebral hemispheres from adults were treated with Klingler's method and subsequently investigated through the fiber microdissection technique in a medial to lateral direction.

RESULTS

A distinct group of fibers is invariably identified in the subcortical territory of the posteromedial cortex, connecting the precuneus and the medial temporal lobe. This tract follows the trajectory of the parietooccipital sulcus in a close spatial relationship with the CingI and the sledge runner fasciculus. It extends inferiorly to the parahippocampal place area and retrosplenial complex area, followed by a lateral curve to terminate toward the fusiform face area (Brodmann area [BA] 37) and lateral piriform area (BA35). Taking into account the aforementioned subcortical architecture, the CB-V allegedly participates as a major subcortical stream within the default mode network, possibly subserving the transfer of multimodal cues relevant to visuospatial, facial, and mnemonic information to the precuneal hub. Although robust clinical evidence on the functional role of this stream is lacking, the modern neurosurgeon should be aware of this tract when manipulating cerebral areas en route to lesions residing in or around the ventricular trigone.

CONCLUSIONS

Through the fiber microdissection technique, the authors were able to provide original, direct structural evidence on the existence, morphology, axonal connectivity, and correlative anatomy of what proved to be a discrete white matter pathway, previously described as the CB-V, connecting the precuneus and medial temporal lobe.

Healthy Aging Alters the Functional Connectivity of Creative Cognition in the Default Mode Network and Cerebellar Network

Creativity is a higher-order neurocognitive process that produces unusual and unique thoughts. Behavioral and neuroimaging studies of younger adults have revealed that creative performance is the product of dynamic and spontaneous processes involving multiple cognitive functions and interactions between large-scale brain networks, including the default mode network (DMN), fronto-parietal executive control network (ECN), and salience network (SN). In this resting-state functional magnetic resonance imaging (rs-fMRI) study, group independent component analysis (group-ICA) and resting state functional connectivity (RSFC) measures were applied to examine whether and how various functional connected networks of the creative brain, particularly the default-executive and cerebro-cerebellar networks, are altered with advancing age. The group-ICA approach identified 11 major brain networks across age groups that reflected age-invariant resting-state networks. Compared with older adults, younger adults exhibited more specific and widespread dorsal network and sensorimotor network connectivity within and between the DMN, fronto-parietal ECN, and visual, auditory, and cerebellar networks associated with creativity. This outcome suggests age-specific changes in the functional connected network, particularly in the default-executive and cerebro-cerebellar networks. Our connectivity data further elucidate the critical roles of the cerebellum and cerebro-cerebellar connectivity in creativity in older adults. Furthermore, our findings provide evidence supporting the default-executive coupling hypothesis of aging and novel insights into the interactions of cerebro-cerebellar networks with creative cognition in older adults, which suggest alterations in the cognitive processes of the creative aging brain.