Humans create internal cognitive maps that allow us to make inferences beyond direct experience. These maps often rely on hexagonal grid-cell-like neural codes, serving as a schema for two-dimensional (2D) spaces. Yet it remains unclear how new experiences become aligned with this schema, especially in non-spatial contexts. Here, we show that hippocampal ripples - brief bursts of neuronal activity during rest - predict the emergence of grid-like codes in a novel 2D inference task. We recorded intracranial neuronal activity in 42 epilepsy patients as they learned rank relationships among feature objects (for example, objects differing in 'magic' or 'speed'). After learning, these objects were combined to form 'compounds' occupying a 2D conceptual space defined by two feature dimensions. During learning, hippocampal ripple activity increased during pauses between trials, suggesting that ripples integrated newly acquired information offline. Subsequently, ripple activity during post-learning rest predicted the later emergence of grid-like codes in the entorhinal cortex (EC) and medial prefrontal cortex (mPFC), a core region of the default mode network (DMN), when participants inferred unseen relationships among the compounds. Critically, coordination during rest between hippocampal ripples and DMN activity in the mPFC predicted participants' ability to infer complex relationships beyond direct memory retrieval. These findings provide the first direct evidence that hippocampal ripples, working with the DMN, align new experiences with a grid-like schema offline, transforming discrete learning events into structured knowledge that supports flexible and adaptive reasoning in human cognition. ### Competing Interest Statement The authors have declared no competing interest.

The aim of this review is to provide an updated commentary on the current literature examining the impact of normal weight obesity (NWO) and normal weight central obesity (NWCO) on type 2 diabetes mellitus in adults. Total 14 studies were included, comprising 9 cross-sectional and 5 cohort studies with 334,438 subjects. The quality of evidence was mixed. The pooled prevalence of NWO was 16.1

Semantic memory offers a rich repository of raw materials (e.g., various concepts and connections between concepts) for creative thinking, represented as a semantic network. Similar to other networks, the semantic network exhibits a modular structure characterized by modules with dense internal connections and sparse connections between them. This organizational principle facilitates the routine storage and retrieval of information but may impede creativity. The present study investigated the effect of hub concepts with varying connection patterns on creative thinking from the perspective of a modular structured semantic network. By analyzing a large-scale semantic network, connector hubs (C-hubs) and provincial hubs (P-hubs) were identified based on their intra- and intermodule connections. These hubs were used as cue words in the alternative uses task, a widely used measure of creative thinking. Across four experiments, behavioral and neural evidence indicated that C-hubs facilitate the generation of more novel and remote ideas compared to P-hubs. However, this effect is predominantly observed in the early stage of the creative thinking process, involving changes in brain activation and functional connectivity in core regions of the default mode network and the frontoparietal network, including the dorsolateral prefrontal cortex, angular gyrus, and precuneus. Neural findings suggest that the superior performance of C-hubs relies on stronger interactions between automatic spreading activation, controlled semantic retrieval, and attentional regulation of salient information. These results provide insight into how concepts with varying semantic connection patterns facilitate and constrain different stages of the creative thinking process through the modular structure of semantic network.

Background: The association between sepsis and noninfectious respiratory diseases is well-documented, yet the specific causal link between the two remains unclear. In order to explore this relationship further, we employed a Mendelian randomization (MR) analysis utilizing data from the UK Biobank and FinnGen Biobank. Methods: We analyzed the summary statistics of a genome-wide association study summary statistics for chronic obstructive pulmonary disease (COPD), asthma, pulmonary embolism (PE), idiopathic pulmonary fibrosis (IPF), obstructive sleep apnea (OSA), lung cancer, sepsis, and sepsis-related mortality. We employed the inverse-variance weighted (IVW) method and four additional MR methods. Heterogeneity and horizontal pleiotropy were assessed using the Cochrane's Q test, MR-Egger intercept, and MR-PRESSO test. A sensitivity analysis was also performed. Results: MR analysis showed associations between COPD and lung cancer with increased sepsis risk (odds ratio (OR)IVW 1.138, P = 0.006; (OR)IVW 1.123, P = 0.031; respectively) and sepsis mortality ((OR)IVW 1.350, P = 0.022; (OR)IVW 1.312, P = 0.022; respectively). Asthma exhibited a potential protective effect against sepsis mortality ((OR)IVW = 0.300, P = 0.039), while PE demonstrated a risk effect ((OR)IVW = 1.148, P = 0.032). No causal association was observed between asthma, PE, and sepsis ( P > 0.05). IPF and OSA were not significantly associated with sepsis or sepsis-related mortality ( P > 0.05). Heterogeneity and horizontal pleiotropy were not evident for asthma or lung cancer ( P > 0.05). However, horizontal pleiotropy was suggested for COPD by the MR-Egger regression ( P < 0.05), but not by the MR-PRESSO test ( P > 0.05). IPF and OSA were not significantly associated with sepsis or sepsis-related mortality ( P > 0.05). Conclusion: Our MR analysis offers new insights into potential links between noninfectious respiratory diseases and the risk of sepsis. However, additional investigation into the underlying mechanisms and clinical studies are necessary to confirm these findings.

Invasive brain-computer interfaces with Electrocorticography (ECoG) have shown promise for high-performance speech decoding in medical applications, but less damaging methods like intracranial stereo-electroencephalography (sEEG) remain underexplored. With rapid advances in representation learning, leveraging abundant recordings to enhance speech decoding is increasingly attractive. However, popular methods often pre-train temporal models based on brain-level tokens, overlooking that brain activities in different regions are highly desynchronized during tasks. Alternatively, they pre-train spatial-temporal models based on channel-level tokens but fail to evaluate them on challenging tasks like speech decoding, which requires intricate processing in specific language-related areas. To address this issue, we collected a well-annotated Chinese word-reading sEEG dataset targeting language-related brain networks from 12 subjects. Using this benchmark, we developed the Du-IN model, which extracts contextual embeddings based on region-level tokens through discrete codex-guided mask modeling. Our model achieves state-of-the-art performance on the 61-word classification task, surpassing all baselines. Model comparisons and ablation studies reveal that our design choices, including (\romannumeral1) temporal modeling based on region-level tokens by utilizing 1D depthwise convolution to fuse channels in the ventral sensorimotor cortex (vSMC) and superior temporal gyrus (STG) and (\romannumeral2) self-supervision through discrete codex-guided mask modeling, significantly contribute to this performance. Overall, our approach -- inspired by neuroscience findings and capitalizing on region-level representations from specific brain regions -- is suitable for invasive brain modeling and represents a promising neuro-inspired AI approach in brain-computer interfaces. Code and dataset are available at https://github.com/liulab-repository/Du-IN.

OBJECTIVE:Proactive aggression can result in many economic, social, and health problems. It has two levels: trait and state. Although the neural basis of trait proactive aggression is becoming clearer, the neural basis of state proactive aggression has been largely ignored and remains unclear.METHOD:We explore the basic brain correlates of state proactive aggression using a reward-interference task (RIT), in which participants play a competitive reactive time task against an opponent. They can make decision to give the opponent noise interference for winning the game and gaining reward or not. Forty healthy participants from a university in China performed the RIT in the scanner and their functional images were obtained on a 3.0-T Siemens Tim Trio scanner. Finally, 38 participants (21 males, M age = 19.24, SD = 1.32) were included in analyses.RESULTS:The results show that relative to the baseline, the medial prefrontal cortex (MPFC), anterior cingulate cortex (ACC), temporoparietal junction (TPJ), and inferior frontal gyrus (IFG) were activated by aggression selection and nonaggression selection in the RIT. Furthermore, relative to nonaggression selection, the MPFC, ACC, TPJ, IFG, middle cingulate cortex (MCC), and middle temporal gyrus (MTG) were more strongly activated during aggression selection and correlated with the scores of some of the three basic proactive aggression motivations (instrumental motivation, moral inhibition motivation, and moral approval motivation).CONCLUSION:The results provide preliminary evidence of neural correlates for state proactive aggression and should be replicated by other methods or with other samples. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The Coronavirus disease of 2019 (COVID-19) and measures to curb it created population-level changes in male-dominant impulsive and risky behaviors such as violent crimes and gambling. One possible explanation for this is that the pandemic has been stressful, and males, more so than females, tend to respond to stress by altering their focus on immediate versus delayed rewards, as reflected in their delay discounting rates. Delay discounting rates from healthy undergraduate students were collected twice during the pandemic. Discounting rates of males (n=190) but not of females (n=493) increased during the pandemic. Using machine learning, we show that prepandemic functional connectome predict increased discounting rates in males (n=88). Moreover, considering that delay discounting is associated with multiple psychiatric disorders, we found the same neural pattern that predicted increased discounting rates in this study, in secondary datasets of patients with major depression and schizophrenia. The findings point to sex-based differences in maladaptive delay discounting under real-world stress events, and to connectome-based neuromarkers of such effects. They can explain why there was a population-level increase in several impulsive and risky behaviors during the pandemic and point to intriguing questions about the shared underlying mechanisms of stress responses, psychiatric disorders and delay discounting.

Trait hope focuses on individual goal-related thoughts and is assumed to be a critical indicator for one's mental health. However, the neurobiological basis of hope and the neurological mechanisms underlying the relationship between positive coping style (PCS) and hope (including the two dimensions of pathway thinking and agency thinking) are still largely unknown. Thus, this study explored the neural basis of trait hope by correlating the regional amplitude of low-frequency fluctuations (ALFF) and resting-state functional connectivity (RSFC) with the self-reported hope of 576 healthy first-year college students underwent RS-fMRI. Our results showed that trait hope was positively associated with PCS. A whole-brain correlation analysis provided early evidence that higher levels of trait hope were associated with decreased ALFF in the left frontal pole cortex (FPC). Additionally, pathway thinking was associated with decreased ALFF in FPC, increased ALFF in the right postcentral gyrus (PCG), decreased RSFC of the left FPC and left posterior cingulate cortex, the left FPC and right middle temporal gyrus, and the right PCG and left cerebellum. Furthermore, mediation analyses demonstrated that the PCG-cerebellum connectivity might link to pathway thinking through PCS and PCS might relate to trait hope through PCG-cerebellum connectivity. Our findings contribute to the neurobiological basis of hope and the neural mechanism underlying the relationship between trait hope and coping style.

BACKGROUND:The novel coronavirus (COVID-19) pandemic has affected humans worldwide and led to unprecedented stress and mortality. Detrimental effects of the pandemic on mental health, including risk of post-traumatic stress disorder (PTSD), have become an increasing concern. The identification of prospective neurobiological vulnerability markers for developing PTSD symptom during the pandemic is thus of high importance. METHODS:Before the COVID-19 outbreak (September 20, 2019-January 11, 2020), some healthy participants underwent resting-state functional connectivity MRI (rs-fcMRI) acquisition. We assessed the PTSD symptomology of these individuals during the peak of COVID-19 pandemic (February 21, 2020-February 28, 2020) in China. This pseudo-prospective cohort design allowed us to test whether the pre-pandemic neural connectome status could predict the risk of developing PTSD symptom during the pandemic. RESULTS:A total of 5.60% of participants (n = 42) were identified as being high-risk to develop PTSD symptom and 12.00% (n = 90) exhibited critical levels of PTSD symptoms during the COVID-19 pandemic. Pre-pandemic measures of functional connectivity (the neural connectome) prospectively classified those with heightened risk to develop PTSD symptom from matched controls (Accuracy = 76.19%, Sensitivity = 80.95%, Specificity = 71.43%). The trained classifier generalized to an independent sample. Continuous prediction models revealed that the same connectome could accurately predict the severity of PTSD symptoms within individuals (r 2 = 0.31p<.0). CONCLUSIONS:This study confirms COVID-19 break as a crucial stressor to bring risks developing PTSD symptom and demonstrates that brain functional markers can prospectively identify individuals at risk to develop PTSD symptom.

The neural substrates that contribute to creative thinking through the recruitment of semantic memory structures remain largely unknown. This study sought to investigate the properties of semantic networks using a semantic judgment rating task at the individual level and explore the relationship among creative abilities, the topological properties of semantic networks, and their underlying brain structures. We first used a semantic judgment rating to assess individual semantic networks and computed their topological properties. The analysis confirmed a significant correlation between the creative thinking abilities assessed by an alternate uses task and all three topological properties. In addition, voxel-based morphometry was employed to assess the neural correlates of gray matter volume (GMV) related to different topological properties of the semantic network. Results revealed a positive correlation between global efficiency and the left temporal pole cortex, considered to be involved in semantic information transmission and processing. Furthermore, mediation analysis found that the global efficiency of the individual semantic network mediated the association between the left temporal pole GMV and creative thinking, showing that the relationship between left temporal pole GMV and creative thinking may be affected by the semantic networks. To the best of our knowledge, this study is the first to combine a behavioral investigation of semantic networks with magnetic resonance imaging to shed light on the cerebral structural basis of semantic memory networks, in addition to their relationship to creativity.

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.

Objective: This study systematically reviewed literature on the neighbourhood food environment in relation to diet and obesity among residents in China. Design: A keyword search of peer-reviewed articles was performed in Cochrane Library, PubMed, and Web of Science. Eligibility criteria include study designs: longitudinal/cohort studies or cross-sectional studies; study participants: people of all ages; exposures: neighbourhood food environment (e.g. restaurants, supermarkets, wet markets, fast-food restaurants, or convenience stores); outcomes: diet and/or body weight status; and country: China. Results: Seventeen studies met all criteria and were included. Among the eight studies that assessed the neighbourhood food environment in relation to diet, six reported at least one statistically significant relationship in the expected direction, whereas the remaining two exclusively reported null effects. Among the eleven studies that assessed the neighbourhood food environment in relation to body weight or overweight/obesity, ten reported a significant association whereas the remaining one reported a null relationship. Variety, density, and proximity of food outlets were positively associated with local residents' dietary diversity, portion size, and daily caloric intake. Density and proximity of fast-food restaurants and convenience stores were positively associated with local residents' adiposity in some but not all studies. Evidence linking any specific food outlet type to diet/obesity remains lacking due to the small number of studies and heterogeneities in food environment measures, geographical locations, and population subgroups. Conclusions: The neighbourhood food environment may influence diet and obesity among Chinese residents but the evidence remains preliminary. Future studies adopting an experimental study design and objective/validated environment and dietary measures are warranted.

BackgroundFew studies explored response inhibition in autistic-like traits people, using task fMRI. In this study, we examine the functional connectivity of the brain using a stop-signal task based on fMRI among young adults with autistic-like traits and investigated their ability to achieve inhibition control.Methods29 of Chinese individuals measured with AQ. Then applied stop signal task to explore the difference in brain functional connectivity in individuals with autistic-like traits.ResultsThe results showed autistic-like traits people the longer the SSRT, the worse the inhibition ability. And we used networks obtained from groupICA analysis at the functional connectivity analysis level, the SN had a negative connection with left SMG; the DAN had a negative connection with left LG; the FPN had a positive connection with left PCG; the LN had a positive connection with vermis 4 5 and negative connection with left ITG. Furthermore, the SMG, LG, PCG, and temporal gyrus were also obtained in ROI-to-ROI analysis.LimitationsOur sample size smaller, still need to multicenter, large sample confirmed this conclusion. We want to use more task paradigms to explore inhibition control in autistic-like traits people.ConclusionsWe found that autistic-like traits people had atypical functional connectivity within brain networks in the SN, DAN, FPN, and LN, and had atypical brain areas centered on the SMG, LG, PCG, and temporal gyrus. And also highlight the importance of considering executive control function of whole-brain functional connections to better characterize brain connectivity in young adults with autistic-like traits.

Research has independently highlighted the roles of semantic memory and associative abilities in creative thinking. However, it remains unclear how these two capacities relate to each other, nor how they facilitate different creative thinking modalities, such as verbal and figural creativity. This study employed multiple cognitive tests and network science methodologies to shed light on the relationship between them. We constructed individual-based semantic networks and assessed associative abilities, verbal and figural creative thinking. In line with previous studies, we found a relation between verbal creativity and more flexible semantic memory structure (higher connectivity, shorter distances between concepts, and lower modularity). However, we did not find any such relation between figural creativity and semantic memory structure. Associative abilities mediated the relationship between semantic memory structure and verbal creativity, implying the efficient spread of information in semantic memory may facilitate verbal creative thinking via associative abilities. These findings support and extend the associative theory of creativity and shed novel light on the relationship between semantic memory structure, associative abilities, and creativity.

Advances in graph-theoretic models of networks have made it possible to investigate the topological properties of the human brain across time and space. Brain flexibility is defined as the frequency with which brain regions switch between different functional modules over time and has been shown to correlate with higher-order cognitive functions. Need for cognition (NFC) refers to a personality trait to engage in and enjoy effortful cognitive endeavors and usually has a positive effect on diverse cognitive activities (e.g., creativity), which may also be closely related to brain flexibility. Here, we tested whether the flexibility of a large-scale brain network associated with NFC facilitated creative achievement. Robust correlation analyses showed that NFC correlates with the flexibility of the insula, the medial prefrontal cortex, and the putamen at the node level. Several large-scale brain networks whose flexibility also correlated with NFC, including the default mode network, salience network, subcortical network, ventral attention network, and control network, imply that higher NFC individuals may exhibit better cognitive abilities, such as executive control, salient detection, spontaneous thought, and motivation function. Interestingly, only global flexibility acted as a mediator in the relationship between NFC and creative achievement, suggesting that the mediating mechanism may involve an interaction between distinct regions or large-scale networks across the entire brain instead of the functional characteristic of local regions. Together, we demonstrate that the higher NFC is, the more flexible the brain, which may provide a potential insight into the acquisition of creative achievement.

The analysis of the relationship between personality and depression can facilitate the development of subclinical preventive measures and clinical treatment schemes. Moreover, the personality is associated with a variety of mental diseases, and there is substantial comorbidity between depression and some other mental diseases. So, to reveal pathological relationships between personality and depression is helpful to understand the etiology of the comorbidity between depression and multiple mental disorders. In this review, we first summarize the empirical researches on the relationship between personality and depression from the aspects of behavior and neural mechanisms, and then discuss the hypothetical model to explain the relationship between personality and depression. In a word, high neuroticism, low extroversion and conscientiousness, and other related traits (rumination, self-criticism, dependency, etc.) have a moderate to strong correlation with depression. Among them, neuroticism is the most concerned. To a certain extent, it can predict the onset of depression and affect the duration and treatment outcome of depression. Other traits, such as positive emotionality/ extroversion and effortful control/responsibility, can moderate the relationship between negative emotionality/neuroticism and depression. And after the onset of depression, the neuroticism may change, but the extroversion does not seem to change.

Creativity is the foundation of human culture. All inventions and innovations in history rely upon us to break with the traditional thinking and create something novel. A number of neuroimaging studies have explored the neural mechanism of creativity. However, a majority of researches have focused only on the stationary functional connectivity in resting-state fMRI and task-related fMRI, neglecting the dynamic variation of brain networks. Here, we used dynamic network analysis to investigate the relation between the dynamic reorganization of brain networks and verbal creativity in 370 healthy subjects. We found that the integration of the left lingual gyrus and left middle temporal gyrus (MTG) in default mode network (DMN) and the integration of the DMN and cerebellum, frontoparietal task control network (FPTC) and auditory network (Aud) showed positive correlation with verbal creativity performance. In addition, the recruitment of the bilateral postcentral gyrus from the sensory/somatomotor network (SMN) and the recruitment of the SMN in general displayed a significant correlation with verbal creativity scores. Taken together, these results suggested that the dynamic reorganization among the brain networks involved multiple cognitive processes, such as memory retrieval, imaginative process, cognitive control - these are all important for verbal creativity. These findings provided direct evidence that verbal creativity was related to the dynamic variation of brain mechanism during resting-state, extending past research on the neural mechanism of creativity. Meanwhile, these results bought about new perspectives for verbal creative training and rehabilitation training of depression.

Little is known about the association between emotional intelligence (EI) and trait creativity (TC), and the brain structural bases which involves. This study investigated the neuroanatomical basis of the association between EI and TC which measured by the Schutte self-report EI scale and the Williams creativity aptitude test. First, the voxel-based morphometry (VBM) analysis was used to explore the brain structures which is closely related to EI in a large young sample (n = 213). The results showed that EI was positively correlated with the regional gray matter volume (rGMV) in the right orbitofrontal cortex (OFC), which is regarded as a key region of emotional processing. More importantly, further mediation analysis revealed that rGMV in the right OFC partially mediated the association between EI and TC, which showed the OFC volume could account for the relationship between EI and TC. These findings confirmed the close relationship between EI and TC, and highlighted that the brain volumetric variation in the OFC associated with the top-down processing of emotion regulation, which may play a critical role in the promotion of TC. Together, these findings contributed to sharpening the understanding of the complex relationship between EI and TC from the perspective of brain structural basis.

Conscientiousness is frequently characterized by tendencies to be self-disciplined, to demonstrate organization and dependability, to act dutifully, to aim for achievement and to have good impulse control; this trait plays an important role in some special contexts, such as legal consciousness. Although a great number of studies have confirmed the impact of conscientiousness on emotion experience, little is known about the relationship between conscientiousness and emotion regulation, or of the brain structural basis that is involved. The current study investigated the neuroanatomical basis of the relationship between conscientiousness and emotion regulation from the perspective of individual differences. The voxel-based morphometry (VBM) method at the whole-brain level was used to identify the brain structural basis related to conscientiousness in a large, young sample (n = 351). The results showed that conscientiousness was significantly and positively correlated with the gray matter volume (GMV) in the right inferior frontal gyrus (IFG), which is the key region for inhibitory control. Further mediation analysis revealed that the IFG volume partially mediated the relation between conscientiousness and expressive suppression (ES), rather than cognitive reappraisal (CR), which showed that the IFG is associated with direct inhibitory control and plays a specific role in the relationship between conscientiousness and the two strategies of emotion regulation. Taken together, these findings contributed to sharpening the understanding of the correlation between conscientiousness and emotion regulation from the perspective of the brain structural basis.