Complex cognition, such as creativity, relies on cognitive integration of various component processes (e.g., memory, attention, and imagery). Yet, current methods cannot fully capture how the brain integrates cognitive processes during complex tasks. Previous research suggests that communication between functionally dissimilar regions might underlie cognitive integration, allowing for complex cognition. Here, we provide a formal test of this notion using task-based fMRI (n = 28) to assess functional connectivity (FC) among sets of regions ("levels") varying in their functional dissimilarity (defined by differences in resting-state FC profiles) across five tasks hypothesized to vary in cognitive complexity. Each task involved conceptual association and/or idea generation. We found that as task complexity increased, task-FC between regions with greater functional dissimilarity also increased, and the strength of this linear trend positively predicted the relative complexity of tasks. Thus, more complex tasks recruited greater interactions between functionally dissimilar regions. Furthermore, this effect was primarily driven by the default mode and frontoparietal control networks, especially connector hubs within these networks. Task-FC at the highest functional dissimilarity levels was most related to metaphor production and bi-association (involving integrating two concepts), followed by generating novel object uses and uncommon association (involving expanding one concept), and was least related to common association (thus, this task was the least complex). Altogether, task-FC across functional dissimilarity levels robustly tracked the cognitive complexity of tasks, supporting the validity of this neural feature for measuring cognitive complexity in a continuous manner and for data-driven tests of theorized differences in task complexity.

Personality neuroscience has traditionally relied on the Big Five model to investigate trait structure and its relationship to individual differences in brain organization and life outcomes. However, existing theoretical frameworks explain only part of the item-level covariance, raising questions about whether alternative factor solutions might complement the canonical five-factor model. Here, we applied an additive and part-based machine learning decomposition to a mega-scale, global dataset (n = 1,336,840) to systematically evaluate trait structure across factor resolutions. Beyond reproducing the canonical Big Five, we identified a robust Big Two comprising Social Adaptation and Spontaneous Mentation. Social Adaptation integrates covarying questionnaire items from Extraversion, Agreeableness, and Conscientiousness, indexing externally oriented social functioning. Spontaneous Mentation, in turn, aggregates Neuroticism with introspective facets of Openness, capturing internally directed affective-cognitive exploration. Embedding individuals in this Big Two space revealed structured manifolds along which neurocognitive profiles aligned with distinct trait orientations. Importantly, this lower-dimensional representation improved prediction of functional brain connectivity relative to Big Five scores, while preserving comparable associations with cognition and mental health. Together, these results establish a neurocognitively grounded Big Two framework that complements the Big Five and offers an interpretable bridge between personality structure, cognitive functioning, and psychopathology.

OBJECTIVE:Posttraumatic stress disorder (PTSD) causes significant morbidity, with acceptance and commitment therapy (ACT) emerging as an effective treatment. Given advances in internet technology, mobile ACT interventions offer a promising approach to PTSD treatment. This study aimed to develop and test a mobile app-delivered ACT intervention for PTSD and assess its effects on symptoms and associated brain activity patterns. METHOD:Using functional magnetic resonance imaging (fMRI), we assessed brain activation related to mood regulation and measured symptom scores (trauma, anxiety, depression, mental flexibility, posttraumatic growth) in 52 PTSD participants (28 ACT intervention, 24 wait-list control). Brain activation patterns were analyzed over time, with their relationship to symptom improvement. RESULTS:The ACT group showed significant improvements in trauma severity, anxiety, psychological flexibility, and posttraumatic cognition. Neuroimaging revealed decreased activation in the right inferior frontal gyrus during implicit emotional processing, positively correlated with psychological flexibility. The ACT group also exhibited reduced right inferior frontal gyrus activation in emotion modulation by attention shifting and increased activation in the parahippocampal gyrus, which was positively correlated with improved anxiety levels. These changes in brain activity suggest the potential effectiveness of the intervention. CONCLUSIONS:These findings provide preliminary evidence that mobile app-delivered ACT may be a feasible and potentially effective approach for improving psychological functioning in individuals with PTSD. However, further studies with active comparators are necessary to strengthen the evidence base. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Aesthetic experience shapes behaviours ranging from everyday consumer choices to art appreciation. Although theoretical accounts propose that such experiences emerge from interactions among core brain systems, the dimensions organising this mental process remain unclear. Here, we introduce a data-driven framework to characterise the latent neural architecture of shared aesthetic evaluations. Participants viewed traditional paintings during 7T functional magnetic resonance imaging (fMRI), and we applied dimensionality reduction to the similarity structure of their aesthetic ratings to identify the dominant axes of variation. Two principal dimensions emerged, visual semantics and hedonic valuation, each predicted by dissociable multivariate neural signatures. Category-selective regions along the ventral visual stream tracked variation in visual semantics, whereas medial prefrontal and subcortical circuitry tracked hedonic valuation. Moreover, individual differences in this latent aesthetic space, particularly within default mode network regions, scaled with visual art expertise. Together, these findings reveal how core brain systems synergistically organise shared aesthetic evaluations of visual artworks.

Flexible cognition requires the adaptive retrieval of conceptual knowledge, spanning a continuum from proximal to distal semantic associations. However, the neural dynamics that facilitate this flexibility remain poorly understood. Here, combining computational linguistics with functional magnetic resonance imaging (fMRI) and machine learning methods, we derive a whole-brain signature that captures graded variations in semantic distance. This domain-specific neural model revealed three distinct large-scale cognitive systems whose interactions coordinate semantic retrieval: a left-lateralised frontotemporal language and a bilateral frontoparietal control network, both recruited for distant associations, and a medial default mode memory network, facilitating access to proximal relations. Importantly, we show that adaptive retrieval across the continuum of semantic distance is facilitated by a dynamic coordination mechanism. As semantic distance increases, representational patterns converge across the three cognitive systems. These findings provide a unifying model of the neural architecture underlying semantic processing, revealing how dynamic interactions between competing cognitive systems enable flexible knowledge retrieval.

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. Robust evidence that creativity is tied to the capacity to dynamically switch between brain networks supporting spontaneous and controlled cognition.

Affect significantly impacts daily creativity, particularly within artistic domains. However, how dynamic affective fluctuations influence creativity remains inadequately understood. Therefore, we used the diary method to investigate how affective fluctuations during the composition period (microlevel), daily affective experiences (mesolevel), long-term affective states (macrolevel), and emotional valence for different poetic themes (task context) influence poetic creativity. The microlevel analysis indicated that increased switching frequency of affective microstates under negative themes predicts increased poetic creativity. At the mesolevel, positive affect significantly predicts poetic creativity. Moreover, the interaction between daily negative affect and microstates tends to positively impact poetic creativity, which is moderated primarily by the task context when individuals experience stable long-term negative affect, whereas under long-term unstable negative affect, it is moderated by the interaction between microstates and the task context. This study demonstrates that affective dynamics across multiple scales interactively shape poetic creativity and enhance our understanding of the conditions enabling creative output, thereby enriching comprehension of everyday creativity in literary studies.

Background/Objectives: Digital food-related videos significantly influence cravings, appetite, and weight outcomes; however, the dynamic neural mechanisms underlying appetite fluctuations during naturalistic viewing remain unclear. This study aimed to identify neural activity patterns associated with moment-to-moment appetite changes during naturalistic food-cue video viewing and to examine their relationships with cravings and weight-related outcomes. Methods: Functional magnetic resonance imaging (fMRI) data were collected from 58 healthy female participants as they viewed naturalistic food-cue videos. Participants concurrently provided continuous ratings of their appetite levels throughout video viewing. Hidden Markov Modeling (HMM), combined with machine learning regression techniques, was employed to identify distinct neural states reflecting dynamic appetite fluctuations. Findings were independently validated using a shorter-duration food-cue video viewing task. Results: Distinct neural states characterized by heightened activation in default mode and frontoparietal networks consistently corresponded with increases in appetite ratings. Importantly, the higher expression of these appetite-related neural states correlated positively with participants’ Body Mass Index (BMI) and post-viewing food cravings. Furthermore, these neural states mediated the relationship between BMI and food craving levels. Longitudinal analyses revealed that the expression levels of appetite-related neural states predicted participants’ BMI trajectories over a subsequent six-month period. Participants experiencing BMI increases exhibited a significantly greater expression of these neural states compared to those whose BMI remained stable. Conclusions: Our findings elucidate how digital food cues dynamically modulate neural processes associated with appetite. These neural markers may serve as early indicators of obesity risk, offering valuable insights into the psychological and neurobiological mechanisms linking everyday media exposure to food cravings and weight management.

On the basis of the confluence theories of creativity, creative ideation depends on forging links between existing memory traces. The synergy between memory and creative thought is well-established, but neural dynamics of memory integration for creativity are understudied. Here, we extended the traditional memory paradigm. Participants read, recalled narratives, and wrote endings. Computational linguistic analysis showed that those integrating more noncentral events-those less semantically connected to other events within the narrative-wrote more original endings. Analyzing fMRI data captured during narrative encoding, we discovered that story ending originality can be predicted by shared event representation across participants in the right Brodmann area 25 (BA25) and stronger hippocampal event segmentation signal during noncentral event encoding. These results held across different narrative types (i.e., crime, romance, and fantasy stories). Overall, these results offer notable insights, from the perspective of network structure into how humans encode and retrieve complex real-world experiences to enhance creativity.

Associative theories of creativity posit that high-creativity individuals possess flexible semantic memory structures that allow broad access to varied information. However, the semantic memory structure characteristics and neural substrates of creative writing are unclear. Here, we explored the semantic network features and the predictive whole-brain functional connectivity associated with creative writing and generated mediation models. Participants completed two creative story continuation tasks. We found that keywords from written texts with superior creative writing performance encompassed more semantic categories and were highly interconnected and transferred efficiently. Connectome predictive modeling (CPM) was conducted with resting-state functional magnetic resonance imaging (fMRI) data to identify whole-brain functional connectivity patterns related to creative writing, dominated by default mode network (DMN). Semantic network features were found to mediate the relationship between brain functional connectivity and creative writing performance. These results highlight how semantic memory structure and the DMN-driven brain functional connectivity patterns support creative writing performance. Our findings extend prior research on the role of semantic memory structure and the DMN in creativity, expand upon previous research on semantic creativity, and provide insight into the cognitive and neural foundations of creative writing.

ObjectiveOverweight and obesity, as commonly indicated by a higher BMI, are associated with functional alterations in the brain, which may potentially result in cognitive decline and emotional illness. However, the manner in which these detrimental impacts manifest in the brain's dynamic characteristics remains largely unknown.MethodsBased on two independent resting-state functional magnetic resonance imaging data sets (Behavioral-Brain Research Project of Chinese Personality, n = 1923; Human Connectome Project, n = 998), the current study employed a Hidden Markov model to identify the spatiotemporal features of brain activity states. Subsequently, the study examined the changes in brain-state dynamics and the corresponding functional outcomes that arise with an increase in BMI.ResultsElevated BMI tends to shift the brain's activity states toward a greater emphasis on a specific set of states, i.e., the metastate, that are relevant to the joint activities of sensorimotor systems, making it harder to transfer to the metastate of transmodal systems. These findings were reconfirmed in a longitudinal sample (Behavioral-Brain Research Project of Chinese Personality, n = 34) that exhibited a significant increase in BMI at follow-up. Importantly, the alternation of brain-state dynamics specifically mediated the relationships between BMI and adverse functional outcomes, including cognitive decline and symptoms of mental illness.ConclusionsThe altered brain-state dynamics within the sensorimotor-to-transmodal hierarchy provide new insights into obesity-related brain dysfunctions and mental health issues.

Preserving a normal body mass index (BMI) is crucial for the healthy growth and development of children. As a core aspect of executive functions, inhibitory control plays a pivotal role in maintaining a normal BMI, which is key to preventing issues of childhood obesity. By studying individual variations in inhibitory control performance and its associated connectivity-based neuromarker in a sample of primary school students (N = 64; 9-12 yr), we aimed to unravel the pathway through which inhibitory control impacts children's BMI. Utilizing resting-state functional MRI scans and a connectivity-based psychometric prediction framework, we found that enhanced inhibitory control abilities were primarily associated with increased functional connectivity in brain structures vital to executive functions, such as the superior frontal lobule, superior parietal lobule, and posterior cingulate cortex. Conversely, inhibitory control abilities displayed a negative relationship with functional connectivity originating from reward-related brain structures, such as the orbital frontal and ventral medial prefrontal lobes. Furthermore, we revealed that both inhibitory control and its corresponding neuromarker can moderate the association between food-related delayed gratification and BMI in children. However, only the neuromarker of inhibitory control maintained its moderating effect on children's future BMI, as determined in the follow-up after one year. Overall, our findings shed light on the potential mechanisms of how inhibitory control in children impacts BMI, highlighting the utility of the connectivity-based neuromarker of inhibitory control in the context of childhood obesity.

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.

Creativity is typically operationalized as divergent thinking (DT) ability, a form of higher-order cognition which relies on memory, attention, and other component processes. Despite recent advances, creativity neuroscience lacks a unified framework to model its complexity across neural, genetic, and cognitive scales. Using task-based fMRI from two independent samples and MVPA, we identified a neural pattern that predicts DT, validated through cognitive decoding, genetic data, and large-scale resting-state fMRI. Our findings reveal that DT neural patterns span brain regions associated with diverse cognitive functions, with positive weights in the default mode and frontoparietal control networks and negative weights in the visual network. The high correlation with the primary gradient of functional connectivity suggests that DT involves extensive integration from concrete sensory information to abstract, higher-level cognition, distinguishing it from other advanced cognitive functions. Moreover, neurobiological analyses show that the DT pattern is positively correlated with dopamine-related neurotransmitters and genes influencing neurotransmitter release, advancing the neurobiological understanding of creativity. This study used fMRI and MVPA to identify neural patterns predicting divergent thinking (DT). DT engages the default mode and frontoparietal control networks, opposing the visual network, and is linked to dopamine-related neurotransmitters and genes.

Novelty and appropriateness are two fundamental components of creativity. However, the way in which novelty and appropriateness are separated at behavioral and neural levels remains poorly understood. In the present study, we aim to distinguish behavioral and neural bases of novelty and appropriateness of creative idea generation. In alignment with two established theories of creative thinking, which respectively, emphasize semantic association and executive control, behavioral results indicate that novelty relies more on associative abilities, while appropriateness relies more on executive functions. Next, employing a connectome predictive modeling (CPM) approach in resting-state fMRI data, we define two functional network-based models—dominated by interactions within the default network and by interactions within the limbic network—that respectively, predict novelty and appropriateness (i.e., cross-brain prediction). Furthermore, the generalizability and specificity of the two functional connectivity patterns are verified in additional resting-state fMRI and task fMRI. Finally, the two functional connectivity patterns, respectively mediate the relationship between semantic association/executive control and novelty/appropriateness. These findings provide global and predictive distinctions between novelty and appropriateness in creative idea generation.

Childhood obesity is a worldwide health issue. Inhibitory control, one of the fundamental components of executive functions, is an important protective factor for childhood obesity. Employing individual differences in inhibitory control performance and its connectivity-based neuromarker acquired in primary school students (N = 64; 9-12yr), we attempted to reveal the pathway by which inhibitory control affects children’s body mass index (BMI). Based on the resting-state functional MRI scanning and a connectivity-based psychometric prediction framework, we observed that higher inhibitory control abilities mainly related to increased functional connectivity in brain structures play vital roles in executive functions, such as superior frontal lobule, superior parietal lobule and precuneus/post cingulate cortex. While inhibitory control was negatively related to functional connectivity from reward-related brain structures, such as orbital frontal and ventral medial prefrontal lobes. Importantly, we revealed that both the inhibitory control and its relevant neuromarker can moderate the association between food-related delayed gratification and BMI in children. However, only the inhibitory control neuromarker maintained the moderating effect even for children’s future BMI acquired in the follow-up after one year. Taken together, our findings shed light on the potential mechanisms by which children’s inhibitory control affects BMI.

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

Complex cognitive processes, like creative thinking, rely on interactions among multiple neurocognitive processes to generate effective and innovative behaviors on demand, for which the brain's connector hubs play a crucial role. However, the unique contribution of specific hub sets to creative thinking is unknown. Employing three functional magnetic resonance imaging datasets (total N = 1,911), we demonstrate that connector hub sets are organized in a hierarchical manner based on diversity, with "control-default hubs"-which combine regions from the frontoparietal control and default mode networks-positioned at the apex. Specifically, control-default hubs exhibit the most diverse resting-state connectivity profiles and play the most substantial role in facilitating interactions between regions with dissimilar neurocognitive functions, a phenomenon we refer to as "diverse functional interaction". Critically, we found that the involvement of control-default hubs in facilitating diverse functional interaction robustly relates to creativity, explaining both task-induced functional connectivity changes and individual creative performance. Our findings suggest that control-default hubs drive diverse functional interaction in the brain, enabling complex cognition, including creative thinking. We thus uncover a biologically plausible explanation that further elucidates the widely reported contributions of certain frontoparietal control and default mode network regions in creativity studies.