The gut–brain axis represents a bidirectional communication system disrupted in obesity. Evidence suggests associations between gut microbiota composition and brain function and eating behaviour, as well as between dysregulated brain networks and dietary choices and metabolic regulation. In this review, we examine how obesity affects both components of this axis and explore physical activity as a modifiable factor related to microbial composition and brain network connectivity. We discuss compositional alterations in the gut microbiota associated with obesity, including reduced microbial diversity and altered short-chain fatty acid production. On the brain side, dysregulation of large-scale functional networks, particularly the salience network, central executive network, and default mode network, is linked to impaired inhibitory control and disinhibited eating patterns. Despite promising evidence connecting physical activity with improvements in both gut microbiota and brain connectivity, observational and interventional studies show inconsistencies regarding temporal dynamics and causal relationships. To examine these questions, we augment our review with longitudinal data from 702 participants assessed across three timepoints using random-intercept cross-lagged panel models, which distinguish stable individual differences from dynamic within-person variation. Our findings indicate temporal associations in which physical activity precedes shifts in connectivity in attention-related networks, which subsequently precede alterations in gut microbiota diversity, consistent with predominantly brain-to-gut temporal patterns with network specificity. Taken together, these results highlight a potential role of physical activity in modulating both brain connectivity and microbial composition, with possible relevance for obesity treatment.

Depression is a major public health issue, and one incidence peak occurs in adolescence. Maternal distress has been recognized as an environmental risk factor for offspring depression, particularly when children are exposed to stressors. Maternal distress is also associated with alterations in offspring cortico-limbic circuitry throughout development. Yet it remains unknown how these neural alterations explain vulnerability to psychopathology across generations. Based on data from a prospective Dutch low-risk cohort, the present study examined the role of cortico-limbic connectivity topography in the relationship between middle-childhood maternal distress and adolescent depressive symptoms during the COVID-19 pandemic. Maternal distress was averaged across maternal-reported depressive and anxiety symptoms from child ages 8 to 10 years. Children's resting-state fMRI data were collected at approximately 12.5 years of age to characterize functional topography within the amygdala–hippocampus complex. Children self-reported depressive symptoms during the pandemic at age 13.5 on average. Results revealed that maternal distress was associated with subsequent adolescent depressive symptoms. Maternal distress was specifically linked to the third-order mode of connectivity in the bilateral amygdala–hippocampus complex, primarily driven by connectivity within the anterior hippocampus. Mediation models showed that these connectivity modes did not mediate the relationship between maternal distress and adolescent depressive symptoms. Moderation models indicated that the left third-order mode interacted with maternal distress to predict adolescent depressive symptoms. These findings highlight that cortico-limbic connectivity topography may play a key role in the pathways linking maternal distress to children’s vulnerability to depressive symptoms.

The hippocampus and amygdala play essential roles in human cognition and emotion, through their extensive connectivity with other brain regions and close interaction between them. Uncovering the functional organization of the hippocampus–amygdala complex and its relationship with neurotransmitter distribution can enhance our understanding of their biological functionality, and provide a basis for further exploration of the clinical relevance. An emerging functional connectivity analysis method termed connectopic mapping, may offer a novel approach to characterize this functional organization. In this study, we applied connectopic mapping to the hippocampus-amygdala complex, testing its utility with resting-state functional magnetic resonance imaging (fMRI) scans of two independent datasets: one comprising healthy individuals (N = 410) and another comprising a psychiatric cohort (N = 367). The spatial organization of derived gradient maps was compared to 18 positron emission tomography (PET) or single photon emission computed tomography (SPECT) scan templates for different neurotransmitter systems. Individual gradient–neurotransmitter similarity indices were correlated with mental health outcomes. Our analyses identified six distinct gradient maps in both datasets. The third-order gradients showed stable similarity with 5-HT1A receptor maps across various resting-state scans. Similarities were also observed between gradient maps and the distribution patterns of neurotransmitters within the dopaminergic system. Individual gradient-to-5-HT1A similarity was positively correlated with depressive severity and anxiety sensitivity, highlighting the psychopathological relevance. These findings demonstrate that across the psychiatric continuum, connectopic mapping is a powerful tool for exploring the relationship between functional connectivity organization and neurotransmitter distribution, showing potential as a comprehensive transdiagnostic biomarker.

Objectives The interplay between emotion and memory is a central topic in cognitive neuroscience, with open questions about the underlying neuronal mechanisms. This article aims to study the effects of order and intensity of emotional information on associative memory encoding. To this aim, we employ dynamic causal modeling to model the dynamic network composed of the hippocampus, amygdala, and orbitofrontal cortex during an fMRI associative memory encoding task and apply graph and control theory tools to obtain novel insights.Methods Participants were clustered into three condition groups, neutral-neutral, neutral-emotional, or emotional-emotional, and viewed image pairs associated with their assigned condition. Using the dynamic causal modeling framework, we explore several dynamic models and show that a stochastic bilinear state-space model best describes the neuronal dynamics in all conditions. Furthermore, we use graph and control theory techniques to both validate and analyze the model. Particularly, we analyze the network dynamics of each condition using tools from graph theory and stability theory and discuss the differences in the strength and direction of connectivity as well as stability of each of these networks.Results We confirm the prior finding that memory is enhanced in the neutral-emotional condition. In our work, this enhanced memory is associated with the increased hippocampus-amygdala coupling strength in this condition. Moreover, we show that in the emotional-emotional condition, coupling of hippocampus and amygdala, as well as the whole network connectivity increases. We further predict that the hippocampus-amygdala connectivity in this condition increases, when the first image's valence is substantially less negative rated than the second image, but decreases otherwise. This pattern mirrors the neutral-emotional condition, where the first image is emotionally neutral compared with the second. Moreover, our model-based analyses suggest that the amygdala predominantly influences the other two regions in the neutral-emotional condition.Conclusion Combined data-driven DCM modeling, stability analyses, and graph-theory tools led to new insights and enhanced the mechanistic understanding of dynamics of emotional associative memory. We discuss these insights, utilize these analytical tools to generalize our findings to some unmeasured conditions, and highlight the potential of these techniques to inform the development of future technological or pharmacological approaches targeting regulatory mechanisms.

Emotional habituation, a basic form of neural plasticity, regulates emotions adaptively, yet its role in stress resilience remains unclear. This study integrated laboratory-based EEG habituation measures and ecological experience sampling to examine valence-specific habituation as a resilience factor against daily life stress in 69 undergraduates. Habituation slopes were derived from Late Positive Potential (LPP) amplitude and arousal trajectories when participants viewed repeated pictures. Daily stressors and anxiety were reported over 30 days. Hierarchical linear modeling (HLM) revealed that habituation, modeled as a between-subjects moderator, significantly buffered stress reactivity: faster habituation to unpleasant stimuli (indexed by arousal and LPP slopes) and slower habituation to pleasant stimuli (indexed exclusively by LPP slopes) predicted reduced state anxiety amid rising daily stressors. These results underscored the role of adaptive emotional habituation as a protective factor for psychological resilience, with distinct pathways for threat disengagement (unpleasant valence) and reward preservation (pleasant valence). This research offers valuable insights for developing targeted interventions to prevent stress-related disorders.

Childhood adversity (CA) is associated with an elevated risk of psychopathology across the lifespan and altered brain functions are thought to play an important role in linking CA to mental vulnerability. Previous research has proposed that CA generally influences emotion processing and particularly affects reward processing and cognitive control, yet convergent evidence for CA-related neural and functional networks underlying these processes remains to be fully understood. To investigate the impact of CA on functional brain activations, the present study performed Activation Likelihood Estimation (ALE) analyses across neuroimaging studies involving three task domains: emotion processing, cognitive control, and reward processing. ALE results revealed two significant CA-related convergences of activation in the left amygdala and insula. To better understand and characterize the functions of these ALE-derived clusters, we applied the Meta-Analytic Connectivity Modeling (MACM) approach to identify co-activation maps, and the functional decoding approach to reveal cluster-related psychological processes. Results demonstrated two distinct neural and functional networks in CA: an amygdala-centered emotion processing network and an insula-centered somatomotor processing network. These specific neural patterns indicate the effect of CA on multiple neural and functional networks engaged in sensory-motor and emotion processing functions. Our results provide insights into the neurobiological embedding associated with CA.

Cognitive reappraisal is a fundamental emotion regulation strategy for mental and physical well-being, but how its neural mechanisms relate to individual differences remains poorly understood. In a consortium effort analyzing 40 fMRI datasets ( N =2,175), we examined the relationship between neural activation during reappraisal tasks and three core individual difference indices of reappraisal capabilities: (1) trait questionnaires, (2) task-based affective ratings, and (3) amygdala down-regulation. Strikingly, there was no shared overlap across these three common indices. Only a very weak correlation emerged between amygdala down-regulation and task-based affective ratings. Whole-brain analyses revealed no reliable neural associations with trait questionnaires, and associations with task-based affective ratings fell outside canonical emotion regulation networks (e.g., prefrontal circuitry). Moreover, amygdala down-regulation, often interpreted as a stable individual marker, was confounded by person-specific whole-brain responses — a limitation extending to fMRI research beyond the emotion regulation domain. These findings challenge the assumption that an individual’s prefrontal activity is a valid indicator of their reappraisal capabilities and suggest that common trait, behavioral, and neural measures might capture distinct facets of emotion regulation. More broadly, our results highlight concrete methodological challenges for fMRI research on individual differences, with implications extending beyond emotion regulation to the neuroscience of personality, psychopathology, and general well-being. ### Competing Interest Statement The authors have declared no competing interest.

In functional magnetic resonance imaging, multivariate proxies of functional brain networks are commonly extracted using spatial independent component analysis. The theoretical premises of spatial overlap among functional processes and the time-varying nature of functional connectivity prompt the question of how to accurately model spatially overlapping and time-varying functional sources. Well-known functional networks have previously been shown to divide into spatially overlapping and functionally distinct subprocesses termedTemporal Functional Modes (TFM)using temporal independent component analysis on the time courses obtained via spatial independent component analysis. In this model, spatial and temporal modes of organisation interact through a single mixing matrix with fixed coefficients. Here, we introduce a time-resolved version termedTime-Resolved Instantaneous Functional Loci Estimation (TRIFLE)to estimate time-varying changes in source allocation. We analytically demonstrate that the originally fixed TFM mixing matrix can be expressed as the temporal average of a time-resolved mixing matrix, which in turn can be obtained in closed form and provides instantaneous estimates of brain network reconfigurations involved in distinct temporal functional modes. We apply TRIFLE to a high-temporal resolution functional magnetic resonance imaging dataset. We demonstrate that spatial source allocation aligns with expectations based on the experimental task design and that successful and unsuccessful trials have different allocation profiles. The proposed method sheds light on the temporal evolution of brain network reconfigurations while explicitly accounting for potential neuroanatomical overlap.

Self-identification as a victim of violence may lead to increased negative emotions and stress and thus, may change both structure and function of the underlying neural network(s). In a trans-diagnostic sample of individuals who identified themselves as victims of violence and a matched control group with no prior exposure to violence, we employed a social exclusion paradigm, the Cyberball task, to stimulate the re-experience of stress. Participants were partially excluded in the ball-tossing game without prior knowledge. We analyzed group differences in brain activity and functional connectivity during exclusion versus inclusion in exclusion-related regions. The victim group showed increased anger and stress levels during all conditions. Activation patterns during the task did not differ between groups, but an enhanced functional connectivity between the IFG and the right vmPFC distinguished victims from controls during exclusion. This effect was driven by aberrant connectivity in victims during inclusion rather than exclusion, indicating that victimization affects emotional responses and inclusion-related brain connectivity rather than exclusion-related brain activity or connectivity. Victims may respond differently to the social context itself. Enhanced negative emotions and connectivity deviations during social inclusion may depict altered social processing and may thus affect social interactions.

Emotion regulation is a critical factor implicated in diverse psychopathologies. However, evidence for the transdiagnostic feature of emotion regulation remains inconclusive. This study explored whether emotion regulation warrants designation as a transdiagnostic construct by examining its distinct neural basis compared to constructs within the existing Research Domain Criteria (RDoC) framework and searching for convergent regional brain activity during emotion regulation across psychiatric disorders. Thus, a two-step analysis approach was implemented. First, using coordinate-based meta-analyses, we reanalysed data from ten prior meta-analyses covering current RDoC domains, assessing unique and overlapping brain regions associated with emotion regulation. This analysis included 3.463 experimental contrasts from 78.338 healthy adults. Results indicated that emotion regulation overlapped with each RDoC domain, especially for those related to cognitive and social processes, yet maintained distinct neural patterns, particularly involving the inferior frontal and medial frontal gyrus. Second, in a separate and the most comprehensive meta-analysis to date, we analysed the neural patterns of emotion regulation in clinical populations. This analysis included 3.576 experimental contrasts from 342 participants, contrasting brain activation patterns during emotion regulation in patients suffering from psychiatric disorders with healthy controls. The findings highlighted the dorsomedial prefrontal cortex's role in emotion regulation across psychiatric disorders. Taken together, these findings support the transdiagnostic nature of emotion regulation by demonstrating its unique neural underpinnings within the RDoC framework and across psychiatric disorders. Recognising the critical importance of emotion regulation in both health and disease may help refine diagnostic criteria and develop treatment strategies, improving mental health outcomes through tailored therapeutic approaches.

As a primary risk factor for psychiatric vulnerability, childhood adversity (CA) leads to several maladaptive behavioral and brain functional changes, including domains of emotion, motivation, and stress regulation. Previous studies on acute stress identified the potential role of a striatum-centered network in revealing the psychopathology outcomes related to CA. To elucidate the interplay between CA, acute stress, and striatal functions in psychiatric disorders, more evidence from large-scale brain connectivity studies in diverse psychiatric populations is necessary. In a sample combining 150 psychiatric patients and 26 controls, we utilized “connectopic gradients” to capture the functional topographic organizations of striatal connectivity during resting-state scans conducted before and after stress induction. Connectivity gradients in rest and under stress were linked to different CA types and their frequency by Spearman correlation. Linear mixed models and moderation models were built to clarify the role of symptom strengths in these correlations. We found one type of CA—emotional neglect negatively predicted the post-stress-induction gradient shape, and stress reactive changes in the anterior-posterior orientation of the first-order striatal gradient. Moderation models revealed the observed correlations were selectively present in individuals with elevated comorbidity. Our results may provide new psychopathology-related biomarkers by tracking stress-induced changes in the general motivation systems. This demonstrates new perspectives in characterizing the striatal network and understanding its alterations in response to adverse childhood experiences.

Emotion has a significant impact on how related experiences are organized into integrated memories. However, the neurobiological mechanisms of how emotion modulates memory integration for related information with different valences remain unclear. In this between-subject functional magnetic resonance imaging (fMRI) study, we investigated different emotional modulations of memory integration by manipulating the valence of stimuli used in an associative memory paradigm. Three groups of participants were tested: one group integrated emotional (i.e., negative) information with neutral information, one group integrated two emotional pieces of information, and one control group integrated two neutral pieces of information. Behaviorally, emotional information facilitated its integration with neutral information but interfered with the other emotional information. Neurally, the emotion-induced facilitation effect, occurring on memory integration of neutral and emotional information, was associated with increased trial-specific reactivation in the hippocampus during both encoding and retrieval. This facilitated integration was also supported by strengthened hippocampal connectivity with the amygdala, as well as a set of neocortical areas related to emotion regulation and the default mode network (DMN). In contrast, the emotion-induced interference effect, occurring on memory integration of two emotional pieces of information, was associated with impaired hippocampal trial-specific reactivation during retrieval that appeared to offset the facilitating effect of increased reactivation during encoding. Similar but relatively weak hippocampal connectivity was found underlying this interfered integration. Taken together, emotional information facilitates memory integration with neutral information, while disrupting the integration with other emotional information, through distinct dynamical processes of hippocampal trial-specific reactivation and connectivity.

Stress-induced dysfunction of reward processing is documented to be a critical factor associated with mental illness. Although many studies have attempted to clarify the relationship between stress and reward, few studies have investigated the effect of acute stress on the temporal dynamics of reward processing. The present study applied event-related potentials (ERP) to examine how acute stress differently influences reward anticipation and consumption. In this study, seventy-eight undergraduates completed a two-door reward task following a Trier Social Stress Task (TSST) or a placebo task. The TSST group showed higher cortisol levels, perceived stress, anxiety, and negative affect than the control group. For the control group, a higher magnitude of reward elicited a reduced cue-N2 but increased stimulus-preceding negativity (SPN), suggesting that controls were sensitive to reward magnitude. In contrast, these effects were absent in the stress group, suggesting that acute stress reduces sensitivity to reward magnitude during the anticipatory phase. However, the reward positivity (RewP) and P3 of both groups showed similar patterns, which suggests that acute stress has no impact on reward responsiveness during the consummatory phase. These findings suggest that acute stress selectively blunts sensitivity to reward magnitude during the anticipatory rather than the consummatory phase.

Childhood adversity might impair corticolimbic brain regions, which play a crucial role in emotion processing and the acute stress response. The dimensional model of childhood adversity proposed that deprivation and threat dimensions might associated with individuals' development through different mechanisms. However, few studies have explored the relationship between different dimensions of childhood stress, emotion processing, and acute stress reactivity despite the overlapping brain regions of the last two. With the aid of the event-related potentials technique, we explore whether negative emotion processing, which might be particularly relevant for adaptive stress responding among individuals with adverse childhood experience, mediates the relationship between dimensional childhood stress and acute stress response. Fifty-one young adults completed a free-viewing task to evaluate neural response to negative stimuli measured by late positive potential (LPP) of ERPs (Event-related potentials). On a separate day, heart rate and salivary cortisol were collected during a social-evaluative stress challenge (i.e. TSST, Trier Social Stress Test). After the TSST, the childhood trauma questionnaire was measured to indicate the level of abuse (as a proxy of threat) and neglect (as a proxy of deprivation) dimensions. Multiple linear regression and mediation analysis were used to explore the relationship among childhood stress, emotion processing, and acute stress response. Higher level of childhood abuse (but not neglect) was distinctly related to smaller LPP amplitudes to negative stimuli, as well as smaller heart rate reactivity to acute stress. For these participants, smaller LPP amplitudes were linked with smaller heart rate reactivity to acute stress. Furthermore, decreased LPP amplitudes to negative stimuli mediated the relationship between higher level of childhood abuse and blunted heart rate reactivity to stress. Consistent with the dimensional model of childhood stress, our study showed that childhood abuse is distinctly associated with neural as well as physiological response to threat. Furthermore, the blunted neural response to negative stimuli might be the underlying mechanism in which childhood abuse leads to the blunted acute stress response. Considering that all the participants are healthy in the present study, the blunted processing of negative stimuli might rather reflect adaptation instead of vulnerability, in order to prevent stress overshooting in the face of early-life threatening experiences.

In line with the Research Domain Criteria (RDoC) , we set out to investigate the brain basis of psychopathology within a transdiagnostic, dimensional framework. We performed an integrative structural-functional linked independent component analysis to study the relationship between brain measures and a broad set of biobehavioral measures in a sample (n = 295) with both mentally healthy participants and patients with diverse non-psychotic psychiatric disorders (i.e. mood, anxiety, addiction, and neurodevelopmental disorders). To get a more complete understanding of the underlying brain mechanisms, we used gray and white matter measures for brain structure and both resting-state and stress scans for brain function. The results emphasize the importance of the executive control network (ECN) during the functional scans for the understanding of transdiagnostic symptom dimensions. The connectivity between the ECN and the frontoparietal network in the aftermath of stress was correlated with symptom dimensions across both the cognitive and negative valence domains, and also with various other health-related biological and behavioral measures. Finally, we identified a multimodal component that was specifically associated with the diagnosis of autism spectrum disorder (ASD). The involvement of the default mode network, precentral gyrus, and thalamus across the different modalities of this component may reflect the broad functional domains that may be affected in ASD, like theory of mind, motor problems, and sensitivity to sensory stimuli, respectively. Taken together, the findings from our extensive, exploratory analyses emphasize the importance of a dimensional and more integrative approach for getting a better understanding of the brain basis of psychopathology.