Large-scale T1-weighted MRI studies have established grey-matter abnormalities in bipolar disorder (BD), with our group contributing to consensus findings. However, structural connectivity, particularly within emotion- and reward-related circuits, remains poorly understood. Diffusion-weighted MRI (dMRI) enables investigation of white-matter pathways, yet prior work is constrained by small samples, methodological heterogeneity, and unclear medication effects. We conducted the largest dMRI network analysis in BD, relating symptom burden and polypharmacy to tractography-derived connectivity and graph-theoretic metrics.

Cross-sectional structural and diffusion MRI scans from 449 individuals with BD (35.7±12.6 years) and 510 controls (33.3±12.6 years), aged 18-65, were analyzed across 16 ENIGMA-BD sites. Standardized segmentation/parcellation and constrained spherical deconvolution tractography generated individual structural connectivity matrices. Graph-theoretic metrics of global and subnetwork organization were related to symptom severity and medications.

BD showed widespread network alterations (lower density and efficiency, longer path length, and higher betweenness centrality), altered microstructural organization in a limbic-basal ganglia circuit, and abnormal streamline counts in a default-mode/salience/fronto-limbic-basal ganglia network. Longer illness duration, later onset, and psychosis history were associated with greater abnormalities in network architecture, whereas more manic episodes were associated with greater fronto-limbic connectivity. Antidepressant (particularly SSRI), anticonvulsant, and antipsychotic use related to poorer global and fronto-limbic connectivity; no clear lithium effects emerged.

As the largest structural connectivity study in BD, we reveal widespread disruption in reward and emotion-regulation networks influenced by illness severity and medication use. Results show that multisite harmonization is feasible and highlight ENIGMA-BD as a scalable framework for identifying reproducible neurobiological markers.

Cognitive decline is common among the oldest-old, particularly in assisted living facilities (ALFs). This pilot randomized controlled trial examined the effects of aerobic, resistance, and mind-body exercises on cognition in ALF residents aged ≥80 years, and the feasibility and safety of exercise programs.

In a 24-week four-arm trial in one Shanghai ALF, 76 participants (aged 86.8 ± 4.1; 72.4% female) were randomized to aerobic, resistance, mind-body (simplified Tai Chi), or non-exercise control groups. Thirty-minute exercise sessions were delivered three times weekly for 24 weeks. Cognition was assessed at baseline, Week 12, and Week 24 using the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), Immediate Story Recall (ISR), Boston Naming Test (BNT), Trail Making Test-A (TMT-A), and Trail Making Test-B (TMTB). Data were analyzed using intention-to-treat baseline-adjusted linear mixed-effects models with Holm-adjusted pairwise contrasts.

Recruitment was 65.5%; mean exercise attendance was 90.1%, and no intervention-related serious adverse events occurred. At week 24, aerobic and mind-body groups showed higher MMSE scores than control (aerobic-control Δ = 3.45, 0.92 to 5.99, p_Holm = 0.0481; mind-body-control Δ = 3.29, 0.81 to 5.77, p_Holm = 0.0492). Mind-body exercise showed higher ISR scores than control (ISR Δ = 9.84, 3.22 to 16.46, p_Holm = 0.0234), whereas aerobic exercise showed better TMT-B performance than control (TMT-B Δ = -25.66 s, -41.95 to -9.37, p_Holm = 0.0137). MoCA, BNT, and TMT-A differences were not significant after multiple-comparison correction.

These exercise programs were feasible and safe in ALF residents aged ≥80. Aerobic and mind-body exercise improved specific cognitive outcomes, while larger trials are needed to confirm these findings.

This study was registered on Chinese Clinical Trail Registry (ChiCTR2500111703).

This study aimed to identify the risk factors for suicide attempts among Chinese patients with major depressive disorder (MDD) and explore the mediating role of suicidal ideation between childhood sexual abuse and suicide attempts.

Data were derived from a multi-center investigation conducted in nine hospitals across six provinces of China. Suicide attempt status was assessed using the suicide module of the Mini International Neuropsychiatric Interview (MINI), and childhood maltreatment was evaluated via the Childhood Trauma Questionnaire (CTQ). Multivariable logistic regression was used to identify factors associated with suicide attempts, and path analysis-based mediation models were performed to examine the mediating role of suicidal ideation in the relationship between childhood sexual abuse and suicide attempts.

A total of 1084 MDD patients were enrolled, among whom 120 (10.1%) had a history of suicide attempts. Logistic regression analysis showed that suicidal ideation (OR = 8.73, P < 0.001) and an earlier age at depression onset (OR = 0.95, P = 0.015) were independent factors associated with suicide attempts. Mediation analysis revealed that childhood sexual abuse was significantly and positively associated with suicidal ideation (β = 0.072, P = 0.018), which in turn was strongly positively associated with suicide attempts (β = 0.267, P < 0.001).

Earlier depression onset and suicidal ideation are associated with suicide attempts in Chinese MDD patients. Childhood sexual abuse is indirectly associated with suicide attempts through its positive association with suicidal ideation. This finding provides targeted insights for suicide prevention strategies for Chinese MDD patients.

Finding indicators of early response to antidepressant treatment in EEG signals recorded from patients suffering from major depressive disorder.

Functional brain connectivity networks based on weighted imaginary coherence and weighted imaginary mean phase coherence were computed for 176 patients for 6 different EEG frequency bands. Cross-hemispheric connectivity (CH) and lateral asymmetry (LA) were estimated from these networks based on EEG signals recorded before the beginning of treatment (Vis1) and one week after the start of the treatment (Vis2). Repeated measures ANOVA was used to check for statistically significant changes in connectivity based on these measures at Vis2 w.r.t. Vis1. Post-hoc analysis was performed with multiple pairwise comparison tests to determine which group means were significantly different.

It was found that CH_Vis2 was significantly reduced w.r.t. CH_Vis1 in the β₁ [12.5 - 17.5 Hz] frequency band for the responders to treatment. Also, LA_Vis2 was significantly increased w.r.t. LA_Vis1 in the β₁ frequency band for the responders. No such significant changes were observed for the non-responders. Brain networks constructed using both weighted imaginary coherence and weighted imaginary mean phase coherence were found to exhibit these results. For the CH connectivity changes, binarized networks and for the LA connectivity changes, weighted networks were found to be more reliable.

Responders were found to show a reduction in cross-hemispheric connectivity and an increase in lateral asymmetry, both in the β₁ band while no such change was observed for the non-responders.

Decrease in cross-hemispheric connectivity and increase in lateral asymmetry in the β₁ band may represent candidate neurophysiological indicators of early treatment response, but they require independent replication before any clinical application can be considered.

Visual perceptual functions are frequently disrupted in patients with schizophrenia. The nature and degree of the visual abnormalities experienced by patients provide important information about altered cognitive mechanisms and may serve as potential endophenotypes for classification and diagnosis of schizophrenia.

To characterize dynamic and integrative visual functions and distinguish patients with schizophrenia from healthy controls, we compared performance on six visual tasks between patients and healthy controls. The tasks included binocular rivalry (interocular dynamics), structure from motion (3D-surface dynamics), surround suppression of contrast (contextual modulation), contour integration (form integration), coherent motion (motion integration), and motion speed discrimination (motion sensitivity). The same set of tests was conducted in 61 early-stage outpatients and 69 chronic inpatients and controls, allowing us to see the effects of long-term treatment on patients' visual functions.

Compared with healthy controls, patients experienced slower switching in binocular rivalry but faster switching in structure from motion, along with impaired spatial form integration. Inpatients had reduced motion sensitivity, while outpatients had deficits in motion integration, two groups differed in susceptibility to surround contrast suppression. Multidimensional test data supported more accurate classification between patients and controls.

Patients with schizophrenia have specific patterns of visual perceptual abnormalities in dynamic and integrative information processing, with deficit in coherent motion (considered more state-linked) more apparent in early-stage outpatients and poor motion speed discrimination (linked to stable traits) seen in chronic inpatients. There is a significant advantage of using multiple independent tests to assist in the classification and diagnosis of schizophrenia.

Linguistic deficits are core features of schizophrenia. Perplexity (PPL) and pseudo-perplexity (PPPL), derived from language models, serve as probabilistic metrics of contextual uncertainty. This study investigated their utility as objective markers for distinguishing patients with schizophrenia from healthy controls.

Speech samples were collected from 249 Korean-speaking patients with schizophrenia and 159 healthy controls across eight tasks, including free, emotional, and projective narratives. PPL and PPPL were calculated using autoregressive and bidirectional models, respectively. Group differences were assessed via Rank ANCOVA, adjusting for age, sex, education, and token count. Additionally, exploratory analyses examined correlations with clinical symptom severity.

Patients exhibited significantly elevated PPL and PPPL values compared to controls across most tasks, a finding consistent across different model architectures. Exploratory correlation analyses indicated that both metrics were associated with global cognitive impairment (CGI-SCH Cognition) and difficulty in abstract thinking (PANSS N5), linking linguistic deviations to psychopathological severity.

Elevated PPL and PPPL effectively characterize linguistic deviations in schizophrenia, reflecting heightened contextual uncertainty in language modeling associated with the underlying psychopathology. These findings support the utility of language models as automated, scalable tools for objectively quantifying linguistic pathology and elucidating the neurocognitive substrates of schizophrenia.

Interpersonal emotion regulation (IER) is crucial for social coordination and inherently bidirectional, yet research has predominantly focused on how regulators affect targets, often neglecting the regulator's own experience and the dyadic neural dynamics supporting mutual benefits. This study (N = 68, average age: M = 20.61 ± 1.56, 100% female, collected in 2024 in China) investigated the behavioral and neural mechanisms of bidirectional benefits in IER, examining strategy-dependent (cognitive reappraisal, distraction) and role-specific (regulator, target) neural dynamics using functional near-infrared spectroscopy hyperscanning. Behaviorally, cognitive reappraisal induced greater valence improvement for both roles compared to distraction. At the single-brain level, prefrontal regions (frontopolar, left orbitofrontal cortex) and the right Broca area showed distinct activation patterns contingent on strategy and role; regulators exhibited stronger activation during cognitive reappraisal, while targets displayed pronounced right-lateralized activation (right orbitofrontal cortex, right Broca area) during distraction, supporting differing cognitive demands. Critically, multivariate pattern analysis of interbrain synchronization revealed that distributed patterns of neural coordination successfully decoded both the IER strategy employed and, notably, regulatory success for both regulators and targets. The regulator's frontopolar synchronization emerged as pivotal in these predictive interbrain synchronization patterns. These findings demonstrate that successful IER relies on a combination of role-dependent neural specialization and dyad-specific, strategy-aligned interbrain coordination, advancing our understanding of IER as a dynamic, multibrain process facilitating mutual emotional alignment. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

War-traumatized adolescents are at heightened risk of persistent anger and emotional dysregulation, which can impair mental health, social functioning, and community adjustment. Evidence-based interventions that specifically address anger in humanitarian settings remain limited. This study aimed to examine the feasibility, acceptability, and preliminary outcomes of a culturally adapted cognitive behavioral group intervention for reducing anger among war-affected adolescents in Jordan.

A single-arm pretest-posttest design was employed with 50 Syrian and Palestinian adolescents exposed to war-related trauma. Participants completed an eight-session group intervention focused on cognitive restructuring and emotion regulation. Anger severity and emotion regulation were assessed before and after the intervention using validated self-report measures.

The intervention demonstrated high feasibility, with full participant retention and strong treatment fidelity. Statistically significant reductions in anger severity were observed following the intervention, alongside improvements in emotion regulation. Outcomes were comparable across nationality and socioeconomic background.

The findings indicate that a culturally adapted cognitive behavioral group intervention is feasible and acceptable in a humanitarian context and may reduce anger among war-traumatized adolescents. Although the absence of a control group and follow-up data limits causal interpretation, the intervention shows promise for integration into community and humanitarian mental health services. Future research should evaluate effectiveness using randomized controlled designs with longer-term follow-up.

This study examines the impact of artificial intelligence (AI)-powered remote learning platforms on students' academic performance and mental health in resource-scarce environments, with a focus on educational equity and sustainable mental health outcomes. We conducted a 12-week randomized controlled trial (RCT) to compare the effects of AI-powered platforms and traditional face-to-face teaching on academic performance, emotional regulation, anxiety, depression, and related indicators. The participants were high school and university students, with pre- and post-assessments used to evaluate both academic outcomes and mental health. Data were analyzed using Structural Equation Modeling (SEM) and Bootstrap. The results show that the AI platform significantly improved students' academic performance (p < 0.001), a finding linked to personalized learning pathways and real-time feedback. Moreover, the AI intervention effectively reduced anxiety (β = -3.378, p < 0.001) and depression (β = -2.919, p < 0.001). However, its effect on emotional regulation was not statistically meaningful (p > 0.05), indicating that while AI systems can alleviate emotional distress, their effect on emotional regulation remains limited. In summary, the study provides evidence that AI-powered learning can narrow equity gaps in resource-scarce contexts, particularly by strengthening academic achievement and reducing negative emotional symptoms. Future studies could extend intervention periods and provide more specialized emotional support to improve both educational and psychological outcomes. These findings highlight the role of educational technology in promoting equity and wellbeing, while also noting the need for context-specific strategies to address emotional regulation.

While social media has become an important medium for adolescents in terms of identity development, belonging, news consumption and public participation, the recommendation algorithms and attention-economy-based design features of platforms can shape adolescents' preferences and weaken their autonomous decision-making processes. This study provides a principle-based bioethical analysis of Australia's regulation (Online Safety Amendment [Social Media Minimum Age] Act 2024; effective: 10 December 2025), which aims to prevent users under the age of 16 from creating accounts on certain social media platforms and maintaining existing accounts, within the framework of digital paternalism and adolescent autonomy. Beauchamp and Childress' principle-based bioethical approach was adopted as the methodology; the regulation was discussed in terms of the principles of respect for autonomy, non-maleficence, beneficence, and justice. The analysis suggests that while the ban can be ethically justified as a protective public health intervention in the context of mental health risks and potential harms of usage, there are debates that the age-based categorical limit does not sufficiently consider the principle of evolving capacities and adolescents' rights to expression/participation. Furthermore, the absolute age ban may generate secondary and unintended harms, such as weakening social support and help-seeking channels, increasing digital inequalities, and directing users towards less secure online environments. The evaluation conducted in this article concludes that, instead of absolute age-based bans, it is recommended to adopt gradual autonomy models, guide companies towards protective and safe design approaches for children, impose a duty of care specific to children on platforms, ensure algorithmic transparency, and adopt a rights-based approach to child protection.