Prior observational studies have reported conflicting results regarding whether antidepressant treatment reduces long-term dementia risk, likely due to confounding by indication and reverse causation. We aimed to investigate the association between baseline antidepressant use and incident dementia, incorporating cognitive and neuroimaging outcomes.

We conducted a prospective cohort study using UK Biobank participants free of dementia at baseline. Antidepressant use was self-reported at baseline (2006–2010). Incident dementia was identified through linked electronic health records until December 19, 2022. Cox proportional hazards models estimated hazard ratios (HRs) for all-cause dementia, Alzheimer’s disease (AD), and vascular dementia (VD), adjusting for sociodemographic, lifestyle, health-related, antidepressant indication factors, and co-medication of other anticholinergics. In subsamples, cognitive performance (n = 57,330) and structural brain imaging (n = 42,276) were examined as intermediate outcomes.

Among 461,464 participants, 33,721 (7.3%) reported baseline antidepressant use. Over a mean follow-up of 13.4 years, 7,922 (1.7%) developed incident dementia. Baseline antidepressant use was associated with higher risks of all-cause dementia (adjusted HR: 1.47, 95% CI 1.36–1.60), AD (1.53, 1.36–1.73), and VD (1.44, 1.23–1.70). Users performed worse on fluid intelligence and prospective memory tasks and showed lower total and gray matter volume, regional reductions in the hippocampal gray matter and basal nucleus, and greater white matter hyperintensity volume.

Baseline antidepressant use was linked to a higher risk of dementia, poorer cognitive performance, and adverse brain structural changes. These findings underscore the importance of judicious prescribing, regular cognitive monitoring, and consideration of non-pharmacological approaches in clinical care.

Adolescent depression often presents with somatic complaints, and its clinical manifestation is strongly shaped by cultural context. In non-western districts, psychological distress is frequently expressed through physical symptoms; a tendency that, combined with mental health stigma and culturally influenced health beliefs, complicates accurate detection, diagnosis and treatment. Standardised diagnostic tools developed in Western populations may overlook culturally specific symptom patterns, contributing to under-recognition and inadequate care. Despite the global impact of adolescent depression, cross-cultural symptom-level studies remain limited, hindering the development of culturally responsive mental health strategies.

This study aims to compare somatic-depressive symptom networks in Chinese and Rwandan adolescents using symptom-level network analysis, to identify culturally distinct central and bridge symptoms, and to assess structural differences between symptom networks across groups.

A cross-sectional sample of 3830 adolescents (China: n = 2017, mean age 15.35 ± 1.56; Rwanda: n = 1813, mean age 15.80 ± 1.90) completed culturally adapted versions of the Patient Health Questionnaires for somatic symptoms (PHQ-15) and depression (PHQ-9). Gaussian Graphical Models were estimated in R to construct symptom networks. Centrality measures (expected influence and bridge expected influence) were used to identify influential symptoms within each group. Network Comparison Tests were conducted to examine differences in global strength and network structure, and bootstrapping was employed to assess network stability.

Depressive symptoms were more prevalent among Rwandan adolescents (54.6%) than among Chinese adolescents (29.2%), whereas somatic symptoms were more commonly reported by Chinese participants (71.0% v. 64.0%). Low energy and sleep problems emerged as key bridge symptoms in both groups. Cultural differences were observed in central symptoms: psychomotor impairment and chest pain were central symptoms in Rwanda, whereas dizziness and headaches were central in China. Network structure differed significantly between groups (S = 0.99, p < 0.05), with culturally specific symptom connections.

The findings revealed distinct central and bridge symptoms in Chinese and Rwandan adolescents, reflecting culturally patterned architectures of symptom expression and distress reporting. These results highlight the need for culturally adapted screening tools and symptom-level interventions that target culture-specific symptoms to improve adolescent mental health care globally.

Attention-deficit/hyperactivity disorder (ADHD) involves altered neurodevelopment, yet the underlying mechanisms remain elusive. Aperiodic EEG components may reflect neural functions like excitatory/inhibitory balance, but their age-related differences in ADHD and link to default mode network (DMN) dysfunction are unexplored.

We included 110 medication-naïve children/adolescents with ADHD and 100 matched typically developing peers aged 6–14 years. Aperiodic parameters (exponent, offset) were derived, and source-localized alpha-band DMN coherence was computed. The sample was stratified into middle childhood (6–9 years) and early adolescence (10–14 years) subgroups to delineate age-dependent patterns.

ADHD showed globally increased exponent and offset versus controls. Normative age-related decreases were significantly attenuated in ADHD, indicating divergence from typical development. Age-stratified analyses revealed distinct patterns: in middle childhood, increased frontal offset correlated positively with inattention (right hemisphere) and hyperactivity/impulsivity (left hemisphere); in early adolescence, it associated with reduced coherence in two DMN pathways (right mSFG–left hippocampus and left mSFG–right MTG).

Aperiodic activity differences in ADHD are age-dependent. Younger children exhibit focal, symptom-linked frontal abnormalities, whereas adolescents show pervasive network-level dysregulation. Aperiodic measures may capture age-varying ADHD pathophysiology, informing developmentally targeted biomarkers.

Neuropsychiatric symptoms (NPSs) are prevalent in Alzheimer’s disease (AD), yet their neurobiological etiology remains elusive. We investigated relationships between NPS subsyndromes, plasma neurofilament light chain (NFL), AD-vulnerable brain atrophy, and cognition.

We included 146 participants from a Chinese cohort. NPSs were assessed using the Neuropsychiatric Inventory Questionnaire and clustered into four subsyndromes (hyperactivity, psychosis, affective, apathy), each graded by severity (none, mild, severe). Sequential mediation analyses examined whether NPSs influence cognition through NFL and atrophy. Additionally, 1534 ADNI participants were enrolled to (1) replicate mediation effects; (2) examine longitudinal relationships of NPSs with incident cognitive decline; and (3) evaluate cognitive discrimination of NPSs and NFL and onset hazards of NPS subsyndromes.

In the discovery cohort, global NPSs burden and three subsyndromes (hyperactivity, affective, apathy) were associated with elevated plasma NFL, poorer global cognition and memory, and reduced brain volumes (all P < 0.05). Sequential mediation revealed that plasma NFL and atrophy mediated the cross-sectional NPSs–cognition relationship, replicated in ADNI. Adding NPSs and NFL improved cognitive discrimination (AUC: 0.6754 to 0.8210, P < 0.001). Additionally, apathy and psychosis showed lower onset hazards than affective and hyperactivity (both P < 0.001).

Baseline NPSs were cross-sectionally associated with elevated NFL, brain atrophy, and poorer cognition. Sequential mediation models supported a pathway linking NPSs to cognition via NFL and atrophy, though longitudinal evidence did not fully confirm temporal directionality. These hypothesis-generating findings require prospective validation.

Depression is associated with pathological dysregulations affecting both the brain and the body, with the latter being reflected in plasma proteins. While plasma protein signatures of depression have been increasingly recognized, a holistic examination of interactions with brain features is lacking.

Leveraging data from 3,966 UK Biobank participants, we identified a multimodal neuroimaging-plasma protein component of depression (NeuroPro-Dep) by integrating plasma proteins and five brain modalities via an ICD-10 diagnosis-constrained multimodal fusion approach.

Notably, NeuroPro-Dep demonstrates detectable associations with depression symptoms across datasets from diverse populations, underscoring its clinical potential. This capability is anchored in its five brain modalities alterations, including hippocampal atrophy, reduced cortical sensorimotor network functional connectivity, and impaired internetwork structural connectivity of the frontoparietal network. The multimodal neuroimaging-derived plasma protein modality of NeuroPro-Dep is enriched in metabolic pathways, as further supported by association analysis linking this modality to body mass index (BMI), type 2 diabetes, and other metabolic indicators. Crucially, two-step Mendelian randomization analysis revealed that the NeuroPro-Dep plasma protein modality exerts a causal effect on depression through BMI (plasma protein to BMI: or=0.28, p=0.035; BMI to depression: or=1.14, p=4.37×10−11).

Overall, this study underscores metabolic dysfunction as a bridge between brain changes, depression, and physical diseases, while providing a novel multimodal biological signature and valuable insights that may inform future treatment strategies.

Although home is frequently the preferred place of death, little is known regarding how home healthcare (HHC) influences this outcome for people with dementia (PWD), particularly within Asian contexts. This study investigates the impact of HHC and its 2016 “Integrated Home-Based Medical Care” reform on home death in Taiwan, explicitly accounting for the cultural phenomenon of “impending death discharge.”

This nationwide retrospective cohort study utilized Taiwan’s National Health Insurance Research Database. We identified PWD decedents from 2011 to 2022 and conducted a nested case–control analysis. Cases (home deaths) and controls (hospital deaths) were matched 1:1 using propensity scores to balance demographics and health status. HHC models included pre-2016 primary HHC, post-2016 primary HHC, and the reformed “HBPC Plus” (Home-Based Primary Care Plus). The outcome was adjusted to include patients discharged terminally to die at home, reflecting distinctive cultural practices.

Among 209,468 decedents, 95,594 were selected after matching. Overall, HHC use was associated with higher odds of home death (adjusted odds ratio [aOR]: 1.17; 95% CI: 1.13–1.21). The reformed HBPC Plus program showed the strongest association compared to pre-2016 primary HHC (aOR: 1.63; 95% CI: 1.34–1.98). Crucially, this association strengthened further when accounting for impending death discharge (aOR: 1.82; 95% CI: 1.40–2.35). Higher visit frequency and services from hospital-based teams were also significantly linked to home death.

HHC significantly increases the likelihood of home death among PWD in culturally influenced contexts. The 2016 reform, particularly the HBPC Plus program, proved highly effective. Policy components like flexible visit frequencies and enhanced hospital–physician coordination appear vital for supporting end-of-life care at home, offering key insights for policy planning in aging societies.

Intrusive trauma memories – vivid, distressing recollections that occur involuntarily and may feel present – is a defining symptom of post-traumatic stress disorder (PTSD). While traditional models emphasize dysregulation within limbic-prefrontal circuits, emerging evidence implicates visual sensory systems in the formation of trauma-memory intrusions. However, direct causal evidence remains lacking.

We combined functional MRI with repetitive transcranial magnetic stimulation (rTMS) to examine the causal role of visual sensory cortices in intrusive memory formation. Healthy participants underwent a trauma-film paradigm, followed by fMRI scanning during memory encoding and a post-encoding resting phase during which spontaneous intrusions were recorded. One group received 1-Hz rTMS targeting early visual cortex (V1/V2); a control group received stimulation at the Vertex. Intrusive memories were recorded over the subsequent 7 days.

rTMS to V1/V2 significantly reduced the frequency, vividness, and emotional intensity of intrusive memories, while preserving recognition of episodic gist. fMRI analyses showed that intrusive episodes were associated with heightened activation and stable neural representations within the occipital visual cortex (OVC). Functional and effective connectivity analyses further revealed that the occurrence of intrusions was predicted by interactions between the middle frontal gyrus (MFG) and OVC. Dynamic causal modeling confirmed direct, bidirectional MFG-OVC interactions that coexisted with, but tracked the intrusion dynamics more closely than, the traditional prefrontal-limbic circuits.

These findings provide the first causal evidence for the direct involvement of the early visual cortex in trauma-memory intrusions. They highlight the visual system as a novel neuromodulation target for therapeutic intervention on PTSD.

The term ‘schizo-obsessive comorbidity (SOC)’ is used to describe the presence of obsessive-compulsive symptoms or obsessive-compulsive disorder (OCD) in patients with schizophrenia (SOC). Recent studies have found overlapped executive dysfunctions in SCZ and OCD implicating shared pathophysiology. However, specific deficits in the components of executive function (EF) in patients with SOC remains unclear.

We recruited 37 patients with SOC, 68 patients with SCZ, 70 patients with OCD, and 59 healthy controls (HCs). All participants completed a battery of measures for EF components, namely initiation, sustained attention, online updating, switching, disinhibition, and planning. Apart from traditional group-mean analysis, we applied machine learning approaches to identify the unique patterns of EF among different clinical groups.

The results showed that the three clinical groups could be distinguished from HCs. The feature importance analysis showed that, to classify clinical groups from HC, online updating was the core feature of SCZ patients, whereas disinhibition and online updating jointly determine classification between OCD patients and HC. In differentiating SOC from HC, online updating, planning, and disinhibition collectively served as key features. Machine learning algorithms classified SOC and OCD with acceptable performance but classified SOC and SCZ with lower performance.

Deficits of EF are shared features among patients with SOC, SCZ, and OCD. However, the specific components of executive dysfunction in these clinical groups appeared distinct.

Anxiety disorders are highly prevalent yet lack objective biomarkers. Whereas threat-related attentional biases are well documented, less is known about broader eye movement alterations that may characterise anxiety.

To characterise multi-paradigm eye movement profiles in anxiety disorders and evaluate their potential as behavioural markers for disorder differentiation.

Eye movements were recorded in 91 patients with anxiety disorders, 118 with depressive disorders and 98 healthy controls during free viewing of neutral-stimuli, smooth-pursuit and fixation-stability tasks. Principal component analysis was applied to derive latent eye movement dimensions, which were then tested for group differences, associations with symptom severity and classification performance.

Compared with both patients with depression and healthy controls, patients with anxiety disorders exhibited hyper-scanning during free viewing, characterised by increased saccade frequency and path length, and hyper-pursuit during smooth pursuit, reflected in increased velocity gain, fewer intrusive saccades and more catch-up saccades. Principal component analysis identified six latent components, among which active visual exploration, pupillary arousal and smooth-pursuit control demonstrated robust group differences. Machine learning models trained on 6 components yielded areas under the receiver operating characteristic curve of 0.82 for anxiety versus healthy controls, 0.83 for depression versus healthy controls and 0.61 for anxiety versus depression.

Hyper-scanning and hyper-pursuit emerge as defining eye movement signatures of anxiety, linking core mechanisms of vigilance and prediction with measurable behavioural markers. These insights position eye-tracking as a promising behavioural modality for mechanism-informed differentiation across affective disorders.