Brain and Behavior

Background and Objectives Transient ischemic attack (TIA) diagnosis is challenging because it relies mainly on clinical assessment and exclusion of common differential. Functional MRI (fMRI) may provide a diagnostic biomarker by detecting transient brain dysfunction not visible on conventional imaging. This pilot study aimed to characterize acute motor-task BOLD activation in patients with suspected DWI-negative TIA and compare functional patterns between confirmed TIA and alternative diagnoses. Secondary objectives were to assess longitudinal changes in activation and connectivity at 3 months. Methods In this prospective single-center study, adults presenting within 24 h of transient anterior-circulation neurological symptoms underwent conventional MRI and additional motor-task fMRI. Patients with acute DWI lesions were excluded. Final diagnosis was established after 3-month follow-up. Whole-brain analyses, individualized motor cortex region-of-interest (ROI) analyses, and generalized psychophysiological interaction (gPPI) connectivity analyses were performed during the acute phase and at 3 months. Results Eight patients were enrolled; six had complete longitudinal imaging data and were included in the final analyses. Final diagnoses were TIA (n=2), migraine aura (n=2), functional neurological disorder (n=1), and hypoglycemia (n=1). Whole-brain and ROI analyses showed reduced bilateral motor-related BOLD responses during the acute phase in both TIA patients and in the patient with hypoglycemia. In contrast, patients with migraine and functional neurological disorder exhibited less marked longitudinal changes. In TIA patients, motor cortex activation increased at 3 months, tending to normalize toward values observed in non-TIA participants. Connectivity analyses revealed heterogeneous patterns, but the 2 TIA patients demonstrated increased longitudinal connectivity between the motor cortex contralateral to symptoms and other sensorimotor regions, including supplementary motor, premotor, parietal, and postcentral cortices. Discussion These preliminary findings suggest that TIA may be associated with transient bilateral reductions in motor-network activity. Functional abnormalities appeared to improve over time, supporting the hypothesis of reversible network dysfunction. Although limited by the very small sample size, this study provides the first longitudinal assessment of emergency task-based fMRI in rigorously defined TIA and supports further investigation of acute functional MRI as a potential biomarker of transient cerebral dysfunction.

Exposure to armed conflict can leave persistent effects on mental health, yet its neurophysiological correlates remain poorly characterized, particularly in populations exposed to prolonged violence outside narrowly defined post traumatic stress disorder samples. Here we examined resting state electroencephalographic activity in 122 Colombian adults, including 74 participants exposed to armed conflict and 48 controls. Eyes closed EEG was analysed for 240 seconds per participant. We quantified absolute and relative spectral power across delta, theta, alpha and beta bands and regional functional connectivity using weighted phase lag index in theta, alpha and beta. Group comparisons were adjusted for age, education, sex and assessment year, with correction across 78 EEG contrasts. Median occipital and global alpha power was lower in exposed participants, although adjusted estimates were close to the null and confidence intervals were broad. Temporal theta relative power was lower in exposed participants at nominal significance, but this association did not survive Holm correction. No spectral power or regional connectivity contrast remained significant after multiple testing correction. Exploratory associations between EEG measures and MoCA performance were modest in participants with confirmed scores. These findings provide a systematic characterization of resting EEG after exposure to armed conflict in a population shaped by prolonged violence and displacement. They also indicate that large or widespread alterations in resting spectral power and connectivity were not detectable with the current sample and analytical framework, while defining candidate signals and methodological priorities for larger studies of conflict related brain health.

Objective: Mindfulness is a robust predictor of mental health, yet the psychometric properties of the short-form Five Facet Mindfulness Questionnaire (FFMQ-15) have not been examined in Iranian populations. This study evaluated the psychometric properties, factor structure, and diagnostic utility of the FFMQ-15 among medical sciences students. Participants: A total of 348 students (178 females, 170 males) from Kermanshah University of Medical Sciences participated. Methods: Participants completed the FFMQ-15, Penn State Worry Questionnaire (PSWQ), Difficulties in Emotion Regulation Scale (DERS), and Emotion Regulation Questionnaire (ERQ). Data were analyzed using exploratory and confirmatory factor analyses, composite reliability, and ROC curve analysis. Results: Both EFA and CFA supported the five-factor model, revealing a culturally unique item loading pattern. The FFMQ-15 demonstrated strong convergent and discriminant validity. ROC analysis indicated acceptable diagnostic accuracy for distinguishing high- and low-worry groups (AUC = 0.72, 95% CI: 0.66-0.78). Conclusions: The FFMQ-15 demonstrated acceptable psychometric properties in Iranian medical students. The non-reactivity facet exhibited cultural variability, suggesting that cross-cultural adaptation is essential. The instrument shows promise for screening in high-stress educational settings.

Introduction: Neuroinflammation is a known pathophysiologic mechanism in multiple sclerosis and a proposed mechanism in fibromyalgia and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Positron Emission Tomography (PET) imaging of the translocator protein (TSPO) has been widely used to measure neuroinflammation, though second-generation ligands are highly sensitive to a single nucleotide polymorphism, rs6971, resulting in high, mixed, and low affinity binders. It is unknown whether this polymorphism is associated with neuroinflammatory disorders. Materials and Methods: Eighty-six total participant genotypes for TSPO binding affinity were identified through Sanger sequencing (30 fibromyalgia, 21 ME/CFS, 11 multiple sclerosis, and 24 healthy controls). Associations between patient group and genotype were assessed with Fishers Exact test. Associations between genotype and symptom severity from self-report questionnaires were assessed with Kruskal-Wallis tests. Results: In the present study individuals with fibromyalgia, (ME/CFS), or multiple sclerosis were more likely to have a mixed- or low-affinity genotypes compared to healthy controls. Presence of the low or mixed genotypes were also associated with greater self-reported fatigue severity and depressive symptoms. Discussion: These findings should be confirmed in larger samples but suggest functional consequences of rs6971 polymorphism that may be related to the pathophysiology of pain and fatigue illnesses.

BACKGROUND: One in three adolescents with a concussion history report experiencing long-lasting somatic, sleep, emotional, and/or cognitive disturbances (persisting symptoms after concussion (PSaC)). Cognitive difficulties, such as attentional problems, are common symptoms and can interfere with ongoing development. Clinically, psychiatric symptoms also present in youth with PSaC. A concussion causes diffuse functional and microstructural alterations to neural networks. To develop targeted treatments for PSaC (e.g., neurostimulation), we need to understand how and where structural alterations and neural dysfunction intersect to cause long-lasting symptoms. OBJECTIVES: 1) Identify functional and microstructural properties in intrinsic connectivity networks, as well as neuropsychological outcomes, that differentiate adolescents with concussion with PSaC from those who do not have PSaC. 2) Determine whether neural activity within intrinsic connectivity networks mediates the relationship between network microstructure and specific neuropsychological features in adolescents with concussion. METHODS: CAMBY is a prospective study of adolescents aged 12 to 18 years with a history of concussion. Participants are allocated based on recovery status (PSaC vs. No-PSaC (recovered controls)). Advanced structural (magnetic resonance imaging; MRI) and functional (magnetoencephalography; MEG) neuroimaging and neuropsychological measures will be collected one month or more after concussion. Microstructural and functional features will be computed within intrinsic connectivity networks, then compared between PSaC and recovered control groups and related to symptom domains and neuropsychological profiles. IMPACT: This will be the first study to integrate MRI, MEG, and neuropsychology in adolescents with PSaC to identify disrupted networks underlying PSaC. This observational study is a necessary step towards future clinical trials that accurately target promising therapeutic neurostimulation protocols.

Stroke is a leading cause of mortality and disability in Uganda, with a prevalence of approximately 2.5% and a 25-30% 30-day mortality rate, exacerbated by limited access to predictive tools and advanced diagnostics. Machine learning (ML) offers potential for early stroke risk stratification, but its application in resource-constrained settings like Uganda requires tailored models and rigorous performance evaluation, as well as assessment of misclassification patterns. This study aimed to develop and internally validate an ML-based predictive model for stroke using clinical and socio-demographic characteristics among patients at Mulago National Referral Hospital (MNRH) and residents of Wakiso District, Uganda, identify key predictors and assess misclassification patterns to enhance targeted prevention. A retrospective case-control study utilized secondary data from 1,016 participants (254 stroke cases, 762 controls) across three prior studies conducted between 2006 and 2015. Eight ML algorithms were evaluated using 5-fold cross-validation, with performance metrics including accuracy, sensitivity, positive predictive value, F1-score, and area under receiver operator characteristics curve (AU-ROC). McNemars test compared model classification performance of the top 2 models. Feature importance identified key predictors, and misclassification patterns were analyzed using classification matrix and line graphs. The Random Forest (RF) model achieved the highest performance (95.18% accuracy, 90.10% F1-score, 97% AU-ROC). McNemars test confirmed RFs superior classification (p=0.01). Age, systolic blood pressure, total cholesterol, and waist-hip ratio were the top drivers of RF stroke predictions. RF misclassified 8.3% of stroke cases and 3.3% of non-stroke cases, due to overlaps in risk profiles (e.g., lower cholesterol, systolic blood pressure and age in false negatives). The RF model demonstrates strong potential for stroke risk prediction in Uganda, leveraging routine data to prioritize high-risk individuals. Misclassification analysis highlights areas for model refinement, supporting its potential for integration into clinical workflows for early intervention and stroke prevention in resource-limited settings. Future external validation across diverse populations is recommended.

Introduction: Cognitive intraindividual variability (IIV), a measure of fluctuation in performance across time or tasks, is an emerging marker of cognitive decline. However, little is known about within-domain IIV in Latino adults. To address this gap, we examined memory IIV and hippocampal integrity in older Latino individuals. Methods: Sixty-seven participants from the Boston Latino Aging Study underwent cognitive testing and MRI. Linear regressions assessed whether memory IIV was associated with hippocampal volume and hippocampus-cingulum tract fractional anisotropy. Additional analyses evaluated associations using mean memory performance as the outcome. Results: Higher mean performance was associated with greater hippocampal volume (=0.24, p=.03), while memory IIV was not (=0.028, p=.84). Higher memory IIV was associated with lower fractional anisotropy in the hippocampus-cingulum tract (=-0.34, p<.01), while mean performance was not (=-0.07, p=.52). Discussion: Memory IIV may be more closely linked to hippocampal white matter, while mean memory performance may better reflect hippocampal volume.

Introduction: This study aimed to characterize the neurochemical profile of Alzheimer s disease (AD) continuum stages using proton magnetic resonance spectroscopy (1H-MRS) data for brain metabolites and macromolecules. We used Orthogonal Projection to Latent Structures Discriminant Analysis (OPLS-DA) to classify diagnostic groups and assess feature importance. Methods: Our dataset consisted of 7 T short-echo time 1H-MRS spectra of the posterior cingulate cortex/precuneus of individuals diagnosed with AD (n = 27) or Mild Cognitive Impairment (MCI, n = 27) and Healthy Controls (HC, n = 31). Classification used 100-round Monte Carlo cross-validation based on metabolite concentrations and macromolecular peak intensities. Variable importance in projection (VIP) was assessed across classification models to identify the most relevant neurochemical features. The resulting metabolite rankings were compared with previous literature to evaluate their biological plausibility. Results: Classification was strongest for AD versus HC (AUC=0.88) and lower for comparisons involving MCI. Metabolites contributing most strongly to classification included myo-inositol, ascorbate, and choline-containing compounds, consistent with previous studies on AD-related neurochemical alterations. In addition, specific macromolecular components were identified as relevant features, suggesting a potential contribution of MM signals to the characterization of AD-related neurochemistry. Discussion: These findings support the use of short-echo-time 1H-MRS as a complementary tool for characterizing neurochemical changes in the AD continuum, with potential applications in disease characterization and monitoring, warranting validation in larger cohorts.

Background: This study compared functional and cognitive trajectories in older women treated for early breast cancer with matched women without cancer. Methods: Data were derived from two Dutch cohorts: the CLIMB study (women aged 75 years and older with operable breast cancer) and the ISCOPE study (community-dwelling women aged 75 years and older without cancer). Breast cancer patients were matched 1:2 to controls on age and baseline functional or cognitive status. Functional status was assessed using the Groningen Activity Restriction Scale (GARS), and cognitive function using the Mini-Mental State Examination (MMSE). Longitudinal changes over 12 months were analyzed using both unadjusted and confounder-adjusted linear mixed models. Results: 168 breast cancer patients and 336 matched breast cancer-free controls were included with a mean age of 80 years. Most breast cancer patients had stage 0-I or II disease and received surgery and/or radiotherapy; 48% received adjuvant endocrine therapy, chemotherapy was rare (<1%). At baseline, both cohorts were comparable in age and functional or cognitive status, although there was a higher comorbidity burden in the control cohort. No significant differences in functional or cognitive decline were observed between the cohorts over 12 months. Conclusions: In older women, early breast cancer and its treatment did not lead to accelerated decline in functional status or cognitive function within the first year compared to matched older women without cancer. These findings suggest that, for relatively fit older patients, breast cancer treatment may not accelerate functional decline in the short term.

OBJECTIVE: Research on neighborhood context and cognitive health often relies on composite indices that collapse neighborhood socioeconomic status (SES) and aspects of the built environment into a single score. This study examined the extent to which neighborhood SES and built environment were associated with late-life cognitive impairment. METHOD: Participants were 281 predominantly Black older adults who completed the Self-Administered Gerocognitive Exam (SAGE), a brief cognitive screening measure. Participants also provided their home address to obtain four neighborhood metrics: Two composite measures of neighborhood disadvantage, the Environmental Justice Index (EJI) and the EJI Social-Environmental Rank, as well as the EJI Social Vulnerability Rank as a measure of neighborhood SES, and the EJI Environmental Burden Rank to measure exposure to hazardous aspects of the built environment. RESULTS: Lower neighborhood SES was associated with higher odds of cognitive impairment. In contrast, greater environmental burden was associated with lower odds of impairment, with years of education as a moderator; the association was strongest among individuals with high levels of education. The two composite scores were not associated with cognitive impairment. CONCLUSION: Composite measures of neighborhood features may obscure distinct pathways of their effects on cognition.

Background: Cervical spinal cord (CSC) compression and myelopathy are frequent, severe complications in mucopolysaccharidosis (MPS) types I and VI. Early detection is critical to prevent irreversible neurological deficits and preserve quality of life. This prospective study aimed to identify quantitative neuroimaging biomarkers of structural CSC damage and myelopathy in MPS I and VI. Methods: Structural and diffusion magnetic resonance imaging (MRI) of the CSC was analyzed in 17 MPS I patients, 3 MPS VI patients (19{+/-}7 years), and 19 case-matched healthy controls (20{+/-}7 years). CSC macrostructure (cross-sectional area, diameters) and microstructure (fractional anisotropy [FA], radial [RD], mean, axial diffusivities) were evaluated within and beyond the maximal compression areas. Results: MPS patients demonstrated reduced CSC cross-sectional area and anterior-posterior diameter at upper cervical levels, alongside widespread microstructural alterations (lower FA, higher RD) throughout the CSC versus controls (pFDR<0.05). Restricted foramen magnum space was associated with microstructural damage at lower cervical levels without overt macrostructural compression. Morphological and microstructural metrics were sensitive to CSC compression and myelopathy severity (pFDR<0.05). Lower CSC integrity correlated with more advanced growth retardation (p<0.001). Among patients receiving hematopoietic stem cell transplantation, earlier treatment correlated with preserved upper CSC morphology (p<0.05). Distinct neuroimaging phenotypes were observed across MPS genotypes (pFDR<0.05). Conclusions: CSC MRI provides candidate neuroimaging biomarkers for early detection and characterization of myelopathy in MPS I and VI. Structural damage extends beyond primary maximal compression areas, highlighting these markers for clinical monitoring and future therapeutic trials.

Objective To evaluate the association of early addiction consultation with withdrawal pharmacotherapy and complications in hospitalized patients with alcohol withdrawal. Methods Retrospective single-center cohort of adult hospitalizations with alcohol withdrawal (diagnosis code or CIWA-Ar [&ge;]10 within 24 hours) from July 2020 to January 2026. Exposure was an addiction consult service order within 24 hours of arrival, compared with no or later consultation. Primary outcomes were intensive care unit (ICU) transfer after the first 24 hours and delirium tremens or withdrawal seizure not present on admission. Process outcomes included phenobarbital and thiamine administration within 24 hours and benzodiazepine dose in the first 48 hours. Secondary outcomes included length of stay and 30-day death or return to hospital. Results Of 4,663 hospitalizations, 1,379 (29.6%) received early consultation. After adjustment, early consultation was associated with lower odds of ICU transfer (odds ratio [OR] 0.73; 95% CI 0.54-0.99) and fewer episodes of delirium tremens (risk difference -1.09 per 100; -1.45 to -0.73), with no significant difference in withdrawal seizure. Early consultation was associated with phenobarbital (OR 1.57; 1.32-1.86) and thiamine (OR 1.23; 1.07-1.41) within 24 hours, higher 48-hour lorazepam-equivalent dose (ratio of geometric means 1.44; 1.32-1.57), shorter stays (ratio 0.92; 0.88-0.97), and lower odds of 30-day death or return to hospital (OR 0.78; 0.66-0.91). Conclusions Early addiction consultation was associated with earlier, more intensive withdrawal pharmacotherapy, lower odds of ICU transfer, and fewer episodes of delirium tremens, although the complication associations were sensitive to cohort definition.

INTRODUCTION: Stroke, dementia, and late-life depression share overlapping vascular pathophysiology, yet simple markers of shared neurological vulnerability across these conditions remain limited. Most gait research has relied on usual walking speed (UWS) alone, leaving it unclear whether quick walking speed (QWS) and gait adaptability (QWS minus UWS), relate to these conditions in the same way. METHODS: We examined associations of UWS, QWS, and gait adaptability with executive function, verbal memory, depressive symptoms, and incident stroke and dementia in the Framingham Heart Study Offspring cohort. A larger sample (n=2,308; mean age 61.5 years [SD 9.2]; 54% women) was used for cross-sectional and stroke analyses, and a dementia-free sample of 1,148 participants aged 60 years or older (mean age 68.5 years [SD 5.8]; 53% women) was used for analyses of incident dementia. We estimated associations per SD slower walking or smaller adaptability using linear, logistic, and Cox regression (10-year follow-up), overall and in women and men. RESULTS: Slower QWS and UWS were each associated with worse executive function, higher odds of high depressive symptoms (QWS OR 1.24, 95% CI 1.07-1.45; UWS OR 1.26, 95% CI 1.09-1.46), and greater hazard of incident stroke (QWS HR 1.30, 95% CI 1.03-1.64; UWS HR 1.36, 95% CI 1.11-1.65). Executive function and stroke associations were observed primarily in men (stroke QWS HR 1.55, 95% CI 1.11-2.17). For incident dementia, slower QWS reached significance (HR 1.34, 95% CI 1.10-1.63), while UWS did not (HR 1.20, 95% CI 0.98-1.46). Lower gait adaptability was associated with worse executive function overall and in women and men, and with incident dementia in women (HR 1.35, 95% CI 1.04-1.76), but not with depressive symptoms or stroke. No gait measure was associated with delayed recall. CONCLUSION: Slower QWS was associated with incident dementia; UWS was not. Adding a brief quick walking trial to routine gait assessment may identify risk that habitual-pace screening overlooks.

Background and Objective: The volume of patient portal messages has grown substantially and artificial intelligence (AI) can support clinical staff and improve the timeliness of patient care. Our objective is to test if an AI tool for managing the electronic inbox In-Basket reduces response times to patient portal messages in neurology. Methods: We conducted an implementation study from January to May 2026 in the neurology department at two clinical sites within a regional medical system. A single AI tool was implemented to auto-categorize and auto-route all patient messages received in the electronic inbox. The tool also generates optional draft replies to messages. Primary process measures were the median weekly time (hours) from message creation to the first action and to closure. Impact was analyzed using a controlled interrupted time-series (ITS) design, comparing message-volume-matched control divisions. Results: Among 24,142 messages analyzed, pre-intervention median weekly time to first action was 11.3 hours [IQR: 5.6, 15.1] (Site A) and 16.1 hours [IQR: 13.8, 19.0] (Site B), falling post-intervention to 1.0 hour [IQR: 0, 3.1] (Site A) and 0.6 hours [IQR: 0.2, 2.4] (Site B). Controlled interrupted time-series analysis showed a significant immediate differential level change in median weekly hours to first action at Site A (-92.5%, 95% CI: -97.5% to -78.0%), and a significant downward trend at Site B (-43.5%, 95% CI: -65.2% to -8.2%). Changes in time to closure were directionally favorable but not statistically significant at either site. There was low use of the generated draft replies, only 0.5% at Site A and 3% at Site B. Discussion: Implementation of AI-assisted message categorization and routing was associated with a substantially reduced initial action time for patient In-Basket messages in Epilepsy. The utilization of AI-generated draft-replies to messages was low. These findings support the feasibility and effectiveness of AI-augmented workflows to improve inbox management.

Background: Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous neurodevelopmental condition, and co-occurring autistic traits may shape its phenotypic expression. Although creativity has been discussed as a relative strength in ADHD, it remains unclear whether autistic traits are associated with different dimensions of creativity in adults with ADHD and whether large-scale brain networks contribute to these associations. Methods: We compared divergent thinking (DT) and real-life creativity between 65 adults with ADHD and 73 neurotypical controls. We used subgroup comparisons, partial correlation analyses, and multiple regression models to determine the effects of autistic traits (ATs) on creativity dimensions within the ADHD cohort. Guided by prior creativity-network research, we analyzed resting-state functional connectivity (FC) of the Default Mode Network (DMN) and Frontoparietal Network (FPN) to uncover the neural mechanisms. Results: The ADHD cohort demonstrated significantly higher scores on both DT (ps = 0.002-0.009) and real-life creativity measures (ps = 0.011-0.017) compared to the neurotypical control group. Importantly, increased ATs within the ADHD group were associated with a dissociated creativity profile, showing positive associations with DT but negative associations with real-life creativity. At the neural level, stronger right DMN FPN connectivity mediated positive associations between ATs and DT performance (ps = 0.007-0.018), but mediated a negative association between ATs and self-reported imagination (p = 0.029). Conclusions: In individuals with ADHD, co-occurring ATs exert a paradoxical effect on creativity, enhancing DT while compromising real-life creative achievement. In this subgroup with ADHD and elevated ATs, interventions should capitalize on ATs-associated ideational strengths while circumventing translational barriers, to enhance real-world creative outcomes.

Background: Pseudo-orthostatic tremor (psOT) is a rare form of tremor of the lower body, triggered by standing, at frequencies lower than 13 Hz. It is believed to be secondary to other neurological disorders in a large proportion of cases. Surface electromyography (sEMG) can identify its core characteristics and differentiate it from other similar disorders such as primary orthostatic tremor (POT) and orthostatic myoclonus (OM). Objectives: Our study aims to illustrate the clinical and neurophysiological features as well as the outcomes and final diagnoses of patients with psOT in a retrospective two-centre cohort. Methods: We retrospectively examined the available clinical and neurophysiological records of 35 consecutive patients with a diagnosis of psOT in the 2022-2026 period. Data on demographics, clinical characteristics, sEMG findings, pharmacological treatments, ancillary investigations and patient reported outcomes were collected. Results: 35 patients with psOT were identified, of which 6 (17%) displayed features consistent with a functional neurological disorder (FND). Among the 29 patients with organic psOT, 21 (72.4%) fulfilled the diagnostic criteria for essential tremor (ET), while an identifiable neurological cause was established in four (13.8%). sEMG findings differed between functional and organic psOT, with the latter often displaying features consistent with weight-bearing hyperkinesias. Conclusions: Our retrospective study suggests that psOT is most often associated with ET, while an identifiable neurological cause was found in a relatively small proportion of patients. We also describe functional psOT as a previously unrecognized clinical presentation of FND.

Negative emotional bias, including reduced processing of positive information and negative interpretation of ambiguous stimuli, is a core feature of depression. Esketamine, an N-methyl-D-aspartate (NMDA) receptor antagonist with rapid antidepressant effects in treatment-resistant depression (TRD), reduces depressive symptoms, but its effects on distinct components of emotional processing remain unclear. Fifty-three patients with TRD and 53 healthy controls performed an Emotional Facial Expression Morphing task. Patients were assessed at baseline, 24 hours after the first esketamine administration, and after 4 weeks of treatment. Statistical models examined detection thresholds for happy and sad faces, negative categorisation of neutral faces, and signal detection indices separating emotion-neutral discrimination sensitivity (d') from response criterion (c), indexing the evidence required to report the presence of an emotion. At baseline, patients required greater happy-face intensity for emotion detection and were more likely to categorise detected neutral faces as negative. They also showed a more conservative response criterion without group difference in discrimination sensitivity. Responders showed an early increase in d'; and, by week 4, less negative categorisation of neutral faces than non-responders. A lower baseline response criterion was associated with responder status and, in secondary continuous analyses, with greater subsequent MADRS improvement. These findings indicate that TRD involves abnormalities across detection-related, valence-related, and decisional aspects of facial-emotion processing that are differently associated with esketamine response: baseline response criterion emerged as a candidate prognostic marker, whereas negative categorisation of neutral faces tracked clinical response. Assessing these domains may inform clinical evaluation, pending independent replication.

Background: Girls are more likely than boys to experience psychological distress during adolescence. Drivers of this gender gap remain under-studied, despite its large impact on later life and outcomes, especially for women. Explanatory factors can be gendered in their prevalence (differential exposure) and/or in their impact (differential susceptibility). We developed a multi-domain framework of explanatory factors for distress and applied it in four low- and middle-income countries. Methods: We first proposed a framework of explanatory factors for psychological distress grouped into seven domains (biological, cognitive, psychological, behavioural, social, environmental and broader societal). We applied this framework to identify explanatory variables assessed in childhood and adolescence in the Young Lives longitudinal cohort studies in Ethiopia (N=908), India (N=952), Peru (N=634) and Vietnam (N=887). Distress symptoms at 18-19 years were measured with the Strengths and Difficulties Questionnaire Emotional Symptoms scale. Gendered prevalence of each explanatory factor was tested with Mann-Whitney tests, and gendered impact with country-specific linear regressions including a gender-by-factor interaction term. Exploratory boosted-tree machine-learning models, interpreted with SHAP values and permutation feature importance, examined the contribution of these factors to the gender gap in each country. Results: Distress was higher in girls than boys in every country, the gap ranging from 0.62 points in Ethiopia and Vietnam to 1.76 in India and 2.45 in Peru. Some explanatory factors were consistently gendered in prevalence (e.g. girls experienced greater role overload in each country), while others were gendered only in some countries (e.g. study amount was higher for girls in Peru and Vietnam, but not Ethiopia or India). Gendered impacts on distress displayed more variability across countries. For example, higher self-esteem was more protective for boys than girls in India, Peru and Vietnam, but more protective for girls in Ethiopia. The machine-learning models identified important predictors across all framework domains, though their salience varied by country. Conclusions: Our findings underscore the importance of considering multi-domain explanations for mental-health outcomes and observed inequalities in mental health. Large cross-country differences in the gender gap and in the prevalence and influence of explanatory factors caution against generalising drivers of mental-health outcomes and inequalities across contexts.

Background: Ultra-low field (ULF) magnetic resonance imaging (MRI) offers accessible point-of-care neuroimaging, yet its capability to support multivariate network analyses remains understudied. Methods: We systematically evaluated the feasibility and reliability of Morphometric Similarity Networks (MSN) and Morphometric Inverse Divergence (MIND) networks derived from paired high-field (HF, 3T/1.5T) and ULF (64mT) scans in a primary cohort(N=23) and an independent replication cohort (N=19). We tested the impact of super-resolution processing, cortical parcellation granularity (Desikan-Killiany vs. Destrieux), and mesh resolution (fsnative vs. fsaverage5) on edge-level cross-scanner agreement (Lin's concordance correlation coefficient, CCC) and subject-level identifiability. Results: MIND networks demonstrated higher edge-level HF-ULF agreement (mean CCC = 0.95) and ULF reproducibility (mean CCC = 0.98) compared to MSNs (mean CCC = 0.86-0.87 and 0.91-0.94, respectively). In contrast, MSNs yielded higher subject-level differential identifiability across field strengths due to a broader distinction between within- and between-subject similarity. Reconstructing MIND networks on native high-resolution meshes (fsnative) maximised cross-scanner agreement, whereas coarser meshes and finer cortical parcellations enhanced individual network identifiability. Conclusions: Structural similarity networks can be reliably constructed from ULF MRI data. Optimal analytic choices depend on study objectives: MIND on native meshes maximises cross-scanner stability, whereas MSNs excel at preserving individual uniqueness, paving the way for globally scalable connectomic research.

Abstract Background: Glycosylated RNAs (GlycoRNAs) participate in immune recognition and intercellular communication, but their relationship with brain cell-type transcriptional signatures in major depressive disorder (MDD) remains unclear. We examined GlycoRNA-related transcriptional coupling with microglial and other cellular signatures in the dorsolateral prefrontal cortex (DLPFC). Method: Postmortem DLPFC transcriptomic data from 22 controls and 26 MDD patients (GSE102556) were analyzed. GlycoRNA-related pathway enrichment was quantified using gene set variation analysis (GSVA), whereas microglial, neuronal, astrocytic, and oligodendrocytic signatures were derived using single-sample gene set enrichment analysis (ssGSEA). Pearson correlations, linear regression, and generalized estimating equations (GEE) evaluated cell-type-specific associations and diagnostic interactions. Exploratory GEE results underwent false discovery rate (FDR) correction. Results: No differentially expressed genes survived FDR correction, and GlycoRNA-related and cell-type signatures did not differ significantly between groups. In controls, GlycoRNA enrichment was positively associated with the microglial signature (beta = 0.447, FDR-adjusted P = 0.006), with significantly weaker associations for neurons, astrocytes, and oligodendrocytes (all FDR-adjusted P < 0.05). The two-way GlycoRNA x is_microglia interaction was nominally significant (beta = 0.210, P = 0.048), confirming that GlycoRNA transcriptional coupling is substantially stronger for microglia than for the other three cell types combined. The microglial association was numerically attenuated in MDD (beta difference = -0.273, P = 0.167), but diagnostic interactions were nonsignificant. Conclusions: GlycoRNA pathway transcriptional enrichment exhibits preferential microglial association in control DLPFC. Its possible attenuation in MDD remains to be validated. keyword: Major depressive disorder; GlycoRNA; microglia; dorsolateral prefrontal cortex; generalized estimating equation; ssGSEA; bioinformatics