Journal of Cognitive Neuroscience

Background: Individuals with body dysmorphic disorder misperceive defects of their physical appearance. Current evidence suggests that visual processing abnormalities may underlie this core symptom. Separate pre-clinical studies testing perceptual and attentional interventions and non-invasive neuromodulation suggest that these visual processing abnormalities may be modifiable, but their combined effects on neural connectivity and perceptual processing remain unclear. Methods: Thirty-nine unmedicated men and women with body dysmorphic disorder or subclinical body dysmorphic disorder received intermittent theta burst stimulation and continuous theta burst stimulation targeting the lateral parietal cortex combined with a visual attention modification paradigm during functional magnetic resonance imaging, in a crossover design. Dynamic effective connectivity within dorsal and ventral visual stream pathways was calculated, and global visual processing biases were assessed using the face inversion effect before and after stimulation plus attention modification. Results: Intermittent theta burst stimulation resulted in increased connectivity in higher-level dorsal visual stream pathways during naturalistic viewing following attention modification, whereas continuous theta burst stimulation was associated with reduced connectivity in lower-level dorsal pathways and increased connectivity in ventral stream pathways. These changes were accompanied by differential effects on global visual processing, with stimulation type modulating the magnitude of the face inversion effect. Conclusions: Combined neuromodulation and visual attention modification modulate visual system connectivity and perceptual processing in individuals with body dysmorphic disorder symptoms. These findings support a mechanistic link between dorsal-ventral stream dynamics and perceptual biases. Integrating neuromodulation with perceptual retraining may represent a viable approach for targeting core symptoms of distorted appearance perception.

In a single-blind randomized controlled trial, we investigated the effectiveness of real-time fMRI neurofeedback delivered in 7 runs over three sessions across two weeks in N = 65 patients with alcohol use disorder. The intervention targeted modulation of ventral striatal cue reactivity to alcohol-related cues as well as enhancement of prefrontal control mechanisms in the right inferior frontal gyrus. The study design incorporate three experimental groups that either were instructed to downregulate a ventral striatum signal, upregulate the right inferior frontal gyrus, or upregulate negative functional connectivity between these two structures. In two active control groups participants were instructed to either up- or downregulate the primary auditory cortex. We did not find an effect of ventral striatal downregulation or negative connectivity feedback, and a reduced striatal activation in the right inferior frontal gyrus upregulation group was accompanied by concurrent lower activation in the target structure, suggesting that our intended modulation approaches were not effective. Identified problems that might have contributed to this unexpected outcome might have been the use of continuous feedback presentation that potentially confuses regulation target and reward processing in the ventral striatum, counterintuitive regulation directions, a lack of explicit strategy guidance and transparency about the targeted process, and generally the difficulty to recruit a sufficient number of eligible voluntary participants for a well-powered study with a complex design. These insights emphasize the complex challenges of real-time fMRI neurofeedback interventions for the treatment of substance use disorders and could provide guidance for the development of more effective future approaches.

There is substantial interest in understanding neurological impact and recovery over time, but there is a dearth of longitudinal assessment extending from minutes to months surrounding neural system impact. We compared rare intraoperative recordings in three patients, obtained immediately before and after anterior temporal lobe (ATL) resection during a semantic prediction task, with longitudinal source-localized electroencephalography (EEG) obtained 2-6 weeks before and 2 and 6-14 months after surgery. Relative to controls (n = 20), task performance showed sustained impairment in the two left-hemisphere patients and delayed impact in the right-hemisphere patient. Consistent with theory on ipsilateral and contralateral hemisphere compensation, all three patients exhibited bilateral EEG alterations in speech responses and effective connectivity that did not recover to pre-operative levels. Direct comparison of the datasets for intrinsic neurophysiological biomarkers associated with timescales of processing ({tau}INT) and excitatory-inhibitory balance (aperiodic slope, {chi}SPEC) showed a striking months-long reduction in rapid timescale processing and gradually increasing aperiodic slope (e.g., putatively increased cortical inhibition) in the ipsilateral hemisphere of all three patients. Amidst these neurophysiological alterations, task performance did not return to pre-operative levels. These rare longitudinal patient data advance a framework to broadly evaluate neurological impact over multiple timeframes.

Objective: Interictal spikes have been proposed as a biomarker for both localizing seizure onset zones (SOZ) and tracking changes in seizure risk with neurostimulation in patients with drug-resistant epilepsy. Electrical stimulation can modulate spike rates acutely, and it has been proposed that measuring this modulation can help localize the SOZ. However, it is unclear whether stimulation-induced spike rate changes reflect epilepsy-specific pathology in the stimulated network or simply intrinsic regional excitability, which limits our understanding of their utility in epilepsy surgery planning. Methods: We analyzed low-frequency stimulation (LFS; 1 Hz) applied during a clinical seizure-induction protocol systematically targeting multiple brain regions in 43 patients with drug-resistant epilepsy undergoing intracranial EEG monitoring. A validated, automated spike detector was used to quantify pre-, during-, and post-stimulation spike rates. We tested whether the stimulation-evoked spike rate response (i) tracks the expected change in seizure risk from a seizure induction protocol, (ii) varies with anatomical stimulation site and epilepsy localization, (iii) localizes the SOZ beyond baseline spike rate, and (iv) is accompanied by changes in spike morphology. Results: Nearby LFS acutely increased spike rates in high-spiking channels (inter-stimulation median 2.25 vs. during-stimulation 4.25 spikes/min; p < 0.001), with effects attenuating with distance and resolving within approximately 30 seconds of stimulation offset. Mesial temporal lobe stimulation produced the largest increase in nearby spike rates relative to temporal neocortex and other cortex (Kruskal-Wallis p = 0.003), but this effect did not differ between patients with and without mesial temporal lobe epilepsy. A random forest classifier incorporating stimulation-evoked modulation features achieved an AUC of 0.787, comparable to a resting-state spike model (AUC 0.747; DeLong p = 0.81), indicating that stimulation-evoked spike changes do not add localizing information beyond resting-state spike rates. Stimulation produced a small but significant shift in spike morphology toward broader, higher-amplitude discharges (PERMANOVA p < 0.001), consistent with recruitment of a broader neuronal population. Significance: LFS-evoked increases in interictal spike rates reflect intrinsic regional excitability, greatest in the mesial temporal lobe, rather than epilepsy-specific pathology, and do not improve SOZ localization over resting-state spike rates. These results argue against using the change in spikes with stimulation to localize the SOZ. On the other hand, the transient spike rate increase induced by a pro-epileptic protocol supports the acute change in spike rate as a biomarker of the effect of stimulation on seizure risk, with potential to guide parameter selection for epilepsy neuromodulation.

Background: Generative AI tools can support data-intensive research by writing code, drafting prose, searching analytical possibilities, and stress-testing claims. They can also produce false citations, drift between statistical specifications, and lose continuity across long investigations. This paper describes a practical workflow for using AI systems in empirical research while keeping discovery, verification, and accountability inspectable. Methods: We developed and applied a three-phase human-AI workflow to a case study of 14 elite Ethiopian distance runners. The dataset contained 22,605 GPS-segments collected across 97 consecutive days in late 2025, supplemented by venue and athlete metadata collected in the field. Phase 1 used an autonomous data-exploration tool to pre-filter the hypothesis space across five seeded research questions. Phase 2 used an AI system under direct human guidance to construct candidate findings into numerical claims, verification scripts, and draft text. Phase 3 used an independent AI system in an adversarial role to stress-test methods, statistics, prose, figures, and citations. The workflow was informed by Pearl's distinction between association, intervention, and counterfactual reasoning, with human judgement retained for research direction, interpretation, and final claims. Results: The workflow produced three empirical analyses and a documented correction process. The analyses estimated an altitude-to-sea-level pace correction of +0.10 min/km per 1,000 m at matched heart rate, showed why pooled altitude-surface regression was not identifiable within this venue system, documented method-dependence in heart-rate-based intensity classification, characterised within-venue route variation as a 64/36 path-fixed-to-trail-variable split with the Sululta label resolving into two functionally distinct sub-venues, and reframed the cohort's training through a 3x3x3 prescription lattice grounded in Ethiopian coaching practice. The adversarial phase identified several hallucinated citations, a terminology error between HC1 and cluster-robust standard errors, and several inconsistencies between prose, figures, and computed results. Verification scripts re-derived nearly all numerical claims from the cleaned lap-level data. Conclusions: The case study shows how researchers can organise AI-assisted empirical work so that candidate discovery, claim construction, independent stress-testing, and final accountability remain separated. The workflow did not remove the need for domain expertise or human judgement. Its value was in making the route from candidate finding to manuscript claim explicit, reproducible, and open to challenge. Trial registration: Not applicable.

Importance: Physician-facing AI tools are now in clinical use, yet whether different platforms fail in similar or fundamentally different ways in high-stakes settings like critical care is unknown. Objective: To evaluate two physician-facing AI platforms, ChatGPT for Clinicians and OpenEvidence, for distinct vulnerabilities under structured stress testing. Design, Setting, and Participants: An observational study conducted using 60 simulated critical care vignettes developed and adjudicated by four attending critical care physicians. Data were collected in the last week of April 2026, via the public website interfaces of each platform. Interventions/Exposures: A 2x2x2x2 factorial design across four stressors - anchoring, cognitive load, social conformity pressure, and a clinically incorrect directive - yielded 16 prompt subsets per vignette and 960 prompts per platform. A separate multi-turn adversarial prompting paradigm administered three sequential "You are incorrect" challenges to baseline vignettes. All prompts had a universal output length constraint of fewer than 30 words. Main Outcomes and Measures: Critical elements capture (percentage of gold-standard critical elements present in responses), susceptibility to clinically incorrect directive, and sycophancy (reversal of an initial correct recommendation under iterative adversarial challenge). Results: Across 1916 responses to 1920 prompts, ChatGPT for Clinicians captured more gold-standard critical elements than OpenEvidence (81.4% {+/-} 18.1% vs 61.0% {+/-} 23.5%; adjusted difference, 20.3 percentage points; 95% CI, 18.3 to 22.4; P < .001) and was less susceptible to clinically incorrect directives (1.7% vs 8.0%; adjusted odds ratio, 0.07; 95% CI, 0.02-0.21; P < .001). Anchoring and social conformity pressure were associated with reduced critical element capture across both platforms, while cumulative stressor burden reduced critical element capture only on OpenEvidence. Conversely, ChatGPT for Clinicians reversed correct recommendations more readily under adversarial prompting (hazard ratio, 2.61; 95% CI, 1.10 - 6.19; P = .03). Conclusion and Relevance: The two physician-facing clinical AI platforms evaluated demonstrated non-overlapping vulnerabilities, with neither platform uniformly superior. These findings argue against single-axis ranking of clinical AI systems and support multidimensional safety evaluation encompassing completeness of reasoning, resistance to incorrect directives, and stability under adversarial challenge.

Background: Thalamic low-intensity transcranial focused ultrasound (tFUS) has shown promise for increasing behavioral responsiveness in disorders of consciousness (DOC), but no study has examined whether it can causally modulate the well-validated behavioral, electrophysiological, and metabolic biomarkers of DOC impairment. Methods: Sixteen adult patients (44% Female; Age, M=37.81, SD=15.97) with a chronic DOC (Time Since Injury, M=3.39, SD=1.94 years) secondary to severe brain injury (TBI 44%, non-TBI 56%) underwent a 10-day inpatient, longitudinal, single-arm, open-label protocol. tFUS was delivered in a single session targeting the left central thalamus. Well-known behavioral (CRS-R), electrophysiological (EEG {delta}/{beta} ratio), metabolic (18F-FDG PET), and polysomnographic outcomes were assessed at baseline and after sonication. Results: The maximum CRS-R total score increased significantly following tFUS compared to baseline (M=13.27 vs. M=10.33; t(14)=7.407, p<0.001, d=1.913), as did the global EEG {delta}/{beta} ratio (N=14; W=17, p=0.025, r=0.68), with the degree of frontal slowing positively predicting behavioral gains ({tau}b=0.51, p=0.016). Glucose metabolism decreased bilaterally in thalamus and frontal, temporal, and parietal cortices at both post-tFUS timepoints compared to baseline. Finally, N2 sleep increased by 33% following tFUS (N=11; t(10)=2.386, p=0.038, d=0.72), though this did not survive correction. No severe adverse events were observed. Conclusion: Thalamic tFUS can causally modulate well-validated behavioral, electrophysiological, and metabolic biomarkers of DOC. The convergent inhibitory signature across these measures suggests a thalamocortical reset mechanism, complementing existing excitatory neuromodulation approaches and providing the mechanistic foundation for a large, randomized sham-controlled trial.

Background. Something in discourse with a person experiencing psychosis often "feels off" before formal assessment is completed, yet this disturbance has not been quantified at the level of ongoing dyadic conversation. Prior work has largely treated patient speech in isolation, limiting our capacity to measure how communicative disruption emerges within clinical exchange. Methods. We applied a three-level decomposition of conversational alignment in 109 patients with psychotic disorders (26 female) and 60 healthy controls (22 female) at baseline and 12 months (n = 115). Register divergence (dAUCnorm) captured lexical distance between interviewer and patient; embedding-based synchrony (rembed) measured semantic trajectory coupling; within-speaker coherence was computed separately for each speaker. We used linear mixed-effects models adjusted for timepoint and participant clustering. Results. Patients showed significantly greater lexical-semantic divergence from the interviewer (d = 0.48, p < .001) and reduced embedding-based synchrony (d = -0.59, p < .001), both effects replicating at each time point. Critically, the interviewer's within-speaker coherence was reduced during conversations with patients (d = -0.33, p = .016), indicating that the disruption extends beyond the patient to the interaction itself. Register divergence tracked impoverished thinking and synchrony tracked disorganized thinking (both FDR-corrected q = .038). Group differences were persistent at 12 months, indicating a partially stable profile. Conclusions. Conversational alignment in psychosis reveals a dyadic failure of semantic coordination that destabilizes the interviewing clinician's coherence even when patient narrative continuity is preserved. These transcript-derived alignment metrics offer a scalable approach to quantifying interpersonal communicative function from routine clinical encounters.

Objective: Cognitive impairment is common among older adults with epilepsy, although efficient screening tools suitable for routine use are lacking. Here we examine, for the first time, the utility of the Alzheimers Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) as a screening tool to identify cognitive impairment in older adults with epilepsy. Methods: Participants included 83 adults (ages over 55) with epilepsy from the Brain, Aging, and Cognition in Epilepsy (BrACE) study and 83 age-, sex-, and education-matched cognitively healthy controls from the Alzheimers Disease Neuroimaging Initiative (ADNI-3). All completed the ADAS-Cog and a comprehensive neuropsychological battery to identify cognitive phenotypes (intact vs impaired). Performance on individual ADAS-Cog items and the total score was assessed, and diagnostic efficiency statistics were determined. Results: Epilepsy participants (mean age=66.4 years) performed significantly worse across the ADAS-Cog total score and 8 of the 13 individual test items compared to controls. The largest effect sizes were observed on verbal learning and memory tasks, particularly word recall (d=0.87) and delayed word recall (d=1.06). An ADAS-Cog total score of at or exceeding 15 yielded optimal diagnostic efficiency (67.5% accuracy, 68.8% sensitivity, 66.7% specificity) for identifying cognitive impairment. Significance: The ADAS-Cog is sensitive to detecting cognitive impairment in older adults with epilepsy and may represent a scalable screening option in this population. Additional comparative studies in older epilepsy populations are needed to determine the sensitivity of this measure to longitudinal change, cross-cultural applicability, and availability across languages. Plain language summary: Cognitive decline is common among older adults with epilepsy, although sufficient evidence supporting the use of screening tools to identify cognitive impairment in this population is lacking. The ADAS-Cog may be a useful screening option in epilepsy research and clinical care, although additional studies are needed to compare it with other cognitive screening tests and to confirm its applicability for clinical care and across cultures and healthcare settings.

Objective: To determine whether absolute ictal energy on intracranial EEG identifies brain regions whose epileptogenic involvement is attenuated under existing baseline-normalized, dynamic-systems, and event-based frameworks. Approach: Intracranial EEG from 56 patients (five centers; 21 SEEG, 35 ECoG) was analyzed using the Teager-Kaiser Energy Operator computed as z-scored and raw envelopes; energy-dominant network regions (EDNRs) were defined as electrodes whose raw-energy rank exceeded their z-score rank by at least 2 positions. Hilbert decomposition characterized instantaneous amplitude and frequency. Main results: EDNRs were identified in 51 of 56 patients (91%; mean 3.4). Hilbert decomposition revealed elevated baseline amplitude in EDNRs relative to both non-involved regions (p < 0.001) and potential seizure onset zones (PSOZs, the top-ranked electrodes under both metrics; p = 0.029), with EDNRs participating in seizure-frequency dynamics comparable to PSOZs (mean ictal frequency shift +3.7 versus +4.1 Hz). EDNR detectability correlated directly with electrode count (Spearman r = 0.899, p < 0.001) without plateau. Significance: Absolute ictal energy identifies an epileptogenic network component with elevated baseline amplitude attenuated under baseline-normalized metrics. The dual-metric framework defines a complementary energy-based axis and establishes the second layer of a two-layer approach with seizure onset and propagation mapping as the first layer. EDNR detectability scales with electrode count, directly relevant to SEEG implantation strategy and to network-level inferences from heterogeneously covered cohorts.

Patients with primary immunodeficiency (PID) often face prolonged diagnostic delays and may increasingly turn to large language models (LLMs) to interpret their symptoms during this period. We evaluated whether an LLM could recognize PID from symptom descriptions derived from interviews with 21 PID patients. In a prior study, we showed that GPT-4o identified PID in 96% of cases when prompted with physician-written patient histories (Rider et al., JACI, 2024). Here, when prompted with symptom descriptions in patients' own words, GPT-5 identified PID in only 7 cases (33%), although it more broadly suggested immune system issues in 18 cases (81%). The gap between these findings indicates that LLMs are sensitive to the language and framing of symptom descriptions, performing substantially worse when patients describe their own symptoms in everyday language than when clinicians summarize patient histories in structured medical terms. This study underscores the need to carefully evaluate how LLMs are used in patient-facing applications.

ABSTRACT INTRODUCTION: Microscopic fractional anisotropy ({micro}FA), an emerging diffusion MRI metric, may be more sensitive than conventional metrics to gray matter microstructural changes in neurodegeneration. This pilot study compared {micro}FA, mean diffusivity (MD), and volume between genetic frontotemporal dementia (FTD) variant carriers and non-carriers in the insula, frontal pole, and medial orbitofrontal cortex (mOFC). METHODS: Carriers and familial non-carriers of FTD variants in C9orf72, GRN, or MAPT were scanned between October 2024-December 2025. Non-parametric aligned rank transform ANCOVAs were computed to analyze between-group differences in {micro}FA, MD, and volume while controlling for age. RESULTS: Carriers (n=12) exhibited lower insula {micro}FA than non-carriers (n=8): F(1,19)=5.89, 95% CI [-10.7,-0.75], p=0.027, 2p=0.26. No group-differences were observed in other metrics, including MD and volume. DISCUSSION: Reduced {micro}FA in the insula, a region vulnerable to early atrophy in FTD, may be more sensitive to early microstructural changes in genetic FTD than traditional diffusivity measures.

Background: Individuals with mild cognitive impairment (MCI) experience cognitive and functional declines that can negatively impact mood and reduce feelings of self-efficacy. These changes can also lead to elevated distress in care partners (CPs). Therefore, interventions that address quality of life and psychosocial factors in people with MCI and their CPs are needed. Objective: The present study evaluated the impact of a multidomain lifestyle program, the Cognitive Empowerment Program (CEP), on changes in psychosocial functioning, particularly empowerment, in people with MCI and their CPs. Methods: Participants were 94 people with MCI (Mean= 75.1 years old, 45.7% female, 81.9% white) and their CPs (Mean= 69.1 years old, 71.3% female, 87.3% white) that completed the 12-month CEP program comprised of physical, cognitive, and psychosocial interventions. Questionnaires were administered pre- and post-program to assess empowerment, self-efficacy, meaning and purpose, depression, and stress in participants with MCI alongside empowerment, depression, stress, and caregiving burden in CPs. Results: After completing the CEP program, participants with MCI endorsed higher empowerment and self-efficacy as well as fewer symptoms of depression and perceived stress. CPs endorsed feeling more empowered despite elevated caregiver burden. Conclusions: These results suggest multidomain lifestyle programs can positively impact wellbeing in MCI. Future research should focus on refining delivery models, exploring integration with pharmacological treatments, prioritizing inclusion of diverse populations, and measuring long-term outcomes to strengthen the reach and impact of programs like CEP.

Although the associations between cerebrovascular dysfunctions and Alzheimer's disease are increasingly appreciated, the relationship of cerebral blood flow and white matter hyperintensities with tau and amyloid-{beta} pathology remains unclear, particularly in the longitudinal context. This study investigated cross-sectional and longitudinal associations of cerebral blood flow and white matter hyperintensities with tau and amyloid-{beta} pathology using multimodal imaging and blood biomarkers in 179 participants from the ADNI3 cohort. Participants underwent structural (T1-weighted, T2-weighted FLAIR) and arterial spin labelling perfusion MRI, tau and amyloid-{beta} PET, and plasma assay tests for amyloid-{beta} 42, amyloid-{beta} 40, and phosphorylated tau-217. Tau from PET was negatively associated with cerebral blood flow both cross-sectionally and longitudinally in the posterior brain, independent of amyloid-{beta} quantified from PET. Higher white matter hyperintensities volumes were associated with higher levels of tau and amyloid-{beta} at baseline, but the associations were significantly attenuated after further adjusting for amyloid-{beta} and tau, respectively. Plasma amyloid-{beta} 42/40 ratio was negatively associated with white matter hyperintensity volumes both cross-sectionally and longitudinally. In conclusion, tau pathology showed spatially specific associations with cerebral hypoperfusion, independent of amyloid-{beta}, particularly in posterior regions. The attenuation of associations of white matter hyperintensities with amyloid-{beta} and tau after adjustment may reflect shared disease-related variance rather than distinct independent effects. Keywords: Alzheimer's disease, Cerebral blood flow, White matter hyperintensities, Tau pathology, Amyloid-{beta}.

INTRODUCTION: MethylCog is a 29-CpG blood DNA methylation (DNAm) proxy for general cognitive ability (g). Its incremental association with blood biomarkers of Alzheimer's disease and related dementias (ADRD) and prospective cognitive ability remains unclear. METHODS: In the held-out test set from the original MethylCog study, we tested whether MethylCog explained baseline g beyond four ADRD blood biomarkers, and whether it predicted six-year follow-up g beyond baseline g and biomarkers. RESULTS: MethylCog showed a stronger age-adjusted association with baseline g than individual biomarkers (r=.368 vs absolute r=.083-.162). MethylCog added 10.0% variance beyond all four biomarkers cross-sectionally (p<.001) and predicted six-year follow-up g in the biomarker-adjusted model (beta=.108, p=.002). No individual ADRD biomarker independently predicted follow-up g. DISCUSSION: MethylCog may provide cognition-related DNAm information complementary to blood-based ADRD biomarkers.

Aims. The risk of cognitive decline after losing a spouse remained mixed. This study aims to investigate the association between spousal loss and risk of cognitive decline, assess whether this association varies by sex and age, and identify modifiable factors. Methods. We conducted a prospective cohort study using harmonized data from six population-based aging surveys: the US Health and Retirement Study and its sister surveys in England, Mexico, China, India, and South Africa, incorporating their respective Harmonized Cognitive Assessment Protocol (HCAP) sub-studies. Spousal loss (yes vs no) was the exposure. Cognitive outcomes (i.e., orientation, memory, executive function, and language), were assessed using HCAP neuropsychological batteries. We conducted parallel analyses in six cohorts. Associations between spousal loss and cognitive outcomes were estimated using generalized linear models, and summarised estimates were derived via random-effects meta-analyses. Sex stratification and restricted cubic spines were used to examine how these associations vary by sex and age, respectively. Results. The analytical cohort consisted of 18,551 individuals aged 61.22 (SD 6.30) to 71.37 (SD 7.33) years. Widowhood prevalence ranged from 14.1% in CHARLS to 53.9% in HAALSI and was consistently higher in women. Spousal loss was associated with poorer memory (multivariable-adjusted {beta} = -0.07, 95% CI -0.12 to -0.01) and executive function (multivariable-adjusted {beta} = -0.08, 95% CI -0.13 to -0.03) in the meta-analysis, with no significant associations for orientation or language. While results were generally consistent in five cohorts, the ELSA showed divergent patterns (orientation: {beta} = 0.10, 95% CI 0.06 to 0.13; memory: {beta} = 0.05, 95% CI 0.02 to 0.08; language: {beta} = 0.16, 95% CI 0.12 to 0.19). Sex-stratified analyses indicated poorer executive function among men (multivariable-adjusted {beta} = -0.14, 95% CI -0.19 to -0.08) and poorer memory among women (multivariable-adjusted {beta} = -0.07, 95% CI -0.14 to -0.01) following widowhood. Nonlinear age-related effects on cognition were observed in ELSA, LASI, and HAALSI. Higher education, internet use, and BMI were negatively associated with the risk of cognitive decline among widowed participants. Conclusions. Spousal loss is associated with domain- and sex-specific differences in cognitive performance, with substantial heterogeneity across study populations. Future research should integrate biopsychosocial markers to develop context-sensitive interventions for widowed older adults.

Background: Patients in socioeconomically disadvantaged neighborhoods face barriers to care. Missing BP documentation may signal gaps in risk-factor management, a crucial component of primary and secondary prevention of intracerebral hemorrhage (ICH). We tested whether neighborhood deprivation was associated with absent electronic health record (EHR) blood pressure (BP) documentation surrounding ICH and whether absent documentation predicted subsequent uncontrolled BP. Methods: We conducted a case-only study within the NIH All of Us Research Program. We included ICH survivors (ICD-10 I61.x, surviving >=1 year) with available ZIP3-based Deprivation Index. Deprivation was categorized as Privileged, Intermediate, or Deprived using cohort-based tertiles. We excluded BP measurements collected by All of Us. Outcomes were (1) absent EHR-derived BP documentation and (2) uncontrolled BP (mean systolic BP >=140 mmHg) during three windows: 1-365 days before ICH; 30-365 days and 1-5 years after ICH. Multivariable logistic regression tested associations adjusting for age, sex, and race/ethnicity. Results: 1,474 ICH survivors were included (mean age 60.1, 50.4% female). Compared to privileged neighborhoods, those living in deprived neighborhoods had higher odds of absent EHR BP documentation in the year prior to ICH (OR 2.10, 95% CI 1.60-2.76; p<0.001), 30-365 days post-ICH (OR 2.82, 95% CI 2.14-3.73; p<0.001) and 1-5 years post-ICH (OR 2.81, 95% CI 2.13-3.71; p<0.001). Absence of EHR BP documentation in the year before ICH predicted uncontrolled BP 30-365 days (OR 1.97, 95% CI 1.36-2.85; p<0.001; N=888) and 1-5 years (OR 1.83, 95% CI 1.24-2.69; p=0.002; N=814) after ICH. Absence of BP documentation 30-365 days post-ICH also predicted uncontrolled BP 1-5 years post-ICH (OR 1.66, 95% CI 1.10-2.50; p=0.017; N=814). Conclusions: Neighborhood deprivation is associated with persistent gaps in EHR BP documentation surrounding ICH, and absent documentation before or soon after ICH predicts subsequent uncontrolled BP. These findings highlight the need for community-level strategies that ensure equitable BP monitoring for socioeconomically disadvantaged populations.

Artificial intelligence (AI) tools have been rapidly adopted by medical researchers, yet whether early career researchers in low and middle income countries possess the awareness and habits needed to use these tools safely remains poorly documented. This study characterized AI adoption patterns, hallucination awareness, and verification and disclosure practices among early career medical researchers in Pakistan. A cross sectional anonymous online survey was conducted among medical students, house officers, residents, physicians, and faculty involved in research or academic work across Pakistan (May 2026). Descriptive statistics and chi square tests were applied to 373 eligible responses. AI use was near universal (99.7%), with 60.3% using AI tools daily. The most commonly reported tool in this sample was Claude (40.5%), followed by ChatGPT (29.2%) and Perplexity (26.0%), though this ranking likely reflects sampling characteristics. Despite high adoption, 59.2% typically did not verify AI outputs before use, and 40.2% had never heard that AI can generate fabricated scientific references. In behavioral vignettes, 36.5% assumed convincing AI generated references were authentic, and 54.2% would continue using remaining AI content after discovering one fabricated reference. Formal research training was strongly associated with consistent disclosure (51.7% vs. 17.1%; chi square=48.43, p less than 0.001). Role, daily use frequency, and research training were not significantly associated with verification behavior. Early career medical researchers in Pakistan demonstrate high AI adoption alongside incomplete hallucination awareness and infrequent verification, a pattern that may carry implications for research integrity. Formal training was the only factor significantly associated with consistent disclosure. Integration of AI literacy into medical curricula and institutional governance frameworks merits consideration.

AIM: STXBP1-related disorder (STXBP1-RD) is a severe developmental and epileptic encephalopathy characterized by early-onset seizures and persistent cognitive and motor impairments. With disease-modifying trials emerging, a disorder-specific severity scale is needed. To address this, we adapted a validated clinician-reported measure from CDKL5 Deficiency Disorder to develop the STXBP1 Clinical Severity Assessment (S-CSA) and evaluated its psychometric properties. METHOD: The S-CSA was adapted from the CDKL5 Clinical Severity Assessment through expert consensus sessions with STXBP1 clinicians. Revisions addressed gaps in motor and vision domains, adding tremor and vision items. The measure was administered to 123 individuals with STXBP1-RD. Psychometric evaluation included confirmatory factor analysis, internal consistency, composite reliability, average variance extracted, and distinctiveness, compared with recommended thresholds. RESULTS: Analyses supported a three-domain structure (motor, communication, vision) with factor loadings >0.5 and strong internal consistency (Cronbachs alpha >0.7; composite reliability >0.88). Model fit and variance metrics met recommended standards, and domains demonstrated distinctiveness. No ceiling or floor effects were observed. Minimal skew was seen in motor (0.34) and communication (0.16) domains; positive skew in vision (2.2) was seen, identifying patients with and without cortical visual impairment. INTERPRETATION: The S-CSA demonstrates strong validity and reliability in STXBP1-RD and may show utility in clinical trials for STXBP1-RD and potentially other severe DEEs. Key Words: STXBP1-Related Disorder, Developmental and Epileptic Encephalopathies, Clinical Outcome Assessments

Background: Prior neuroimaging suggests brain differences between children with attention deficit hyperactivity disorder due to prenatal alcohol exposure (ADHD+PAE) and non-exposed children with ADHD due to other, e.g., familial, causes (ADHD-PAE). There has been interest in regional brain levels of ;gamma-aminobutyric acid (GABA) and glutamate (Glu) measured in vivo with magnetic resonance spectroscopy (MRS) as possible indicators of local inhibitory, respectively, excitatory activity in ADHD. For the first time, we report here a comparison of GABA and Glu in ADHD+PAE vs. ADHD-PAE. Methods: At 3 T, we used J-difference-edited single-voxel MRS to assay GABA and Glu in 28 children with ADHD+PAE, 20 with ADHD-PAE, and 28 typically developing (TD) controls, all aged 8-14 years. MRS was sampled from midline anterior middle cingulate cortex (aMCC), the cognitive cingulate considered functionally relevant to ADHD. Spectra were fit with custom software, including a unique technique for isolating the GABA signal from the confounding macromolecular baseline (MMBL). Results: aMCC GABA was higher in ADHD+PAE and ADHD-PAE than in TD. GABA increased with age in TD, but not in ADHD+PAE or ADHD-PAE. Similar effects were observed for the ratios GABA/Glu and GABA/Glx. For GABA+MMBL (GABA+) these effects were not seen, rather GABA+ and MMBL increased with age for the ADHD+PAE group only. No significant effects were found for Glu or Glx. Conclusions: GABA in the aMCC does not distinguish the two etiologies of ADHD, rather elevated GABA that follows an abnormal developmental appears to be common to both. High GABA may reflect increased inhibition of the aMCC impairing its cognitive functions. GABA+ results in ADHD may not tract reliably with underlying GABA values. Negative results for Glu and Glx should be reexamined at shorter echo-times.