Brain Imaging and Behavior

BackgroundCognitive restructuring, the process of identifying and challenging negative thoughts, is a key technique for treating depressive and anxiety disorders. Although neuroimaging studies have characterised the brain systems supporting cognitive restructuring in healthy individuals, it remains unclear how these systems are altered in depression and anxiety, or whether each disorder is associated with distinct neural dysfunction. MethodsSeventy-three clinical participants with depressive or anxiety disorders and 70 healthy controls completed a cognitive restructuring paradigm during 7 Tesla functional magnetic resonance imaging (fMRI). The task required participants to either repeat a series of negative statements or challenge them using Socratic questioning. Group-level fMRI analyses examined the effects of depressive and anxiety symptom severity on brain activation, while dynamic causal modelling characterized the directional neural influences between implicated regions. ResultsDuring challenging compared to repeating statements, greater depressive symptoms were associated with reduced dorsolateral prefrontal cortex (dlPFC) activation. Conversely, greater anxiety symptoms were associated with greater dlPFC activation. Effective connectivity results revealed that depressive symptoms were associated with greater inhibition from the ventrolateral prefrontal cortex (vlPFC) to the ventromedial prefrontal cortex, whereas anxiety symptoms were associated with greater excitation from the dlPFC to amygdala and greater inhibition from the vlPFC to amygdala. ConclusionsWhile clinical participants modified negative beliefs as effectively as healthy controls, depressive and anxiety symptoms were associated with dissociable neural signatures during restructuring. This suggests that cognitive behavioral therapy may engage partially distinct mechanisms depending on symptom profile, a possibility that warrants longitudinal investigation of treatment response.

Moderate-to-severe traumatic brain injury (msTBI) is recognized as a chronic and evolving neurological condition characterized by progressive structural brain changes and persistent cognitive impairment. While prior studies have demonstrated widespread atrophy following msTBI, less is known regarding the longitudinal trajectory of gray matter (GM) changes during recovery and post-rehabilitation. The current study used longitudinal voxel-based morphometry (VBM) to characterize GM volume changes over a period of 9 months, in individuals with msTBI relative to healthy controls (HC). Associations between regional GM volume and neuropsychological functioning were examined. Twenty-eight participants (14 msTBI, 14 HC) completed MRI and neuropsychological assessments across three timepoints spanning outpatient rehabilitation and follow-up. Longitudinal VBM analyses revealed significant group and time interactions within subcortical and limbic regions. Relative to HC, individuals with msTBI showed lower GM volume in these regions at baseline, with trajectories that converged toward HC values (right hippocampus) or increased relative to HC over the rehabilitation period (bilateral pulvinar), whereas the right amygdala and inferior cerebellar vermis remained persistently reduced. Significant longitudinal improvements in memory and psychomotor speed during the rehabilitation period were demonstrated in msTBI. Greater (preserved) GM volume within the right hippocampus, thalamus, and bilateral pulvinar was associated with better performance across measures of verbal memory, processing speed, executive functioning, and cognitive flexibility. These findings suggest that msTBI is associated with dynamic structural brain changes involving subcortical, limbic, and cerebellar networks, and that the rehabilitation period was accompanied by relative volumetric stabilization in these regions and by meaningful cognitive improvement.

A central challenge in neuroscience is understanding how the human brain is organised to support optimal functioning and adaptability. One approach to characterise complex brain dynamics is by artificially perturbing whole-brain models. Here, we asked whether whole-brain organisation under perturbation in major depressive disorder (MDD) changes after intervention with psilocybin and escitalopram. First, we built whole-brain models of pre- and post-treatment resting-state functional magnetic resonance imaging (fMRI) and obtained an initial generative effective connectivity (GEC) matrix for each individual. Then, we employed systematic and local artificial perturbations across intensities, re-optimised each model to create a response GEC (GECr), and assessed the extent of brain reorganisation by quantifying the brain network reconfiguration index (NRI). Our results showed that the global brain NRI increases with psilocybin and decreases with escitalopram. Across sessions and interventions, higher global NRI was related with localised perturbations in brain areas orchestrating the brain's hierarchical dynamics. Traditional approaches complemented our investigation. Our findings suggest distinct neural changes following each treatment for MDD. The increase in brain reorganisation under perturbation following psilocybin is consistent with greater brain flexibility and changeability, whereas the decrease following escitalopram suggests more stabilised brain dynamics. Overall, perturbation-induced brain NRI may represent a useful approach for uncovering neural changes following different interventions for depression.

Background Chemotherapy-related cognitive impairment is a well-documented concern among cancer survivors, yet the neural mechanisms underlying deficits in cognitive control remain poorly understood. This study examined group differences in brain activation during a flanker task using functional MRI (fMRI) between chemotherapy-exposed participants and healthy controls. Methods Participants (21 survivors (24.9 years old; 71.4 % female; 15 years from diagnosis) and 21 healthy controls (26.7 years old; 61.9 % female) completed a flanker task during fMRI, with congruent and incongruent conditions. Reaction time, accuracy, and Flanker scores were collected. Whole-brain group comparisons were performed for congruent, incongruent, and incongruent > congruent contrasts. Associations between the incongruent > congruent contrast and cognitive performance were examined. Results Compared to controls, the Chemo group had longer reaction times in both congruent and incongruent conditions (p < .001) and lower NIH Flanker scores (p = .01), with no differences in accuracy. They showed reduced activation in the bilateral inferior frontal gyri, supplementary motor area, and bilateral caudate, but greater activation in the right inferior temporal and cerebellar regions. The incongruent > congruent contrast correlated with increased activation in the orbitofrontal cortex, inferior temporal gyri, and fusiform gyrus with cognitive performance. Conclusions Chemotherapy-exposed participants showed cognitive control deficits and altered neural activation during a flanker task, indicating disrupted recruitment of frontoparietal and subcortical regions key for conflict processing. These findings improve understanding of neural causes of chemotherapy-related cognitive impairment and may help identify at-risk survivors and guide personalized rehabilitation.

Quantitative MRI enables the detection of subtle microstructural alterations in normal-appearing white matter (NAWM) associated with pathological conditions such as multiple sclerosis. Quantitative metrics including R1, R2, and the bSSFP asymmetry index (AI) were evaluated in the WM of 20 relapsing-remitting multiple sclerosis (RRMS) patients and 10 healthy controls (HC). A multi-parametric frame-work based on a phase-cycled balanced steady-state free precession (pc-bSSFP) sequence was used. Diffusion tensor imaging-derived measures, including fiber-to-field angle, number of fiber orientations, and fractional anisotropy, were incorporated to assess parameter anisotropy. Statistical analysis was performed using linear mixed-effects models to test for group, ROI, and group-by-ROI effects for each metric, with ROI-specific group comparisons derived from the model. Significant main effects of group, ROI, and group-by-ROI interaction were observed for both R1 and R2, whereas for AI only the ROI effect reached significance (group p= 0.462; group-by-ROI p = 0.786). Fourteen of sixteen ROIs demonstrated significantly lower R1 and R2 values in RRMS compared with HC. No ROI showed significant differences in AI. In conclusion, pc-bSSFP-based relaxometry reveals predominantly white matter alterations in RRMS, while enabling a comprehensive whole-brain assessment that also encompasses gray matter.

Nonduality is a foundational but conceptually elusive notion across several contemplative traditions. Nondual traditions challenge the assumption that a subject-object structure characteristic of ordinary experience is an intrinsic feature of conscious awareness. However, little remains known about the neurocognitive mechanisms associated with such experiential state. Here, we investigated how Open Presence (OP) meditation, a form of non-dual mindfulness practice, modulates bodily self-representation and large-scale brain functional organization. We combined the Full-Body Illusion Experience (FBIE), a virtual reality paradigm manipulating bodily self-processing, with resting-state functional connectivity gradient analyses in expert meditators (>10,000 hours of practice) and meditation novices. We hypothesized that OP would attenuate bodily self susceptibility as measured by FBIE and increase large-scale integration of functional brain networks, consistent with prior findings linking reduced self-boundaries and ego-dissolution to increased connectome integration. Seventy-five participants (28 experts, 47 novices) underwent fMRI scanning during OP meditation. Brain network organization was assessed using connectivity gradients and network dispersion/ eccentricity metrics. Group differences were evaluated using bootstrap statistics and support vector classification. Compared with novices, expert practitioners showed reduced global network eccentricity during OP, particularly within dorsal attention, ventral attention, and frontoparietal networks, suggesting greater large-scale integration of functional networks. These neural patterns were positively correlated with FBIE self-report measures and negatively with cognitive defusion scores, a construct thought to reflect reduced self-grasping toward thoughts and mental contents. Together, these findings suggest that nondual meditation is associated with alterations in self-representation and increased large-scale functional integration, providing candidate neural markers of nondual awareness.

Background: Coronary artery disease (CAD) increases the risk of cognitive impairment, dementia, and brain structural alterations. This heart-brain connection suggests that exercise-induced cardiovascular responses may influence brain regions vulnerable to Alzheimer's disease (AD), the most common cause of dementia. This study aimed to examine the effects of 12-weeks of either high-intensity interval training (HIIT) plus resistance training (RT) or HIIT alone on AD brain signatures in individuals with CAD, to explore moderating factors, and to assess associations between changes in AD brain signatures and cognition and physical fitness. Methods: This secondary analysis of a single-site, three-arm, single-blinded randomized controlled trial included 105 individuals with CAD (50-75 years; 21% female) randomly allocated to HIIT+RT, HIIT, or usual care (UC) groups. T1- and diffusion-weighted magnetic resonance imaging were acquired before and after the 12-week intervention. Primary outcomes were thickness/volume and gray matter mean diffusivity (GMMD) signatures, derived from seven cortical regions and the hippocampus. Moderators included age, sex, education, and baseline AD brain signatures. Results: For the thickness/volume signature, no between-group differences in changes were observed between HIIT+RT and UC (+0.13 standardized mean difference [SMD]; 95% CI, -0.07 to 0.33) or between HIIT and UC (-0.1 SMD; 95% CI, -0.3 to 0.1); however, a small but significant between-group difference in change was found between HIIT+RT and HIIT, in favor of HIIT+RT (+0.23 SMD; 95% CI, 0.03 to 0.42). For the GMMD signature, no significant between-group differences in changes were found between HIIT+RT and UC (+0.08 SMD; 95% CI, -0.18 to 0.34), HIIT and UC (+0.1 SMD; 95% CI, -0.16 to 0.36), or HIIT+RT and HIIT (-0.02 SMD; 95% CI, -0.28 to 0.23). No moderation effects were identified, and no associations were observed between changes in AD brain signatures and cognition or physical fitness. Conclusion: A 12-week HIIT+RT intervention was more effective than HIIT alone in increasing the thickness/volume signature in individuals with CAD, yet no differences were observed compared to UC and the interventions did not affect the GMMD signature. These findings suggest that the intra-session inclusion of RT with HIIT may enhance AD-related brain macrostructure in individuals with CAD more than just HIIT training.

Many forms of memory are thought to rely on visual imagery, but individuals who report lacking visual imagery (aphantasia) can still perform various memory tasks. There is, however, evidence that aphantasia may lead to less detailed autobiographical memories, suggesting there may be deficits in the underlying cognitive processes that support personal memories. One such process is associative memory, which requires binding of different types of information. Here, we tested whether associative visual memory is intact in aphantasia. We assessed 72 self-identified individuals with aphantasia and 77 controls who reported having visual imagery. Participants completed an associative memory task which involved memorising displays where a unique object in a specific location was associated with a particular colour fixation point. Individuals with aphantasia performed equivalently to controls for object locations and outperformed controls on the associated object-identity. In addition, whereas controls were significantly worse at remembering associated object-identity than object-location, individuals with aphantasia showed no such difference. Both groups showed good metacognitive performance evidenced by a positive correlation between confidence and accuracy; there were no significant differences in confidence between the groups. Reported strategies varied between groups: a large proportion of control participants reported using visual imagery and self-reported use of imagery positively correlated with performance. Conversely, individuals with aphantasia mostly reported using nonvisual strategies to remember the associations. Overall, the findings suggest that individuals with aphantasia can form associative memories using nonvisual strategies. Thus, difficulties with autobiographical memory in aphantasia seem unlikely to be due to fundamental issues with associative memory.

Compared to traditional gross volumetrics, surface- based models provide greater spatial precision for understanding brain alterations related to developmental, neurological, and psychiatric disorders. Large-scale brain initiatives are combining data from around the world to discover and improve illness- related brain markers. Here, we present a toolkit for 3D brain geometry analysis aimed at addressing key challenges facing large- scale neuroimaging studies. Our framework incorporates scalable methods for multisite data integration, site-specific confound correction, accelerated statistical modeling, interpretable machine learning, and interactive results visualization. The toolkit was tested on data from 21 independently collected study samples participating in the ENIGMA Bipolar Disorder Working Group (N = 3,373). Compared to traditional volume features, we show how subcortical shape measures can be combined across study sites to capture spatially complex differences between diagnostic groups and associations with common treatments. Statistical modeling was accelerated using the Fast and Efficient Mixed- Effects Algorithm (FEMA) and achieved a 16-fold reduction in computation time compared to traditional approaches. Machine learning models showed shape features may provide greater predictive performance over traditional volumes for both diagnostic and treatment prediction tasks, with interpretable weight maps providing insights into the local features driving model performance.

Background: Childhood trauma exposure (TE) may heighten negative emotional responses, overwhelm cognitive control, and increase risk for anxiety disorders. Cognitive control is facilitated by glutamatergic (Glu) excitatory neurotransmission within the dorsal anterior cingulate cortex (dACC). Dynamic changes in dACC Glu levels were investigated using 1H functional magnetic resonance spectroscopy (1H fMRS) to assess the impact of negative emotional processing on neural mechanisms supporting cognitive control in TE-youth. Methods: Fifty adolescents were categorized into two TE-Groups: Higher (Mtrauma=6{+/-}1events) and Lower (Mtrauma=3{+/-}1events). 1H fMRS from the dACC was acquired during an inhibitory motor control task requiring tapping responses to stimuli under two Response Modes, NonSelective (100% response) and Selective (80% response, 20% inhibition), executed with two Stimuli Conditions, Squares (no emotion) and Faces (emotion). Glu modulation (relative to basal levels) was tested across TE-Group, Stimuli Condition, and their interaction. Within each Stimuli Condition, Glu modulation was tested across Response Modes by TE-Group. Results: We observed a 2-way interaction of TE-Group x Stimuli Condition ({chi}2=4.66, p=0.031). Post-hoc tests revealed significantly lower Glu modulation in Higher TE vs Lower TE (p=.023) during Faces but not Squares. This Glu modulation did not differ across Response Modes. Within the Higher TE-Group, Glu was significantly reduced during Faces compared to Squares (p<.001). Basal dACC Glu levels did not differ between groups. Conclusions: TE-Group differences in adolescent dACC Glu modulation were observed during cognitive control performed with emotional, but not non-emotional, stimuli, highlighting the value of 1H fMRS for detecting trauma-related differences in task-related excitatory neurochemical dynamics.

IntroductionBipolar disorder (BD) is characterized by recurring episodes of mania and depression. Despite extensive research, the pathophysiology underlying these mood swings remains elusive. Emerging evidence indicates a potential role for neuroinflammation and microglial activation in the pathophysiology of BD. MethodsWe employed a reverse-translational approach to generate directly induced microglia-like (iMG) cells from peripheral blood monocytes of a single patient with BD, repeatedly sampled across depressive, manic, and subsequent depressive phases. RNA sequencing was performed on iMG cells at each time point to identify differentially expressed genes related to mood state transitions. ResultsA thorough analysis of longitudinal gene expression data has led to the identification of three functional gene categories: "state-dependent genes", "depression-to-mania transition genes (named: firing genes)", and "mania-to-depression transition genes (named: extinguishing genes)". A total of 168 firing, 59 extinguishing, and 77 state-dependent genes were identified. Notably, functional annotation revealed that, compared to the extinction gene set, the firing gene set was enriched in immune and inflammatory response pathways, particularly early-response cytokines such as IL1B and TNF. ConclusionsBased on these findings, we propose that inflammatory immunomodulation by microglia contributes to mood switching in BD, especially in the process of depression-to-mania transition. The classification of genes by their relationship to state transitions offers a novel framework for understanding the molecular mechanisms underlying this complex disorder and may identify potential therapeutic targets to stabilize mood. Further validation with larger cohorts is warranted.

BACKGROUND: Cognitive flexibility represents a crucial function in adapting to new environments. In this study we examined the ecological validity of a cognitive flexibility task by studying its relationship with individual traits (dogmatism, dependence on routines and perspective taking). Second, we investigated whether global and local structural brain connectivity properties were related to cognitive flexibility as well as associated traits and their possible age-related differences. METHOD: Thirty-eight young (18-35 years) and thirty-seven older (60-85 years) healthy participants took part in an MRI protocol including a Diffusion Weighted Imaging (DWI) sequence. Participants also performed a Rule-Switching task to measure cognitive flexibility performance and filled in questionnaires assessing dogmatism, dependence on routines and perspective taking. RESULTS: A higher cognitive flexibility was related to lower dogmatism and lower dependence on routines only in young adults. In relation to structural connectivity, we found that: a) global and local connectivity properties negatively predicted dogmatism levels in the full sample, b) local connectivity properties of the inferior frontal gyrus (IFG) positively predicted performance in cognitive flexibility performance in the full sample and in older adults, and c) connectivity between left inferior parietal lobule (IPL) and left putamen negatively predicted dogmatism in older adults. DISCUSSION: A deeper understanding of the shaping of structural networks supports a better understanding of cognitive flexibility and dogmatism in a highly dynamic world.

Background: Previous large-scale structural MRI analyses of the brain in autism have identified gray matter (GM) differences when using region-of-interest analyses based on gross anatomical regions. However, such analyses have limited spatial specificity for localizing neuroanatomical alterations and may obscure subtle, spatially focal differences. Whole brain voxel-based morphometry (VBM) analyses enable greater spatial precision for localizing GM and white matter (WM) alterations in autism. Purpose: To rigorously identify voxel-wise GM and WM volume differences in autism in the largest VBM mega-analysis to date. Materials and Methods: This retrospective mega-analysis included structural 3D volumetric T1-weighted MRI brain scans from 3,051 participants (1,519 autism; 1,532 neurotypicals) collected across 51 sites/scanners. Voxel-wise GM and WM volumes were quantified using the ENIGMA CAT12 VBM pipeline. Linear mixed-effects regression was performed at each voxel to evaluate the association between diagnostic group and voxel-wise volume while adjusting for standard nuisance covariates Results: A total of 3,051 participants (15.0 {+/-} 8.2 yrs; 2,342 male) were included in the study. Autism was associated with widespread lower GM volume involving cortical, subcortical, and cerebellar regions. The most extensive alterations in autism were detected in the orbitofrontal cortex, amygdala, thalamus, and posterior lobes of the cerebellum. WM volume was lower in autism across major projection, commissural, association, and cerebellar/brainstem tracts, including the corona radiata, internal capsule, corpus callosum, and cerebellar peduncles. These findings remained consistent in sensitivity analyses, including the application of increasingly strict motion exclusion criteria. Conclusion: Autism is associated with smaller voxel-wise GM and WM volume involving widespread cortical, subcortical, and cerebellar regions. Our findings remained robust across supplementary analyses and provide high-resolution localization of structural brain differences in autism. These findings support the involvement of distributed neural systems underlying reward processing, sensory integration, and motor functioning in autism.

Non-suicidal self-injury (NSSI) among adolescents is a prevalent mental health problem and an important indicator of potential suicide risk. Early objective identification and neural mechanism analysis are therefore crucial for clinical screening and intervention. Traditional assessments mainly rely on self-report scales and clinical interviews, which are vulnerable to subjective bias, clinical experience, and missed diagnosis. Electroencephalography (EEG), with its non-invasive, low-cost, and high-temporal-resolution characteristics, provides a promising physiological basis for identifying NSSI-related neural abnormalities. However, EEG-based intelligent recognition of adolescent NSSI remains limited, and existing studies often emphasize classification performance while lacking systematic neurophysiological interpretation. To address these issues, this study proposes CGA-NSSI, a lightweight deep learning framework for adolescent NSSI recognition. The model integrates a one-dimensional convolutional neural network, bidirectional gated recurrent unit, and multi-head self-attention mechanism to extract local spatiotemporal EEG features, model long-range temporal dependencies, and focus on key pathology-related time segments and channels. A standardized preprocessing pipeline, together with Mixup augmentation and Focal Loss, is further used to alleviate sample imbalance and improve robustness in small clinical EEG datasets. Experiments on a real-world adolescent clinical EEG dataset show that CGA-NSSI can effectively identify NSSI-related EEG patterns under imbalanced sample conditions. Interpretability and functional connectivity analyses further reveal prefrontal-centered cross-regional network reorganization, excessive static functional coupling, reduced dynamic connectivity fluctuations, and increased abnormal state occupancy. These findings suggest that CGA-NSSI not only improves objective NSSI recognition but also provides neurophysiological evidence for understanding adolescent self-injury.

Purpose: To investigate sex differences in cerebral blood flow through densely parcellated cortical and subcortical regions using explainable artificial intelligence methods and identify neurobiologically interpretable perfusion biomarkers. Methods: High-resolution pseudo-continuous arterial spin labelling (1.875 mm x 1.875 mm x 3 mm) and structural MRI data were curated from 215 healthy young adults (150 females, 95 males; age 18-30 years) from the publicly available I See your Brains (ISYB) dataset. Cerebral blood flow was quantified using atlas-based regional analysis with the Brainnetome Atlas (246 regions) and optimized registration procedures. Sex classification employed diverse machine learning paradigms including linear classifiers, ensemble methods, and kernel-based approaches for regional CBF features, with deep convolutional neural networks (CNN) applied to whole-brain 3D imaging data. Model interpretability was achieved using SHapley Additive exPlanations (SHAP), computed over an ensemble of 500 logistic regression models (100 iterations x 5-fold cross-validation). Regions appearing among the top 20% of discriminative features more than 289 times were considered statistically significant using binomial testing. GradCAM was used to obtain class-specific attribution maps from the CNN model. Results: Perfusion-based features demonstrated superior sex classification performance compared to structural morphometry. Regional CBF analysis using logistic regression achieved 91 +/- 2% balanced accuracy and 0.95 +/- 0.05 ROC-AUC, substantially outperforming morphometric features (85 +/- 8% balanced accuracy, 0.88 +/- 0.06 ROC-AUC). Deep learning classification of 3D CBF maps achieved a performance of 92 +/- 5% balanced accuracy, 0.92 +/- 0.05 ROC-AUC. SHAP analysis identified 30 statistically significant aggregation-agnostic CBF-based biomarker regions using regional CBF, predominantly involving frontoparietal control networks (27%) and default mode networks (17%). Grad-CAM revealed that the 3D CNN model primarily focused on regions within the frontal lobe. Morphometry-based analysis identified 28 discriminative regions with markedly different anatomical distribution (r = 0.21) emphasizing visual (32%) and default mode (14%) networks. Conclusion: Cerebral blood flow patterns provide highly sensitive and biologically interpretable markers of sex differences in young adult brain. The identification of robust perfusion biomarkers through explainable AI demonstrates the clinical potential of ASL imaging for precision medicine applications in neuroscience. We establish a methodological framework for investigating sex-specific brain physiology using non-invasive neuroimaging.

Background: The Western Aphasia Battery-Revised (WAB-R) Aphasia Quotient is the most widely used standardized post-stroke aphasia measure; its conventional 93.8 cutoff has limited sensitivity to mild residual impairment. Beyond the cutoff, it offers limited objective discourse assessment, no action-naming assessment, and naming tests limited to very common objects. Aims: We sought short tests capturing subtle aphasia in patients recovered above the WAB-R threshold, then its demographic and lesion correlates. Methods & Procedures: Sixty-seven patients with acute left-hemisphere ischemic stroke completed acute structural MRI and a 12-month language battery comprising the WAB-R, Boston Naming Test (BNT), Hopkins Action Naming Assessment (HANA), and Modern Cookie Theft (MCT) picture description. Hierarchical logistic (binary deficit) and linear (control-referenced composite z-score) regressions evaluated acute aphasia history, sex, education, age, acute depression (PHQ-9), and residualized regional lesion load. Outcomes & Results: Of 67 participants, 45 (67%) recovered above the WAB-R threshold. Of these, 18 (40%) had residual deficits on at least one supplemental test ("subtle aphasia"). BNT plus MCT content-unit count captured all 18 (100%); HANA added none beyond these two. The binary model discriminated deficit from no-deficit at AUC = 0.80 (95% CI [0.70, 1.00]); higher education significantly lowered deficit odds (OR = 0.80/year, 95% CI [0.64, 1.00], p = .049). On the continuous composite, acute PHQ-9 independently predicted 12-month outcome ({beta} = -0.13 per point, 95% CI [-0.22, -0.04], p = .006, cumulative R-squared = 0.38). Applying the Senthilkumar et al. (2026) stricter cutoff (WAB-AQ [&ge;] 96.7) reclassified 12 of 45 (27%) out of recovery, capturing 8 of 18 (44%) subtle-aphasia patients. Composite residualized lesion load did not differentiate the groups when adjusted. Conclusions: Above the WAB-R recovery threshold, subtle aphasia is present on the BNT or MCT in ~40%, with higher education associated with lower odds at 12 months; acute depression emerged as a candidate correlate but did not survive removal of a single high-influence observation, warranting replication in larger samples. Regional lesion variables informative at greater stroke severity contribute little as large lesions cluster in the persistently aphasic group, reducing lesion variance within the recovered subgroup and its discrimination of subtle deficits. This adds to evidence that clinicians should not infer complete language recovery from the WAB-AQ alone, and that identifying residual deficits may require greater investment in behavioral assessment and consideration of alternative WAB-AQ cutoffs. Structural anatomical information, by contrast, appears to add little discriminative value at the upper performance range.

The current study assessed whether N-acetylcysteine (NAC), which inhibits the kynurenic acid (KYNA)-synthesizing enzyme kynurenine aminotransferase (KAT) II, affects tryptophan (TRYP)-induced peripheral formation of the kynurenine pathway metabolites kynurenine and KYNA and improves selected functional outcome measures in people with schizophrenia. Fifty-eight participants with DSM-5 schizophrenia or schizoaffective disorder entered a double-blind, placebo-controlled, randomized cross-over challenge study, in which they were pretreated with either NAC (up to a maximum of 15 g) or placebo, then received TRYP, 6 g. Prior to and after receiving the study medications, participants underwent laboratory (serum kynurenine and KYNA), symptom (BPRS, SANS, and CDS), cognitive (6 MCCB tests) and brain MRI (ASL, DTI, 1H-MRS) assessments. In contrast to placebo pre-treatment, NAC significantly reduced the TRYP-induced increase in peripheral serum levels of kynurenine (t=-2.02; p<0.05) and KYNA (t=-3.21; p=0.002). NAC pre-treatment was associated with significantly smaller increases in total white matter (WM) cerebral blood flow (CBF) (t=-2.15; p=0.04) and a trend for smaller increases in total gray matter (GM) CBF (t=-1.81; p=0.08). NAC pre-treatment significantly reduced the TRYP-induced decrease in MCCB composite score (t=2.07; p=0.04). There was no differential treatment effect on DTI or 1H-MRS or symptom measures. The observation that NAC attenuated the de novo formation of KYNA, reduced WM CBF elevations, tended to decrease GM CBF, and blocked the worsening of cognitive performance in participants following TRYP administration, supports the concept that KAT II inhibition is a promising novel strategy for the treatment of cognitive impairments in people with schizophrenia.

While evidence suggests magnocellular deficits in the geniculostriate pathway in adults with dyslexia, neural deficits in the subcortical pathways during childhood remain unclear. Here, we used high-resolution fMRI to investigate subcortical abnormalities in Chinese children with developmental dyslexia. Fast achromatic motion stimuli and slowly drifting chromatic gratings were used to assess magnocellular (M) and parvocellular (P) functions, respectively. Relative to controls, children with dyslexia showed a selective reduction in responses to the M stimulus in the ventromedial pulvinar (vmPul) and the superficial layers of the superior colliculus (SCs), along with significantly reduced SCs-vmPul connectivity. Importantly, while vmPul responses to the M stimulus were positively associated with reading skills in healthy controls, this correlation was absent in children with dyslexia. Unlike previous findings in adults, the lateral geniculate nucleus (LGN) exhibited a non-selective reduction in responses to both stimuli, no volume reduction, and no correlation with reading ability. These findings demonstrate a selective deficit to achromatic motion processing in the colliculus-pulvinar pathway in children with dyslexia, which contributes to their reading difficulties. This early subcortical disruption differs from, and precedes, the neural deficits previously reported in the adult LGN, offering new insight into the developmental trajectory of dyslexia.

Aphasia diagnosis in Indonesia remains challenging due to limited culturally and linguistically appropriate instruments. Widely used tools such as the Boston Diagnostic Aphasia Examination (BDAE) and Western Aphasia Battery (WAB) are not adapted to the Indonesian context, while Tes Afasia untuk Diagnosis, Informasi, dan Rehabilitasi (TADIR) provides screening but lacks diagnostic accuracy. To address this gap, we developed the Instrumen Diagnosis dan Evaluasi Afasia (IDEA) for native Indonesian speakers and evaluated its validity, reliability, and normative cutoff values in cognitively healthy Indonesian adults. Eighty-three cognitively normal adults (screened using MoCA-Ina) with no history of neurological disease were assessed using IDEA, which evaluates six language domains. Items were adapted from existing tools and reviewed by experts. Content validity, internal consistency (Cronbachs alpha), and construct validity (Exploratory Factor Analysis) were analyzed using SPSS v25. A total of 83 participants were included (median age = 55.81 years, 54% secondary education). IDEA demonstrated good feasibility, with an average completion time of 45-60 minutes depending on participant engagement. Content validity was established by unanimous expert consensus. Construct validity showed meritorious sampling adequacy (KMO = .872) and significant sphericity (Bartletts test {chi}^2 (15) = 278.523, p<.001), supporting factor analysis. Internal consistency showed good reliability across six domains (Cronbachs = 0.896). IDEA is a valid and reliable tool for assessing aphasia in Indonesian natives. It is a culturally appropriate assessment tool which offers structured, domain-based evaluation and supports differential diagnosis of both classical and progressive aphasia syndromes. Keywords: Aphasia, Language Assessment, Indonesian, IDEA, Validity

Background Functional neurological disorder (FND), one of the most common neurological conditions, affects women almost twice as frequently as men. The reasons for this are unknown, and there has been minimal research into how physiological and pathological features of women's health interact with symptoms of FND. Methods We conducted an online survey assessing the effect of several aspects of women's health with the severity of symptoms of FND. Results 484 people completed the survey. Among the 223 who had regular or fairly regular menstrual cycles, a strong difference across the menstrual cycle was seen, with symptoms at their best in the follicular phase, worsening in the luteal phase, and worst in the pre-menstrual period and the menses. This effect was not moderated by a proxy measure of pre-menstrual dysphoric disorder (PMDD). Participants who were taking the combined oral contraceptive (COC, n=43) and progesterone-based contraception (n=80) were more likely to report symptom improvement from starting the medication than worsening. When compared to menstruating participants who were not taking the COC, participants taking the COC reported less worsening in their symptoms of FND in the luteal, pre-menstrual, and menstrual phases. Of the 99 women who had passed menopause since developing FND, 76% reported worsening of their FND symptoms after menopause. Discussion This study demonstrates interactions between several aspects of women's health and symptoms of FND. The observed pattern of symptom fluctuation across hormonal states suggests a potential modulatory role of oestrogen, warranting further targeted investigation.