NeuroImage: Reports

Background: Transcranial direct current stimulation (tDCS) is increasingly used as an adjunct to rehabilitation for young people with cerebral palsy (CP), yet considerable variability exists in clinical response. Individualised electric field modelling provides an opportunity to estimate the distribution of electrical fields generated by the stimulation delivered to the brain and explore potential relationships with functional outcomes. Methods: Structural MRI scans from nineteen participants (10-16 years) from a previously published randomised controlled trial (ISRCTN74235136) investigating the effects of tDCS combined with motor training, underwent participant-specific finite element modelling using SimNIBS. Electric field strength was quantified within anatomically defined motor regions of interest, including the primary motor cortex (M1), dorsal premotor cortex (PMd), supplementary motor area (SMA), and a combined motor network. Global grey matter electric field metrics and stimulation focality were also extracted. Results: Estimated electric field strength differed significantly across motor regions (p<0.001), with PMd receiving significantly greater stimulation than both M1 and SMA. Electric field strength within a control region (primary visual cortex) was significantly lower than within M1 (p<0.001). Despite inter-individual variability in regional and global electric field metrics, no significant associations were observed between estimated electric field strength or focality and changes in function following intervention. Conclusion: Individualised electric field modelling demonstrated that an M1-targeted tDCS montage preferentially stimulated PMd rather than M1 in young people with CP. These findings highlight the importance of subject-specific modelling when characterising current distribution and suggest that variability in electric field strength alone does not explain variability in behavioural response.

Background: Large language models have been proposed to improve patient comprehension of radiology reports. However, whether they improve objective understanding remains unproven. Purpose: To evaluate the effect of appending an LLM-generated lay summary to brain MRI reports on objective and subjective patient comprehension in a randomized controlled trial. Materials and Methods: In this randomized controlled trial, 2,727 adult participants from the ComPaRe e-cohort were randomly assigned to interpret six standardized brain MRI reports for headache, presented either in their native format (control; n = 1,401) or appended with a lay summary generated by an open-weights LLM (Mistral Small 3.2) (intervention; n = 1,326). The primary outcome was objective comprehension, defined as the rate of correct classification of whether the report provided a probable explanation for the headache, with ground truth established by four-radiologist consensus. Secondary outcomes included satisfaction, subjective comprehension, anxiety, and willingness to contact a healthcare professional. Generalized estimating equations accounted for repeated within-participant observations. Results: A total of 2,727 participants (mean age, 52 years +/- 15; 75.2% women) were evaluated. Objective comprehension did not differ between arms (58.3% vs 59.4%; odds ratio (OR) 0.97; 95% CI: 0.90-1.06; P = .54). The intervention significantly improved overall satisfaction (64.9% vs 36.7%; OR 3.26; 95% CI: 2.93-3.64; P < .001) and subjective comprehension (50.3% vs 24.0%; OR 3.17; 95% CI: 2.82-3.56; P < .001). High anxiety was modestly reduced (25.1% vs 26.6%; OR 0.92; P = .037). The effect on objective comprehension varied by report type (P for interaction < .001): summaries improved comprehension of symptom-explaining reports (42.4% vs 37.4%; P < .001) but reduced it for normal reports (72.5% vs 76.6%; P = .001). Conclusion: LLM-generated lay summaries appended to brain MRI reports improved patient satisfaction and subjective comprehension but did not improve objective comprehension, indicating a gap between perceived and actual understanding that should be addressed before clinical integration.

Objectives: Non-invasive brain stimulation (NIBS) holds significant promise for treating neurological and neuropsychiatric conditions, yet translation into routine clinical practice remains limited. We aimed to explore stakeholder perceptions of NIBS and barriers to its clinical adoption. Methods: We conducted focus-group interviews with 33 participants across three key stakeholder groups in the UK: (1) people with lived experience of brain injury, depression, or dementia; (2) healthcare professionals; and (3) researchers. Reflexive thematic analysis was used to identify themes in the data. Findings: Seven key themes emerged spanning preferences, hope and disappointment, communication, accessibility, infrastructure, ethical/regulatory uncertainty, and the evidence base. Across groups, NIBS was viewed positively and with cautious optimism, but substantial barriers were highlighted, including limited public and clinical awareness, challenges in demonstrating cost-effectiveness, infrastructure constraints, and difficulties navigating regulatory and translational pathways. Participants emphasised the importance of clear communication, improved education, and stronger interdisciplinary collaboration to support adoption. Notably, stakeholders prioritised evidence of clinical efficacy and usability over detailed mechanistic understanding. Conclusions: These findings provide actionable insights into the translational gap in NIBS and highlight priorities for facilitating its integration into clinical care.

Objective: This computational modeling study quantified the influence of sex and race-related cranial anatomy on predicted brain-wide current flow during electroconvulsive therapy (ECT) across conventional (bifrontal (BF), bitemporal/bilateral (BL), right unilateral (RUL)) and experimental (focal electrically administered seizure therapy (FEAST) and frontomedial (FM)) electrode montages. The objective was to determine whether race-associated variability meaningfully contributes to differences in ECT stimulation metrics across montages. Methods: Finite element head models of Chinese, Black, and Caucasian subjects were developed using high-resolution magnetic resonance imaging and analyzed using the Realistic vOlumetric- Approach-based Stimulator for Transcranial electric stimulation (ROAST) pipeline (N = 150 total; n = 50 per cohort, comprising 25 M and 25 F, age range: 20-30 years). Five ECT montages were simulated under a constant-current condition (900mA). Stimulation strength (Ebrain/Eth) was quantified as 90th percentile of brain-wide E-field magnitude (Ebrain) relative to neuronal activation threshold (Eth = 0.25 V/cm) quantified stimulation strength. Overall focality was evaluated as a percentage of brain volume stimulated above the neural activation threshold (Ebrain [&ge;] Eth), while laterality was quantified as the median right-to-left hemispheric E-field magnitude ratio. The effects of race, sex, and montage on stimulation strength, focality, and hemispheric laterality were statistically analyzed. Results: Substantial race- and sex-related differences observed in cranial anatomy resulted in systematic variation in predicted ECT-induced E-field intensity. Brain-wide E-field magnitude varied by both race and montage, with the largest fields generally observed in Caucasian head models and during BL stimulation. Montage exerted the strongest effect on stimulation strength (Ebrain/Eth) with BL and FEAST producing the highest stimulation strengths, followed by RUL and FM, while BF produced the lowest. Caucasian subjects generally predicted higher stimulation strengths than Black and Chinese subjects, whereas females predicted modestly higher stimulation strengths than males. Laterality was primarily determined by montage, with FEAST producing the greatest hemispheric asymmetry, followed by RUL. Chinese subjects demonstrated higher laterality ratios than both Black and Caucasian subjects. BL, RUL, and FEAST stimulated substantially larger brain volumes above neural activation threshold (less focal stimulation) than BF. Lower focality was observed in Caucasian subjects relative to Black and Chinese subjects, and in females relative to males. Conclusions: Electrode montage was the primary determinant of predicted ECT stimulation strength, focality, and laterality. Race-related anatomical differences and, to a lesser extent, sex-related differences systematically altered stimulation patterns, supporting consideration of individualized anatomy in ECT dosing and treatment optimization.

Introduction The superior longitudinal fasciculus (SLF) is a major association fiber bundle implicated in cognition, visuospatial attention, language, and motor control, and its impairment is linked to several neurological and neuropsychiatric disorders. This proof-of-concept study was performed with three main objectives in healthy adults. First, to fuse whole brain spectroscopic (WBSI) and diffusion MRI (dMRI) derived parametric maps along the SLF I and II segments to quantify their spatial concordance, second, to evaluate regional metabolite concentrations and microstructural properties along these trajectories and finally, to determine the relationships between the WBSI and dMRI parameters within these segments. Methods Ten healthy adults (4F, 6M; mean age 31.4 {+/-} 7.53 years) underwent 3T MRI including multi-shell high angular resolution diffusion imaging and WBSI. After preprocessing and non-linear co-registration, WBSI-derived white matter metabolite maps and neurite orientation dispersion and density imaging (NODDI) / diffusion tensor imaging (DTI) derived parametric maps were spatially aligned and projected along the centroid of reconstructed SLF I and II segments divided into 20 discrete, anatomically contiguous sections. Results A strong spatial alignment between WBSI and dMRI imaging modalities was confirmed by mutual information and Pearson's correlation analyses. Intra-subject repeatability, as assessed from a single participant scanned three times, demonstrated high tract reconstruction reliability (mean Dice similarity coefficients >0.79; track density-weighted Dice >0.97) and acceptable intra-subject coefficients of variation. Inter-subject coefficients of variation were within acceptable ranges ({approx}3-17%) for most parameters, with free water fraction (fiso) exhibiting relatively higher variability. Single and multivariate regression analyses revealed significant associations between WBSI and dMRI tract profiles: choline/creatine (Cho/Cr) and choline/ N-acetyl aspartate (Cho/NAA) ratios showed positive linear associations with intra-cellular volume fraction (ficvf) and fractional anisotropy (FA), and negative associations with mean diffusivity (MD) along bilateral SLF I, with ficvf and MD identified as the strongest combined predictors of metabolite ratios. Conclusion Co-localization/fusion of WBSI and NODDI/DTI data into one framework offers a reliable, user-independent way for mapping regional metabolite and microstructural alterations along the path of SLF. Moving forward, this image processing pipeline has the potential to enhance diagnosis and clinical assessment of neurological disorders linked to SLF damage.

Background: Choroid plexus (CP) volume is an emerging magnetic resonance imaging (MRI) biomarker in various disorders of the central nervous system (CNS). However, clinical translation is hindered by methodological heterogeneity and inconsistent anatomical coverage. Double inversion recovery (DIR) - a sequence providing dual-tissue suppression - is a promising candidate to improve CP segmentation. Methods: The dataset included 93 scans across healthy subjects and individuals with multiple sclerosis (MS), divided into a training set (n = 63), an internal test set (n = 20), and an external test set (n = 10). First, relative CP signal intensity and tissue contrast ratios on DIR were compared against fluid-attenuated inversion recovery (FLAIR) and T1-weighted (T1w) sequences (pre- and post-contrast). Reproducibility of manual CP segmentations was assessed via intraclass correlation coefficients (ICCs). Subsequently, we developed a 3D nnU-Net model for CP segmentation based on manually labeled DIR masks. Model performance was evaluated against manual segmentation using spatial overlap and volumetric error metrics. Finally, we compared our DIR-based model against three publicly available T1w- or FLAIR-based tools by assessing slice-wise volume distributions and voxel-wise density maps. Results: DIR demonstrated the highest CP signal intensity and most consistent tissue contrast among evaluated MRI sequences (p < 0.001). Intra- and inter-rater agreement for manual CP segmentations was robust (ICC = 0.92 and 0.83, respectively). The trained nnU-Net achieved high internal accuracy (Dice = 0.82) independent of scanner, diagnosis, or absolute CP volume, and generalized well to the external test set (Dice = 0.75). Compared to public T1w- and FLAIR-based models, DIR-based approaches (nnU-Net and manual) yielded significantly larger CP volumes (p < 0.01). Axial volume distribution analysis attributed this difference to a distinct bimodal profile in DIR segmentations, more fully capturing the CP inside the temporal horn of the lateral ventricle (p < 0.001 against T1w- and FLAIR-based models). Conclusions: By leveraging the superior tissue contrast of DIR, our nnU-Net model achieves highly accurate CP segmentation that generalizes across scanners and captures the inferior extent of the C-shaped structure often missed by conventional models. This may improve standardization of CP volumetry and allow for more reliable studies in CNS disorders.

Purpose: To develop and evaluate an anatomy-aware deep learning framework for enhancement of neonatal 64mT T2-weighted MRI that improves anatomical visibility while preserving native ultra-low-field contrast and enabling quantitative structural analysis. Methods: A multitask network, jointly performing image enhancement and tissue segmentation, was trained on 75 and evaluated on 20 paired neonatal 64mT/3T MRI datasets spanning a broad range of gestational ages and pathologies. To preserve native 64mT contrast, 3T images were locally harmonized before training. The framework also generated quality-control maps and regional volumetric measurements. Volumetric agreement was further assessed in 40 paired term-born control datasets. Results: Enhanced 64mT images showed improved image quality metrics and better delineation of cortical, deep gray matter, ventricular, white matter, and posterior fossa structures while maintaining native contrast characteristics. Tissue segmentations demonstrated good agreement with reference 3T labels. Volumetric measurements showed excellent correspondence with 3T across major tissue compartments, with only small systematic regional biases. Conclusions: Anatomy-aware enhancement enables automated tissue segmentation and volumetric analysis directly from neonatal 64mT MRI while preserving native image contrast. These findings support the feasibility of quantitative neonatal neuroimaging at ultra-low field.

Background and Objectives: Word-finding difficulty is common in healthy aging and in neurologic disorders, including temporal lobe epilepsy (TLE) and early Alzheimer disease. Standard language measures have limited sensitivity for detecting subtle or longitudinal changes in spontaneous speech. We examined whether natural language processing and acoustic analysis of spoken biographical recall could identify lexical and temporal speech features associated with language and memory performance in TLE. Methods: We conducted a cross-sectional observational study of spoken recall during a Famous Faces biographical memory task. Adults with TLE and healthy controls (HCs) viewed 20 famous faces and spontaneously recalled biographical details. Speech was transcribed and diarized using automated tools. Lexical measures included word counts and lexical index (ratio of rare to common words). Acoustic measures included utterance and pause duration and pause frequency. Features were compared between groups and correlated with neuropsychological measures, including Montreal Cognitive Assessment (MoCA), Boston Naming Test (BNT), delayed recall, education, and biographical recall accuracy Results: Eighty-one adults participated (51 TLE, 30 HCs). Lexical measures did not differ between groups. In TLE, lexical index correlated with BNT performance (rs=0.62) and MoCA score (rs=0.35). Compared with HCs, participants with TLE produced shorter utterances (5.54 {+/-} 2.50 vs. 6.59 {+/-} 2.63; Cohen's d=0.41, 95% CI -0.05 to 0.86, p=0.041), shorter pauses (0.61 {+/-} 0.21 vs 0.67 {+/-} 0.22, Cohen's d=0.29, 95% CI -0.16 to 0.74, p=0.043), and more frequent pauses (10.81 {+/-} 3.30 vs 9.29 {+/-} 3.59, Cohen's d=-0.45, 95% CI -0.90 to 0.01, p=0.036). Higher education was associated with longer utterances, longer pauses, and lower pause frequency, without evidence of a diagnosis-by-education interaction. Faster utterance rate was associated with better biographical recall in both groups, while higher pause rate was associated with worse recall in TLE. Discussion: Speech-derived lexical and temporal features from naturalistic recall capture clinically relevant variation in language and memory-related performance. Although lexical output did not distinguish TLE from HCs, lexical richness tracked naming and global cognition in TLE, while temporal speech features related to recall performance. These findings support the potential of automated speech analysis as a digital behavioral biomarker for word-finding difficulty in neurologic populations.

Background: Neuroimaging studies implicate network alterations in functional motor disorder (FND-motor), yet white matter remains poorly characterized. Objectives: To characterize white matter microstructure in FND-motor relative to healthy (HCs) and psychiatric (PCs) controls and examine symptom associations. Methods: Fifty individuals with FND-motor, 50 age- and sex-matched HCs, and 50 PCs matched on age, sex, depression, anxiety, and post-traumatic stress disorder severity underwent multi-shell diffusion MRI. Voxel-based analyses examined whole-brain white matter using diffusion tensor imaging (fractional anisotropy [FA], mean diffusivity [MD]) and neurite orientation dispersion and density imaging (NODDI) (neurite density index [NDI], orientation dispersion index, and free water fraction [FWF]) metrics. Cross-metric convergence was characterized using atlas-based tract overlap analyses and probabilistic tractography. Associations with FND symptoms and transdiagnostic physical symptoms were also evaluated. Results: Compared with HCs, FND-motor showed higher FA/NDI and lower MD/FWF, predominantly in the middle cerebellar peduncle. Compared with PCs, differences were limited to lower MD/FWF, involving the corpus callosum, middle cerebellar peduncle, and left inferior longitudinal fasciculus. Greater FND symptom severity was associated with a lower FA/NDI and higher MD/FWF in the corpus callosum and right-lateralized association and projection pathways, whereas greater transdiagnostic physical symptom burden across FND-motor and PCs was associated with higher FA and lower MD/FWF in the middle cerebellar peduncle. Conclusions: This study provides a comprehensive multi-metric diffusion-weighted characterization of white matter microstructure in FND-motor relative to both HCs and PCs - highlighting cortico-cerebellar connections via the middle cerebellar peduncle as distinct in FND-motor and associated transdiagnostically with physical symptom burden.

The subgenual anterior cingulate cortex (sgACC) is a key node in treatment-resistant depression (TRD), but precise non-invasive neuromodulation of this target is challenging. Preclinical studies of non-ablative stereotactic radiosurgery (SRS) have shown neuromodulatory ("radiomodulation") effects. In this single-center, double-masked, randomized, dose-seeking pilot trial, nine adults with TRD were randomly assigned to bilateral sgACC radiomodulation at a dose of either 15, 20, or 25 Gy per hemispheric target. Primary endpoints were safety and feasibility; the efficacy endpoint was week-4 change in the Montgomery-Asberg Depression Rating Scale (MADRS). Both primary endpoints were met: the only treatment-related adverse event was transient grade 1 dizziness, with no structural MRI abnormality through week 12. Mean MADRS fell from 33.0 to 17.0 (48.5% reduction); 67% responded and 44% remitted, with benefit sustained to week 12. Resting-state fMRI revealed regional connectivity changes correlating with clinical improvement, with tractography showing streamline counts differing by response status. These first-in-human findings support a larger randomized controlled trial of sgACC radiomodulation for TRD. ClinicalTrial.gov registration: NCT07274917.

Purpose: Attenuation correction (AC) of PET images is essential for accurate quantification. Brain PET studies comprising simultaneous EEG (PETEEG) may suffer from metal artifacts in CT images (CTEEG), or improper correction when electrodes are not present in the CT (CT0). As these influences are not well-characterized, we aim to compare metal artifact reduction (MAR) techniques for CTEEG images, and evaluate differences between attenuated-corrected PETEEG using CT0 and CTEEG with MAR, synthetically placed electrodes (CTEEG-synth) and extended Hounsfield unit (HU) range. Methods: 19 healthy participants underwent two total-body PET/CT scans with [18F]FDG, with and without 32 EEG scalp electrodes, respectively. We evaluated five MARs to reduce streaks caused by the EEG electrodes in the CTEEG. Finally, CT0, CTEEG with (CTEEG-iMAR-Ext) and without extended HU range (CTEEG-iMAR) and CTEEG-synth were used to perform attenuation correction of PETEEG. We compared our results to PET0/CT0 scan using relative differences. Results: CTEEG and CTEEG-iMAR showed the smallest differences to CT0. PETEEG/CTEEG-iMAR-Ext exhibited the lowest differences to PET0/CT0 (average bias across all regions of -0.46%), followed by similar performance of PETEEG/CTEEG-iMAR (-0.73%) and PETEEG/CTEEG (-0.76%). Conversely, PETEEG/CT0 demonstrated the largest average differences (-1.81%), with values reaching -2.71% in the parietal lobe. These differences were consistent across subjects, yielding significant effects in most of the brain (pFWE < 0.05). CTEEG-synth performed not as good as CTEEG (-1.21%). Conclusions: CTEEG with extended HU range is most suitable for attenuation correction of PETEEG images, with MAR correction offering little additional improvement.

Background: Hippocampal sclerosis (HS) is a common cause of drug-resistant focal epilepsy (DRFE) and amenable to neurosurgical treatment. Detection relies on MRI but can be challenging. 7 Tesla (T) ultra-high field MRI and automated MRI post-processing tools have independently been shown to improve radiological diagnosis of HS. However, combining these approaches remains underexplored. This study evaluated whether AID-HS, a tool for HS detection developed using 3T MRI, generalises to 7T MRI data. Methods: We collated a dataset of paired 3T and 7T T1-weighted MRI from four epilepsy centres, including 23 patients with HS, 39 healthy controls, and 23 individuals with focal cortical dysplasia as disease controls. Histopathology served as the gold standard for defining HS where available (n=7), otherwise radiological findings (n=16). AID-HS was applied to images acquired at both field strengths, and sensitivity and specificity for detection and lateralisation of HS were compared. Additionally, agreement of hippocampal features across 3T and 7T was evaluated. Results: We found no evidence of a difference in performance of AID-HS between 3T and 7T. Sensitivity for detection of unilateral HS was 63% (12/19) at 3T and 68% (13/19) at 7T (McNemar's exact test p=1.0). Specificity in controls was 97% (60/62) at 3T and 100% (62/62) at 7T (p=0.5). Bilateral HS was correctly flagged in 3 of 4 cases using feature-based criteria, with high specificity in controls. Quantitative hippocampal features showed moderate to good agreement across field strengths (ICC 0.70 to 0.98), with small differences observed for volume and thickness estimates. Conclusion: AID-HS provides robust detection and lateralisation of HS across multiple 7T MRI centres, highlighting its potential to enhance lesion detection. Future work is needed to investigate whether models trained on 7T data can leverage the improved image quality for further gains in HS detection performance.

BackgroundSingle-voxel magnetic resonance spectroscopy (MRS) is a non-invasive method for measuring clinically and cognitively relevant metabolites. Reliable measurements require precise voxel placement across sessions and participants. We developed a scanner-console-based approach to improve voxel placement precision. MethodsIn a crossover design (n=7; six sessions each), we compared test-retest reliability of three voxel placement methods in a reference benchmark (left parietal cortex) and a technically challenging region (left ventromedial prefrontal cortex). Methods included (1) conventional anatomy-based placement, (2) mask-guided real-time positioning (MGRP), and (3) semiautomated session-locked voxel repositioning (SSVR). Resting-state MRS data were acquired using PRESS and MEGA-PRESS. Within-subject reliability of voxel placement and metabolite concentrations, namely, total N-acetylaspartate (tNAA), total Creatine (tCr), GABA (gamma-aminobutyric acid), and Glx (glutamate + glutamine) are reported using the coefficient of variation (CV), the intraclass correlation coefficient (ICC), minimal detectable change (MDC), and the spatial overlap. ResultsSSVR markedly improved voxel placement reliability, increasing spatial overlap (up to 88%) and achieving near-perfect geometric reproducibility (ICC = 0.99) compared to conventional anatomy-based placement and MGRP. SSVR improved tissue composition consistency and reduced metabolite variability in the technically challenging region (variability reduction of [~]70% tCr, [~]59% tNAA, and [~]51% Glx) while further refining already stable measurements in the benchmark region (tNAA from [~]15% to [~]10%). ConclusionBoth MGRP and SSVR improved voxel placement and metabolite measurement reproducibility compared with conventional anatomy-based placement. SSVR further enhanced within-subject reproducibility across repeated sessions, particularly in the technically challenging region, providing a robust approach for longitudinal single-voxel MRS studies.

BackgroundThe pre-supplementary motor area (preSMA) is increasingly being explored as a neuromodulation target for impulsive behaviour in several clinical populations. Treatment effects are generally interpreted as improvements in inhibitory control. However, healthy studies report improved/impaired/unchanged inhibitory control following identical preSMA stimulation protocols, and few studies examine accompanying neurophysiological changes. We therefore investigated whether preSMA stimulation influences downstream corticomotor excitability to modify a general stopping mechanism, other components of action control, or wider cue-dependent attentional processes relevant to impulsive behaviour. MethodsIn a preregistered, double-blind crossover study, 18 healthy adults received active and sham continuous theta burst stimulation (cTBS) over right preSMA. Motor-evoked potentials (MEPs), anticipatory response inhibition task measures, and alcohol dot-probe reaction times were collected before and after stimulation and analysed with linear mixed models. ResultsMEPs increased during sham (p = .028) but not after active cTBS (p = .741). Active cTBS did not affect complete or partial stopping on the response inhibition task. Instead, active cTBS slowed the continuing response after partial stopping (p < .001) whereas response execution sped up across the sham session (p < .001). No alcohol attentional bias or stimulation effect was detected. ConclusionsPreSMA cTBS did not impair general inhibitory or attentional control. Instead, it attenuated session-related corticomotor facilitation and selectively slowed reinitiation of a partially inhibited action. These findings suggest that clinical effects to impulsive behaviour from preSMA neuromodulation are primarily rooted in changes to motor preparation and action updating rather than a unitary stopping mechanism.

Background. Post-stroke anxiety and depression frequently co-occur, and whether each is independently associated with cognitive impairment remains unclear because most studies model one without adjusting for the other variable. In a five-year cohort, we tested whether anxiety and depression have distinct cognitive correlates and whether early affective status predicted subsequent cognitive recovery. Methods. Patients from the STROKDEM cohort were assessed at 6, 12, 36, and 60 months post-stroke for anxiety, depression, and five cognitive domains (memory, executive functioning, attention, visuospatial functioning, and language). Two symmetric random-intercept linear mixed models regressed each affective score on the cognitive domains while adjusting for other scores. Repeated-measures correlations, multiple imputations for attrition, and exploratory trajectory and prognostic models were also used. Results. After mutual adjustment and correction, depression was independently associated with executive and visuospatial function, whereas anxiety showed no independent cognitive correlation. Repeated-measures correlation confirmed this dissociation. The anxiety findings were stable across the sensitivity analyses and multiple imputations. Attrition was selective for baseline cognition, and exploratory associations between early affect and cognitive recovery did not survive multiple imputations and were inconclusive. Limitations. Attrition was substantial and selective on baseline cognition; the persistent anxiety subgroup was small, limiting the power for trajectory analyses; and psychiatric history, psychotropic medication, and cognitive reserve beyond education were unavailable. Conclusions. The cognitive burden of post-stroke affective disorders is carried by depression, rather than anxiety. Because anxiety-related cognitive impairment largely reflects comorbid depression, screening for depression rather than anxiety alone may better identify stroke survivors at risk of cognitive impairment.

Background. Dynamic susceptibility contrast MRI with capillary-function post-processing exports a relative maximum cerebral metabolic rate of oxygen, formed from blood flow and a transit-time-derived extraction term. The share each contributes to an observed contrast is unquantified. Methods. In a retrospective single-centre cohort with untreated glioblastoma, six perfusion maps normalised to normal-appearing white matter were sampled in automatically segmented enhancing tumour and peritumoral brain. The paired compartment contrast in the oxygen-metabolism index was partitioned into flow, extraction and residual terms and examined against tumour-core volume. Results. Of 131 patients, 122 were analysable. Flow-linked maps were about twice as high in enhancing tumour, the transit and extraction maps only modestly (all q < 0.05). Flow accounted for 92.6% (95% CI 85.9-98.8) of the contrast and extraction for 6.6% (0.7-12.9). Across volume tertiles the flow share rose from 67.8% to 104.0%, a gradient arising peritumorally: every map changed with volume there, none in enhancing tumour. Conclusion. The compartment contrast in the oxygen-metabolism index is largely accounted for by blood flow and varies with lesion size, that dependence originating peritumorally. It should be read within the complete perfusion panel, not as independent metabolic evidence.

Post-traumatic stress disorder (PTSD) has been associated with impairments in cognitive function, including working memory, and may involve altered glutamatergic regulation in the prefrontal cortex. In this study, we used 7T functional magnetic resonance spectroscopy (fMRS) to examine dorsolateral prefrontal cortex (DLPFC) glutamate during working memory in individuals with PTSD, trauma exposure without PTSD (TE), and no trauma exposure (NT). Eighty participants (27 PTSD, 27 TE, 26 NT) underwent baseline MRS followed by fMRS during a letter n-back task. A linear mixed-effects model was used to evaluate glutamate concentrations across baseline, 0-back, 1-back, 2-back, and post-task fixation conditions. Behavioral performance was assessed using repeated-measures ANOVA for percentage correct, reaction time, and the discrimination index (d) across the 0-back, 1-back, and 2-back conditions. Glutamate differed significantly by group, condition, and the group x condition interaction. Individuals with PTSD exhibited lower glutamate than NT at baseline and during the 0-back, 1-back, and 2-back conditions. TE participants also showed lower glutamate than NT during the 1-back and 2-back conditions. Within-group analyses showed higher glutamate during the 0-back, 1-back, and 2-back conditions than at baseline in the NT group, whereas these baseline-to-task differences were limited in the PTSD and TE groups. Accuracy decreased and reaction time increased with increasing working memory load, and discrimination (d) was lower in PTSD than NT. These findings demonstrate altered DLPFC glutamate dynamics during working memory in PTSD and trauma-exposed individuals. Functional MRS provides complementary information beyond resting-state MRS by characterizing glutamatergic responses during cognitive engagement and may improve our understanding of neurochemical alterations associated with trauma and PTSD.

Background. Serotonergic psychedelics show promise for treating psychiatric disorders, with symptom improvements lasting for weeks after a single dose. Clarifying the neural basis of these effects would benefit from an identification of empirical biomarkers of such lasting shifts in brain function. Resting state EEG offers a rapid (<5 minute), low-cost window into functional brain networks. However, connectivity is not static, but cycles between recurring semi-stable patterns that vary across frequency bands. Here we employed a dynamic function connectivity (dFC) framework to identify frequency-specific connectivity states and examine how they change in the weeks following psychedelic use. Methods. We collected resting-state EEG from individuals who had used one of two serotonergic psychedelic subclasses within the prior three weeks, psilocybin/LSD (typical; n=14) or 5-MeO-DMT (atypical; n=12), and age- and sex-matched controls (n=16). Frequency-band-specific spatial connectivity states (phase-lag index) were estimated across the full sample (5 per band). Groups were compared on proportion and dwell-time (per state) and state-to-state transitions. Results. A right frontoparietally-distributed beta synchrony state was dominant after both typical and atypical psychedelics use (proportion/dwell-time). This effect correlated with the number of days since using psychedelics. A globally-distributed theta-band state was prominent in recent users of typical psychedelics but occurred less often in atypical users. In contrast, neural entropy (Lempel-Ziv complexity; known to increase acutely during psychedelic dosing) was not altered in recent users of either subclass. Conclusion. These results reveal a beta-band signature of altered neural dynamics in the week following a psychedelic dose, consistent with a relaxation of brain network hierarchy after psychedelics.

Objective: Disruption of the excitation/inhibition balance may contribute to the pathophysiology of bipolar disorder, with post-mortem studies reporting abnormalities in GABA-receptors, interneurons and inhibitory signaling in prefrontal areas. Transcranial magnetic stimulation with electroencephalography (TMS-EEG) enables in vivo assessment of cortical excitability/inhibition. This study examined short-latency intracortical inhibition (SICI) after left- and right-dorsolateral prefrontal cortex (DLPFC) stimulation in bipolar depression (BDep, n=10) and healthy controls (HC, n=22). Methods: SICI (paired-pulse TMS) and excitability (single-pulse TMS) were quantified using local- and global-mean-field-power. Associations with lithium use and between-group differences in TMS-evoked potential amplitudes were also explored. Results: For left-DLPFC stimulation, BDep showed weaker SICI than HC (local: 3.7%{+/-}12.5 vs 9.0%{+/-}20.3, p=0.05; global: 1.5%{+/-}11.7 vs 8.8%{+/-}20.6, p=0.10), driven by larger ppTMS responses (weaker inhibition). For right-DLPFC stimulation, BDep showed stronger SICI than HC (local: 17.3%{+/-}16.1 vs 0.75%{+/-}27.1, p=0.36; global: 16.2%{+/-}14.6 vs -1.0%{+/-}21.8, p=0.03), driven by a larger spTMS response (enlarged excitability). Stronger right-hemispheric global-SICI was most pronounced in BDep patients not using lithium (17.9%{+/-}7.0) vs lithium users (3.9%{+/-}11.9) and HC (pFDR=0.03). Conclusions: BDep is characterized by reduced cortical inhibition after left DLPFC stimulation and enlarged cortical excitability after right DLPFC stimulation; the latter partly normalized by lithium. Significance: To our knowledge, this is the first study to apply TMS-EEG to the bilateral DLPFC in BDep, revealing distinct patterns of hemispheric dysfunction. These findings warrant replication in larger samples, to further elucidate the underlying pathophysiology and inform the mechanisms of action of neuromodulation treatments, such as rTMS.

BackgroundThe Trail Making Test (TMT) is a widely used instrument for assessing executive functions due to its sensitivity. But, its traditional scoring, based solely on total completion time, limits its specificity by losing the rich behaviour required to complete the task, involving integrating visual search, motor planning and task switching. A computerised implementation of the TMT (cTMT) allows high-resolution cursor trajectories to be recorded, offering access to fine-grained features of the trajectory, while an online administration improves accessibility and statistical power. ObjectiveThis study aimed to extract high-resolution cursor trajectory features from an online cTMT and evaluate their capacity to predict individual differences in core executive functions, such as visual working memory (VWM), inhibitory control and age, using machine learning, as well as validating the feasibility of a fully online data acquisition pipeline as a basis for digital biomarkers. MethodsParticipants completed an online battery comprising the cTMT and three validation tasks: the Change Detection Task (CDT), the Stop-Signal Task (SST) and the Go/No-Go task (GNG). A total of 104 features (26 features x Part A/B x whole-trial/first-10-targets) were extracted from cursor trajectories, including trajectory profiles and segmentation into latent states: Search, Travel and Hesitation. Regression models were trained within a nested Leave-One-Out cross-validation framework with inner 10-fold hyperparameter tuning, feature selection and standardisation applied strictly within folds. Performance was assessed via mean absolute error (MAE), normalised error (MAE/SD) and permutation testing; SHapley Additive exPlanations (SHAP) were used to characterise feature importance. ResultscTMT features strongly predicted age across all models (p < .001), with MAEs roughly one-third lower than the targets dispersion, driven predominantly by distance-based "circuitousness" metrics from both parts. GNG accuracy and c-coefficient were both significantly predicted, but with a dissociated pattern: accuracy was best explained by Part B (alternation) metrics, whereas the c-coefficient was almost exclusively predicted by Part A (simple sequencing) metrics. SST response time (SSRT) was not significantly predicted by any model. VWM, characterised by the mean Cowan s K, was significantly predicted mainly by the more complex models, and involving state transitions and search phases in both Part A and B. ConclusionsMoving beyond completion time, cursor trajectory dynamics from an online cTMT provide a rich behavioural signal for predicting age, VWM capacity and distinct aspects of inhibitory control. The dissociation between Part A and Part B predictors supports differentiated cognitive processes within the TMT and positions the cTMT as a scalable, portable digital biomarker with promise for computational psychiatry and personalised neuropsychology.