NeuroImage: Clinical

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.

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.

Background: Multiple sclerosis subpial cortical lesions are prevalent and associated with disability but difficult to detect on MRI. Inversion recovery susceptibility weighted imaging with enhanced T2 weighting (IR-SWIET) and T1/T2 ratio imaging have been proposed for cortical lesion detection on 3 tesla (T) MRI. Objectives: To assess cortical lesion detection using IR-SWIET and T1/T2 ratio imaging. Methods: Cortical lesions were identified in 20 persons with MS (pwMS) independently on six image sets: T1 weighted (w) magnetization prepared 2 rapid acquisition gradient echoes (MP2RAGE) + T2w fluid attenuated inversion recovery (FLAIR) alone or with T1/T2, IR-SWIET single acquisition (x1), average of two (x2) or median of four (x4) acquisitions, or denoised single acquisition (IR-SWIETx1DN). In 10 additional pwMS with 7T-based cortical lesion segmentations, lesions were identified on MP2RAGE + FLAIR + IR-SWIETx1DN. Results: Median subpial lesions identified on MP2RAGE + FLAIR was 0 (interquartile range (IQR) 2) vs 0 with T1/T2 (IQR 1, p=0.07), 1 with IR-SWIETx1 (IQR 6, p=0.42), 5 with IR-SWIETx2 (IQR 5, p=0.008), 4 with IR-SWIETx4 (IQR 6, p=0.008), and 4 with IR-SWIETx1DN (IQR 6, p=0.008). Versus 7T, IR-SWIETx1DN detected subpial lesions with similar sensitivity to IR-SWIETx2. Conclusions: IR-SWIET, but not T1/T2, improves subpial cortical lesion detection. Denoising may be an efficient and sensitive alternative to multi-acquisition averaging.

Paramagnetic rim lesions are a subset of focal white matter lesions specific to multiple sclerosis that are chronically inflamed and are associated with increased tissue injury, brain atrophy, and clinical disability. The molecular mechanisms linking paramagnetic rim lesions to these progressive biological outcomes remain unclear. Glutamatergic dysregulation has been hypothesized as a mechanism of multiple sclerosis progression potentially via excitotoxicity, but lesion-specific involvement is unknown. Here, 7T MRI was used to investigate glutamate-related metabolic alterations in paramagnetic rim lesions. Glutamate-weighted chemical exchange saturation transfer, together with T1 mapping and quantitative susceptibility mapping, was evaluated across paramagnetic rim lesions, non-paramagnetic rim lesions, and normal-appearing tissues in participants with multiple sclerosis (n=20) and healthy controls (n=11). Glutamate-weighted chemical exchange saturation transfer contrast was significantly higher in paramagnetic rim lesions compared to non- paramagnetic rim lesions (+10.7%) and normal-appearing white matter (+13%), while no differences were observed in normal-appearing tissue between multiple sclerosis and healthy controls. Additionally, reduced glutamate-weighted chemical exchange saturation transfer contrast in normal-appearing tissues was associated with worse motor and dexterity performance, linking observed metabolic abnormalities to clinical disability. These results identify a distinct metabolic phenotype of paramagnetic rim lesions marked by elevated glutamate-weighted signal consistent with localized excitotoxic stress. This work also implicates lesion-specific glutamatergic dysregulation in paramagnetic rim lesion-related neurodegeneration and demonstrates the potential of metabolic MRI to probe pathogenic mechanisms in multiple sclerosis.

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.

Background: Storage symptoms after stroke-isolated urgency, urgency with frequency, and isolated frequency are common but traditionally attributed to a single overactive bladder mechanism via suprapontine disinhibition. However, clinical heterogeneity in symptom presentation suggests distinct underlying mechanisms. We aimed to characterize the neural substrates of three storage symptom subtypes after stroke using comprehensive lesion-symptom mapping. Methods: We prospectively evaluated 1,498 consecutive subacute stroke patients admitted for inpatient rehabilitation (1,105 men, 73.8%; median age 61 years). Storage symptoms were classified into three subtypes: isolated urgency (n=109), urgency with frequency (n=32), and isolated frequency (n=19). Multivariable logistic regression models with Bonferroni correction identified independent predictors across demographic, clinical, white matter hyperintensity (WMH), brain atrophy, and lesion location variables. Results: The three subtypes demonstrated largely distinct sets of independent predictors. The left genu of the corpus callosum (aOR=20.06, 95% CI 7.78-51.74, P<0.001) and the inferior frontal gyrus (aOR=3.48, 95% CI 1.81-6.67, P<0.001) were independently associated with isolated urgency and survived Bonferroni correction, together with a right IFG-insula synergistic effect (OR=21.46, 95% CI 10.49-43.88, P<0.001). Urgency with frequency was associated with a broad fronto-cingulate network-the IFG (aOR=11.45, 95% CI 3.10-42.33, P<0.001, surviving Bonferroni correction) and the ACC (aOR=11.53, 95% CI 2.40-55.49, P=0.002) with diffuse right-hemisphere dominance, older age and brain atrophy. Isolated frequency was associated with anterior corona radiata involvement (aOR=5.46, 95% CI 1.92-15.54, P=0.002) and male sex (aOR=10.62, 95% CI 1.36-82.98, P=0.024), though none reached the strict Bonferroni threshold. Conclusions: These findings identify three mechanistically distinct post-stroke storage symptom subtypes with separable neural substrates, lateralization profiles, and clinical determinants. The triple dissociation across subtypes supports a discrete pathway model over the traditional unitary OAB framework, providing a neuroanatomically grounded basis for subtype-stratified treatment Keywords: storage symptoms; subacute stroke; hemispheric lateralization; structural synergy; lesion-syndrome mapping

Background and PurposeBrain arteriovenous malformations may be associated with atypical language lateralization, but whether individual variation in task-derived hemispheric dominance is reflected in time-varying intrinsic connectivity is unclear. We examined task-based language lateralization and resting-state dynamic connectivity in unruptured, untreated brain arteriovenous malformations and controls. MethodsThirty patients and 23 controls underwent language-task fMRI and resting-state fMRI. Language lateralization indices were derived from threshold-swept activation maps. Resting-state time series were modeled with hidden Markov models and canonical clustering across three atlases, yielding fractional occupancy, mean dwell time, and flexibility. The prespecified primary analysis used Schaefer-100 with four canonical states. ResultsPatients showed reduced leftward language lateralization compared with controls, most clearly in left-sided lesions. Canonical dynamic summary metrics did not differ robustly between groups after false-discovery-rate correction. Within-group partial least squares models showed that language lateralization was associated with dynamic state metrics in both groups. In patients, stronger leftward lateralization was linked mainly to flexibility; in controls, it was linked more consistently to longer dwell time. Exploratory perfusion analysis did not show a clear relationship between gross hemispheric perfusion asymmetry and language lateralization. ConclusionsDynamic resting-state features tracked individual variation in language lateralization despite limited group-level differences in dynamic state usage. These findings provide proof-of-concept evidence of brain-behavior coupling rather than an AVM-specific dynamic biomarker or a validated clinical prediction tool.

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.

Background: People with chronic stroke retain the capacity to learn new motor skills, yet how preserved motor learning is expressed during practice remains incompletely understood. Sequence learning provides a useful model for examining these within-session learning dynamics and their neural basis after stroke. Objective: To characterize a temporally resolved behavioral phenotype of motor sequence learning in chronic stroke and establish its neural context using task-based functional MRI (fMRI). Methods: Twenty-four individuals with chronic stroke and 14 neurologically healthy controls performed a bimanual force-tracking sequence-learning task during functional MRI. Performance convergence was defined as the sequence-specific reduction in the accuracy difference between the paretic and less-affected hands across practice. Neural activity was evaluated using whole-brain, region-of-interest, and functional-connectivity analyses following preprocessing tailored to structurally heterogeneous stroke lesions. Results: Stroke participants demonstrated significant performance convergence despite persistent motor impairment, indicating preserved expression of sequence learning during practice that was not detected by conventional behavioral measures. Lesion-aware fMRI identified robust task-related activation and preserved stage-dependent modulation within cerebellar, premotor, and striatal learning networks, together with reduced bilateral putaminal activity after stroke. However, preregistered analyses found no reproducible associations between individual differences in performance convergence and learning-related activation or functional connectivity. Conclusions: Performance convergence provides a sensitive, temporally resolved behavioral phenotype of preserved motor sequence learning in chronic stroke that complements conventional endpoint measures. Together, performance convergence and task-based functional MRI provide a framework for investigating individual differences in motor learning capacity and their implications for rehabilitation responsiveness.

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: 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.

Hand dexterity impairment is a major contributor to long-term disability after acquired brain injury, yet the white matter substrates supporting residual dexterity remain incompletely understood. We investigated diffusion MRI markers of hand dexterity in individuals with chronic stroke (n = 9) and traumatic brain injury (TBI; n = 8) using complementary tract-specific and whole- brain approaches. Partial least squares regression (PLSR) was used to evaluate the cross-validated predictive relevance of bilateral corticospinal tract (CST) diffusion and tractometry features, while quantitative anisotropy (QA)-based correlational tractography was used to identify distributed white matter pathways associated with dexterity performance measured using Box and Block Test (BBT) and MusicGlove Dexterity Test(MGDT). In stroke, CST features predicted BBT performance (Q2 = 0.69, r = 0.85, permutation p = .010) and, more modestly, MGDT performance (Q2= 0.22, r = 0.72, permutation p = .008). In contrast, CST-based models showed no predictive relevance for dexterity outcomes in TBI. Whole-brain connectometry revealed that better dexterity after stroke was associated with greater QA across distributed pathways extending beyond the CST, including commissural, association, and projection fibers. Box and Block Test performance was prominently associated with callosal and cingulum-related pathways, whereas MusicGlove performance showed greater representation of CST and projection pathways. In TBI, significant connectometry findings for the BBT similarly implicated distributed commissural and association pathways, whereas no significant pathways were identified for the MusicGlove test. Together, these findings suggest that the structural correlates of hand dexterity extend beyond the CST and vary across dexterity measures and injury populations. Although preliminary given the small cohorts, the complementary tractometry and connectometry findings support a network-level characterization of residual hand function after acquired brain injury and motivate validation in larger cohorts.

Accurate stroke lesion segmentation is essential for large-scale neuroimaging studies, yet manual delineation remains labor-intensive, and existing automated methods often struggle to generalize across imaging protocols and stages of recovery. We developed MAESTRO, a deep learning framework for automated lesion segmentation across the stroke recovery continuum using T1-weighted (T1) MRI alone. We hypothesized that combining a transformer-based architecture with an image augmentation strategy would improve segmentation accuracy and robustness under heterogeneous imaging conditions. T1 MRI scans and expert-traced lesion masks from 955 stroke participants across 33 international cohorts were used to train and evaluate MAESTRO within the open-source nnU-Net framework. Performance was evaluated on a held-out test set using spatial and volumetric agreement metrics. An exploratory human-in-the-loop (HITL) evaluation compared correction of MAESTRO-generated segmentations with manual tracing from scratch. MAESTRO achieved the strongest performance across several evaluated model configurations, providing the most accurate lesion localization and lesion volume estimates (median Dice = 0.686; Pearson r = 0.861; ICC = 0.792). Segmentation performance was sensitive to lesion size and stroke chronicity but remained robust across diverse imaging conditions. Additionally, using a HITL workflow to correct MAESTRO segmentations reduced annotation time by 47.4% compared to manual tracing while improving accuracy relative to both automated and manual workflows. MAESTRO is publicly available to enable robust, automated stroke lesion segmentation from T1 MRI. When combined with human review and correction, MAESTRO offers a practical approach for generating standardized, high-quality lesion annotations, helping reduce a major practical barrier to large-scale stroke imaging studies.

Background: The Boston Criteria v2.0 represent the gold standard for diagnosing Cerebral Amyloid Angiopathy (CAA), but their application is currently precluded in mixed small vessel disease (SVD), where deep and lobar hemorrhages coexist. The aims of this study are: (i) to determine which cerebrospinal fluid (CSF) biomarker (A{beta}42, A{beta}40, A{beta}42/40 ratio) is the best candidate to support the CAA diagnosis; (ii) to define a data-driven cut-off, and (iii) to explore if a biomarker-integrated classification significantly improves the phenotypical concordance with the suspected predominant SVD (CAA vs. arteriosclerosis). Methods: We analyzed data from a retrospective multicenter cohort of patients with suspected CAA, defined as probable CAA (Boston criteria v2.0) but allowing deep hemorrhagic lesions, and with available CSF biomarkers. We visually quantified MRI-visible SVD markers (e.g., cerebral microbleeds [CMB], cortical superficial siderosis [cSS], lacunes) and their association with MRI-visible SVD features. We employed a Gaussian Mixture Model (GMM) to identify a data-driven threshold for amyloid positivity (A+). Then, we compared the prevalence of MRI-visible manifestations of SVD between subgroups applying different frameworks, namely the current MRI-based classification (probable CAA vs. mixed SVD) and a CSF biomarker-integrated classification (A+ vs. A-). Results: We enrolled 121 patients (age: 72 [66-77] years; 60% probable CAA, 40% mixed SVD with suspected CAA). The CSF A{beta}42/40 ratio showed a bimodal distribution and consistent associations with all CAA-specific radiological features. The CSF biomarker-integrated reclassification, particularly using the GMM cut-off, significantly improved the distinction between subgroups regarding CAA- and arteriosclerosis-related MRI features (e.g., cSS presence: probable CAA vs. mixed SVD: aOR=2.84 [95%CI 1.27-6.39], p=0.011; A+ vs. A-: aOR=12.68 [95%CI 4.31-37.32], p<0.001; deep lacunes presence: probable CAA vs. mixed SVD: aOR=0.20 [95%CI 0.08-0.50], p<0.001; A+ vs. A-: aOR=0.04 [95%CI 0.01-0.11], p<0.001). Notably, patients classified as A+ never demonstrated more than four deep CMBs. Discussion: A CSF biomarker-integrated classification may improve the classification of CAA compared with the current MRI-based framework. These findings are cohort-specific and would benefit from further validation, especially with a neuropathological reference. Still, these results support a future transition toward an integrated biological-radiological framework, which may refine in vivo CAA diagnosis, particularly in mixed SVD.

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: The subplate is a transient fetal brain compartment that provides an early foundation for downstream cerebral development. Congenital heart disease (CHD) alters fetal circulation and cerebral substrate delivery, but its impact on subplate development and whether resulting alterations relate to later neurodevelopmental outcomes remain unclear. Methods: In this retrospective observational cohort study, We used fetal MRI to quantify whole-brain, lobar, and regional (17 bilateral cortical regions) subplate volume and thickness to evaluate group differences between 76 fetuses with CHD and 62 typically developing (TD) fetuses scanned between 21-32 weeks of gestation, and estimated individualized deviations from TD developmental trajectories. Associations with fetal hemodynamic indices (substrate delivery score, cerebroplacental ratio [CPR]) and two-year neurodevelopmental outcomes (Bayley Scales of Infant and Toddler Development, N=46 CHD, N=37 TD) were explored. Results: Whole-brain subplate volume was lower in CHD, corresponding to a 5.7% reduction relative to age- and sex-expected values (p=0.003), but this difference was substantially attenuated after accounting for global brain volume (p=0.090). In contrast, regional analyses identified persistent spatially structured deviations beyond global scaling, most consistently involving posterior parietal, occipital and temporal regions, with a left-hemisphere bias in subplate thickness. Normative modelling demonstrated bidirectional regional deviations and increased inter-individual variability in CHD, with extreme subplate volume deviations enriched across 73% of cortical regions (p=0.009). Higher CPR was associated with lower SP thickness deviations, with the association strengthening after accounting for cerebral substrate delivery (p=0.010), although these analyses were exploratory. In CHD fetuses with postnatal follow-up, prenatal subplate deviations showed modest associations with neurodevelopmental outcomes, with right precuneus subplate thickness associated with receptive ({beta}=-11.87, q=0.017) and expressive ({beta}=-14.50, q=0.039) communication on the Bayley, after correction for multiple comparisons. Conclusions: Fetal subplate alterations in CHD are dominated by global reductions in brain growth but also include spatially heterogeneous and individually variable regional deviations beyond global scaling. Exploratory associations with fetal hemodynamics and postnatal neurodevelopment provide hypotheses for future studies investigating the developmental significance of these prenatal alterations.

Background: The primary neuroanatomical site of Huntington-s disease (HD) pathology resides in the striatum and its atrophy identifies important disease progression from HD-ISS Stage 0 to Stage 1. Immune-associated proteins may capture variation in HD that is incompletely represented by markers of neuroaxonal injury. Objectives: To determine whether cerebrospinal-fluid myeloperoxidase contributes information about striatal volume loss beyond genetic disease burden and neurofilament light. Methods: Cross-sectional data from 88 persons with HD were analyzed. Cerebrospinal-fluid myeloperoxidase and neurofilament light were measured with a nucleic acid-linked immunosandwich assay. Normalized putamen volume was derived from structural magnetic resonance imaging. Linear regression adjusted for genetic disease burden and sex. Results: Higher neurofilament light was associated with smaller normalized putamen volume (standardized {beta} = -0.322, (P=.0066)). Higher myeloperoxidase was associated with larger normalized putamen volume after adjustment for genetic disease burden, sex, and neurofilament light (standardized {beta} = 0.183, (P=.0386)). Adding myeloperoxidase increased explained variance in striatal loss. Conclusions: Cerebrospinal fluid myeloperoxidase contributed modest incremental information about striatal volume in this cross-sectional sample. Independent longitudinal studies are needed to determine its biological source, temporal behavior, and potential biomarker value. Findings advance efforts to characterize multicomponent biological markers of HD.

Retinitis pigmentosa (RP) progressively deprives the retina of input, but whether the responsiveness of the visual cortex declines in parallel, remains preserved, or increases through compensatory gain remains unclear. Indeed, a weaker visually evoked response cannot, on its own, distinguish these possibilities, since it is equally compatible with a passively degraded input and with an actively recalibrated cortex. We combined spatially resolved steady-state visual evoked potentials (SSVEPs), which index stimulus-driven activity, with transcranial magnetic stimulation combined with electroencephalography (TMS-EEG), which probes cortical reactivity independently of vision, in patients with RP and in healthy controls. Nine patients (PTs) with RP (five women, age range 28 to 69 years) and nineteen sex-, age-, and handedness-matched healthy controls (thirteen women, mean age 42.6 years) were tested. They underwent SSVEP recordings to stimuli presented at three eccentricities (central, intermediate, peripheral) and single-pulse TMS-EEG over the left and right occipital cortex and, as a non-visual control site, the dominant motor cortex. We quantified SSVEP amplitude and phase at 12 Hz, early TMS-evoked potentials, oscillatory power, inter-trial phase synchrony, and functional connectivity and graph-theoretical network measures derived from the weighted phase lag index. SSVEP amplitude followed the expected central-to-peripheral gradient: PTs were comparable to healthy controls at the center, reduced but still above their own resting baseline at intermediate eccentricity, and no longer distinguishable from baseline in the periphery; phase differed from controls in a quarter of the central and half of the intermediate sectors. Occipital stimulation elicited a larger early negative deflection after left-hemisphere stimulation in PTs compared to controls, a stronger beta-band event-related spectral perturbation after stimulation of either hemisphere, and stronger, more efficiently distributed post-stimulus connectivity, despite comparable pre-stimulus connectivity, resting motor threshold, and most early evoked components. The pattern was site- and hemisphere-specific: left occipital stimulation produced widespread, mainly contralateral effects; right occipital stimulation a more circumscribed ipsilateral one, and motor cortex stimulation showed altered alpha-band activity without the bilateral occipital beta effect. Together, these results show that progressive retinal deafferentation in RP does not produce a parallel decline in cortical responsiveness. Visually driven activity weakens with eccentricity, while direct cortical perturbation reveals preserved and, at selected sites, enhanced reactivity. This dissociation is consistent with a homeostatic increase in cortical gain rather than a uniform loss of cortical function, and indicates that the deafferented cortex retains, and in places strengthens, its capacity to respond as retinal input deteriorates.

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 Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a poorly understood, debilitating multisystem condition. Converging evidence implicates impaired cellular bioenergetics, neuroinflammation and defective neurovascular coupling that may manifest as "virtual hypoxia" only under physiological stress. Methods We performed a single-session multimodal 3T MRI study combining brain volumetry, arterial spin labelling (ASL) and multivoxel proton magnetic resonance spectroscopy under normoxia and two controlled hypoxic challenges (oxygen saturation 87 {+/-} 3%) in 26 ME/CFS patients and 27 age- and sex-matched healthy controls. Results After intracranial-volume normalization, patients showed a reduced brainstem volume (1.46 0.14 vs. 1.55 {+/-} 0.18 % of eTIV; p = 0.013, FDR-p = 0.039), whereas deep grey matter and whole-brain parenchymal fraction did not differ between groups. Whole-brain cerebral blood flow (CBF) rose under hypoxia in both groups (controls +4.8 {+/-} 13.0%, patients +3.7 {+/-} 11.7%), with greater initial inter-individual variability in patients (patient-to-control variance ratio up to 6.94; FDR-p = 0.001). Thalamic lactate-to-creatine (Lac/tCr) ratios increased with hypoxia in controls (FDR-p = 0.028) but were already elevated at normoxia in patients (0.171 vs. 0.135; FDR-p = 0.021) and did not rise further (FDR-p = 0.38). In exploratory analyses, patients showed exaggerated inverse coupling between thalamic total N-acetylaspartate (tNAA/tCr) and white-matter CBF. Conclusions These findings provide in vivo evidence of impaired neuro-metabolic and vascular adaptive capacity in ME/CFS, supporting the virtual hypoxia hypothesis and highlighting candidate imaging markers for stratification that warrant validation.