NeuroImage: Clinical

Background: Quantitative susceptibility mapping (QSM) exhibits phase cancellation between paramagnetic (e.g. iron) and diamagnetic (e.g. myelin/protein) sources, obscuring microstructural lesion heterogeneity in multiple sclerosis (MS). We evaluated whether biophysical {chi}-separation identifies clinically meaningful lesion phenotypes and whether reduced echo sampling preserves microstructural sensitivity. Methods: In this cross-sectional study of 183 people with multiple sclerosis (PwMS), we analyzed 3327 quality-controlled white matter lesions using 3T MRI with a five-echo gradient-recalled echo sequence (GRE5) and a subsampled two-echo dataset (GRE2). A hybrid framework combining unsupervised clustering on whole-lesion paramagnetic ({chi}para) and diamagnetic ({chi}dia) features with rule-based compartmental edge-core gradient assignment resolved MS lesion phenotypes. Intralesional microstructural properties were evaluated using linear mixed-effects models. Multivariable linear regressions assessed associations with physical disability (Expanded Disability Status Scale, EDSS; n = 158), cognitive processing speed (Symbol Digit Modalities Test, SDMT; n = 79), and disease duration (DD; n = 161), with sensitivity models adjusting for total lesion volume, count, or DD. Results: The framework identified four reproducible lesion phenotypes (Adjusted Rand Index = 0.924): Type 1 (22.7%; preserved {chi}dia), Type 2 (32.9%; high {chi}para without positive edge-core gradient), Type 3 (35.8%; attenuated {chi}dia), and Type 4 (8.6%; high {chi}para with a positive edge-core paramagnetic gradient). Higher EDSS was selectively associated with more negative signed {chi}dia within Type 4 lesions (whole: {beta} = -0.37, q = 0.020; core: {beta} = -0.37, q = 0.006; edge: {beta} = -0.34, q = 0.030) and Type 2 edge ({beta} = -0.33, q = 0.044). Type 4 core associations remained robust across sensitivity models adjusting for total lesion volume ({beta} = -0.35, q = 0.004), total lesion count ({beta} = -0.37, q = 0.008), and DD ({beta} = -0.32, q = 0.033). Abbreviated GRE2 attenuated Type 4 compartmental associations to non-significance (all q greater than 0.05; core: {beta} = -0.20, q = 0.215). Conclusions: Quantitative {chi}-separation identified four internally stable susceptibility-defined MS lesion phenotypes, revealing disability-associated tissue heterogeneity beyond total lesion burden. Higher EDSS was associated with more negative diamagnetic measures within Type 4 cores after adjustment for lesion burden, pointing toward complex intralesional non-myelin tissue remodeling or reactive astrogliosis. Two-echo subsampling may influence compartment-specific clinical associations. By uncoupling susceptibility sources, {chi}-separation provides a quantitative framework for characterizing disability-associated lesion heterogeneity.

White matter hyperintensities on brain magnetic resonance imaging are established markers of cerebral small vessel disease and typically associate inversely with brain volume in the general population, reflecting irreversible tissue loss. In Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy, a monogenic small vessel disease caused by NOTCH3 cysteine-altering mutations, white matter hyperintensities may instead reflect tissue water accumulation and perivascular space dilation rather than net structural damage. Whether this distinct pathophysiological relationship is detectable at population level among carriers of NOTCH3 cysteine-altering variants without clinically manifest disease remains unknown. We conducted a cross-sectional neuroimaging study using UK Biobank data acquired between 2014 and 2023. Among 44,943 participants with complete brain magnetic resonance imaging data (mean age 64 years +/- 8 years), 96 carried heterozygous NOTCH3 cysteine-altering variants within epidermal growth factor-like repeat domains 7 to 34 and 44,847 were non-carriers. White matter hyperintensity volume was automatically quantified and normalized to total intracranial volume. Brain parenchymal fraction was defined as combined gray and white matter volumes divided by total intracranial volume. Lacunes were manually assessed in all carriers. Linear regression and generalized additive models examined the association between white matter hyperintensity volume and brain parenchymal fraction stratified by genotype, adjusting for age, sex, lacune count, and vascular risk factors. NOTCH3 variant carriers showed markedly higher normalized white matter hyperintensity volume than non-carriers (0.83% versus 0.36%; P<10^-8) but only marginally higher brain parenchymal fraction (81.1% versus 80.5%; P=0.03). In non-carriers, white matter hyperintensity volume was inversely associated with brain parenchymal fraction (beta=-0.116% per 1% increase; P=3.10^-6). In contrast, NOTCH3 variant carriers demonstrated a positive association (beta=+0.51%; P=0.019), strengthened after adjusting for lacune count (beta=+0.61%; P=0.006). A significant genotype-specific interaction confirmed this divergence (P=0.036), persisting across age groups and after vascular risk factor adjustment. NOTCH3 cysteine-altering variant carriers identified at population level exhibit a fundamentally distinct white matter hyperintensity-brain volume relationship compared with non-carriers, consistent with lesions reflecting tissue water accumulation rather than irreversible structural loss at this early, predominantly preclinical disease stage. These findings establish that genetic context modifies neuroimaging biomarker interpretation in cerebral small vessel disease and underscore the need for genotype-aware approaches when evaluating white matter hyperintensities as markers of disease severity or progression.

Focal lesions are common after complicated mild-to-severe traumatic brain injury (cmsTBI) in children, yet it is unclear whether the location of focal damage relates to cognitive outcome beyond overall lesion burden. Combining 13 international cohorts through the ENIGMA Pediatric cmsTBI working group, we conducted voxelwise lesion-symptom mapping (VLSM) to test whether focal lesion location relates to cognitive outcome, and how this compares with overall lesion volume. From 357 patients with imaging that passed quality assurance, 67 had a focal lesion visible on T1-weighted MRI along with at least one performance-based cognitive outcome (D-KEFS Trail Making conditions and WISC/WAIS Coding). We tested whether lesion location related to cognitive outcome using VLSM, adjusting for age, sex, and time since injury, and separately tested total lesion volume as a predictor of each outcome. Lesions in the right middle frontal gyrus were associated with poorer performance on number sequencing (D-KEFS Trail Making condition 2), a timed visuomotor sequencing task (false discovery rate corrected). In separate regression analyses, greater lesion volume was associated with poorer number-letter switching and motor speed. The switching association remained significant after adjusting for injury severity, whereas the motor-speed association did not. In the largest lesion sample assembled in pediatric cmsTBI to date, focal lesion location and injury burden index separable contributions to cognitive outcome, with number sequencing linked to focal prefrontal damage and switching and motor speed to overall lesion volume, underscoring the value of precise lesion characterization for large-scale multi-site neuroimaging.

Background: Behavioral variant frontotemporal dementia (bvFTD) is clinically defined by progressive changes in personality, executive function, and language, yet the structural neural correlates of symptom severity remain unclear. This study aimed to assess the association between clinical findings and neuroimaging biomarkers. Methods: We included 87 patients with bvFTD. Clinical functioning was covering behavior and language. Spearman rank correlations were used to assess univariate associations, and Bonferroni correction was applied for multiple comparisons. Principal component analysis (PCA) was conducted on regional volumes, and multivariable logistic regression was used to model high behavioral impairment (FBI total [&ge;]30), adjusting for age, sex, and education. Results: No individual regional volume was significantly correlated with clinical scores after Bonferroni correction (all adjusted p>0.05), and PCA-derived imaging components failed to predict behavioral severity in multivariable models. Age emerged as the only significant predictor (OR=1.11 per year; p=0.009). Model discrimination was modest (AUC=0.735) and did not improve with the inclusion of imaging features (p=0.453 vs. demographics-only model). Conclusions: In this bvFTD cohort, structural volumes of key frontotemporal and perisylvian regions did not predict behavioral or language impairments after correction for multiple comparisons. These findings show the limitations of regional volumetric analysis in isolation and stress the need for network-based, multimodal, and longitudinal approaches.

Background and Objective: For their acceptance as endpoints in clinical trials, biomarkers and clinical outcome assessment (COA) measures should show reliability by being reproducible (precise) and responsive to change. We evaluated precision and responsiveness of MRI-derived brain volume metrics and various COAs in ceroid-lipofuscinosis, neuronal-3 (CLN3) disease. Methods: This longitudinal observational study (NCT03307304) included 44 individuals with CLN3-related disease (ages 0.5-29.1 years, 48% female). Brain volumetric measures were computed using SynthSeg-v2.0 from T1-weighted 3D MPRAGE images acquired at 3T (Median [Q1, Q3] total MRI follow-up duration from baseline: 2.04 [0.00, 3.69] years). Compartmental tissue volumes were normalized to a model-adjusted total intracranial volume and scaled to the tissue-specific volume fraction expected in healthy adolescent brains to extract measures of brain atrophy. COAs included the Vineland Adaptive Behavior Scales, verbal IQ, and the Unified Batten Disease Rating Scale (UBDRS). Analysis of linear mixed-effects models included only CLN3 participants with syndromic presentation, having three or more visits per measurement to estimate slope, its relative standard error (RSE), and the minimum inter-visit interval (Tmin) for statistically significant progression for each participant. Tmin to detect progression in 75% of the population (Tmin,75%) was computed for each metric. Results: Among brain volumetric measures, brain parenchyma volume (BPV) and gray matter volume (GMV) were the most precise and responsive metrics. BPV showed an overall intra-individual decline with age of -1.32%/year (95% CI: -1.64% to -0.99%), low RSE of 12.5%, and short Tmin,75% of 0.85 years (95% CI: 0.47-1.24). Amongst COAs, the UBDRS Clinical Global Impression (CGI) score was the most precise and responsive with an overall intra-individual increase of 1.26 units/year (95% CI: 1.03-1.49), RSE of 24.10%, and Tmin,75% of 2.56 years (95% CI: 1.73-3.46), though with lower precision (RSE higher) and lower responsiveness (Tmin,75% longer) than BPV. Discussion: MRI-derived metrics, in particular BPV and GMV, detected change in brain atrophy with high precision and responsiveness suggesting that they would be informative for evaluating potential neuroprotective therapies in CLN3 disease. These findings support incorporating MRI-derived volumetric measurements alongside clinical assessments in future clinical trials in CLN3.

Importance: Brain MRIs are routinely acquired following moderate or severe traumatic brain injury (TBI) because of their high sensitivity for detecting traumatic brain lesions. However, there is no standard framework for their interpretation, and their clinical utility is unproven. Objective: Here, we test whether MRI-based quantification of traumatic brain lesions improves outcome prediction relative to the best tools currently available to clinicians. Design, Setting and Participants: We analyzed hemorrhagic contusions and axonal injury in four prospective studies of moderate or severe TBI, validating results in a fifth held-out dataset. Exposure: Contusion volume was measured via manual segmentation. Axonal injury volume was quantified with diffusion tensor imaging, by measuring the volume of skeletonized fractional anisotropy significantly lower than that of healthy controls. Main Outcomes and Measures: Functional outcomes were assessed at 6 months with the Glasgow Outcome Scale-Extended; values [&le;] 4 were considered unfavorable. Results: Among 201 patients with MRI (mean age: 41, median Glasgow Coma Scale (GCS) score on admission: 7, MRI obtained median 14 days post-injury), MRI-measured contusion volume discriminated outcomes better than CT Marshall score (AUC 0.81 vs 0.64; p=0.001), and remained associated with unfavorable outcomes controlling for multiple commonly-measured clinical variables. Quantitative axonal injury volume discriminated outcomes better than manual MRI grading (AUC 0.82 vs 0.62; p<0.001) and remained associated with unfavorable outcomes independent of other clinical predictors. The prognostic discrimination of traumatic lesion volumes was not improved by accounting for the location or normative connectivity of either lesion type. In a multivariate model, contusion and axonal injury volumes were independently predictive, with age-dependent volume thresholds for 90% probability of unfavorable outcome, and strong discrimination in an external cohort (N=27; AUC 0.83, p<0.001). Replacing all CT-based measures with MRI lesion volumes in the IMPACT model significantly improved out-of-sample prognostic performance (AUC 0.85 vs 0.64; p<0.05). Conclusions and Relevance: MRI-based lesion quantification improves prognostic discrimination relative to measures currently available to clinicians treating patients with TBI. Global functioning at 6-months is driven more by the volume than the location or connectivity of traumatic lesions. These findings support integrating MRI-based lesion quantification into clinical workflows and updated TBI classification frameworks.

Disorders of consciousness (DoC) are characterised by marked reductions in cerebral glucose metabolism, but the specific cellular and neurochemical processes driving this impairment remain unclear. To elucidate these mechanisms, a multimodal imaging approach combining [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) and magnetic resonance spectroscopy (MRS) was applied to the posterior medial cortex (PMC) in 15 DoC patients and 14 healthy controls. Regional FDG metabolic index (FDG-MI) values and MRS concentration estimates of glutamate plus glutamine (Glx), {gamma}-aminobutyric acid (GABA+), total N-acetylaspartate (tNAA), total creatine (tCr), and total choline (tCho) were compared between groups and evaluated against Coma Recovery Scale-Revised (CRS-R) scores at baseline and follow-up (mean 127 days). Patients demonstrated reductions within the PMC in Glx, tCr, and tNAA concentrations, as well as a reduced Glx/GABA+ ratio. Local FDG-MI was substantially reduced in patients and correlated positively with tNAA and tCr. Furthermore, baseline tCho concentrations positively predicted long-term clinical recovery, as indexed by changes in CRS-R scores at follow-up. These findings suggest that macroscopic glucose hypometabolism in DoC may be linked to disrupted intracellular mitochondrial energy production pathways and a shift towards relative synaptic inhibition in the PMC. Moreover, the association between choline levels and behavioural recovery may point to the relevance of retained structural synthesis capacity for functional outcomes.

Background: Autism spectrum disorder (ASD) is neurobiologically heterogeneous, and group comparisons may mask effects confined to subgroups. We tested whether distinct biotypes exist within ASD using unsupervised clustering of multimodal MRI. Methods: We analyzed 149 participants with ASD and 129 typically developing (TD) controls from the Autism Brain Imaging Data Exchange II (6 sites; age 5 to 64 years). Site-harmonized features comprised free water (FW), tissue anisotropy and diffusivity, diffusion tensor image analysis along the perivascular space (DTI-ALPS), cerebrospinal fluid (CSF) volumes and exploratory resting-state regional homogeneity. ASD participants were clustered with k-means using global (7 features) and regional (17 features) sets, with robustness tested by permutation and two further algorithms. TD participants were projected post hoc to test specificity. A composite imaging score was related to Social Responsiveness Scale (SRS) subscales, symptom severity and IQ using partial correlations with false discovery rate correction. Results: Clustering identified an elevated free-water (EFW) biotype comprising approximately 10% of ASD participants, defined by markedly increased FW (d = +4.91 versus remaining ASD participants), reduced tissue anisotropy, reduced DTI-ALPS and enlarged ventricles. It was recovered across feature sets and algorithms (permutation p < .0001) and departed from TD norms, unlike the remaining ASD participants. The composite score correlated with social-perceptual and communicative SRS subscales, most strongly social awareness (r = +0.253, q = .026), but not with symptom severity or IQ. FW related to social motivation in children and adolescents (r = +0.287, q = .037) but not adults. Limitations: Each person was scanned once, so we cannot tell whether these brain differences cause social difficulties or how they change with age. The subgroup was small, clinical data were incomplete, the sample was mostly male with a wide age range, and the findings await confirmation in an independent group. Free water can reflect inflammation, swelling or tissue loss, so its biological meaning remains uncertain. Conclusions: We identify an ASD subgroup defined by extracellular fluid excess and altered white matter that is associated with greater social difficulties. If replicated, this signature may help stratify autistic individuals in mechanistic studies and clinical trials.

In aphasia, variability in lesion location and post-stroke network reorganization complicates efforts to identify the regions that support semantic versus phonological processing. In prior work, researchers have often examined these domains in separate patient cohorts, further limiting direct comparison of their neural substrates within aphasia. To address this gap, we investigated the degree of overlap and specialization within semantic and phonological networks in adults with and without aphasia and examined how neural activity relates to task performance and lesion profiles. Sixteen neurologically healthy adults and 15 participants with aphasia following left hemisphere stroke completed adaptive Semantic Matching and Rhyme Judgment tasks during functional near-infrared spectroscopy (fNIRS) recording. Changes in oxyhemoglobin and deoxyhemoglobin were measured within regions of interest, and activation was related to standardized task performance and damage to left ventral and dorsal language pathways in participants with aphasia. Controls showed largely distinct activation patterns consistent with prior fMRI findings: Semantic Matching preferentially recruited ventral stream regions, particularly left temporal cortex, whereas Rhyme Judgment more strongly recruited dorsal regions, including left inferior frontal and inferior parietal cortex. Participants with aphasia showed greater inter-individual variability and no clear group-level segregation of dorsal and ventral activity. Better Semantic Matching performance was associated with less left ventral stream damage and greater left dorsal activation, whereas better Rhyme Judgment performance was associated with lower right hemisphere ventral and dorsal activation. These findings suggest that post-stroke language performance reflects residual specialization, lesion-dependent constraints, and flexible recruitment of surviving tissue. Overall, fNIRS shows promise as an alternative to fMRI for language mapping in post-stroke aphasia, although replication in larger samples with more extensive cortical coverage is warranted.

Identifying regional brain atrophy is critical for understanding neurodegenerative disorders. Traditionally, group comparisons rely on frequentist statistics, utilising $p$-values and point estimates that offer limited characterization of uncertainty. Bayesian methods provide an alternative by estimating effect sizes and credible intervals while incorporating prior knowledge and uncertainty. This study evaluated the feasibility of Bayesian hierarchical modelling to assess regional brain atrophy in Progressive Supranuclear Palsy (PSP) and Corticobasal Syndrome (CBS) compared to healthy controls. Participants meeting diagnostic criteria for CBS or PSP, together with healthy controls, were recruited from the Cambridge Centre for Parkinson-plus. Grey matter volume, cortical thickness, and subcortical volumes were derived using FreeSurfer for 210 cortical and 36 subcortical regions defined by the Human Brainnetome Atlas. Participants with PSP were classified into Richardson syndrome (PSP-RS), corticobasal syndrome variant (PSP-CBS), frontal variant (PSP-F), and other presentations (PSP-Other). Bayesian hierarchical ANOVA models with appropriate priors were used to estimate group differences. Regions of practical equivalence (ROPE) were calculated to assess evidence of meaningful group effects. A total of 428 people were included (113 PSP-RS, 30 PSP-CBS, 23 PSP-Other, 19 PSP-F, 81 CBS, and 162 healthy controls). For grey matter volume, there was evidence of whole brain volume loss compared to controls for all disease groups except PSP-Other, which showed evidence of no difference. For cortical thickness, there was evidence of global cortical thinning in CBS compared to controls, but for no other group. For subcortical volume all groups showed evidence of volume loss compared to controls. Patterns of regional atrophy were identified in keeping with previous literature, with the largest effect observed in the left pre-motor thalamus (30\% reduction in CBS). There was greater loss of subcortical volume in PSP-RS compared to other PSP subgroups. Bayesian hierarchical modelling provides a feasible framework for quantifying regional brain atrophy, with interpretable effect size estimates and uncertainty measures. This approach complements conventional statistical methods, particularly in the assessment of rare neurodegenerative and neuropsychiatric disorders.

Background: Secondary progressive multiple sclerosis (SPMS) is traditionally viewed as predominantly neurodegenerative, with limited inflammatory activity. However, chronic active lesions characterised by persistent rim inflammation and gradual expansion may continue to contribute to tissue injury. Objectives: To characterise chronic lesion dynamics in SPMS and determine whether chronic lesion expansion contributes to tissue damage and neurodegeneration. Thirty-one patients with SPMS underwent longitudinal MRI including T1-weighted, FLAIR and diffusion imaging. White matter lesions were manually segmented and chronic lesion tissue expansion (CLTE) was quantified as annualised percentage change. Associations between lesion expansion, mean diffusivity (MD) changes and brain atrophy were assessed using correlation, regression and mixed-effects modelling. Results: CLTE remained prominent, with a mean annual expansion rate of 7.1 +- 4.1%. Expansion substantially exceeded the contribution of newly formed lesions and occurred at rates comparable to relapsing multiple sclerosis. CLTE demonstrated moderate intra-patient clustering (ICC = 0.23). MD increased significantly within lesions during follow-up and was associated with lesion expansion. Chronic lesion expansion was also strongly associated with ventricular enlargement (partial r = 0.72, p < 0.001). Conclusions: Chronic lesion expansion persists in SPMS and represents a major source of tissue injury associated with microstructural degeneration and brain atrophy.

Major depressive disorder (MDD) is marked by disorganization in electrophysiological brain networks, yet it remains unclear whether such disorganization reflects the state-dependent pathological effects or a trait-like vulnerability. We analyzed resting-state electroencephalographic (EEG) delta-beta phase-amplitude coupling (PAC) in two sibling cohorts. Current-MDD families included individuals with current MDD and their currently unaffected siblings (n=36), and remitted-MDD families comprised individuals with remitted MDD and their lifetime unaffected siblings (n=110). Delta-Betahigh PAC was significantly elevated (pcorr[&le;]0.05) over the left-medial frontal region in participants with current MDD relative to their unaffected siblings. In the remitted-MDD families, no significant differences were observed. Regrouping all individuals irrespective of family ties into current MDD, remitted MDD, and never-depressed controls confirmed significantly elevated frontal delta-Betahigh PAC at rest in the current-MDD subgroup compared to other subgroups. Overall, delta-Betahigh coupling reflects the depressive state rather than a trait-like or familial vulnerability.

Major depressive disorder (MDD) is biologically heterogeneous, but how this variability is expressed in the temporal organization of brain activity remains unclear. Using resting-state functional MRI from 2,225 participants, we applied hidden Markov modeling to identify recurrent brain states and quantify their temporal organization. Five states formed a shared repertoire across individuals with MDD and healthy controls, while MDD-related alterations were distributed across states, functional systems, and temporal properties. Within MDD, unsupervised clustering of state occupancy, persistence, and switching delineated two prototype neurodynamic architectures characterized by preferential deployment of ACS/VSS or MAS/DMS states within a preserved state repertoire and broadly similar transition backbone. The architectures showed different within-group brain-symptom associations and symptom-network patterns. Connectome transcriptome analyses organized architecture-state imaging patterns into three transcriptomic state families shared across architectures, and contrasting group-level deployment patterns were recovered in an independent MDD cohort. These findings suggest that MDD heterogeneity is expressed not only through spatially distributed neural alterations, but also through differences in how a common repertoire of recurrent brain states is organized over time.

Abstract Background and Objectives Cerebral microhaemorrhages influence eligibility and monitoring for anti-amyloid therapies. Emerging evidence and expert opinion suggest that subcortical microhaemorrhages may be less closely related to cerebral amyloidosis than lobar lesions and may therefore warrant separate consideration in anti-amyloid treatment eligibility criteria. Using longitudinal MRI data from cognitively unimpaired individuals with preclinical Alzheimer disease in the A4 study, we hypothesised that lobar and subcortical microhaemorrhages would show distinct location-specific patterns of progression and associated risk profiles. Methods We conducted a retrospective longitudinal cohort analysis of centrally assessed MRI data from A4 study participants with at least two evaluable MRI examinations. Baseline and follow-up were defined as the first and last evaluable scans, respectively. Participants were classified according to the anatomical distribution of baseline microhaemorrhages as lobar or subcortical, and subsequent location-specific lesion accumulation was examined. Multivariable logistic regression was used to assess whether baseline lobar and subcortical microhaemorrhage counts were independently associated with the development of additional lobar and subcortical microhaemorrhages. Results Among 1,146 participants followed for a mean of 4.55 years (SD = 1.78), 38 had subcortical-only and 157 had lobar-only microhaemorrhages at baseline. Subsequent lesions preferentially accumulated in the same anatomical compartment. Baseline subcortical microhaemorrhage count was associated with additional subcortical lesions (OR 3.60, 95% CI 2.00-6.47), but not with additional lobar lesions (OR 1.25, 95% CI 0.73-2.15). Conversely, baseline lobar microhaemorrhage count was associated with additional lobar lesions (OR 2.74, 95% CI 2.06-3.64), but not with additional subcortical lesions (OR 1.08, 95% CI 0.77-1.53). White matter hyperintensity burden was associated with subcortical progression, while APOE4 homozygosity and greater cerebral amyloid burden were associated with lobar progression. Systolic blood pressure was directionally positive but not associated with lobar microhaemorrhage accumulation in either analysis. Discussion Our findings support the emerging view that subcortical and lobar microhaemorrhages exhibit distinct longitudinal patterns and associated risk profiles. Longitudinal studies in patients receiving contemporary plaque-clearing therapies are needed to determine whether microhaemorrhages should be considered differently according to anatomical location in treatment eligibility and monitoring guidelines.

C9orf72 encodes a protein that is important for both typical neurodevelopment and homeostatic processes across the lifespan. Pathogenic C9orf72 repeat expansions constitute the most common genetic cause of frontotemporal lobar degeneration (FTLD). Collectively, preclinical models and clinical neuroimaging studies have observed smaller thalamic volumes in C9orf72-associated FTLD, including in asymptomatic young adult C9orf72 repeat expansion carriers across 18 to 30 years old, supportive of potential neurodevelopmental origins. However, it is unknown whether asymptomatic young adult C9orf72 expansion carriers demonstrate volume differences in specific thalamic nuclei, as reported in older asymptomatic carriers and symptomatic patients; if so, normative transcriptomic patterns could reveal relevant neurodevelopmental and/or FTLD-related neurodegenerative processes. This study investigated volumetric MRI differences of the thalamic nuclei in asymptomatic young adult C9orf72 expansion carriers compared to non-carriers, and examined spatial associations with normative thalamic transcriptomics from 8 weeks post-conception through middle age. Young adult C9orf72 expansion carriers (n=72) and non-carriers (n=48) were enrolled in the Frontotemporal Dementia Prevention Initiative across Europe, Canada, and the USA (ages: 18-30 years; sex: 57% female). Spatial associations between young adult thalamic nuclei volumes and normative transcriptomics from the Allen Human Brain Atlas were examined using complementary data-driven and hypothesis-driven approaches. Spatial expression patterns of transcripts of interest were characterized across prenatal and postnatal neurodevelopment using BrainSpan data. Smaller volumes of the pulvinar, mediodorsal, and lateral nuclei were observed in young adult C9orf72 expansion carriers compared to non-carriers. These nuclei showed higher normative expression of transcripts involved concurrently in neurodevelopmental and C9orf72-associated FTLD neurodegenerative processes (including lysosomal, autophagic, and small GTPase functions), and lower normative expression of CALB1, a marker of prenatal human thalamic development. Normative expression of CALB2 (another human thalamic development marker) yielded positive correlations with C9orf72 across prenatal development to adulthood. These findings identify candidate transcripts that may provide insight into the molecular architecture leading to smaller thalamic nuclei volumes in C9orf72-associated FTLD.

Open-source deep learning models promise scalable quantification of MRI-visible perivascular spaces (PVS), an emerging marker of glymphatic dysfunction in Alzheimer's disease (AD). Whether these models remain valid when applied to heterogeneous AD cohorts and preserve ground-truth derived biological associations has not been established. We benchmarked five open-source nnU-Net-based PVS segmentation models (nnU-Net T1, nnU-Net T1+FLAIR, mcPVS-Net, MedNet-PVS, ADNI-PVS-Net) against manual labels in 60 multi-site ADNI-3 participants balanced across cognitively unimpaired, mild cognitive impairment, and AD dementia, and in 12 publicly available scans from the VAscular Lesions object-level and segmentatiOn (VALDO) challenge. We evaluated overall, voxel, object, and lesion-wise Dice; stratified performance by region, diagnosis, scanner, PVS severity, and white matter hyperintensity (WMH) burden; and tested whether model-derived PVS burden reproduced ground-truth derived associations with AD-related biomarkers. Despite high internal performance, all models showed a specialist-generalist trade-off: the AD-trained ADNI-PVS-Net achieved highest internal performance (overall Dice = 0.58 {+/-} 0.14) but degraded most externally (Dice [&le;] 0.11), while MedNet-PVS and mcPVS-Net generalized externally (Dice 0.27-0.30) but systematically misestimated PVS burden. Models were relatively robust across scanner and diagnosis but inconsistent across PVS severity, and some misclassified up to 32% of WMH as PVS. Notably, only AD-trained models reproduced the expected PVS-amyloid biomarker relationship; other models returned a null result, despite comparable or superior Dice scores. These findings show that internal segmentation accuracy and external generalizability alone do not guarantee downstream inferential validity. Careful model selection and cohort-specific validation against manual labels should precede clinical inference in AD.

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

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

Introduction: Major depressive disorder (MDD) is a highly prevalent and disabling psychiatric disorder. Human neuroimaging studies increasingly frame its neurobiological substrate in terms of alterations of large-scale brain network organization. Resting-state fMRI findings broadly align with this view, yet remaining highly heterogeneous, reflecting both clinical and analytic variability. Predominant approaches largely characterize functional organization in terms of pairwise relationships between regions, which may limit the ability to capture more global features of brain organization associated with depression and its course. Here we use novel methods from Topological Data Analysis to provide new perspectives on these brain-behavior associations Objectives: The main objective of this study was to determine whether whole-brain topological descriptors of functional connectivity capture alterations associated with MDD. In particular, we examined whether these features vary along clinically relevant dimensions of heterogeneity, focusing on illness course (single-episode vs. recurrent MDD) and current antidepressant medication status. To this end, we analyzed the area under the curve (AUC) of the zeroth and first Betti numbers (B and B), which index global network integration and higher-order cycle structure across scales, respectively. Methods: Neuroimaging (resting state fMRI) and phenotypic data were obtained from 1,490 participants (776 individuals with MDD and 714 never-depressed controls) included in the REST-meta-MDD project of the DIRECT consortium. Functional connectivity matrices were computed using Pearson correlations between regions defined by the Power-264 atlas and harmonized across sites using CovBat. Topological Data Analysis was applied to characterize whole-brain network organization across connectivity thresholds using B and B curves and their areas under the curve (AUC). B associated cycle counts and their coarse anatomical configurations were further examined. Group differences and effects of illness course and medication status were assessed using multiple linear and generalized linear regression models. Results: Compared with controls, individuals with MDD showed significantly higher B AUC, indicating altered global integration profiles across connectivity thresholds. B AUC did not differ by illness course, illness duration, or symptom severity. In contrast, B AUC showed a graded increase across illness courses, with the highest values observed in recurrent depression. This effect was driven by an increased number of one-dimensional cycles rather than greater cycle persistence. Medication status further modulated B alterations, with elevated values observed in unmedicated single-episode and medicated recurrent MDD. Anatomical decomposition revealed that higher-order alterations were primarily driven by inter-network configurations spanning multiple large-scale functional systems. Discussion:These findings indicate that MDD is associated with altered multiscale functional organization, combining less compact global integration with an increased prevalence of cross-network hole-defining cycles, with these features varying systematically with illness course and current medication, suggesting that topology-informed measures capture clinically relevant variability in brain organization in depression.

Trauma-related intrusive memories (TRIMs) are a core symptom of posttraumatic stress disorder and cause significant distress and impairment for trauma-exposed individuals due to their vivid sensory features that intrude on ongoing thought. These phenomenological properties point to a neuropathology that spans autobiographical memory, spontaneous thought, and sensory perception. The hierarchical organization of the cortex maximally segregates the default mode network (DMN), which supports autobiographical memory and ongoing thought, from the sensory cortices (SC). Accruing evidence implicates altered interactions between the DMN and SC in PTSD and TRIMs, suggesting a breakdown in this segregation. We sought to test whether diminished DMN-SC segregation, indexed by a shorter functional distance between the DMN and SC within cortical connectivity gradients, was associated with the vividness and intrusiveness of TRIMs. One-hundred eight trauma-exposed adults completed two weeks of ecological momentary assessments (EMAs) of TRIM properties followed by resting-state fMRI. Gradient analysis of cortical functional connectivity was performed to compute the Euclidean distance between resting-state networks. Pearson correlations revealed an association between a shorter DMN-SC distance and greater TRIM vividness and intrusiveness, with multivariate models indicating a specificity for intrusiveness. Importantly, the DMN-SC distance was not associated with clinician-rated symptom severity and explained unique variance above and beyond conventional functional connectivity measures. These findings suggest that a loss of functional segregation between the DMN and SC - a core organizational feature of the cortical hierarchy - is associated with the intrusive sensory vividness of TRIMs, offering insights into candidate mechanisms of and neurotherapeutic targets for intrusive trauma memories.