Brain Structure and Function

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.

The lateral habenula (LHb) shapes reward and aversion learning via projections to midbrain monoaminergic centers. Recent studies have demonstrated significant genetic, anatomical, and electrophysiological diversity within the LHb. However, it remains unclear how genetic or intrinsic electrophysiological characteristics relate to in vivo neuronal activity patterns. Additionally, there are few descriptions of transgenic mouse lines labeling specific LHb neuronal subtypes. Here we describe spatial gene expression patterns, electrophysiological characteristics, and projection targets for specific subpopulations of neurons in the LHb targeted via existing transgenic mouse lines. Furthermore, we demonstrate that two genetically defined subpopulations differentially respond to value, prediction errors, and directional movement during flexible, reward-guided behavior. These findings indicate that specific, genetically targetable, neuronal subpopulations in LHb may control discrete aspects of motivated behavior through parallel circuits targeting serotonergic and dopaminergic midbrain centers.

In-vivo examination of neurites to understand microstructural properties of white matter tissue utilizing neurite orientation dispersion and density imaging (NODDI) has shown sensitivity to healthy aging as well as disease biomarkers and status. Neurite density index (NDI), which is a proxy for the amount of neurites, in white matter tissue typically decreases with age. However, orientation dispersion index (ODI), which is a proxy for neurite dispersion or fanning, has been mixed with studies finding both increases and decreases with age. Furthermore, white matter tracts are not uniform and hold its own unique spatial pattern or gradient in microstructural properties. In addition to the spatial pattern of the microstructural property, age-related effects have also shown spatial patterns with stronger age effects in the medial, anterior, and dorsal portions of white matter tissue. However, spatial gradients along cardinal axes within an individual's tract have yet to be examined with age in an adult lifespan sample. The current aim of the study was to examine whether average and spatial gradients of neurite microstructural properties within tracts related to the cortico-striato-pallido-thalamic (CSPT) loop were age-sensitive. An adult lifespan sample aged 20-90 years old was recruited from the Dallas-Fort Worth metroplex (N = 104, 62% females) as part of the Dallas Area Longitudinal Lifespan Area Study (DALLAS). Participants completed an MRI session that included a structural T1-weighted image as well as multi-shell diffusion weighted imaging (MS-DWI). MS-DWI were preprocessed and tracts of interest related to the CSPT loop were obtained using probabilistic tractography. For most tracts, a significant inverted-U association with age was found for both average NDI and ODI. Most tracts revealed a reliable spatial gradient of NDI and ODI in the medial-to-lateral, posterior-to-anterior, and ventral-to-dorsal direction. Tracts related to CSPT loop were age-sensitive such that the spatial gradient was becoming more homogenous with age. This loss of spatial gradients with age is analogous to network-level dedifferentiation observed in BOLD functional connectivity. These findings highlight that age effects in a fundamental circuit for both basic and higher-order function is significantly age sensitive and while organized into spatial gradients, these gradients are also vulnerable to aging.

The ventral motor and the centromedian (CM) nuclei receive prominent GABAergic inputs from the basal ganglia, massive glutamatergic projections from motor cortices and significant GABAergic afferents from the reticular thalamic nucleus. There is strong evidence that disrupted processing of information through these connections may contribute to the pathophysiology of the basal ganglia-thalamocortical loop in Parkinson's disease (PD). To further assess potential ultrastructural changes in synaptic connectivity and mitochondrial integrity that may contribute to these network dysfunctions, we used a 3D electron microscopic approach to determine whether the pattern of synaptic innervation and morphological integrity of dendritic mitochondria are altered in the basal ganglia-receiving parvocellular ventral anterior nucleus (VApc) and CM neurons of MPTP-treated parkinsonian monkeys. Three main conclusions can be drawn from our findings: (1) Although the overall pattern of synaptic innervation of VApc and CM neurons is not altered in parkinsonian monkeys, the volume of putative corticothalamic terminals is significantly increased in both nuclei, (2) the prevalence of corticothalamic terminals in contact with distal dendrites is several orders of magnitude higher in VApc than CM in both control and parkinsonian monkeys, (3) the complexity and ultrastructural integrity of dendritic mitochondria is altered in CM, but not in the VApc, of parkinsonian monkeys. These findings lay the foundation for future studies of changes in cortical neuromodulation of VApc and CM neurons in parkinsonism and suggest that mitochondrial defects may contribute to the degeneration of CM neurons in PD.

Human hand coordination exceeds that of other species, including great apes, and is marked by pronounced right-hand dominance. This specialization parallels an expansion of its cortical representation, forming the hand-knob in the motor cortex. In humans, this region shows high myelination on quantitative MRI (qMRI), but whether this feature is shared with great apes remains unclear. It is also unknown whether increased right-hand dominance in humans is mirrored by greater hemispheric asymmetry in cortical microstructure. Using high-resolution qMRI, we compared motor cortex subdivisions controlling the leg, hand, and face in humans and chimpanzees. We found consistently higher myelin and iron content in the hand-knob in both species, suggesting an evolutionarily conserved role. However, only humans showed enhanced rightward lateralization. These results highlight both conserved and species-specific features of the motor cortex, offering insights into the evolution of manual dexterity and handedness.

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.

Recent work has revealed two food-selective areas in the lateral and ventromedial occipitotemporal cortex (OTC). These studies have shown that food selectivity in these regions cannot be explained by mid-level features like shape, texture, or colour but differences in their representational content remain unclear. Across two fMRI experiments conducted in the same group of participants, we characterized the dimensions underlying food representations in lateral and ventral OTC by examining the contribution of action-related object properties, such as manipulability, relevant to object interaction, and visual features, such as colour and ensemble statistics, relevant to object recognition. Our results reveal a clear dissociation between lateral and ventral OTC, indicating that food representations in these regions reflect distinct computational constraints. In lateral OTC, food representations were primarily associated with action-related properties shared between food and other graspable objects, whereas in ventral OTC, food representations were sensitive to surface object properties, such as colour and ensemble configuration. Consistent with this distinction, lateral OTC showed greater sensitivity to individual objects against distinctive background and responded equally to colour and greyscale stimuli, while ventral OTC exhibited greater sensitivity to coloured stimuli and ensembles with no distinctive background. Finally, topographic artificial neural networks implementing architectural constraints meant to capture OTC spatial organization similarly exhibited two dissociable clusters of food-selective units based on sensitivity to ensemble statistics. Together, these findings suggest that lateral food representations reflect action-relevant properties shared with other manipulable objects, whereas ventral food representations arise from surface-based visual features critical for food identification.

In this paper, we address the problem of quantifying similarity between planar 2D shapes, which is relevant to studies of internal representations in cognitive, developmental, and neurological research. We designed a set of test shapes arranged along a visually defined perceptual similarity gradient and used them to evaluate classical geometric methods for shape comparison, including Procrustes and Chamfer distance, as well as a convolutional neural network (CNN)-inspired feature-based method. Based on the limitations identified for these individual methods, we developed a hybrid Geometric-Feature Similarity (GFS) algorithm that combines geometric alignment, global contour properties, and convolutional feature-based descriptors into a unified weighted similarity score. By combining global geometric information with local structural features, the GFS algorithm more accurately reproduces human perceptual judgments of shape similarity than either geometric or feature-based methods alone. Requiring neither network training nor large labelled datasets, the proposed algorithm provides an efficient and interpretable tool for a broad range of studies involving quantitative shape comparison.

Congenital sensory loss reveals how experience shapes the brain organization, yet most accounts of such plasticity have focused on cortex rather than the thalamic systems that link sensory input, cortical development, and distributed networks. Here, we tested whether primary and higher-order thalamic nuclei show distinct relationships with thalamocortical organization after early sensory loss. In congenital blindness, structural differences were focal to the lateral geniculate nucleus (LGN), the primary thalamic nucleus of the visual system, with individual differences in LGN volume associated with areal features of primary visual cortex morphology. Functional differences, by contrast, involved altered relationships between visual cortex and higher-order cortical and thalamic systems, including stronger functional similarity between visual cortex and control-related networks at rest and during active nonvisual cognition. A parallel analysis of congenital deafness showed no detectable volumetric difference in the medial geniculate nucleus, the primary thalamic nucleus of the auditory system, but revealed altered functional relationships between auditory cortex and higher-order cortical and thalamic systems. These findings suggest that primary thalamic pathways are associated with modality-specific structural consequences of early sensory loss, whereas higher-order thalamocortical systems contribute to convergent functional reorganization of affected sensory cortices across sensory modalities.

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.

ObjectiveGlucagon-like peptide-1 (GLP-1), a peptide neurotransmitter in the brain, is synthesized from proglucagon, encoded by the glucagon gene (Gcg). Besides medullary GLP-1 neurons, Gcg-expressing neuron populations were identified in the olfactory bulb and basolateral amygdala. However, several lines of evidence suggest that additional Gcg neuron populations might exist. MethodsWe conducted a brain-wide mapping of Gcg-expressing cells by fluorescent in situ hybridization in C57BL/6J and FVB/Ant mice. Proglucagon and GLP-1 expression were studied with immunofluorescence. We characterized a Gcg-Cre;tdTomato mouse line and studied the expression of proglucagon-processing enzymes in Gcg-expressing neuron populations. We used adeno-associated virus-mediated tracing in Gcg-Cre mice to map the projections of hypothalamic Gcg neurons. ResultsGcg-expressing neuron populations were identified in the olfactory bulb, claustrum, piriform cortex, basolateral amygdala, posterior hippocampus, posterior hypothalamic nucleus (PH), periaqueductal gray/dorsal raphe, and dorsal nucleus of the lateral lemniscus. These neurons express lower Gcg mRNA levels than medullary GLP-1 neurons. Proglucagon and GLP-1-immunoreactivity (C-terminus) were detected in almost all Gcg-expressing neuron populations, along with the mRNAs for prohormone convertases 1/3 and 2, enzymes generating GLP-1 or glucagon, respectively. Fasting markedly increased Gcg mRNA, proglucagon and GLP-1 synthesis in the PH. PH Gcg neurons project densely to the ventral and intermediate lateral septum, preoptic region, ventrolateral preoptic nucleus, lateral hypothalamus and zona incerta, establishing close contacts with both GLP-1 receptor-positive and -negative neurons. ConclusionsProglucagon is expressed in 9 distinct neuron populations. Feeding status regulates GLP-1 synthesis in PH neurons that likely control feeding- or energy balance-related functions.

IntroductionThe insula is an increasingly important target for functional neurosurgery given its involvement in a range of neurological and neuropsychiatric disorders, including epilepsy and chronic pain. As this practice evolves, optimal targeting will require standardized outcome measures that relate electrode or laser trajectory to postprocedural outcome. Traditional whole- brain registration approaches fail to capture the substantial person-to-person variability in insular gyral configuration, including the relative internal rotation of the insular gyri with respect to standard stereotactic space. ObjectiveWe propose and validate a stereotactic coordinate system based on local anatomical landmarks to facilitate surgical planning and standardized outcome assessment within the insular cortex. MethodsOur approach transforms brain MRI first into standard AC-PC space, and then into an insular-specific space defined by five anatomical landmarks: four points along the central sulcus of the insula and one point at the middle cerebral artery (MCA) bifurcation (at the limen insulae). The system calculates two angles - {theta} (axial) and {varphi} (sagittal) - between the AC-PC line and the insular axis, and the brain volume undergoes sequential rotation through these angles followed by translation to place the coordinate systems origin along the insular axis. ResultsIn a sample of 32 patients, the angle between the AC-PC line and the insular axis ranged from -17{degrees} to 17{degrees} in the axial plane ({theta}) and 31{degrees} to 69{degrees} in the sagittal plane ({varphi}). In the resulting coordinate system, the insular axis defines z = 0 and the MCA turning point defines y = 0. We developed a custom, open-access MATLAB graphical interface that allows intuitive implementation of this system for both surgical planning and postoperative analysis; implanted electrodes, laser fiber position, and ablation geometry can each be localized within this common space. As a demonstration of its utility for pooling data across subjects, we applied the transformation to a previously acquired intracranial electrophysiology dataset and found that anatomically consistent, effector-specific motor representations emerged across 18 subjects once electrode positions were expressed in insular-specific coordinates. ConclusionAs stereotactic surgery for insular targets becomes more common with expanding scientific inquiry, an insular-specific coordinate system may facilitate operative planning and functional mapping, and may help standardize outcome assessment across patients and institutions. SIGNIFICANCE STATEMENTThe insular cortex represents an increasingly important surgical target for therapeutic interventions, yet substantial person-to-person anatomical variability hampers standardized targeting and outcome comparison. The insula is simultaneously the subject of expanding scientific inquiry -- into interoception, pain, autonomic regulation, salience processing, and sensorimotor representation -- much of it now pursued through intracranial recording and stimulation in humans, where cohorts are small, electrode sampling is idiosyncratic, and progress therefore depends on pooling data across patients in a frame that respects insular gyral architecture. We present "Insulotaxy," a stereotactic coordinate system built from consistent, easily identifiable local anatomical landmarks that accounts for the insulas unique rotational relationship to standard brain coordinates. An open-source MATLAB tool transforms imaging into insular-specific coordinates, facilitating surgical planning for ablation and electrode placement while enabling standardized outcome reporting across institutions. By providing locally anchored, anatomically aligned coordinates rather than relying on whole-brain registration, this framework addresses a practical gap in functional neurosurgery and lays a foundation for pooling clinical and electrophysiological data as insular interventions become more prevalent.

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.

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.

Introduction: Auditory brainstem responses (ABRs) are routinely used to assess neural timing and function along the auditory pathway. In older adults, however, peripheral hearing loss, central auditory dysfunction, and broader structural changes in the brain may converge to shape the recorded response. Because ABR waves arise from multiple overlapping neural sources, how their electrophysiological features map onto specific auditory pathway structures in vivo remains poorly understood. Here, we examined the associations between cortical and subcortical gray matter volumes and the latencies and amplitudes of click evoked ABR Waves I and V in older adults. Methods: We evaluated 88 adults aged > 65 years from the Auditory and Dementia Study (ANDES) cohort. Click evoked ABRs were recorded at 80 dB nHL, and the latencies and amplitudes of Waves I and V were measured. High resolution 3T structural MRI data were processed using voxel based morphometry and standardized anatomical masks to estimate bilateral gray matter volumes of the cochlear nucleus, superior olivary complex, inferior colliculus, medial geniculate nucleus, and auditory cortex. Associations were assessed using partial correlations adjusted for age, pure tone hearing thresholds, and intracranial volume, as well as multivariate linear regression models. Results: ABR latencies, rather than amplitudes, showed significant associations with regional gray matter volumes. After adjustment for age, hearing thresholds, and intracranial volume, larger superior olivary complex volume was associated with shorter Wave I latency ({rho}partial = -0.305, p = 0.005), whereas larger medial geniculate nucleus and auditory cortex volumes were associated with shorter Wave V latency ({rho}partial = -0.265, p = 0.014 and {rho}partial = -0.404, p < 0.001, respectively). In multivariate models, superior olivary complex volume remained associated with Wave I latency ({beta} = -0.310, p = 0.007). Medial geniculate nucleus volume was initially associated with Wave V latency ({beta} = -0.247, p = 0.038); however, this relationship was attenuated once auditory cortex volume was included in the model ({beta} = -0.350, p = 0.002), which emerged as the dominant predictor. Inferior colliculus volume was not significantly associated with Wave V latency or amplitude. Conclusions: In older adults, ABR latencies showed selective associations with regional gray matter volumes, whereas amplitudes did not. These associations extended beyond the structures traditionally considered the main generators of Waves I and V, suggesting that interindividual variation in ABR latency may reflect distributed anatomical variation across the auditory pathway rather than a strict one-wave-one-generator correspondence.

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: 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.

Developmental dyslexia is a specific, highly prevalent and often debilitating reading and spelling disorder with unknown neurocomputational mechanisms. Here we discovered, in a preregistered functional magnetic resonance imaging study optimized for the subcortical sensory pathway, that dyslexia is characterized by altered predictive coding in left-hemispheric auditory sensory pathway nuclei. The neurocomputational alterations were related to one of the two main dyslexia risk scores, indicating a crucial role for dyslexia pathophysiology.

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: Quantitative MRI (qMRI) provides voxel-wise measurements of tissue properties related to myelin, iron and water content, making it a powerful tool for studying brain aging and microstructural alterations in vivo. However, conventional spatial smoothing can introduce partial-volume effects and blur tissue boundaries, potentially affecting both statistical sensitivity and anatomical specificity. Several tissue-specific smoothing strategies have been proposed to address these limitations, yet their relative impact on voxel-wise statistical analyses remains insufficiently characterized. The present study aims (i) to systematically compare three tissue-specific smoothing strategies: a linear tissue-weighted compensated approach (TWS), a generalized version of nonlinear tissue-masked compensated smoothing approach (gTSPOON), and an intensity-weighted edge-preserving approach based on the Smallest Univalue Segment Assimilating Nucleus smoothing (SUSANs), and (ii) to investigate how smoothing approaches interact with statistical inference frameworks by comparing parametric and non-parametric voxel-wise analyse. Methods: Analyses were performed on a publicly available lifespan qMRI dataset comprising 138 healthy participants (19-75 years) and quantitative maps of MTsat, PD, R1, and R2*. The generalized TSPOON (gTSPOON) method was implemented using tissue-specific masks derived from probabilistic tissue segmentation. All three smoothing approaches (TWS, gTSPOON and SUSANs) were parameterized to achieve comparable nominal spatial smoothing. Age-related effects were investigated separately in GM and WM using voxel-wise general linear models following a previously published framework. Statistical inference was assessed using multiple complementary approaches, including parametric Random Field Theory (RFT), under both stationarity and non-stationarity assumptions, as well as non-parametric permutation-based inference. In addition to conventional thresholded statistical parametric maps, voxel-wise log-likelihood (LL) maps were computed to quantify general linear model (GLM) goodness-of-fit independently of statistical thresholding. Bland-Altman analyses and spatial agreement metrics were subsequently used to compare smoothing strategies. Results: TWS and gTSPOON produced highly similar spatial distributions of age-related effects across all qMRI parameters and tissue classes. However, TWS consistently yielded a larger number of significant voxels and clusters, reflecting slightly higher sensitivity, from slightly wider effective smoothness and reduced RESEL counts. By contrast, SUSANs generated substantially fewer significant voxels and clusters, associated with approximately half the effective smoothness and a markedly larger number of RESELs. Despite these differences in statistical sensitivity, voxel-wise LL analyses revealed distinct anatomical preferences for each smoothing strategy. TWS provided the best model fit predominantly within GM, whereas gTSPOON showed superior performance in homogeneous WM regions. Conversely, SUSANs achieved the highest LL values at GM-WM interfaces, particularly within sulcal and gyral transitions, indicating improved preservation of sharp anatomical gradients. These spatial patterns were consistently observed across MTsat, PD, R1 and R2* maps. Comparisons across stationary and non-stationary RFT assumptions revealed only minor differences, while non-parametric inference produced highly concordant results, indicating that the primary source of variability originated from the smoothing procedure itself rather than the inference framework. Conclusions: Tissue-specific smoothing strategies substantially influence both statistical sensitivity and voxel-wise model fitting in qMRI analyses. While TWS and gTSPOON provide highly consistent results, the edge-preserving SUSANs approach preferentially enhances model fit at tissue boundaries. Importantly, voxel-wise log-likelihood mapping revealed that no smoothing strategy is uniformly optimal throughout the brain; instead, each method exhibits anatomically preferential regions where model fit is maximized. These findings suggest that smoothing should be viewed as a region-dependent optimization problem and highlight voxel-wise LL mapping as a principled framework for selecting or developing adaptive smoothing strategies tailored to specific neuroanatomical structures and biological processes, including age-related brain changes.