Brain Structure and Function

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

Background and Objectives: Are some brain regions intrinsically more vulnerable to metastatic colonization? We sought to characterize the spatial distribution of brain metastases and determine whether regional patterns vary according to primary tumor origin. Methods: We analyzed baseline MRI scans and expert tumor segmentations from 906 patients with 3,492 brain metastases treated with stereotactic radiosurgery. Lesions were normalized to MNI152 standard space and superimposed to generate probabilistic atlases of metastatic occurrence. Regional metastatic burden was quantified using anatomical and vascular atlases. Spatial distributions were additionally compared between lung cancer and melanoma metastases. Results: Metastatic burden was distributed nonuniformly throughout the brain. The cerebellum demonstrated the strongest enrichment relative to its anatomical volume (fold change 1.61, p < 0.001), accompanied by overrepresentation of the vertebrobasilar circulation (fold change 1.49, p < 0.001). Spatial distribution also varied by primary tumor type. Lung cancer metastases demonstrated greater infratentorial involvement than melanoma metastases (16.6% vs. 8.7%, p < 0.05), with a corresponding increase in cerebellar burden (14.8% vs. 6.8%, p < 0.05), whereas melanoma metastases were relatively concentrated within the frontal lobe (37.7% vs. 24.6%, p < 0.01). Infratentorial enrichment was observed across all carcinoma subgroups, with the greatest enrichment seen in gastrointestinal metastases (32.9% infratentorial). Conclusion: Brain metastases exhibit nonrandom spatial distributions, with preferential involvement of posterior and infratentorial structures. Regional patterns vary according to primary tumor origin, supporting the existence of region-specific vulnerability to metastatic disease.

The thalamic reticular nucleus (TRN) is a thin, inhibitory shell surrounding the thalamus. It regulates the thalamocortical information flow, and thereby plays a central role in attention, task switching, and the sleep-wake cycle. Despite its importance, the TRN remains poorly studied in the human brain. This is largely because its small size and deep anatomical location limit its visibility with conventional non-invasive neuroimaging techniques. Here, we assessed whether the human TRN can be reliably visualised and segmented in vivo using ultra-high field (UHF) magnetic resonance imaging (MRI) at 7 Tesla. High resolution (0.35 mm isotropic) partial-brain T2* and T1 scans were acquired from healthy individuals, followed by manual delineation of the TRN. These in vivo segmentations were compared with TRN estimates obtained from two high-quality postmortem datasets serving as an anatomical reference. In vivo segmentations of TRN volume and thickness closely matched measurements derived from the postmortem reference datasets, and quantitative comparisons showed high consistency in TRN shape and location across individuals while also capturing meaningful inter-individual variability. Using these segmentations, we constructed a publicly available probabilistic atlas of the human TRN. This atlas provides a new resource for incorporating TRN anatomy into functional, structural, and clinical neuroimaging studies. Our findings demonstrate that the human TRN can be robustly mapped in vivo at 7T and establish a foundation for future investigations into its structure and function.

Recurrent processing involves feedforward, feedback and lateral connections and is thought to allow efficient visual processing. Anatomical and behavioral studies in humans have suggested that feedback connections mature later in development than feedforward connections and thus were proposed to depend to a larger degree on experience. In order to isolate feedforward from feedback activity and to investigate the role of early visual experience, we assessed seven individuals with reversed congenital cataracts and nine sighted controls using an "occlusion paradigm" with 7T magnetic resonance imaging (Smith & Muckli, 2010): Grayscale images of scenes were presented with the lower right quadrant covered by a white rectangle. We examined whether information about category (beaches, buildings, highways) and individual scenes could be extracted from early visual region vertices (V1 - V3) associated with the occluded quadrant of the visual field, in the absence of bottom-up visual input. This was achieved by decoding individual category or scene context utilizing a linear support vector machine. In addition, bidirectional information flow was assessed using connective field modeling. While both groups showed successful decoding of scene and category from vertices receiving bottom-up visual input, the accuracy was higher in normally sighted individuals than in individuals with reversed congenital cataracts. When bottom-up input was removed, decoding of categories remained successful in both groups, but decoding of individual scenes was only possible in normally sighted control individuals. Connective field modeling results indicated a less precise alignment of feedforward and feedback processing during visual stimulation in individuals with reversed congenital cataracts. These findings suggest that early visual experience is crucial for the refinement of feedback activity which in turn is crucial for well-tuned feedforward processing.

The basal ganglia and thalamus are key nodes in subcortico-cortical loops involved in sensory, motor, and cognitive function. In adults, posterior regions of the subcortex link to cortical sensorimotor networks and anterior regions link to association networks. Alterations in the size, strength, and selectivity of these subcortical regional network representations are implicated in several neuropsychiatric disorders, many of which originate early in development. However, the organization of these network representations at birth remains incompletely understood, limiting our ability to devise normative and atypical developmental models of subcortico-cortical interactions. Using resting-state fMRI, we characterized the size, strength, and selectivity of cortical network representations in the basal ganglia and thalamus in a set of neonates (n=261) and compared results to children (age range 9-11 years, n=69) and adults (n=120). We found that the broad anterior-posterior organization of the subcortex is present at birth, yet representations of somatomotor networks were larger at birth compared to children and adults (p<0.001). The strength and selectivity of subcortico-cortical functional connectivity (FC) exhibited interactions between age group and network (all p<0.001), such that subcortical representations of sensorimotor networks exhibited stronger FC and higher selectivity in neonates, while subcortical representations of association networks exhibited stronger FC and higher selectivity in older cohorts. In parallel, data-driven clustering revealed areas with integration of multiple networks in the neonatal subcortex. These results suggest that subcortico-cortical FC evolves over development largely in a sensorimotor-association manner and provide a baseline for normative and disordered subcortical development.

A recent study (Manjarrez et al., 2026) showed that the classification of cortical dendritic spines into stubby, thin, and mushroom subtypes is unstable under rotation. That result criticizes the categorical scheme but leaves an open question. What is the actual structure of spine morphology once the viewing angle is controlled? Here we answer it. We analyzed 228 spines from layer II pyramidal neurons in the H01 nanometer-resolution reconstruction of human temporal cortex. We first quantified the source of instability. We found that rotating dendritic segments by 90 degrees about their axes shifted the apparent spine height and head width in opposite directions across the population, thereby confirming orientation-dependent measurement error. Furthermore, to obtain measurements free of this artifact, we developed the Spine Morphometry Hub (SMH), a 12-point anatomical landmark framework that characterizes each spine in all three orthogonal planes and extracts geometric, voxel-based, and mesh-based metrics. All morphometric distributions were unimodal and right-skewed. Density-based clustering assigned most spines to noise, and a Monte-Carlo test against a discrete two-type null model confirmed that this pattern is incompatible with categorical subtypes. We also confirmed that apical and basal spines were statistically indistinguishable. Unlike previous reports of a spine continuum, all based on orientation-dependent measurements, our framework removes the viewing-angle confound itself, so the continuum we observe cannot be attributed to a projection artifact. Hence, our framework will be useful to quantify dendritic-spine remodeling in neurological disorders, in which spine shape has long been observed but never measured against an orientation-invariant morphometric standard. HighlightsO_LISpine Morphometry Hub (SMH) measures spines free of viewing-angle error C_LIO_LISMH was validated as an orientation-invariant morphometry framework C_LIO_LIRotating dendrites by 90{degrees} shifts spine height and head width oppositely C_LIO_LIAll morphometric distributions are unimodal and right-skewed, not categorical C_LIO_LISMH could be used to quantify dendritic-spine remodeling in neurological disorders C_LI

The corpus callosum is a major white matter bundle responsible for connecting both hemispheres. In mammals, due to a variety of causes, the development of the corpus callosum can be impaired - this brain malformation is known as corpus callosum dysgenesis (CCD). The clinical presentation of CCD varies, with patients exhibiting three morphological phenotypes: agenesis, partial dysgenesis, and hypoplasia. Although the first two presentations are easily detectable on MRI scans, the latter is more challenging, as the structure is fully formed but has a reduced area. In this study, we develop (1) a pipeline to generate synthetic MRI scans with apparent anatomical variation and (2) train a U-Net-based tool to automatically segment the corpus callosum of marmosets in both healthy and disease contexts. Methodologically, a custom script was devised to apply rotation and translation to T1-weighted MRI scans at the volume level. Because the slicing grid remains unchanged, these rigid transformations translate into apparent anatomical variations at the slice level. We compared corpus callosum measurements obtained from automatically segmented masks with those from manually delineated masks. The average Dice score was above 0.90, and the Hausdorff distance was below 0.4 mm. We also stratified our cohort according to phenotype (healthy controls and hypoplastic animals). The magnitude of the effect and the significance level observed between the voxel counts of healthy and hypoplastic animals using manually delineated masks were comparable to those obtained via automatic segmentations. These results show that our pipeline can generate a sufficiently varied training pool to build an accurate U-Net segmentation model with high diagnostic capability.

Subcortical structures play a key role in shaping cortical computation through distributed cortico-subcortical networks, yet it remains unclear whether individual differences in subcortical anatomy are reflected in resting-state cortical oscillations. We analysed resting-state magnetoencephalography (MEG) and structural MRI from 533 healthy adults in the Cambridge Centre for Ageing and Neuroscience (CamCAN) cohort to test whether hemispheric asymmetries in subcortical volume predict asymmetries in cortical oscillatory power. Lateralisation indices were calculated for subcortical volumes and for oscillatory power across homologous MEG sensor pairs. Cluster-based permutation testing revealed frequency-specific associations between subcortical anatomy and cortical activity. Globus pallidus asymmetry was positively associated with posterior alpha-band power lateralisation, putamen and caudate asymmetries were associated with beta-band lateralisation, and hippocampal asymmetry was negatively associated with delta-band lateralisation. These findings extend previous task-based observations linking pallidal anatomy with alpha oscillations to the resting state and demonstrate that distinct subcortical structures are associated with specific cortical frequency bands. Our results suggest that resting-state MEG captures functional signatures of cortico-subcortical organisation and provides a non-invasive framework for studying healthy ageing and disorders involving subcortical degeneration.

The hippocampus is characterized by a stereotypical macroscopic structure, where the nuclei are densely and heterogeneously packed among different subregions of the hippocampus. Despite the fact that tissue-specific cellular organization has been implicated in neural function, it has been technically challenging to quantitatively analyze mesoscopic cellular organization in the hippocampus due to its high cellular density. To overcome this technical hurdle, we developed Computational Biophysical Histomorphometry Software (CBHS), an automated image-analysis pipeline, aimed at quantifying nuclear shape and the order of the cellular ensemble in high-density areas. When applied to the subfields of hippocampus, we found that denser regions, most notably the dentate gyrus, were the most positionally, but least orientationally ordered. Nuclear shape exhibited a dependence on the local environment in a packing-dependent manner. This association was cell-type specific, with neurons, but not astrocytes displaying nuclear shape that varied with neighbour proximity, although astrocytes demonstrated greater intrinsic shape variance. The results reveal the presence of reproducible mesoscale cell packing order in hippocampal tissue, and are consistent with a nucleus-driven mechanical coupling between neighbouring cells. The present study provides a quantitative framework with which to understand mesoscopic tissue organization, thus enabling the formulation of testable hypotheses for future investigation.

People differ widely in their sensitivity to pain, and this variability is clinically relevant, yet the underlying structural brain mechanisms remain poorly understood. White matter hyperintensities (WMH), a common imaging marker of cerebral small vessel disease, are associated with microstructural abnormalities in white matter tracts and have also been linked to pain related outcomes; however, the mechanisms linking WMH to altered pain perception remain unclear. We investigated whether WMH are linked to pain sensitivity through tract specific microstructural alterations and cortical structural differences. We analysed data from 1,448 participants (mean age 73 years; 53% women) in the population based Rotterdam Study and independently replicated the findings in 1,522 participants (mean age 63 years; 52% women) from the population based Tromso Study. Pain sensitivity was quantified using the cold pressor test. Multimodal magnetic resonance imaging, including T1 weighted, fluid attenuated inversion recovery and diffusion tensor imaging, was used to map WMH to predefined white matter tracts, derive tract specific fractional anisotropy (FA), and estimate cortical measurements. Cox proportional hazards models assessed associations with pain sensitivity, and tract specific mediation analyses evaluated whether white matter microstructure or tract connected cortical regions mediated the relationship between white matter hyperintensities and pain sensitivity. WMH were present in 20 of 27 predefined tracts and were associated with reduced FA in 18 tracts. Higher WMH burden was associated with greater pain sensitivity, particularly in the left anterior thalamic radiation and left superior thalamic radiation, while lower FA in the anterior thalamic radiation, medial lemniscus, superior thalamic radiation and inferior fronto occipital fasciculus was associated with greater pain sensitivity. Mediation analyses showed that white matter microstructural disruption was the principal pathway linking WMH to pain sensitivity, with the strongest indirect effects observed through the inferior fronto occipital fasciculus (44.6% mediated) and anterior thalamic radiation (32.6% mediated). Cortical atrophy in the precentral and postcentral gyri provided a smaller secondary pathway, mediating approximately from 3 to 6% of the association between corticospinal or superior thalamic radiation WMH and pain sensitivity. Replication analyses supported these cortical mediation pathways, and meta analysis strengthened the tract specific associations. Together, the results suggest that vascular white matter injury is associated with pain perception through specific structural pathways, with DTI based markers appearing particularly sensitive to these relationships.

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

Multimodal imaging approaches that combine structural and functional neuroimaging provide a robust framework for examining neuroplastic adaptations that may not be captured by any single modality. The present study investigated the effects of a four-week expiratory muscle strength training (EMST) program on structural and resting-state functional connectivity in healthy young adults. Five healthy young adult males (aged 19-35 years) completed a standard four-week EMST protocol and underwent pre- and post-training imaging assessments. Structural neuroimaging included T1-weighted and diffusion-weighted MRI, which were analyzed using voxel-based morphometry, surface-based morphometry, and white-matter structural connectivity. Functional neuroimaging consisted of resting-state fMRI to assess training-related changes in functional architecture, network connectivity, and global network measures. Structural MRI analyses revealed no significant changes in gray or white matter volume, cortical morphology, or white-matter structural connectivity following EMST (all FWE- or FDR-corrected p > .05). In contrast, resting-state fMRI demonstrated a significant increase in whole-brain functional connectivity (FDR-corrected p = .036), accompanied by greater network integration, reflected in increased local efficiency and transitivity and reduced modularity. Network-level analyses showed enhanced within- and between-network connectivity in sensorimotor and cognitive circuits. Our findings demonstrate robust functional reorganization following EMST, despite the absence of detectable macrostructural or large-scale white-matter connectivity changes, at least within the timescale and sample characteristics of the current study. These results reflect early-stage neuroplasticity, both globally and within the networks underlying speech and swallowing control and suggest that functional reorganization occurs early in training and likely precedes longer-term structural modifications in these networks.

IntroductionChemogenetic tools such as Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) provide a powerful means to causally manipulate defined neuronal populations in vivo. While chemogenetic fMRI studies have consistently demonstrated robust hemodynamic responses following circuit perturbation, considerably less is known about the accompanying metabolic consequences. Functional magnetic resonance spectroscopy (fMRS) offers the potential to probe these neurochemical processes, yet the relationship between hemodynamic and metabolic responses remains poorly understood. Here, we combined chemogenetics, pharmacological fMRI (ph-fMRI), and proton magnetic resonance spectroscopy (1H-MRS/fMRS) at 7 T to investigate the temporal evolution of metabolic and hemodynamic responses in the rat motor cortex. MethodsFemale Fischer rats received viral injections in the motor cortex to express either a pan-neuronal hM3D(Gq) DREADD construct (hSyn-hM3Dq) or an interneuron-targeted construct (hDlx-hM3Dq). Ph-fMRI, fMRS, and 1H-MRS measurements were performed before, during, and following systemic administration of clozapine-N-oxide (CNO, 1 mg/kg). Functional MRS was acquired during the acute response phase (0-60 min post-injection), while conventional 1H-MRS measurements were obtained at a delayed time point (70 min post-injection). ResultsChemogenetic modulation produced robust and opposing hemodynamic responses. Pan-neuronal activation elicited focal positive BOLD responses (+3.5 {+/-} 1.5%), whereas interneuron-targeted activation generated significant negative BOLD responses (-3.3 {+/-} 0.8%). In contrast, acute fMRS measurements revealed no significant changes in Glx or GABA concentrations during the first hour following CNO administration, despite the presence of strong hemodynamic effects. However, delayed metabolic alterations were detected 70 min after CNO administration. Animals expressing the pan-neuronal construct exhibited significant increases in GABA (+14.4%) and total choline compounds (+57.8%), whereas interneuron-targeted animals displayed reductions in several metabolites, including Glx (-15.6%), total NAA (-16.9%), glucose (-25.9%), and total creatine (-25.4%). ConclusionChemogenetic perturbation of cortical circuits produced robust hemodynamic responses but more subtle and temporally complex metabolic effects. The absence of detectable acute changes in Glx and GABA despite strong BOLD responses, together with the emergence of delayed neurochemical alterations, highlights the challenges of interpreting metabolic signals in relation to circuit activity.

White matter lesion (WML) identification, assessment, and characterization using magnetic resonance imaging (MRI) are fundamental for diagnosis and monitoring of multiple sclerosis (MS). Portable ultra-low field (pULF) MRI at 64 millitesla (mT) has been shown to visualize WML with at least one dimension greater than 4 mm. An automated WML segmentation tool catered to pULF-MRI can provide standardized and accurate quantitative measurements of WML volume. In this study, we sought to investigate and compare the accuracy of machine-learning (ML) and deep-learning (DL) pULF MRI segmentation tools. Same-day paired pULF (64mT) and high-field (HF, 3T) MRI scans from 84 adults with MS or suspected-MS (mean age {+/-} SD: 48 {+/-} 13, 62 females) included T2-FLAIR and T1w images. Reference WML segmentations were manually annotated on pULF T2-FLAIR for all scans, with WML confirmed with registered HF T2-FLAIR. HF reference WML segmentations were created. Four automated segmentation methods were applied to pULF scans: Method for Inter-Modal Segmentation Analysis (MIMoSA), an ML algorithm trained on HF WML masks; WMH-SynthSeg, a convolutional neural network model with flexible segmentation capabilities across field strengths and resolution; nnU-Net, a DL algorithm trained on pULF reference WML masks; and Pseudo-Label Assisted nnU-Net (PLAn), a DL algorithm pre-trained on HF reference WML masks and refined with 64mT reference WML masks. Two models were trained with nnU-Net, one using T2-FLAIR images only (nnU-Net-FL) and one using T1w and T2-FLAIR images (nnU-Net-FL/T1). The same was done with PLAn, creating PLAn-FL and PLAn-FL/T1. The six automated WML segmentation outputs were compared to the manual segmentations to determine Dice Similarity Coefficient (DSC) scores. Associations of WML volume estimates with clinical measures were investigated. DSC scores with pULF reference WML masks from PLAn-FL (DSC mean {+/-} SD: 0.50 {+/-} 0.24) outperformed MIMoSA (0.24 {+/-} 0.20, p < 0.0001), WMH-SynthSeg (0.30 {+/-} 0.18, p < 0.0001), nnU-Net-FL (0.41 {+/-} 0.24, p < 0.0001), and nnU-Net-FL/T1 (0.41 {+/-} 0.26, p = 0.0004). Worse Expanded Disability Status Scale (EDSS) and Scripps Neurologic Rating Scale (SNRS) scores were correlated with higher WML volumes in the pULF and HF reference masks. They were also correlated with WML volumes derived from WHM-SynthSeg, nnU-Net-FL, nnU-Net-FL/T1, PLAn-FL, and PLAn-FL/T1, but not MIMoSA. After adjusting for age, WHM-SynthSeg, nnU-Net FL, nnU-Net-FL/T1, PLAn-FL, and PLAn-FL/T1 had significant associations with EDSS and SNRS scores. nnU-Net and PLAn performed best in segmenting WML on pULF-MRI at 64 mT, providing accurate quantitative estimates of WML burden. Moreover, WML volumes estimated by these algorithms were associated with clinical measures of disability, underscoring their utility for reflecting clinical and radiological disease severity. Given pULF-MRI's mobility and lower cost, these findings highlight its relevance in clinical trials, particularly in involving more participants who face logistical constraints and barriers.

The human thalamus is composed of multiple nuclei that differ in structure and function. From early development onwards, these nuclei form reciprocal, nucleus-specific connections with the cerebral cortex, contributing to sensory and cognitive processing. In childhood and adolescence, a key period of neurocognitive development, these connections undergo widespread refinement, yet how developmental trajectories of thalamocortical connections vary across nuclei remains unknown. Here, we leveraged the Human Connectome Project in Development dataset (HCP-D, N = 604, age range 8-21) and segmented 10 thalamic nuclei using a segmentation approach optimized for intrathalamic contrast. Applying probabilistic tractography, we reconstructed nucleus-specific thalamocortical connections and charted their maturational profiles based on changes in fractional anisotropy (FA) using generalized additive models. We found FA to increase in thalamocortical connections, with nucleus-specific variation in temporal profiles and magnitude of age effects. Connections of core-cell-rich, sensory-projecting nuclei, such as the lateral geniculate nucleus, showed earlier maturational plateaus, whereas matrix-cell-rich, association-projecting nuclei, such as ventral anterior nucleus, showed more sustained maturation. This links maturational heterochronicity to thalamic organization of cell distribution and connectivity embedding. In parallel, functional thalamocortical connectivity decreased with age, with FA and functional connectivity age effects coupled in nucleus-connections showing prolonged maturation. Finally, concordant age effects in connectivity and nucleus volumes suggest that intra-nucleus remodeling may support refinement of structural connections while reducing thalamocortical functional synchrony. Together, our work reveals that thalamocortical maturation is anchored in the developmental and organizational heterogeneity of thalamic nuclei, offering a framework for understanding how diverse thalamic nuclei contribute to neurocognitive development.

Background: Norepinephrine (NE) released from locus coeruleus (LC) projections regulates astrocyte structure and function through adrenergic receptor signaling. We previously showed that increasing noradrenergic tone with the NE reuptake inhibitor desipramine increases astrocyte ramification in the molecular layer of the dentate gyrus. However, whether tonic LC-derived noradrenergic tone is required to maintain astrocyte morphological complexity in vivo, and whether {beta}-adrenergic receptor activation is the effector pathway, remained unclear. Methods: Adult male C57BL/6J mice received DSP-4 (50 mg/kg X 3 days i.p.), a selective LC neurotoxin, with or without concurrent isoproterenol that continued for 21 additional days post cessation of DSP-4 treatment (ISO; 2 mg/kg/day X 24 days), or saline (n = 4 mice per group). Animals were sacrificed 22 days after the final DSP-4 injection. Noradrenergic denervation was confirmed by dopamine {beta}-hydroxylase (DBH) immunostaining. GFAP-immunostained astrocytes in the molecular layer of the dentate gyrus were morphologically characterized using Sholl analysis. Astrocyte density was quantified by SOX9 immunostaining. Results: DSP-4 produced >83% reduction in DBH fiber coverage in the molecular layer. Sholl analysis revealed significant reductions in astrocyte branching complexity in both treatment groups, with the reductions concentrated at distances of 5-15 m from the soma. The maximum number of intersections was also significantly reduced in both groups. Unexpectedly, ISO did not rescue morphological complexity. While DSP-4 alone did not alter astrocyte density, as measured by the number of SOX9-expressing astrocytes, DSP-4+ISO increased SOX9-positive cell density, dissociating the effects of adrenergic signaling on morphology from those on cell numbers. Conclusions: LC-derived noradrenergic tone is required for the maintenance of astrocyte arbour complexity in the dentate gyrus molecular layer. {beta}-adrenergic receptor activation alone is insufficient to restore structural integrity following noradrenergic denervation, yet promotes astrocyte density independently of structural remodeling. These findings have implications for understanding how LC neurodegeneration in Alzheimer's disease and depression may compromise hippocampal astrocyte structure and function.

The diffusion tensor image analysis along the perivascular space (DTI-ALPS) index is increasingly used as a non-invasive MRI biomarker of glymphatic and perivascular function, yet the anatomical validity and measurement stability of the metric remain incompletely characterised. Using diffusion MRI data from 850 healthy young adults and 150 healthy ageing participants from the Human Connectome Project, I systematically evaluated the influence of region-of-interest (ROI) placement and ventricular anatomy on ALPS measurements. Reference ALPS implementations demonstrated substantial hemispheric variability, with a median left-right difference of 12.5% and marked asymmetry in the underlying numerator and denominator tensor components. A two-stage optimisation framework incorporating fibre-pool alignment, hemispheric symmetry, component stability, and directional purity identified anatomically improved ROI configurations that significantly increased fibre specificity and reduced measurement variability in independent validation cohorts. Despite these improvements, residual hemispheric asymmetry persisted, suggesting an intrinsic anatomical contribution to ALPS variability. In the healthy ageing cohort, ventricular volume emerged as the strongest predictor of ALPS, explaining substantially more variance than chronological age. Voxel-wise deformation-based morphometry demonstrated that lower ALPS values were associated with ventricular and periventricular expansion, while optimisation increased coupling between ALPS and ventricular anatomy. Collectively, these findings indicate that ALPS measurements are strongly influenced by ROI definition, ventricular morphology, and surrounding periventricular tissue architecture. Rather than functioning as a direct measure of glymphatic transport in isolation, ALPS appears to represent a composite anatomical diffusion biomarker shaped by both methodological implementation and underlying neuroanatomy. These results provide a framework for improving methodological standardisation and interpretation of ALPS measurements in future neuroimaging studies.

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

The lateral grasp network, responsible for translating visual properties of an object to execution of a motor act, is comprised of the anterior intraparietal area (AIP), area F5, and the primary motor cortex (M1). Non-human primate studies of F5 have shown that it encodes a wide range of hand positions and object properties. Human studies in F5 human homologue, the inferior frontal gyrus (IFG), have leveraged the ability of this area to encode grasp-object pairs for the purposes of Brain Machine Interface (BMI) control. However, whether modulation is driven by grasp, object, or the interaction between grasp and object is unclear. In the present study, sixty-four features were recorded from IFG during a motor visualization task where grasp and object were varied. Grasp was found to be the predominant factor driving modulation of IFG signals. Object was found to only be weakly represented in neural data. However, object contribution peaked earlier than grasp contribution, indicating early integration of object information. Grasp-object interactions were also found to have a significant impact. Cortical separation between grasping conditions varied based on the object presented. In addition, subspace analysis showed that the underlying neural population structure associated with each object type was significantly different from one another. Despite the impact of object type, the present study suggests that due to the significantly larger impact of grasp, BMI decoders can be used to decode grasp with above chance accuracy across a variety of grasp-object pairs.

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