Biology subjects

Gore, J. C.

Publications and source records attributed to Gore, J. C..

At least 19 recordsLinked to original sources

bioRxiv2026

Functional connectivity gradients depend on cortical sampling position and brain state

Functional-connectivity analyses often treat signals sampled from nearby cortical positions as interchangeable, despite anatomical and hemodynamic transitions at the gray-white boundary. We tested whether sampling position constitutes a state-sensitive dimension of macroscale functional organization. In 176 Human Connectome Project young adults with four 7 T resting-state and four movie-watching runs, BOLD time series were sampled from subject-specific midthickness and gray-white-boundary surfaces, summarized across 400 cortical parcels, and embedded in a common functional-gradient space. Movie viewing reduced principal-gradient separation between surfaces, but this effect was spatially heterogeneous: Visual, Limbic and Default networks converged, whereas Salience/ventral-attention cortex differentiated. Shapley decomposition and counterfactual analyses showed that the state change reflected coordinated reconfiguration of both surface representations rather than one surface approaching the other. Changes in the original connectivity profiles tracked gradient changes, indicating that the result was not solely introduced by embedding. Both surfaces also exhibited stimulus-locked intersubject functional connectivity during movies. However, stimulus-shared separation captured only part of movie-state organization and did not explain the movie-minus-rest change. Finally, in 172 matched participants, resting-state separation maps generalized from 7 T to 3 T, whereas absolute magnitude and cross-field individual ranking were less stable. These findings establish cortical sampling position as an interpretable measurement dimension of functional-connectivity geometry. Its spatial organization is reproducible across acquisitions, but its magnitude and state dependence vary, emphasizing that where BOLD signals are sampled relative to the cortical boundary can shape conclusions about macroscale brain organization.

neuroscience↗

bioRxiv2026

White-Matter BOLD Encoding Beyond Marginal Connectivity

Functional MRI studies have traditionally focused on gray matter, whereas white-matter BOLD signals have often been treated as weak or artifactual. Recent work suggests that white-matter BOLD fluctuations contain reproducible functional information, but most gray-to-white matter analyses rely on marginal functional connectivity, which cannot separate pairwise coupling from shared variance among distributed cortical systems. Here, we used a multivariate cortical encoding framework to test whether spontaneous white-matter BOLD activity can be predicted from distributed cortical gray-matter activity and whether this predictive structure reveals organization beyond marginal connectivity. Resting-state fMRI data from 81 Human Connectome Project young adult participants were analyzed using a strict white-matter mask with no overlap with cortical predictors. For each white-matter voxel, time series from 400 Schaefer cortical parcels were used to predict held-out white-matter BOLD signals with nested leave-one-run-out ridge regression. Cortical activity modestly but reliably predicted white-matter BOLD dynamics, demonstrating consistent cross-validated prediction accuracy across a broad spatial extent of the white matter. Ridge beta fingerprints strongly recapitulated marginal functional connectivity fingerprints, indicating a shared functional backbone, but their first gradients diverged reproducibly. This beta-FC divergence axis organized FC-adjusted prediction residuals and remained robust after controlling for gray-matter proximity, mask-boundary distance, white-matter prevalence, temporal signal variability, spatial coordinates, and spatial autocorrelation. The high-divergence end showed relatively low marginal FC but high FC-adjusted prediction residuals and was enriched for posterior thalamic/optic-radiation and posterior corona-radiata anatomy. These findings suggest that multivariate cortical encoding reveals a tract-organized dimension of white-matter functional coupling not captured by pairwise connectivity alone.

neuroscience↗

bioRxiv2026

Charting Cervical Spinal Cord Morphometry Across the Lifespan

Spinal cord morphometry provides essential biomarkers of neurological health, but clinical interpretations are confounded by inter-subject variability and a lack of normative references across the full human lifespan. We address this gap by generating the first comprehensive lifespan charts for cervical spinal cord morphometry. We leveraged 30 population-based brain MRI datasets, aggregating 78,269 scans from 41,042 individuals (ages 0-100) whose imaging protocols included cervical cord coverage. To overcome contrast variability, we employed a state-of-the-art contrast-agnostic deep learning segmentation method, extracting cross-sectional area (CSA), anteroposterior (AP) and right-left (RL/transverse), and shape indices (compression ratio, eccentricity, and solidity) from C1 to C7. Normative trajectories were modeled using Generalized Additive Models for Location, Scale, and Shape (GAMLSS). The resulting charts reveal distinct non-linear lifespan changes: rapid growth through childhood and adolescence, peak maturation occurring in early-to-mid adulthood (e.g., mid-30s for CSA), followed by gradual decreases. Significant regional variations along the cervical cord and consistent sex differences (males > females for size metrics) were quantified. Spinal cord trajectories showed strong temporal coupling with brain white matter and brainstem volumes, suggesting integrated CNS development and aging. These lifespan charts provide a robust normative framework, enabling age- and sex-specific centile scoring of individual spinal cord morphometry. This resource offers a critical tool for differentiating typical variation from pathological changes, enhancing the clinical utility of spinal cord MRI in studies of development and neurodegeneration.

neuroscience↗

bioRxiv2026

Relative Hemodynamic Timing in Human White Matter

Hemodynamic lag in white matter (WM) remains poorly understood despite its relevance to neurovascular health. We developed Local Propagation Mapping to quantify the spatiotemporal architecture of relative hemodynamic timing within WM. In young adults, WM lag architecture was reliable, aligned with venous anatomy, and reconfigured during working-memory task engagement; the magnitude of macroscopic lag modulation was associated with cognitive performance. Across aging, resting-state WM lag showed tract-specific bidirectional shifts and increased spatial fragmentation, with partial overlap with task-sensitive systems observed in young adults. Static baseline markers did not significantly mediate age-related cognitive differences, suggesting that aging effects may not operate through a simple resting-state pathway. Together, these findings establish relative WM lag as an informative dimension of neurovascular regulation and motivate a baseline-load hypothesis for future studies of cognitive aging.

neuroscience↗

bioRxiv2026

Analytic Bounds on GAMLSS Model Variability of Normative White Matter Brain Charts

Brain charts, or normative models of quantitative neuroimaging measures, can identify trajectories of brain development and abnormalities in groups and individuals by leveraging large populations. Recent work has extended these brain charts to model microstructural and macrostructural features of white matter. Assessments of variance for these brain charts are necessary to determine whether the models being used for these data are stable. We implement an analytic approach to characterize variability of the parameters in previously released brain charts created using the generalized additive models for location, scale, and shape (GAMLSS) framework. Additionally, we empirically validate the accuracy of each analytic model through a comparison to a bootstrapping approach from 0.2 to 90 years of age. We find that across all models, the analytic coefficient of variation (COV) remains below 5% for ages greater than 0.25 years, with the maximum empirical observed COV reaching 7% at 0.2 years of age. Further, the empirical assessment shows high agreement with the analytic assessment, with COV estimates averaged across the lifespan for all models having a Pearson correlation coefficient of 0.776 and a mean difference of 4 x 10-4. Both methods exhibit volume and surface area as the features with the largest average COV for the majority of tracts. However, the analytic assessment yields axial diffusivity as the feature most frequently having the smallest COV, whereas the corresponding feature for the empirical assessment is average length. These results suggest that the analytic approach overestimates model stability for WM brain charts when the COV is low and that the validation method is suitable for assessing whether GAMLSS models are unstable.

bioengineering↗

bioRxiv2025

White-Matter BOLD Mediates Time-Varying Cortico-Cortical Functional Connectivity

Functional connectivity (FC) measurements in the brain using BOLD fMRI have largely focused on correlations between gray-matter (GM) BOLD signals, ignoring the possible relevance of white-matter (WM) in delineating neural networks. We first employed a tract-informed mediation framework to test whether WM pathways contribute indirect, bundle-specific effects to cortico-cortical coupling. Using resting-state fMRI data from the Human Connectome Project, we quantified pathway-level mediation effects across GM-WM-GM units and found that WM BOLD signals significantly mediated GM-GM associations, with clear tract-dependent heterogeneity. Building upon this, we examined how dynamic features of WM BOLD signals relate to time-varying intra-cortical FC. We found that temporal variability of WM signals, rather than their mean amplitudes, more closely tracked fluctuations in GM-GM dynamic connectivity, with correlations reaching approximately 0.4 across specific tracts. Together, these results indicate that WM BOLD signals are related to how cortical regions interact, underscoring their integral role in large-scale brain network organization.

neuroscience↗

bioRxiv2025

Lifespan Trajectories of Asymmetry in White Matter Tracts

Asymmetry in white matter is believed to give rise to the brains capacity for specialized processing and is involved in the lateralization of various cognitive processes, such as language and visuo-spatial reasoning. Although studies of white matter asymmetry have been previously documented, they have often been constrained by limited age ranges, sample sizes, or the scope of the tracts and structural features examined. While normative lifespan charts for brain structures are emerging, comprehensive charts detailing white matter asymmetries across numerous pathways and diverse structural measures have been notably absent. This study addresses this gap by leveraging a large-scale dataset of 35,120 typically developing and aging individuals, ranging from 0 to 100 years of age, from 50 primary neuroimaging studies. We generated comprehensive lifespan trajectories for 30 lateralized association and projection white matter tracts, examining 6 distinct microstructural and macrostructural features of these pathways. Our findings reveal that: (1) asymmetries are widespread across the brains white matter and are present in all 30 pathways; (2) for a given pathway, the degree and direction of asymmetry differ between features of tissue microstructure and pathway macrostructure; (3) asymmetries vary across and within pathway types (association and projection tracts); and (4) these asymmetries are not static, following unique trajectories across the lifespan, with distinct changes during development, and a general trend of becoming more asymmetric with increasing age (particularly in later adulthood) across pathways. This study represents the most extensive characterization of white matter asymmetry across the lifespan to date, charting how lateralization patterns emerge, mature, and change throughout life. It provides a foundational resource for understanding the principles of white matter organization from early to late life, its relation to functional specialization and inter-individual variability, and offers a key reference for interpreting deviations during healthy development and aging as well as those associated with clinical populations.

neuroscience↗

bioRxiv2025

Detection of Region-specific Fiber Damage within Injured Spinal Cord Using Advanced Diffusion MRI

This study aimed to evaluate diffusion parameters derived from diffusion tensor imaging (DTI) and spherical mean technique (SMT) for detecting region-specific, fine-grained tissue damage and white matter (WM) tract disruptions following spinal cord injury (SCI). Diffusion MRI data were acquired from the cervical spinal cord of monkeys before and after a unilateral dorsal column lesion at the C5 level, using a 9.4T scanner. Parametric maps derived from DTI and SMT effectively detected regional fiber damage around 16 weeks post-injury. Post-mortem silver staining served as the ground truth for assessing region-specific fiber damage. Diffusion MRI maps aligned well with histological measures and captured the severity of WM damage at the lesioned segment (in an order of dorsal > ventral > lateral WM tracts) and along the dorsal column tract across segments (in an order of lesion center > rostral > caudal). Among the diffusion parameters, fractional anisotropy (FA), axonal volume fraction (Vax), radial diffusivity (RD), and extra axonal transverse diffusivity (Dex) showed most significant changes at and around the lesion site where severe tissue damage occurred. FA, Vax, and axial diffusivity (AD) exhibited marked changes in dorsal column proximal to the lesion center, where moderate axonal damage occurred. Additionally, AD and FA showed the greatest sensitivity (true positive rate) and specificity (true negative rate) to mild fiber disruption and demyelination in regions distal to the lesion. Overall, FA provided the highest sensitivity and specificity for detecting fiber degeneration and demyelination, while Vax demonstrated the strongest spatial correlation with histologic markers of regional fiber damage. The combination of DTI and SMT thus offers reliable biomarkers for assessing SCI.

neuroscience↗

bioRxiv2025

Early Detection of Neuroinflammation and White Matter Damage Following Dorsal Spinal Nerve Root Sectioning in a Nonhuman Primate Model

PurposeDorsal rhizotomy, or spinal dorsal nerve root lesioning, is a surgical procedure used to treat intractable nerve pain by selectively severing sensory afferent nerve roots. This study aimed to evaluate whether multiparametric MRI, including diffusion tensor imaging (DTI), quantitative magnetization transfer (qMT), and chemical exchange saturation transfer (CEST), can sensitively detect structural and biochemical changes in the intact spinal cord following a focal dorsal nerve root section in a non-human primate model. MethodsIn four squirrel monkeys, unilateral dorsal nerve roots at cervical segments C4 and C5 were surgically transected. MRI data were collected using a 9.4 T scanner with a custom saddle-shaped transmit-receive quadrature coil before and one week after lesioning. DTI-derived fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD); qMT-derived pool size ratio (PSR); and CEST and nuclear Overhauser enhancement (NOE) effects were quantified across seven spinal cord regions of interest (ROIs). CEST and NOE effects were extracted using five-pool Lorentzian fitting of Z-spectra. ResultsAt the lesioned dorsal nerve root bundles, FA, PSR, and NOE (-1.6 ppm) values decreased, while RD and CEST (3.5 ppm) increased, consistent with fiber degeneration, demyelination, and inflammation. Similar, though less pronounced, changes were observed in the dorsal root entry zone, particularly within the first week post-lesion. ConclusionMultiparametric MRI enables region-specific detection of early spinal cord pathology as soon as one week following dorsal nerve root injury. These findings support its potential as a noninvasive tool for monitoring secondary degeneration due to spinal nerve damage and for evaluating outcomes of therapeutic interventions.

neuroscience↗

bioRxiv2025

BrainVAE: Exploring the role of white matter BOLD in preclinical Alzheimer disease classification

INTRODUCTIONLike gray matter (GM), white matter (WM) BOLD functional signals change in preclinical AD. However, the potential of WM BOLD for identifying preclinical AD remains underexplored. METHODSWe developed BrainVAE, a transformer-based variational autoencoder with interpretability, to classify preclinical AD and normal controls using resting-state fMRI data. We benchmarked BrainVAE against nine alternative models under three input configurations: WM-only, GM-only, and combined WM+GM. Interpretability analysis was also performed to investigate each brain regions contribution to the classification task. RESULTSBrainVAE outperformed other models and performed well (accuracy = 83.42%, F1-score = 91.62%, AUC = 64.50%) using the combined input compared to WM-only and GM-only. Specific WM bundles--including corpus callosum, fornix, and corticospinal tract--were among the most influential features contributing to the classification. DISCUSSIONIncorporating WM BOLD signals improves the distinction of preclinical AD from controls, underscoring the potential role of WM BOLD features for detecting early-stage AD. HighlightsO_LIBrainVAE integrates white and gray matter BOLD signals for classification of pre-AD and controls. C_LIO_LIBrainVAE achieves high accuracy (83.42%) and F1-score (91.62%) in identifying pre-AD. C_LIO_LIModels using combined WM+GM inputs outperform those using WM-only or GM-only inputs. C_LIO_LIWM regions, such as corpus callosum and fornix, contribute significantly to model predictions. C_LIO_LIResults suggest WM BOLD signals are informative markers for early AD detection. C_LI

neuroscience↗

bioRxiv2025

White matter microstructure and macrostructure brain charts across the human lifespan

Normative reference charts are widely used in healthcare, especially for assessing the development of individuals by benchmarking anatomic and physiological features against population trajectories across the lifespan. Recent work has extended this concept to gray matter morphology in the brain, but no such reference framework currently exists for white matter (WM) even though WM constitutes the essential substrate for neuronal communication and large-scale network integration. Here, we present the first comprehensive WM brain charts, which describe how microstructural and macrostructural features of WM evolve across the lifespan, by leveraging over 35,120 diffusion MRI scans from 50 harmonized studies. Using generalized additive models for location, scale, and shape (GAMLSS), we estimate age- and sex-stratified trajectories for 72 individual white matter pathways, quantifying both tract-specific microstructural and morphometric features. We demonstrate that these WM brain charts enable four important applications: (1) defining normative trajectories of WM maturation and decline across distinct pathways, (2) identifying previously uncharacterized developmental milestones and spatial gradients of tract maturation, (3) detecting individualized deviations from normative patterns with clinical relevance across multiple neurological disorders, and (4) facilitating standardized, cross-study centile scoring of new datasets. By establishing a unified, interpretable reference framework for WM structure, these brain charts provide a foundational metric for research and clinical neuroscience. The accompanying open-access trajectories, centile scoring tools, and harmonization methods facilitate precise mapping of WM development, aging, and pathology across diverse populations. We release the brain charts and provide an out-of-sample alignment process as a Docker image: https://zenodo.org/records/17561821.

neuroscience↗

bioRxiv2025

The relationship of white matter tract orientation to vascular geometry in the human brain

The white matter of the human brain exhibits highly ordered anisotropic structures of both axonal nerve fibers and cerebral vasculature. Separately, the anisotropic nature of white matter axons and white matter vasculature have been shown to cause an orientation dependence on various MRI contrasts used to study the structure and function of the brain; however, little is known of the relationship between axonal and vascular orientations. Thus, the aim of this study is to compare the orientation between nerve fibers and vasculature within the white matter. To do this, we use diffusion MRI and susceptibility weighted imaging acquired in the same healthy young adult volunteers and analyze the alignment between white matter fibers and blood vessels in different brain regions, and along different pathways, to determine the degree of alignment between these structures. We first describe vascular orientation throughout the brain and note several regions with consistent orientations across individuals. Next, we find that vasculature does not necessarily align with the dominant direction of white matter in many regions, but, due to the presence of crossing fiber populations, does align with at least some white matter within each MRI voxel. Even though the spatial patterns of blood vessels run in parallel to several white matter tracts, they do not do so along the entire pathway, nor for all pathways, suggesting that vasculature does not supply/drain blood in a tract-specific manner. Overall, these findings suggest that the vascular architecture within the white matter is closely related to, but not the same as, the organization of neural pathways. This study contributes to a better understanding of the microstructural arrangement of the brain and may have implications for interpreting neuroimaging data in health and disease.

neuroscience↗

bioRxiv2024

Assessing White Matter Engagement in Brain Networks through Functional and Structural Connectivity Mapping

Understanding the intricate interplay between gray matter (GM) and white matter (WM) is crucial for deciphering the complex activities of the brain. While diffusion tensor imaging (DTI) has advanced the mapping of these structural pathways, the relationship between structural connectivity (SC) and functional connectivity (FC) remains inadequately understood. This study addresses the need for a more integrative approach by mapping the importance of the inter-GM functional link to its structural counterparts in WM. This mapping yields a spatial distribution of engagement that is not only highly reproducible but also aligns with direct structural, functional, and bioenergetic measures within WM, illustrating a notable interdependence between the function of GM and the characteristics of WM. Additionally, our research has uncovered a set of unique engagement modes through a clustering analysis of window-wise engagement maps, highlighting the dyanmic nature of the engagement. The engagement along with their temporal variations revealed significant differences across genders and age groups. These findings suggest the potential of WM engagement as a biomarker for neurological and cognitive conditions, offering a more nuanced understanding of individualized brain activity and connectivity patterns.

neuroscience↗

bioRxiv2023

Influence of preprocessing, distortion correction and cardiac triggering on the quality of diffusion MR images of spinal cord

Diffusion MRI of the spinal cord (SC) is susceptible to geometric distortion caused by field inhomogeneities, and prone to misalignment across time series and signal dropout caused by biological motion. Several modifications of image acquisition and image processing techniques have been introduced to overcome these artifacts, but their specific benefits are largely unproven and warrant further investigations. We aim to evaluate two specific aspects of image acquisition and processing that address image quality in diffusion studies of the spinal cord: susceptibility corrections to reduce geometric distortions, and cardiac triggering to minimize motion artifacts. First, we evaluate 4 distortion preprocessing strategies on 7 datasets of the cervical and lumbar SC and find that while distortion correction techniques increase geometric similarity to structural images, they are largely driven by the high-contrast cerebrospinal fluid, and do not consistently improve the geometry within the cord nor improve white-to-gray matter contrast. We recommend at a minimum to perform bulk-motion correction in preprocessing and posit that improvements/adaptations are needed for spinal cord distortion preprocessing algorithms, which are currently optimized and designed for brain imaging. Second, we design experiments to evaluate the impact of removing cardiac triggering. We show that when triggering is foregone, images are qualitatively similar to triggered sequences, do not have increased prevalence of artifacts, and result in similar diffusion tensor indices with similar reproducibility to triggered acquisitions. When triggering is removed, much shorter acquisitions are possible, which are also qualitatively and quantitatively similar to triggered sequences. We suggest that removing cardiac triggering for cervical SC diffusion can be a reasonable option to save time with minimal sacrifice to image quality.

neuroscience↗

bioRxiv2023

White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan

Characterizing how, when and where the human brain changes across the lifespan is fundamental to our understanding of developmental processes of childhood and adolescence, degenerative processes of aging, and divergence from normal patterns in disease and disorders. We aimed to provide detailed descriptions of white matter pathways across the lifespan by thoroughly characterizing white matter microstructure, white matter macrostructure, and morphology of the cortex associated with white matter pathways. We analyzed 4 large, high-quality, publicly-available datasets comprising 2789 total imaging sessions, and participants ranging from 0 to 100 years old, using advanced tractography and diffusion modeling. We first find that all microstructural, macrostructural, and cortical features of white matter bundles show unique lifespan trajectories, with rates and timing of development and degradation that vary across pathways - describing differences between types of pathways and locations in the brain, and developmental milestones of maturation of each feature. Second, we show cross-sectional relationships between different features that may help elucidate biological changes occurring during different stages of the lifespan. Third, we show unique trajectories of age-associations across features. Finally, we find that age associations during development are strongly related to those during aging. Overall, this study reports normative data for several features of white matter pathways of the human brain that will be useful for studying normal and abnormal white matter development and degeneration.

neuroscience↗

bioRxiv2023

Small volume blood-brain barrier opening in macaques with a 1 MHz ultrasound phased array

Focused ultrasound blood-brain barrier (BBB) opening is a promising tool for targeted delivery of therapeutic agents into the brain. The volume of opening determines the extent of therapeutic administration and sets a lower bound on the size of targets which can be selectively treated. We tested a custom 1 MHz array transducer optimized for cortical regions in the macaque brain with the goal of achieving small volume openings. We integrated this device into a magnetic resonance image guided focused ultrasound system and demonstrated twelve instances of small volume BBB opening with average opening volumes of 59 {+/-} 37 mm3 and 184 {+/-} 2 mm3 in cortical and subcortical targets, respectively. We developed real-time cavitation monitoring using a passive cavitation detector embedded in the array and characterized its performance on a bench-top flow phantom mimicking transcranial BBB opening procedures. We monitored cavitation during in-vivo procedures and compared cavitation metrics against opening volumes and safety outcomes measured with FLAIR and susceptibility weighted MR imaging. Our findings show small BBB opening at cortical targets in macaques and characterize the safe pressure range for 1 MHz BBB opening. Additionally, we used subject-specific simulations to investigate variance in measured opening volumes and found high correlation (R2 = 0.8577) between simulation predictions and observed measurements. Simulations suggest the threshold for 1 MHz BBB opening was 0.53 MPa. This system enables BBB opening for drug delivery and gene therapy to be targeted to more specific brain regions.

bioengineering↗

bioRxiv2023

Whole-brain, gray and white matter time-locked functional signal changes with simple tasks and model-free analysis

Recent studies have revealed the production of time-locked blood oxygenation-level dependent (BOLD) functional MRI (fMRI) signals throughout the entire brain in response to a task, challenging the idea of sparse and localized brain functions, and highlighting the pervasiveness of potential false negative fMRI findings. In these studies, whole-brain refers to gray matter regions only, which is the only tissue traditionally studied with fMRI. However, recent reports have also demonstrated reliable detection and analyses of BOLD signals in white matter which have been largely ignored in previous reports. Here, using model-free analysis and simple tasks, we investigate BOLD signal changes in both white and gray matters. We aimed to evaluate whether white matter also displays time-locked BOLD signals across all structural pathways in response to a stimulus. We find that both white and gray matter show time-locked activations across the whole-brain, with a majority of both tissue types showing statistically significant signal changes for all task stimuli investigated. We observed a wide range of signal responses to tasks, with different regions showing very different BOLD signal changes to the same task. Moreover, we find that each region may display different BOLD responses to different stimuli. Overall, we present compelling evidence that the whole brain, including both white and gray matter, show time-locked activation to multiple stimuli, not only challenging the idea of sparse functional localization, but also the prevailing wisdom of treating white matter BOLD signals as artefacts to be removed.

neuroscience↗

bioRxiv2022

Superficial white matter across the lifespan: volume, thickness, change, and relationship with cortical features

Superficial white matter (SWM) represents a significantly understudied part of the human brain, despite comprising a large portion of brain volume and making up a majority of cortical structural connections. Using multiple, high-quality, datasets with large sample sizes (N=2421, age range 5-100) in combination with methodological advances in tractography, we quantified features of SWM volume and thickness across the brain and across the lifespan. We address four questions: (1) How does U-fiber volume change with age? (2) What does U-fiber thickness look like across the brain? (3) How does SWM thickness change with age? (4) Are there relationships between SWM thickness and cortical features? Our main findings are that (1) SWM volume shows unique volumetric trajectories with age that are distinct from gray matter and other white matter trajectories; (2) SWM thickness varies across the brain, with patterns robust across individuals and across the population at the region-level and vertex-level; (3) SWM shows nonlinear changes across the lifespan that vary across regions; and (4) SWM thickness is associated with cortical thickness and curvature. For the first time, we show that SWM volume follows a similar trend as overall white matter volume, peaking at a similar time in adolescence, leveling off throughout adulthood, and decreasing with age thereafter. Notably, the relative fraction of total brain volume of SWM continuously increases with age, and consequently takes up a larger proportion of total white matter volume, unlike the other tissue types that decrease with respect to total brain volume. This study represents the first characterization of SWM features across the lifespan and provides the background for characterizing normal aging and insight into the mechanisms associated with SWM development and decline.

neuroscience↗