Biology subjects

Tardif, C. L.

Publications and source records attributed to Tardif, C. L..

At least 19 recordsLinked to original sources

bioRxiv2026

The Canadian Pediatric Imaging Platform (C-PIP) Reference Sample: Neuroimaging Protocol and Cross-site Validation for Harmonized Multimodal Pediatric Imaging

Understanding how the human brain matures from infancy through adolescence is essential for identifying factors that influence health outcomes. Magnetic resonance imaging (MRI) provides powerful tools for characterizing structural, microstructural, functional, and metabolic aspects of brain development; however, many pediatric imaging studies are constrained by small sample sizes, limited geographic diversity, lack of longitudinal measurement, restricted age ranges, and heterogeneous acquisition protocols. While recent large-scale neuroimaging consortia have begun to address these challenges, such resources remain limited in the Canadian context, creating a critical gap. The Canadian Pediatric Imaging Platform (C-PIP) has developed a multisite neuroimaging framework across three of Canada's largest pediatric hospitals: Alberta Children's Hospital (Calgary), Centre Hospitalier Universitaire Sainte-Justine (Montreal), and the Hospital for Sick Children (Toronto). These three sites were united through a national initiative, leveraging high-performance MRI systems to accelerate Canadian neurodevelopmental research. In addition, C-PIP has implemented a centralized data sharing infrastructure to facilitate open science and collaborative research across institutions. Here, we describe the development and implementation of a multimodal MRI acquisition protocol designed to support multimodal longitudinal studies of typical and atypical brain development spanning infancy through adolescence. Within-site stability and cross-site stability of C-PIP core MRI sequences were evaluated using a travelling-participant study. The C-PIP MRI protocol establishes a harmonized, multisite imaging framework that supports large-scale investigations of pediatric brain development and disorders.

neuroscience↗

bioRxiv2026

Dose-dependent myelin g-ratio alterations in the white matter of 16p11.2 copy number variations

Copy number variations (CNVs) at the 16p11.2 locus are major genetic risk factors for neurodevelopmental conditions and drive reciprocal alterations in cerebral white matter structure and connectivity. However, whether these alterations reflect differences in the axonal or myelin compartments remains unresolved with conventional diffusion MRI. We combined diffusion MRI with magnetization transfer saturation mapping across two ComBat-harmonized cohorts comprising 80 controls, 26 16p11.2 deletion carriers, and 13 duplication carriers. We quantified axonal volume, myelin volume, and aggregate g-ratio of white matter tracts forming the structural connectome. Metrics were evaluated using normative modeling across tract length, resting-state functional networks, and cortical nodes. We additionally examined 29 individuals carrying other neurodevelopmental CNVs. 16p11.2 gene dosage was associated with regional reciprocal differences in tract axonal volume, with greater volume in deletion carriers and lower volume in duplication carriers. In contrast, myelin volume did not differ significantly from controls. This mismatch resulted in pervasive aggregate g-ratio alterations, with higher g-ratios (relatively thinner myelin sheaths) in deletion carriers and lower g-ratios (relatively thicker sheaths) in duplication carriers. Regional g-ratio alterations also extended to other neurodevelopmental CNVs. These findings resolve some of the biological ambiguity underlying white matter alterations in 16p11.2 CNV carriers, implicating the axonal compartment while revealing comparatively stable myelin volume. The disrupted axon-myelin scaling results in connectome-wide g-ratio alterations and may represent a shared microstructural hallmark of genetic neurodevelopmental risk.

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bioRxiv2026

Longitudinal changes in control energy of brain networks in older adults at familial risk for Alzheimers disease

The ability of structural brain networks to control neural dynamics is affected by healthy and pathological aging, including Alzheimers disease (AD). According to network control theory, transitions between functional brain states incur energetic costs. How these costs change longitudinally with aging remains unknown. Here, in 279 older adults at familial risk for AD, control energy increased longitudinally for state maintenance and transitions between sensorimotor and attentional networks, while decreasing for another sensorimotor--attentional transition. Changes in transition costs between higher-order networks were associated with cognitive performance: greater DorsAttn--Executive cost was associated with poorer immediate memory, while lower Executive--Def+Lim cost was associated with poorer attention. Higher plasma p-tau181 was associated with lower DorsAttn--Def+Lim transition cost. These findings reveal transition-specific alterations in the energetic landscape of aging and distinct relationships with cognition and AD pathology. Together, they highlight energetic constraints on brain network reconfiguration as a complementary perspective on neurocognitive aging.

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bioRxiv2026

Heterogeneity of Brain Dynamics in Genetic and Psychiatric Conditions

Whether the heterogeneity of psychiatric conditions converges on shared neurophysiological alterations or translates into distinct signatures remains unclear. We assembled high-density electroencephalogram (hd-EEG) resting-state recordings from 4,812 individuals aged 5 months to 66 years across 11 psychiatric conditions, a broad spectrum of rare genetic variants, and typically developing (TD) individuals. We established normative developmental trajectories of source-space EEG across spectral organization, connectivity, and signal complexity. Psychiatric conditions showed small deviations, revealing a shared transdiagnostic profile. In contrast, single rare variants showed substantially larger, distinct and sometimes mirror-opposite signatures that collapsed toward the psychiatric profile when pooled. Autism Spectrum Disorder showed some of the smallest group-level effects yet the largest individual deviations, indicating substantial but directionally inconsistent alterations. EEG deviations followed a cortical gradient, with larger effects in sensorimotor regions. We demonstrate that sample sizes in the hundreds are required for robust associations with psychiatric diagnoses. This interactive open resource provides normative scores to benchmark future results.

neuroscience↗

bioRxiv2026

The Q1K Integrated EEG and Eye-Tracking Experimental Test Battery for Open Autism Science

The Quebec 1000 Families (Q1K) platform has been designed to recruit, phenotype, and collect biospecimens from a large cohort of families with at least one member with autism spectrum disorder or a related neurodevelopmental condition. As part of the Q1K protocol, an experimental test battery was developed and validated using simultaneous high-density electroencephalography (EEG) and eye tracking (ET). We report on the general approach and design principles, multimodal EEG/ET integration, the tasks, and their validation, providing a blueprint for implement such a project. It also describes the cohort and its methods as a reference for future studies using this dataset. By releasing openly this experimental test battery, we aim to support task standardization and multi-project data pooling in autism and related neurodevelopmental disorders.

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bioRxiv2026

Fiber-tract development contributes to functional specialization in the human hippocampus

Fiber-tracts exhibit distinct projection patterns along the anterior-posterior axis of the hippocampus, promoting a specialization in function. This specialization becomes increasingly pronounced throughout child development, with important implications for neurocognitive outcomes. Developmental changes in fiber-tract properties, including intra-axonal cross-sectional area and myelin content, may contribute to this anterior-posterior functional specialization. To test this, we developed a diffusion-MRI tractography pipeline to identify hippocampal fiber-tracts in single subjects, then examined whether age-related differences in total intra-axonal cross-sectional area and myelin content (T1w/T2w) could predict functional specialization in a large cross-sectional sample (N=539, aged 5-21 years). With age, we found that the cross-sectional area of short-range medial-temporal tracts, which primarily target the anterior/body of the hippocampus, exhibited rapid growth. Concomitantly, the cross-sectional area of long-range occipito-parietal tracts, which primarily target the posterior hippocampus, exhibited a modest pruning. Increases in myelin content were relatively homogenous across fiber-tracts. In support of our hypothesis, we found that the cross-sectional area of fiber-tracts significantly predicts the surface-area of an fMRI-defined posterior system; a sensitive marker of functional specialization in the hippocampus. Tracts targeting early visual cortex (V2, V3, V4) showed the strongest association, with statistical modeling indicating a mediating effect of early-visual tract development on the relation between age and functional specialization. These findings provide evidence consistent with a mechanism whereby anatomical neurodevelopment contributes to functional specialization in the human hippocampus.

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bioRxiv2026

White Matter Myelin Shapes Macroscale Functional Connectivity Through Integrative Communication

White matter structural connectivity constrains large-scale brain communication, yet most network models do not account for biologically meaningful differences between connections. Although axonal diameter and myelination influence neural signaling at the microscale, how these features shape systems-level functional connectivity remains unclear. Here, we test whether structural connectomes weighted by white matter microstructure give rise to distinct communication regimes that differentially predict multimodal functional connectivity. Combining quantitative MRI and advanced diffusion modeling, we constructed whole-brain networks weighted by tract caliber and multiple myelin-sensitive measures. To these, we applied routing- and diffusion-based communication models and used the resulting communication metrics to predict haemodynamic and frequency-resolved electromagnetic connectivity. Myelin-weighted networks preferentially enhanced long-range communication efficiency and redistributed spectral energy toward globally integrative topological eigenmodes. In contrast, caliber-weighted networks emphasized mesoscale organization and short-range communication. Across nested regression models controlling for geometric embedding and network topology, myelin-sensitive communication explained unique variance in functional connectivity with effects varying systematically across cortical systems and frequency bands. The strongest coupling was observed for alpha-band connectivity in association and attentional networks, consistent with a role for myelin-dependent communication delays in supporting long-range alpha synchrony. These findings demonstrate how distinct white matter microstructural features give rise to heterogeneous large-scale communication regimes: tract caliber and myelin bias communication toward locally specialized and globally integrative architectures, respectively. By integrating biologically informed connectomics with communication modeling and multimodal functional data, this work advances a mechanistic account of how white matter microstructure shapes macroscale brain dynamics.

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bioRxiv2026

Coronary artery disease is linked with demyelination and iron deposition in white matter watershed areas

Coronary artery disease increases risk of cognitive decline and stroke and is associated with white matter alterations. However, the biological basis of these changes remains unclear. Myelin content and iron deposition are crucial measures of white matter health and can be measured with quantitative MRI. This study investigated whether myelin and iron alterations occur in coronary artery disease, and their relationship with cognition. In this cross-sectional study, 46 individuals with coronary artery disease and 40 healthy controls aged > 50 years, with normal cognition underwent 3T MRI and cognitive assessments. Quantitative MRI metrics (susceptibility, magnetization transfer saturation, R2* and R1 relaxation rates) were calculated in the border zones between adjacent arterial territories (watershed regions) and in the areas outside these borders (non-watershed regions). Relative to controls, the coronary artery disease group showed lower myelin and higher iron content, as measured by lower magnetization transfer saturation and R1, and higher susceptibility specifically in watershed regions. Importantly, these microstructural alterations were associated with poorer cognitive performance in the coronary artery disease group with lower magnetization transfer and R1related to poorer global cognition and with higher magnetic susceptibility with poorer verbal memory. These findings suggest that coronary artery disease is associated with demyelination and iron deposition in white matter, most prominently in watershed regions, which are known for their susceptibility to stroke. The association of these microstructural alterations with cognition highlights the role of white matter as a key vulnerable region and a promising focus for future mechanistic and therapeutic studies.

neuroscience↗

bioRxiv2025

The role of white matter myelin in structural-functional network coupling

The brain is a complex network of neuronal populations interconnected by white matter tracts. The composition of these white matter connections (SC) shapes inter-regional signaling dynamics giving rise to spatial patterns of synchronous functional connectivity (FC). Several modeling approaches have proven useful for studying the mechanisms underlying the relationship between SC and FC. However, the myelination of white matter tracts -- a major component of white matter connectivity -- is not accounted for by conventional SC networks, and thus, has largely been excluded from models of FC. Here, we expand structure-function brain modeling by integrating a multi-feature white matter SC network. We use multi-modal MRI to compute an SC network with connections (edges) weighted by the caliber, myelination, and length of white matter tracts. We investigate the relationship of this multi-feature SC network with both haemodynamic and electromagnetic FC. Edge myelin was strongly predictive of FC in a pattern that was heterogeneous across brain regions and timescales of neural function. Edge myelin showed strong, frequency-specific interactions with both edge caliber and length suggesting a modulatory role for white matter myelin in structure-function coupling. This was further supported by antagonistic gradients of white matter myelin and structure-function coupling along the sensory-association axis. We describe in detail the individual and joint relationships between these major white matter features and multi-frequency FC. These results illustrate the advantage of a more comprehensive characterization of white matter in structure-function models and establish how white matter myelin -- known for roles in conduction velocity, plasticity, and metabolic support at the microscale -- shapes brain function at the macroscale.

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bioRxiv2025

A unified imaging-histology framework for superficial white matter architecture studies in the human brain

The superficial white matter (SWM), immediately beneath the cortical mantle, is thought to play a major role in cortico-cortical connectivity as well as large-scale brain function. Yet, this compartment remains rarely studied due to its complex organization. Our objectives were to develop and disseminate a robust computational framework to study SWM organization based on 3D histology and high-field 7T MRI. Using data from the BigBrain and Ahead 3D histology initiatives, we first interrogated variations in cell staining intensities across different cortical regions and different SWM depths. These findings were then translated to in-vivo 7T quantitative myelin-sensitive MRI, including T1 relaxometry (T1 map) and magnetization transfer saturation (MTsat). As indicated by the statistical moments of the SWM intensity profiles, the first 2 mm below the cortico-subcortical boundary were characterized by high structural complexity. We quantified SWM microstructural variation using a non-linear dimensionality reduction method and examined the relationship of the resulting microstructural gradients with indices of cortical geometry, as well as structural and functional connectivity. Our results showed correlations between SWM microstructural gradients, as well as curvature and cortico-cortical functional connectivity. Our study provides novel insights into the organization of SWM in the human brain and underscores the potential of SWM mapping to advance fundamental and applied neuroscience research. HighlightsO_LIDeveloped an anatomy-based open science framework to study SWM organization based on 3D post-mortem histology and/or in-vivo high-field MRI C_LIO_LIThe first 2 mm into the white matter are characterized by high structural complexity C_LIO_LIInter-regional trends in SWM microstructural variation, which related to cortical geometry, as well as cortico-cortical connectivity C_LI

neuroscience↗

bioRxiv2025

Multivariate white matter microstructure alterations in older adults with coronary artery disease

Patients with coronary artery disease (CAD) face an increased risk of cognitive impairment, dementia, and stroke. While white matter (WM) lesions are frequently reported in patients with CAD, the effects on WM microstructure alterations remain largely unknown. We aimed to identify WM microstructural alterations in individuals with CAD compared to healthy controls (HC), and to examine their relationships with cognitive performance. Forty-three (43) patients with CAD and 36 HC aged 50 and older underwent comprehensive neuropsychological testing and multi-modal 3T MRI. A novel multivariate approach - the Mahalanobis distance (D2) - was used to quantify WM abnormalities as the amount of deviation from the HC reference group. D2 integrates multiple MRI-derived diffusion-weighted imaging, R1 relaxometry, and magnetization transfer imaging metrics, while accounting for covariance between metrics. Relationships between WM D2 and cognition (executive function and processing speed) were also assessed. Compared to HCs, patients with CAD had higher D2 values in the whole WM (p=0.009) and in the territories right anterior, bilateral middle, and right posterior cerebral artery territories (p<0.05). Myelin-sensitive metrics, particularly R1 relaxation rate and MT saturation (MTsat), were the most important contributors to D2. Processing speed was positively associated with greater R1 in both the whole WM and left middle cerebral artery territory. These findings suggest that greater WM microstructural alterations observed in patients with CAD were mainly driven by differences in myelin content, as R1 and MTsat were the most important contributors. These alterations may contribute to a heightened risk of cognitive impairment.

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bioRxiv2024

Mapping the aggregate g-ratio of white matter tracts using multi-modal MRI

The g-ratio of a myelinated axon is defined as the ratio of the inner-to-outer diameter of the myelin sheath and modulates conduction speed of action potentials along axons. This g-ratio can be mapped in vivo at the macroscopic scale across the entire human brain using multi-modal MRI and sampled along white matter streamlines reconstructed from diffusion-weighted images to derive the g-ratio of a white matter tract. This tractometry approach has shown spatiotemporal variations in myelin g-ratio across white matter tracts and networks. However, tractometry is biased by partial volume effects where voxels contain multiple fiber populations. To address this limitation, we used the Convex Optimization Modeling for Microstructure-Informed Tractography (COMMIT) framework to derive tract-specific axonal and myelin volumes, which are used to compute the tract-specific aggregate g-ratio. We compare our novel COMMIT-based tract-specific g-ratio mapping approach to conventional tractometry in a group of 10 healthy adults. Our findings demonstrate that the tract-specific g-ratio mapping approach preserves the overall spatial distribution observed in tractometry and enhances contrast between tracts. Additionally, our scan-rescan data shows high repeatability for medium to large caliber tracts. We show that short and large caliber tracts have a lower g-ratio, whereas tractometry results show the opposite trends. This technique advances tract-specific analysis by reducing biases introduced by the complex network of crossing white matter fibers.

neuroscience↗

bioRxiv2024

Sex and APOE4-specific links between cardiometabolic risk factors and white matter alterations in individuals with a family history of Alzheimer's disease

INTRODUCTIONWhite matter (WM) alterations are among the earliest changes in Alzheimers disease (AD), yet limited work has comprehensively characterized the effects of AD risk factors on WM. METHODSIn older adults with a family history of AD, we investigated the sex-specific and APOE genotype-related relationships between WM microstructure and risk factors. Multiple MRI-derived metrics were integrated using a multivariate approach based on the Mahalanobis distance (D2). The links between WM D2 and cognition were also explored. RESULTSWM D2 in several regions was associated with high systolic blood pressure, BMI, and glycated hemoglobin, and low cholesterol, in both males and females. APOE4+ displayed a distinct risk pattern, with LDL-cholesterol having a detrimental effect only in carriers, and this pattern was linked to immediate memory performance. Myelination was the main mechanism underlying WM alterations. DISCUSSIONOur findings reveal that combined exposure to multiple cardiometabolic risk factors negatively impacts microstructural health, which may subsequently affect cognition. Notably, APOE4 carriers exhibited a different risk pattern, especially in the role of LDL, suggesting distinct underlying mechanisms in this group.

neuroscience↗

bioRxiv2024

Multimodal Precision Neuroimaging of the Individual Human Brain at Ultra-high fields

Multimodal neuroimaging, in particular magnetic resonance imaging (MRI), allows for non-invasive examination of human brain structure and function across multiple scales. Precision neuroimaging builds upon this foundation, enabling the mapping of brain structure, function, and connectivity patterns with high fidelity in single individuals. Highfield MRI, operating at magnetic field strengths of 7 Tesla (T) or higher, increases signal-to-noise ratio and opens up possibilities for gains spatial resolution. Here, we share a multimodal Precision Neuroimaging and Connectomics (PNI) 7T MRI dataset. Ten healthy individuals underwent a comprehensive MRI protocol, including T1 relaxometry, magnetization transfer imaging, T2*-weighted imaging, diffusion MRI, and multi-state functional MRI paradigms, aggregated across three imaging sessions. Alongside anonymized raw MRI data, we release cortex-wide connectomes from different modalities across multiple parcellation scales, and supply "gradients" that compactly characterize spatial patterning of cortical organization. Our precision MRI dataset will advance our understanding of structure-function relationships in the individual human brain and is publicly available via the Open Science Framework.

neuroscience↗

bioRxiv2024

MULTIMODAL GRADIENTS UNIFY LOCAL AND GLOBAL CORTICAL ORGANIZATION

AO_SCPLOWBSTRACTC_SCPLOWSpecialization of brain areas and subregions, as well as their integration into large-scale networks are key principles in neuroscience. Consolidating both local and global cortical organization, however, remains challenging. Our study developed a new approach to map global cortex-wise similarities of microstructure, structural connectivity, and functional interactions, and integrate these patterns with maps of cortical arealization. Our analysis combined repeated high-field in-vivo 7 tesla (7T) Magnetic Resonance Imaging (MRI) data collected in 10 healthy adults with a recently introduced probabilistic post-mortem atlas of cortical cytoarchitecture. We obtained multimodal eigenvectors describing cortex-wide gradients at the level of microstructural covariance, structural connectivity, and intrinsic functional interactions, and then assessed inter- and intra-area differences in cortex-wide embedding based on these multimodal eigenvectors. Inter-area similarities followed a canonical sensory-fugal gradient, with primary sensorimotor cortex being the most distinctive from all other areas, while paralimbic regions were least distinctive. This pattern largely corresponded to functional connectivity variations across different tasks collected in the same participants, suggesting that the degree of global cortical integration mirrors the functional diversity of brain areas across contexts. When studying heterogeneity within areas, we did not observe a similar relationship, despite overall higher heterogeneity in association cortices relative to paralimbic and idiotypic cortices. The results were replicated in a different dataset. Our findings highlight a close coupling between cortical arealization and global cortical motifs in shaping specialized versus integrative human brain function. SO_SCPLOWIGNIFICANCEC_SCPLOWOur work situates cytoarchitecture-derived cortical areas within multimodal gradients of cortical microstructure, connectivity, and function derived from high-definition multimodal neuroimaging. We demonstrated that primary sensory and motor areas show most distinctive gradient profiles while paralimbic areas were least distinctive, overall recapitulating a sensory-fugal axis. This axis was shown to relate to the diversity of cortical areas across different functional contexts, and findings could be replicated across an independent dataset. Overall, our work shows how frameworks of cortical arealization and macroscale gradients converge in shaping functional specialization versus integration in the human brain.

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bioRxiv2024

Joint signatures of morphological and microstructural inter-individual variation in the Alzheimer's spectrum

Alzheimers disease (AD) is primarily characterized by the accumulation of amyloid and tau pathologies. However, alterations in the detailed organization and composition of neural tissue also contribute to the diseases early stages. Here, we sought to explore whether hippocampal and cortical microstructural changes, such as myelin alterations and inflammation-mediated increases in iron, could serve as indices of AD-related pathophysiology. In this study, we included 158 participants across the AD spectrum: from individuals without cognitive impairment, at high risk for AD, in the prodromal phase with mild cognitive impairment, and suffering from clinical dementia. We measured atrophy using structural magnetic resonance imaging (MRI) and estimated myelin and iron content using quantitative MRI (qMRI) metrics derived from T1 and T2* relaxation, times respectively. We integrated these contrasts to estimate a joint multivariate signature of tissue alterations across the cortex and hippocampus using non-negative matrix factorization. The relevance of these signatures to AD-spectrum measures of medical history, lifestyle, and cognition were further explored using partial least squares correlation. Our results reveal lower disease-related cortical thickness over large areas of the cortex while T2* provided specific variation across the brain (lower in dorsomedial and superior temporal areas, superior frontal cortex, and premotor cortex, and higher in the occipital lobe). Additionally, we observed longer T1 and T2* times in the hippocampus associated with specific lifestyle risk factors like past smoking, high blood pressure, high cholesterol levels, and higher anxiety. These patterns were significantly related to older age, associated with AD progression, being female, and being an APOE-{square}4 carrier. Taken together, our results suggest that qMRI metrics could serve as a valuable non-invasive tool for exploring the role of myelin and inflammation in AD-related pathophysiology and could be sensitive to modifiable risk factors related to lifestyle and medical history. Future studies may use these signatures to investigate their relationship in investigations related to lifestyle interventions or novel therapeutics.

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bioRxiv2023

The Human Brain Connectome Weighted by the Myelin Content and Total Intra-Axonal Cross-Sectional Area of White Matter Tracts

A central goal in neuroscience is the development of a comprehensive mapping between structural and functional brain features. Computational models support in vivo investigation of the mechanisms mediating this relationship but currently lack the requisite biological detail. Here, we characterize human structural brain networks weighted by multiple white matter microstructural features to assess their potential joint utilization in computational models. We report edge-weight-dependent spatial distributions, variance, small-worldness, rich club, hubs, as well as relationships with function, edge length and myelin. Contrasting networks weighted by the total intra-axonal cross-sectional area and myelin content of white matter tracts, we find opposite relationships with functional connectivity, an edge-length-independent inverse relationship with each other, and the lack of a canonical rich club in myelin-weighted networks. When controlling for edge length, tractometry-derived networks weighted by either tensor-based metrics or neurite density show no relationship with whole-brain functional connectivity. We conclude that structure-function brain models are likely to be improved by the co-utilization of structural networks weighted by total intra-axonal cross-sectional area and myelin content. We anticipate that the proposed microstructure-weighted computational modeling approach will support mechanistic understanding of the structure-function relationship of the human brain. AUTHOR SUMMARYFor computational network models to provide mechanistic links between brain structure and function, they must be informed by networks in which edge weights quantify structural features relevant to brain function. Here, we characterized several weighted structural networks capturing multiscale features of white matter connectivity. We describe these networks in terms of edge weight distribution, variance and network topology, as well as their relationships with each other, edge length and function. Overall, these findings support the joint use of structural networks weighted by the total intra-axonal cross-sectional area and myelin content of white matter tracts in structure-function models. This thorough characterization serves as a benchmark for future investigations of weighted structural brain networks.

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bioRxiv2023

Assessment of white matter hyperintensity severity using multimodal MRI in Alzheimer's Disease

White matter hyperintensities (WMHs) are clinically significant MRI abnormalities often detected in the elderly and early stages of Alzheimers Disease. They are indicative of vascular pathology but represent a mixture of microstructural tissue alterations that is highly variable between individuals. To better understand these alterations, we leveraged the signal of different MRI contrasts sampled within WMHs, which have differential sensitivity to microstructural properties. Subsequently, we sought to examine the asso of these WMH signal measures to clinically-relevant measures such as cortical and global brain atrophy, cognitive function, diagnostic and demographic differences, and Alzheimers Disease-relevant cardiovascular risk factors. Our sample of 118 subjects was composed of healthy controls (n=30), high-risk of Alzheimers Disease due to familial history (n=47), mild cognitive impairment (n=32), and clinical Alzheimers Disease (n=9) as a means of ascertaining a spectrum of impairment. We sampled the median signal within WMHs on weighted MRI images that are commonly acquired (T1-weighted [T1w], T2-weighted [T2w], T1w/T2w ratio, Fluid-Attenuated Inversion Recovery [FLAIR]), and the relaxation times from quantitative T1 (qT1) and T2* (qT2*) images. Main analyses were performed with a periventricular/deep/superficial white matter parcellation and were repeated with a lobar white matter parcellation. We demonstrated that the correlations between WMH signal measures were variable, suggesting that they are likely influenced by different microstructural properties. We observed that the WMH qT2* and FLAIR measures displayed different age- and disease-related trends compared to normal-appearing white matter, highlighting sensitivity to WMH-specific tissue deterioration. Further, WMH qT2* particularly in periventricular and occipital white matter regions was consistently associated with several of our clinical variables of interest using both parcellation schemes in univariate analyses, and further showed high contributions to a pattern of brain variables that was associated with age and cognitive variables in multivariate Partial Least Squares Correlation analyses. qT1 and FLAIR measures showed consistent clinical relationships in multivariate analyses only, while T1w, T2w, and T1w/T2w ratio measures were not consistently associated with clinical variables. We observed that the qT2* signal was sensitive to clinically-relevant microstructural tissue alterations specific to WMHs. Combining volumetric and signal measures of WMH, particularly qT2* and to a lesser extent qT1 and FLAIR, should be considered to more precisely characterize the severity of WMHs in vivo. These findings may have implications in determining the reversibility of WMHs and potential efficacy of cardio- and cerebrovascular treatments.

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