Evidence for wakefulness-related changes to extracellular space in human brain white matter from diffusion-weighted MRI

Sleep Health and White Matter Integrity in the UK Biobank

Many people experience impaired sleep health, yet knowledge about its neurobiological correlates is limited. As previous studies have found associations between white matter integrity and several sleep traits, white matter integrity could be causally implicated in poor sleep health. However, these studies were often limited by small sample sizes. In this study, we examine associations between multiple indices of white matter integrity and sleep health in 29,114 UK Biobank participants. Late chronotype, daytime sleepiness, insomnia symptoms and, most extensively, long sleep duration were independently associated with diffusion MRI markers of reduced white matter integrity. Previous findings showing an association between insomnia symptoms and decreased fractional anisotropy (FA) in the anterior internal capsule could not be replicated. To our knowledge, the current analysis is the first study to find an association between long sleep duration and impaired microstructural white matter integrity. Previous assumptions concerning the role of white matter integrity for insomnia are challenged.

Perivascular space diffusivity and brain microstructural measures are associated with circadian time and sleep quality

The glymphatic system is centred around brain cerebrospinal fluid flow and is enhanced during sleep, and the synaptic homeostasis hypothesis proposes that sleep acts on brain microstructure by selective synaptic downscaling. While so far primarily studied in animals, we here examine in humans if brain diffusivity and microstructure is related to time of day, sleep quality and cognitive performance. We use diffusion weighted images from 916 young healthy individuals, aged between 22 and 37 years, collected as part of the Human Connectome Project to assess diffusion tensor image analysis along the perivascular space index, white matter fractional anisotropy, intra-neurite volume fraction and extra-neurite mean diffusivity. Next, we examine if these measures are associated with circadian time of acquisition, the Pittsburgh Sleep Quality Index (high scores correspond to low sleep quality) and age-adjusted cognitive function total composite score. Consistent with expectations, we find that diffusion tensor image analysis along the perivascular space index and orbitofrontal grey matter extra-neurite mean diffusivity are negatively and white matter fractional anisotropy positively correlated with circadian time. Further, we find that grey matter intra-neurite volume fraction correlates positively with Pittsburgh Sleep Quality Index, and that this correlation is driven by sleep duration. Finally, we find positive correlations between grey matter intra-neurite volume fraction and cognitive function total composite score, as well as negative interaction effects between cognitive function total composite score and Pittsburgh Sleep Quality Index on grey matter intra-neurite volume fraction. Our findings propose that perivascular flow is under circadian control and that sleep downregulates the intra-neurite volume in healthy adults with positive impact on cognitive function.

Anesthesia-related brain microstructure modulations detected by diffusion magnetic resonance imaging

Recent studies have shown significant changes to brain microstructure during sleep and anesthesia. In vivo optical microscopy and magnetic resonance imaging (MRI) studies have attributed these changes to anesthesia and sleep-related modulation of the brain's extracellular space (ECS). Isoflurane anesthesia is widely used in preclinical diffusion MRI (dMRI) and it is therefore important to investigate if the brain's microstructure is affected by anesthesia to an extent detectable with dMRI. Here, we employ diffusion kurtosis imaging (DKI) to assess brain microstructure in the awake and anesthetized mouse brain (n = 22). We find both mean diffusivity (MD) and mean kurtosis (MK) to be significantly decreased in the anesthetized mouse brain compared with the awake state (p < 0.001 for both). This effect is observed in both gray matter and white matter. To further investigate the time course of these changes we introduce a method for time-resolved fast DKI. With this, we show the time course of the microstructural alterations in mice (n = 5) as they transition between states in an awake-anesthesia-awake paradigm. We find that the decrease in MD and MK occurs rapidly after delivery of gas isoflurane anesthesia and that values normalize only slowly when the animals return to the awake state. Finally, time-resolved fast DKI is employed in an experimental mouse model of brain edema (n = 4), where cell swelling causes the ECS volume to decrease. Our results show that isoflurane affects DKI parameters and metrics of brain microstructure and point to isoflurane causing a reduction in the ECS volume. The demonstrated DKI methods are suitable for in-bore perturbation studies, for example, for investigating microstructural modulations related to sleep/wake-dependent functions of the glymphatic system. Importantly, our study shows an effect of isoflurane anesthesia on rodent brain microstructure that has broad relevance to preclinical dMRI.

Chronotype and subjective sleep quality predict white matter integrity in young people with emerging mental disorders

Protecting brain health is a goal of early intervention. We explored whether sleep quality or chronotype could predict white matter (WM) integrity in emerging mental disorders. Young people (N = 364) accessing early-intervention clinics underwent assessments for chronotype, subjective sleep quality, and diffusion tensor imaging. Using machine learning, we examined whether chronotype or sleep quality (alongside diagnostic and demographic factors) could predict four measures of WM integrity: fractional anisotropy (FA), and radial, axial, and mean diffusivities (RD, AD and MD). We prioritised tracts that showed a univariate association with sleep quality or chronotype and considered predictors identified by ≥80% of machine learning (ML) models as 'important'. The most important predictors of WM integrity were demographics (age, sex and education) and diagnosis (depressive and bipolar disorders). Subjective sleep quality only predicted FA in the perihippocampal cingulum tract, whereas chronotype had limited predictive importance for WM integrity. To further examine links with mood disorders, we conducted a subgroup analysis. In youth with depressive and bipolar disorders, chronotype emerged as an important (often top-ranking) feature, predicting FA in the cingulum (cingulate gyrus), AD in the anterior corona radiata and genu of the corpus callosum, and RD in the corona radiata, anterior corona radiata, and genu of corpus callosum. Subjective quality was not important in this subgroup analysis. In summary, chronotype predicted altered WM integrity in the corona radiata and corpus callosum, whereas subjective sleep quality had a less significant role, suggesting that circadian factors may play a more prominent role in WM integrity in emerging mood disorders.

Tracing diurnal differences in brain anatomy with voxel-based morphometry - associations with sleep characteristics

Multiple aspects of brain functioning, including arousal, motivation, and cognitive performance, are governed by circadian rhythmicity. Although the recent rise in the use of magnetic resonance imaging (MRI) has enabled investigations into the macroscopic correlates of the diurnal brain processes, neuroanatomical studies are scarce. The current work investigated how time-of-day (TOD) impacts white (WM) and grey matter (GM) volumes using voxel-based morphometry (VBM) in a large dataset (N = 72) divided into two equal, comparable subsamples to assess the replicability of effects. Furthermore, we aimed to assess how the magnitude of these diurnal differences was related to actigraphy-derived indices of sleep health. The results extend the current knowledge by reporting that TOD is predominantly associated with regional WM volume decreases. Additionally, alongside corroborating previously observed volumetric GM decreases, we provide the first evidence for positive TOD effects. Higher replicability was observed for WM, with the only two replicated GM clusters being volumetric increases in the amygdala and hippocampus, and decreases in the retrosplenial cortex, with the latter more pronounced in individuals with shorter sleep times. These findings implicate the existence of region-specific mechanisms behind GM effects, which might be related to cognitive processes taking place during wakefulness and homeostatic sleep pressure.

Diurnal oscillations of MRI metrics in the brains of male participants

Regulation of biological processes according to a 24-hr rhythm is essential for the normal functioning of an organism. Temporal variation in brain MRI data has often been attributed to circadian or diurnal oscillations; however, it is not clear if such oscillations exist. Here, we provide evidence that diurnal oscillations indeed govern multiple MRI metrics. We recorded cerebral blood flow, diffusion-tensor metrics, T1 relaxation, and cortical structural features every three hours over a 24-hr period in each of 16 adult male controls and eight adult male participants with bipolar disorder. Diurnal oscillations are detected in numerous MRI metrics at the whole-brain level, and regionally. Rhythmicity parameters in the participants with bipolar disorder are similar to the controls for most metrics, except for a larger phase variation in cerebral blood flow. The ubiquitous nature of diurnal oscillations has broad implications for neuroimaging studies and furthers our understanding of the dynamic nature of the human brain.

Peripherally acting anti-CGRP monoclonal antibodies alter cortical gray matter thickness in migraine patients: A prospective cohort study

Migraine is underpinned by central nervous system neuroplastic alterations thought to be caused by the repetitive peripheral afferent barrage the brain receives during the headache phase (cortical hyperexcitability). Calcitonin gene-related peptide monoclonal antibodies (anti-CGRP-mAbs) are highly effective migraine preventative treatments. Their ability to alter brain morphometry in treatment-responders vs. non-responders is not well understood. Our aim was to determine the effects of the anti-CGRP-mAb galcanezumab on cortical thickness after 3-month treatment of patients with high-frequency episodic or chronic migraine. High-resolution magnetic resonance imaging was performed pre- and post-treatment in 36 migraine patients. In this group, 19 patients were classified responders (≥50 % reduction in monthly migraine days) and 17 were considered non-responders (<50 % reduction in monthly migraine days). Following cross-sectional processing to analyze the baseline differences in cortical thickness, two-stage longitudinal processing and symmetrized percent change were conducted to investigate treatment-related brain changes. At baseline, no significant differences were found between the responders and non-responders. After 3-month treatment, decreased cortical thickness (compared to baseline) was observed in the responders in regions of the somatosensory cortex, anterior cingulate cortex, medial frontal cortex, superior frontal gyrus, and supramarginal gyrus. Non-responders demonstrated decreased cortical thickness in the left dorsomedial cortex and superior frontal gyrus. We interpret the cortical thinning seen in the responder group as suggesting that reduction in head pain could lead to changes in neural swelling and dendritic complexity and that such changes reflect the recovery process from maladaptive neural activity. This conclusion is further supported by our recent study showing that 3 months after treatment initiation, the incidence of premonitory symptoms and prodromes that are followed by headache decreases but not the incidence of the premonitory symptoms or prodromes themselves (that is, cortical thinning relates to reductions in the nociceptive signals in the responders). We speculate that a much longer recovery period is required to allow the brain to return to a more 'normal' functioning state whereby prodromes and premonitory symptoms no longer occur.

Sleep and Perivascular Spaces

PURPOSE OF REVIEW

The glymphatic system is hypothesized to act as the brain's filtration system to remove toxic solutes that accumulate throughout the day. Perivascular spaces (PVSs) play a fundamental role in the ability of the glymphatic system to function, and sleep influences the effectiveness of this system. This article reviews the complexity of the interplay between sleep, the glymphatic system, and PVS.

RECENT FINDINGS

New imaging techniques have illuminated the structure of PVS and their associations with differing disease states. Research has shown that sleep may play a key role in the function of PVS and the influence of adenosine, astrocyte, and aquaporin-4 channel in the function of the glymphatic system. Emerging data suggest that differing pathological states such as neuroinflammatory conditions, neurodegenerative diseases, and cognitive dysfunction may be associated with underlying glymphatic system dysfunction, and sleep disorders could be a potential intervention target.

Understanding Neuropeptide Transmission in the Brain by Optical Uncaging and Release

Neuropeptides are abundant and essential signaling molecules in the nervous system involved in modulating neural circuits and behavior. Neuropeptides are generally released extrasynaptically and signal via volume transmission through G-protein-coupled receptors (GPCR). Although substantive functional roles of neuropeptides have been discovered, many questions on neuropeptide transmission remain poorly understood, including the local diffusion and transmission properties in the brain extracellular space. To address this challenge, intensive efforts are required to develop advanced tools for releasing and detecting neuropeptides with high spatiotemporal resolution. Because of the rapid development of biosensors and materials science, emerging tools are beginning to provide a better understanding of neuropeptide transmission. In this perspective, we summarize the fundamental advances in understanding neuropeptide transmission over the past decade, highlight the tools for releasing neuropeptides with high spatiotemporal solution in the brain, and discuss open questions and future directions in the field.

Physiology of Glymphatic Solute Transport and Waste Clearance from the Brain

This review focuses on the physiology of glymphatic solute transport and waste clearance, using evidence from experimental animal models as well as from human studies. Specific topics addressed include the biophysical characteristics of fluid and solute transport in the central nervous system, glymphatic-lymphatic coupling, as well as the role of cerebrospinal fluid movement for brain waste clearance. We also discuss the current understanding of mechanisms underlying increased waste clearance during sleep.

Robustness of radiomics to variations in segmentation methods in multimodal brain MRI

Radiomics in neuroimaging uses fully automatic segmentation to delineate the anatomical areas for which radiomic features are computed. However, differences among these segmentation methods affect radiomic features to an unknown extent. A scan-rescan dataset (n = 46) of T1-weighted and diffusion tensor images was used. Subjects were split into a sleep-deprivation and a control group. Scans were segmented using four segmentation methods from which radiomic features were computed. First, we measured segmentation agreement using the Dice-coefficient. Second, robustness and reproducibility of radiomic features were measured using the intraclass correlation coefficient (ICC). Last, difference in predictive power was assessed using the Friedman-test on performance in a radiomics-based sleep deprivation classification application. Segmentation agreement was generally high (interquartile range = 0.77–0.90) and median feature robustness to segmentation method variation was higher (ICC > 0.7) than scan-rescan reproducibility (ICC 0.3–0.8). However, classification performance differed significantly among segmentation methods (p < 0.001) ranging from 77 to 84%. Accuracy was higher for more recent deep learning-based segmentation methods. Despite high agreement among segmentation methods, subtle differences significantly affected radiomic features and their predictive power. Consequently, the effect of differences in segmentation methods should be taken into account when designing and evaluating radiomics-based research methods.

Evidence for widespread alterations in cortical microstructure after 32 h of sleep deprivation

Cortical microstructure is influenced by circadian rhythm and sleep deprivation, yet the precise underpinnings of these effects remain unclear. The ratio between T₁-weighted and T₂-weighted magnetic resonance images (T₁w/T₂w ratio) has been linked to myelin levels and dendrite density and may offer novel insight into the intracortical microstructure of the sleep deprived brain. Here, we examined intracortical T₁w/T₂w ratio in 41 healthy young adults (26 women) before and after 32 h of either sleep deprivation (n = 18) or a normal sleep-wake cycle (n = 23). Linear models revealed significant group differences in T₁w/T₂w ratio change after 32 h in four clusters, including bilateral effects in the insular, cingulate, and superior temporal cortices, comprising regions involved in attentional, auditory and pain processing. Across clusters, the sleep deprived group showed an increased T₁w/T₂w ratio, while the normal sleep-wake group exhibited a reduced ratio. These changes were not explained by in-scanner head movement, and 95% of the effects across clusters remained significant after adjusting for cortical thickness and hydration. Compared with a normal sleep-wake cycle, 32 h of sleep deprivation yields intracortical T₁w/T₂w ratio increases. While the intracortical changes detected by this study could reflect alterations in myelin or dendritic density, or both, histological analyses are needed to clarify the precise underlying cortical processes.

Fluid transport in the brain

The brain harbors a unique ability to, figuratively speaking, shift its gears. During wakefulness, the brain is geared fully toward processing information and behaving, while homeostatic functions predominate during sleep. The blood-brain barrier establishes a stable environment that is optimal for neuronal function, yet the barrier imposes a physiological problem; transcapillary filtration that forms extracellular fluid in other organs is reduced to a minimum in brain. Consequently, the brain depends on a special fluid [the cerebrospinal fluid (CSF)] that is flushed into brain along the unique perivascular spaces created by astrocytic vascular endfeet. We describe this pathway, coined the term glymphatic system, based on its dependency on astrocytic vascular endfeet and their adluminal expression of aquaporin-4 water channels facing toward CSF-filled perivascular spaces. Glymphatic clearance of potentially harmful metabolic or protein waste products, such as amyloid-β, is primarily active during sleep, when its physiological drivers, the cardiac cycle, respiration, and slow vasomotion, together efficiently propel CSF inflow along periarterial spaces. The brain's extracellular space contains an abundance of proteoglycans and hyaluronan, which provide a low-resistance hydraulic conduit that rapidly can expand and shrink during the sleep-wake cycle. We describe this unique fluid system of the brain, which meets the brain's requisites to maintain homeostasis similar to peripheral organs, considering the blood-brain-barrier and the paths for formation and egress of the CSF.

Altered Glymphatic System in Middle-Aged cART-Treated Patients With HIV: A Diffusion Tensor Imaging Study

Objective:

The brain relies on the glymphatic system to clear metabolic wastes and maintain brain homeostasis to fulfill its functions better. Yet, the complexity of the glymphatic flow and clearance and its changes in HIV infection and its role in neurocognitive dysfunction remain poorly understood. This study aims to explore the impact of HIV and combination antiretroviral therapy (cART) on the glymphatic system and establish a potential biomarker of HIV-associated neurocognitive disorders (HAND).

Methods

Here, we examined the glymphatic profiles of middle-aged virosuppressed patients with HIV (n = 27) receiving cART over 1–6 years and healthy controls (n = 28) along the perivascular space (PVS) using diffusion tensor image analysis along the perivascular space (ALPS) with guided and unguided approaches. We later combined data from these analyses to investigate MRI glymphatic correlates of cognitive impairment and other clinical tests of HIV (CD4+ T-cell counts and CD4+/CD8+ ratio).

Results

We found that glymphatic function as measured by the ALPS index increased significantly in the right and left PVSs of patients with HIV having cART. On antiretroviral therapy, a changing pattern in glymphatic clearance function in patients with HIV having cART correlated with attention and working memory. Duration on cART was also associated with cognitive performances of abstract and executive function and learning and memory.

Conclusion

These findings provide MRI evidence of the presence of HIV-induced changes in the glymphatic flow and clearance, which might underlie cognitive impairment among patients with HIV having cART. An increase in the glymphatic activity might reflect a compensatory mechanism to regulate microenvironment homeostasis compromised by HIV. This compensation might be necessary to maintain the proper functioning of the brain while coping with HIV pathology. These findings also shed light on the clinical importance of evaluating glymphatic function based on the ALPS index and suggest that improving the glymphatic system may serve as an alternative therapeutic strategy for HAND.

Time-of-Day Effects in Resting-State Functional Magnetic Resonance Imaging: Changes in Effective Connectivity and Blood Oxygenation Level Dependent Signal

Introduction:

In the light of the ongoing replication crisis in the field of neuroimaging, it is necessary to assess the possible exogenous and endogenous factors that may affect functional magnetic resonance imaging (fMRI). The current project investigated time-of-day effects in the spontaneous fluctuations (<0.1 Hz) of the blood oxygenation level dependent (BOLD) signal.

Method:

Using data from the human connectome project release S1200, cross-spectral density dynamic causal modeling (DCM) was used to analyze time-dependent effects on the hemodynamic response and effective connectivity parameters. The DCM analysis covered three networks, namely the default mode network, the central executive network, and the saliency network. Hierarchical group-parametric empirical Bayes (PEB) was used to test varying design-matrices against the time-of-day model.

Results:

Hierarchical group-PEB found no support for changes in effective connectivity, whereas the hemodynamic parameters exhibited a significant time-of-day dependent effect, indicating a diurnal vascular effect that might affect the measured BOLD signal in the absence of any diurnal variations of the underlying neuronal activations and effective connectivity.

Conclusion:

We conclude that these findings urge the need to account for the time of data acquisition in future MRI studies and suggest that time-of-day dependent metabolic variations contribute to reduced reliability in resting-state fMRI studies.

Impact statement

The results from this study suggest that the circadian mechanism influences the blood oxygenation level dependent signal in resting-state functional magnetic resonance imaging (fMRI). The current study urges to record and report the time of fMRI scan acquisition in future research, as it may increase the replicability of findings. Both exploratory and clinical studies would benefit by incorporating this small change in fMRI protocol, which to date has been often overlooked.

Excessive Daytime Sleepiness in Obstructive Sleep Apnea. Mechanisms and Clinical Management

Many patients with obstructive sleep apnea (OSA) experience excessive daytime sleepiness (EDS), which can negatively affect daily functioning, cognition, mood, and other aspects of well-being. Although EDS can be reduced with primary OSA treatment, such as continuous positive airway pressure (CPAP) therapy, a significant proportion of patients continue to experience EDS despite receiving optimized therapy for OSA. This article reviews the pathophysiology and clinical evaluation and management of EDS in patients with OSA. The mechanisms underlying EDS in CPAP-treated patients remain unclear. Experimental risk factors include chronic intermittent hypoxia and sleep fragmentation, which lead to oxidative injury and changes in neurons and brain circuit connectedness involving noradrenergic and dopaminergic neurotransmission in wake-promoting regions of the brain. In addition, neuroimaging studies have shown alterations in the brain's white matter and gray matter in patients with OSA and EDS. Clinical management of EDS begins with ruling out other potential causes of EDS and evaluating its severity. Tools to evaluate EDS include objective and self-reported assessments of sleepiness, as well as cognitive assessments. Patients who experience residual EDS despite primary OSA therapy may benefit from wake-promoting pharmacotherapy. Agents that inhibit reuptake of dopamine or of dopamine and norepinephrine (modafinil/armodafinil and solriamfetol, respectively) have demonstrated efficacy in reducing EDS and improving quality of life in patients with OSA. Additional research is needed on the effects of wake-promoting treatments on cognition in these patients and to identify individual or disorder-specific responses.

White matter microstructural changes in short-term learning of a continuous visuomotor sequence

Efficient neural transmission is crucial for optimal brain function, yet the plastic potential of white matter (WM) has long been overlooked. Growing evidence now shows that modifications to axons and myelin occur not only as a result of long-term learning, but also after short training periods. Motor sequence learning (MSL), a common paradigm used to study neuroplasticity, occurs in overlapping learning stages and different neural circuits are involved in each stage. However, most studies investigating short-term WM plasticity have used a pre-post design, in which the temporal dynamics of changes across learning stages cannot be assessed. In this study, we used multiple magnetic resonance imaging (MRI) scans at 7 T to investigate changes in WM in a group learning a complex visuomotor sequence (LRN) and in a control group (SMP) performing a simple sequence, for five consecutive days. Consistent with behavioral results, where most improvements occurred between the two first days, structural changes in WM were observed only in the early phase of learning (d1-d2), and in overall learning (d1-d5). In LRNs, WM microstructure was altered in the tracts underlying the primary motor and sensorimotor cortices. Moreover, our structural findings in WM were related to changes in functional connectivity, assessed with resting-state functional MRI data in the same cohort, through analyses in regions of interest (ROIs). Significant changes in WM microstructure were found in a ROI underlying the right supplementary motor area. Together, our findings provide evidence for highly dynamic WM plasticity in the sensorimotor network during short-term MSL.

Evidence of Genetic Overlap Between Circadian Preference and Brain White Matter Microstructure

Several neuroimaging studies have reported associations between brain white matter microstructure and chronotype. However, it is unclear whether those phenotypic relationships are causal or underlined by genetic factors. In the present study, we use genetic data to examine the genetic overlap and infer causal relationships between chronotype and diffusion tensor imaging (DTI) measures. We identify 29 significant pairwise genetic correlations, of which 13 also show evidence for a causal association. Genetic correlations were identified between chronotype and brain-wide mean, axial and radial diffusivities. When exploring individual tracts, 10 genetic correlations were observed with mean diffusivity, 10 with axial diffusivity, 4 with radial diffusivity and 2 with mode of anisotropy. We found evidence for a possible causal association of eveningness with white matter microstructure measures in individual tracts including the posterior limb and the retrolenticular part of the internal capsule; the genu and splenium of the corpus callosum and the posterior, superior and anterior regions of the corona radiata. Our findings contribute to the understanding of how genes influence circadian preference and brain white matter and provide a new avenue for investigating the role of chronotype in health and disease.

Sleep and sleep deprivation differentially alter white matter microstructure: A mixed model design utilising advanced diffusion modelling

Sleep deprivation influences several critical functions, yet how it affects human brain white matter (WM) is not well understood. The aim of the present work was to investigate the effect of 32 hours of sleep deprivation on WM microstructure compared to changes observed in a normal sleep-wake cycle (SWC). To this end, we utilised diffusion weighted imaging (DWI) including the diffusion tensor model, diffusion kurtosis imaging and the spherical mean technique, a novel biophysical diffusion model. 46 healthy adults (23 sleep deprived vs 23 with normal SWC) underwent DWI across four time points (morning, evening, next day morning and next day afternoon, after a total of 32 hours). Linear mixed models revealed significant group × time interaction effects, indicating that sleep deprivation and normal SWC differentially affect WM microstructure. Voxel-wise comparisons showed that these effects spanned large, bilateral WM regions. These findings provide important insight into how sleep deprivation affects the human brain.

White matter microstructure across the adult lifespan: A mixed longitudinal and cross-sectional study using advanced diffusion models and brain-age prediction

The macro- and microstructural architecture of human brain white matter undergoes substantial alterations throughout development and ageing. Most of our understanding of the spatial and temporal characteristics of these lifespan adaptations come from magnetic resonance imaging (MRI), including diffusion MRI (dMRI), which enables visualisation and quantification of brain white matter with unprecedented sensitivity and detail. However, with some notable exceptions, previous studies have relied on cross-sectional designs, limited age ranges, and diffusion tensor imaging (DTI) based on conventional single-shell dMRI. In this mixed cross-sectional and longitudinal study (mean interval: 15.2 months) including 702 multi-shell dMRI datasets, we combined complementary dMRI models to investigate age trajectories in healthy individuals aged 18 to 94 years (57.12% women). Using linear mixed effect models and machine learning based brain age prediction, we assessed the age-dependence of diffusion metrics, and compared the age prediction accuracy of six different diffusion models, including diffusion tensor (DTI) and kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), restriction spectrum imaging (RSI), spherical mean technique multi-compartment (SMT-mc), and white matter tract integrity (WMTI). The results showed that the age slopes for conventional DTI metrics (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD]) were largely consistent with previous research, and that the highest performing advanced dMRI models showed comparable age prediction accuracy to conventional DTI. Linear mixed effects models and Wilk's theorem analysis showed that the 'FA fine' metric of the RSI model and 'orientation dispersion' (OD) metric of the NODDI model showed the highest sensitivity to age. The results indicate that advanced diffusion models (DKI, NODDI, RSI, SMT mc, WMTI) provide sensitive measures of age-related microstructural changes of white matter in the brain that complement and extend the contribution of conventional DTI.