Abstract Meningeal lymphatic vessels (mLV) play essential roles in draining cerebrospinal fluid (CSF) into peripheral blood. The mLVs are hypothesized to be supportive structures to the glymphatic system, which is thought to remove metabolic byproducts from brain parenchyma and has been most directly studied in rodent models. Previous rodent studies have indicated a correlation between mLV function and cognitive performance, but this relationship in humans remains unexplored. Age-related declines in glymphatic system efficiency in humans and cognitive performance have been observed separately. This study investigates age- and sex-related differences in CSF production via choroid plexus volumes, mLV characteristics, and glymphatic system efficiency, overall elucidating the implication of cerebral lymphatic function on cognition. We recruited 26 healthy adults from Dallas-Fort Worth and acquired magnetic resonance images. mLVs along the sagittal sinus were visualized and segmented from T 2 -FLAIR images. The glymphatic system was evaluated by measuring diffusivity along the perivascular space. Choroid plexus volume and brain volume were estimated from T 1 -MPRAGE. Neuropsychological tests were conducted to assess cognitive function. Our findings indicate that glymphatic function diminishes with age, while mLV and choroid plexus volumes increase. Males displayed greater mLV volume than females, yet no sex differences were found in glymphatic function or choroid plexus volume. Notably, mLV volume increased as glymphatic function declined, independent of age. Moreover, a glymphatic-mLV latent variable significantly predicted processing speed, underscoring the influence of cerebral lymphatics on cognition. In conclusion, this study highlights a decline in glymphatic function with age, accompanied by increased mLV volumes and altered processing speed. These lymphatic system changes may underlie or contribute to the cognitive declines observed in healthy and pathological aging. Significance Statement The glymphatic system and meningeal lymphatic vessels play crucial roles in removing brain cell waste. The relationship between these systems and their effect on human cognition, particularly processing speed, is unknown. We demonstrate that these systems change with advancing age. Variations in cerebral lymphatic function contribute to differences in processing speed independent of age, ultimately affecting higher-order cognitive function. The findings presented have implications for cognitive function in both healthy and diseased states.

Depression is a common mental health disorder affecting millions worldwide. Pharmacotherapies are partially effective, but numerous side effects often make them unfavorable. Recent investigations show that mindfulness meditation effectively mitigates depression-symptoms but the underlying mechanisms remain elusive. Here, we examined the sequential influence of emotion regulation (ER) and rumination tendencies to explore trait mindfulness (TM) effects on depression-symptoms. 1000 undergraduates provided ratings on their depression-symptoms, mindfulness-experience, TM, ER strategy-use and rumination tendencies. Structural equation modeling was used to examine sequential influences of ER strategies and rumination tendencies on TM-depression relationships and how these mechanisms were moderated by meditation-experience. All TM facets showed sequential influences on depression-symptoms through increases in reappraisal and decreases in brooding rumination. Describe, Act with Aware and Nonjudge facets showed additional pathways including reductions in suppression, brooding-rumination and reflective-pondering. The Nonreact facet showed significant influence of meditation-experience on the mediation pathway through suppression. For individuals without meditation-experience there were positive associations between nonreactivity and brooding-rumination, reflective-pondering and depression-symptoms via suppression. These associations were absent in meditation-experienced individuals. Findings suggest the hypothesis that sequential influences of ER strategies and ruminative processes underlie TM-depression relationships and might have implications for how TM facets influence ER and rumination to promote or mitigate depression.

Multiple sclerosis (MS) is an autoimmune, demyelineating disease of the central nervous system. Cognitive dysfunction and processing speed decline are some of the most prominent deficits in MS. Resting-state functional connectivity demonstrates the functional organization of spatially distributed regions that comprise different cognitive networks. MS patients are also known to exhibit altered connectivity networks compared to healthy controls (HC). Previous work in healthy populations has shown that connectivity between the cerebellum and frontal areas is associated with cognitive speed. In this study, we sought to use MS as a model for cognitive dysfunction to examine the role that cerebellar-frontal connectivity may play in processing speed. 20 participants (10 MS, 10 HC) who met inclusion criteria underwent resting-state functional magnetic resonance (fMRI) imaging using a 3T MRI scanner. Cerebellar and frontal regions of interest (ROIs) were obtained from MPRAGE using FreeSurfer. Data were pre-processed and connectivity differences were analyzed using the CONN Toolbox. Outside of the scanner, the Digit Symbol Substitution Test (DSST) was administered as a measure of information processing speed and cognitive dysfunction. DSST performance was correlated with connectivity measures. MS patients exhibited higher connectivity between the cerebellum and left frontal lobe compared to HC. Furthermore, the relationship between processing speed and cerebello-frontal connectivity fundamentally differed between MS patients and HC. These results suggest a cerebello-frontal network that is vital to processing speed, and changes to this network as a result of MS pathophysiology may contribute to the impairment of MS patients.

To explore how age and sex affect cerebrospinal fluid (CSF) dynamics, particularly examining the relationships between CSF production, meningeal lymphatic vessel (mLV) characteristics, and glymphatic function. To determine the impact of brain lymphatic function on processing speed and cognitive performance.

The goal of precision brain health is to accurately predict individuals' longitudinal patterns of brain change. We trained a machine learning model to predict changes in a cognitive index of brain health from neurophysiologic metrics. A total of 48 participants (ages 21-65) completed a sensorimotor task during 2 functional magnetic resonance imaging sessions 6 mo apart. Hemodynamic response functions (HRFs) were parameterized using traditional (amplitude, dispersion, latency) and novel (curvature, canonicality) metrics, serving as inputs to a neural network model that predicted gain on indices of brain health (cognitive factor scores) for each participant. The optimal neural network model successfully predicted substantial gain on the cognitive index of brain health with 90% accuracy (determined by 5-fold cross-validation) from 3 HRF parameters: amplitude change, dispersion change, and similarity to a canonical HRF shape at baseline. For individuals with canonical baseline HRFs, substantial gain in the index is overwhelmingly predicted by decreases in HRF amplitude. For individuals with non-canonical baseline HRFs, substantial gain in the index is predicted by congruent changes in both HRF amplitude and dispersion. Our results illustrate that neuroimaging measures can track cognitive indices in healthy states, and that machine learning approaches using novel metrics take important steps toward precision brain health.

Background: Most multiple sclerosis (MS) patients experience fatigue and cognitive decline but the underlying mechanisms remain unknown. Previous work has shown whole brain resting cerebral metabolic rate of oxygen (CMRO2) is associated with the extent of these symptoms. However, it is not known if the association between global CMRO2 and MS-related cognitive speed and fatigue can be localized to specific brain regions. Based upon previous research suggesting prefrontal involvement in MS-related changes in cognitive speed and fatigue, we hypothesized that oxygen metabolic changes within prefrontal cortex (PFC) might form the pathophysiologic basis of cognitive performance and fatigue in MS patients.Objective: Investigate whether PFC Delta CMRO2 is associated with cognitive speed and fatigue in MS.Methods: MS and healthy control (HC) participants were scanned using a dual-echo fMRI sequence and underwent a hypercapnia calibration experiment that permitted estimation of Delta CMRO2 while performing a scanner version of symbol-digit modalities task, a measure of information processing speed and utilized in the clinic as a reliable sentinel biomarker for global cognitive impairment in MS. Participants then completed the Modified Fatigue Impact Scale (MFIS) to measure fatigue.Results: MS patients exhibited significant reductions in cognitive performance relative to HCs (p < 0.04). Prefrontal Delta CMRO2 explained significant variability (Delta R-2 = 0.11) in cognitive speed, over and above disease and demographic variables, for the MS group only. Prefrontal Delta CMRO2 was not associated with fatigue across groups. Delta CMRO2 in visual and motor areas were not associated with cognitive performance or fatigue for either group.Conclusion: Prefrontal oxygen metabolism may be a sensitive measure of MS-related cognitive decline.

Wearing a face mask has become essential to contain the spread of COVID-19 and has become mandatory when collecting fMRI data at most research institutions. Here, we investigate the effects of wearing a surgical mask on fMRI data in n = 37 healthy participants. Activations during finger tapping, emotional face matching, working memory tasks, and rest were examined. Preliminary fMRI analyses show that despite the different mask states, resting-state signals and task activations were relatively similar. Resting-state functional connectivity showed negligible attenuation patterns in mask-on compared with mask-off. Task-based ROI analysis also demonstrated no significant difference between the two mask states under each contrast investigated. Notwithstanding the overall insignificant effects, these results indicate that wearing a face mask during fMRI has little to no significant effect on resting-state and task activations.

Neural-vascular coupling (NVC) is the process by which oxygen and nutrients are delivered to metabolically active neurons by blood vessels. Murine models of NVC disruption have revealed its critical role in healthy neural function. We hypothesized that, in humans, aging exerts detrimental effects upon the integrity of the neural-glial-vascular system that underlies NVC. To test this hypothesis, calibrated functional magnetic resonance imaging (cfMRI) was used to characterize age-related changes in cerebral blood flow (CBF) and oxygen metabolism during visual cortex stimulation. Thirty-three younger and 27 older participants underwent cfMRI scanning during both an attention-controlled visual stimulation task and a hypercapnia paradigm used to calibrate the blood-oxygen-level-dependent signal. Measurement of stimulus-evoked blood flow and oxygen metabolism permitted calculation of the NVC ratio to assess the integrity of neural-vascular communication. Consistent with our hypothesis, we observed monotonic NVC ratio increases with increasing visual stimulation frequency in younger adults but not in older adults. Age-related changes in stimulus-evoked cerebrovascular and neurometabolic signal could not fully explain this disruption; increases in stimulus-evoked neurometabolic activity elicited corresponding increases in stimulus-evoked CBF in younger but not in older adults. These results implicate age-related, demand-dependent failures of the neural-glial-vascular structures that comprise the NVC system.

The conventional approach to investigating functional connectivity in the block-designed study usually concatenates task blocks or employs residuals of task activation. While providing many insights into brain functions, the block design adds more manipulation in functional network analysis that may reduce the purity of the blood oxygenation level-dependent signal. Recent studies utilized one single long run for task trials of the same condition, the so-called continuous design, to investigate functional connectivity based on task functional magnetic resonance imaging. Continuous brain activities associated with the single-task condition can be directly utilized for task-related functional connectivity assessment, which has been examined for working memory, sensory, motor, and semantic task experiments in previous research. But it remains unclear how the block and continuous design influence the assessment of task-related functional connectivity networks. This study aimed to disentangle the separable effects of block/continuous design and working memory load on task-related functional connectivity networks, by using repeated-measures analysis of variance. Across 50 young healthy adults, behavioral results of accuracy and reaction time showed a significant main effect of design as well as interaction between design and load. Imaging results revealed that the cingulo-opercular, fronto-parietal, and default model networks were associated with not only task activation, but significant main effects of design and load as well as their interaction on intra- and inter-network functional connectivity and global network topology. Moreover, a significant behavior-brain association was identified for the continuous design. This work has extended the evidence that continuous design can be used to study task-related functional connectivity and subtle brain-behavioral relationships.

Most studies examining neurocognitive aging are based on the blood-oxygen level-dependent signal obtained during functional magnetic resonance imaging (fMRI). The physiological basis of this signal is neural-vascular coupling, the process by which neurons signal cerebrovasculature to dilate in response to an increase in active neural metabolism due to stimulation. These fMRI studies of aging rely on the hemodynamic equivalence assumption that this process is not disrupted by physiologic deterioration associated with aging. Studies of neural-vascular coupling challenge this assumption and show that neural-vascular coupling is closely related to cognition. In this review, we put forward a theory of processing speed decline in aging and how it is related to age-related neural-vascular coupling changes based on the results of studies elucidating the relationships between cognition, cerebrovascular dynamics, and aging.

Aging entails a multifaceted complex of changes in macro- and micro-structural properties of human brain gray matter (GM) and white matter (WM) tissues, as well as in intellectual abilities. To better capture tissue-specific brain aging, we combined volume and distribution properties of diffusivity indices to derive subject-specific age scores for each tissue. We compared age-related variance between younger and older adults for GM and WM age scores, and tested whether tissue-specific age scores could explain different effects of aging on fluid (Gf) and crystalized (Gc) intelligence in younger and older adults. Chronological age was strongly associated with GM (R2 = 0.73) and WM (R2 = 0.57) age scores. The GM age score accounted for significantly more variance in chronological age in younger relative to older adults (p < 0.001), whereas the WM age score accounted for significantly more variance in chronological age in older compared to younger adults (p < 0.025). Consistent with existing literature, younger adults outperformed older adults in Gf while older adults outperformed younger adults in Gc. The GM age score was negatively associated with Gf in younger adults (p < 0.02), whereas the WM age score was negatively associated with Gc in older adults (p < 0.02). Our results provide evidence for differences in the effects of age on GM and WM in younger versus older adults that may contribute to age-related differences in Gf and Gc.

Standard magnetic resonance imaging approaches offer high-resolution but indirect measures of neural activity, limiting understanding of the physiological processes associated with imaging findings. Here, we used calibrated functional magnetic resonance imaging during the resting state to recover low-frequency fluctuations of the cerebral metabolic rate of oxygen (CMRO2 ). We tested whether functional connections derived from these fluctuations exhibited organization properties similar to those established by previous standard functional and anatomical connectivity studies. Seventeen participants underwent 20 min of resting imaging during dual-echo, pseudocontinuous arterial spin labeling, and blood-oxygen-level dependent (BOLD) signal acquisition. Participants also underwent a 10 min normocapnic and hypercapnic procedure. Brain-wide, CMRO2 low-frequency fluctuations were subjected to graph-based and voxel-wise functional connectivity analyses. Results demonstrated that connections derived from resting CMRO2 fluctuations exhibited complex, small-world topological properties (i.e., high integration and segregation, cost efficiency) consistent with those observed in previous studies using functional and anatomical connectivity approaches. Voxel-wise CMRO2 connectivity also exhibited spatial patterns consistent with four targeted resting-state subnetworks: two association (i.e., frontoparietal and default mode) and two perceptual (i.e., auditory and occipital-visual). These are the first findings to support the use of calibration-derived CMRO2 low-frequency fluctuations for detecting brain-wide organizational properties typical of healthy participants. We discuss interpretations, advantages, and challenges in using calibration-derived oxygen metabolism signals for examining the intrinsic organization of the human brain.

AbstractThe process of aging includes changes in cellular biology that affect local interactions between cells and their environments and eventually propagate to systemic levels. In the brain, where neurons critically depend on an efficient and dynamic supply of oxygen and glucose, age‐related changes in the complex interaction between the brain parenchyma and the cerebrovasculature have effects on health and functioning that negatively impact cognition and play a role in pathology. Thus, cerebrovascular health is considered one of the main mechanisms by which a healthy lifestyle, such as habitual cardiorespiratory exercise and a healthful diet, could lead to improved cognitive outcomes with aging. This review aims at detailing how the physiology of the cerebral vascular system changes with age and how these changes lead to differential trajectories of cognitive maintenance or decline. This provides a framework for generating specific mechanistic hypotheses about the efficacy of proposed interventions and lifestyle covariates that contribute to enhanced cognitive well‐being. Finally, we discuss the methodological implications of age‐related changes in the cerebral vasculature for human cognitive neuroscience research and propose directions for future experiments aimed at investigating age‐related changes in the relationship between physiology and cognitive mechanisms.