Investigating nutrient biomarkers of healthy brain aging: a multimodal brain imaging study.

The emerging field of Nutritional Cognitive Neuroscience aims to uncover specific foods and nutrients that promote healthy brain aging. Central to this effort is the discovery of nutrient profiles that can be targeted in nutritional interventions designed to promote brain health with respect to multimodal neuroimaging measures of brain structure, function, and metabolism. The present study therefore conducted one of the largest and most comprehensive nutrient biomarker studies examining multimodal neuroimaging measures of brain health within a sample of 100 older adults. To assess brain health, a comprehensive battery of well-established cognitive and brain imaging measures was administered, along with 13 blood-based biomarkers of diet and nutrition. The findings of this study revealed distinct patterns of aging, categorized into two phenotypes of brain health based on hierarchical clustering. One phenotype demonstrated an accelerated rate of aging, while the other exhibited slower-than-expected aging. A t-test analysis of dietary biomarkers that distinguished these phenotypes revealed a nutrient profile with higher concentrations of specific fatty acids, antioxidants, and vitamins. Study participants with this nutrient profile demonstrated better cognitive scores and delayed brain aging, as determined by a t-test of the means. Notably, participant characteristics such as demographics, fitness levels, and anthropometrics did not account for the observed differences in brain aging. Therefore, the nutrient pattern identified by the present study motivates the design of neuroscience-guided dietary interventions to promote healthy brain aging.

The utilitarian brain: Moving beyond the Free Energy Principle.

The Free Energy Principle (FEP) is a normative computational framework for iterative reduction of prediction error and uncertainty through perception-intervention cycles that has been presented as a potential unifying theory of all brain functions (Friston, 2006). Any theory hoping to unify the brain sciences must be able to explain the mechanisms of decision-making, an important cognitive faculty, without the addition of independent, irreducible notions. This challenge has been accepted by several proponents of the FEP (Friston, 2010; Gershman, 2019). We evaluate attempts to reduce decision-making to the FEP, using Lucas' (2005) meta-theory of the brain's contextual constraints as a guidepost. We find reductive variants of the FEP for decision-making unable to explain behavior in certain types of diagnostic, predictive, and multi-armed bandit tasks. We trace the shortcomings to the core theory's lack of an adequate notion of subjective preference or "utility", a concept central to decision-making and grounded in the brain's biological reality. We argue that any attempts to fully reduce utility to the FEP would require unrealistic assumptions, making the principle an unlikely candidate for unifying brain science. We suggest that researchers instead attempt to identify contexts in which either informational or independent reward constraints predominate, delimiting the FEP's area of applicability. To encourage this type of research, we propose a two-factor formal framework that can subsume any FEP model and allows experimenters to compare the contributions of informational versus reward constraints to behavior.

Assessing blood oxygen level-dependent signal variability as a biomarker of brain injury in sport-related concussion.

Mild traumatic brain injury is a complex neurological disorder of significant concern among athletes who play contact sports. Athletes who sustain sport-related concussion typically undergo physical examination and neurocognitive evaluation to determine injury severity and return-to-play status. However, traumatic disruption to neurometabolic processes can occur with minimal detectable anatomic pathology or neurocognitive alteration, increasing the risk that athletes may be cleared for return-to-play during a vulnerable period and receive a repetitive injury. This underscores the need for sensitive functional neuroimaging methods to detect altered cerebral physiology in concussed athletes. The present study compared the efficacy of Immediate Post-concussion Assessment and Cognitive Testing composite scores and whole-brain measures of blood oxygen level-dependent signal variability for classifying concussion status and predicting concussion symptomatology in healthy, concussed and repetitively concussed athletes, assessing blood oxygen level-dependent signal variability as a potential diagnostic tool for characterizing functional alterations to cerebral physiology and assisting in the detection of sport-related concussion. We observed significant differences in regional blood oxygen level-dependent signal variability measures for concussed athletes but did not observe significant differences in Immediate Post-concussion Assessment and Cognitive Testing scores of concussed athletes. We further demonstrate that incorporating measures of functional brain alteration alongside Immediate Post-concussion Assessment and Cognitive Testing scores enhances the sensitivity and specificity of supervised random forest machine learning methods when classifying and predicting concussion status and post-concussion symptoms, suggesting that alterations to cerebrovascular status characterize unique variance that may aid in the detection of sport-related concussion and repetitive mild traumatic brain injury. These results indicate that altered blood oxygen level-dependent variability holds promise as a novel neurobiological marker for detecting alterations in cerebral perfusion and neuronal functioning in sport-related concussion, motivating future research to establish and validate clinical assessment protocols that can incorporate advanced neuroimaging methods to characterize altered cerebral physiology following mild traumatic brain injury.

Connectome-based predictive modeling of fluid intelligence: evidence for a global system of functionally integrated brain networks.

Cognitive neuroscience continues to advance our understanding of the neural foundations of human intelligence, with significant progress elucidating the role of the frontoparietal network in cognitive control mechanisms for flexible, intelligent behavior. Recent evidence in network neuroscience further suggests that this finding may represent the tip of the iceberg and that fluid intelligence may depend on the collective interaction of multiple brain networks. However, the global brain mechanisms underlying fluid intelligence and the nature of multi-network interactions remain to be well established. We therefore conducted a large-scale Connectome-based Predictive Modeling study, administering resting-state fMRI to 159 healthy college students and examining the contributions of seven intrinsic connectivity networks to the prediction of fluid intelligence, as measured by a state-of-the-art cognitive task (the Bochum Matrices Test). Specifically, we aimed to: (i) identify whether fluid intelligence relies on a primary brain network or instead engages multiple brain networks; and (ii) elucidate the nature of brain network interactions by assessing network allegiance (within- versus between-network connections) and network topology (strong versus weak connections) in the prediction of fluid intelligence. Our results demonstrate that whole-brain predictive models account for a large and significant proportion of variance in fluid intelligence (18%) and illustrate that the contribution of individual networks is relatively modest by comparison. In addition, we provide novel evidence that the global architecture of fluid intelligence prioritizes between-network connections and flexibility through weak ties. Our findings support a network neuroscience approach to understanding the collective role of brain networks in fluid intelligence and elucidate the system-wide network mechanisms from which flexible, adaptive behavior is constructed.

Integrating Nutrient Biomarkers, Cognitive Function, and Structural MRI Data to Build Multivariate Phenotypes of Healthy Aging.

BACKGROUND: Research in the emerging field of nutritional cognitive neuroscience demonstrates that many aspects of nutrition-from entire diets to specific nutrients-affect cognitive performance and brain health. OBJECTIVES: Although previous research has primarily examined the bivariate relationship between nutrition and cognition or nutrition and brain health, this study sought to investigate the joint relationship between these essential and interactive elements of human health. METHODS: We applied a state-of-the-art data fusion method, coupled matrix tensor factorization, to characterize the joint association between measures of nutrition (52 nutrient biomarkers), cognition (Wechsler Abbreviated Test of Intelligence and Wechsler Memory Scale), and brain health (high-resolution MRI measures of structural brain volume) within a cross-sectional sample of 111 healthy older adults, with an average age of 69.1 y, 62% being female, and an average body mass index of 26.0 kg/m2. RESULTS: Data fusion uncovered latent factors that capture the joint association between specific nutrient profiles, cognitive measures, and cortical volumes, demonstrating the respects in which these health domains are coupled. A hierarchical cluster analysis further revealed systematic differences between a subset of variables contributing to the underlying latent factors, providing evidence for multivariate phenotypes that represent high and low levels of performance across multiple health domains. The primary features that distinguish between each phenotype were as follows: 1) nutrient biomarkers for monounsaturated and polyunsaturated fatty acids; 2) cognitive measures of immediate, auditory, and delayed memory; and 3) brain volumes within frontal, temporal, and parietal cortexes. CONCLUSIONS: By incorporating innovations in nutritional epidemiology (nutrient biomarker analysis), cognitive neuroscience (high-resolution structural brain imaging), and statistics (data fusion), this study provides an interdisciplinary synthesis of methods that elucidate how nutrition, cognition, and brain health are integrated through lifestyle choices that affect healthy aging.

Investigating cognitive neuroscience theories of human intelligence: A connectome-based predictive modeling approach.

Central to modern neuroscientific theories of human intelligence is the notion that general intelligence depends on a primary brain region or network, engaging spatially localized (rather than global) neural representations. Recent findings in network neuroscience, however, challenge this assumption, providing evidence that general intelligence may depend on system-wide network mechanisms, suggesting that local representations are necessary but not sufficient to account for the neural architecture of human intelligence. Despite the importance of this key theoretical distinction, prior research has not systematically investigated the role of local versus global neural representations in predicting general intelligence. We conducted a large-scale connectome-based predictive modeling study (N = 297), administering resting-state fMRI and a comprehensive cognitive battery to evaluate the efficacy of modern neuroscientific theories of human intelligence, including spatially localized theories (Lateral Prefrontal Cortex Theory, Parieto-Frontal Integration Theory, and Multiple Demand Theory) and recent global accounts (Process Overlap Theory and Network Neuroscience Theory). The results of our study demonstrate that general intelligence can be predicted by local functional connectivity profiles but is most robustly explained by global profiles of whole-brain connectivity. Our findings further suggest that the improved efficacy of global theories is not reducible to a greater strength or number of connections, but instead results from considering both strong and weak connections that provide the basis for intelligence (as predicted by the Network Neuroscience Theory). Our results highlight the importance of considering local neural representations in the context of a global information-processing architecture, suggesting future directions for theory-driven research on system-wide network mechanisms underlying general intelligence.

The Effects of Sustained Literacy Engagement on Cognition and Sentence Processing Among Older Adults.

Considerable evidence suggests that language processing depends on memory processes, which are vulnerable to declines with aging. Yet little is known about the effects of language processing in the form of sustained literacy engagement on memory and other aspects of cognition. In the current study, adults (60-79 years of age) were randomly assigned to an 8-week program of leisure reading (n = 38) or to an active puzzle control (n = 38). Relative to the control, the experimental group showed differential improvement in verbal working memory and episodic memory. The experimental group also showed evidence of enhanced conceptual integration in sentence processing. These effects did not vary as a function of personality characteristics (e.g., openness) hypothesized to be compatible with literacy engagement. These findings support the idea that the exercise of cognitive capacities in the context of everyday life may offset age-related impairment in areas of cognition engaged by the activity, regardless of dispositional fit.

Cognitive Neuroscience Meets the Community of Knowledge.

Cognitive neuroscience seeks to discover the biological foundations of the human mind. One goal is to explain how mental operations are generated by the information processing architecture of the human brain. Our aim is to assess whether this is a well-defined objective. Our contention will be that it is not because the information processing of any given individual is not contained entirely within that individual's brain. Rather, it typically includes components situated in the heads of others, in addition to being distributed across parts of the individual's body and physical environment. Our focus here will be on cognition distributed across individuals, or on what we call the "community of knowledge," the challenge that poses for reduction of cognition to neurobiology and the contribution of cognitive neuroscience to the study of communal processes.

Beyond IQ: The Importance of Metacognition for the Promotion of Global Wellbeing.

Global policy makers increasingly adopt subjective wellbeing as a framework within which to measure and address human development challenges, including policies to mitigate consequential societal problems. In this review, we take a systems-level perspective to assemble evidence from studies of wellbeing, of collective intelligence, and of metacognition and argue for a virtuous cycle for health promotion in which the increased collective intelligence of groups: (1) enhances the ability of such groups to address consequential societal problems; (2) promotes the wellbeing of societies and the individual wellbeing of people within groups; and, finally, (3) enables prosocial actions that further promote collective problem-solving and global wellbeing. Notably, evidence demonstrates that effective collaboration and teamwork largely depend on social skills for metacognitive awareness-the capacity to evaluate and control our own mental processes in the service of social problem-solving. Yet, despite their importance, metacognitive skills may not be well-captured by measures of general intelligence. These skills have instead been the focus of decades of research in the psychology of human judgment and decision-making. This literature provides well-validated tests of metacognitive awareness and demonstrates that the capacity to use analysis and deliberation to evaluate intuitive responses is an important source of individual differences in decision-making. Research in network neuroscience further elucidates the topology and dynamics of brain networks that enable metacognitive awareness, providing key targets for intervention. As such, we further discuss emerging scientific interventions to enhance metacognitive skills (e.g., based on mindfulness meditation, and physical activity and aerobic fitness), and how such interventions may catalyze the virtuous cycle to improve collective intelligence, societal problem-solving, and global wellbeing.

Carotenoid-Rich Brain Nutrient Pattern Is Positively Correlated With Higher Cognition and Lower Depression in the Oldest Old With No Dementia.

Background: Healthy dietary patterns are related to better cognitive health in aging populations. While levels of individual nutrients in neural tissues are individually associated with cognitive function, the investigation of nutrient patterns in human brain tissue has not been conducted. Methods: Brain tissues were acquired from frontal and temporal cortices of 47 centenarians from the Georgia Centenarian Study. Fat-soluble nutrients (carotenoids, vitamins A, E, K, and fatty acids [FA]) were measured and averaged from the two brain regions. Nutrient patterns were constructed using principal component analysis. Cognitive composite scores were constructed from cognitive assessment from the time point closest to death. Dementia status was rated by Global Deterioration Scale (GDS). Pearson's correlation coefficients between NP scores and cognitive composite scores were calculated controlling for sex, education, hypertension, diabetes, and APOE ε4 allele. Result: Among non-demented subjects (GDS = 1-3, n = 23), a nutrient pattern higher in carotenoids was consistently associated with better performance on global cognition (r = 0.38, p = 0.070), memory (r = 0.38, p = 0.073), language (r = 0.42, p = 0.046), and lower depression (r = -0.40, p = 0.090). The findings were confirmed with univariate analysis. Conclusion: Both multivariate and univariate analyses demonstrate that brain nutrient pattern explained mainly by carotenoid concentrations is correlated with cognitive function among subjects who had no dementia. Investigation of their synergistic roles on the prevention of age-related cognitive impairment remains to be performed.

Enhanced physical and cognitive performance in active duty Airmen: evidence from a randomized multimodal physical fitness and nutritional intervention.

Achieving military mission objectives requires high levels of performance from Airmen who operate under extreme physical and cognitive demands. Thus, there is a critical need to establish scientific interventions to enhance physical fitness and cognitive performance-promoting the resilience of Airmen and aiding in mission success. We therefore conducted a comprehensive, 12-week randomized controlled trial in active-duty Air Force Airmen (n = 148) to compare the efficacy of a multimodal intervention comprised of high-intensity interval aerobic fitness and strength training paired with a novel nutritional supplement [comprised of ß-hydroxy ß-methylbutyrate (HMB), lutein, phospholipids, DHA and selected micronutrients including B12 and folic acid] to high-intensity interval aerobic fitness and strength training paired with a standard of care placebo beverage. The exercise intervention alone improved several dimensions of physical fitness [strength and endurance (+ 8.3%), power (+ 0.85%), mobility and stability (+ 22%), heart rate (- 1.1%) and lean muscle mass (+ 1.4%)] and cognitive function [(episodic memory (+ 9.5%), processing efficiency (+ 7.5%), executive function reaction time (- 4.8%) and fluid intelligence accuracy (+ 19.5%)]. Relative to exercise training alone, the multimodal fitness and nutritional intervention further improved working memory (+ 9.0%), fluid intelligence reaction time (- 7.7%), processing efficiency (+ 1.8%), heart rate (- 2.4%) and lean muscle mass (+ 1.5%). These findings establish the efficacy of a multimodal intervention that incorporates aerobic fitness and strength training with a novel nutritional supplement to enhance military performance objectives and to provide optimal exercise training and nutritional support for the modern warfighter.

Standard-space atlas of the viscoelastic properties of the human brain.

Standard anatomical atlases are common in neuroimaging because they facilitate data analyses and comparisons across subjects and studies. The purpose of this study was to develop a standardized human brain atlas based on the physical mechanical properties (i.e., tissue viscoelasticity) of brain tissue using magnetic resonance elastography (MRE). MRE is a phase contrast-based MRI method that quantifies tissue viscoelasticity noninvasively and in vivo thus providing a macroscopic representation of the microstructural constituents of soft biological tissue. The development of standardized brain MRE atlases are therefore beneficial for comparing neural tissue integrity across populations. Data from a large number of healthy, young adults from multiple studies collected using common MRE acquisition and analysis protocols were assembled (N = 134; 78F/ 56 M; 18-35 years). Nonlinear image registration methods were applied to normalize viscoelastic property maps (shear stiffness, µ, and damping ratio, ξ) to the MNI152 standard structural template within the spatial coordinates of the ICBM-152. We find that average MRE brain templates contain emerging and symmetrized anatomical detail. Leveraging the substantial amount of data assembled, we illustrate that subcortical gray matter structures, white matter tracts, and regions of the cerebral cortex exhibit differing mechanical characteristics. Moreover, we report sex differences in viscoelasticity for specific neuroanatomical structures, which has implications for understanding patterns of individual differences in health and disease. These atlases provide reference values for clinical investigations as well as novel biophysical signatures of neuroanatomy. The templates are made openly available (github.com/mechneurolab/mre134) to foster collaboration across research institutions and to support robust cross-center comparisons.

Opposing associations between sedentary time and decision-making competence in young adults revealed by functional connectivity in the dorsal attention network.

How daily physical activity and sedentary time relate to human judgement and functional connectivity (FC) patterns that support them remains underexplored. We investigated the relationships between accelerometer-measured moderate-to-vigorous physical activity (MVPA) and sedentary time to decision-making competence (DMC) in young adults using a comprehensive Adult-Decision Making Competence battery. We applied graph theory measures of global and local efficiency to test the mediating effects of FC in cognitively salient brain networks (fronto-parietal; dorsal attention, DAN; ventral attention; and default mode), assessed from the resting-state fMRI. Sedentary time was related to lower susceptibility to a framing bias. However, once global and local efficiency of the DAN were considered we observed (1) higher susceptibility to framing with more sedentary time, mediated through lower local and global efficiency in the DAN, and (2) lower susceptibility to framing with more sedentary time. MVPA was not related to DMC or graph theory measures. These results suggest that remaining sedentary may reduce neurofunctional readiness for top-down control and decrease engagement of deliberate thought, required to ignore irrelevant aspects of a problem. The positive effect suggests that the relationship between sedentary time and DMC may be moderated by unmeasured factors such as the type of sedentary behavior.

Body mass and cardiorespiratory fitness are associated with altered brain metabolism.

Magnetic Resonance Spectroscopy provides measures of brain chemistry that are sensitive to cardiorespiratory fitness and body composition. The concentration of N-acetyl aspartic acid (NAA) is of interest because it is a marker of neuronal integrity. The ratio of NAA to creatine, a standard reference metabolite, has been shown to correlate with measures of both cardiorespiratory fitness and body composition. However, previous studies have explored these effects in isolation, making it impossible to know which of these highly correlated measures drive the correlations with NAA/Cr. As a result, the mechanisms underlying their association remain to be established. We therefore conducted a comprehensive study to investigate the relative contributions of cardiorespiratory fitness and percent body fat in predicting NAA/Cr. We demonstrate that NAA/Cr in white matter is correlated with percent body fat, and that this relationship largely subsumes the correlation of NAA/Cr with cardiorespiratory fitness. These results underscore the association of body composition with axonal integrity and suggests that this relationship drives the association of NAA/Cr with physical fitness in young adults.

Comorbid Conditions Differentiate Rehabilitation Profiles in Traumatic Versus Nontraumatic Brain Injury: A Retrospective Analysis Using a Medical Database.

PURPOSE: We examined the relationship between comorbid medical conditions and changes in cognition over the course of rehabilitation following acquired brain injury. In particular, we compared outcomes between traumatic brain injury (TBI) and non-TBI using a retrospective inpatient rehabilitation dataset. We hypothesized that differences by diagnosis would be minimized among subgroups of patients with common comorbid medical conditions. MATERIALS AND METHODS: We used the Functional Independence Measure (FIM)-cognition subscale to index changes in cognition over rehabilitation. A decision tree classifier determined the top 10 comorbid conditions that maximally differentiated TBI and non-TBI. Ten subsets of patients were identified by matching on these conditions, in rank order. Data from these subsets were submitted to repeated-measures logistic regression to establish the minimum degree of commonality in comorbid conditions that would produce similar cognitive rehabilitation, regardless of etiology. RESULTS: The TBI group demonstrated a greater increase in ordinal scores over time relative to non-TBI, across all subscales of the FIM-cognition. When both groups were matched on the top 3 symptoms, there were no significant group differences in rehabilitation trajectory in problem-solving and memory domains (Cohen's d range: 0.2-0.4). CONCLUSION: Comorbid medical conditions explain differences in cognitive rehabilitation trajectories following acquired brain injury beyond etiology.

Antioxidant Therapies in Traumatic Brain Injury.

Due to a multiplicity of causes provoking traumatic brain injury (TBI), TBI is a highly heterogeneous pathology, characterized by high mortality and disability rates. TBI is an acute neurodegenerative event, potentially and unpredictably evolving into sub-chronic and chronic neurodegenerative events, with transient or permanent neurologic, cognitive, and motor deficits, for which no valid standardized therapies are available. A vast body of literature demonstrates that TBI-induced oxidative/nitrosative stress is involved in the development of both acute and chronic neurodegenerative disorders. Cellular defenses against this phenomenon are largely dependent on low molecular weight antioxidants, most of which are consumed with diet or as nutraceutical supplements. A large number of studies have evaluated the efficacy of antioxidant administration to decrease TBI-associated damage in various animal TBI models and in a limited number of clinical trials. Points of weakness of preclinical studies are represented by the large variability in the TBI model adopted, in the antioxidant tested, in the timing, dosages, and routes of administration used, and in the variety of molecular and/or neurocognitive parameters evaluated. The analysis of the very few clinical studies does not allow strong conclusions to be drawn on the real effectiveness of antioxidant administration to TBI patients. Standardizing TBI models and different experimental conditions, as well as testing the efficacy of administration of a cocktail of antioxidants rather than only one, should be mandatory. According to some promising clinical results, it appears that sports-related concussion is probably the best type of TBI to test the benefits of antioxidant administration.

Individual differences in the neurobiology of fluid intelligence predict responsiveness to training: Evidence from a comprehensive cognitive, mindfulness meditation, and aerobic exercise intervention.

BACKGROUND: Fluid intelligence (Gf) is a critical cognitive ability that is predictive of real-world outcomes, and it has been a persistent aim to characterize its neural architecture. PROCEDURE: We advance our prior research by applying latent class analysis to evaluate individual differences in the neural and cognitive foundations of Gf over the course of a 16-week randomized, multi-modal intervention trial in neurologically healthy, younger adults (N = 424). RESULTS: Controlling for pre-intervention ability, three latent classes described individual performance at post-intervention and one group (n = 71) showed greater gains in visuospatial reasoning and high performance at post-intervention. The high performance group was predicted by larger anterior cingulate cortex, caudate and hippocampus volumes, and smaller middle frontal, insula and parahippocampal cortex volumes. CONCLUSION: Regions that support cognitive control, working memory, and relational processes differentiated individuals who had higher Gf ability at pre-intervention and demonstrated a cumulative better response to the intervention.

Concentrations of Circulating Phylloquinone, but Not Cerebral Menaquinone-4, Are Positively Correlated with a Wide Range of Cognitive Measures: Exploratory Findings in Centenarians.

BACKGROUND: Vitamin K (VK) exists in the form of phylloquinone (PK) and menaquinones (MKs). Roles of VK on cognitive health in the elderly are emerging, but there is limited evidence on VK uptake and metabolism in human brain. OBJECTIVES: The primary objective of this study was to characterize VK distribution in brains of an elderly population with varied cognitive function. In addition, associations among circulating (a biomarker of VK intake) and cerebral VK concentrations and cognition were investigated. METHODS: Serum or plasma (n = 27) and brain samples from the frontal cortex (FC; n = 46) and the temporal cortex (TC; n = 33) were acquired from 48 decedents (aged 98-107 y; 25 demented and 23 nondemented) enrolled in the Georgia Centenarian Study. Both circulating and brain VK concentrations were measured using HPLC with fluorescence detection. Cognitive assessment was performed within 1 y prior to mortality. Partial correlations between serum/plasma or cerebral VK concentrations and cognitive function were performed, adjusting for covariates and separating by dementia and antithrombotic use. RESULTS: MK-4 was the predominant vitamer in both FC (mean ± SD = 4.92 ± 2.31 pmol/g, ≥89.15% ± 5.09% of total VK) and TC (4.60 ± 2.11 pmol/g, ≥89.71% ± 4.43% of total VK) regardless of cognitive status. Antithrombotic users had 34.0% and 53.9% lower MK-4 concentrations in FC (P < 0.05) and TC (P < 0.001), respectively. Circulating PK was not correlated with cerebral MK-4 or total VK concentrations. Circulating PK concentrations were significantly associated with a wide range of cognitive measures in nondemented centenarians (P < 0.05). In contrast, cerebral MK-4 concentrations were not associated with cognitive performance, either before or after exclusion of antithrombotic users. CONCLUSIONS: Circulating VK concentrations are not related to cerebral MK-4 concentrations in centenarians. Cerebral MK-4 concentrations are tightly regulated over a range of VK intakes and cognitive function. Circulating PK may reflect intake of VK-rich foods containing other dietary components beneficial to cognitive health. Further investigation of VK uptake and metabolism in the brain is warranted.