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.

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.

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.

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.

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.

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.

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.

Nutrient biomarker patterns, cognitive function, and fMRI measures of network efficiency in the aging brain.

A central aim of research in the psychological and brain sciences is to establish therapeutic interventions to promote healthy brain aging. Accumulating evidence indicates that diet and the many bioactive substances present in food are reasonable interventions to examine for dementia prevention. However, interdisciplinary research that applies methods from nutritional epidemiology and network neuroscience to investigate the role of nutrition in shaping functional brain network efficiency remains to be conducted. The present study therefore sought to combine methods across disciplines, applying nutrient biomarker pattern (NBP) analysis to capture the effects of plasma nutrients in combination and to examine their collective influence on measures of functional brain network efficiency (small-world propensity). We examined the contribution of NBPs to multiple indices of cognition and brain health in non-demented elders (n = 116), investigating performance on measures of general intelligence, executive function, and memory, and resting-state fMRI measures of brain network efficiency within seven intrinsic connectivity networks. Statistical moderation investigated whether NBPs influenced network efficiency and cognitive outcomes. The results revealed five NBPs that were associated with enhanced cognitive performance, including biomarker patterns high in plasma: (1) ω-3 and ω-6 polyunsaturated fatty acids (PUFAs), (2) lycopene, (3) ω-3 PUFAs, (4) carotenoids, and (5) vitamins B (riboflavin, folate, B12) and D. Furthermore, three NBPs were associated with enhanced functional brain network efficiency, including biomarker patterns high in plasma: (1) ω-6 PUFAs, (2) ω-3 PUFAs, and (3) carotene. Finally, ω-3 PUFAs moderated the fronto-parietal network and general intelligence, while ω-6 PUFAs and lycopene moderated the dorsal attention network and executive function. In sum, NBPs account for a significant proportion of variance in measures of cognitive performance and functional brain network efficiency. The results motivate a multidisciplinary approach that applies methods from nutritional epidemiology (NBP analysis) and cognitive neuroscience (functional brain network efficiency) to characterize the impact of nutrition on human health, aging, and disease.

Individual differences in analogical reasoning revealed by multivariate task-based functional brain imaging.

Although analogical reasoning (AR) plays a central role in higher-level cognition and constitutes a key source of individual differences in intellectual ability, the neural mechanisms that account for individual differences in AR remain to be well characterized. Here we investigated individual differences in AR within a large sample (n = 229), using multivariate fMRI analysis (a simple multiple kernel learning machine). The individual AR capability was positively correlated with activation level in a prefrontal executive network and a visuospatial network. Notably, the best predictors of individual differences in AR within these networks were activation in the dorsomedial prefrontal cortex (response selection) and the lingual gyrus (visual feature mapping). In contrast, AR capability was negatively correlated with activation in the default mode network. The implications of the reported findings are twofold: (i) Individual differences in AR depend on multiple executive and visuospatial brain regions, where their respective contributions are contingent upon the individuals' cognitive skills; (ii) Brain regions associated with individual differences in AR only partially overlap with brain regions sensitive to the associated task demands (i.e., brain regions sensitive to the analogy relational complexity, at the group-level). We discuss implications of such brain organization supporting AR as an example for brain architecture underlying higher-level cognitive processes.

Cognitive and neural architecture of decision making competence.

Although cognitive neuroscience has made remarkable progress in understanding the neural foundations of goal-directed behavior and decision making, neuroscience research on decision making competence, the capacity to resist biases in human judgment and decision making, remain to be established. Here, we investigated the cognitive and neural mechanisms of decision making competence in 283 healthy young adults. We administered the Adult Decision Making Competence battery to assess the respondent's capacity to resist standard biases in decision making, including: (1) resistance to framing, (2) recognizing social norms, (3) over/under confidence, (4) applying decision rules, (5) consistency in risk perception, and (6) resistance to sunk costs. Decision making competence was assessed in relation to core facets of intelligence, including measures of crystallized intelligence (Shipley Vocabulary), fluid intelligence (Figure Series), and logical reasoning (LSAT). Structural equation modeling was applied to examine the relationship(s) between each cognitive domain, followed by an investigation of their association with individual differences in cortical thickness, cortical surface area, and cortical gray matter volume as measured by high-resolution structural MRI. The results suggest that: (i) decision making competence is associated with cognitive operations for logical reasoning, and (ii) these convergent processes are associated with individual differences within cortical regions that are widely implicated in cognitive control (left dACC) and social decision making (right superior temporal sulcus; STS). Our findings motivate an integrative framework for understanding the neural mechanisms of decision making competence, suggesting that individual differences in the cortical surface area of left dACC and right STS are associated with the capacity to overcome decision biases and exhibit competence in decision making.

Nutrient biomarkers shape individual differences in functional brain connectivity: Evidence from omega-3 PUFAs.

A wealth of neuroscience evidence demonstrates that diet and nutrition play an important role in structural brain plasticity, promoting the development of gray matter volume and maintenance of white matter integrity across the lifespan. However, the role of nutrition in shaping individual differences in the functional brain connectome remains to be well established. We therefore investigated whether nutrient biomarkers known to have beneficial effects on brain structure (i.e., the omega-3 polyunsaturated fatty acids; ω-3 PUFAs), explain individual differences in functional brain connectivity within healthy older adults (N = 96). Our findings demonstrate that ω-3 PUFAs are associated with individual differences in functional connectivity within regions that support executive function (prefrontal cortex), memory (hippocampus), and emotion (amygdala), and provide key evidence that the influence of these regions on global network connectivity reliably predict general, fluid, and crystallized intelligence. The observed findings not only elucidate the role of ω-3 PUFAs in functional brain plasticity and intelligence, but also motivate future studies to examine their impact on psychological health, aging, and disease.

Aerobic Fitness Explains Individual Differences in the Functional Brain Connectome of Healthy Young Adults.

A wealth of neuroscience evidence demonstrates that aerobic fitness enhances structural brain plasticity, promoting the development of gray matter volume and maintenance of white matter integrity within networks for executive function, attention, learning, and memory. However, the role of aerobic fitness in shaping the functional brain connectome remains to be established. The present work therefore investigated the effects of aerobic fitness (as measured by VO2max) on individual differences in whole-brain functional connectivity assessed from resting state fMRI data. Using a connectome-wide association study, we identified significant brain-fitness relationships within a large sample of healthy young adults (N = 242). The results revealed several regions within frontal, temporal, parietal, and cerebellar cortex, having significant association with aerobic fitness. We further characterized the influence of these regions on 7 intrinsic connectivity networks, demonstrating the greatest association with networks that are known to mediate the beneficial effects of aerobic fitness on executive function (frontoparietal network), attention and learning (dorsal and ventral attention network), and memory (default mode network). In addition, we provide evidence that connectivity strength between these regions and the frontoparietal network is predictive of individuals' fluid intelligence.

Double dissociation of structure-function relationships in memory and fluid intelligence observed with magnetic resonance elastography.

Brain tissue mechanical properties, measured in vivo with magnetic resonance elastography (MRE), have proven to be sensitive metrics of neural tissue integrity. Recently, our group has reported on the positive relationship between viscoelasticity of the hippocampus and performance on a relational memory task in healthy young adults, which highlighted the potential of sensitive MRE measures for studying brain health and its relation to cognitive function; however, structure-function relationships outside of the hippocampus have not yet been explored. In this study, we examined the relationships between viscoelasticity of both the hippocampus and the orbitofrontal cortex and performance on behavioral assessments of relational memory and fluid intelligence. In a sample of healthy, young adults (N = 53), there was a significant, positive relationship between orbitofrontal cortex viscoelasticity and fluid intelligence performance (r = 0.42; p = .002). This finding is consistent with the previously reported relationship between hippocampal viscoelasticity and relational memory performance (r = 0.41; p = .002). Further, a significant double dissociation between the orbitofrontal-fluid intelligence relationship and the hippocampal-relational memory relationship was observed. These data support the specificity of regional brain MRE measures in support of separable cognitive functions. This report of a structure-function relationship observed with MRE beyond the hippocampus suggests a future role for MRE as a sensitive neuroimaging technique for brain mapping.

Individual differences in decision making competence revealed by multivariate fMRI.

While an extensive literature in decision neuroscience has elucidated the neurobiological foundations of decision making, prior research has focused primarily on group-level effects in a sample population. Due to the presence of inherent differences between individuals' cognitive abilities, it is also important to examine the neural correlates of decision making that explain interindividual variability in cognitive performance. This study therefore investigated how individual differences in decision making competence, as measured by the Adult Decision Making Competence (A-DMC) battery, are related to functional brain connectivity patterns derived from resting-state fMRI data in a sample of 304 healthy participants. We examined connectome-wide associations, identifying regions within frontal, parietal, temporal, and occipital cortex that demonstrated significant associations with decision making competence. We then assessed whether the functional interactions between brain regions sensitive to decision making competence and seven intrinsic connectivity networks (ICNs) were predictive of specific facets of decision making assessed by subtests of the A-DMC battery. Our findings suggest that individual differences in specific facets of decision making competence are mediated by ICNs that support executive, social, and perceptual processes, and motivate an integrative framework for understanding the neural basis of individual differences in decision making competence.

Multivariate Associations of Fluid Intelligence and NAA.

Understanding the neural and metabolic correlates of fluid intelligence not only aids scientists in characterizing cognitive processes involved in intelligence, but it also offers insight into intervention methods to improve fluid intelligence. Here we use magnetic resonance spectroscopic imaging (MRSI) to measure N-acetyl aspartate (NAA), a biochemical marker of neural energy production and efficiency. We use principal components analysis (PCA) to examine how the distribution of NAA in the frontal and parietal lobes relates to fluid intelligence. We find that a left lateralized frontal-parietal component predicts fluid intelligence, and it does so independently of brain size, another significant predictor of fluid intelligence. These results suggest that the left motor regions play a key role in the visualization and planning necessary for spatial cognition and reasoning, and we discuss these findings in the context of the Parieto-Frontal Integration Theory of intelligence.

Determinants of fluid intelligence in healthy aging: Omega-3 polyunsaturated fatty acid status and frontoparietal cortex structure.

INTRODUCTION: Accumulating evidence indicates that cognitive decline depends not only upon changes in brain health, but critically, also upon nutritional status. Decline in fluid intelligence, one of the most debilitating aspects of cognitive aging, has been linked to omega-3 polyunsaturated fatty acid (PUFA) status; however, it is not known whether this phenomenon results from specific omega-3 PUFAs acting on particular aspects of brain health. Therefore, this study aims to explore whether particular patterns of omega-3 PUFAs influence fluid intelligence by supporting specific neural structures. METHODS: We measured six plasma phospholipid omega-3 PUFAs, fluid intelligence, and regional gray matter volume in the frontal and parietal cortices in 100 cognitively intact older adults (65-75 years old). A four-step mediation analysis was implemented using principal component analysis and multivariate linear regressions, adjusted for age, gender, education, and body mass index. RESULTS: The mediation analysis revealed that one pattern of omega-3 PUFAs, consisting of alpha-linolenic acid, stearidonic acid, and eicosatrienoic acid, was linked to fluid intelligence, and that total gray matter volume of the left frontoparietal cortex (FPC) fully mediated the relationship between this omega-3 PUFA pattern and fluid intelligence. DISCUSSION: These data demonstrate that fluid intelligence may be optimally supported by specific omega-3 PUFAs through preservation of FPC gray matter structure in cognitively intact older adults. This report provides novel evidence for the benefits of particular omega-3 PUFA patterns on fluid intelligence and underlying gray matter structure.

A brief assessment tool for investigating facets of moral judgment from realistic vignettes.

Humans make moral judgments every day, and research demonstrates that these evaluations are based on a host of related event features (e.g., harm, legality). In order to acquire systematic data on how moral judgments are made, our assessments need to be expanded to include real-life, ecologically valid stimuli that take into account the numerous event features that are known to influence moral judgment. To facilitate this, Knutson et al. (in Social Cognitive and Affective Neuroscience, 5(4), 378-384, 2010) developed vignettes based on real-life episodic memories rated concurrently on key moral features; however, the method is time intensive (~1.4-3.4 h) and the stimuli and ratings require further validation and characterization. The present study addresses these limitations by: (i) validating three short subsets of these vignettes (39 per subset) that are time-efficient (10-25 min per subset) yet representative of the ratings and factor structure of the full set, (ii) norming ratings of moral features in a larger sample (total N = 661, each subset N = ~220 vs. Knutson et al. N = 30), (iii) examining the generalizability of the original factor structure by replicating it in a larger sample across vignette subsets, sex, and political ideology, and (iv) using latent profile analysis to empirically characterize vignette groupings based on event feature ratings profiles and vignette content. This study therefore provides researchers with a core battery of well-characterized and realistic vignettes, concurrently rated on key moral features that can be administered in a brief, time-efficient manner to advance research on the nature of moral judgment.

Nutritional status, brain network organization, and general intelligence.

The high energy demands of the brain underscore the importance of nutrition in maintaining brain health and further indicate that aspects of nutrition may optimize brain health, in turn enhancing cognitive performance. General intelligence represents a critical cognitive ability that has been well characterized by cognitive neuroscientists and psychologists alike, but the extent to which a driver of brain health, namely nutritional status, impacts the neural mechanisms that underlie general intelligence is not understood. This study therefore examined the relationship between the intrinsic connectivity networks supporting general intelligence and nutritional status, focusing on nutrients known to impact the metabolic processes that drive brain function. We measured general intelligence, favorable connective architecture of seven intrinsic connectivity networks, and seventeen plasma phospholipid monounsaturated and saturated fatty acids in a sample of 99 healthy, older adults. A mediation analysis was implemented to investigate the relationship between empirically derived patterns of fatty acids, general intelligence, and underlying intrinsic connectivity networks. The mediation analysis revealed that small world propensity within one intrinsic connectivity network supporting general intelligence, the dorsal attention network, was promoted by a pattern of monounsaturated fatty acids. These results suggest that the efficiency of functional organization within a core network underlying general intelligence is influenced by nutritional status. This report provides a novel connection between nutritional status and functional network efficiency, and further supports the promise and utility of functional connectivity metrics in studying the impact of nutrition on cognitive and brain health.

Aerobic fitness, hippocampal viscoelasticity, and relational memory performance.

The positive relationship between hippocampal structure, aerobic fitness, and memory performance is often observed among children and older adults; but evidence of this relationship among young adults, for whom the hippocampus is neither developing nor atrophying, is less consistent. Studies have typically relied on hippocampal volumetry (a gross proxy of tissue composition) to assess individual differences in hippocampal structure. While volume is not specific to microstructural tissue characteristics, microstructural differences in hippocampal integrity may exist even among healthy young adults when volumetric differences are not diagnostic of tissue health or cognitive function. Magnetic resonance elastography (MRE) is an emerging noninvasive imaging technique for measuring viscoelastic tissue properties and provides quantitative measures of tissue integrity. We have previously demonstrated that individual differences in hippocampal viscoelasticity are related to performance on a relational memory task; however, little is known about health correlates to this novel measure. In the current study, we investigated the relationship between hippocampal viscoelasticity and cardiovascular health, and their mutual effect on relational memory in a group of healthy young adults (N=51). We replicated our previous finding that hippocampal viscoelasticity correlates with relational memory performance. We extend this work by demonstrating that better aerobic fitness, as measured by VO2max, was associated with hippocampal viscoelasticity that mediated the benefits of fitness on memory function. Hippocampal volume, however, did not account for individual differences in memory. Therefore, these data suggest that hippocampal viscoelasticity may provide a more sensitive measure to microstructural tissue organization and its consequences to cognition among healthy young adults.