Whole-brain intrinsic functional connectivity predicts symptoms and functioning in early psychosis.

Theories of psychotic illness suggest that abnormal intrinsic functional connectivity may explain its characteristic positive and disorganization symptoms as well as lead to impaired general functioning. Here we used resting state functional magnetic resonance imaging (fMRI) to evaluate associations between these symptoms and the degree to which global connectivity is abnormal in early psychosis (EP). Eighty-six healthy controls (HCs) and 108 individuals with EP with resting state fMRI data were included in primary analyses. The EP group included 83 participants with schizophrenia-spectrum disorders and 25 with bipolar disorder type I with psychotic features. A global intrinsic connectivity "similarity index" for each EP individual was determined by calculating its correlation with the average HC connectivity matrix extracted using Schaefer atlases of multiple parcellations (100, 200, 300, and 400 region parcellations). As hypothesized, connectivity similarity with the average HC matrix was negatively associated with Brief Psychiatric Rating Scale total score, Scale for the Assessment of Positive Symptoms total score, and disorganization symptoms. Similarity was also positively associated with Global Assessment of Functioning score. Results were not driven by sex or diagnosis effects and were consistent across parcellation schemes. These results support the hypothesis that changes in whole-brain connectivity patterns are associated with psychosis symptoms and support the use of functional connectivity as a biomarker for these symptoms in EP.

Hierarchical Principal Components for Data-Driven Multiresolution fMRI Analyses.

Understanding the organization of neural processing is a fundamental goal of neuroscience. Recent work suggests that these systems are organized as a multiscale hierarchy, with increasingly specialized subsystems nested inside general processing systems. Current neuroimaging methods, such as independent component analysis (ICA), cannot fully capture this hierarchy since they are limited to a single spatial scale. In this manuscript, we introduce multiresolution hierarchical principal components analysis (hPCA) and compare it to ICA using simulated fMRI datasets. Furthermore, we describe a parametric statistical filtering method developed to focus analyses on biologically relevant features. Lastly, we apply hPCA to the Human Connectome Project (HCP) to demonstrate its ability to estimate a hierarchy from real fMRI data. hPCA accurately estimated spatial maps and time series from networks with diverse hierarchical structures. Simulated hierarchies varied in the degree of branching, such as two-way or three-way subdivisions, and the total number of levels, with varying equal or unequal subdivision sizes at each branch. In each case, as well as in the HCP, hPCA was able to reconstruct a known hierarchy of networks. Our results suggest that hPCA can facilitate more detailed and comprehensive analyses of the brain's network of networks and the multiscale regional specializations underlying neural processing and cognition.

Relationship between functional connectivity and weight-gain risk of antipsychotics in schizophrenia.

BACKGROUND: The mechanisms by which antipsychotic medications (APs) contribute to obesity in schizophrenia are not well understood. Because AP effects on functional brain connectivity may contribute to weight effects, the current study investigated how AP-associated weight-gain risk relates to functional connectivity in schizophrenia. METHODS: Fifty-five individuals with schizophrenia (final N = 54) were divided into groups based on previously reported AP weight-gain risk (no APs/low risk [N = 19]; moderate risk [N = 17]; high risk [N = 18]). Resting-state functional magnetic resonance imaging (fMRI) was completed after an overnight fast ("fasted") and post-meal ("fed"). Correlations between AP weight-gain risk and functional connectivity were assessed at the whole-brain level and in reward- and eating-related brain regions (anterior insula, caudate, nucleus accumbens). RESULTS: When fasted, greater AP weight-gain risk was associated with increased connectivity between thalamus and sensorimotor cortex (pFDR = 0.021). When fed, greater AP weight-gain risk was associated with increased connectivity between left caudate and left precentral/postcentral gyri (pFDR = 0.048) and between right caudate and multiple regions, including the left precentral/postcentral gyri (pFDR = 0.001), intracalcarine/precuneal/cuneal cortices (pFDR < 0.001), and fusiform gyrus (pFDR = 0.008). When fed, greater AP weight-gain risk was also associated with decreased connectivity between right anterior insula and ventromedial prefrontal cortex (pFDR = 0.002). CONCLUSIONS: APs with higher weight-gain risk were associated with greater connectivity between reward-related regions and sensorimotor regions when fasted, perhaps relating to motor anticipation for consumption. Higher weight-gain risk APs were also associated with increased connectivity between reward, salience, and visual regions when fed, potentially reflecting greater desire for consumption following satiety.

Functional magnetic resonance imaging of headache: Issues, best-practices, and new directions, a narrative review.

OBJECTIVE: To ensure readers are informed consumers of functional magnetic resonance imaging (fMRI) research in headache, to outline ongoing challenges in this area of research, and to describe potential considerations when asked to collaborate on fMRI research in headache, as well as to suggest future directions for improvement in the field. BACKGROUND: Functional MRI has played a key role in understanding headache pathophysiology, and mapping networks involved with headache-related brain activity have the potential to identify intervention targets. Some investigators have also begun to explore its use for diagnosis. METHODS/RESULTS: The manuscript is a narrative review of the current best practices in fMRI in headache research, including guidelines on transparency and reproducibility. It also contains an outline of the fundamentals of MRI theory, task-related study design, resting-state functional connectivity, relevant statistics and power analysis, image preprocessing, and other considerations essential to the field. CONCLUSION: Best practices to increase reproducibility include methods transparency, eliminating error, using a priori hypotheses and power calculations, using standardized instruments and diagnostic criteria, and developing large-scale, publicly available datasets.

Sex Differences in Effects of Mood, Eating-Related Behaviors, and BMI on Food Appeal and Desire to Eat: A Cross-Sectional Survey Study.

Although sex differences in food intake have been observed consistently, contributing factors are not well understood. Using a cross-sectional online survey (n = 306; 151 men, 155 women), this study aimed to assess how sex impacts relationships between food ratings (appeal/desire to eat for high-calorie (HC) and low-calorie (LC) food images) and eating-related attitudes/behaviors, body mass index (BMI), and mood. Across participants, increased state- and trait-based hunger, disinhibition, and cravings were associated with both increased HC appeal and desire (p < 0.001). Increased state-based hunger and cravings were associated with greater LC desire (p < 0.001). Greater satiety was associated with decreased desire for both HC and LC (p < 0.001), while greater anxiety was associated with increased desire for both HC and LC (p < 0.001). Significant associations between BMI and food ratings were not observed. Women reported greater dietary restraint, trait-based hunger, disinhibition, eating disorder-related behaviors, depression, and stress compared to men, in addition to greater appeal and familiarity with LC foods (all p < 0.05). Significant effects of sex on the associations between food ratings and eating-related attitudes/behaviors, BMI, and mood were not observed, however. Findings support the importance of considering mood and eating-related attitudes/behaviors in investigations of food cue responsivity.

Spike-Associated Networks Predict Postsurgical Outcomes in Children With Refractory Epilepsy.

PURPOSE: Up to half of the children undergoing epilepsy surgery will continue to have seizures (szs) despite a cortical resection or ablation. Functional connectivity has shown promise in better identifying the epileptogenic zone. We hypothesized that cortical areas showing high information outflow during interictal epileptiform discharges are part of the epileptogenic zone. METHODS: We identified 22 children with focal epilepsy who had undergone stereo electroencephalography, surgical resection or ablation, and had ≥1 year of postsurgical follow-up. The mean phase slope index, a directed measure of functional connectivity, was calculated for each electrode contact during interictal epileptiform discharges. The positive predictive value and negative predictive value for a sz-free outcome were calculated based on whether high information outflow brain regions were resected. RESULTS: Resection of high outflow (z-score ≥ 1) and very high outflow (z-score ≥ 2) electrode contacts was associated with higher sz freedom (high outflow: χ 2 statistic = 59.1; P < 0.001; very high outflow: χ 2 statistic = 31.3; P < 0.001). The positive predictive value and negative predictive value for sz freedom based on resection at the electrode level increased at higher z-score thresholds with a peak positive predictive value of 0.86 and a peak negative predictive value of 0.9. CONCLUSIONS: Better identification of the epileptogenic zone has the potential to improve epilepsy surgery outcomes. If the surgical plan can be modified to include these very high outflow areas, more children might achieve sz freedom. Conversely, if deficits from resecting these areas are unacceptable, ineffective surgeries could be avoided and alternative therapies offered.

Hippocampal, basal ganglia and olfactory connectivity contribute to cognitive impairments in Parkinson's disease.

Cognitive impairment is increasingly recognized as a characteristic feature of Parkinson's disease (PD), yet relatively little is known about its underlying neurobiology. Previous investigations suggest that dementia in PD is associated with subcortical atrophy, but similar studies in PD with mild cognitive impairment have been mixed. Variability in cognitive phenotypes and diversity of PD symptoms suggest that a common neuropathological origin results in a multitude of impacts within the brain. These direct and indirect impacts of disease pathology can be investigated using network analysis. Functional connectivity, for instance, may be more sensitive than atrophy to decline in specific cognitive domains in the PD population. Fifty-eight participants with PD underwent a neuropsychological test battery and scanning with structural and resting state functional MRI in a comprehensive whole-brain association analysis. To investigate atrophy as a potential marker of impairment, structural gray matter atrophy was associated with cognitive scores in each cognitive domain using voxel-based morphometry. To investigate connectivity, large-scale networks were correlated with voxel time series and associated with cognitive scores using distance covariance. Structural atrophy was not associated with any cognitive domain, with the exception of visuospatial measures in primary sensory and motor cortices. In contrast, functional connectivity was associated with attention, executive function, language, learning and memory, visuospatial, and global cognition in the bilateral hippocampus, left putamen, olfactory cortex, and bilateral anterior temporal poles. These preliminary results suggest that cognitive domain-specific networks in PD are distinct from each other and could provide a network signature for different cognitive phenotypes.

Appetitive and Metabolic Responses to an Exercise versus Dietary Intervention in Adults with Obesity.

Introduction/Purpose: Dietary restriction (DIET) and aerobic exercise (AEX) interventions may impact energy balance differently. Our aim was to describe the effects of weight loss interventions via DIET or AEX on measures of energy balance. Methods: Adults with overweight or obesity were randomized to 12 weeks of DIET or AEX with similar calorie deficit goals. A study day was conducted before and after the intervention to assess subjective and hormonal (ghrelin, peptide-YY, glucagon-like peptide-1) appetite responses to a control meal, ad libitum energy intake (EI) at a single meal, and over three days of free-living conditions and eating behavior traits. Resting metabolic rate (RMR) was measured with indirect calorimetry and adjusted for body composition measured by dual X-ray absorptiometry. Non-exercise activity was measured using accelerometers. Results: Forty-four individuals were included (age: 37 ± 9 years, body mass index: 30.6 ± 3.1 kg/m2). Both interventions resulted in weight and fat mass loss. The DIET group lost fat-free mass, although differences between groups were not significant (DIET: -1.2 ± 1.7 kg, p<0.001; AEX: 0.4 ± 1.5 kg, p=0.186; p=0.095 interaction). There were no differences in RMR after body composition adjustment. Both interventions were associated with an increase in dietary restraint (DIET: 4.9 ± 1.2, AEX: 2.8 ± 0.7; p<0.001 in both groups). Hunger decreased with DIET (-1.4 ± 0.5, p=0.003), and disinhibition decreased with AEX (-1.5 ± 0.5, p<0.001), although these changes were not different between groups (i.e., no group × time interaction). No other differences in appetite, EI, or non-exercise physical activity were observed within or between groups. Conclusions: AEX did not result in compensatory alterations in appetite, ad libitum EI, or physical activity, despite assumed increased energy expenditure. Modest evidence also suggested that disinhibition and hunger may be differentially impacted by weight loss modality.

An implicit priming intervention alters brain and behavioral responses to high-calorie foods: a randomized controlled study.

BACKGROUND: Conditioned food cues (e.g., smell, sight) can affect intake of foods associated with those cues, regardless of homeostatic need. As such, altering automatic associations with food cues could support weight loss or maintenance efforts by affecting the salience of those cues and the effort required to resist consumption. OBJECTIVES: This study investigated neuronal and behavioral effects of an implicit priming (IP) intervention, in which negatively valenced images were paired with high-calorie foods and positively valenced images with low-calorie foods. Priming images were presented immediately before food images, but below conscious perception (20 ms). We hypothesized that this evaluative conditioning approach could alter food cue responses by modifying affective associations. METHODS: The final sample included 41 adults with BMI ≥25 kg/m2 (n = 22, active IP; n = 19, control IP). In control IP, food images were primed with neutral, scrambled images. Participants completed a visual food cue task during fMRI, both before and after IP. To determine the replicability of prior behavioral findings, food image ratings were completed before and after IP as a secondary outcome. RESULTS: In a whole-brain analysis, reduced dorsolateral prefrontal cortex (dlPFC) response to high-calorie foods was observed after active compared with control IP (t = 4.93, P = 0.033). With a region of interest analysis, reduced response to high-calorie foods in active compared with control IP was also observed in the striatum (t = 2.40, P = 0.009) and insula (t = 2.38, P = 0.010). Active compared with control IP was associated with reduced high-calorie food ratings (F = 4.70, P = 0.038). CONCLUSIONS: Reduced insula and striatum response to high-calorie foods after active compared with control IP suggests effectiveness of IP in altering food cue salience. Reduced dlPFC response to high-calorie foods after active compared with control IP may reflect fewer attentional resources being directed to those images and reduced engagement of inhibitory processes.This trial was registered at clinicaltrials.gov as NCT02347527.

Stable Meta-Networks, Noise, and Artifacts in the Human Connectome: Low- to High-Dimensional Independent Components Analysis as a Hierarchy of Intrinsic Connectivity Networks.

Connectivity within the human connectome occurs between multiple neuronal systems-at small to very large spatial scales. Independent component analysis (ICA) is potentially a powerful tool to facilitate multi-scale analyses. However, ICA has yet to be fully evaluated at very low (10 or fewer) and ultra-high dimensionalities (200 or greater). The current investigation used data from the Human Connectome Project (HCP) to determine the following: (1) if larger networks, or meta-networks, are present at low dimensionality, (2) if nuisance sources increase with dimensionality, and (3) if ICA is prone to overfitting. Using bootstrap ICA, results suggested that, at very low dimensionality, ICA spatial maps consisted of Visual/Attention and Default/Control meta-networks. At fewer than 10 components, well-known networks such as the Somatomotor Network were absent from results. At high dimensionality, nuisance sources were present even in denoised high-quality data but were identifiable by correlation with tissue probability maps. Artifactual overfitting occurred to a minor degree at high dimensionalities. Basic summary statistics on spatial maps (maximum cluster size, maximum component weight, and average weight outside of maximum cluster) quickly and easily separated artifacts from gray matter sources. Lastly, by using weighted averages of bootstrap stability, even ultra-high dimensional ICA resulted in highly reproducible spatial maps. These results demonstrate how ICA can be applied in multi-scale analyses, reliably and accurately reproducing the hierarchy of meta-networks, large-scale networks, and subnetworks, thereby characterizing cortical connectivity across multiple spatial scales.

Altered between-network connectivity in individuals prone to obesity.

OBJECTIVE: Investigating intrinsic brain functional connectivity may help identify the neurobiology underlying cognitive patterns and biases contributing to obesity propensity. To address this, the current study used a novel whole-brain, data-driven approach to examine functional connectivity differences in large-scale network interactions between obesity-prone (OP) and obesity-resistant (OR) individuals. METHODS: OR (N = 24) and OP (N = 25) adults completed functional magnetic resonance imaging (fMRI) during rest. Large-scale brain networks were identified using independent component analysis (ICA). Voxel-specific between-network connectivity analysis assessed correlations between ICA component time series' and individual voxel time series, identifying regions strongly connected to many networks, i.e., "hubs". RESULTS: Significant group differences in between-network connectivity (OP vs. OR; FDR-corrected) were observed in bilateral basal ganglia (left: q = 0.009; right: q = 0.010) and right dorsolateral prefrontal cortex (dlPFC; q = 0.026), with OP>OR. Basal ganglia differences were largely driven by a more strongly negative correlation with a lateral sensorimotor network in OP, with dlPFC differences driven by a more strongly negative correlation with an inferior visual network in OP. CONCLUSIONS: Greater between-network connectivity was observed in the basal ganglia and dlPFC in OP, driven by stronger associations with lateral sensorimotor and inferior visual networks, respectively. This may reflect a disrupted balance between goal-directed and habitual control systems and between internal/external monitoring processes.

In Utero Exposure to Maternal Overweight or Obesity is Associated with Altered Offspring Brain Function in Middle Childhood.

OBJECTIVE: The impact of in utero exposure to maternal overweight and obesity on offspring metabolic health is well documented. Neurodevelopmental outcomes among these children are, however, less well studied. To address this gap, the current study investigated brain function among 4- to 6-year-old children exposed to maternal overweight or obesity during gestation compared with that of children born to mothers with healthy BMI in pregnancy. METHODS: Resting-state functional magnetic resonance imaging was used to study neuronal activity and connectivity during a passive viewing task (movie) among 101 typically developing children enrolled in the Healthy Start study, a longitudinal prebirth cohort in Colorado. RESULTS: Forty-nine children (48%) were exposed to maternal overweight or obesity in utero (mean age = 5 years, SD = 0.9). Children born to mothers with overweight or obesity demonstrated hyperactivity in the left posterior cingulate cortex and hypoactivity in the dorsal anterior cingulate and the supplementary motor area (P < 0.05 for all). Children born to mothers with overweight or obesity also showed ubiquitously weaker brain connectivity (P < 0.05 for all). CONCLUSIONS: These novel results suggest altered brain function among children exposed to maternal overweight and obesity in utero.

Spike-associated networks and intracranial electrographic findings.

Functional connectivity is providing new insights into the network nature of epilepsy with growing clinical applications. Our objective was to validate a novel magnetoencephalography-based method to non-invasively measure the epileptic network. We retrospectively identified pediatric and adult patients with refractory focal epilepsy who underwent pre-surgical magnetoencephalography with subsequent intracranial electrographic monitoring. Magnetoencephalography tracings were visually reviewed, and interictal epileptiform discharges ("spikes") were individually marked. We then evaluated differences in whole-brain connectivity during brief epochs preceding the spikes and during the spikes using the Network-Based Statistic to test differences at the network level. In six patients with statistically-significant network differences, we observed substantial overlap between the spike-associated networks and electrographically active areas identified during intracranial monitoring (the spike-associated network was 78% and 83% sensitive for intracranial electroencephalography-defined regions in the irritative and seizure onset zones, respectively). These findings support the neurobiological validity of the spike-associated network method. Assessment of spike-associated networks has the potential to improve surgical planning in epilepsy surgery patients by identifying components of the epileptic network prior to implantation.

Autism Spectrum Disorder Symptoms are Associated with Connectivity Between Large-Scale Neural Networks and Brain Regions Involved in Social Processing.

The neurobiology of autism spectrum disorder remains poorly understood. The present study addresses this knowledge gap by examining the relationship between functional brain connectivity and Autism Diagnostic Observation Schedule (ADOS) scores using publicly available data from the Autism Brain Imaging Data Exchange (ABIDE) database (N = 107). This relationship was tested across all brain voxels, without a priori assumptions, using a novel statistical approach. ADOS scores were primarily associated with decreased connectivity to right temporoparietal junction, right anterior insula, and left fusiform gyrus (p < 0.05, corrected). Seven large-scale brain networks influenced these associations. Findings largely encompassed brain regions involved in processing socially relevant information, highlighting the importance of these processes in autism spectrum disorder.

Effects of Exercise during Weight Loss Maintenance on Appetite Regulation in Women.

Exercise is accepted as a method to improve weight loss maintenance; however, the mechanisms by which this occurs have yet to be elucidated. In this pilot study, 13 women with obesity underwent a structured weight loss program (goal 8%-10% weight loss) and were then randomized to either a 12-wk diet (n = 7) or an aerobic exercise training (n = 6) intervention aimed at maintaining weight loss. At baseline, post-weight loss, and following the weight loss maintenance interventions, measurements of appetite (hunger and satiety) and appetite-regulating hormones (leptin, ghrelin, peptide tyrosine tyrosine, and glucagon-like peptide 1) were obtained after an overnight fast and for 3 h after a standardized test meal. Ad libitum energy intake was measured at a lunch meal. During the weight loss phase, participants lost 9.1% ± 1.1% of baseline body weight. Participants in both groups maintained weight loss during the 12-wk weight loss maintenance intervention. No differences in fasting leptin (P = 0.68) or in ghrelin (P = 0.30), peptide tyrosine tyrosine (P = 0.93), and glucagon-like peptide 1 (P = 0.98) area under the curve were detected between groups. Similarly, ratings of hunger (P = 0.99) and satiety (P = 0.65) area under the curve after the standardized test meal also did not differ between the groups nor did ad libitum energy intake at lunch. In summary, the 12-wk diet and exercise interventions were equally effective at maintaining weight loss in women, and no differences in measures of appetite regulation and food intake were found.

Hemodynamic responses are abnormal in isolated cervical dystonia.

Neuroimaging studies using functional magnetic resonance imaging (fMRI), which measures brain activity by detecting the changes in blood oxygenation levels, are advancing our understanding of the pathophysiology of dystonia. Neurobiological disturbances in dystonia, however, may affect neurovascular coupling and impact the interpretability of fMRI studies. We evaluated here whether the hemodynamic response patterns during a behaviorally matched motor task are altered in isolated cervical dystonia (CD). Twenty-five CD patients and 25 healthy controls (HCs) underwent fMRI scanning during a paced finger tapping task (nondystonic task in patients). Imaging data were analyzed using a constrained principal component analysis-a statistical method that combines regression analysis and principal component analysis and enables the extraction of task-related functional networks and determination of the spatial and temporal hemodynamic response patterns associated with the task performance. Data from three patients and two controls were removed due to excessive movement. No significant differences in demographics or motor performance were observed. Three task-associated functional brain networks were identified. During task performance, reduced hemodynamic responses were seen in a sensorimotor network and in a network that included key nodes of the default mode, executive control and visual networks. During rest, reductions in hemodynamic responses were seen in the cognitive/visual network. Lower hemodynamic responses within the primary sensorimotor network in patients were correlated with the increased dystonia severity. Pathophysiological disturbances in isolated CD, such as alterations in inhibitory signaling and dopaminergic neurotransmission, may impact neurovascular coupling. Not accounting for hemodynamic response differences in fMRI studies of dystonia could lead to inaccurate results and interpretations.

The epileptic network and cognition: What functional connectivity is teaching us about the childhood epilepsies.

Our objective was to summarize and evaluate the rapidly expanding body of literature studying functional connectivity in childhood epilepsy. In the self-limited childhood epilepsies, awareness of cognitive comorbidities has been steadily increasing, and recent advances in our understanding of the network effects of these disorders promise insights into the underlying neurobiology. We reviewed publications addressing functional connectivity in children with epilepsy with an emphasis on studies of children with self-limited childhood epilepsies. The majority of studies have been published in the past 10 years and predominantly examine childhood epilepsy with centrotemporal spikes and childhood absence epilepsy. Cognitive network alterations are commonly observed across the childhood epilepsies. Some of these effects appear to be nonspecific to epilepsy syndrome or even to category of neurological disorder. Other patterns, such as changes in the connectivity of cortical language areas in childhood epilepsy with centrotemporal spikes, provide clues to the underlying cognitive deficits seen in affected children. The literature to date is dominated by general observations of connectivity patterns without a priori hypotheses. These data-driven studies build an important foundation for hypothesis generation and are already providing useful insights into the neuropathology of the childhood epilepsies. Future work should emphasize hypothesis-driven approaches and rigorous clinical correlations to better understand how the knowledge of network alterations can be applied to guidance and treatment for the children in our clinics.

Childhood Metabolic Biomarkers Are Associated with Performance on Cognitive Tasks in Young Children.

OBJECTIVE: To evaluate the hypothesis that metabolic measures (fasting glucose, insulin, and Homeostatic Model of Assessment for Insulin Resistance [HOMA-IR] levels) are inversely associated with performance on cognitive tasks using data from young (4- to 6-year-old), typically developing, healthy children. STUDY DESIGN: Data were obtained from children participating in the Healthy Start study, a pre-birth cohort in Colorado. HOMA-IR, glucose, and insulin values were centered and scaled using the study sample means and SD. Thus, they are reported in number of SD units from the mean. Fully corrected T scores for inhibitory control (Flanker task), cognitive flexibility (Dimensional Change Card Sort test), and receptive language (Picture Vocabulary test) were obtained via the National Institutes of Health Toolbox cognition battery. RESULTS: Children included in this analysis (n = 137) were 4.6 years old, on average. Per 1-SD unit, fasting glucose (B = -2.0, 95% CI -3.5, -0.5), insulin (B = -1.7, 95% CI -3.0, -0.4), and HOMA-IR values (B = -1.8, 95% CI -3.1, -0.5) were each significantly and inversely associated with inhibitory control (P < .05 for all, respectively). Fasting glucose levels were also inversely associated with cognitive flexibility (B = -2.0, 95% CI -3.7, -0.2, P = .03). CONCLUSIONS: Our data suggest that metabolic health may impact fluid cognitive function in healthy, young children.