Brain effective connectivity and functional connectivity as markers of lifespan vascular exposures in middle-aged adults: The Bogalusa Heart Study

Introduction

Effective connectivity (EC), the causal influence that functional activity in a source brain location exerts over functional activity in a target brain location, has the potential to provide different information about brain network dynamics than functional connectivity (FC), which quantifies activity synchrony between locations. However, head-to-head comparisons between EC and FC from either task-based or resting-state functional MRI (fMRI) data are rare, especially in terms of how they associate with salient aspects of brain health.

Methods

In this study, 100 cognitively-healthy participants in the Bogalusa Heart Study aged 54.2 ± 4.3years completed Stroop task-based fMRI, resting-state fMRI. EC and FC among 24 regions of interest (ROIs) previously identified as involved in Stroop task execution (EC-task and FC-task) and among 33 default mode network ROIs (EC-rest and FC-rest) were calculated from task-based and resting-state fMRI using deep stacking networks and Pearson correlation. The EC and FC measures were thresholded to generate directed and undirected graphs, from which standard graph metrics were calculated. Linear regression models related graph metrics to demographic, cardiometabolic risk factors, and cognitive function measures.

Results

Women and whites (compared to men and African Americans) had better EC-task metrics, and better EC-task metrics associated with lower blood pressure, white matter hyperintensity volume, and higher vocabulary score (maximum value of p = 0.043). Women had better FC-task metrics, and better FC-task metrics associated with APOE-ε4 3–3 genotype and better hemoglobin-A1c, white matter hyperintensity volume and digit span backwards score (maximum value of p = 0.047). Better EC rest metrics associated with lower age, non-drinker status, and better BMI, white matter hyperintensity volume, logical memory II total score, and word reading score (maximum value of p = 0.044). Women and non-drinkers had better FC-rest metrics (value of p = 0.004).

Discussion

In a diverse, cognitively healthy, middle-aged community sample, EC and FC based graph metrics from task-based fMRI data, and EC based graph metrics from resting-state fMRI data, were associated with recognized indicators of brain health in differing ways. Future studies of brain health should consider taking both task-based and resting-state fMRI scans and measuring both EC and FC analyses to get a more complete picture of functional networks relevant to brain health.

Validation of the Activity Preference Assessment: a tool for quantifying children's implicit preferences for sedentary and physical activities

BACKGROUND

High levels of sedentary behavior and low physical activity are associated with poor health, and the cognitive determinants of these behaviors in children and adolescents are not well understood. To address this gap, we developed a novel, non-verbal, computer-based assessment to quantify the degree to which youth prefer to be sedentary relative to physically active in their leisure time.

METHODS

The Activity Preference Assessment (APA) uses a forced-choice paradigm to understand implicit decision-making processes when presented with common sedentary and physical activities. The APA bias score ranges from - 100 to + 100, with positive scores indicating a relative preference for sedentary activities, and negative scores representing a preference for physical activities. In 60 children ages 8-17 years, we assessed the validity of this behavioral task against a free-choice play observation, accelerometry-measured activity, anthropometrics and body composition, and cardiorespiratory fitness. We explored neighborhood, family, and individual-level factors that may influence implicit activity preferences. Test-retest reliability was assessed over one week.

RESULTS

The majority of children (67%) preferred sedentary relative to physical activities. APA bias scores were positively associated with sedentary time during free-choice play. In girls, bias scores were negatively associated with average daily MVPA. APA bias scores were positively associated with body fat and negatively associated with cardiorespiratory fitness. These findings were independent of age, sex, and race/ethnicity. Neighborhood access to physical activity spaces, the number of people in the home, perceived physical self-competence (e.g., coordination, strength), and self-reported depressive symptoms were associated with activity preferences. The intra-class correlation for test-retest reliability was r = 0.59.

CONCLUSIONS

The APA shows promise as a novel tool for quantifying children's relative preference for sedentary versus physical activities. Implicit bias scores from the APA are clinically meaningful, as shown by significant associations with adiposity and cardiorespiratory fitness. Future longitudinal studies should examine the directionality of the association between preferences and health markers, and the degree to which implicit activity preferences are modifiable. Importantly, the task only takes an average of 10 min to complete, highlighting a potential role as an efficient screening tool for the propensity to be sedentary versus physically active.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03624582 .

The Effects of the Form of Sugar (Solid vs. Beverage) on Body Weight and Neuronal Activity: A 28 Day Randomized Pilot Study (P08-001-19)

Objectives

To test if sugar sweetened beverages (SSBs) and sugar sweetened solids (SSSs) have differential effects on body weight and food reward processing.

Methods

In a single blind RCT, twenty participants with a BMI between 20–40 kg/m2 were randomized to consume a 20 fl oz soda/d (SSB, 248 kcal) vs. the equivalent energy and nutrients in solid form (SSS; similar to a thick jello and/or gummy candy). At baseline and day 28, fasting body weight and fed state brain activation responses to low fat high sugar foods (LF < 30%, HS > 30%) and non-food objects were assessed. The fMRI scan began 30 min after initiation of consumption of the 248 kcal dose of their randomized treatment. Summary measures of differences in fMRI BOLD signals between LFHS vs non-food images were calculated in a set of a priori defined brain regions implicated in energy homeostasis, taste, reward, and motivation to eat.

Results

Ten participants in the SSB (6F 4 M; 80% White; 39 ±4 y, Mean ± SEM) and ten in the SSS (3F 7 M; 60% White; 36 ± 5) completed the study. Baseline BMI was 28.2 ± 1.7 kg/m2 and 26.3 ± 1.4 in the SSB and SSS groups, respectively. No difference in change in body weight for SSB vs. SSS (0.56 ± 0.43 kg; P  =  0.22) was seen. Changes in fMRI activation in homeostatic and taste regions were not different. Among reward and motivation related regions, fMRI activation within the caudate nucleus, cingulate gyrus, and medial orbitofrontal cortex were not different at baseline, but increased in SSS and decreased in SSB group (mean group differences in activation change: –0.30 ± 0.15, –0.36 ± 0.11, and –0.60 ± 0.25, P ˂ 0.05; respectively). fMRI activation in the insula was greater at baseline in SSS compared to SSB but the two groups converged to similar values at day 28 (mean group differences in activation change: 0.19 ± 0.08, P ˂ 0.05).

Conclusions

Consumption of SSB vs. SSS products produced distinct changes to brain activity within specific brain regions that control eating behavior despite no change in body weight between groups. Understanding the neural and physiological consequences of consuming added sugar in different forms will better inform current efforts to reduce its consumption and help regulate policy. This pilot study provides promising data for a longer duration, well-powered follow-up study.

Funding Sources

NIH U54GM104940, P30DK072476, Pennington Biomedical Research Foundation.

Perceptual Characterization of the Macronutrient Picture System (MaPS) for Food Image fMRI

Food image fMRI paradigms are used widely for investigating the neural basis of ingestive behavior. However, these paradigms have not been validated in terms of ingestive behavior constructs, engagement of food-relevant neural systems, or test-retest reliability, making the generalizability of study findings unclear. Therefore, we validated the Macronutrient Picture System (MaPS) (McClernon et al., 2013), which includes food images from the six categories represented in the Geiselman Food Preference Questionnaire (FPQ) (Geiselman et al., 1998). Twenty-five healthy young adults (n = 21 female, mean age = 20.6 ± 1.1 years, mean BMI = 22.1 ± 1.9 kg/m²) rated the MaPS images in terms of visual interest, appetitive quality, nutrition, emotional valence, liking, and frequency of consumption, and completed the FPQ. In a second study, 12 individuals (n=8 female, mean age = 25.0 ± 6.5 years, mean BMI = 28.2 ± 8.7 kg/m²) viewed MaPS and control images (vegetables and non-food) during two separate 3T BOLD fMRI scans after fasting overnight. Intuitively, high fat/high sugar (HF/HS) and high fat/high complex carbohydrate (HF/HCCHO) images achieved higher liking and appetitive ratings, and lower nutrition ratings, than low fat/low complex carbohydrate/high protein (LF/LCHO/HP) images on average. Within each food category, FPQ scores correlated strongly with MaPS image liking ratings (p < 0.001). Brain activation differences between viewing images of HF/HS and vegetables, and between HF/HCCHO and vegetables, were seen in several reward-related brain regions (e.g., putamen, insula, and medial frontal gyrus). Intra-individual, inter-scan agreement in a summary measure of brain activation differences in seven reward network regions of interest was high (ICC = 0.61), and was even higher when two distinct sets of food images with matching visual ratings were shown in the two scans (ICC = 0.74). These results suggest that the MaPS provides valid representation of food categories and reliably activates food-reward-relevant neural systems.