Role of Brain Structure in Predicting Adherence to a Physical Activity Regimen

The bidirectional relationship between brain structure and physical activity: A longitudinal analysis in the UK Biobank

Physical activity is a protective factor against brain atrophy, while loss of brain volume could also be a determinant of physical activity. Therefore, we aimed to explore the bidirectional association of physical activity with brain structures in middle-aged and older adults from the UK Biobank. Overall, 3027 participants (62.45 ± 7.27 years old, 51.3% females) had data at two time points. Hippocampal volume was associated with total (β=0.048, pFDR=0.016) and household (β=0.075, pFDR<0.001) physical activity. Global fractional anisotropy (β=0.042, pFDR=0.028) was also associated with household physical activity. In the opposite direction, walking was negatively associated with white matter volume (β=-0.026, pFDR=0.008). All these associations were confirmed by the linear mixed models. Interestingly, sports at baseline were linked to hippocampal and frontal cortex volumes at follow-up but these associations disappeared after adjusting for multiple comparisons (pall>0.104). In conclusion, we found more consistent evidence that a healthier brain structure predicted higher physical activity levels than for the inverse, more established relationship.

Dietary Adherence Is Associated with Perceived Stress, Anhedonia, and Food Insecurity Independent of Adiposity

We examined whether perceived stress, anhedonia, and food insecurity were associated with dietary adherence during a 6-week intervention. Sixty participants (23 m; 53 ± 14 y) completed psychosocial measures and were provided with full meals. Individuals with obesity were randomized to a weight-maintaining energy needs (WMENs) (n = 18; BMI 33 ± 4) or a 35% calorie-reduced diet (n = 19; BMI 38 ± 9); normal-weight individuals (n = 23; BMI 23 ± 2) were assigned to a WMENs diet. Adherence scores were determined via weekly assessments and daily ecological momentary assessments (EMAs) of real-time behavior in a natural environment. Perceived stress and anhedonia were associated with % body fat (all r-values > 0.25, all p-values < 0.05), but food insecurity and adherence were not. Higher perceived stress (r = -0.31, p = 0.02), anhedonia (r = -0.34, p = 0.01), and food insecurity (r = -0.27, p = 0.04) were associated with lower adherence scores, even after adjusting for age, sex, and % body fat. In all adjusted models, % body fat was not associated with adherence. Higher measures of stress, anhedonia, and food insecurity predicted lower adherence independently of body fat, indicating that psychosocial factors are important targets for successful adherence to dietary interventions, regardless of body size.

Temporal Interactions between Maintenance of Cerebral Cortex Thickness and Physical Activity from an Individual Person Micro-Longitudinal Perspective and Implications for Precision Medicine

Maintenance of brain structure is essential for neurocognitive health. Precision medicine has interests in understanding how maintenance of an individual person's brain, including cerebral cortical structure, interacts with lifestyle factors like physical activity. Cortical structure, including cortical thickness, has recognized relationships with physical activity, but concepts of these relationships come from group, not individual, focused findings. Whether or how group-focused concepts apply to an individual person is fundamental to precision medicine interests but remains unclear. This issue was studied in a healthy man using concurrent micro-longitudinal tracking of magnetic resonance imaging-defined cortical thickness and accelerometer-defined steps/day over six months. These data permitted detailed examination of temporal relationships between thickness maintenance and physical activity at an individual level. Regression analyses revealed graded significant and trend-level temporal interactions between preceding activity vs. subsequent thickness maintenance and between preceding thickness maintenance vs. subsequent activity. Interactions were bidirectional, delayed/prolonged over days/weeks, positive, bilateral, directionally asymmetric, and limited in strength. These novel individual-focused findings in some ways are predicted, but in other ways remain unaddressed or undetected, by group-focused work. We suggest that individual-focused concepts of temporal interactions between maintenance of cortical structure and activity can provide needed new insight for personalized tailoring of physical activity, cortical, and neurocognitive health.

Cross-sectional and longitudinal neural predictors of physical activity and sedentary behaviour from a 6-month randomized controlled trial

A sedentary lifestyle offers immediate gratification, but at the expense of long-term health. It is thus critical to understand how the brain evaluates immediate rewards and long-term health effects in the context of deciding whether to engage in moderate-to-vigorous physical activity (MVPA) or sedentary behaviour (SB). In this secondary analysis of a 6-month randomized controlled trial to increase MVPA and reduce SB among community-dwelling adults, we explored how neural activity during an executive control task was associated with MVPA and SB levels. At baseline, a subset of participants (n = 26/61) underwent task-based functional magnetic resonance imaging (fMRI) to examine neural activity underlying executive control using the Now/Later task. MVPA and SB were measured objectively using the Sensewear Mini at baseline, and 2, 4, and 6 months follow-up. We then examined the associations of baseline neural activation underlying executive control with: (1) baseline MVPA or SB; and (2) changes in MVPA and SB over 6 months. Our results determined that there is a complex neurocognitive system associated with MVPA levels, while SB appears to lack any neurocognitive control. In other words, MVPA appears to require neurocognitive effort, while SB may be the default behavioural pattern in adults.

Morphology of the prefrontal cortex predicts body composition in early adolescence: cognitive mediators and environmental moderators in the ABCD Study

Morphological features of the lateral prefrontal cortex (PFC) in late childhood and early adolescence may provide important clues as to the developmental etiology of clinical conditions such as obesity. Body composition measurements and structural brain imaging were performed on 11 226 youth at baseline (age 9 or 10 years) and follow-up (age 11 or 12 years). Baseline morphological features of the lateral PFC were examined as predictors of body composition. Findings revealed reliable associations between middle frontal gyrus volume, thickness and surface area and multiple indices of body composition. These findings were consistent across both time points and remained significant after covariate adjustment. Cortical thicknesses of the inferior frontal gyrus and lateral orbitofrontal cortex were also reliable predictors. Morphology effects on body composition were mediated by performance on a non-verbal reasoning task. Modest but reliable moderation effects were observed with respect to environmental self-regulatory demand after controlling for sex, race/ethnicity, income and methodological variables. Overall findings suggest that PFC morphology is a reliable predictor of body composition in early adolescence, as mediated through select cognitive functions and partially moderated by environmental characteristics.

Strategies to Promote Cognitive Health in Aging: Recent Evidence and Innovations

PURPOSE OF REVIEW

We review recent work on applications of non-pharmacologic strategies to promote cognitive health in older adulthood and discuss potential network mechanisms, limitations, and considerations for improving intervention uptake and efficacy.

RECENT FINDINGS

In healthy older adults and patients with mild cognitive impairment, cognitive training produces global and domain-specific cognitive gains, though effect sizes tend to be modest and transfer is variable. Non-invasive brain stimulation has shown moderate success in enhancing cognitive function, though the optimum approach, parameters, and cortical targets require further investigation. Physical activity improves cognitive functions in late life, with emerging trials highlighting key intervention components that may maximize treatment outcomes. Multimodal interventions may be superior to single-component interventions in conferring cognitive gains, although interpretation is limited by modest sample sizes and variability in training components and parameters. Across modalities, individual differences in patient characteristics predict therapeutic response. These interventions may advance cognitive health by modulating functional networks that support core cognitive abilities including the default mode, executive control, and salience networks. Effectiveness of cognitive enhancement strategies may be increased with clinician-led coaching, booster sessions, gamification, integration of multiple intervention modalities, and concrete applications to everyday functioning. Future trials involving rigorous comparisons of training components, parameters, and delivery formats will be essential in establishing the precise approaches needed to maximize cognitive outcomes. Novel studies using patient-level clinical and neuroimaging features to predict individual differences in training gains may inform the development of personalized intervention prescriptions to optimize cognitive health in late life.

Brain Structure and Function Predict Adherence to an Exercise Intervention in Older Adults

INTRODUCTION

Individual differences in brain structure and function in older adults are potential proxies of brain reserve or maintenance and may provide mechanistic predictions of adherence to exercise. We hypothesized that multimodal neuroimaging features would predict adherence to a 6-month randomized controlled trial of exercise in 131 older adults (age, 65.79 ± 4.65 yr, 63% female), alone and in combination with psychosocial, cognitive, and health measures.

METHODS

Regularized elastic net regression within a nested cross-validation framework was applied to predict adherence to the intervention in three separate models (brain structure and function only; psychosocial, health, and demographic data only; and a multimodal model).

RESULTS

Higher cortical thickness in somatosensory and inferior frontal regions and less surface area in primary visual and inferior frontal regions predicted adherence. Higher nodal functional connectivity (degree count) in default, frontoparietal, and attentional networks and less nodal strength in primary visual and temporoparietal networks predicted exercise adherence ( r = 0.24, P = 0.004). Survey and clinical measures of gait and walking self-efficacy, biological sex, and perceived stress also predicted adherence ( r = 0.17, P = 0.056); however, this prediction was not significant when tested against a null test statistic. A combined multimodal model achieved the highest predictive strength ( r = 0.28, P = 0.001).

CONCLUSIONS

Our results suggest that there is a substantial utility of using brain-based measures in future research into precision and individualized exercise interventions older adults.

Computational approaches to predicting treatment response to obesity using neuroimaging

Obesity is a worldwide disease associated with multiple severe adverse consequences and comorbid conditions. While an increased body weight is the defining feature in obesity, etiologies, clinical phenotypes and treatment responses vary between patients. These variations can be observed within individual treatment options which comprise lifestyle interventions, pharmacological treatment, and bariatric surgery. Bariatric surgery can be regarded as the most effective treatment method. However, long-term weight regain is comparably frequent even for this treatment and its application is not without risk. A prognostic tool that would help predict the effectivity of the individual treatment methods in the long term would be essential in a personalized medicine approach. In line with this objective, an increasing number of studies have combined neuroimaging and computational modeling to predict treatment outcome in obesity. In our review, we begin by outlining the central nervous mechanisms measured with neuroimaging in these studies. The mechanisms are primarily related to reward-processing and include "incentive salience" and psychobehavioral control. We then present the diverse neuroimaging methods and computational prediction techniques applied. The studies included in this review provide consistent support for the importance of incentive salience and psychobehavioral control for treatment outcome in obesity. Nevertheless, further studies comprising larger sample sizes and rigorous validation processes are necessary to answer the question of whether or not the approach is sufficiently accurate for clinical real-world application.

Associations of cardiorespiratory fitness and exercise with brain white matter in healthy adults: A systematic review and meta-analysis

Magnetic resonance imaging (MRI) studies have revealed positive associations between brain structure and physical activity, cardiorespiratory fitness, and exercise (referred to here as PACE). While a considerable body of research has investigated the effects of PACE on grey matter, much less is known about effects on white matter (WM). Hence, we conducted a systematic review of peer-reviewed literature published prior to 5^th July 2021 using online databases (PubMed and Scopus) and PRISMA guidelines to synthesise what is currently known about the relationship between PACE and WM in healthy adults. A total of 60 studies met inclusion criteria and were included in the review. Heterogeneity across studies was calculated using Qochran's q test, and publication bias was assessed for each meta-analysis using Begg and Mazumdar rank correlation test. A meta-regression was also conducted to explore factors contributing to any observed heterogeneity. Overall, we observed evidence of positive associations between PACE and global WM volume (effect size (Hedges's g) = 0.137, p < 0.001), global WM anomalies (effect size = 0.182, p < 0.001), and local microstructure integrity (i.e., corpus callosum: effect size = 0.345, p < 0.001, and anterior limb of internal capsule: effect size = 0.198, p < 0.001). These findings suggest that higher levels of PACE are associated with improved global WM volume and local integrity. We appraise the quality of evidence, and discuss the implications of these findings for the preservation of WM across the lifespan. We conclude by providing recommendations for future research in order to advance our understanding of the specific PACE parameters and neurobiological mechanisms underlying these effects.

Daily Physical Activity Patterns as a Window on Cognitive Diagnosis in the Baltimore Longitudinal Study of Aging (BLSA)

BACKGROUND

Gradual disengagement from daily physical activity (PA) could signal present or emerging mild cognitive impairment (MCI) or Alzheimer's disease (AD).

OBJECTIVE

This study examined whether accelerometry-derived patterns of everyday movement differ by cognitive diagnosis in participants of the Baltimore Longitudinal Study of Aging (BLSA).

METHODS

Activity patterns, overall and by time-of-day, were cross-sectionally compared between participants with adjudicated normal cognition (n = 549) and MCI/AD diagnoses (n = 36; 5 participants [14%] living with AD) using covariate-adjusted regression models.

RESULTS

Compared to those with normal cognition, those with MCI/AD had 2.1% higher activity fragmentation (SE = 1.0%, p = 0.036) but similar mean total activity counts/day (p = 0.075) and minutes/day spent active (p = 0.174). Time-of-day analyses show MCI/AD participants had lower activity counts and minutes spent active during waking hours (6:00 am-5:59 pm; p < 0.01 for all). Also, they had lower activity fragmentation from 12:00-5:59 am (p < 0.001), but higher fragmentation from 12:00-5:59 pm (p = 0.026).

CONCLUSION

Differences in the timing and patterns of physical activity throughout the day linked to MCI/AD diagnoses warrant further investigation into potential clinical utility.

Evidence for exercise-related plasticity in functional and structural neural network connectivity

The number of studies investigating exercise and cardiorespiratory fitness (CRF)-related changes in the functional and structural organization of brain networks continues to rise. Functional and structural connectivity are critical biomarkers for brain health and many exercise-related benefits on the brain are better represented by network dynamics. Here, we reviewed the neuroimaging literature to better understand how exercise or CRF may facilitate and maintain the efficiency and integrity of functional and structural aspects of brain networks in both younger and older adults. Converging evidence suggests that increased exercise performance and CRF modulate functional connectivity of the brain in a way that corresponds to behavioral changes such as cognitive and motor performance improvements. Similarly, greater physical activity levels and CRF are associated with better cognitive and motor function, which may be brought about by enhanced structural network integrity. This review will provide a comprehensive understanding of trends in exercise-network studies as well as future directions based on the gaps in knowledge that are currently present in the literature.

The effects of aerobic exercise on corpus callosum integrity: systematic review

Objective: To evaluate the influence of exercise on the body and genu of the corpus callosum (CC), which is a critical brain structure involved in facilitating interhemispheric communication. Methods: Studies were identified using electronic databases, including PubMed, PsychInfo, Sports Discus and Google Scholar. The search terms, including their combinations, included exercise, physical activity, cardiorespiratory fitness, interhemispheric, and corpus callosum. To be eligible for inclusion in this review, studies had to be published in English; employ a cross-sectional, prospective or experimental design; include a measure of exercise as the independent variable; and the outcome variable had to include an integrity, volumetric or functional measure of the CC. Extraction parameters include study design, study population, exercise protocol, CC assessment, main findings regarding the relationship between exercise and the CC, and the evaluated or speculated mechanisms of this relationship. Results: 20 articles met the study inclusion criteria. Among these, 5 were conducted in animals and 15 were conducted in humans. Among the 5 animal studies, all provided suggestive evidence associating aerobic exercise with increased white matter integrity. Among the 15 human studies, 6 studies employed tract-based special statistics (TBSS), 4 utilized regions of interest (ROI) approach and 5 executed whole brain voxel wise analysis. Changes in the body was detected by 5 out of 6 TBSS studies and the genu by 3. Out of 4 ROI studies, three detected changes in the genu, but only one did in the body (out of 3 studies). One whole brain voxelwise study detected changes in the CC body of old adults and two found changes in the genu. Conclusion: This review provides evidence to suggest that aerobic exercise, and in turn, enhanced cardiorespiratory fitness, are associated with structural and functional outcomes increasing CC integrity.

Applying machine learning to predict future adherence to physical activity programs

BACKGROUND

Identifying individuals who are unlikely to adhere to a physical exercise regime has potential to improve physical activity interventions. The aim of this paper is to develop and test adherence prediction models using objectively measured physical activity data in the Mobile Phone-Based Physical Activity Education program (mPED) trial. To the best of our knowledge, this is the first to apply Machine Learning methods to predict exercise relapse using accelerometer-recorded physical activity data.

METHODS

We use logistic regression and support vector machine methods to design two versions of a Discontinuation Prediction Score (DiPS), which uses objectively measured past data (e.g., steps and goal achievement) to provide a numerical quantity indicating the likelihood of exercise relapse in the upcoming week. The respective prediction accuracy of these two versions of DiPS are compared, and then numerical simulation is performed to explore the potential of using DiPS to selectively allocate financial incentives to participants to encourage them to increase physical activity.

RESULTS

we had access to a physical activity trial data that were continuously collected every 60 sec every day for 9 months in 210 participants. By using the first 15 weeks of data as training and test on weeks 16-30, we show that both versions of DiPS have a test AUC of 0.9 with high sensitivity and specificity in predicting the probability of exercise adherence. Simulation results assuming different intervention regimes suggest the potential benefit of using DiPS as a score to allocate resources in physical activity intervention programs in reducing costs over other allocation schemes.

CONCLUSIONS

DiPS is capable of making accurate and robust predictions for future weeks. The most predictive features are steps and physical activity intensity. Furthermore, the use of DiPS scores can be a promising approach to determine when or if to provide just-in-time messages and step goal adjustments to improve compliance. Further studies on the use of DiPS in the design of physical activity promotion programs are warranted.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01280812 Registered on January 21, 2011.

Neuroimaging, neuromodulation, and population health: the neuroscience of chronic disease prevention

Preventable chronic diseases are the leading cause of death in the majority of countries throughout the world, and this trend will continue for the foreseeable future. The potential to offset the social, economic, and personal burdens associated with such conditions depends on our ability to influence people's thought processes, decisions, and behaviors, all of which can be understood with reference to the brain itself. Within the health neuroscience framework, the brain can be viewed as a predictor, mediator, moderator, or outcome in relation to health-related phenomena. This review explores examples of each of these, with specific reference to the primary prevention (i.e., prevention of initial onset) of chronic diseases. Within the topic of primary prevention, we touch on several cross-cutting themes (persuasive communications, delay discounting of rewards, and self-control), and place a special focus on obesity as a disorder influenced by both eating behavior and exercise habits.

Dopamine-Related Genotypes and Physical Activity Change During an Intervention: The Lifestyle Interventions and Independence for Elders Study

OBJECTIVES

To determine whether intervention-induced physical activity (PA) changes in sedentary older adults differed according to dopamine-related genotype.

DESIGN

Randomized clinical trial (Lifestyle Interventions and Independence for Elders Trial (2010-13)).

SETTING

Multicenter study, 8 U.S.

LOCATIONS

PARTICIPANTS

Volunteer sample of sedentary adults aged 70 to 89 at risk of disability (N=1635).

INTERVENTIONS

Structured PA versus health education (HE) for an average of 2.6 years.

MEASUREMENTS

Single-nucleotide polymorphisms of dopamine-related genes (dopamine receptor (DR) D1, DRD2, DRD3, and catechol-O-methyltransferase (COMT)) were assessed. Average moderate to vigorous PA (MVPA) was calculated using accelerometry (min/d) at baseline and 6, 12, and 24 months. Between-arm MVPA differences according to genotype and genotype with square root-transformed MVPA separately according to arm were tested, stratified according to race, and adjusted for multiple comparisons.

RESULTS

White participants in the PA arm (n=513) had higher average square root transformed MVPA (4.91±1.91)than those in the HE arm (n=538) (4.51±1.82) (p=.001). Between-arm differences were greater for DRD2 Met/Met (high dopamine; HE: 4.76±1.80, PA: 5.53±1.60, p=.03) than Val/Val (low dopamine; HE: 4.58±1.92, PA: 4.81±1.83, p=.16); results were similar for COMT. In the PA arm, DRD2 Met/Met was associated with higher average MVPA (5.39±2.00) than Met/Val (4.46±2.51) (p=.01) and Val/Val (4.65±2.71) (p=.01). There were no associations for other genes. Associations were not significant in blacks but followed similar trends.

CONCLUSION

Higher dopamine signaling may support changes in PA during an intervention. The role of dopamine-related pathways in promoting PA participation and enhancing response to interventions in sedentary older adults should be studied.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT01072500.