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

Asthma, the central nervous system, and neurocognition: Current findings, potential mechanisms, and treatment implications

Accumulating behavioral evidence suggests that asthma is associated with cognitive deficits. A number of studies have identified potential biological contributions to cognition in asthma; however, mechanistic pathways of central nervous system (CNS) involvement in asthma are yet to be established. We therefore conducted a literature review to identify studies examining potential CNS contributions to cognition in asthma. In this review, we discuss our general understanding of the CNS in asthma in the context of cognitive performance and outline a working model of mechanistic pathways linking the proposed neural influences of asthma pathology with cognition. To this extent, we incorporate neural, behavioral, psychological, social and environmental factors. Finally, we underscore the clinical significance of the CNS and neurocognitive sequelae in asthma, highlighting potential opportunities for routine monitoring, therapeutic intervention, and recommend key areas for future research.

Testing and Optimizing Guided Thinking Tasks to Promote Physical Activity: Protocol for a Randomized Factorial Trial (Preprint)

Background

Objective

Methods

Results

Conclusions

Trial Registration

International Registered Report Identifier (IRRID)

Harnessing Neuroimaging to Reduce Socioeconomic Disparities in Chronic Disease: A Conceptual Framework for Improving Health Messaging

Socioeconomic status (SES)-related health disparities persist for numerous chronic diseases, with lower-SES individuals exhibiting greater risk of morbidity and mortality compared to their higher-SES counterparts. One likely contributor is disparities in health messaging efforts, which are currently less effective for motivating health behavior change among those lower in SES. Drawing on communication neuroscience and social neuroscience research, we describe a conceptual framework to improve health messaging effectiveness in lower SES communities. The framework is based on evidence that health-message-induced activity in the ventral striatum (VS) and subdivisions of the medial pre-frontal cortex (MPFC) predicts behavior change. Additionally, we draw from social neuroscience work showing that activity in these regions during valuation and the processing of self-related vs. social information, differs as a function of SES. Bringing together these previously disparate lines of work, we argue that health messages emphasizing the benefits to close others (vs. the self) of engaging in behavior change will be more effective among lower SES individuals. We also outline a research agenda based on our framework. Ultimately, we hope that this framework utilizing a “brain-as-predictor” approach generates novel insights about the neural underpinnings of message-induced behavior change among lower SES individuals, and helps to close the gap in SES-based health disparities by harnessing the power of neuroimaging.

Individual Differences in Brain Responses: New Opportunities for Tailoring Health Communication Campaigns

Prevention neuroscience investigates the brain basis of attitude and behavior change. Over the years, an increasingly structurally and functionally resolved "persuasion network" has emerged. However, current studies have only identified a small handful of neural structures that are commonly recruited during persuasive message processing, and the extent to which these (and other) structures are sensitive to numerous individual difference factors remains largely unknown. In this project we apply a multi-dimensional similarity-based individual differences analysis to explore which individual factors-including characteristics of messages and target audiences-drive patterns of brain activity to be more or less similar across individuals encountering the same anti-drug public service announcements (PSAs). We demonstrate that several ensembles of brain regions show response patterns that are driven by a variety of unique factors. These results are discussed in terms of their implications for neural models of persuasion, prevention neuroscience and message tailoring, and methodological implications for future research.

Neural Indicators Of Food Cue Reactivity, Regulation, And Valuation And Their Associations With Body Composition And Daily Eating Behavior

Exposure to food cues activates the brain's reward system and undermines efforts to regulate impulses to eat. During explicit regulation, lateral prefrontal cortex activates and modulates activity in reward regions and decreases food cravings. However, it is unclear the extent to which between-person differences in recruitment of regions associated with reward processing, subjective valuation, and regulation during food cue exposure-absent instructions to regulate-predict body composition and daily eating behaviors. In this preregistered study, we pooled data from five fMRI samples (N = 262) to examine whether regions associated with reward, valuation, and regulation, as well as whole-brain pattern expression indexing these processes, were recruited during food cue exposure and associated with body composition and real-world eating behavior. Regression models for a single a priori analytic path indicated that univariate and multivariate measures of reward and valuation were associated with individual differences in BMI and enactment of daily food cravings. Specification curve analyses further revealed reliable associations between univariate and multivariate neural indicators of reactivity, regulation, and valuation, and all outcomes. These findings highlight the utility of these methods to elucidate brain-behavior associations and suggest that multiple processes are implicated in proximal and distal markers of eating behavior.

Multivariate neural signatures for health neuroscience: assessing spontaneous regulation during food choice

Establishing links between neural systems and health can be challenging since there is not a one-to-one mapping between brain regions and psychological states. Building sensitive and specific predictive models of health-relevant constructs using multivariate activation patterns of brain activation is a promising new direction. We illustrate the potential of this approach by building two 'neural signatures' of food craving regulation (CR) using multivariate machine learning and, for comparison, a univariate contrast. We applied the signatures to two large validation samples of overweight adults who completed tasks measuring CR ability and valuation during food choice. Across these samples, the machine learning signature was more reliable. This signature decoded CR from food viewing and higher signature expression was associated with less craving. During food choice, expression of the regulation signature was stronger for unhealthy foods and inversely related to subjective value, indicating that participants engaged in CR despite never being instructed to control their cravings. Neural signatures thus have the potential to measure spontaneous engagement of mental processes in the absence of explicit instruction, affording greater ecological validity. We close by discussing the opportunities and challenges of this approach, emphasizing what machine learning tools bring to the field of health neuroscience.

Greater delay discounting and cannabis coping motives are associated with more frequent cannabis use in a large sample of adult cannabis users

BACKGROUND

Self-regulation deficits expressed through a decreased ability to value future rewards (delay discounting (DD)) and impaired emotion regulation (negative urgency (NU), cannabis coping motives (CCM), and anxiety sensitivity (AS)) relate to more frequent or problematic cannabis use. However, there is a need to better understand how self-regulation and emotion regulation constructs reflect competition between deliberative and reactive systems that drive individual differences in cannabis use patterns. Further, few studies assess frequency of cannabis use within and across days of use, which may obscure differentiation of individual differences.

METHODS

In a large national sample of 2545 cannabis users, Latent Class Analysis was used to derive participant sub-classes based on two frequency indices, self-reported cannabis use days and times cannabis was used per day. Three classes emerged: Low (1-9 days/month, 1 time/day; 23 %), moderate (10-29 days/month, 2-3 times/day; 41 %), and high (30 days/month, ≥4 times/day; 36 %). Relationships among frequency classes and emotional regulation and impulsivity were assessed with a multinomial logistic regression.

RESULTS

Higher frequency use was associated with greater DD (χ2 = 6.0, p = .05), greater CCM (χ2 = 73.3, p < .001), and lower cognitive AS (χ2 = 12.1, p = .002), when controlling for demographics, tobacco use, and number of cannabis administration methods. Frequency class and NU were not significantly associated.

CONCLUSIONS

Identifying meaningful patterns of cannabis use may improve our understanding of individual differences that increase risk of frequent or problematic cannabis use. Excessive delay discounting and using cannabis to cope with negative affect may be relevant targets for treatments designed to reduce cannabis use.

Cardiorespiratory Fitness and Gray Matter Volume in the Temporal, Frontal, and Cerebellar Regions in the General Population

OBJECTIVE

To analyze the association between cardiorespiratory fitness (CRF) and global and local brain volumes.

PARTICIPANTS AND METHODS

We studied 2103 adults (21-84 years old) from 2 independent population-based cohorts (Study of Health in Pomerania, examinations from June 25, 2008, through September 30, 2012). Cardiorespiratory fitness was measured using peak oxygen uptake (VO₂peak), oxygen uptake at the anaerobic threshold (VO₂@AT), and maximal power output from cardiopulmonary exercise testing on a bicycle ergometer. Magnetic resonance imaging brain data were analyzed by voxel-based morphometry using regression models with adjustment for age, sex, education, smoking, body weight, systolic blood pressure, glycated hemoglobin level, and intracranial volume.

RESULTS

Volumetric analyses revealed associations of CRF with gray matter (GM) volume and total brain volume. After multivariable adjustment, a 1-standard deviation increase in VO₂peak was related to a 5.31 cm³ (95% CI, 3.27 to 7.35 cm³) higher GM volume. Whole-brain voxel-based morphometry analyses revealed significant positive relations between CRF and local GM volumes. The VO₂peak was strongly associated with GM volume of the left middle temporal gyrus (228 voxels), the right hippocampal gyrus (146 voxels), the left orbitofrontal cortex (348 voxels), and the bilateral cingulate cortex (68 and 43 voxels).

CONCLUSION

Cardiorespiratory fitness was positively associated with GM volume, total brain volume, and specific GM and white matter clusters in brain areas not primarily involved in movement processing. These results, from a representative population sample, suggest that CRF might contribute to improved brain health and might, therefore, decelerate pathology-specific GM decrease.

Low Body Mass Index and Low Intelligence Quotient Are Infection Risk Factors in Vagus Nerve Stimulation

BACKGROUND

Risk factors for infection after vagus nerve stimulation (VNS) device implantation represent an important issue but remain unclear. We hypothesized that specific risk factors for infection would be associated with VNS device implantation. This study reviewed patients with epilepsy who underwent VNS device implantation and undertook a statistical analysis of risk factors for surgical site infection (SSI).

METHODS

We reviewed all medical records for patients who underwent VNS therapy in our facility between August 2011 and May 2018. Age, sex, height, body weight, body mass index (BMI), intelligence quotient (IQ), surgical incision opening time, blood loss, epilepsy classification, activities of daily living, and generator replacement were statistically compared between cases with and without SSI.

RESULTS

We performed 208 VNS device implantation surgeries at our facility during the study period. Among these, 150 patients underwent initial implantation, 56 patients underwent first generator replacement, and 2 patients underwent second replacement. Six patients (2.7%) with initial implantation and 3 patients (5.4%) with first replacement showed SSI. Low BMI was a risk factor for infection at initial implantation (P < 0.0012) using a BMI within 1.78 kg/m² of the cutoff for being underweight (100% sensitivity, 25% specificity). Low IQ (P = 0.0015) was also a risk factor for SSI.

CONCLUSIONS

This study identified low BMI and low IQ at initial implantation as risk factors for infection.

Recruitment of cognitive control regions during effortful self-control is associated with altered brain activity in control and reward systems in dieters during subsequent exposure to food commercials

Engaging in effortful self-control can sometimes impair people’s ability to resist subsequent temptations. Existing research has shown that when chronic dieters’ self-regulatory capacity is challenged by prior exertion of effort, they demonstrate disinhibited eating and altered patterns of brain activity when exposed to food cues. However, the relationship between brain activity during self-control exertion and subsequent food cue exposure remains unclear. In the present study, we investigated whether individual differences in recruitment of cognitive control regions during a difficult response inhibition task are associated with a failure to regulate neural responses to rewarding food cues in a subsequent task in a cohort of 27 female dieters. During self-control exertion, participants recruited regions commonly associated with inhibitory control, including dorsolateral prefrontal cortex (DLPFC). Those dieters with higher DLPFC activity during the initial self-control task showed an altered balance of food cue elicited activity in regions associated with reward and self-control, namely: greater reward-related activity and less recruitment of the frontoparietal control network. These findings suggest that some dieters may be more susceptible to the effects of self-control exertion than others and, whether due to limited capacity or changes in motivation, these dieters subsequently fail to engage control regions that may otherwise modulate activity associated with craving and reward.

Low-cost, Implantable Wireless Sensor Platform for Neuromodulation Research

The role of peripheral nerves in regulating major organ function in health and disease is not well understood. Elucidating the relationships between biomarkers and neural activity during conditions free form anesthesia is essential to advancing future investigations of autonomic organ control and improving precision for neuromodulation treatment approaches. Here we present a simple, customizable, off-the-shelf component sensor platform to meet research needs for studying different organs under conscious, free movement. The platform consists of a small, rechargeable coin-cell battery, an energy-harvesting IC, a low-power microcontroller, a low-power pressure transducer, customizable number of electrodes with a common anode, inductive recharge input, and OOK inductive transmission. A case study demonstrating a bladder implant for long-term monitoring is presented, utilizing a novel, non-hermetic encapsulation approach. The customized platform uses two sleep modes to minimize battery loading, exhibiting a maximum time-averaged current draw of 125 micro-amps during sensing and transmission, with a quiescent current draw of 95 nano-amps into the microcontroller.