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

Abstract

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.

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

“…11 Current literature suggests a positive relationship between CRF and gray matter (GM) volumes of the prefrontal cortex and the hippocampus. 12 Findings concerning white matter (WM) volumes are heterogeneous but point to higher WM volumes, fewer WM lesions, and improved WM microstructure in relation to higher physical fitness. 13 Existing studies were often limited by small study samples (rarely exceeding a few hundred participants), strongly selected patient groups (such as those with multiple sclerosis, heart failure, Alzheimer disease, or mild cognitive impairment), or restriction to older adults.…”

“…The present findings of positive relationships between the 3 CRF measures (VO 2 peak , VO 2 @AT, and W max ) and segmented brain volumes (total GM volume and TBV) are in line with the previous literature. 12,26 Zooming into a fine spatial resolution, VBM analyses on GM segmentations revealed several large clusters of voxels with P peak,FWE <.05 that were positively associated with CRF. Thus, VO 2 peak and W max were significantly associated with greater GM volumes in the hippocampus/parahippocampus, the temporal gyrus, the fusiform gyrus, the cingulate cortex, the orbitofrontal cortex, the cerebellum, the left caudate nucleus, and the left thalamus.…”

“…The present findings in the hippocampus and the orbitofrontal cortex, which is a part of the prefrontal cortex, are in line with the most robustly replicated results throughout the physical activity and CRF literature related to brain volumes. 12,26,27 The hippocampus itself plays a central role in memory-related functions (coding of memories, long-term memory, and retrieval) 28 and in stress regulation. 29 Hippocampus atrophy was found to be associated with several diseases and disorders, such as Alzheimer disease, 30 depression, 31 and schizophrenia.…”

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

“…Recent neuroimaging research has begun shifting from functional localization to prediction of health-relevant outcomes (Bzdok & Ioannidis, 2019;Yarkoni & Westfall, 2017). For example, "brain-as-predictor" approaches (Berkman & Falk, 2013) have found connections between brain activity in regions of interest (ROIs) and future health outcomes such as eating behavior, weight gain, and smoking (Demos et al, 2012;Falk et al, 2011;Hall et al, 2018;Lopez et al, 2014). Yet, several barriers limit the predictive utility of this approach.…”

Contextual cues as modifiers of cTBS effects on indulgent eating

“…However, there is both theoretical and empirical justification for considering the latter two factors, when attempting to quantify the direction and magnitude of any causal effect of the dlPFC on eating outcomes. In theory, brain systems that support cognitive control have potential to be more consequential for food consumption when the food is calorie-dense than otherwise, and when environmental cues impel indulgence rather than restraint [7][8][9].…”