Comparing two neurocognitive models of self-control during dietary decisions

Body mass index-dependent shifts along large-scale gradients in human cortical organization explain dietary regulatory success

Making healthy dietary choices is essential for keeping weight within a normal range. Yet many people struggle with dietary self-control despite good intentions. What distinguishes neural processing in those who succeed or fail to implement healthy eating goals? Does this vary by weight status? To examine these questions, we utilized an analytical framework of gradients that characterize systematic spatial patterns of large-scale neural activity, which have the advantage of considering the entire suite of processes subserving self-control and potential regulatory tactics at the whole-brain level. Using an established laboratory food task capturing brain responses in natural and regulatory conditions (N = 123), we demonstrate that regulatory changes of dietary brain states in the gradient space predict individual differences in dietary success. Better regulators required smaller shifts in brain states to achieve larger goal-consistent changes in dietary behaviors, pointing toward efficient network organization. This pattern was most pronounced in individuals with lower weight status (low-BMI, body mass index) but absent in high-BMI individuals. Consistent with prior work, regulatory goals increased activity in frontoparietal brain circuits. However, this shift in brain states alone did not predict variance in dietary success. Instead, regulatory success emerged from combined changes along multiple gradients, showcasing the interplay of different large-scale brain networks subserving dietary control and possible regulatory strategies. Our results provide insights into how the brain might solve the problem of dietary control: Dietary success may be easier for people who adopt modes of large-scale brain activation that do not require significant reconfigurations across contexts and goals.

If you're happy and you know it: neural correlates of self-evaluated psychological health and well-being

Psychological health and well-being have important implications for individual and societal thriving. Research underscores the subjective nature of well-being, but how do individuals intuit this subjective sense of well-being in the moment? This pre-registered study addresses this question by examining the neural correlates of self-evaluated psychological health and their dynamic relationship with trial-level evaluations. Participants (N = 105) completed a self-evaluation task and made judgments about three facets of psychological health and positive functioning-self-oriented well-being, social well-being and ill-being. Consistent with pre-registered hypotheses, self-evaluation elicited activity in the default mode network, and there was strong spatial overlap among constructs. Trial-level analyses assessed whether and how activity in a priori regions of interest-perigenual anterior cingulate cortex (pgACC), ventromedial prefrontal cortex (vmPFC) and ventral striatum-were related to subjective evaluations. These regions explained additional variance in whether participants endorsed or rejected items but were differentially related to evaluations. Stronger activity in pgACC was associated with a higher probability of endorsement across constructs, whereas stronger activity in vmPFC was associated with a higher probability of endorsing ill-being items, but a lower probability of endorsing self-oriented and social well-being items. These results add nuance to neurocognitive accounts of self-evaluation and extend our understanding of the neurobiological basis of subjective psychological health and well-being.

Value-based neural representations predict social decision preferences

Social decision-making is omnipresent in everyday life, carrying the potential for both positive and negative consequences for the decision-maker and those closest to them. While evidence suggests that decision-makers use value-based heuristics to guide choice behavior, very little is known about how decision-makers' representations of other agents influence social choice behavior. We used multivariate pattern expression analyses on fMRI data to understand how value-based processes shape neural representations of those affected by one's social decisions and whether value-based encoding is associated with social decision preferences. We found that stronger value-based encoding of a given close other (e.g. parent) relative to a second close other (e.g. friend) was associated with a greater propensity to favor the former during subsequent social decision-making. These results are the first to our knowledge to explicitly show that value-based processes affect decision behavior via representations of close others.

Stimulation of the dorsolateral prefrontal cortex modulates brain cue reactivity to reward (un)availability

Brain imaging studies have shown that stimulation of the left dorsolateral prefrontal cortex (dlPFC), which plays a pivotal role in high-order cognitive control processes, modulates brain reactivity to reward-related cues. Nevertheless, the impact of contextual factors such as reward availability (the reward that is depicted in the cue exposure task) on such modulation effect remains unclear. Here we tested whether a single session of high-frequency repetitive transcranial magnetic stimulation (HF-rTMS) over the left dlPFC differently impacts brain reactivity to cues signalling either availability or unavailability of a sports betting opportunity. Employing a within-subject design (verum versus sham HF-rTMS) among thirty-two frequent sports bettors, we first observed that, as compared to the sham condition, verum HF-rTMS modulated brain reactivity to game cues prior to being made (un)available for betting, through simultaneous increases (posterior insula and caudate nucleus) and decreases (occipital pole) in brain activation. Second, verum HF-rTMS led to increased ventral striatal activity towards cues available for betting but did not modulate brain response to cues unavailable for betting. Taken together, these findings demonstrate that transient stimulation of the left dlPFC led to a general modulation in brain activity in responses to cues, and that this effect is only partly dependent on cues signalling for reward (un)availability.

Recruitment of dlPFC during dietary self-regulation predicts the transience of regulatory effects

Recent work on the cognitive regulation of dietary decision-making suggests that regulation can alter both the choices that people make in the moment and longer-lasting preferences. However, it is unclear what mechanisms lead to temporary or lingering changes. To address this question, we used fMRI during a task employing the cognitive regulation of food choice and assessed changes in food preference from baseline to post-regulation. We found evidence that regulation may result in a temporary reconfiguration of the neural drivers of choice, de-emphasizing goal-inconsistent value-related computations in the ventromedial prefrontal cortex and resulting in more goal-consistent changes in value-related computations in the dorsolateral prefrontal cortex (dlPFC). Moreover, we find that the extent to which the dlPFC was recruited to represent different regulatory goals during the moment of choice negatively predicted the extent to which those regulatory goals produced lingering changes in preference. Our results suggest that the recruitment of the dlPFC in the service of regulation may have a downside: it is effective at changing behavior in the moment, but its effects on preferences are transient.

The Use of Self-Help Strategies in Obesity Treatment. A Narrative Review Focused on Hypnosis and Mindfulness

PURPOSE OF REVIEW

The aim of this narrative review was to summarize the evidence evaluating the possibilities and limitations of self-hypnosis and mindfulness strategies in the treatment of obesity.

RECENT FINDINGS

Psychological factors, such as mood disorders and stress, can affect eating behaviors and deeply influence weight gain. Psychological approaches to weight management could increase the motivation and self-control of the patients with obesity, limiting their impulsiveness and inappropriate use of food. The cognitive-behavioral therapy (CBT) represents the cornerstone of obesity treatment, but complementary and self-directed psychological interventions, such as hypnosis and mindfulness, could represent additional strategies to increase the effectiveness of weight loss programs, by improving dysfunctional eating behaviors, self-motivation, and stimulus control. Both hypnosis and mindfulness provide a promising therapeutic option by improving weight loss, food awareness, self-acceptance of body image, and limiting food cravings and emotional eating. Greater effectiveness occurs when hypnosis and mindfulness are associated with other psychological therapies in addition to diet and physical activity. Additional research is needed to determine whether these strategies are effective in the long term and whether they can be routinely introduced into the clinical practice.

Revisiting the Neural Architecture of Adolescent Decision-Making: Univariate and Multivariate Evidence for System-Based Models

Understanding adolescent decision-making is significant for informing basic models of neurodevelopment as well as for the domains of public health and criminal justice. System-based theories posit that adolescent decision-making is guided by activity related to reward and control processes. While successful at explaining behavior, system-based theories have received inconsistent support at the neural level, perhaps because of methodological limitations. Here, we used two complementary approaches to overcome said limitations and rigorously evaluate system-based models. Using decision-level modeling of fMRI data from a risk-taking task in a sample of 2000+ decisions across 51 human adolescents (25 females, mean age = 15.00 years), we find support for system-based theories of decision-making. Neural activity in lateral PFC and a multivariate pattern of cognitive control both predicted a reduced likelihood of risk-taking, whereas increased activity in the NAcc predicted a greater likelihood of risk-taking. Interactions between decision-level brain activity and age were not observed. These results garner support for system-based accounts of adolescent decision-making behavior.SIGNIFICANCE STATEMENT Adolescent decision-making behavior is of great import for basic science, and carries equally consequential implications for public health and criminal justice. While dominant psychological theories seeking to explain adolescent decision-making have found empirical support, their neuroscientific implementations have received inconsistent support. This may be partly because of statistical approaches used by prior neuroimaging studies of system-based theories. We used brain modeling, an approach that predicts behavior from brain activity, of univariate and multivariate neural activity metrics to better understand how neural components of psychological systems guide decision behavior in adolescents. We found broad support for system-based theories such that neural systems involved in cognitive control predicted a reduced likelihood to make risky decisions, whereas value-based systems predicted greater risk-taking propensity.

Neural Substrates of Food Valuation and Its Relationship With BMI and Healthy Eating in Higher BMI Individuals

Considerable evidence points to a link between body mass index (BMI), eating behavior, and the brain's reward system. However, much of this research focuses on food cue reactivity without examining the subjective valuation process as a potential mechanism driving individual differences in BMI and eating behavior. The current pre-registered study (https://osf.io/n4c95/) examined the relationship between BMI, healthy eating, and subjective valuation of healthy and unhealthy foods in a community sample of individuals with higher BMI who intended to eat more healthily. Particularly, we examined: (1) alterations in neurocognitive measures of subjective valuation related to BMI and healthy eating; (2) differences in the neurocognitive valuation for healthy and unhealthy foods and their relation to BMI and healthy eating; (3) and whether we could conceptually replicate prior findings demonstrating differences in neural reactivity to palatable vs. plain foods. To this end, we scanned 105 participants with BMIs ranging from 23 to 42 using fMRI during a willingness-to-pay task that quantifies trial-by-trial valuation of 30 healthy and 30 unhealthy food items. We measured out of lab eating behavior via the Automated Self-Administered 24 H Dietary Assessment Tool, which allowed us to calculate a Healthy Eating Index (HEI). We found that our sample exhibited robust, positive linear relationships between self-reported value and neural responses in regions previously implicated in studies of subjective value, suggesting an intact valuation system. However, we found no relationship between valuation and BMI nor HEI, with Bayes Factor indicating moderate evidence for a null relationship. Separating the food types revealed that healthy eating, as measured by the HEI, was inversely related to subjective valuation of unhealthy foods. Imaging data further revealed a stronger linkage between valuation of healthy (compared to unhealthy) foods and corresponding response in the ventromedial prefrontal cortex (vmPFC), and that the interaction between healthy and unhealthy food valuation in this region is related to HEI. Finally, our results did not replicate reactivity differences demonstrated in prior work, likely due to differences in the mapping between food healthiness and palatability. Together, our findings point to disruptions in the valuation of unhealthy foods in the vmPFC as a potential mechanism influencing healthy eating.

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.

Is obesity related to enhanced neural reactivity to visual food cues? A review and meta-analysis

Theoretical work suggests that obesity is related to enhanced incentive salience of food cues. However, evidence from both behavioral and neuroimaging studies on the topic is mixed. In this work we review the literature on cue reactivity in obesity and perform a preregistered meta-analysis of studies investigating effects of obesity on brain responses to passive food pictures viewing. Further, we examine whether age influences brain responses to food cues in obesity. In the meta-analysis we included 13 studies of children and adults that investigated group differences (obese vs. lean) in responses to food vs. non-food pictures viewing. While we found no significant differences in the overall meta-analysis, we show that age significantly influences brain response differences to food cues in the left insula and the left fusiform gyrus. In the left insula, obese vs. lean brain differences in response to food cues decreased with age, while in the left fusiform gyrus the pattern was opposite. Our results suggest that there is little evidence for obesity-related differences in responses to food cues and that such differences might be mediated by additional factors that are often not considered.