Functional Abnormality of the Executive Control Network in Individuals With Obesity During Delay Discounting

Functional alterations in overweight/obesity: focusing on the reward and executive control network

Overweight (OW) and obesity (OB) have become prevalent issues in the global public health arena. Serving as a prominent risk factor for various chronic diseases, overweight/obesity not only poses serious threats to people's physical and mental health but also imposes significant medical and economic burdens on society as a whole. In recent years, there has been a growing focus on basic scientific research dedicated to seeking the neural evidence underlying overweight/obesity, aiming to elucidate its causes and effects by revealing functional alterations in brain networks. Among them, dysfunction in the reward network (RN) and executive control network (ECN) during both resting state and task conditions is considered pivotal in neuroscience research on overweight/obesity. Their aberrations contribute to explaining why persons with overweight/obesity exhibit heightened sensitivity to food rewards and eating disinhibition. This review centers on the reward and executive control network by analyzing and organizing the resting-state and task-based fMRI studies of functional brain network alterations in overweight/obesity. Building upon this foundation, the authors further summarize a reward-inhibition dual-system model, with a view to establishing a theoretical framework for future exploration in this field.

Healthy dietary choices involve prefrontal mechanisms associated with long-term reward maximization but not working memory

Taste and health are critical factors to be considered when choosing foods. Prioritizing healthiness over tastiness requires self-control. It has also been suggested that self-control is guided by cognitive control. We then hypothesized that neural mechanisms underlying healthy food choice are associated with both self-control and cognitive control. Human participants performed a food choice task and a working memory task during functional MRI scanning. Their degree of self-control was assessed behaviorally by the value discount of delayed monetary rewards in intertemporal choice. Prioritizing healthiness in food choice was associated with greater activity in the superior, dorsolateral, and medial prefrontal cortices. Importantly, the prefrontal activity was greater in individuals with smaller delay discounting (i.e. high self-control) who preferred a delayed larger reward to an immediate smaller reward in intertemporal choice. On the other hand, working memory activity did not show a correlation with delay discounting or food choice activity, which was further supported by supplementary results that analyzed data from the Human Connectome Project. Our results suggest that the prefrontal cortex plays a critical role in healthy food choice, which requires self-control, but not working memory, for maximization of reward attainments in a remote future.

Additive effects of depression and obesity on neural correlates of inhibitory control

BACKGROUND

Depression and obesity are associated with impaired inhibitory control. Behavioral evidence indicates an exacerbating additive effect when both conditions co-occur. However, the underlying neural mechanisms remain unclear. Moreover, systemic inflammation affects neurocognitive performance in both individuals with depression and obesity. Here, we investigate additive effects of depression and obesity on neural correlates of inhibitory control, and examine inflammation as a connecting pathway.

METHODS

We assessed inhibitory control processing in 64 individuals with obesity and varying degrees of depressed mood by probing neural activation and connectivity during an fMRI Stroop task. Additionally, we explored associations of altered neural responses with individual differences in systemic inflammation. Data were collected as part of the BARICO (Bariatric surgery Rijnstate and Radboudumc neuroimaging and Cognition in Obesity) study.

RESULTS

Concurrent depression and obesity were linked to increased functional connectivity between the supplementary motor area and precuneus and between the inferior occipital and inferior parietal gyrus. Exploratory analysis revealed that circulating inflammation markers, including plasma leptin, IL-6, IL-8, and CCL-3 correlated with the additive effect of depression and obesity on altered functional connectivity.

LIMITATIONS

The observational design limits causal inferences. Future research employing longitudinal or intervention designs is required to validate these findings and elucidate causal pathways.

CONCLUSION

These findings suggest increased neural crosstalk underlying impaired inhibitory control in individuals with concurrent obesity and depressed mood. Our results support a model of an additive detrimental effect of concurrent depression and obesity on neurocognitive functioning, with a possible role of inflammation.

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.

Neuroanatomical profile of BMI implicates impulsive delay discounting and general cognitive ability

OBJECTIVE

Obesity is a disorder of excessive adiposity, typically assessed via the anthropometric density measure of BMI. Numerous studies have implicated BMI with differences in brain structure, but with highly inconsistent findings.

METHODS

Machine learning elastic net regression models with cross-validation were conducted to characterize a neuroanatomical morphometry profile associated with BMI in 1100 participants (22% BMI > 30, n = 242) from the Human Connectome Project Young Adult project.

RESULTS

Using five-fold cross-validation, the multiregion neuroanatomical profile substantively predicted BMI (R2  = 10.05%), and this was robust in a held-out test set (R2  = 8.87%). In terms of specific regions, the neuroanatomical profile was enriched for nodes in the default mode, executive control, and salience networks. The relationship between the morphometry profile and BMI itself was partially mediated by impulsive delay discounting and general cognitive ability.

CONCLUSIONS

Taken together, these findings reveal a robust machine learning-derived neuroanatomical profile of BMI, one that comprises nodes in motivational brain networks and suggests the functional links to obesity are via self-regulatory capacity and cognitive function.

Brain functional and structural magnetic resonance imaging of obesity and weight loss interventions

Obesity has tripled over the past 40 years to become a major public health issue, as it is linked with increased mortality and elevated risk for various physical and neuropsychiatric illnesses. Accumulating evidence from neuroimaging studies suggests that obesity negatively affects brain function and structure, especially within fronto-mesolimbic circuitry. Obese individuals show abnormal neural responses to food cues, taste and smell, resting-state activity and functional connectivity, and cognitive tasks including decision-making, inhibitory-control, learning/memory, and attention. In addition, obesity is associated with altered cortical morphometry, a lowered gray/white matter volume, and impaired white matter integrity. Various interventions and treatments including bariatric surgery, the most effective treatment for obesity in clinical practice, as well as dietary, exercise, pharmacological, and neuromodulation interventions such as transcranial direct current stimulation, transcranial magnetic stimulation and neurofeedback have been employed and achieved promising outcomes. These interventions and treatments appear to normalize hyper- and hypoactivations of brain regions involved with reward processing, food-intake control, and cognitive function, and also promote recovery of brain structural abnormalities. This paper provides a comprehensive literature review of the recent neuroimaging advances on the underlying neural mechanisms of both obesity and interventions, in the hope of guiding development of novel and effective treatments.

Perigenual anterior cingulate cortex and its structural covariance as predictors for future body fat gain in young adults

OBJECTIVE

This study aimed to examine whether baseline gray matter (GM) volume and structural covariance patterns could predict body fat gain over 1 to 2 years in a relatively large sample.

METHODS

Voxel-based morphometry (VBM) analysis was applied to examine the association between baseline GM volume and body fat gain in 502 participants over 1 to 2 years. Furthermore, this study tested whether the structural covariances between the regions identified as seeds from VBM analysis and the rest of the brain were associated with future body fat gain.

RESULTS

A significant positive association was observed between baseline GM volume in the perigenual anterior cingulate cortex (pgACC) and body fat gain over 1 to 2 years. Furthermore, relative to those with lower future body fat gain, pgACC covaried more extensively with the middle frontal gyrus, middle temporal gyrus, inferior temporal gyrus, and cerebellum in participants with higher future body fat gain.

CONCLUSIONS

Using VBM and structural covariance network analysis, the current study revealed that higher GM volume of pgACC and its increased structural covariances with specific brain regions were associated with future weight gain, which may guide the development of more effective prevention and treatment interventions for obesity.

OUP accepted manuscript

The Coronavirus disease of 2019 (COVID-19) and measures to curb it created population-level changes in male-dominant impulsive and risky behaviors such as violent crimes and gambling. One possible explanation for this is that the pandemic has been stressful, and males, more so than females, tend to respond to stress by altering their focus on immediate versus delayed rewards, as reflected in their delay discounting rates. Delay discounting rates from healthy undergraduate students were collected twice during the pandemic. Discounting rates of males (n=190) but not of females (n=493) increased during the pandemic. Using machine learning, we show that prepandemic functional connectome predict increased discounting rates in males (n=88). Moreover, considering that delay discounting is associated with multiple psychiatric disorders, we found the same neural pattern that predicted increased discounting rates in this study, in secondary datasets of patients with major depression and schizophrenia. The findings point to sex-based differences in maladaptive delay discounting under real-world stress events, and to connectome-based neuromarkers of such effects. They can explain why there was a population-level increase in several impulsive and risky behaviors during the pandemic and point to intriguing questions about the shared underlying mechanisms of stress responses, psychiatric disorders and delay discounting.

How Impulsiveness Influences Obesity: The Mediating Effect of Resting-State Brain Activity in the dlPFC

Impulsiveness is a stable personal characteristic that contributes to obesity and may interact with it. Specifically, obesity is caused by unrestrained impulse eating that is not consciously controlled and leads to a hormonal imbalance that also can impair impulse control. However, the mechanism of this relationship is unclear. In our study, 35 obese individuals (body mass index, BMI > 28) were recruited and matched with 31 healthy controls (BMI < 24) in age and education level. All the participants underwent a resting-state fMRI and completed the Barratt Impulsiveness Scale-11. The results showed that patients with obesity had a significantly lower fractional amplitude of low-frequency fluctuations (fALFF) in the bilateral dorsolateral prefrontal cortex (dlPFC) and higher fALFF in the left fusiform cortex. In addition, non-planning impulsiveness was positively correlated with BMI. Importantly, we found that the right dlPFC completely mediated the relationship between non-planning impulsiveness and BMI. Our findings suggest that impulsivity is statistically more likely to precede obesity than to precede impulsivity and contributes to obesity by downregulating spontaneous activity in the dlPFC. This suggests that the dlPFC, which is associated with executive control, may be able a potential target for treating obesity.