Failing to learn from negative prediction errors: Obesity is associated with alterations in a fundamental neural learning mechanism

Behavioral and neural alterations of the ventral tegmental area by exposure to junk food in rats

The brain reward system is essential for regulating appetitive and consummatory behaviors in response to various incentive stimuli. Junk food, characterized by its high palatability, is particularly associated with the potential for excessive consumption. While prior studies indicate that excessive junk food intake can impact reward circuitry, the precise mechanisms underlying these effects remain elusive. Furthermore, it is unclear whether the functionality of this neural system is similarly altered in response to other natural rewards. In this study, we used fiber photometry combined with a behavioral reward test to investigate the effects of six weeks of excessive cafeteria (CAF) diet consumption on ventral tegmental area (VTA) neural activity and behavioral responses to food and sexual rewards in female rats. Our findings demonstrate that prolonged exposure to a CAF diet reduced the exploration and consumption of food rewards. These behavioral changes were accompanied by attenuated neural activity in the VTA. Similarly, reductions in VTA activity were observed in response to a sexual partner, although no significant behavioral differences were detected during sexual interactions. Moreover, a two-week reversal diet of standard chow proved insufficient to restore VTA neural activity in CAF-exposed animals, which continued to exhibit decreased VTA responses to both food rewards and sexual partners. Our results suggest that prolonged junk food exposure induces desensitization of the VTA, resulting in reduced responsiveness to natural rewards.

Disentangling negative reinforcement, working memory, and deductive reasoning deficits in elevated BMI

Neuropsychological data suggest that being overweight or obese is associated with a tendency to perseverate behavior despite negative feedback. This deficit might be observed due to other cognitive factors, such as working memory (WM) deficits or decreased ability to deduce model-based strategies when learning by trial-and-error. In the present study, a group of subjects with overweight or obesity (Ow/Ob, n = 30) was compared to normal-weight individuals (n = 42) in a modified Reinforcement Learning (RL) task. The task was designed to control WM effects on learning by manipulating cognitive load and to foster model-based learning via deductive reasoning. Computational modelling and analysis were conducted to isolate parameters related to RL mechanisms, WM use, and model-based learning (deduction parameter). Results showed that subjects with Ow/Ob had a higher number of perseverative errors and used a weaker deduction mechanism in their performance than control individuals, indicating impairments in negative reinforcement and model-based learning, whereas WM impairments were not responsible for deficits in RL. The present data suggests that obesity is associated with impairments in negative reinforcement and model-based learning.

Neurocomputational Mechanisms Underlying Differential Reinforcement Learning From Wins and Losses in Obesity With and Without Binge Eating

BACKGROUND

Binge-eating disorder (BED) is thought of as a disorder of cognitive control, but evidence regarding its neurocognitive mechanisms is inconclusive. Key limitations of previous research include a lack of consistent separation between effects of BED and obesity and a disregard for self-report evidence suggesting that neurocognitive alterations may emerge primarily in loss- or harm-avoidance contexts.

METHODS

To address these gaps, in this longitudinal study we investigated behavioral flexibility and its underlying neurocomputational processes in reward-seeking and loss-avoidance contexts. Obese participants with BED, obese participants without BED, and healthy normal-weight participants (n = 96) performed a probabilistic reversal learning task during functional imaging, with different blocks focused on obtaining wins or avoiding losses. They were reinvited for a 6-month follow-up assessment.

RESULTS

Analyses informed by computational models of reinforcement learning showed that unlike obese participants with BED, obese participants without BED performed worse in the win than in the loss condition. Computationally, this was explained by differential learning sensitivities in the win versus loss conditions in the groups. In the brain, this was echoed in differential neural learning signals in the ventromedial prefrontal cortex per condition. The differences were subtle but scaled with BED symptoms, such that more severe BED symptoms were associated with increasing bias toward improved learning from wins versus losses. Across conditions, obese participants with BED switched more between choice options than healthy normal-weight participants. This was reflected in diminished representation of choice certainty in the ventromedial prefrontal cortex.

CONCLUSIONS

Our study highlights the importance of distinguishing between obesity with and without BED to identify unique neurocomputational alterations underlying different styles of maladaptive eating behavior.

Working memory gating in obesity is moderated by striatal dopaminergic gene variants

Everyday life requires an adaptive balance between distraction-resistant maintenance of information and the flexibility to update this information when needed. These opposing mechanisms are proposed to be balanced through a working memory gating mechanism. Prior research indicates that obesity may elevate the risk of working memory deficits, yet the underlying mechanisms remain elusive. Dopaminergic alterations have emerged as a potential mediator. However, current models suggest these alterations should only shift the balance in working memory tasks, not produce overall deficits. The empirical support for this notion is currently lacking, however. To address this gap, we pooled data from three studies (N = 320) where participants performed a working memory gating task. Higher BMI was associated with overall poorer working memory, irrespective of whether there was a need to maintain or update information. However, when participants, in addition to BMI level, were categorized based on certain putative dopamine-signaling characteristics (single-nucleotide polymorphisms [SNPs]; specifically, Taq1A and DARPP-32), distinct working memory gating effects emerged. These SNPs, primarily associated with striatal dopamine transmission, appear to be linked with differences in updating, specifically, among high-BMI individuals. Moreover, blood amino acid ratio, which indicates central dopamine synthesis capacity, combined with BMI shifted the balance between distractor-resistant maintenance and updating. These findings suggest that both dopamine-dependent and dopamine-independent cognitive effects exist in obesity. Understanding these effects is crucial if we aim to modify maladaptive cognitive profiles in individuals with obesity.

Practical strategies to manage obesity in type 2 diabetes

The rising phenomenon of obesity, a major risk factor for the development and progression of type 2 diabetes, is a complex and multifaceted issue that requires a comprehensive and coordinated approach to be prevented and managed. Although novel pharmacological measures to combat obesity have achieved unprecedented efficacy, a healthy lifestyle remains essential for the long-term success of any therapeutic intervention. However, this requires a high level of intrinsic motivation and continued behavioural changes in the face of multiple metabolic, psychological and environmental factors promoting weight gain, particularly in the context of type 2 diabetes. This review is intended to provide practical recommendations in the context of a holistic, person-centred approach to weight management, including evidence-based and expert recommendations addressing supportive communication, shared decision-making, as well as nutritional and pharmacological therapeutic approaches to achieve sustained weight loss.

Working memory gating in obesity: Insights from a case-control fMRI study

Computational models and neurophysiological data propose that a 'gating mechanism' coordinates distractor-resistant maintenance and flexible updating of working memory contents: While maintenance of information is mainly implemented in the prefrontal cortex, updating of information is signaled by phasic increases in dopamine in the striatum. Previous literature demonstrates structural and functional alterations in these brain areas, as well as differential dopamine transmission among individuals with obesity, suggesting potential impairments in these processes. To test this hypothesis, we conducted an observational case-control fMRI study, dividing participants into groups with and without obesity based on their BMI. We probed maintenance and updating of working memory contents using a modified delayed match to sample task and investigated the effects of SNPs related to the dopaminergic system. While the task elicited the anticipated brain responses, our findings revealed no evidence for group differences in these two processes, neither at the neural level nor behaviorally. However, depending on Taq1A genotype, which affects dopamine receptor density in the striatum, participants with obesity performed worse on the task. In conclusion, this study does not support the existence of overall obesity-related differences in working memory gating. Instead, we propose that potentially subtle alterations may manifest specifically in individuals with a 'vulnerable' genotype.

How are overweight and obesity associated with reinforcement learning deficits? A systematic review

Reinforcement learning (RL) refers to the ability to learn stimulus-response or response-outcome associations relevant to the acquisition of behavioral repertoire and adaptation to the environment. Research data from correlational and case-control studies have shown that obesity is associated with impairments in RL. The aim of the present study was to systematically review how obesity and overweight are associated with RL performance. More specifically, the relationship between high body mass index (BMI) and task performance was explored through the analysis of specific RL processes associated with different physiological, computational, and behavioral manifestations. Our systematic analyses indicate that obesity might be associated with impairments in the use of aversive outcomes to change ongoing behavior, as revealed by results involving instrumental negative reinforcement and extinction/reversal learning, but further research needs to be conducted to confirm this association. Hypotheses regarding how obesity might be associated with altered RL were discussed.

Liraglutide restores impaired associative learning in individuals with obesity

Survival under selective pressure is driven by the ability of our brain to use sensory information to our advantage to control physiological needs. To that end, neural circuits receive and integrate external environmental cues and internal metabolic signals to form learned sensory associations, consequently motivating and adapting our behaviour. The dopaminergic midbrain plays a crucial role in learning adaptive behaviour and is particularly sensitive to peripheral metabolic signals, including intestinal peptides, such as glucagon-like peptide 1 (GLP-1). In a single-blinded, randomized, controlled, crossover basic human functional magnetic resonance imaging study relying on a computational model of the adaptive learning process underlying behavioural responses, we show that adaptive learning is reduced when metabolic sensing is impaired in obesity, as indexed by reduced insulin sensitivity (participants: N = 30 with normal insulin sensitivity; N = 24 with impaired insulin sensitivity). Treatment with the GLP-1 receptor agonist liraglutide normalizes impaired learning of sensory associations in men and women with obesity. Collectively, our findings reveal that GLP-1 receptor activation modulates associative learning in people with obesity via its central effects within the mesoaccumbens pathway. These findings provide evidence for how metabolic signals can act as neuromodulators to adapt our behaviour to our body's internal state and how GLP-1 receptor agonists work in clinics.

Dorsal striatal response to taste is modified by obesity and insulin resistance

OBJECTIVE

In preclinical models, insulin resistance in the dorsal striatum (DS) contributes to overeating. Although human studies support the concept of central insulin resistance, they have not investigated its effect on consummatory reward-induced brain activity.

METHODS

Taste-induced activation was assessed in the caudate and putamen of the DS with blood oxygen level-dependent (BOLD) functional magnetic resonance imaging. Three phenotypically distinct groups were studied: metabolically healthy lean, metabolically healthy obesity, and metabolically unhealthy obesity (MUO; presumed to have central insulin resistance). Participants with MUO also completed a weight loss intervention followed by a second functional magnetic resonance imaging session.

RESULTS

The three groups were significantly different at baseline consistent with the design. The metabolically healthy lean group had a primarily positive BOLD response, the MUO group had a primarily negative BOLD response, and the metabolically healthy obesity group had a response in between the two other groups. Food craving was predicted by taste-induced activation. After weight loss in the MUO group, taste-induced activation increased in the DS.

CONCLUSIONS

These data support the hypothesis that insulin resistance and obesity contribute to aberrant responses to taste in the DS, which is only partially attenuated by weight loss. Aberrant responses to food exposure may be a barrier to weight loss.

Food reinforcement architecture: A framework for impulsive and compulsive overeating and food abuse

Few reward-based theories address key drivers of susceptibility to food cues and consumption beyond fullness. Decision-making and habit formation are governed by reinforcement-based learning processes that, when overstimulated, can drive unregulated hedonically motivated overeating. Here, a model food reinforcement architecture is proposed that uses fundamental concepts in reinforcement and decision-making to identify maladaptive eating habits that can lead to obesity. This model is unique in that it identifies metabolic drivers of reward and incorporates neuroscience, computational decision-making, and psychology to map overeating and obesity. Food reinforcement architecture identifies two paths to overeating: a propensity for hedonic targeting of food cues contributing to impulsive overeating and lack of satiation that contributes to compulsive overeating. A combination of those paths will result in a conscious and subconscious drive to overeat independent of negative consequences, leading to food abuse and/or obesity. Use of this model to identify aberrant reinforcement learning processes and decision-making systems that can serve as markers of overeating risk may provide an opportunity for early intervention in obesity.

Reduced sensitivity but intact motivation to monetary rewards and reversal learning in obesity

BACKGROUND

Obesity has been linked to altered reward processing but little is known about which components of reward processing including motivation, sensitivity and learning are impaired in obesity. We examined whether obesity compared to healthy weight controls is associated with differences in distinct subdomains of reward processing. To this end, we used two established paradigms, namely the Effort Expenditure for Rewards task (EEfRT) and the Probabilistic Reversal Learning Task (PRLT).

METHODS

30 individuals with obesity (OBS) and 30 healthy weight control subjects (HC) were included in the study. Generalized estimating equation models were used to analyze EEfRT choice behavior. PRLT data was analyzed using both conventional behavioral variables of choices and computational models.

RESULTS

Our findings from the different tasks speak in favor of a hyposensitivity to non-food rewards in obesity. OBS did not make fewer overall hard task selections compared to HC in the EEfRT suggesting generally intact non-food reward motivation. However, in highly rewarding trials (i.e.,trials with high reward magnitude and high reward probability),OBSmadefewer hard task selections compared to normal weight subjects suggesting decreased sensitivity to highly rewarding non-food reinforcers. Hyposensitivity to non-food rewards was also evident in OBS in the PRLT as evidenced by lower win-stay probability compared to HC. Our computational modelling analyses revealed decreased stochasticity but intact reward and punishment learning rates in OBS.

CONCLUSIONS

Our findings provide evidence for intact reward motivation and learning in OBS but lower reward sensitivity which is linked to stochasticity of choices in a non-food context. These findings might provide further insight into the mechanism underlying dysfunctional choices in obesity.

Impact of insulin and insulin resistance on brain dopamine signalling and reward processing- an underexplored mechanism in the pathophysiology of depression?

Type 2 diabetes and major depressive disorder (MDD) are the leading causes of disability worldwide and have a high comorbidity rate with fatal outcomes. Despite the long-established association between these conditions, the underlying molecular mechanisms remain unknown. Since the discovery of insulin receptors in the brain and the brain's reward system, evidence has accumulated indicating that insulin modulates dopaminergic (DA) signalling and reward behaviour. Here, we review the evidence from rodent and human studies, that insulin resistance directly alters central DA pathways, which may result in motivational deficits and depressive symptoms. Specifically, we first elaborate on the differential effects of insulin on DA signalling in the ventral tegmental area (VTA) - the primary DA source region in the midbrain - and the striatum as well as its effects on behaviour. We then focus on the alterations induced by insulin deficiency and resistance. Finally, we review the impact of insulin resistance in DA pathways in promoting depressive symptoms and anhedonia on a molecular and epidemiological level and discuss its relevance for stratified treatment strategies.

Self-reported intake of high-fat and high-sugar diet is not associated with cognitive stability and flexibility in healthy men

Animal studies indicate that a high-fat/high-sugar diet (HFS) can change dopamine signal transmission in the brain, which could promote maladaptive behavior and decision-making. Such diet-induced changes may also explain observed alterations in the dopamine system in human obesity. Genetic variants that modulate dopamine transmission have been proposed to render some individuals more prone to potential effects of HFS. The objective of this study was to investigate the association of HFS with dopamine-dependent cognition in humans and how genetic variations might modulate this potential association. Using a questionnaire assessing the self-reported consumption of high-fat/high-sugar foods, we investigated the association with diet by recruiting healthy young men that fall into the lower or upper end of that questionnaire (low fat/sugar group: LFS, n = 45; high fat/sugar group: HFS, n = 41) and explored the interaction of fat and sugar consumption with COMT Val¹⁵⁸Met and Taq1A genotype. During functional magnetic resonance imaging (fMRI) scanning, male participants performed a working memory (WM) task that probes distractor-resistance and updating of WM representations. Logistic and linear regression models revealed no significant difference in WM performance between the two diet groups, nor an interaction with COMT Val¹⁵⁸Met or Taq1A genotype. Neural activation in task-related brain areas also did not differ between diet groups. Independent of diet group, higher BMI was associated with lower overall accuracy on the WM task. This cross-sectional study does not provide evidence for diet-related differences in WM stability and flexibility in men, nor for a predisposition of COMT Val¹⁵⁸Met or Taq1A genotype to the hypothesized detrimental effects of an HFS diet. Previously reported associations of BMI with WM seem to be independent of HFS intake in our male study sample.

The changes in cognitive function following bariatric surgery considering the function of gut microbiome

Background

There is a correlation between gut microbiota and cognitive function. The mechanisms and pathways explain why the incidence of Alzheimer's disease in subjects undergoing bariatric surgery is lower than in other people with obesity.

Methods

In this review article, we aim to discuss the association of obesity, cognitive impairment, and physiological changes after bariatric surgery.

Results

Bariatric surgery has a series of physiological benefits which may lead to an improvement in cognitive functions in individuals who are prone to later developing Alzheimer's disease. Also, taxonomical change in the gut microbiome profile provides a healthy condition for living with better levels of cognition without neuropathological damages in older ages.

Conclusion

It can be concluded that there is a possible correlation between cognitive dysfunction and increased risk of cognitive dysfunction in people with a BMI higher than 40 kg/m2. Bariatric surgery may increase neurotransmitters and improve the gut bacteria, leading to a significant reduction in the risk of Alzheimer's disease.

A Neuroeconomics Approach to Obesity

Obesity is a heterogeneous condition that is affected by physiological, behavioral, and environmental factors. Value-based decision making is a useful framework for integrating these factors at the individual level. The disciplines of behavioral economics and reinforcement learning provide tools for identifying specific cognitive and motivational processes that may contribute to the development and maintenance of obesity. Neuroeconomics complements these disciplines by studying the neural mechanisms underlying these processes. We surveyed recent literature on individual decision characteristics that are most frequently implicated in obesity: discounting the value of future outcomes, attitudes toward uncertainty, and learning from rewards and punishments. Our survey highlighted both consistent and inconsistent behavioral findings. These findings underscore the need to examine multiple processes within individuals to identify unique behavioral profiles associated with obesity. Such individual characterization will inform future studies on the neurobiology of obesity as well as the design of effective interventions that are individually tailored.

Parsing the link between reinforcement sensitivity theory and eating behavior: A systematic review

The Reinforcement Sensitivity Theory (RST) is a widely studied psychobiological model of personality. RST factors seem to influence eating behavior, but how these personality traits are associated with distinct features of eating behavior is still unclear. In the present systematic review, we analyzed the relationship between RST personality factors and eating behavior using a parsing approach in which BMI-related results, self-reported results, and behavioral results were distinguished. Our analysis revealed that reward and punishment sensitivity seem to correlate and influence distinct features of eating behavior. The association between BMI and RST factors was uncertain, but nonlinear associations between reward sensitivity and weight need further testing. Reward sensitivity was linked to most eating behavior phenotypes (e.g., emotional eating and restrained eating), but only punishment sensitivity was primarily correlated with eating pathology. Reward sensitivity was the main factor linked with reactivity to food stimuli on many behavioral measures. The neurobiological personality factors of RST offer parsimonious concepts to understand eating behavior outcomes and the differential relationships observed are useful to translational research.

Recovering Reliable Idiographic Biological Parameters from Noisy Behavioral Data: the Case of Basal Ganglia Indices in the Probabilistic Selection Task

Behavioral data, despite being a common index of cognitive activity, is under scrutiny for having poor reliability as a result of noise or lacking replications of reliable effects. Here, we argue that cognitive modeling can be used to enhance the test-retest reliability of the behavioral measures by recovering individual-level parameters from behavioral data. We tested this empirically with the Probabilistic Stimulus Selection (PSS) task, which is used to measure a participant’s sensitivity to positive or negative reinforcement. An analysis of 400,000 simulations from an Adaptive Control of Thought-Rational (ACT-R) model of this task showed that the poor reliability of the task is due to the instability of the end-estimates: because of the way the task works, the same participants might sometimes end up having apparently opposite scores. To recover the underlying interpretable parameters and enhance reliability, we used a Bayesian Maximum A Posteriori (MAP) procedure. We were able to obtain reliable parameters across sessions (intraclass correlation coefficient ≈ 0.5). A follow-up study on a modified version of the task also found the same pattern of results, with very poor test-retest reliability in behavior but moderate reliability in recovered parameters (intraclass correlation coefficient ≈ 0.4). Collectively, these results imply that this approach can further be used to provide superior measures in terms of reliability, and bring greater insights into individual differences.

Is the habit system altered in individuals with obesity? A systematic review

Habit-like eating behavior is repeatedly pointed to as a key cognitive mechanism contributing to the emergence and maintenance of obesity. Here, we conducted a systematic review of the literature to assess the existent behavioral evidence for the Habit Hypothesis for Overeating (HHO) which states that obesity is the consequence of an imbalance between the habit and goal-directed reward learning systems, leading to overconsumption of food. We found a total of 19 studies implementing a variety of experimental protocols (i.e., free operant paradigm, slips-of-action test, two-step task, Pavlovian-to-Instrumental paradigm, probabilistic learning task) and manipulations. Taken together, the studies on clinical (binge eating disorder) and non-clinical individuals with overweight or obesity do not support the HHO conclusively. While the scientific literature on HHO is still in its infancy, the heterogeneity of the extant studies makes it difficult to evaluate the degree of convergence of these findings. Uncovering the role of reward learning systems in eating behaviors might have a transformative impact on public health.

Reliance on model-based and model-free control in obesity

Consuming more energy than is expended may reflect a failure of control over eating behaviour in obesity. Behavioural control arises from a balance between two dissociable strategies of reinforcement learning: model-free and model-based. We hypothesized that weight status relates to an imbalance in reliance on model-based and model-free control, and that it may do so in a linear or quadratic manner. To test this, 90 healthy participants in a wide BMI range [normal-weight (n = 31), overweight (n = 29), obese (n = 30)] performed a sequential decision-making task. The primary analysis indicated that obese participants relied less on model-based control than overweight and normal-weight participants, with no difference between overweight and normal-weight participants. In line, secondary continuous analyses revealed a negative linear, but not quadratic, relationship between BMI and model-based control. Computational modelling of choice behaviour suggested that a mixture of both strategies was shifted towards less model-based control in obese participants. Our findings suggest that obesity may indeed be related to an imbalance in behavioural control as expressed in a phenotype of less model-based control potentially resulting from enhanced reliance on model-free computations.

Preliminary evidence for an association between intake of high-fat high-sugar diet, variations in peripheral dopamine precursor availability and dopamine-dependent cognition in humans

Obesity is associated with alterations in dopaminergic transmission and cognitive function. Rodent studies suggest that diets rich in saturated fat and refined sugars (HFS), as opposed to diets diets low in saturated fat and refined sugars (LFS), change the dopamine system independent of excessive body weight. However, the impact of HFS on the human brain has not been investigated. Here, we compared the effect of dietary dopamine depletion on dopamine-dependent cognitive task performance between two groups differing in habitual intake of dietary fat and sugar. Specifically, we used a double-blind within-subject cross-over design to compare the effect of acute phenylalanine/tyrosine depletion on a reinforcement learning and a working memory task, in two groups that are on opposite ends of the spectrum of self-reported HFS intake (low vs high intake: LFS vs HFS group). We tested 31 healthy young women matched for body mass index (mostly normal weight to overweight) and IQ. Depletion of peripheral precursors of dopamine reduced the working memory specific performance on the operation span task in the LFS, but not in the HFS group (P = 0.016). Learning from positive- and negative-reinforcement (probabilistic selection task) was increased in both diet groups after dopamine depletion (P = 0.049). As a secondary exploratory research question, we measured peripheral dopamine precursor availability (pDAP) at baseline as an estimate for central dopamine levels. The HFS group had a significantly higher pDAP at baseline compared to the LFS group (P = 0.025). Our data provide the first evidence indicating that the intake of HFS is associated with changes in dopamine precursor availability, which is suggestive of changes in central dopamine levels in humans. The observed associations are present in a sample of normal to overweight participants (ie, in the absence of obesity), suggesting that the consumption of a HFS might already be associated with altered behaviours. Alternatively, the effects of HFS diet and obesity might be independent.

Dopaminergic modulation of the exploration/exploitation trade-off in human decision-making

Involvement of dopamine in regulating exploration during decision-making has long been hypothesized, but direct causal evidence in humans is still lacking. Here, we use a combination of computational modeling, pharmacological intervention and functional magnetic resonance imaging to address this issue. Thirty-one healthy male participants performed a restless four-armed bandit task in a within-subjects design under three drug conditions: 150 mg of the dopamine precursor L-dopa, 2 mg of the D2 receptor antagonist haloperidol, and placebo. Choices were best explained by an extension of an established Bayesian learning model accounting for perseveration, directed exploration and random exploration. Modeling revealed attenuated directed exploration under L-dopa, while neural signatures of exploration, exploitation and prediction error were unaffected. Instead, L-dopa attenuated neural representations of overall uncertainty in insula and dorsal anterior cingulate cortex. Our results highlight the computational role of these regions in exploration and suggest that dopamine modulates how this circuit tracks accumulating uncertainty during decision-making.

Enhanced Go and NoGo Learning in Individuals With Obesity

Overeating in individuals with obesity is hypothesized to be partly caused by automatic action tendencies to food cues that have the potential to override goal-directed dietary restriction. Individuals with obesity are often characterized by alterations in the processing of such rewarding food, but also of non-food stimuli, and previous research has suggested a stronger impact on the execution of goal-directed actions in obesity. Here, we investigated whether Pavlovian cues can also corrupt the learning of new approach or withdrawal behavior in individuals with obesity. We employed a probabilistic Pavlovian-instrumental learning paradigm in which participants (29 normal-weight and 29 obese) learned to actively respond (Go learning) or withhold a response (NoGo learning) in order to gain monetary rewards or avoid losses. Participants were better at learning active approach responses (Go) in the light of anticipated rewards and at learning to withhold a response (NoGo) in the light of imminent punishments. Importantly, there was no evidence for a stronger corruption of instrumental learning in individuals with obesity. Instead, they showed better learning across conditions than normal-weight participants. Using a computational reinforcement learning model, we additionally found an increased learning rate in individuals with obesity. Previous studies have mostly reported a lower reinforcement learning performance in individuals with obesity. Our results contradict this and suggest that their performance is not universally impaired: Instead, while previous studies found reduced stimulus-value learning, individuals with obesity may show better action-value learning. Our findings highlight the need for a broader investigation of behavioral adaptation in obesity across different task designs and types of reinforcement learning.

The Effect of Combined Aerobic Exercise and Calorie Restriction on Mood, Cognition, and Motor Behavior in Overweight and Obese Women

BACKGROUND

The benefits of weight loss programs on mood, cognitive, and motor behavior are largely limited to those of calorie restriction or exercise alone. Our aim was to investigate the effect of combined calorie restriction and aerobic exercise intervention on mood, brain activity, and cognitive and motor behavior in overweight and obese women.

METHODS

Participants aged 36-56 years were randomized to either a control or an experimental group (aerobic exercise + 12.5% energy intake reduction) for a 6-month period. Changes in brain-derived neurotrophic factor levels, mood, prefrontal cortex activity, cognitive and motor performance were assessed.

RESULTS

Confusion and depression increased in the control group (P < .05), whereas tension decreased in the experimental group (P < .05). Brain-derived neurotrophic factor level and learning of a speed-accuracy task remained unchanged. Although prefrontal cortex activity and executive functions were not affected, the reaction time of visual scanning and associative learning were improved in the experimental group (P < .05). An improvement in reaction time during the speed-accuracy task was observed (P < .05).

CONCLUSION

Combined calorie restriction and aerobic exercise intervention improved the psychosocial state, had little impact on cognition, and no effect on brain activity and learning of the speed-accuracy task.

Neuroendocrinological mechanisms underlying impulsive and compulsive behaviors in obesity: a narrative review of fMRI studies

Impulsivity and compulsivity are multidimensional constructs that are increasingly considered determinants of obesity. Studies using functional magnetic resonance imaging (fMRI) have provided insight on how differences in brain response during tasks exploring facets of impulsivity and compulsivity relate to the ingestive behaviors that support the etiology and maintenance of obesity. In this narrative review, we provide an overview of neuroimaging studies exploring impulsivity and compulsivity factors as they relate to weight status. Special focus will be placed on studies examining the impulsivity-related dimensions of attentional bias, delayed gratification and emotion regulation. Discussions of compulsivity within the context of obesity will be restricted to fMRI studies investigating habit formation and response flexibility under shifting contingencies. Further, we will highlight neuroimaging research demonstrating how alterations in neuroendocrine functioning are linked to excessive food intake and may serve as a driver of the impulsive and compulsive behaviors observed in obesity. Research on the associations between brain response with neuroendocrine factors, such as insulin, peptide YY (PYY), leptin, ghrelin and glucagon-like peptide 1 (GLP-1), will be reviewed.

The impact of elevated body mass on brain responses during appetitive prediction error in postpartum women

Repeated exposure to highly palatable foods and elevated weight promote: 1) insensitivity to punishment in striatal regions and, 2) increased willingness to work for food. We hypothesized that BMI would be positively associated with negative prediction error BOLD response in the occipital cortex. Additionally, we postulated that food reinforcement value would be negatively associated with negative prediction error BOLD response in the orbital frontal cortex and amygdala. Postpartum women (n = 47; BMI = 25.5 ± 5.1) were 'trained' to associate specific cues paired to either a highly palatable milkshake or a sub-palatable milkshake. We then violated these cue-taste pairings in 40% of the trials by showing a palatable cue followed by the sub-palatable taste (negative prediction error). Contrary to our hypotheses, during negative prediction error (mismatched cue-taste) versus matched palatable cue-taste, women showed increased BOLD response in the central operculum (pFWE = 0.002; k = 1680; MNI: -57, -7,14) and postcentral gyrus (pFWE = 0.006, k = 1219; MNI: 62, -8,18). When comparing the matched sub-palatable cue-taste to the negative prediction error trials, BOLD response increased in the postcentral gyrus (r = -0.60, pFWE = 0.008), putamen (r = -0.55, pFWE = 0.02), and insula (r = -0.50, pFWE = 0.01). Similarly, viewing the palatable cue vs sub-palatable cue was related to BOLD response in the putamen (pFWE = 0.025, k = 53; MNI: -20, 6, -8) and the insula (pFWE = 0.04, k = 19, MNI:38, -12, -6). Neither BMI at 6-month postpartum nor food reinforcement value was related to BOLD response. The insula and putamen appear to encode for visual food cue processing, and the gustatory and somatosensory cortices appear to encode negative prediction errors. Differential response in the somatosensory cortex to the matched cue-taste pairs to negative prediction error may indicate that a palatable cue may dull aversive qualities in the stimulus.

Health, pleasure, and fullness: changing mindset affects brain responses and portion size selection in adults with overweight and obesity

BACKGROUND

Increased portion size is an essential contributor to the current obesity epidemic. The decision of how much to eat before a meal begins (i.e. pre-meal planning), and the attention assigned to this task, plays a vital role in our portion control.

OBJECTIVE

We investigated whether pre-meal planning can be influenced by a shift in mindset in individuals with overweight and obesity in order to influence portion size selection and brain activity.

DESIGN

We investigated the neural underpinnings of pre-meal planning in 36 adults of different weight groups (BMI < 25 kg/m² and BMI ≥ 25 kg/m²) by means of functional magnetic resonance imaging. To examine the important role of attentional focus, participants were instructed to focus their mindset on the health effects of food, expected pleasure, or their intention to stay full until dinnertime, while choosing their portion size for lunch.

RESULTS

We observed that participants of all weight groups reduced their portion size when adopting a health mindset, which was accompanied by enhanced activation of the self-control network (i.e. left prefrontal cortex). Fullness and pleasure mindsets resulted in contrasting reward responses in individuals with overweight and obesity compared to normal-weight individuals. Under the pleasure mindset, persons with overweight and obesity showed heightened activity in parts of the taste cortex (i.e. right frontal operculum), while the fullness mindset caused reduced activation in the ventral striatum, an important component of the reward system. Moreover, participants with overweight and obesity did not modify their behaviour under the pleasure mindset and selected larger portions than the normal-weight group.

CONCLUSIONS

We were able to identify specific brain response patterns as participants made a final choice of a portion size. The results demonstrate that different brain responses and behaviours during pre-meal planning can inform the development of effective strategies for healthy weight management.

Altered monetary loss processing and reinforcement-based learning in individuals with obesity

Individuals with obesity are often characterized by alterations in reward processing. This may affect how new information is used to update stimulus values during reinforcement-based learning. Here, we investigated obesity-related changes in non-food reinforcement processing, their impact on learning performance as well as the neural underpinnings of reinforcement-based learning in obesity. Nineteen individuals with obesity (BMI > = 30 kg/m², 10 female) and 23 lean control participants (BMI 18.5–24.9 kg/m², 11 female) performed a probabilistic learning task during functional magnetic resonance imaging (fMRI), in which they learned to choose between advantageous and disadvantageous choice options in separate monetary gain, loss, and neutral conditions. During learning individuals with obesity made a significantly lower number of correct choices and accumulated a significantly lower overall monetary outcome than lean control participants. FMRI analyses revealed aberrant medial prefrontal cortex responses to monetary losses in individuals with obesity. There were no significant group differences in the regional representation of prediction errors. However, we found evidence for increased functional connectivity between the ventral striatum and insula in individuals with obesity. The present results suggest that obesity is associated with aberrant value representations for monetary losses, alterations in functional connectivity during the processing of learning outcomes, as well as a decresased reinforcement-based learning performance. This may affect how new information is incorporated to adjust dysfunctional behavior and could be a factor contributing to the maintenance of dysfunctional eating behavior in obesity.

Greater mindful eating practice is associated with better reversal learning

Mindfulness-based interventions are thought to reduce compulsive behavior such as overeating by promoting behavioral flexibility. Here the main aim was to provide support for mindfulness-mediated improvements in reversal learning, a direct measure of behavioral flexibility. We investigated whether an 8-week mindful eating intervention improved outcome-based reversal learning relative to an educational cooking (i.e., active control) intervention in a non-clinical population. Sixty-five healthy participants with a wide BMI range (19–35 kg/m²), who were motivated to change their eating habits, performed a deterministic reversal learning task that enabled the investigation of reward- and punishment-based reversal learning at baseline and following the intervention. No group differences in reversal learning were observed. However, time invested in the mindful eating, but not the educational cooking intervention correlated positively with changes in reversal learning, in a manner independent of outcome valence. These findings suggest that greater amount of mindfulness practice can lead to increased behavioral flexibility, which, in turn, might help overcome compulsive eating in clinical populations.

Cardiac Concomitants of Feedback and Prediction Error Processing in Reinforcement Learning

Successful learning hinges on the evaluation of positive and negative feedback. We assessed differential learning from reward and punishment in a monetary reinforcement learning paradigm, together with cardiac concomitants of positive and negative feedback processing. On the behavioral level, learning from reward resulted in more advantageous behavior than learning from punishment, suggesting a differential impact of reward and punishment on successful feedback-based learning. On the autonomic level, learning and feedback processing were closely mirrored by phasic cardiac responses on a trial-by-trial basis: (1) Negative feedback was accompanied by faster and prolonged heart rate deceleration compared to positive feedback. (2) Cardiac responses shifted from feedback presentation at the beginning of learning to stimulus presentation later on. (3) Most importantly, the strength of phasic cardiac responses to the presentation of feedback correlated with the strength of prediction error signals that alert the learner to the necessity for behavioral adaptation. Considering participants' weight status and gender revealed obesity-related deficits in learning to avoid negative consequences and less consistent behavioral adaptation in women compared to men. In sum, our results provide strong new evidence for the notion that during learning phasic cardiac responses reflect an internal value and feedback monitoring system that is sensitive to the violation of performance-based expectations. Moreover, inter-individual differences in weight status and gender may affect both behavioral and autonomic responses in reinforcement-based learning.