Impaired Flexible Reward-Based Decision-Making in Binge Eating Disorder: Evidence from Computational Modeling and Functional Neuroimaging

Relevance of Probabilistic Reversal Learning for Adolescent Drinking Trajectories

One of the many human capabilities acquired during adolescence is the adaptivity in changing environments. In this longitudinal study, we investigated this adaptivity, as measured by probabilistic reversal learning (PReL) tasks, in N = 143 adolescents at ages 14, 16 and 18. Computational modelling and functional magnetic resonance imaging were applied to identify the neurocognitive processes underlying reversal learning and its development. Previous studies have demonstrated a correlation between heavy alcohol use and impaired reversal learning. Our hypothesis was that PReL is negatively associated with current and future alcohol use and that alcohol use impairs PReL by altering neurocognitive processes. Behaviourally, PReL performance improved, which was associated with a lower probability of switching choices and was considered an adaptive process. Computationally, this was accounted for by higher learning rates, enhanced sensitivity to wins and reduced sensitivity to losses in older adolescents. Alcohol consumption increased but remained at a low level for most participants. More risky drinking was associated with less medial frontal activity elicited by reward prediction errors. These findings suggest that reversal learning may be more relevant for the maintenance or escalation of risky than for low-level drinking. Challenges and potential solutions for longitudinal studies such as reliability are discussed.

A Computational Account of the Development and Evolution of Psychotic Symptoms

The mechanisms of psychotic symptoms such as hallucinations and delusions are often investigated in fully formed illness, well after symptoms emerge. These investigations have yielded key insights but are not well positioned to reveal the dynamic forces underlying symptom formation itself. Understanding symptom development over time would allow us to identify steps in the pathophysiological process leading to psychosis, shifting the focus of psychiatric intervention from symptom alleviation to prevention. We propose a model for understanding the emergence of psychotic symptoms within the context of an adaptive, developing neural system. We make the case for a pathophysiological process that begins with cortical hyperexcitability and bottom-up noise transmission, which engenders inappropriate belief formation via aberrant prediction error signaling. We argue that this bottom-up noise drives learning about the (im)precision of new incoming sensory information because of diminished signal-to-noise ratio, causing a compensatory relative overreliance on prior beliefs. This overreliance on priors predisposes to hallucinations and covaries with hallucination severity. An overreliance on priors may also lead to increased conviction in the beliefs generated by bottom-up noise and drive movement toward conversion to psychosis. We identify predictions of our model at each stage, examine evidence to support or refute those predictions, and propose experiments that could falsify or help select between alternative elements of the overall model. Nesting computational abnormalities within longitudinal development allows us to account for hidden dynamics among the mechanisms driving symptom formation and to view established symptoms as a point of equilibrium among competing biological forces.

Psychoneurological Links Contributing to Body Mass Index and Eating Disorder Severity

BACKGROUND-OBJECTIVES

Multiple dynamic interacting factors contribute to the presence and progression of eating disorders (ED). Empirical research has provided mixed findings regarding the mechanisms explaining the contribution of body mass index (BMI) to the diverse ED endophenotypes. The present study aims to evaluate the underlying processes (direct and indirect effects) contributing to BMI and ED severity, considering the contribution of multiple neuropsychological constructs.

METHOD

Path analysis, implemented through structural equation models (SEM), was applied to a sample of N = 193 ED patients, men and women, aged 17 to 50 years old, and diagnosed with bulimia nervosa, night eating syndrome, binge eating disorder, and other specified feeding.

RESULTS

BMI was directly associated with ED severity level. The ED symptom level was also a mediational link into the relationship between BMI with emotion regulation strategies, decision-making capacity, stress levels, and impulsiveness. Multigroup SEM revealed invariance of the structural coefficients by sex, but differences according to the ED subtype.

CONCLUSIONS

This study provides new empirical evidence on predictors of ED severity, focusing on the role of impaired decision-making and BMI. Our results could contribute to new intervention plans with techniques specifically aimed at improving emotional regulation capacity, decreasing impulsivity levels, and improving reasoning skills. Nutrition education plans may also play a key role for preventing the onset and progression of ED, helping patients understand how food affects their physical and emotional health and how to manage anxiety and fears related to food.

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.

Decrease in decision noise from adolescence into adulthood mediates an increase in more sophisticated choice behaviors and performance gain

Learning and decision-making undergo substantial developmental changes, with adolescence being a particular vulnerable window of opportunity. In adolescents, developmental changes in specific choice behaviors have been observed (e.g., goal-directed behavior, motivational influences over choice). Elevated levels of decision noise, i.e., choosing suboptimal options, were reported consistently in adolescents. However, it remains unknown whether these observations, the development of specific and more sophisticated choice processes and higher decision noise, are independent or related. It is conceivable, but has not yet been investigated, that the development of specific choice processes might be impacted by age-dependent changes in decision noise. To answer this, we examined 93 participants (12 to 42 years) who completed 3 reinforcement learning (RL) tasks: a motivational Go/NoGo task assessing motivational influences over choices, a reversal learning task capturing adaptive decision-making in response to environmental changes, and a sequential choice task measuring goal-directed behavior. This allowed testing of (1) cross-task generalization of computational parameters focusing on decision noise; and (2) assessment of mediation effects of noise on specific choice behaviors. Firstly, we found only noise levels to be strongly correlated across RL tasks. Second, and critically, noise levels mediated age-dependent increases in more sophisticated choice behaviors and performance gain. Our findings provide novel insights into the computational processes underlying developmental changes in decision-making: namely a vital role of seemingly unspecific changes in noise in the specific development of more complex choice components. Studying the neurocomputational mechanisms of how varying levels of noise impact distinct aspects of learning and decision processes may also be key to better understand the developmental onset of psychiatric diseases.

The explore/exploit trade-off: An ecologically valid and translational framework that can advance mechanistic understanding of eating disorders

The explore/exploit trade-off is a decision-making process that is conserved across species and balances exploring unfamiliar choices of unknown value with choosing familiar options of known value to maximize reward. This framework is rooted in behavioral ecology and has traditionally been used to study maladaptive versus adaptive non-human animal foraging behavior. Researchers have begun to recognize the potential utility of understanding human decision-making and psychopathology through the explore/exploit trade-off. In this article, we propose that explore/exploit trade-off holds promise for advancing our mechanistic understanding of decision-making processes that confer vulnerability for and maintain eating pathology due to its neurodevelopmental bases, conservation across species, and ability to be mathematically modeled. We present a model for how suboptimal explore/exploit decision-making can promote disordered eating and present recommendations for future research applying this framework to eating pathology. Taken together, the explore/exploit trade-off provides a translational framework for expanding etiologic and maintenance models of eating pathology, given developmental changes in explore/exploit decision-making that coincide in time with the emergence of eating pathology and evidence of biased explore/exploit decision-making in psychopathology. Additionally, understanding explore/exploit decision-making in eating disorders may improve knowledge of their underlying pathophysiology, informing targeted clinical interventions such as neuromodulation and pharmacotherapy. PUBLIC SIGNIFICANCE STATEMENT: The explore/exploit trade-off is a cross-species decision-making process whereby organisms choose between a known option with a known reward or sampling unfamiliar options. We hypothesize that imbalanced explore/exploit decision-making can promote disordered eating and present preliminary data. We propose that explore/exploit trade-off has significant potential to advance understanding of the neurocognitive and neurodevelopmental mechanisms of eating pathology, which could ultimately guide revisions of etiologic models and inform novel interventions.

A computational account of the development and evolution of psychotic symptoms

The mechanisms of psychotic symptoms like hallucinations and delusions are often investigated in fully-formed illness, well after symptoms emerge. These investigations have yielded key insights, but are not well-positioned to reveal the dynamic forces underlying symptom formation itself. Understanding symptom development over time would allow us to identify steps in the pathophysiological process leading to psychosis, shifting the focus of psychiatric intervention from symptom alleviation to prevention. We propose a model for understanding the emergence of psychotic symptoms within the context of an adaptive, developing neural system. We will make the case for a pathophysiological process that begins with cortical hyperexcitability and bottom-up noise transmission, which engenders inappropriate belief formation via aberrant prediction error signaling. We will argue that this bottom-up noise drives learning about the (im)precision of new incoming sensory information because of diminished signal-to-noise ratio, causing an adaptive relative over-reliance on prior beliefs. This over-reliance on priors predisposes to hallucinations and covaries with hallucination severity. An over-reliance on priors may also lead to increased conviction in the beliefs generated by bottom-up noise and drive movement toward conversion to psychosis. We will identify predictions of our model at each stage, examine evidence to support or refute those predictions, and propose experiments that could falsify or help select between alternative elements of the overall model. Nesting computational abnormalities within longitudinal development allows us to account for hidden dynamics among the mechanisms driving symptom formation and to view established symptomatology as a point of equilibrium among competing biological forces.

Impaired flexible reward learning in ADHD patients is associated with blunted reinforcement sensitivity and neural signals in ventral striatum and parietal cortex

Reward-based learning and decision-making are prime candidates to understand symptoms of attention deficit hyperactivity disorder (ADHD). However, only limited evidence is available regarding the neurocomputational underpinnings of the alterations seen in ADHD. This concerns flexible behavioral adaption in dynamically changing environments, which is challenging for individuals with ADHD. One previous study points to elevated choice switching in adolescent ADHD, which was accompanied by disrupted learning signals in medial prefrontal cortex. Here, we investigated young adults with ADHD (n = 17) as compared to age- and sex-matched controls (n = 17) using a probabilistic reversal learning experiment during functional magnetic resonance imaging (fMRI). The task requires continuous learning to guide flexible behavioral adaptation to changing reward contingencies. To disentangle the neurocomputational underpinnings of the behavioral data, we used reinforcement learning (RL) models, which informed the analysis of fMRI data. ADHD patients performed worse than controls particularly in trials before reversals, i.e., when reward contingencies were stable. This pattern resulted from 'noisy' choice switching regardless of previous feedback. RL modelling showed decreased reinforcement sensitivity and enhanced learning rates for negative feedback in ADHD patients. At the neural level, this was reflected in a diminished representation of choice probability in the left posterior parietal cortex in ADHD. Moreover, modelling showed a marginal reduction of learning about the unchosen option, which was paralleled by a marginal reduction in learning signals incorporating the unchosen option in the left ventral striatum. Taken together, we show that impaired flexible behavior in ADHD is due to excessive choice switching ('hyper-flexibility'), which can be detrimental or beneficial depending on the learning environment. Computationally, this resulted from blunted sensitivity to reinforcement of which we detected neural correlates in the attention-control network, specifically in the parietal cortex. These neurocomputational findings remain preliminary due to the relatively small sample size.

Striatal correlates of Bayesian beliefs in self-efficacy in adolescents and their relation to mood and autonomy: a pilot study

Major depressive disorder often originates in adolescence and is associated with long-term functional impairment. Mechanistically characterizing this heterogeneous illness could provide important leads for optimizing treatment. Importantly, reward learning is known to be disrupted in depression. In this pilot fMRI study of 21 adolescents (16-20 years), we assessed how reward network disruption impacts specifically on Bayesian belief representations of self-efficacy (SE-B) and their associated uncertainty (SE-U), using a modified instrumental learning task probing activation induced by the opportunity to choose, and an optimal Hierarchical Gaussian Filter computational model. SE-U engaged caudate, nucleus accumbens (NAcc), precuneus, posterior parietal and dorsolateral prefrontal cortex (PFWE < 0.005). Sparse partial least squares analysis identified SE-U striatal activation as associating with one's sense of perceived choice and depressive symptoms, particularly anhedonia and negative feelings about oneself. As Bayesian uncertainty modulates belief flexibility and their capacity to steer future actions, this suggests that these striatal signals may be informative developmentally, longitudinally and in assessing response to treatment.

Back to the future: Progressing memory research in eating disorders

OBJECTIVE

Human behaviors, thoughts, and emotions are guided by memories of the past. Thus, there can be little doubt that memory plays a fundamental role in the behaviors (e.g., binging), thoughts (e.g., body-image concerns), and emotions (e.g., guilt) that characterize eating disorders (EDs). Although a growing body of research has begun to investigate the role of memory in EDs, this literature is limited in numerous ways and has yet to be integrated into an overarching framework.

METHODS

In the present article, we provide an operational framework for characterizing different domains of memory, briefly review existing ED memory research within this framework, and highlight crucial gaps in the literature.

RESULTS

We distinguish between three domains of memory-episodic, procedural, and working-which differ based on functional attributes and underlying neural systems. Most recent ED memory research has focused on procedural memory broadly defined (e.g., reinforcement learning), and findings within all three memory domains are highly mixed. Further, few studies have attempted to assess these different domains simultaneously, though most behavior is achieved through coordination and competition between memory systems. We, therefore, offer recommendations for how to move ED research forward within each domain of memory and how to study the interactions between memory systems, using illustrative examples from other areas of basic and clinical research.

DISCUSSION

A stronger and more integrated understanding of the mechanisms that connect memory of past experiences to present ED behavior may yield more comprehensive theoretical models of EDs that guide novel treatment approaches.

PUBLIC SIGNIFICANCE

Memories of previous eating-related experiences may contribute to the onset and maintenance of eating disorders (EDs). However, research on the role of memory in EDs is limited, and distinct domains of ED memory research are rarely connected. We, therefore, offer a framework for organizing, progressing, and integrating ED memory research, to provide a better foundation for improving ED treatment and intervention going forward.

Dysfunctional decision-making in binge-eating disorder: A meta-analysis and systematic review

Binge-Eating Disorder (BED) involves anticipatory craving and urges, subjective loss-of-control during binge-eating episodes, and post-feeding psychological distress and guilt. Evidence indicates neurocognitive dysfunctions contribute to BED onset, maintenance, and treatment response. However, an integrated understanding of how cognitive processes underpin BED symptomology is lacking. We utilised a multi-stage decision-making model defining ten cognitive processes underpinning Preference Formation, Choice Implementation, Feedback Processing, and Flexibility/Shifting, to comprehensively review research published since 2013. We used preregistered PICOS criteria to assess 1966 articles identified from PubMed, PsycInfo, and Scopus database searches. This yielded 50 studies reporting behavioural cognitive tasks outcomes, comparing individuals with BED to controls with normal and higher weight. Meta-analyses revealed a unique profile of cognitive dysfunctions that spanned all decision-making stages. Significant deficits were evident in Uncertainty Evaluation, Attentional Inhibition, Choice Consistency, and Cognitive Flexibility/Set-shifting. We propose a novel model of dysfunctional decision-making processes in BED and describe their role in binge-eating behaviour. We further highlight the potential for cognitive interventions to target these processes and address the significant treatment gap in BED.

Integrating aspects of affect, reward, and cognition to develop more comprehensive models of binge-eating pathology

Reward-related processes are an increasing focus of eating disorders research. Although evidence suggests that numerous distinct reward processes may contribute to eating pathology (e.g., reward learning and delay discounting), existing etiological models of reward dysfunction tend to focus on only a limited number of reward processes, and frequently lack specificity when identifying the individual reward processes hypothesized to contribute to dysregulated eating behavior. Moreover, existing theories have been limited in their integration of reward-related processes with other demonstrated risk and maintenance factors for eating disorders (e.g., affect and cognition), potentially contributing to underdeveloped models of eating pathology. In this article, we highlight five distinct reward processes with theorized or demonstrated relevance to eating disorders involving binge-eating, followed by a review of two well-established risk/maintenance factors for binge-eating pathology. We then introduce two novel models of binge eating onset and maintenance that integrate these factors (i.e., the Affect, Reward, Cognition models), and discuss methods for testing each of the models in future research. Ultimately, we hope that the proposed models provide a springboard for the continued evolution of more precise and comprehensive theories of reward dysfunction in the eating disorders, as well as the development of novel intervention approaches. PUBLIC SIGNIFICANCE STATEMENT: Eating disorders are associated with abnormalities in multiple domains of reward functioning. However, models of reward dysfunction within the eating disorders have not been well-integrated with prominent models of affect and cognition. This article presents two novel models of onset and maintenance for binge-eating pathology, which attempt to integrate observed reward abnormalities with other affective and cognitive processes implicated in binge-type eating disorders.

Binge-Eating Precursors in Children and Adolescents: Neurodevelopment, and the Potential Contribution of Ultra-Processed Foods

Binge-eating disorder (BED) is a highly prevalent disorder. Subthreshold BED conditions (sBED) are even more frequent in youth, but their significance regarding BED etiology and long-term prognosis is unclear. A better understanding of brain findings associated with BED and sBED, in the context of critical periods for neurodevelopment, is relevant to answer such questions. The present narrative review starts from the knowledge of the development of emotional self-regulation in youth, and the brain circuits supporting emotion-regulation and eating behaviour. Next, neuroimaging studies with sBED and BED samples will be reviewed, and their brain-circuitry overlap will be examined. Deficits in inhibition control systems are observed to precede, and hyperactivity of reward regions to characterize, sBED, with overlapping findings in BED. The imbalance between reward/inhibition systems, and the implication of interoception/homeostatic processing brain systems should be further examined. Recent knowledge of the potential impact that the high consumption of ultra-processed foods in paediatric samples may have on these sBED/BED-associated brain systems is then discussed. There is a need to identify, early on, those sBED individuals at risk of developing BED at neurodevelopmental stages when there is a great possibility of prevention. However, more neuroimaging studies with sBED/BED pediatric samples are needed.

Decision-making difficulties mediate the association between poor emotion regulation and eating disorder symptoms in adolescence

BACKGROUND

The emergence of eating problems during childhood increases the risk for eating disorders (EDs) during young adulthood. Previous studies highlight a relationship between poor self-regulation and onset of eating pathology. In this study, we investigated whether this association is mediated by decision-making difficulties.

METHODS

To test this hypothesis, we used data from the Millennium Cohort Study. Decision-making performance was assessed with the Cambridge Gambling Task at age 11. Principal components analysis was used to derive an index of ED symptoms at age 14. The trajectories of scores of two subscales of the Child Social Behaviour Questionnaire, Independence and Self-Regulation (ISR) and Emotional Dysregulation (EmotDy), were modelled from ages 3 to 7 years in a latent growth curve analysis. The individual predicted values of the intercept (set at baseline, 3 years) and the slope (rate of annual change) were then used in the mediation analysis.

RESULTS

In our sample of 11 303 individuals, there was evidence for mediation by three measures of decision-making at age 11 (poor quality of decision-making, delay aversion and low risk-adjustment) in the association between EmotDy across ages 3-7 and ED symptoms at age 14 even after the adjustment for relevant covariates. We found no evidence of association between ISR and ED symptoms.

CONCLUSION

Our findings suggest that emotion regulation processes during childhood may be relevant for the future onset of ED symptoms via their association with decision-making skills. These findings, obtained from a large, representative, sample, shed light on the relationship between self-regulation, decision-making and symptoms of EDs.

Computational models of behavioral addictions: State of the art and future directions

Non-pharmacological behavioral addictions, such as pathological gambling, videogaming, social networking, or internet use, are becoming major public health concerns. It is not yet clear how behavioral addictions could share many major neurobiological and behavioral characteristics with substance use disorders, despite the absence of direct pharmacological influences. A deeper understanding of the neurocognitive mechanisms of addictive behavior is needed, and computational modeling could be one promising approach to explain intricately entwined cognitive and neural dynamics. This review describes computational models of addiction based on reinforcement learning algorithms, Bayesian inference, and biophysical neural simulations. We discuss whether computational frameworks originally conceived to explain maladaptive behavior in substance use disorders can be effectively extended to non-substance-related behavioral addictions. Moreover, we introduce recent studies on behavioral addictions that exemplify the possibility of such extension and propose future directions.

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.

Diminished reinforcement sensitivity in adolescence is associated with enhanced response switching and reduced coding of choice probability in the medial frontal pole

Precisely charting the maturation of core neurocognitive functions such as reinforcement learning (RL) and flexible adaptation to changing action-outcome contingencies is key for developmental neuroscience and adjacent fields like developmental psychiatry. However, research in this area is both sparse and conflicted, especially regarding potentially asymmetric development of learning for different motives (obtain wins vs avoid losses) and learning from valenced feedback (positive vs negative). In the current study, we investigated the development of RL from adolescence to adulthood, using a probabilistic reversal learning task modified to experimentally separate motivational context and feedback valence, in a sample of 95 healthy participants between 12 and 45. We show that adolescence is characterized by enhanced novelty seeking and response shifting especially after negative feedback, which leads to poorer returns when reward contingencies are stable. Computationally, this is accounted for by reduced impact of positive feedback on behavior. We also show, using fMRI, that activity of the medial frontopolar cortex reflecting choice probability is attenuated in adolescence. We argue that this can be interpreted as reflecting diminished confidence in upcoming choices. Interestingly, we find no age-related differences between learning in win and loss contexts.

Acute stress alters probabilistic reversal learning in healthy male adults

Behavioural adaptation is a fundamental cognitive ability, ensuring survival by allowing for flexible adjustment to changing environments. In laboratory settings, behavioural adaptation can be measured with reversal learning paradigms requiring agents to adjust reward learning to stimulus-action-outcome contingency changes. Stress is found to alter flexibility of reward learning, but effect directionality is mixed across studies. Here, we used model-based functional MRI (fMRI) in a within-subjects design to investigate the effect of acute psychosocial stress on flexible behavioural adaptation. Healthy male volunteers (n = 28) did a reversal learning task during fMRI in two sessions, once after the Trier Social Stress Test (TSST), a validated psychosocial stress induction method, and once after a control condition. Stress effects on choice behaviour were investigated using multilevel generalized linear models and computational models describing different learning processes that potentially generated the data. Computational models were fitted using a hierarchical Bayesian approach, and model-derived reward prediction errors (RPE) were used as fMRI regressors. We found that acute psychosocial stress slightly increased correct response rates. Model comparison revealed that double-update learning with altered choice temperature under stress best explained the observed behaviour. In the brain, model-derived RPEs were correlated with BOLD signals in striatum and ventromedial prefrontal cortex (vmPFC). Striatal RPE signals for win trials were stronger during stress compared with the control condition. Our study suggests that acute psychosocial stress could enhance reversal learning and RPE brain responses in healthy male participants and provides a starting point to explore these effects further in a more diverse population.

Dissociable feedback valence effects on frontal midline theta during reward gain versus threat avoidance learning

While frontal midline theta (FMθ) has been associated with threat processing, with cognitive control in the context of anxiety, and with reinforcement learning, most reinforcement learning studies on FMθ have used reward rather than threat-related stimuli as reinforcer. Accordingly, the role of FMθ in threat-related reinforcement learning is largely unknown. Here, n = 23 human participants underwent one reward-, and one punishment-, based reversal learning task, which differed only with regard to the kind of reinforcers that feedback was tied to (i.e., monetary gain vs. loud noise burst, respectively). In addition to single-trial EEG, we assessed single-trial feedback expectations based on both a reinforcement learning computational model and trial-by-trial subjective feedback expectation ratings. While participants' performance and feedback expectations were comparable between the reward and punishment tasks, FMθ was more reliably amplified to negative vs. positive feedback in the reward vs. punishment task. Regressions with feedback valence, computationally derived, and self-reported expectations as predictors and FMθ as criterion further revealed that trial-by-trial variations in FMθ specifically relate to reward-related feedback-valence and not to threat-related feedback or to violated expectations/prediction errors. These findings suggest that FMθ as measured in reinforcement learning tasks may be less sensitive to the processing of events with direct relevance for fear and anxiety.

Sufficient reliability of the behavioral and computational readouts of a probabilistic reversal learning task

Task-based measures that capture neurocognitive processes can help bridge the gap between brain and behavior. To transfer tasks to clinical application, reliability is a crucial benchmark because it imposes an upper bound to potential correlations with other variables (e.g., symptom or brain data). However, the reliability of many task readouts is low. In this study, we scrutinized the retest reliability of a probabilistic reversal learning task (PRLT) that is frequently used to characterize cognitive flexibility in psychiatric populations. We analyzed data from N = 40 healthy subjects, who completed the PRLT twice. We focused on how individual metrics are derived, i.e., whether data were partially pooled across participants and whether priors were used to inform estimates. We compared the reliability of the resulting indices across sessions, as well as the internal consistency of a selection of indices. We found good to excellent reliability for behavioral indices as derived from mixed-effects models that included data from both sessions. The internal consistency was good to excellent. For indices derived from computational modeling, we found excellent reliability when using hierarchical estimation with empirical priors and including data from both sessions. Our results indicate that the PRLT is well equipped to measure individual differences in cognitive flexibility in reinforcement learning. However, this depends heavily on hierarchical modeling of the longitudinal data (whether sessions are modeled separately or jointly), on estimation methods, and on the combination of parameters included in computational models. We discuss implications for the applicability of PRLT indices in psychiatric research and as diagnostic tools.

The effect of body image dissatisfaction on goal-directed decision making in a population marked by negative appearance beliefs and disordered eating

Eating disorders are associated with one of the highest mortality rates among all mental disorders, yet there is very little research about them within the newly emerging and promising field of computational psychiatry. As such, we focus on investigating a previously unexplored, yet core aspect of eating disorders-body image dissatisfaction. We continue a freshly opened debate about model-based learning and its trade-off against model-free learning-a proxy for goal-directed and habitual behaviour. We perform a behavioural study that utilises a two-step decision-making task and a reinforcement learning model to understand the effect of body image dissatisfaction on model-based learning in a population characterised by high scores of disordered eating and negative appearance beliefs, as recruited using Prolific. We find a significantly reduced model-based contribution in the body image dissatisfaction task condition in the population of interest as compared to a healthy control. This finding suggests general deficits in deliberate control in this population, leading to habitual, compulsive-like behaviours (body checking) dominating the experience. Importantly, the results may inform treatment approaches, which could focus on enhancing the reliance on goal-directed decision making to help cope with unwanted behaviours.

The neurobiological reward system and binge eating: A critical systematic review of neuroimaging studies

OBJECTIVE

Changes in reward processing are hypothesized to play a role in the onset and maintenance of binge eating (BE). However, despite an increasing number of studies investigating the neurobiological reward system in individuals who binge eat, no comprehensive systematic review exists on this topic. Therefore, this review has the following objectives: (1) identify structural and functional changes in the brain reward system, either during rest or while performing a task; and (2) formulate directions for future research.

METHODS

A search was conducted of articles published until March 31, 2022. Neuroimaging studies were eligible if they wanted to study the reward system and included a group of individuals who binge eat together with a comparator group. Their results were summarized in a narrative synthesis.

RESULTS

A total of 58 articles were included. At rest, individuals who binge eat displayed a lower striatal dopamine release, a change in the volume of the striatum, frontal cortex, and insula, as well as a lower frontostriatal connectivity. While performing a task, there was a higher activity of the brain reward system when anticipating or receiving food, more model-free reinforcement learning, and more habitual behavior. Most studies only included one patient group, used general reward-related measures, and did not evaluate the impact of comorbidities, illness duration, race, or sex.

DISCUSSION

Confirming previous hypotheses, this review finds structural and functional changes in the neurobiological reward system in BE. Future studies should compare disorders, use measures that are specific to BE, and investigate the impact of confounding factors.

PUBLIC SIGNIFICANCE STATEMENT

This systematic review finds that individuals who binge eat display structural and functional changes in the brain reward system. These changes could be related to a higher sensitivity to food, relying more on previous experiences when making decisions, and more habitual behavior. Future studies should use a task that is specific to binge eating, look across different patient groups, and investigate the impact of comorbidities, illness duration, race, and sex.

Revealing human sensitivity to a latent temporal structure of changes

Precisely timed behavior and accurate time perception plays a critical role in our everyday lives, as our wellbeing and even survival can depend on well-timed decisions. Although the temporal structure of the world around us is essential for human decision making, we know surprisingly little about how representation of temporal structure of our everyday environment impacts decision making. How does the representation of temporal structure affect our ability to generate well-timed decisions? Here we address this question by using a well-established dynamic probabilistic learning task. Using computational modeling, we found that human subjects' beliefs about temporal structure are reflected in their choices to either exploit their current knowledge or to explore novel options. The model-based analysis illustrates a large within-group and within-subject heterogeneity. To explain these results, we propose a normative model for how temporal structure is used in decision making, based on the semi-Markov formalism in the active inference framework. We discuss potential key applications of the presented approach to the fields of cognitive phenotyping and computational psychiatry.

Reinforcement learning with associative or discriminative generalization across states and actions: fMRI at 3 T and 7 T

The model-free algorithms of "reinforcement learning" (RL) have gained clout across disciplines, but so too have model-based alternatives. The present study emphasizes other dimensions of this model space in consideration of associative or discriminative generalization across states and actions. This "generalized reinforcement learning" (GRL) model, a frugal extension of RL, parsimoniously retains the single reward-prediction error (RPE), but the scope of learning goes beyond the experienced state and action. Instead, the generalized RPE is efficiently relayed for bidirectional counterfactual updating of value estimates for other representations. Aided by structural information but as an implicit rather than explicit cognitive map, GRL provided the most precise account of human behavior and individual differences in a reversal-learning task with hierarchical structure that encouraged inverse generalization across both states and actions. Reflecting inference that could be true, false (i.e., overgeneralization), or absent (i.e., undergeneralization), state generalization distinguished those who learned well more so than action generalization. With high-resolution high-field fMRI targeting the dopaminergic midbrain, the GRL model's RPE signals (alongside value and decision signals) were localized within not only the striatum but also the substantia nigra and the ventral tegmental area, including specific effects of generalization that also extend to the hippocampus. Factoring in generalization as a multidimensional process in value-based learning, these findings shed light on complexities that, while challenging classic RL, can still be resolved within the bounds of its core computations.

Computational Methods in Psychotherapy: A Scoping Review

BACKGROUND

The study of complex systems, such as the psychotherapeutic encounter, transcends the mechanistic and reductionist methods for describing linear processes and needs suitable approaches to describe probabilistic and scarcely predictable phenomena.

OBJECTIVE

The present study undertakes a scoping review of research on the computational methods in psychotherapy to gather new developments in this field and to better understand the phenomena occurring in psychotherapeutic interactions as well as in human interaction more generally.

DESIGN

Online databases were used to identify papers published 2011-2022, from which we selected 18 publications from different resources, selected according to criteria established in advance and described in the text. A flow chart and a summary table of the articles consulted have been created.

RESULTS

The majority of publications (44.4%) reported combined computational and experimental approaches, so we grouped the studies according to the types of computational methods used. All but one of the studies collected measured data. All the studies confirmed the usefulness of predictive and learning models in the study of complex variables such as those belonging to psychological, psychopathological and psychotherapeutic processes.

CONCLUSIONS

Research on computational methods will benefit from a careful selection of reference methods and standards. Therefore, this review represents an attempt to systematise the empirical literature on the applications of computational methods in psychotherapy research in order to offer clinicians an overview of the usefulness of these methods and the possibilities of their use in the various fields of application, highlighting their clinical implications, and ultimately attempting to identify potential opportunities for further research.

Characterizing cerebral metabolite profiles in anorexia and bulimia nervosa and their associations with habitual behavior

Anorexia nervosa (AN) and bulimia nervosa (BN) are associated with altered brain structure and function, as well as increased habitual behavior. This neurobehavioral profile may implicate neurochemical changes in the pathogenesis of these illnesses. Altered glutamate, myo-inositol and N-acetyl aspartate (NAA) concentrations are reported in restrictive AN, yet whether these extend to binge-eating disorders, or relate to habitual traits in affected individuals, remains unknown. We therefore used single-voxel proton magnetic resonance spectroscopy to measure glutamate, myo-inositol, and NAA in the right inferior lateral prefrontal cortex and the right occipital cortex of 85 women [n = 22 AN (binge-eating/purging subtype; AN-BP), n = 33 BN, n = 30 controls]. To index habitual behavior, participants performed an instrumental learning task and completed the Creature of Habit Scale. Women with AN-BP, but not BN, had reduced myo-inositol and NAA concentrations relative to controls in both regions. Although patient groups had intact instrumental learning task performance, both groups reported increased routine behaviors compared to controls, and automaticity was related to reduced prefrontal glutamate and NAA participants with AN-BP. Our findings extend previous reports of reduced myo-inositol and NAA levels in restrictive AN to AN-BP, which may reflect disrupted axonal-glial signaling. Although we found inconsistent support for increased habitual behavior in AN-BP and BN, we identified preliminary associations between prefrontal metabolites and automaticity in AN-BP. These results provide further evidence of unique neurobiological profiles across binge-eating disorders.

A literature review of dopamine in binge eating

OBJECTIVE

Binge eating, a core diagnostic symptom in binge eating disorder and bulimia nervosa, increases the risk of multiple physiological and psychiatric disorders. The neurotransmitter dopamine is involved in food craving, decision making, executive functioning, and impulsivity personality trait; all of which contribute to the development and maintenance of binge eating. The objective of this paper is to review the associations of dopamine levels/activities, dopamine regulator (e.g., dopamine transporter, degrading enzymes) levels/activities, and dopamine receptor availability/affinity with binge eating.

METHODS

A literature search was conducted in PubMed and PsycINFO to obtain human and animal studies published since 2010.

RESULTS

A total of 31 studies (25 human, six animal) were included. Among the human studies, there were 12 case-control studies, eight randomized controlled trials, and five cross-sectional studies. Studies used neuroimaging (e.g., positron emission tomography), genetic, and pharmacological (e.g., dopamine transporter inhibitor) techniques to describe or compare dopamine levels/activities, dopamine transporter levels/activities, dopamine degrading enzyme (e.g., catechol-O-methyltransferase) levels/activities, and dopamine receptor (e.g., D1, D2) availability/affinity among participants with and without binge eating. Most human and animal studies supported an altered dopaminergic state in binge eating (26/31, 83.9%); however, results were divergent regarding whether the altered state was hyperdopaminergic (9/26, 34.6%) or hypodopaminergic (17/26, 65.4%). The mixed findings may be partially explained by the variability in sample characteristics, study design, diagnosis criteria, and neuroimaging/genetic/pharmacological techniques used. However, it is possible that instead of being mutually exclusive, the hyperdopaminergic and hypodopaminergic state may co-exist, but in different stages of binge eating or in different individual genotypes.

CONCLUSIONS

For future studies to clarify the inconsistent findings, a homogenous sample that controls for confounders that may influence dopamine levels (e.g., psychiatric diseases) is preferable. Longitudinal studies are needed to evaluate whether the hyper- and hypo-dopaminergic states co-exist in different stages of binge eating or co-exist in individual phenotypes. Binge eating is characterized by eating a large amount of food in a short time and a feeling of difficulty to stop while eating. Binge eating is the defining symptom of binge eating disorder and bulimia nervosa, both of which are associated with serious health consequences. Studies have identified several psychological risk factors of binge eating, including a strong desire for food, impaired cognitive skills, and distinct personality traits (e.g., quick action without careful thinking). However, the physiological markers of binge eating remain unclear. Dopamine is a neurotransmitter that is heavily involved in feeding behavior, human motivation, cognitive ability, and personality. Therefore, dopamine is believed to play a critical role in binge eating. This review synthesized study findings related to the levels and activities of dopamine, dopamine regulators, and dopamine receptors in the context of binge eating. The primary finding is that most studies that used neuroimaging, genetic, or drug techniques found an altered dopaminergic state related to binge eating. However, the literature is inconsistent concerning the direction of the alteration. Considering the mixed findings and the limitations in study design, future studies, especially those that include repeated measurements, are needed to clarify the role of dopamine in binge eating.

OUP accepted manuscript

The medial prefrontal cortex (mPFC) is thought to be central for flexible behavioral adaptation. However, the causal relationship between mPFC activity and this behavior is incompletely understood. We investigated whether transcranial direct current stimulation (tDCS) over the mPFC alters flexible behavioral adaptation during reward-based decision-making, targeting Montreal Neurological Institute (MNI) coordinates X = −8, Y = 62, Z = 12, which has previously been associated with impaired behavioral adaptation in alcohol-dependent patients. Healthy human participants (n = 61) received either anodal (n = 30) or cathodal (n = 31) tDCS versus sham tDCS while performing a reversal learning task. To assess the mechanisms of reinforcement learning (RL) underlying our behavioral observations, we applied computational models that varied with respect to the updating of the unchosen choice option. We observed that anodal stimulation over the mPFC induced increased choice switching after punishments compared with sham stimulation, whereas cathodal stimulation showed no effect on participants’ behavior compared with sham stimulation. RL revealed increased updating of the unchosen choice option under anodal as compared with sham stimulation, which accounted well for the increased tendency to switch after punishments. Our findings provide a potential model for tDCS interventions in conditions related to flexible behavioral adaptation, such as addiction.

Cognitive function in binge eating disorder and food addiction: A systematic review and three-level meta-analysis

BACKGROUND

An extensive body of recent research has focused on the contribution of cognitive functioning to eating behaviors. In binge eating disorder (BED) and food addiction (FA), the extent of cognitive impairment is still unclear. This study aimed to characterize, among those with BED and FA, neurocognitive functions using performances based on neuropsychological tasks in the context of neutral stimuli in adults.

METHOD

MEDLINE, Embase, PsycINFO, Cochrane Database of Systematic Reviews, CINAHL and gray literature (ProQuest and OpenGrey) were used to identify studies that reported neurocognitive assessments in BED or FA up to December 2019. A three-level meta-analysis was conducted.

RESULTS

A significant overall effect was found for global cognitive impairments, suggesting that individuals with BED or FA have poorer performances when completing cognitive tasks. Analyses for specific cognitive domains revealed that individuals with BED showed poorer performances at tasks assessing cognitive flexibility, inhibitory control, attention and planning. Analyses regarding FA were inconclusive due to a lack of studies. Thus, the results were described qualitatively.

CONCLUSION

Our meta-analysis highlighted the cognitive weaknesses that seem to come with BED and the necessity to integrate them in the assessment and treatment of this condition. It also stressed the lack of quality studies surrounding the cognitive features of FA.

Cultural shifts in the symptoms of Anorexia Nervosa: The case of Orthorexia Nervosa

Orthorexia Nervosa (ON) is a term describing a fixation on food purity, involving ritualized eating patterns and a rigid avoidance of "unhealthy foods." Those self-identified as having ON tend to focus on food composition and feel immense guilt after eating food deemed "unhealthy." Although not formally recognized as a psychiatric disorder by the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), ON has received increasing attention since its identification in 1997. There is ongoing work to establish diagnostic and empirical tools for measuring ON; embedded in this is the question as to whether or not ON is a new eating disorder. In this paper, we argue ON is not a new psychiatric disorder but rather a new cultural manifestation of anorexia nervosa (AN). We begin by providing an overview of historical representations and classification of eating disorders, with a specific focus on AN. This is followed by discussion of the rise in diet culture and healthism since the 19th century. We conclude by examining the diagnostic validity and utility of ON through a discussion of empirical evidence. Classifying ON under the diagnostic umbrella of AN may improve our understanding of factors underlying restrictive eating behaviors.

Neuronal activities during palatable food consumption in the reward system of binge-like eating female rats

Binge eating disorder (BED), characterized by bingeing episodes and compulsivity, is the most prevalent eating disorder; however, little is known about its neurobiological underpinnings. In humans, BED is associated with desensitization of the reward system, specifically, the medial prefrontal cortex (mPFC), nucleus accumbens (Acb), and ventral tegmental area (VTA). Additionally, BED patients feel relieved during bingeing, suggesting that bingeing helps to decrease the negative emotions they were feeling prior to the binge episode. However, the mechanisms that underlie this feeling of relief in BED patients have not been well investigated. To investigate neuronal activity before and during palatable food consumption in BED, we performed in vivo electrophysiological recordings in a binge-like eating rat model (bingeing, n = 12 and non-bingeing, n = 14) and analyzed the firing rate of neurons in the mPFC, Acb, and VTA before and during access to sucrose solution. We also investigated changes in the firing rate of neurons in these regions during and between active bingeing, which may underlie the feeling of relief in BED patients. We found that neuronal firing rates of mPFC and VTA neurons in bingeing rats were lower than those in non-bingeing rats before and during sucrose consumption. Palatable food consumption increased neuronal firing rates during and between active bingeing in bingeing rats. Our results suggest a desynchronization in the activity of reward system regions, specifically in the mPFC, in bingeing rats, which may also contribute to BED. These results are consistent with those of functional magnetic resonance imaging (fMRI) studies that reported decreased activity in the reward system in BED patients. We propose that increased neuronal activity in the mPFC, Acb, or VTA produces an antidepressant effect in rats, which may underlie the sense of relief patients express during bingeing episodes.

To learn or to gain: neural signatures of exploration in human decision-making

Individuals not only take actions to obtain immediate rewards but also to gain more information to guide future choices. An ideal exploration-exploitation balance is crucial for maximizing reward over the long run. However, the neural signatures of exploration in humans remain unclear. Using quantitative meta-analyses of functional magnetic resonance imaging experiments on exploratory behaviors, we sought to identify the concordant activity pertaining to exploration over a range of experiments. The results revealed that exploration activates concordant brain activity associated with risk (e.g., dorsal medial prefrontal cortex and anterior insula), cognitive control (e.g., dorsolateral prefrontal cortex and inferior frontal gyrus), and motor processing (e.g., premotor cortex). These stereotaxic maps of exploration may indicate that exploration is highly linked to risk processing, but is also specifically associated with regions involved in executive control processes. Although this explanation should be treated as exploratory, these findings support theories positing an important role for the prefrontal-insular-motor cortical network in exploration.

A review of effort-based decision-making in eating and weight disorders

Effort-based decision-making provides a framework to understand the mental computations estimating the amount of work ("effort") required to obtain a reward. The aim of the current review is to systematically synthesize the available literature on effort-based decision-making across the spectrum of eating and weight disorders. More specifically, the current review summarises the literature examining whether 1) individuals with eating disorders and overweight/obesity are willing to expend more effort for rewards compared to healthy controls, 2) if particular components of effort-based decision-making (i.e. risk, discounting) relate to specific binge eating conditions, and 3) how individual differences in effort and reward -processing measures relate to eating pathology and treatment measures. A total of 96 studies were included in our review, following PRISMA guidelines. The review suggests that individuals with binge eating behaviours 1) are more likely to expend greater effort for food rewards, but not monetary rewards, 2) demonstrate greater decision-making impairments under risk and uncertainty, 3) prefer sooner rather than delayed rewards for both food and money, and 4) demonstrate increased implicit 'wanting' for high fat sweet foods. Finally, individual differences in effort and reward -processing measures relating to eating pathology and treatment measures are also discussed.

Interactive influences of food, contexts and neurocognitive systems on addictive eating

Compulsive eating is a common symptom of different conditions, including obesity, binge eating disorder and bulimia. One hypothesis is that contemporary food products promote compulsive eating via addiction-like mechanisms. However, what is the addictive substance in food, and what is the phenotypic overlap between obesity / eating disorders and addictions are questions that remain unresolved. In this review, we applied a multilevel framework of addiction, which encompasses the 'drug' (certain foods), the person's mindset, and the context, to improve understanding of compulsive eating. Specifically, we reviewed evidence on the addictive properties of specific foods, the neurocognitive systems that control dietary choices, and their interaction with physical, emotional and social contexts. We focused on different target groups to illustrate distinct aspects of the proposed framework: the impact of food and contextual factors were examined across a continuum, with most studies conducted on healthy participants and subclinical populations, whereas the review of neurocognitive aspects focused on clinical groups in which the alterations linked to addictive and compulsive eating are particularly visible. The reviewed evidence suggest that macronutrient composition and level of processing are associated with the addictive properties of food; there are overlapping neuroadaptations in reward and decision-making circuits across compulsive eating conditions; and there are physical and social contexts that fuel compulsive eating by exploiting reward mechanisms and their interaction with emotions. We conclude that a biopsychosocial model that integrates food, neurobiology and context can provide a better understanding of compulsive eating manifestations in a transdiagnostic framework.

Loss of control over eating: A systematic review of task based research into impulsive and compulsive processes in binge eating

Recurring episodes of excessive food intake in binge eating disorder can be understood through the lens of behavioral control systems: patients repeat maladaptive behaviors against their explicit intent. Self-report measures show enhanced impulsivity and compulsivity in binge eating (BE) but are agnostic as to the processes that might lead to impulsive and compulsive behavior in the moment. Task-based neurocognitive investigations can tap into those processes. In this systematic review, we synthesize neurocognitive research on behavioral impulsivity and compulsivity in BE in humans and animals, published between 2010-2020. Findings on impulsivity are heterogeneous. Findings on compulsivity are sparse but comparatively consistent, indicating an imbalance of goal-directed and habitual control as well as deficits in reversal learning. We urge researchers to address heterogeneity related to mood states and the temporal dynamics of symptoms, to systematically differentiate contributions of body weight and BE, and to ascertain the validity and reliability of tasks. Moreover, we propose to further scrutinize the compulsivity findings to unravel the computational mechanisms of a potential reinforcement learning deficit.

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.

Are methamphetamine users compulsive? Faulty reinforcement learning, not inflexibility, underlies decision making in people with methamphetamine use disorder

Methamphetamine use disorder involves continued use of the drug despite negative consequences. Such 'compulsivity' can be measured by reversal learning tasks, which involve participants learning action-outcome task contingencies (acquisition-contingency) and then updating their behaviour when the contingencies change (reversal). Using these paradigms, animal models suggest that people with methamphetamine use disorder (PwMUD) may struggle to avoid repeating actions that were previously rewarded but are now punished (inflexibility). However, difficulties in learning task contingencies (reinforcement learning) may offer an alternative explanation, with meaningful treatment implications. We aimed to disentangle inflexibility and reinforcement learning deficits in 35 PwMUD and 32 controls with similar sociodemographic characteristics, using novel trial-by-trial analyses on a probabilistic reversal learning task. Inflexibility was defined as (a) weaker reversal phase performance, compared with the acquisition-contingency phases, and (b) persistence with the same choice despite repeated punishments. Conversely, reinforcement learning deficits were defined as (a) poor performance across both acquisition-contingency and reversal phases and (b) inconsistent postfeedback behaviour (i.e., switching after reward). Compared with controls, PwMUD exhibited weaker learning (odds ratio [OR] = 0.69, 95% confidence interval [CI] [0.63-0.77], p < .001), though no greater accuracy reduction during reversal. Furthermore, PwMUD were more likely to switch responses after one reward/punishment (OR = 0.83, 95% CI [0.77-0.89], p < .001; OR = 0.82, 95% CI [0.72-0.93], p = .002) but just as likely to switch after repeated punishments (OR = 1.03, 95% CI [0.73-1.45], p = .853). These results indicate that PwMUD's reversal learning deficits are driven by weaker reinforcement learning, not inflexibility.

The insulo-opercular cortex encodes food-specific content under controlled and naturalistic conditions

The insulo-opercular network functions critically not only in encoding taste, but also in guiding behavior based on anticipated food availability. However, there remains no direct measurement of insulo-opercular activity when humans anticipate taste. Here, we collect direct, intracranial recordings during a food task that elicits anticipatory and consummatory taste responses, and during ad libitum consumption of meals. While cue-specific high-frequency broadband (70–170 Hz) activity predominant in the left posterior insula is selective for taste-neutral cues, sparse cue-specific regions in the anterior insula are selective for palatable cues. Latency analysis reveals this insular activity is preceded by non-discriminatory activity in the frontal operculum. During ad libitum meal consumption, time-locked high-frequency broadband activity at the time of food intake discriminates food types and is associated with cue-specific activity during the task. These findings reveal spatiotemporally-specific activity in the human insulo-opercular cortex that underlies anticipatory evaluation of food across both controlled and naturalistic settings.

Animal studies have shown that insulo-opercular network function is critical in gustation and in behaviour based on anticipated food availability. The authors describe activities within the human insulo-opercular cortex which underlie anticipatory food evaluation in both controlled and naturalistic settings.

Fronto-striatal structures related with model-based control as an endophenotype for obsessive-compulsive disorder

Recent theories suggest a shift from model-based goal-directed to model-free habitual decision-making in obsessive–compulsive disorder (OCD). However, it is yet unclear, whether this shift in the decision process is heritable. We investigated 32 patients with OCD, 27 unaffected siblings (SIBs) and 31 healthy controls (HCs) using the two-step task. We computed behavioral and reaction time analyses and fitted a computational model to assess the balance between model-based and model-free control. 80 subjects also underwent structural imaging. We observed a significant ordered effect for the shift towards model-free control in the direction OCD > SIB > HC in our computational parameter of interest. However less directed analyses revealed no shift towards model-free control in OCDs. Nonetheless, we found evidence for reduced model-based control in OCDs compared to HCs and SIBs via 2nd stage reaction time analyses. In this measure SIBs also showed higher levels of model-based control than HCs. Across all subjects these effects were associated with the surface area of the left medial/right dorsolateral prefrontal cortex. Moreover, correlations between bilateral putamen/right caudate volumes and these effects varied as a function of group: they were negative in SIBs and OCDs, but positive in HCs. Associations between fronto-striatal regions and model-based reaction time effects point to a potential endophenotype for OCD.

Anhedonia, positive affect dysregulation, and risk and maintenance of binge-eating disorder

Low positive affect has been identified as an antecedent of binge-eating episodes among individuals with binge-eating disorder (BED), yet positive affect has received far less attention in eating disorders research than its counterpart, negative affect. In this article, we argue that the low levels of positive affect which occur with anhedonia (i.e., loss of interest or pleasure in activities) may contribute to the onset and maintenance of BED. We introduce a theoretical model in which anhedonia increases the risk for BED through its interrelationships with dysregulated eating and weight gain, and we describe potential direct (e.g., reward-related processes) as well as indirect (e.g., influences on depressive symptoms and physical activity) pathways by which anhedonia may lead to adverse eating- and weight-related outcomes. We also propose a momentary maintenance model in which low positive affect and positive affect dysregulation occurring with anhedonia maintain binge eating directly and indirectly through maladaptive health behaviors, such as decreased physical activity, less healthy eating, and fewer social interactions, which in turn maintain anhedonia. We draw upon outside literature to present evidence that aligns with the proposed risk and maintenance models and conclude by outlining avenues for future research-including methodological/measurement, theoretical, and clinical research directions.

Decision-Making in Gambling Disorder, Problematic Pornography Use, and Binge-Eating Disorder: Similarities and Differences

Purpose of Review

The present review attempts to provide a comprehensive and critical overview of the neurocognitive mechanisms of gambling disorder (GD), problematic pornography use (PPU) and binge-eating disorder (BED), focusing specifically on decision-making processes.

Recent findings

GD, PPU and BED have been associated with decision-making impairments both under risk and ambiguity. Features such as intelligence, emotions, social variables, cognitive distortions, comorbidities, or arousal may condition decision-making processes in these individuals.

Summary

Impairments in decision-making seem to be a shared transdiagnostic feature of these disorders We also hypothesized the EG relative to the NEG group would demonstrate weaker relationships between problem-gambling severity and health/functioning measures (e.g., substance use) and gambling behaviors (e.g., more time spent gambling) given that EG would account for some of the variance in the relationships between ARPG and these measures. However, there is varying support for the degree to which different features may affect decision-making. Therefore, the study of decision-making processes can provide crucial evidence for understanding addictions and other disorders with addiction-like symptomatology.

The Neurobiology of Binge-eating Disorder Compared with Obesity: Implications for Differential Therapeutics

PURPOSE

Emerging work indicates divergence in the neurobiologies of binge-eating disorder (BED) and obesity despite their frequent co-occurrence. This review highlights specific distinguishing aspects of BED, including elevated impulsivity and compulsivity possibly involving the mesocorticolimbic dopamine system, and discusses implications for differential therapeutics for BED.

METHODS

This narrative review describes epidemiologic, clinical, genetic, and preclinical differences between BED and obesity. Subsequently, this review discusses human neuroimaging work reporting differences in executive functioning, reward processing, and emotion reactivity in BED compared with obesity. Finally, on the basis of the neurobiology of BED, this review identifies existing and new therapeutic agents that may be most promising given their specific targets based on putative mechanisms of action relevant specifically to BED.

FINDINGS

BED is characterized by elevated impulsivity and compulsivity compared with obesity, which is reflected in divergent neurobiological characteristics and effective pharmacotherapies. Therapeutic agents that influence both reward and executive function systems may be especially effective for BED.

IMPLICATIONS

Greater attention to impulsivity/compulsivity-related, reward-related, and emotion reactivity-related processes may enhance conceptualization and treatment approaches for patients with BED. Consideration of these distinguishing characteristics and processes could have implications for more targeted pharmacologic treatment research and interventions.

Clinical binge eating, but not uncontrolled eating, is associated with differences in executive functions: Evidence from meta-analytic findings

•

To study the relationship between executive functions and binge eating behaviors.

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Executive functions do not differ along non-clinical binge eating patterns.

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Binge eating disorder might be related with small deficits in executive function.

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Mood disorders linked with severe binge eating might influence cognitive deficits.

Introduction

Binge eating disorder (BED) is a common psychiatric diagnosis characterized by the presence of episodes of loss of control over food consumption. Understanding the neurocognitive factors associated with binge eating pathology might help to design clinical strategies aimed at preventing or treating BED. However, results in the field are notably heterogeneous. In the current study, we aimed to establish whether binge eating behaviors (both at a clinical and at a non-clinical level) are associated with executive functions.

Methods

We performed a pre-registered meta-analysis to examine the link between executive functions, BED, and uncontrolled eating, a psychobiological construct closely associated with binge eating behaviors. Articles were searched on PubMed and the main exclusion criteria were lack of information about participants’ age or sex distribution or adiposity measurements, studies performed in older populations (age > 65 years old) or studies including participants with purging symptoms.

Results

Relative to healthy controls, patients with BED showed lower performance in executive functions, with a small effect size. At the same time, uncontrolled eating patterns were not associated with differences in executive functions. Neither age nor body mass index (BMI) influenced these results.

Conclusions

Our findings suggest that there is no association between performance in executive functions and variations along the non-clinical spectrum of binge eating behaviors. Small deficits in executive functions, however, seem to appear in individuals showing severe binge eating symptoms, that is, individuals meeting diagnostic criteria for BED. We speculate that the close links between BED and emotional distress could partly explain these results.

Differential Expression of DeltaFosB in Reward Processing Regions Between Binge Eating Prone and Resistant Female Rats

Binge eating (BE) is characterized by the consumption of large amounts of palatable food in a discrete period and compulsivity. Even though BE is a common symptom in bulimia nervosa (BN), binge eating disorder (BED), and some cases of other specified feeding or eating disorders, little is known about its pathophysiology. We aimed to identify brain regions and neuron subtypes implicated in the development of binge-like eating in a female rat model. We separated rats into binge eating prone (BEP) and binge eating resistant (BER) phenotypes based on the amount of sucrose they consumed following foot-shock stress. We quantified deltaFosB (ΔFosB) expression, a stably expressed Fos family member, in different brain regions involved in reward, taste, or stress processing, to assess their involvement in the development of the phenotype. The number of ΔFosB-expressing neurons was: (1) higher in BEP than BER rats in reward processing areas [medial prefrontal cortex (mPFC), nucleus accumbens (Acb), and ventral tegmental area (VTA)]; (2) similar in taste processing areas [insular cortex, IC and parabrachial nucleus (PBN)]; and (3) higher in the paraventricular nucleus of BEP than BER rats, but not different in the locus coeruleus (LC), which are stress processing structures. To study subtypes of ΔFosB-expressing neurons in the reward system, we performed in situ hybridization for glutamate decarboxylase 65 and tyrosine hydroxylase (TH) mRNA after ΔFosB immunohistochemistry. In the mPFC and Acb, the proportions of γ-aminobutyric acidergic (GABAergic) and non-GABAergic ΔFosB-expressing neurons were similar in BER and BEP rats. In the VTA, while the proportion of dopaminergic ΔFosB-expressing neurons was similar in both phenotypes, the proportion of GABAergic ΔFosB-expressing neurons was higher in BER than BEP rats. Our results suggest that reward processing brain regions, particularly the VTA, are important for the development of binge-like eating.

Change in decision-making skills and risk for eating disorders in adolescence: A population-based study

BACKGROUND

Despite the growing interest in the involvement of decision-making under conditions of risk in the onset of eating disorders in adolescence, no studies have investigated how the development of decision-making across that period may influence such a risk. Using data from the Millennium Cohort Study this study explored whether changes in performance on the Cambridge Gambling Task (CGT) between age 11 and age 14 were associated with presence of eating disorder (ED) symptoms at age 14.

METHODS

Latent class analysis was used to identify groups with distinct profiles based on their responses to questions investigating eating and dieting at age 14. CGT change scores were used as predictors of latent class membership in a logistic regression while accounting for confounders.

RESULTS

In our sample of 11,303 participants, the best class solution was a two-class one reflecting high and low risk for ED symptoms. Higher risk-taking scores and lower quality of decision-making scores at age 11 were associated with increased odds of belonging to the high-risk group at age 14. Risk-taking was reduced from age 11 to age 14, but a smaller reduction was associated with a higher probability of being in the higher risk group at age 14. The change over time in the other CGT measures was not associated with risk for ED symptoms.

CONCLUSIONS

Atypical change in risk-taking from early to middle adolescence may be implicated in the risk of ED symptoms in middle adolescence. These results should be replicated in clinical samples.

Impaired decision-making under risk in patients with functional dyspepsia

INTRODUCTION

The cognitive processing in patients with functional dyspepsia (FD) has not been well established. Decision-making is an important component of cognitive function. Most brain regions involved in decision-making are abnormal in FD patients. This study aimed to investigate the decision-making under ambiguity and risk in FD patients.

METHODS

We recruited 40 FD patients meeting Rome III criteria and 40 healthy controls (HCs) matched for age, sex, marital status, and education level. The Hamilton Anxiety Scale (HAMA) and the 17-item Hamilton Depression Scale (HAMD-17) were used to evaluate their anxiety and depression emotions. The Iowa Gambling Task (IGT) and Game of Dice Task (GDT) were used to evaluate decision-making under ambiguity and risk, respectively. Helicobacter pylori status, disease duration, dyspeptic symptom score, and the Nepean Dyspepsia Life Quality Index (NDLQI) were obtained from all patients.

RESULTS

In IGT, FD patients had a lower total net score, chose more adverse choices, and showed a slower response to change their behavior than HCs. However, there was no significant difference in the net score of the first 2 blocks between the two groups. In GDT, FD patients had a lower total net score, higher risk score, and lower use of negative feedback than HCs. In addition, FD patients showed better GDT performance than those without early satiation.

CONCLUSIONS

FD patients showed impaired decision-making under risk. The deficiency might be related to dyspeptic symptoms of FD patients.

Brain white matter microstructure in obese women with binge eating disorder

OBJECTIVE

Research on potential brain circuit abnormalities in binge eating disorder (BED) is limited. Here, we assess white matter (WM) microstructure in obese women with BED.

METHOD

Diffusion tensor imaging data were acquired, and tract-based spatial statistics used to examine WM in women with BED who were obese (n = 17) compared to normal-weight (NWC) (n = 17) and to women who were obese (OBC) (n = 13). Body mass index (BMI) was a covariate in the analyses.

RESULTS

The BED group (vs. NWC) had greater axial diffusion (AD) in the forceps minor, anterior thalamic radiation, superior and inferior longitudinal fasciculus, that is, in pathways connecting fronto-limbic regions. Microstructures differences in AD between the BED and OBC groups were seen in fronto-limbic pathways extending to temporoparietal pathways. The BED (vs. OBC) group had greater fractional anisotropy in the forceps minor and greater AD in the superior longitudinal fasciculus, cingulate gyrus, and corpus callosum, consistent with fronto-tempoparietal pathways.

CONCLUSION

Women with BED show WM alterations in AD in fronto-limbic and parietal pathways that are important in decision-making processes. As BMI was a covariate in the analyses, alterations in BED may be part of the pathology, but whether they are a cause or effect of illness is unclear.

Goal-oriented and habitual decisions: Neural signatures of model-based and model-free learning

Human decision-making is mainly driven by two fundamental learning processes: a slow, deliberative, goal-directed model-based process that maps out the potential outcomes of all options and a rapid habitual model-free process that enables reflexive repetition of previously successful choices. Although many model-informed neuroimaging studies have examined the neural correlates of model-based and model-free learning, the concordant activity among these two processes remains unclear. We used quantitative meta-analyses of functional magnetic resonance imaging experiments to identify the concordant activity pertaining to model-based and model-free learning over a range of reward-related paradigms. We found that: 1) both processes yielded concordant ventral striatum activity, 2) model-based learning activated the medial prefrontal cortex and orbital frontal cortex, and 3) model-free learning specifically activated the left globus pallidus and right caudate head. Our findings suggest that model-free and model-based decision making engage overlapping yet distinct neural regions. These stereotaxic maps improve our understanding of how deliberative goal-directed and reflexive habitual learning are implemented in the brain.

Weight and age do not account for a worse executive functioning among BED-obese patients

PURPOSE

Research has demonstrated impaired executive functioning among Binge Eating Disorder (BED) patients that could be influenced by age and weight. We aim to compare decision-making, set-shifting and central coherence between BED-obese patients (BED-Ob), non-BED-obese patients (non-BED-Ob), and normal-weight healthy controls (NW-HC) without the influence of these variables.

METHODS

Overall, 35 BED-Ob, 32 non-BED-Ob and 26 NW-HC participants completed the Iowa Gambling Task, the Trail Making Test and the Rey-Osterrieth Complex Figure Test.

RESULTS

BED-Ob patients showed higher cognitive impairment compared to NW-HC on decision-making, set-shifting, visual attention and memory.

CONCLUSIONS

BED-Ob patients have an impaired cognitive profile on decision-making, set-shifting, visual attention and memory but not impaired central coherence. As all groups were aged-matched and no significant differences between BED-Ob and non-BED-Ob participants were evident, our results demonstrate that this impairment is independent from weight/age, pointing out that it is BED itself to account for inefficiencies in cognitive functioning.

LEVEL OF EVIDENCE

Level III, case-control study.

The Neurobiology of Impulsive Decision-Making and Reinforcement Learning in Nonhuman Animals

Impulsive decisions are those that favor immediate over delayed rewards, involve the acceptance of undue risk or uncertainty, or fail to adapt to environmental changes. Pathological levels of impulsive decision-making have been observed in individuals with mental illness, but there may be substantial heterogeneity in the processes that drive impulsive choices. Understanding this behavioral heterogeneity may be critical for understanding associated diverseness in the neural mechanisms that give rise to impulsivity. The application of reinforcement learning algorithms in the deconstruction of impulsive decision-making phenotypes can help bridge the gap between biology and behavior and provide insights into the biobehavioral heterogeneity of impulsive choice. This chapter will review the literature on the neurobiological mechanisms of impulsive decision-making in nonhuman animals; specifically, the role of the amine neuromodulatory systems (dopamine, serotonin, norepinephrine, and acetylcholine) in impulsive decision-making and reinforcement learning processes is discussed. Ultimately, the integration of reinforcement learning algorithms with sophisticated behavioral and neuroscience techniques may be critical for advancing the understanding of the neurochemical basis of impulsive decision-making.