Deficient Goal-Directed Control in a Population Characterized by Extreme Goal Pursuit

A transdiagnostic and translational framework for delineating the neuronal mechanisms of compulsive exercise in anorexia nervosa

OBJECTIVE

The development of novel treatments for anorexia nervosa (AN) requires a detailed understanding of the biological underpinnings of specific, commonly occurring symptoms, including compulsive exercise. There is considerable bio-behavioral overlap between AN and obsessive-compulsive disorder (OCD), therefore it is plausible that similar mechanisms underlie compulsive behavior in both populations. While the association between these conditions is widely acknowledged, defining the shared mechanisms for compulsive behavior in AN and OCD requires a novel approach.

METHODS

We present an argument that a better understanding of the neurobiological mechanisms that underpin compulsive exercise in AN can be achieved in two critical ways. First, by applying a framework of the neuronal control of OCD to exercise behavior in AN, and second, by taking better advantage of the activity-based anorexia (ABA) rodent model to directly test this framework in the context of feeding pathology.

RESULTS

A cross-disciplinary approach that spans preclinical, neuroimaging, and clinical research as well as compulsive neurocircuitry and behavior can advance our understanding of when, why, and how compulsive exercise develops in the context of AN and provide targets for novel treatment strategies.

DISCUSSION

In this article, we (i) link the expression of compulsive behavior in AN and OCD via a transition between goal-directed and habitual behavior, (ii) present disrupted cortico-striatal circuitry as a key substrate for the development of compulsive behavior in both conditions, and (iii) highlight the utility of the ABA rodent model to better understand the mechanisms of compulsive behavior relevant to AN.

PUBLIC SIGNIFICANCE

Individuals with AN who exercise compulsively are at risk of worse health outcomes and have poorer responses to standard treatments. However, when, why, and how compulsive exercise develops in AN remains inadequately understood. Identifying whether the neural circuitry underlying compulsive behavior in OCD also controls hyperactivity in the activity-based anorexia model will aid in the development of novel eating disorder treatment strategies for this high-risk population.

Testing the role of associative learning in evidence-based treatments for anorexia nervosa

Treatments for anorexia nervosa (AN) remain ineffective for many patients. Processes that can account for differential treatment outcomes remain mostly unknown. We propose that the field test the role of associative learning in current psychological treatments. We hold that this line of research could yield actionable information for understanding non-response and improving long-term outcomes. To make this argument, we define associative learning and outline its proposed role in understanding psychiatric disorders and their treatment. We then briefly review data exploring associative learning in AN. We argue that associative learning processes are implicitly implicated in existing treatments; by this rationale, baseline differences in learning may interfere with treatment response. Finally, we outline future research to test our hypotheses. Altogether, future research aimed at better understanding how associative learning may contribute to AN symptom persistence has the potential to inform novel directions in intervention research. PUBLIC SIGNIFICANCE: There is a pressing need to improve outcomes in treatments for anorexia nervosa (AN). We propose that individual differences in associative learning-the ability to form and update associations between cues, contexts, behaviors, and outcomes-may account for differential response to existing treatments. Undertaking this research could provide an understanding of how current treatments work and inform new approaches for those who may be at risk of poor outcomes.

Neural Response to Expecting a Caloric Sweet Taste Stimulus Predicts Body Mass Index Longitudinally Among Young Adult Women With Anorexia Nervosa

BACKGROUND

Anorexia nervosa (AN) is an often-chronic illness, and we lack biomarkers to predict long-term outcome. Recent neuroimaging studies using caloric taste stimuli suggest that paradigms that have tested conditioned neural responses to expectation or salient stimulus receipt may underpin behaviors. However, whether activation of those neural circuits can predict long-term outcome has not been studied.

METHODS

We followed women treated for AN (n = 35, mean age [SD] = 23 [7] years) and tested whether functional imaging brain response during a taste conditioning paradigm could predict posttreatment body mass index (BMI). We anticipated greater neural activity relative to caloric stimulus expectation and that dopamine-related receipt conditions would predict lower posttreatment BMI, indicating fear-associated arousal.

RESULTS

Follow-up occurred at mean (SD) = 1648 (1216) days after imaging. Stimulus expectation in orbitofrontal and striatal regions and BMI and BMI change at follow-up were negatively correlated, and these correlations remained significant for the right superior orbitofrontal cortex and BMI change after multiple comparison correction (r = -0.484, p = .003). This relationship remained significant after including time between brain scanning and follow-up in the model. Reward prediction error response did not predict long-term BMI.

CONCLUSIONS

The orbitofrontal cortex is involved in learning and conditioning, and these data implicate this region in learned caloric stimulus expectation and long-term prediction of weight outcomes in AN. Thus, conditioned elevated brain response to the anticipation of receiving a caloric stimulus may drive food avoidance, suggesting that breaking such associations is central for long-term recovery from AN.

Greater reliance on model-free learning in adolescent anorexia nervosa: An examination of dual-system reinforcement learning

Alterations in learning and decision-making systems are thought to contribute to core features of anorexia nervosa (AN), a psychiatric disorder characterized by persistent dietary restriction and weight loss. Instrumental learning theory identifies a dual-system of habit and goal-directed decision-making, linked to model-free and model-based reinforcement learning algorithms. Difficulty arbitrating between these systems, resulting in an over-reliance on one strategy over the other, has been implicated in compulsivity and extreme goal pursuit, both of which are observed in AN. Characterizing alterations in model-free and model-based systems, and their neural correlates, in AN may clarify mechanisms contributing to symptom heterogeneity (e.g., binge/purge symptoms). This study tested whether adolescents with restricting AN (AN-R; n = 36) and binge/purge AN (AN-BP; n = 20) differentially utilized model-based and model-free learning systems compared to a healthy control group (HC; n = 28) during a Markov two-step decision-making task under conditions of reward and punishment. Associations between model-free and model-based learning and resting-state functional connectivity between neural regions of interest, including orbitofrontal cortex (OFC), nucleus accumbens (NAcc), putamen, and sensory motor cortex (SMC) were examined. AN-R showed higher utilization of model-free learning compared to HC for reward, but attenuated model-free and model-based learning for punishment. In AN-R only, higher model-based learning was associated with stronger OFC-to-left NAcc functional connectivity, regions linked to goal-directed behavior. Greater utilization of model-free learning for reward in AN-R may differentiate this group, particularly during adolescence, and facilitate dietary restriction by prioritizing habitual control in rewarding contexts.

Model-based and model-free mechanisms in methamphetamine use disorder

People with methamphetamine use disorder (MUD) struggle to shift their behaviour from methamphetamine-orientated habits to goal-oriented choices. The model-based/model-free framework is well suited to understand this difficulty by unpacking the computational mechanisms that support experienced-based (model-free) and goal-directed (model-based) choices. We aimed to examine whether 1) participants with MUD differed from controls on behavioural proxies and/or computational mechanisms of model-based/model-free choices; 2) model-based/model-free decision-making correlated with MUD symptoms; and 3) model-based/model-free deficits improved over six weeks in the group with MUD. Participants with MUD and controls with similar age, IQ and socioeconomic status completed the Two-Step Task at treatment commencement (MUD n = 30, Controls n = 31) and six weeks later (MUD n = 23, Controls n = 26). We examined behavioural proxies of model-based/model-free decisions using mixed logistic regression, and their underlying mechanisms using computational modelling. At a behavioural level, participants with MUD were more likely to switch their choices following rewarded actions, although this pattern improved at follow up. At a computational level, groups were similar in their use of model-based mechanisms, but participants with MUD were less likely to apply model-free mechanisms and less likely to repeat rewarded actions. We did not find evidence that individual differences in model-based or model-free parameters were associated with greater severity of methamphetamine dependence, nor did we find that group differences in computational parameters changed between baseline and follow-up assessment. Decision-making challenges in people with MUD are likely related to difficulties in pursuing choices previously associated with positive outcomes.

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.

Mouse-cursor trajectories reveal reduced contextual influence on decision conflict during delay discounting in anorexia nervosa

OBJECTIVE

The capacity of individuals with anorexia nervosa (AN) to forgo immediate food rewards in their long-term pursuit of thinness is thought to reflect elevated self-control and/or abnormal reward sensitivity. Prior research attempted to capture an increased tendency to delay gratification in AN using delay-discounting tasks that assess how rapidly the subjective value of rewards decreases as a function of time until receipt. However, significant effects were mostly subtle or absent. Here, we tested whether the process leading to such decisions might be altered in AN.

METHOD

We recorded mouse-cursor movement trajectories leading to the final choice in a computerized delay-discounting task (238 trials) in 55 acutely underweight females with AN and pairwise age-matched female healthy controls (HC). We tested for group differences in deviations from a direct choice path, a measure of conflict strength in decision making, and whether group moderated the effect of several predictors of conflict strength (e.g., choice difficulty, consistency). We also explored reaction times and changes in trajectory directions (X-flips).

RESULTS

No group differences in delay-discounting parameters or movement trajectories were detected. However, the effect of the aforementioned predictors on deviations (and to a lesser extent reaction times) was reduced in AN.

DISCUSSION

These findings suggest that while delay discounting and conflict strength in decision making are generally unaltered in AN, conflict strength was more stable across different decisions in the disorder. This might enable individuals with AN to pursue (maladaptive) long-term body-weight goals, because particularly conflicting choices may not be experienced as such.

PUBLIC SIGNIFICANCE

The deviations from a direct path of mouse-cursor movements during a computerized delay-discounting task varied less in people with anorexia nervosa. Assuming such deviations measure decision conflict, we speculate that this increased stability might help people with anorexia nervosa achieve their long-term weight goals, as for them the struggle with the decision to eat high-calorie meals when hungry will be milder, so they would be more likely to skip them.

Identifying Transdiagnostic Mechanisms in Mental Health Using Computational Factor Modeling

Most psychiatric disorders do not occur in isolation, and most psychiatric symptom dimensions are not uniquely expressed within a single diagnostic category. Current treatments fail to work for around 25% to 40% of individuals, perhaps due at least in part to an overreliance on diagnostic categories in treatment development and allocation. In this review, we describe ongoing efforts in the field to surmount these challenges and precisely characterize psychiatric symptom dimensions using large-scale studies of unselected samples via remote, online, and "citizen science" efforts that take a dimensional, mechanistic approach. We discuss the importance that efforts to identify meaningful psychiatric dimensions be coupled with careful computational modeling to formally specify, test, and potentially falsify candidate mechanisms that underlie transdiagnostic symptom dimensions. We refer to this approach, i.e., where symptom dimensions are identified and validated against computationally well-defined neurocognitive processes, as computational factor modeling. We describe in detail some recent applications of this method to understand transdiagnostic cognitive processes that include model-based planning, metacognition, appetitive processing, and uncertainty estimation. In this context, we highlight how computational factor modeling has been used to identify specific associations between cognition and symptom dimensions and reveal previously obscured relationships, how findings generalize to smaller in-person clinical and nonclinical samples, and how the method is being adapted and optimized beyond its original instantiation. Crucially, we discuss next steps for this area of research, highlighting the value of more direct investigations of treatment response that bridge the gap between basic research and the clinic.

Distinct reinforcement learning profiles distinguish between language and attentional neurodevelopmental disorders

BACKGROUND

Theoretical models posit abnormalities in cortico-striatal pathways in two of the most common neurodevelopmental disorders (Developmental dyslexia, DD, and Attention deficit hyperactive disorder, ADHD), but it is still unclear what distinct cortico-striatal dysfunction might distinguish language disorders from others that exhibit very different symptomatology. Although impairments in tasks that depend on the cortico-striatal network, including reinforcement learning (RL), have been implicated in both disorders, there has been little attempt to dissociate between different types of RL or to compare learning processes in these two types of disorders. The present study builds upon prior research indicating the existence of two learning manifestations of RL and evaluates whether these processes can be differentiated in language and attention deficit disorders. We used a two-step RL task shown to dissociate model-based from model-free learning in human learners.

RESULTS

Our results show that, relative to neurotypicals, DD individuals showed an impairment in model-free but not in model-based learning, whereas in ADHD the ability to use both model-free and model-based learning strategies was significantly compromised.

CONCLUSIONS

Thus, learning impairments in DD may be linked to a selective deficit in the ability to form action-outcome associations based on previous history, whereas in ADHD some learning deficits may be related to an incapacity to pursue rewards based on the tasks' structure. Our results indicate how different patterns of learning deficits may underlie different disorders, and how computation-minded experimental approaches can differentiate between them.

Learned industriousness as a translational mechanism in anorexia nervosa

It remains unexplained why some behaviours persist despite being non-hedonic and ostensibly aversive. This phenomenon is especially baffling when such behaviours are taken to excess in the form of psychopathology. Anorexia nervosa is one psychiatric disorder in which effortful behaviours that most people find unpleasant (suchas restrictive eating) are persistently performed. We propose thatthe social psychology theory of learned industriousness providesa novel mechanistic account for such phenomena. This theoryposits that high-effort behaviour can be conditioned to acquire secondary reinforcing properties through repeated pairing with reward. Accordingly, effort sensations become less aversive andmore appetitive, increasing willingness to engage in effortful behaviour. In this Perspective, we review pre-clinical behaviouraland biological data that support learned industriousness, contrast learned industriousness with other models of non-hedonic persistence (such as habit learning), highlight evidence that supports learned industriousness in individuals with anorexia nervosa and consider implications of the model, including translation to other psychiatric presentations.

Food Restriction in Anorexia Nervosa in the Light of Modern Learning Theory: A Narrative Review

Improvements in the clinical management of anorexia nervosa (AN) are urgently needed. To do so, the search for innovative approaches continues at laboratory and clinical levels to translate new findings into more effective treatments. In this sense, modern learning theory provides a unifying framework that connects concepts, methodologies and data from preclinical and clinical research to inspire novel interventions in the field of psychopathology in general, and of disordered eating in particular. Indeed, learning is thought to be a crucial factor in the development/regulation of normal and pathological eating behaviour. Thus, the present review not only tries to provide a comprehensive overview of modern learning research in the field of AN, but also follows a transdiagnostic perspective to offer testable explanations for the origin and maintenance of pathological food rejection. This narrative review was informed by a systematic search of research papers in the electronic databases PsycInfo, Scopus and Web of Science following PRISMA methodology. By considering the number and type of associations (Pavlovian, goal-directed or habitual) and the affective nature of conditioning processes (appetitive versus aversive), this approach can explain many features of AN, including why some patients restrict food intake to the point of life-threatening starvation and others restrict calorie intake to lose weight and binge on a regular basis. Nonetheless, it is striking how little impact modern learning theory has had on the current AN research agenda and practice.

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 potential application of event-related potentials to enhance research on reward processes in eating disorders

OBJECTIVE

Reward-related processes have been posited as key mechanisms underlying the onset and persistence of eating disorders, prompting a growing body of research in this area. Existing studies have primarily utilized self-report, behavioral, and functional magnetic resonance imaging measures to interrogate reward among individuals with eating disorders. However, limitations inherent in each of these methods (e.g., poor temporal resolution) may obscure distinct neurocognitive reward processes, potentially contributing to underdeveloped models of reward dysfunction within eating disorders. The temporal precision of event-related potentials (ERPs), derived from electroencephalography, may thus offer a powerful complementary tool for elucidating the neurocognitive underpinnings of reward. Indeed, a considerable amount of research in other domains of psychopathology (e.g., depression, substance use disorders), as well as studies investigating food reward among non-clinical samples, highlights the utility of ERPs for probing reward processes. However, no study to date has utilized ERPs to directly examine reward functioning in eating disorders.

METHODS

In this paper, we review evidence underscoring the clinical utility of ERP measures of reward, as well as a variety of reward-related tasks that can be used to elicit specific ERP components with demonstrated relevance to reward processing. We then consider the ways in which these tasks/components may be used to help answer a variety of open questions within the eating disorders literature on reward.

RESULTS/DISCUSSION

Given the promise of ERP measures of reward to the field of eating disorders, we ultimately hope to spur and guide research in this currently neglected area.

PUBLIC SIGNIFICANCE

Abnormalities in reward functioning appear to contribute to eating disorders. Event-related potentials (ERPs) offer temporally precise measures of neurocognitive reward processing and thus may be important tools for understanding the relationship between reward and disordered eating. However, research in this area is currently lacking. This paper attempts to facilitate the use of ERPs to study reward among individuals with eating disorders by reviewing the relevant theories and methods.

Increased Habit Frequency in the Daily Lives of Patients with Acute Anorexia Nervosa

Strict eating routines and frequent rigid behavior patterns are commonly observed in patients with anorexia nervosa (AN). A recent theory proposes that while these behaviors may have been reinforced initially, they later become habitual. To date, however, research has been overly focused on eating-disorder (ED)-related habits. Over the course of seven days, we applied an ecological momentary assessment (EMA) to investigate the habit frequency and strength of ED-specific (food intake) and ED-unspecific (hygiene) habits in the daily lives of a sample of n = 57 AN and n = 57 healthy controls (HC). The results of the hierarchical models revealed that habits were significantly more likely in patients compared with HC for both categories, independently. Furthermore, a lower body mass index (BMI) was associated with increased habit frequency in AN. Our study strengthens the habit theory of AN by showing the relevance of habits beyond ED-specific behavioral domains. This also supports the development of innovative therapeutic interventions targeting habitual behavior in EDs.

Optimizing relapse prevention and changing habits (REACH+) in anorexia nervosa

INTRODUCTION

Relapse rates in anorexia nervosa (AN) are high, even after full weight restoration. This study aims to develop a relapse prevention treatment that specifically addresses persistent maladaptive behaviors (habits). Relapse Prevention and Changing Habits (REACH+) aims to support patients in developing routines that promote weight maintenance, encourage health, and challenge habits that perpetuate illness. The clinical trial design uses the Multiphase Optimization STrategy (MOST) framework to efficiently identify which components of treatment contribute to positive outcomes.

METHODS

Participants will be 60 adults with AN who have achieved weight restoration in an inpatient setting. Treatment will consist of 6 months of outpatient telehealth sessions. REACH+ consists of behavior, cognitive, and motivation components, as well as food monitoring and a skill consolidation phase. A specialized online platform extends therapy between sessions. Participants will be randomly assigned to different versions of each component in a fractional factorial design. Outcomes will focus on maintenance of remission, measured by rate of weight loss and end-of-trial status. Interventions that contribute to remission will be included in an optimized treatment package, suitable for a large-scale clinical trial of relapse prevention in AN.

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.

Gastrointestinal Interoception in Eating Disorders: Charting a New Path

PURPOSE OF REVIEW

Abnormal interoception has been consistently observed across eating disorders despite limited inclusion in diagnostic conceptualization. Using the alimentary tract as well as recent developments in interoceptive neuroscience and predictive processing as a guide, the current review summarizes evidence of gastrointestinal interoceptive dysfunction in eating disorders.

RECENT FINDINGS

Eating is a complex process that begins well before and ends well after food consumption. Abnormal prediction and prediction-error signals may occur at any stage, resulting in aberrant gastrointestinal interoception and dysregulated gut sensations in eating disorders. Several interoceptive technologies have recently become available that can be paired with computational modeling and clinical interventions to yield new insights into eating disorder pathophysiology. Illuminating the neurobiology of gastrointestinal interoception in eating disorders requires a new generation of studies combining experimental probes of gut physiology with computational modeling. The application of such techniques within clinical trials frameworks may yield new tools and treatments with transdiagnostic relevance.

Beyond Description and Deficits: How Computational Psychiatry Can Enhance an Understanding of Decision-Making in Anorexia Nervosa

PURPOSE OF REVIEW

Despite decades of research, knowledge of the mechanisms maintaining anorexia nervosa (AN) remains incomplete and clearly effective treatments elusive. Novel theoretical frameworks are needed to advance mechanistic and treatment research for this disorder. Here, we argue the utility of engaging a novel lens that differs from existing perspectives in psychiatry. Specifically, we argue the necessity of expanding beyond two historically common perspectives: (1) the descriptive perspective: the tendency to define mechanisms on the basis of surface characteristics and (2) the deficit perspective: the tendency to search for mechanisms associated with under-functioning of decision-making abilities and related circuity, rather than problems of over-functioning, in psychiatric disorders.

RECENT FINDINGS

Computational psychiatry can provide a novel framework for understanding AN because this approach emphasizes the role of computational misalignments (rather than absolute deficits or excesses) between decision-making strategies and environmental demands as the key factors promoting psychiatric illnesses. Informed by this approach, we argue that AN can be understood as a disorder of excess goal pursuit, maintained by over-engagement, rather than disengagement, of executive functioning strategies and circuits. Emerging evidence suggests that this same computational imbalance may constitute an under-investigated phenotype presenting transdiagnostically across psychiatric disorders. A variety of computational models can be used to further elucidate excess goal pursuit in AN. Most traditional psychiatric treatments do not target excess goal pursuit or associated neurocognitive mechanisms. Thus, targeting at the level of computational dysfunction may provide a new avenue for enhancing treatment for AN and related disorders.

The costs and benefits of intensive day treatment programs and outpatient treatments for eating disorders: An idea worth researching

Outpatient care (e.g., individual, group, or self-help therapies) and day treatment programs (DTPs) are common and effective treatments for adults with eating disorders. Compared to outpatient care, DTPs have additional expenses and could have unintended iatrogenic effects (e.g., may create an overly protective environment that undermines self-efficacy). However, these potential downsides may be offset if DTPs are shown to have advantages over outpatient care. To explore this question, our team conducted a scoping review that aimed to synthesize the existing body of adult eating disorder literature (a) comparing outcomes for DTPs to outpatient care, and (b) examining the use of DTPs as a higher level of care in a stepped care model. Only four studies met the predefined search criteria. The limited results suggest that the treatments have similar effects and that outpatient care is more cost-effective. Furthermore, no studies explored the use of DTPs as a higher level of care in a stepped care model (despite international guidelines recommending this approach). Given the clear dearth of literature on this clinically relevant topic, we have provided specific avenues for further research.

Exploring Neural Mechanisms Related to Cognitive Control, Reward, and Affect in Eating Disorders: A Narrative Review of FMRI Studies

Studies using functional magnetic resonance imaging (fMRI) have contributed to our understanding of possible neural abnormalities among individuals with eating disorders. Many of these studies have focused on three domains: 1) cognitive control, 2) reward processing, and 3) affective processing. This review attempts to summarize the recent fMRI findings across these domains among the most well-characterized eating disorders: anorexia nervosa (AN), bulimia nervosa (BN), and binge eating disorder (BED). Though the literature is a bit murky, a few major themes have emerged. Cognitive control systems are affected among individuals across eating disorder diagnoses, but effects seem least pronounced in AN. Specifically, individuals with all eating disorders appear to show decreased prefrontal activation during cognitive control, but there is less evidence in AN linking decreased prefrontal activation with behavior. There is some evidence that the reinforcing value of food is reduced in AN, but individuals with BN and BED show hyperactivation to rewarding food-related stimuli, suggesting the reinforcing value of food may be enhanced. However, more complex reward processing paradigms show that individuals with BN and BED exhibit hypoactivation to reward anticipation and provide mixed results with regards to reward receipt. There are fewer neuroimaging findings related to affective processing, yet behavioral findings suggest affective processing is important in understanding eating disorders. Though the extant literature is complicated, these studies represent a foundation from which to build and provide insight into potential neurobiological mechanisms that may contribute to the pathophysiology of eating disorders.