Change in food choice during acute treatment and the effect on longer-term outcome in patients with anorexia nervosa.

BACKGROUND: Restriction of food intake is a central pathological feature of anorexia nervosa (AN). Maladaptive eating behavior and, specifically, limited intake of calorie-dense foods are resistant to change and contribute to poor long-term outcomes. This study is a preliminary examination of whether change in food choices during inpatient treatment is related to longer-term clinical course. METHODS: Individuals with AN completed a computerized Food Choice Task at the beginning and end of inpatient treatment to determine changes in high-fat and self-controlled food choices. Linear regression and longitudinal analyses tested whether change in task behavior predicted short-term outcome (body mass index [BMI] at discharge) and longer-term outcome (BMI and eating disorder psychopathology). RESULTS: Among 88 patients with AN, BMI improved significantly with hospital treatment (p < 0.001), but Food Choice Task outcomes did not change significantly. Change in high-fat and self-controlled choices was not associated with BMI at discharge (r = 0.13, p = 0.22 and r = 0.10, p = 0.39, respectively). An increase in the proportion of high-fat foods selected (ß = 0.91, p = 0.02) and a decrease in the use of self-control (ß = -1.50, p = 0.001) predicted less decline in BMI over 3 years after discharge. CONCLUSIONS: Short-term treatment is associated with improvement in BMI but with no significant change, on average, in choices made in a task known to predict actual eating. However, the degree to which individuals increased high-fat choices during treatment and decreased the use of self-control over food choice were associated with reduced weight loss over the following 3 years, underscoring the need to focus on changing eating behavior in treatment of AN.

Reduced dorsal fronto-striatal connectivity at rest in anorexia nervosa.

BACKGROUND: Anorexia nervosa (AN) is a serious psychiatric illness that remains difficult to treat. Elucidating the neural mechanisms of AN is necessary to identify novel treatment targets and improve outcomes. A growing body of literature points to a role for dorsal fronto-striatal circuitry in the pathophysiology of AN, with increasing evidence of abnormal task-based fMRI activation within this network among patients with AN. Whether these abnormalities are present at rest and reflect fundamental differences in brain organization is unclear. METHODS: The current study combined resting-state fMRI data from patients with AN (n = 89) and healthy controls (HC; n = 92) across four studies, removing site effects using ComBat harmonization. First, the a priori hypothesis that dorsal fronto-striatal connectivity strength - specifically between the anterior caudate and dlPFC - differed between patients and HC was tested using seed-based functional connectivity analysis with small-volume correction. To assess specificity of effects, exploratory analyses examined anterior caudate whole-brain connectivity, amplitude of low-frequency fluctuations (ALFF), and node centrality. RESULTS: Compared to HC, patients showed significantly reduced right, but not left, anterior caudate-dlPFC connectivity (p = 0.002) in small-volume corrected analyses. Whole-brain analyses also identified reduced connectivity between the right anterior caudate and left superior frontal and middle frontal gyri (p = 0.028) and increased connectivity between the right anterior caudate and right occipital cortex (p = 0.038). No group differences were found in analyses of anterior caudate ALFF and node centrality. CONCLUSIONS: Decreased coupling of dorsal fronto-striatal regions indicates that circuit-based abnormalities persist at rest and suggests this network may be a potential treatment target.

Neural Representations of Food-Related Attributes in the Human Orbitofrontal Cortex during Choice Deliberation in Anorexia Nervosa.

Decisions about what to eat recruit the orbitofrontal cortex (OFC) and involve the evaluation of food-related attributes such as taste and health. These attributes are used differently by healthy individuals and patients with disordered eating behavior, but it is unclear whether these attributes are decodable from activity in the OFC in both groups and whether neural representations of these attributes are differentially related to decisions about food. We used fMRI combined with behavioral tasks to investigate the representation of taste and health attributes in the human OFC and the role of these representations in food choices in healthy women and women with anorexia nervosa (AN). We found that subjective ratings of tastiness and healthiness could be decoded from patterns of activity in the OFC in both groups. However, health-related patterns of activity in the OFC were more related to the magnitude of choice preferences among patients with AN than healthy individuals. These findings suggest that maladaptive decision-making in AN is associated with more consideration of health information represented by the OFC during deliberation about what to eat.SIGNIFICANCE STATEMENT An open question about the OFC is whether it supports the evaluation of food-related attributes during deliberation about what to eat. We found that healthiness and tastiness information was decodable from patterns of neural activity in the OFC in both patients with AN and healthy controls. Critically, neural representations of health were more strongly related to choices in patients with AN, suggesting that maladaptive overconsideration of healthiness during deliberation about what to eat is related to activity in the OFC. More broadly, these results show that activity in the human OFC is associated with the evaluation of relevant attributes during value-based decision-making. These findings may also guide future research into the development of treatments for AN.

Restrictive eating across a spectrum from healthy to unhealthy: behavioral and neural mechanisms.

BACKGROUND: Restriction of food intake is a central feature of anorexia nervosa (AN) and other eating disorders, yet also occurs in the absence of psychopathology. The neural mechanisms of restrictive eating in health and disease are unclear. METHODS: This study examined behavioral and neural mechanisms associated with restrictive eating among individuals with and without eating disorders. Dietary restriction was examined in four groups of women (n = 110): healthy controls, dieting healthy controls, patients with subthreshold (non-low weight) AN, and patients with AN. A Food Choice Task was administered during fMRI scanning to examine neural activation associated with food choices, and a laboratory meal was conducted. RESULTS: Behavioral findings distinguished between healthy and ill participants. Healthy individuals, both dieting and non-dieting, chose significantly more high-fat foods than patients with AN or subthreshold AN. Among healthy individuals, choice was primarily influenced by tastiness, whereas, among both patient groups, healthiness played a larger role. Dorsal striatal activation associated with choice was most pronounced among individuals with AN and was significantly associated with selecting fewer high-fat choices in the task and lower caloric intake in the meal the following day. CONCLUSIONS: A continuous spectrum of behavior was suggested by the increasing amount of weight loss across groups. Yet, data from this Food Choice Task with fMRI suggest there is a behavioral distinction between illness and health, and that the neural mechanisms underlying food choice in AN are distinct. These behavioral and neural mechanisms of restrictive eating may be useful targets for treatment development.

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

Research in computational psychiatry has sought to understand the basis of compulsive behavior by relating it to basic psychological and neural mechanisms: specifically, goal-directed versus habitual control. These psychological categories have been further identified with formal computational algorithms, model-based and model-free learning, which helps to provide quantitative tools to distinguish them. Computational psychiatry may be particularly useful for examining phenomena in individuals with anorexia nervosa (AN), whose self-starvation appears both excessively goal directed and habitual. However, these laboratory-based studies have not aimed to examine complex behavior, as seen outside the laboratory, in contexts that extend beyond monetary rewards. We therefore assessed (1) whether behavior in AN was characterized by enhanced or diminished model-based behavior, (2) the domain specificity of any abnormalities by comparing learning in a food-specific (i.e., illness-relevant) context as well as in a monetary context, and (3) whether impairments were secondary to starvation by comparing learning before and after initial treatment. Across all conditions, individuals with AN, relative to healthy controls, showed an impairment in model-based, but not model-free, learning, suggesting a general and persistent contribution of habitual over goal-directed control, across domains and time points. Thus, eating behavior in individuals with AN that appears very goal-directed may be under more habitual than goal-directed control, and this is not remediated by achieving weight restoration.

Dopamine is associated with prioritization of reward-associated memories in Parkinson's disease.

Patients with Parkinson's disease have reduced reward sensitivity related to dopaminergic neuron loss, which is associated with impairments in reinforcement learning. Increasingly, however, dopamine-dependent reward signals are recognized to play an important role beyond reinforcement learning. In particular, it has been shown that reward signals mediated by dopamine help guide the prioritization of events for long-term memory consolidation. Meanwhile, studies of memory in patients with Parkinson's disease have focused on overall memory capacity rather than what is versus what isn't remembered, leaving open questions about the effect of dopamine replacement on the prioritization of memories by reward and the time-dependence of this effect. The current study sought to fill this gap by testing the effect of reward and dopamine on memory in patients with Parkinson's disease. We tested the effect of dopamine modulation and reward on two forms of long-term memory: episodic memory for neutral objects and memory for stimulus-value associations. We measured both forms of memory in a single task, adapting a standard task of reinforcement learning with incidental episodic encoding events of trial-unique objects. Objects were presented on each trial at the time of feedback, which was either rewarding or not. Memory for the trial-unique images and for the stimulus-value associations, and the influence of reward on both, was tested immediately after learning and 2 days later. We measured performance in Parkinson's disease patients tested either ON or OFF their dopaminergic medications and in healthy older control subjects. We found that dopamine was associated with a selective enhancement of memory for reward-associated images, but that it did not influence overall memory capacity. Contrary to predictions, this effect did not differ between the immediate and delayed memory tests. We also found that while dopamine had an effect on reward-modulated episodic memory, there was no effect of dopamine on memory for stimulus-value associations. Our results suggest that impaired prioritization of cognitive resource allocation may contribute to the early cognitive deficits of Parkinson's disease.

Use of high-frequency repetitive transcranial magnetic stimulation to probe the neural circuitry of food choice in anorexia nervosa: A proof-of-concept study.

Repetitive transcranial magnetic stimulation (rTMS) is used to modulate neural systems and provides the opportunity for experimental tests of hypotheses regarding mechanisms underlying anorexia nervosa (AN). The present pilot study has investigated whether high-frequency repetitive transcranial magnetic stimulation (HF-rTMS) to a region of the right dorsolateral prefrontal cortex (DLPFC) might be associated with change in food selection among adult inpatients with AN. Ten women received one session of sham and one session of HF-rTMS targeting the right DLPFC while completing a computerized Food Choice Task. Compared to sham, HF-rTMS was associated with changes in food ratings and food choice: inpatients reported higher healthiness ratings of low- and high-fat foods and selected a significantly greater proportion of high-fat foods over a neutrally rated reference item while receiving HF-rTMS. Findings suggest that HF-rTMS to the right DLPFC was associated with a reduction of fat avoidance on a food choice task among inpatients with AN and provide additional support for the possibility that this region, and related neural circuits, may underlie restrictive food choice. Research using rTMS to experimentally test neural mechanisms is needed to elucidate the underpinnings of AN and supports the development of novel treatment targets.

A comparison of food-based decision-making between restricting and binge-eating/purging subtypes of anorexia nervosa.

OBJECTIVE: By definition, restricting (ANR) and binge-eating/purging (ANBP) subtypes of anorexia nervosa (AN) differ in some manifestations of maladaptive eating behavior. This study aimed to determine whether the groups differ in the choices they make about what to eat, and whether there are differences in valuation related to food choice, using an experimental paradigm. METHOD: Inpatients with ANR (n = 40) and ANBP (n = 46) participated in a Food Choice Task. During the task, participants rated 76 food images for healthiness and tastiness, and choice preferences. Groups were compared in percent selection of high-fat and low-fat foods, value ratings of foods, and engagement of self-control in food choice. RESULTS: There were no differences between AN subtypes in healthiness or tastiness ratings, or in tendency to limit choice of high-fat foods. There was no difference between the groups in measures of self-control in food choice. DISCUSSION: Individuals with ANR and ANBP similarly manifest reduced choices of high-fat foods, with similar tendencies to undervalue the tastiness of high-fat foods. These results suggest that while individuals with ANR and ANBP differ across a range of clinical characteristics, the decision-making process associated with the maladaptive restriction of high-fat foods characteristic of AN is shared by both subtypes.

The effect of repetitive transcranial magnetic stimulation on food choice-related self-control in patients with severe, enduring anorexia nervosa.

OBJECTIVE: Individuals with anorexia nervosa (AN) pursue low-fat, low-calorie diets even when in a state of emaciation. These maladaptive food choices may involve fronto-limbic circuitry associated with cognitive control, habit, and reward. We assessed whether high-frequency repetitive transcranial magnetic stimulation (rTMS) to the left dorsolateral prefrontal cortex (DLPFC) influenced food-related choice behavior in patients with severe, enduring (SE)-AN. METHOD: Thirty-four females with SE-AN completed a Food Choice Task before and after 20 sessions of real or sham rTMS treatment and at a 4-month follow-up. During the task, participants rated high- and low-fat food items for healthiness and tastiness and then made a series of choices between a neutral-rated food and high- and low-fat foods. Outcomes included the proportion of high-fat and self-controlled choices made. A comparison group of 30 healthy women completed the task at baseline only. RESULTS: Baseline data were consistent with previous findings: relative to healthy controls, SE-AN participants showed a preference for low-fat foods and exercised self-control on a greater proportion of trials. There was no significant effect of rTMS treatment nor time on food choices related to fat content. However, among SE-AN participants who received real rTMS, there was a decrease in self-controlled food choices at post-treatment, relative to baseline. Specifically, there was an increase in the selection of tasty-unhealthy foods. DISCUSSION: In SE-AN, rTMS may promote more flexibility in relation to food choice. This may result from neuroplastic changes in the DLPFC and/or in associated brain areas.

Dynamic Flexibility in Striatal-Cortical Circuits Supports Reinforcement Learning.

Complex learned behaviors must involve the integrated action of distributed brain circuits. Although the contributions of individual regions to learning have been extensively investigated, much less is known about how distributed brain networks orchestrate their activity over the course of learning. To address this gap, we used fMRI combined with tools from dynamic network neuroscience to obtain time-resolved descriptions of network coordination during reinforcement learning in humans. We found that learning to associate visual cues with reward involves dynamic changes in network coupling between the striatum and distributed brain regions, including visual, orbitofrontal, and ventromedial prefrontal cortex (n = 22; 13 females). Moreover, we found that this flexibility in striatal network coupling correlates with participants' learning rate and inverse temperature, two parameters derived from reinforcement learning models. Finally, we found that episodic learning, measured separately in the same participants at the same time, was related to dynamic connectivity in distinct brain networks. These results suggest that dynamic changes in striatal-centered networks provide a mechanism for information integration during reinforcement learning.SIGNIFICANCE STATEMENT Learning from the outcomes of actions, referred to as reinforcement learning, is an essential part of life. The roles of individual brain regions in reinforcement learning have been well characterized in terms of updating values for actions or cues. Missing from this account, however, is an understanding of how different brain areas interact during learning to integrate sensory and value information. Here we characterize flexible striatal-cortical network dynamics that relate to reinforcement learning behavior.

The Role of Habits in Anorexia Nervosa: Where We Are and Where to Go From Here?

PURPOSE OF REVIEW: The persistent maladaptive eating behavior characteristic of anorexia nervosa (AN) can be understood as a learned habit. This review describes the cognitive neuroscience background and the existing data from research in AN. RECENT FINDINGS: Behavior is habitual after it is frequently repeated and becomes nearly automatic, relatively insensitive to outcome, and mediated by dorsal frontostriatal neural systems. There is evidence for such behavior in AN, in which restrictive intake has been related to dorsal frontostriatal systems. Other neural and neurocognitive data provide mixed findings, some of which suggest disturbances in habit systems in AN. There are compelling behavioral and neural data to suggest that habit systems may underlie the persistence of AN. The habit model needs further research, via more direct behavioral hypothesis testing and probes of the development of habitual behavior. Investigation of the habit-centered model of AN may open avenues for the development of novel treatments.

Assessment of test-retest reliability of a food choice task among healthy individuals.

Aberrations in eating patterns constitute a substantial public health burden. Computer-based paradigms that measure responses to images of foods are potentially useful tools for assessing food attitudes and characteristics of eating behavior. In particular, food choice tasks attempt to directly probe aspects of individuals' decisions about what to eat. In the Food Choice Task participants rate the healthiness and tastiness of a variety of food items presented one at a time. Next, participants choose for each food item whether they prefer to eat the item vs. a neutrally rated reference food item. The goal of the current study was to assess the stability and reliability of this Food Choice Task over time and with repeated testing. Secondary analyses were conducted using data from healthy volunteers in two separate studies that administered the task at two time points, separated either by several days or about a month. The overall reliability of the Food Choice Task across multiple administrations was assessed using intra-class correlation coefficients and the reliability of ratings of individual food items was assessed using kappa coefficients. The results indicated that test-retest reliability of the Food Choice Task in healthy volunteers was high at both shorter and longer test-retest intervals. In addition, the reliability of individual food item ratings was good for a majority of items. The proportion of healthy volunteers' high-fat food choices did not change over time in either of the two studies. Thus, the Food Choice Task is suitable for measuring food choices in studies with multiple assessment points. In particular, the task may be well suited to assess restrictive eating, a construct which it has been difficult to assess in experimental settings.

Dopamine selectively remediates 'model-based' reward learning: a computational approach.

Patients with loss of dopamine due to Parkinson's disease are impaired at learning from reward. However, it remains unknown precisely which aspect of learning is impaired. In particular, learning from reward, or reinforcement learning, can be driven by two distinct computational processes. One involves habitual stamping-in of stimulus-response associations, hypothesized to arise computationally from 'model-free' learning. The other, 'model-based' learning, involves learning a model of the world that is believed to support goal-directed behaviour. Much work has pointed to a role for dopamine in model-free learning. But recent work suggests model-based learning may also involve dopamine modulation, raising the possibility that model-based learning may contribute to the learning impairment in Parkinson's disease. To directly test this, we used a two-step reward-learning task which dissociates model-free versus model-based learning. We evaluated learning in patients with Parkinson's disease tested ON versus OFF their dopamine replacement medication and in healthy controls. Surprisingly, we found no effect of disease or medication on model-free learning. Instead, we found that patients tested OFF medication showed a marked impairment in model-based learning, and that this impairment was remediated by dopaminergic medication. Moreover, model-based learning was positively correlated with a separate measure of working memory performance, raising the possibility of common neural substrates. Our results suggest that some learning deficits in Parkinson's disease may be related to an inability to pursue reward based on complete representations of the environment.

Decreased feedback learning in anorexia nervosa persists after weight restoration.

OBJECTIVE: Anorexia Nervosa (AN) is a serious disorder, with a mortality rate the highest of any psychiatric illness. It is notoriously challenging to treat and mechanisms of illness are not well understood. Reward system abnormalities have been proposed across theoretical models of the persistence of AN. Feedback learning is an important component of how reward systems shape behavior and we hypothesized that individuals with AN would show poorer learning from feedback. METHODS: We administered the acquired equivalence task to measure both learning from incremental feedback and generalization of that learning to novel stimuli. Participants were individuals with AN (n = 36) before and after intensive weight restoration treatment and healthy comparison participants (HC, n = 26) tested twice. Performance was assessed as accuracy during the Learning and Test phases, for both trained and novel stimuli. The relationship between task performance and eating disorder severity at baseline was also assessed. RESULTS: Both before and after treatment, individuals with AN showed reduced learning from feedback in the Learning phase (F3,180 = 2.75, p = .048) and lower accuracy during the Test phase (F1,60 = 4.29, p = .043), as compared with HC. Individuals with AN did not differ from HC in accuracy for novel stimuli (F1,60 = 1.04, p = .312), indicating no deficit in generalization. Decreased acquisition of feedback learning was associated with longer illness duration and with greater eating disorder symptom severity at baseline. CONCLUSIONS: Individuals with AN show reduced learning from feedback or reinforcement, which may contribute to difficulties in changing maladaptive behaviors.

Dopamine Modulation of Intertemporal Decision-making: Evidence from Parkinson Disease.

Choosing between smaller prompt rewards and larger later rewards is a common choice problem, and studies widely agree that frontostriatal circuits heavily innervated by dopamine are centrally involved. Understanding how dopamine modulates intertemporal choice has important implications for neurobiological models and for understanding the mechanisms underlying maladaptive decision-making. However, the specific role of dopamine in intertemporal decisions is not well understood. Dopamine may play a role in multiple aspects of intertemporal choices--the valuation of choice outcomes and sensitivity to reward delays. To assess the role of dopamine in intertemporal decisions, we tested Parkinson disease patients who suffer from dopamine depletion in the striatum, in either high (on medication, PDON) or low (off medication, PDOFF) dopaminergic states. Compared with both PDOFF and healthy controls, PDON made more farsighted choices and reduced their valuations less as a function of increasing time to reward. Furthermore, reduced discounting in the high dopaminergic state was robust across multiple measures, providing new evidence for dopamine's role in making decisions about the future.

Restrictive food intake as a choice--a paradigm for study.

OBJECTIVE: Inadequate intake and preference for low-calorie foods are salient behavioral features of Anorexia Nervosa (AN). The neurocognitive mechanisms underlying pathological food choice have not been characterized. This study aimed to develop a new paradigm for experimentally modeling maladaptive food choice in AN. METHOD: Individuals with AN (n = 22) and healthy controls (HC, n = 20) participated in a computer-based Food Choice Task, adapted for individuals with eating disorders. Participants first rated 43 food images (including high-fat and low-fat items) for Healthiness and Tastiness; an item rated neutral on both blocks was then selected as the Reference item. On each of 42 subsequent trials participants were asked to choose between the food item presented and the Reference item. RESULTS: The AN group was less likely to choose high-fat foods relative to HC, as evidenced both in multilevel logistic regression (z = 2.59, p = .009) and ANOVA (F(1,39) = 7.80, p = .008) analyses. Health ratings influenced choice significantly more in AN relative to HC (z = 2.7, p = .006), and were more related to Taste among AN (χ(2) = 4.10, p = .04). Additionally, taste ratings declined with duration of illness (r = -.50, p = .02). DISCUSSION: The Food Choice Task captures the preference for low-fat foods among individuals with AN. The findings suggest that the experience of tastiness changes over time and may contribute to perpetuation of illness. By providing an experimental quantitative measure of food restriction, this task opens the door to new experimental investigations into the cognitive, affective, and neural factors contributing to maladaptive food choices characteristic of AN.

A role for the medial temporal lobe in feedback-driven learning: evidence from amnesia.

The ability to learn from feedback is a key component of adaptive behavior. This type of learning is traditionally thought to depend on neural substrates in the striatum and not on the medial temporal lobe (MTL). Here we show that in humans the MTL becomes necessary for feedback-based learning when feedback is delayed. Specifically, amnesic patients with MTL damage were impaired at probabilistic learning of cue-outcome associations when response-contingent feedback was delayed by a few seconds, but not when feedback was immediate. By contrast, patients with striatal dysfunction due to Parkinson's disease demonstrated the opposite pattern: impaired learning when trial-by-trial feedback was immediate but not when feedback was delayed, indicating that the striatum is necessary for learning only when feedback is immediate. Together, these results reveal that multiple complementary learning processes support what appears to be identical behavior in healthy individuals and point to an important role for the MTL in feedback-driven learning.

A trade-off between feedback-based learning and episodic memory for feedback events: evidence from Parkinson's disease.

Parkinson's disease (PD) is characterized by a loss of dopaminergic projections to the striatum, leading to both motor and cognitive impairments. The cognitive impairments are relatively selective and include deficits in incremental learning from trial-by-trial feedback, while other forms of learning, such as hippocampal-dependent episodic memory, remain intact. Interestingly, it has been suggested that the striatum and the hippocampus compete during learning, leading to the intriguing prediction that the striatal disruption in PD could lead to enhanced performance on tasks that depend on the hippocampus. We tested this prediction by simultaneously assessing incremental learning and episodic memory for trial-unique feedback events, within a single task, in patients with PD. Further, in order to modulate the engagement of the striatum versus the hippocampus, we manipulated the timing of feedback during learning, building on prior results showing that delaying feedback by a few seconds shifts learning to depend on the hippocampus instead of the striatum. We found that Parkinson's patients were impaired at learning from immediate feedback, but had enhanced episodic memory for those immediate feedback events. Thus, our results provide evidence for concurrent impaired and enhanced learning and memory functions within the same group of patients from a single task.

Large-Scale Exploration of Whole-Brain Structural Connectivity in Anorexia Nervosa: Alterations in the Connectivity of Frontal and Subcortical Networks.

BACKGROUND: Anorexia nervosa (AN) is characterized by disturbances in cognition and behavior surrounding eating and weight. The severity of AN combined with the absence of localized brain abnormalities suggests distributed, systemic underpinnings that may be identified using diffusion-weighted magnetic resonance imaging and tractography to reconstruct white matter pathways. METHODS: Diffusion-weighted magnetic resonance imaging data acquired from female patients with AN (n= 147) and female healthy control (HC) participants (n = 119), ages 12 to 40 years, were combined across 5 studies. Probabilistic tractography was completed, and full-cortex connectomes describing streamline counts between 84 brain regions were generated and harmonized. Graph theory methods were used to describe alterations in network organization in AN. The network-based statistic tested between-group differences in brain subnetwork connectivity. The metrics strength and efficiency indexed the connectivity of brain regions (network nodes) and were compared between groups using multiple linear regression. RESULTS: Individuals with AN, relative to HC peers, had reduced connectivity in a network comprising subcortical regions and greater connectivity between frontal cortical regions (p < .05, familywise error corrected). Node-based analyses indicated reduced connectivity of the left hippocampus in patients relative to HC peers (p < .05, permutation corrected). Severity of illness, assessed by body mass index, was associated with subcortical connectivity (p < .05, uncorrected). CONCLUSIONS: Analyses identified reduced structural connectivity of subcortical networks and regions, and stronger cortical network connectivity, among individuals with AN relative to HC peers. These findings are consistent with alterations in feeding, emotion, and executive control circuits in AN, and may direct hypothesis-driven research into mechanisms of persistent restrictive eating behavior.

Feedback timing modulates brain systems for learning in humans.

The ability to learn from the consequences of actions--no matter when those consequences take place--is central to adaptive behavior. Despite major advances in understanding how immediate feedback drives learning, it remains unknown precisely how the brain learns from delayed feedback. Here, we present converging evidence from neuropsychology and neuroimaging for distinct roles for the striatum and the hippocampus in learning, depending on whether feedback is immediate or delayed. We show that individuals with striatal dysfunction due to Parkinson's disease are impaired at learning when feedback is immediate, but not when feedback is delayed by a few seconds. Using functional imaging (fMRI) combined with computational model-derived analyses, we further demonstrate that healthy individuals show activation in the striatum during learning from immediate feedback and activation in the hippocampus during learning from delayed feedback. Additionally, later episodic memory for delayed feedback events was enhanced, suggesting that engaging distinct neural systems during learning had consequences for the representation of what was learned. Together, these findings provide direct evidence from humans that striatal systems are necessary for learning from immediate feedback and that delaying feedback leads to a shift in learning from the striatum to the hippocampus. The results provide a link between learning impairments in Parkinson's disease and evidence from single-unit recordings demonstrating that the timing of reinforcement modulates activity of midbrain dopamine neurons. Collectively, these findings indicate that relatively small changes in the circumstances under which information is learned can shift learning from one brain system to another.