The contribution of brain reward circuits to the obesity epidemic (2013)

Neurosci Biobehav Rev. Author manuscript; available in PMC 2014 Nov 1.

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One of the defining characteristics of the research of Ann E. Kelley was her recognition that the neuroscience underlying basic learning and motivation processes also shed significant light upon mechanisms underlying drug addiction and maladaptive eating patterns. In this review, we examine the parallels that exist in the neural pathways that process both food and drug reward, as determined by recent studies in animal models and human neuroimaging experiments. We discuss contemporary research that suggests that hyperphagia leading to obesity is associated with substantial neurochemical changes in the brain. These findings verify the relevance of reward pathways for promoting consumption of palatable, calorically dense foods, and lead to the important question of whether changes in reward circuitry in response to intake of such foods serve a causal role in the development and maintenance of some cases of obesity. Finally, we discuss the potential value for future studies at the intersection of the obesity epidemic and the neuroscience of motivation, as well as the potential concerns that arise from viewing excessive food intake as an “addiction”. We suggest that it might be more useful to focus on overeating that results in frank obesity, and multiple health, interpersonal, and occupational negative consequences as a form of food “abuse”.

Keywords: Obesity, feeding, reward, reinforcement, mesolimbic dopamine system, opioids, food addiction, drug addiction, food abuse

1. Introduction

One of the most alarming public health threats during the past 50 years is the increased prevalence of obesity. According to reports from the Centers for Disease Control, during the past three decades the average prevalence of obesity in the US adult population has risen from below 20% to 35.7% (). During the same period, childhood obesity has tripled to a rate of 17%. Currently, more than 1/3 of all children and adolescents are overweight or obese. This high prevalence appears to have plateaued in the United States (; ), and continues to be a major public health concern: The collective medical costs of obesity within the United States were estimated at $147 billion in 2008 (), and continue to increase with the rising cost of health care. Obesity has become a global phenomenon; the World Health Organization estimates that obesity is responsible for up to 8% of health costs in Europe and over 10% of deaths ().

Obesity is a multifaceted problem, and its rapid increase in societies such as the U.S. is likely to have been brought about by several causes, both physiological and environmental. There has been a substantial change in the food environment over the past half century. In developed nations, the availability of palatable foods that are high in sugar, fat, and calories has transformed the modern food environment into one of abundance. Until the development of modern agricultural practices, food resources have been historically scarce, and thus human physiology evolved in an environment in which significant resources were required to forage for and consume sufficient calories. Physical activity also declined during this period, contributing to obesity. Across vertebrate species, central nervous system control of energy homeostasis includes behavioral regulation by hypothalamic neural circuits that monitor energy balance based upon peripheral endocrine and metabolic signals, and that serve to motivate us to seek food when energy resources are depleted. A subset of this circuitry, including that connected with the mesolimbic dopamine pathway, processes the hedonic and rewarding aspects of food and can promote the predisposition to overeat when presented with palatable and energy dense food sources. Food serves as a strong reinforcer, whether evaluated in controlled behavioral paradigms in the laboratory, or in naturalistic or societal circumstances.

The reinforcing attributes of drugs have always been, either explicitly or implicitly, linked to the reinforcement circuitry that serves to shape and select behavior based upon more natural (or physiologically relevant) rewards such as food, water, and sex. The early use of brain stimulation reward techniques and agents of abuse such as amphetamine in research both targeted and aided understanding of the neural pathways and mechanisms involved in positive reinforcement, broadly defined (e.g., ; ). Subsequent research, including that from the laboratory of Ann E. Kelley, demonstrated that the motivational circuitry that drugs of abuse act upon serves important and distinct roles in regulating the learning and motivation underlying natural reinforcement, particularly food. In two memorable reviews, Dr. Kelley emphasized the insight that basic neuroscience research into the mechanisms of reward () and learning and memory () provided in terms of understanding the processes and neural substrates that regulate adaptive behavior, and which are often driven in maladaptive ways by exposure to drugs of abuse and to the current food environment. Her scientific approach of examining the neural pathways, neurotransmitters, and molecular processes underlying learning and food motivation (reviewed elsewhere in this issue; see Andrzejewski et al., Baldo et al.) anticipated the work of many contemporary researchers interested in food and drug motivation and the intersection between the two topics.

Recently, it has been suggested that excess intake of palatable foods may be a problem akin to that of drug addiction. Although overeating is not a psychiatric disorder, like anorexia nervosa or bulimia nervosa, it represents consistently elevated non-homeostatic feeding. The apparent parallels that might be drawn between drug and food intake as “addictive” behaviors may lie, to some extent, in the overlapping neural circuitry that is engaged by both types of motivated behaviors. However, the fact that drugs of abuse activate reinforcement circuitry involved in feeding behavior is not sufficient evidence to deduce that excessive intake of high-calorie palatable food is therefore akin to a “food addiction”. For such an argument to be made, there must first be agreement upon what qualifies as an addiction, and evidence must be provided that the “addictive” intake of food parallels the behavioral patterns and physiological processes of other addictive behaviors.

The main goal of this review will be to provide a brief overview of recent research demonstrating the overlap between brain reward/reinforcement circuits as they relate to food- and drug-motivated behavior. Evidence from studies with both humans and animals will be examined. First, we will discuss the interplay between metabolic signals that monitor energy balance and the motivational circuitry that regulates the rewarding value of food and drug reinforcement. We will then discuss the ways in which food and drugs of abuse activate similar neural pathways and affect motivated behavior, how reward/reinforcement circuitry is changed by drug use or the consumption of energy-dense foods, as well as how the brain responds differently to food or drugs of abuse. Finally, we will discuss the implications from this literature review regarding the heuristic value of invoking an addiction process as it relates to overeating and obesity, including the potential insights from viewing overeating patterns as an “addiction”, as well as the challenges/problems/social concerns that arise from such a characterization. We suggest instead that it might be more useful to consider overeating that results in multiple negative health, interpersonal, and occupational consequences as “food abuse”.

2. From Motivation to Action: Metabolic influences on reward circuits

That the mesolimbic dopaminergic pathway is involved in the reinforcing and addictive properties of drugs of abuse has been well documented ever since reported that catecholaminergic lesions of the nucleus accumbens reduced self-administration of cocaine in a rodent model. As reviewed below, both the human and rodent literature is replete with examples of how the dopaminergic and opioid systems within the substantia nigra, ventral tegmentum, and their projections to the striatum are affected by drugs of abuse. Natural reinforcers also affect behavior through these same pathways (e.g., ; ; ). Despite this understanding, it is only recently that food, and hyperpalatable foods in particular, have been posited to be potentially “addictive”. This may in part be due to the fact that many early researchers interested in obesity focused upon the dysregulation of metabolic processes that result from gaining excess weight. Obesity is a complex metabolic syndrome that is characterized by energy dyshomeostasis and involves not only the brain, but also basic biochemical reactions within liver, fat, and muscle tissue. Early lines of research evolved, from the 1970s forward, that considered energy homeostasis—the regulation of feeding and regulation of body weight metabolism—as a separate CNS-regulated function from appetitive motivation. However, there has always been evidence that such a dichotomy between metabolic regulation and motivated behavior might be overly simplistic. In 1962, Margules and Olds observed that both feeding and self-stimulation could be induced by electrical stimulation of identical sites within the lateral hypothalamus (LH); self-stimulation is a paradigm by which an animal presses a lever and receives a small, direct electrical stimulation of the site into which a probe is implanted. The LH was identified as a major target for self-stimulation activity and it was concluded that it was part of intrinsic ‘reward circuitry’ within the brain. Subsequently, reported that this self-stimulation activity could be enhanced by food deprivation. The extensive research of Marilyn Carroll and colleagues from the 1980s onward (e.g., ), in both animal models and humans, made it clear that the ‘addictiveness’ of rewarding substances such as drugs of abuse could be modified by metabolic states, including how and whether the subjects were fed.

How is the reward circuitry ‘informed’ of an animal’s nutritional status? Research has revealed that the CNS circuitry, transmitters, and the peripheral signals that inform the CNS of metabolic and nutritional status all impact directly and indirectly on the key substrates of motivation, particularly the mesolimbic dopamine neurons and their projections from the ventral tegmental area (VTA) to the nucleus accumbens (). Teleologically, it makes sense that motivation to seek food would be greater in circumstances of food deprivation, and conversely, food would be less ‘rewarding’ under circumstances of repletion. This phenomenon, which resides in CNS crosstalk between these circuitries and endocrine/neuroendocrine signals, would of course be dramatically manifest in subjects taking drugs that directly and strongly activate mesolimbic circuitry. Thus, ingestion of calorically dense palatable foods may override the circuitry of energy homeostasis; and they may also override homeostatic restraints on dopaminergic and other components of the reward circuitry.

The key endocrine signals that reflect the acute and chronic energy status of an animal have direct effects on dopaminergic function. For example, the hormones insulin and leptin, which correlate with caloric repletion and energy stores in adipose tissue, not only affect hypothalamic regulation of energy homeostasis but also reduce dopamine release, facilitate its synaptic re-uptake, and can decrease dopamine neuronal excitability (; ). In contrast, the gut hormone ghrelin, which is elevated in association with caloric deprivation, enhances dopaminergic function (; Perello and Zigman, 2012). All three of these hormones have predictable effects in animal models on ‘reward tasks’ in which solid or liquid foods serve as the reward. Insulin and leptin decrease food reward, and ghrelin enhances it. Specifically, ghrelin enhances place preference conditioning and the self-administration of rewarding foods (; Perello and Zigman, 2012). Both insulin and leptin decrease rewarding self-stimulation behavior; leptin appears effective in animals that are food-restricted, and insulin likewise is effective in both food-restricted and diabetic (hence, insulinopenic) animals, when either are administered directly into the cerebral ventricles. Studies in the 2000s demonstrated that insulin and leptin can decrease food reward in rats assessed by two different tasks: conditioning of a place preference for a food treat () and self-administration of sucrose solutions (). In the self-administration study, insulin and leptin were ineffective in animals fed a high fat diet, compared with low-fat chow (). This observation of an effect of a high fat background diet is a clue that qualitative changes in the macronutrient composition of the background diet can impact food reward: In addition to the blockade of insulin and leptin effects, the high fat diet-fed animals showed an increase in sucrose self-administration relative to (low fat) chow-fed controls. Additional animal studies have demonstrated that higher fat diets, or longer diet exposures, can result in suppression of dopamine synthesis, release or turnover, and reductions in motivated behaviors, not limited to motivation for food (e.g., ). Although the underlying mechanisms for this phenomenon have not been completely elucidated, the involvement of intrinsic CNS circuitry and transmitters has been identified in food reward behavior and function and suggests, indeed, multiple links between feeding, nutritional status, and reward circuitry. Recent research has demonstrated that multiple medial hypothalamic nuclei (the arcuate [ARC], paraventricular [PVN], and ventromedial [VMN]) are active at the onset of sucrose self-administration (). Further, the ability of the peripheral satiety signal insulin to decrease sucrose self-administration is localized to the ARC (). Recent research from several labs has demonstrated that the ARC-based orexigenic neuropeptide, agouti-related protein (AGRP), can stimulate motivation for food, assessed in multiple paradigms, in the mouse and rat (; , ). Since ARC AGRP neurons project to the PVN, which in turn relays to the LH, this represents a major hypothalamic transmitter system that can enhance motivated, “addictive” behavior.

As noted, the lateral hypothalamus (LH) is a key site within reward circuitry. The effect of food restriction or fasting on increased self-stimulation activity can be reversed by direct CNS administration of the satiety hormones insulin and leptin. Although identification of the precise mechanisms for these effects is not yet clear, it should be noted that within the LH are, first, projections to the VTA dopaminergic neurons, and, second, populations of orexin neurons. Orexin is known to stimulate feeding, and also arousal, and functional anatomy has determined that the LH orexin neurons are not only critical for arousal but are important modulators of motivational function and circuitry. There are reports of orexin involvement in feeding of palatable foods and reward-based paradigms (food self-administration and sucrose seeking). These effects of orexin appear to be substantially influenced by the paradigm used and the nutritional state of the animal ().

Thus, homeostasis-regulating factors co-modulate motivational circuitry and function, both directly and indirectly (for a summary of the relevant neural pathways involved, see Figure 1). These findings have, for the most part, been elucidated in non-obese rodents, although numerous studies have evaluated rodents after consumption of a high fat diet. One notable study accomplished with humans found that administration of leptin to two obese human patients with congenital leptin deficiency modulated neural striatal response to palatable food images (fMRI measurement), providing direct support for a role of basal leptin in blunting reward circuitry (). This finding was extended by evidence that blocking the expression of leptin receptors in the VTA (the site of dopaminergic cell bodies) resulted in increased sucrose self-administration in rodents (). The advantage of carrying out such studies in rodents is that the time course and other stimulus aspects of high fat diet exposure, during pre-obesity or at established obesity, allow for the study of development or adaptation to diet effects, ultimately at the level of the mesolimbic dopaminergic circuitry. For the purpose of this article, the important point is that high fat diet and diet-induced obesity are known to modulate efficacy of peripheral endocrine signals, as well as hypothalamic signaling systems (). Animal studies allow us to find out about initiating events in this process. The use of functional CNS imaging approaches in humans also provides a powerful tool for determining how the human brain changes as a result of diet experience and obesity. Given that diet and obesity can have dramatic effects on homeostatic circuitry, it is to be expected that diet and obesity likewise have substantial effects on the functioning of motivational circuitry, both when it comes to patterns of feeding or drug intake.

Figure 1 

Integrative signaling of homeostatic and hedonic feeding in the CNS. Major monosynaptic connections are shown, emphasizing the extensive anatomical interconnectivity of functional sets of circuitry that mediate aspects of feeding. Green-framed boxes represent

3. Food and Drug Effects within Reward Circuitry

3.1. Effects of Drug Use and Palatable Food Intake on Mesolimbic Circuitry

In both animal and human models, several parallels have been shown between the effects of use of drugs of abuse and palatable foods intake on mesolimbic circuitry. First, acute administration of abused drugs causes activation of the VTA, nucleus accumbens, and other striatal regions according to studies with humans and other animals (; ). Consumption of palatable food likewise causes increased activation in the midbrain, insula, dorsal striatum, subcallosal cingulate, and prefrontal cortex in humans and these responses decrease as a function of satiety and reduced pleasantness of the foods consumed (; ).

Second, humans with, versus without, various substance use disorders show greater activation of reward regions (e.g., amygdala, dorsolateral prefrontal cortex [dlPFC], VTA, prefrontal cortex) and attention regions (anterior cingulate cortex [ACC]) and report greater craving in response to substance use cues (e.g., ; ; ; ; ). Craving in response to cues correlates with the magnitude of dorsal striatum dopamine release (the latter being inferred from the measure of 11C-raclopride uptake; ) and with activation in the amygdala, dlPFC, ACC, nucleus accumbens, and orbitofrontal cortex (OFC; ; ; ). In a similar fashion, obese versus lean humans show greater activation of regions that play a role in encoding the reward value of stimuli, including the striatum, amygdala, orbitofrontal cortex [OFC], and mid-insula; in attention regions (ventral lateral prefrontal cortex [vlPFC]); and in somatosensory regions, in response to high-fat/high-sugar food images relative to control images (e.g., ; ; ; ; ; ). These findings in humans closely parallel regions that are activated by cues associated with drugs and palatable food in rats (). There is also some evidence that obese versus lean humans show reduced activation in inhibitory control regions in response to palatable food images versus control images (e.g., ; ). Obese versus lean humans likewise show elevated activation in reward valuation and attention regions in response to cues that signal impending high-fat/high-sugar food receipt versus control cues that signal impending receipt of tasteless solution (; ). A meta-analytic review found considerable overlap in the reward valuation regions activated in response to palatable food images in humans and brain reward regions activated by drug cues among drug dependent humans ().

These data confirm that drugs of abuse and palatable foods, as well as the cues that predict drug and food reward, activate similar regions that have been implicated in reward and reward learning. The circuits involved include the mesolimbic dopamine system, which projects from the VTA to the medial ventral striatum. The following sections emphasize the overlapping nature of the effects of food and drug reward on dopaminergic and opioid signaling within this critical reward pathway.

3.2. Effects of Drug Use and Palatable Food Intake on Dopamine Signaling

In addition to the parallels observed across food and drug intake on neuronal activity, there are also striking parallels in terms of the effects of drugs of abuse and palatable food intake on dopamine signaling. First, intake of commonly abused drugs causes dopamine release in the striatum and associated mesolimbic regions (; ; ; ; , ). Palatable food intake likewise causes dopamine release in the nucleus accumbens in animals (). Consumption of high-fat and high-sugar palatable food is similarly associated with dopamine release in the dorsal striatum and the magnitude of release correlates with ratings of meal pleasantness in humans (). Second, dopamine is released in the dorsal striatum of the rat during drug seeking behavior (). Similarly, responding to earn palatable food is also associated with increased phasic dopamine signaling (). Third, exposure to cues that signal the availability of the administration of commonly abused drugs, such as tones or a light, cause phasic dopamine signaling after a period of conditioning in rodents (). However, visual and olfactory exposure to palatable food has not been shown to change availability of D2 receptors in the striatum in two separate studies (; ), suggesting that food cue exposure does not produce detectable effects on extracellular dopamine in the striatum, at least in human studies with very small samples.

3.3. The Role of Opioids in Food Reward

Research has revealed that opioid peptides and their receptors play a role in the regulation of food intake, and that the mu opioid system appears to be particularly involved in mediating food reward (see ; , ; ; for reviews). Evidence for this involvement includes findings that opioid agonists and antagonists generally are more effective in increasing and decreasing, respectively, the intake of palatable foods or fluids than that of standard chow or water. Human studies suggest that opioid antagonists generally decrease ratings of taste pleasantness without affecting taste perception (). In animal models, the mu opioid agonist DAMGO will stimulate food intake when microinjected into several brain sites, including the nucleus of the solitary tract, parabrachial nucleus, various nuclei within the hypothalamus (notably the paraventricular nucleus), the amygdala (notably the central nucleus), nucleus accumbens, and VTA (see ; ; ). Finally, several studies indicate differences in brain opioid peptides and receptors in rats exposed to highly palatable food (when compared to rats fed chow; ; ; ; ; ; ).

Generally, the ingestion of highly palatable food is associated with increased mu opioid receptor gene expression in multiple brain areas, and changes (increases or decreases) in opioid peptide precursor mRNA in many of the same areas. It has been suggested that increases in mu opioid receptors may reflect reduced peptide release () and that reduced enkephalin expression may be a compensatory down-regulation (). There is also some evidence of differences in opioid peptide or receptor gene expression that can be attributed to preferences for a given diet rather than to actual consumption of that diet. For example, selected rats with a high or low preference for a high fat diet based on intake measures over a 5-day period. After a 14-day period of maintenance only on rat chow, there was increased proenkephalin expression in the PVN, nucleus accumbens and the central nucleus of the amygdala in the rats with a high preference for the high fat diet. The authors suggest that this effect represents an inherent characteristic of the fat-preferring rats, as opposed to an effect due to intake of the diet. Similarly, Osborne-Mendel rats, known to be susceptible to diet-induced obesity, when compared to rats of a strain known to be resistant to diet-induced obesity (S5B/Pl) showed an increased level of mu opioid receptor mRNA in the hypothalamus ().

The complex role of opioids in the control of feeding has great significance for the understanding of eating disorders and obesity. Opioid antagonists, particularly naloxone and naltrexone, have been shown to reduce food intake in normal-weight and obese participants in short-term trials (; ). Unfortunately, these antagonists have adverse side effects (e.g., nausea and elevation of liver function tests) that have precluded their widespread use in the treatment of obesity and eating disorders; it was suggested that newer opioid antagonists may offer a more favorable risk/benefit ratio (). One compound that shows promise in this regard is GSK1521498, a mu opioid receptor inverse agonist. This drug, which is reported to have a favorable safety and tolerability profile, has been shown to reduce hedonic ratings of high-sugar and high-fat dairy products, to reduce caloric intake of snack foods, an to reduce fMRI-assessed activation of the amygdala induced by palatable food (; ). Finally, recent genetic analyses indicate that variants in the human mu opioid receptor gene (OPRM1) are associated with variability in preference for sweet and fatty foods. Humans with the G/G genotype of the functional A118G marker of this gene reported higher preferences for foods with high fat and/or sugar than humans with the G/A and A/A genotypes (). It was also observed that, in obese humans, a subgroup with binge eating disorder had an increased frequency of the G allele at the A118G marker of the mu opioid receptor gene compared to obese subjects without binge eating disorder (). Thus, human genetic analyses support the results of pharmacological studies that indicate a role for opioids in mediating food palatability and reward, and suggest that variations in mu opioid receptors are associated with disordered eating. It addition to the role of opioids in mediating food reward, they may also facilitate eating by attenuating satiety and/or aversion. This effect may be mediated via the inhibition of a central oxytocin (OT) system. OT reduces food intake, and OT neuronal activation is greater toward the end of feeding than at the initiation of feeding (; ). The opioid agonist butorphanol reduced this OT activation (). In what may be a related action, OT is thought to contribute to the formation of a conditioned taste aversion, and pretreatment with various opioid receptor ligands inhibited activity of OT neurons precipitated by lithium chloride in a conditioned taste aversion (CTA) procedure (; ). This opioid-induced decrease in OT neuronal activity was associated with a diminished aversive responsiveness in rats. In line with a proposed relation between opioid-driven feeding reward and the OT system, long-term exposure to a high-sugar diet caused a down-regulation of OT neuronal responsiveness to a food load, an effect that may contribute to elevated intakes of rewarding tastants (). This idea is supported by a report that OT knockout mice over-consume carbohydrate solutions, but not lipid emulsions ().

3.4. Positive Relations Between Food/Taste Preferences and Drugs of Abuse

Behavioral studies with rats indicate that relative propensity to consume (or self-administer) palatable foods is often positively related to drug self-administration. Rats selectively bred for high or low sweet preferences, or selected on the basis of their saccharin or sucrose intake, show corresponding high or low intakes of alcohol, cocaine, amphetamine and morphine (; ; ; ). Sucrose intake also enhances the rewarding and analgesic effects of morphine (; ), increases behavioral sensitization to the DR2 agonist quinpirole, cocaine, and amphetamine (; ; ), and enhances the discriminative stimulus effects of nalbuphine, a mu opioid receptor agonist (). As noted, intake of sucrose and other highly palatable foods causes an up-regulation of mu opioid receptors; this change may underlie many of the aforementioned behavioral effects.

In humans, an increased preference for sweet solutions has been observed in subjects with alcoholism and/or a family history of alcoholism (, ; ), although this relationship was not observed in other studies (; ). Interestingly, a high preference for sweet tastes has been suggested as a possible predictor of non-abstinence in alcohol-dependent subjects () and as a possible predictor of efficacy of naltrexone in reducing relapses to heavy drinking (). Opioid dependent subjects also report increases in craving, intake and/or preferences for sweet foods (; ; ; ).

3.5. Relation of Reward Region Responsivity to Future Increases in Drug Use and Weight Gain

Emerging evidence suggests parallels in individual differences in responsivity of reward regions to future onset of substance use and initial unhealthy weight gain. A large prospective study of 162 adolescents found that elevated responsivity in the caudate and putamen to monetary reward predicted initial onset of substance use among initially non-using teens (). These results dovetail with the well-replicated finding that greater responsivity of reward and attention regions to drug use cues in humans is also associated with increased risk for subsequent relapse (Gruser et al., 2004; ; ; ). Although elevated reward region responsivity did not predict initial unhealthy weight gain among healthy weight adolescents in the study by , those data extend prior evidence that found that greater responsivity of a region implicated in reward valuation (orbitofrontal cortex) to a cue signaling impending presentation of palatable food images predicted future weight gain ().

3.6. Effects of Habitual Drug Use and Palatable Food Intake on Dopamine Circuitry and Signaling

There is also evidence that habitual drug use and palatable food intake are associated with similar neural plasticity of reward circuitry. Animal experiments show that regular substance use reduces striatal D2 receptors (; ) and sensitivity of reward circuitry (; ). Data also indicate that habitual psychostimulant and opiate use causes increased DR1 binding, decreased DR2 receptor sensitivity, increased mu-opioid receptor binding, decreased basal dopamine transmission, and enhanced accumbens dopamine response (; ; ). Consistent with this, adults with, versus without, alcohol, cocaine, heroin, or methamphetamine dependence show reduced striatal D2 receptor availability and sensitivity (, , ; ). Further, human cocaine abusers show blunted dopamine release in response to stimulant drugs relative to controls (; ) and tolerance to the euphoric effects of cocaine ().

With regard to obesity, three human studies found that obese versus lean individuals showed reduced D2 binding potential in the striatum (; ; ; though the obese and healthy weight participants were not systematically matched on hours since last caloric intake in the former study and there was some overlap in the participants in the latter two studies), suggesting reduced D2 receptor availability, an effect that also emerged in obese versus lean rats (). Interestingly, also found that as the rats gained weight, they showed a further reduction in D2 binding potential, suggesting that overeating contributes to the reduction in D2 receptor availability. found that regular glucose intake on a limited-access schedule increases DR1 binding in the striatum and nucleus accumbens and decreases DR2 binding in the striatum and nucleus accumbens, in addition to other CNS alterations in the rat. Interestingly, intake of palatable food resulted in down regulation of striatal D1 and D2 receptors in rats relative to isocaloric intake of low-fat/sugar chow (), implying that it is intake of palatable energy dense foods versus a positive energy balance that causes plasticity of reward circuitry. These results prompted a study comparing reward region responsivity of lean adolescents (n=152) to their reported intake of ice cream over the past 2-weeks (). Ice cream intake was examined because it is particularly high in fat and sugar and was the primary source of these nutrients in the milkshake used in that fMRI paradigm. Ice cream intake was inversely related to activation in the striatum (bilateral putamen: right r = −.31; left r = −.30; caudate: r = −.28) and insula (r = −.35) in response to milkshake receipt (> tasteless receipt). Yet, total kcal intake over the past 2-weeks did not correlate with dorsal striatum or insula activation in response to milkshake receipt, suggesting that it is intake of energy dense food, rather than overall caloric intake that is related to reward circuitry activation. These findings are consistent with the observations of endocrine regulation of sucrose motivation described above–specifically, that effects of insulin and leptin occur at doses that are subthreshold for decreasing overall caloric intake and body weight–and emphasizes the pre-eminent sensitivity of reward circuitry and its plasticity with regards to food rewards.

4. Reward Circuits, “Food Addiction”, and Obesity

The above sections have outlined the potential importance of mesolimbic circuitry in regulating food intake, and have examined the parallels between food and drug reward as they relate to the dopamine and opioid systems within reward pathways. Several themes emerge from this review. First, consistent with the pioneering work of Ann Kelley, the overlap in the motivational systems engaged by drugs and food rewards is substantial. Second, to the extent that it has been examined, dietary manipulations and exposure to palatable diets often result in changes in opioid peptides, mu-opioid receptor availability, and D2 receptor expression that parallel those seen after repeated exposure to drugs of abuse. Third, there is evidence to suggest that, in both humans and animal models, individuals that have higher behavioral or physiological responses to palatable foods (due to either experience or genetic variation) are also more likely to have subsequent increases in body weight, and may be more sensitive to the rewarding effects of drugs of abuse.

It should be noted that there is also evidence demonstrating differential signaling of reward types within the brain: even within the nucleus accumbens, individual neurons tend to alter their firing rate in response to tasks that signal natural (water or food) reward or drug (cocaine) reward, but relatively few neurons encode both (). Further, it has been shown that inactivation or deep brain stimulation of the rat subthalamic nucleus, a separate node within basal ganglia motivational circuitry, reduces motivation for cocaine while leaving food motivation relatively intact (, ; ; , but see ). Other studies that have examined potential pharmaceutical treatments for reducing drug intake in animal models of self-administration have often used self-administration of food reward as the control condition (e.g., ; ). Presumably, the desire for pharmacotherapy of drug addiction is to reduce motivation for drug reward without simultaneously suppressing motivation for natural reinforcement. Thus, accumulating evidence suggests that natural rewards and drug rewards are distinguishable within brain reward circuitry, even though the same brain regions are involved in processing them.

Despite these caveats, the brain pathways involved in flexibly directing our behavior towards rewarding stimuli in the environment are similar, regardless of whether the reinforcement is food or a drug of abuse. But what do these findings suggest in terms of using a heuristic of “food addiction” to describe the elevated intake of calories that leads to obesity? First, it is important to note that many humans who consume energy dense foods do not become obese or show persistent overeating in the face of adverse consequences, just as the majority of humans who try an addictive drug like cocaine do not progress to regular use with negative consequences. Within animal models, only 9% of rats that engage in regular self-administration continue to do so in a manner that results in severe adverse health effects (e.g., the neglect of food intake; ). This is fairly similar to the finding that only 12-16% of the general human population aged 15-54 who try cocaine go on to develop cocaine addiction (; ).

As noted, obesity is a systemic metabolic disorder, whereas “addiction” is behaviorally defined. One difficulty in applying “addiction” to food intake is that the current version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR) does not define addiction per se as a mental disorder. It does define substance abuse and substance dependence, and there have been attempts to extrapolate from these drug-centered definitions a framework to apply to food and food intake (for critical evaluations of applying these to human obesity, see and ). The most successful attempt to do so to date is a report on rats trained to binge on sugar, and then subjected to behavioral tests that examined individual components of dependence, either in terms of examining the behavioral effects of sucrose abstinence, or by precipitating withdrawal symptoms after systemic injections of an opioid antagonist (; ). Although those authors argue that an “addiction-like” (dependence) for sugar can be elicited in animal models, the “addiction” was not paired with an increase in body weight versus control animals, suggesting that the sugar “addiction” does not lead to obesity. Further, when rats were exposed to sweetened diets that are high in fat in a similar paradigm, caloric consumption increased, but there was little evidence of behavioral dependence (; ). Thus, even in controlled animal models, it has been difficult to argue food dependence for diets high in both fat and sugar that have been shown to increase caloric consumption and body weight beyond that of normal, chow-fed controls. Within humans, evidence has been equivalently difficult to establish in terms of a food “addiction” as it relates to dependence ().

It should be noted that most drug users do not meet the criterion for dependence, and nonetheless consume drugs of abuse in ways that are harmful to themselves and society. The argument of food “addiction” might be less contentious if the DSM-IV-TR classification of substance abuse were applied, which focuses on use-related negative consequences on the individual and their family rather than on physiologic dependence on the substance (tolerance and withdrawal). Any one of the DSV-IV-TR criteria might be satisfied within this classification scheme to qualify for substance abuse; two notable criteria are:

“Recurrent substance use resulting in a failure to fulfill major role obligations at work, school, or home (e.g., repeated absences or poor work performance related to substance use; substance-related absences, suspensions, or expulsions from school; or neglect of children or household)” P. 199.


“Continued substance use despite having persistent or recurrent social or interpersonal problems caused or exacerbated by the effects of the substance (for example, arguments with spouse about consequences of intoxication and physical fights).” P. 199.

Given that it has been challenging to provide evidence for the key features of dependence as applied to food (tolerance and withdrawal), perhaps a more useful heuristic with regard to the behavioral patterns that lead to overconsumption of food might be to apply the DSM criterion for substance abuse. We suggest the following provisional definition of “food abuse”: a chronic pattern of overeating that results in not only an obese BMI (>30) but also multiple negative health, emotional, interpersonal, or occupational (school or work) consequences. There are clearly many factors that can lead to unhealthy weight gain, but the commonality is that they result in a protracted positive energy balance. There are numerous health consequences that are often associated with obesity, including type 2 diabetes, heart disease, dyslipidemia, hypertension, and some forms of cancer. Negative emotional consequences of overweight/obesity include low self-worth, feelings of guilt and shame, and significant body image concerns. Interpersonal problems might include recurrent conflict with family members about failure to maintain a healthy weight. One example of an occupational consequence from obesity is being discharged from the military services because of excess weight, an occurrence that affects over 1000 military personnel yearly. Some individuals may overeat and not experience unhealthy weight gain; and some individuals might not experience unhealthy weight gain but would be more appropriately diagnosed with an eating disorder, such as bulimia nervosa (which involves unhealthy compensatory behaviors, such as vomiting or excessive exercise for weight control) or binge eating disorder (which may not be associated with obesity during the initial phase of this condition). We acknowledge that in addition to overeating, other factors (e.g., genetics) contribute to risk for obesity-related morbidity. However, factors other than excessive alcohol and drug use contribute to negative consequences in substance abuse, such as behavioral control deficits for example, which increase risk for use-related legal problems.

Having stated the potential for viewing certain types of food intake as “abuse”, there are two additional important points to be made. First, we acknowledge that numerous factors increase risk for entering the prolonged positive energy balance necessary for obesity, which is beyond the scope of this review. Regardless of how obesity is achieved, the disorder becomes a metabolic one, and the new body weight is defended both metabolically and behaviorally through the actions of peripheral metabolic signaling and its interactions with hypothalamic homeostatic regulation of feeding. This is exemplified, for example, by resistance to the satiety-inducing effects provided by insulin and leptin hormone signaling to the brain, which occurs in both the obese and the aging. Secondly, although “food abuse” may be prevalent according to the above definition, the term “addiction” is fraught with intrinsic meaning for the general public. In the absence of a clear clinical definition, the use of the term “addiction” implies that the individual has little control over his/her behavior, and is compelled to make bad decisions in terms of his/her life circumstances. Until the medical and scientific communities agree to a clear definition of addiction, or provide a more compelling case for “food dependence”, it may not be in the best interest of society or obese persons to suggest that obese people of any sort are “addicts”. More comment regarding the risks of so characterizing obesity, or feeding patterns that lead to obese outcomes, will be discussed below. First, however, we will provide a brief discussion of some of the advantages that we have gained by viewing palatable food intake as a “disorder of appetitive motivation” () that affects reward circuitry in similar manners as drugs of abuse.

4.1 Lessons applied from drug addiction research

Despite the potential for negative consequences in defining the feeding patterns that lead to obesity as “addiction-like”, there have been positive developments that have resulted from the noted behavioral and physiological parallels that exist between feeding (particularly on palatable foods) and the intake of drugs of abuse. During the past 50 years, the drug abuse field has developed and/or refined a substantial number of animal models and behavioral paradigms that have recently been utilized by researchers interested in motivated behavior more broadly. For example, there are numerous labs now examining the food intake equivalents of bingeing on palatable diets when such diets are restricted (as is commonly the case in drug abuse studies; e.g., ). Additionally, models of “craving” that were initially developed in drug intake studies have been adopted to examine craving for sucrose and other palatable foods (e.g., Grimm et al., 2005, ). In both animal models and humans, relapse to drug-seeking behavior can be caused by exposure to cues that predict the drug, by stressful life circumstances, or by priming with a single unexpected dose of the drug. Similar reinstatement can be observed in animal models of food-seeking behavior, and such reinstatement paradigms are being used to examine the role of brain reward circuitry in promoting the relapse that is often experienced in humans who are trying to maintain a diet (; ; ; ). As food motivation can be argued to have anticipatory “appetitive” components as well as a consummatory feeding component, different behavioral paradigms have been developed that can dissociate the impact of pharmacological treatments on these separable components (see Baldo et al, this issue; ; ). Further experiments, utilizing these and other paradigms, may provide insight into the circumstances and neural mechanisms that contribute to regular overconsumption of food, that may in some cases lead to obesity.

With regards to contemporary human studies, the acknowledgement of the role of basal ganglia circuitry in reward processes that contribute to food intake, particularly in the face of palatable foods, has led to an exciting era of examining the role of this circuitry in the processing of food reward and the cues that predict it. Additionally, many of the recent neuroimaging experiments have utilized similar methodology, in terms of cue and stimulus exposure, as has been previously done within the drug abuse literature. Thus, in both animal and human models, the heuristic of viewing both overconsumption of palatable foods, and drug addiction as “disorders of appetitive motivation” (whether it is classified as an “addiction”, or something else) has led to new approaches and insight regarding how reward circuits may contribute to the onset and maintenance of unhealthy feeding habits in the presence of densely caloric food sources.

4.2 Problems with viewing obesity as an “addictive” disorder

Few lay people are likely to recognize obesity and the food intake patterns that may contribute to obesity as distinct phenomena, the former being a metabolic disorder and the other potentially a “food addiction” (and potentially not). Thus, as noted, even if it is established that some foods have abuse potential, it is likely that individuals with obesity may be labeled as “food addicts”, when that may or may not be the case. There are some potential dangers to such a characterization. Implying that individuals have a disease or mental illness may result in social stigmatization (and obese individuals already are subject to societal stigmas and biases), a sense of lack of control or choice over their behavior, or excusing behavior on a disease label (“I can’t help myself, I’m addicted”). Understanding the limits of research findings in this field is as important as the research findings themselves, and these caveats need to be publicly communicated.

Another caution for the field is that anthropomorphic interpretation of animal studies— and ascribing motives to animals that obviously cannot be validated—should be avoided. A further limitation of animal studies is that issues of control and choice, which play a major role in human feeding from an early age forward, are not and frequently cannot be addressed. Certainly, the complexity of the human environment is not simulated in the majority of animal studies to date, and thus represents a challenge and opportunity for future animal studies. To provide a direct comparison, the after-school U.S. teenager may have choices between sports, playing video games, doing homework, or ‘hanging out’ and eating snacks. All of these choices may have an equivalent cost value and eating snacks may not necessarily be the default. In animal studies, the animal may have a choice of eating or not eating a palatable food, but has no control over what that food is, has limited behavioral options, and has little or no control over when that food is available.

Moreover, suggesting that foods are “addictive” is likely to lead to questions of “which foods are addictive?” From the standpoint of the obesity epidemic, such questions shift the focus away from promoting healthy diet and exercise habits and onto the avoidance of specific foods. As has been previously suggested (), to label the affinity for a particular type of food (even one that is caloric and highly palatable) as an “addiction” trivializes the serious and disruptive nature of the condition in those suffering from drug dependence or addiction. Very few humans are driven to violent criminal behavior due to a craving for chocolate.

4.3. Final thoughts and future directions

Given that eating food is necessary for survival and that reward circuitry presumably evolved to drive this survival behavior, the criticism of eating activity (even abundant quantities of palatable but unhealthy foods) would seem to be a misplaced societal target. As alluded to above, a more appropriate focus would seem to be the elucidation of why individuals engage in overeating or drug use to the point that neural circuitry is altered in a manner that keeps them engaged in the behavior for extended periods of time. However, a second focus for research, education, and perhaps therapy could be upon nutritional choices and balance with an emphasis not on behavior (“addiction”), but on the downstream pathophysiological consequences, which are manifest to a greater degree in the current population, and at a younger age (pediatric population). A great deal of emphasis has been placed upon fructose which has unique metabolic consequences, although some findings are based upon consumption of very large amounts of fructose, in animal or clinical studies (see recent review from ). The generically motivating contribution of sucrose to intake of tasty beverages, and the enhancement of sucrose motivation by a background diet high in fat (, , ) suggests that research and education about the metabolic consequences of these macronutrients should be a continued focus, and approaches for effective messaging in different target groups need to be developed.

Additional research in humans is also not only desirable but very necessary. Now that the initial ‘generation’ of studies have been carried out confirming the expected activation of reward circuitry, it is time for the second and third generation studies which are much more difficult: the examination of the neural basis of choices in addition to the underlying motives. Equally challenging and necessary will be the extension of within-subjects’ studies across time, as well as identifying vulnerable populations for study prior to the onset of unhealthy eating habits, frank obesity, or both. Stated another way, the field must move from observational studies to studies that begin to address causality (i.e., whether CNS changes mediate behavioral changes, or are a concomitant or a result of behavioral changes) using both prospective and experimental designs.

Further evaluation of obesity-related changes versus palatable food-related changes, as highlighted by new findings from Stice and colleagues, is also needed. As mentioned above, studies in rodents demonstrate a high fat diet effect to increase motivation for sucrose, independent of obesity or metabolic changes, emphasizing the effect of nutrients or macronutrients per se to modulate CNS reward circuits. Thus, this represents another research direction where translational animal studies and human/clinical research may converge. Finally, although there may be some common events that trigger overeating under circumstances of high food availability, there are likely key ‘vulnerability factors’ that may play a role in the individual expression of eating patterns. This hypothetical begs for further studies combining genetics, and perhaps epigenetics, with brain imaging and clinical psychological studies. Identification of ‘vulnerability’ genes could lead to ‘reverse translational’ studies in animals, using appropriate designed models or paradigms to ascertain the role of such genes in, for example, simple food choices. Clearly, this area of study is at a point where contemporary research findings, as well as tools and technologies for human and animal research, can be put into service.


  • The brain circuitry that processes drug and natural reward are similar
  • We review evidence of overlapping brain processing of food and drug rewards
  • We discuss the implications of viewing food overconsumption as a “food addiction”


Eric Stice is a Senior Research Scientist at Oregon Research Institute; his research cited herein was supported by NIH grants R1MH064560A, DK080760, and DK092468. Dianne Figlewicz Lattemann is a Senior Research Career Scientist, Biomedical Laboratory Research Program, Department of Veterans Affairs Puget Sound Health Care System, Seattle, Washington; and her research cited in this paper has been supported by NIH grant DK40963. The research by Blake A. Gosnell and Allen S. Levine was supported by NIH/NIDA (R01DA021280) (ASL, BAG) and NIH/NIDDK (P30DK50456) (ASL). Wayne E. Pratt is currently supported by DA030618.


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  1. Ahmed S, Kenny P, Koob G, Markou A. Neurobiological evidence of hedonic allostasis associated with escalating cocaine use. Nature Neurosci. 2002;5:625–626. [PubMed]
  2. Alsio J, Olszewski PK, Norback AH, Gunnarsson ZE, Levine AS, Pickering C, Schioth HB. Dopamine D1 receptor gene expression decreases in the nucleus accumbens upon long-term exposure to palatable food and differs depending on diet-induced obesity phenotype in rats. Neuroscience. 2010;171:779–87. [PubMed]
  3. American Psychiatric Association . Diagnostic and statistical manual of mental disorders. 4th ed. Author; Washington, DC: 2000. text rev.
  4. Anthony J, Warner L, Kessler R. Comparative epidemiology of dependence on tobacco, alcohol, controlled substances and inhalants: Basic findings from the National Comorbidity Study. Experimental and Clinical Psychopharmacology, 1994;2:244–268.
  5. Aponte Y, Atasoy D, Sternson SM. AGRP neurons are sufficient to orchestrate feeding behavior rapidly and without training. Nature Neurosci. 2011;14:351–355. [PMC free article] [PubMed]
  6. Avena NM, Hoebel BG. Amphetamine-sensitized rats show sugar-induced hyperactivity (cross-sensitization) and sugar hyperphagia. Pharmacol Biochem Behav. 2003;74:635–9. [PubMed]
  7. Avena NM, Rada P, Hoebel BG. Evidence for sugar addiction: behavioral and neurochemical effects of intermittent, excessive sugar intake. Neurosci Biobehav Rev. 2008;32:20–39. [PMC free article] [PubMed]
  8. Avena NM, Rada P, Hoebel BG. Sugar and fat bingeing have notable differences in addictive-like behavior. J Nutr. 2009;139:623–628. [PMC free article] [PubMed]
  9. Barnes MJ, Holmes G, Primeaux SD, York DA, Bray GA. Increased expression of mu opioid receptors in animals susceptible to diet-induced obesity. Peptides. 2006;27:3292–8. [PubMed]
  10. Barnes MJ, Lapanowski K, Conley A, Rafols JA, Jen KL, Dunbar JC. High fat feeding is associated with increased blood pressure, sympathetic nerve activity and hypothalamic mu opioid receptors. Brain Res Bull. 2003;61:511–9. [PubMed]
  11. Bassareo V, Di Chiara G. Differential responsiveness of dopamine transmission to food-stimuli in nucleus accumbens shell/core compartments. Neuroscience. 1999;89(3):637–41. [PubMed]
  12. Baunez C, Amalric M, Robbins TW. Enhanced food-related motivation after bilateral lesions of the subthalamic nucleus. J Neurosci. 2002;22:562–568. [PubMed]
  13. Baunez C, Dias C, Cador M, Amalric M. The subthalamic nucleus exerts opposite control on cocaine and ‘natural’ rewards. Nat Neurosci. 2005;8:484–489. [PubMed]
  14. Benton D. The plausibility of sugar addiction and its role in obesity and eating disorders. Clin Nutr. 2010;29:288–303. [PubMed]
  15. Berridge KC. Motivation concepts in behavioral neuroscience. Physiol Behav. 2004;81:179–209. [PubMed]
  16. Bocarsly ME, Berner LA, Hoebel BG, Avena NM. Rats that binge eat fat-rich food do not show somatic signs or anxiety associated with opiate-like withdrawal: implications for nutrient-specific food addiction behaviors. Physiol Behav. 2011;104:865–872. [PMC free article] [PubMed]
  17. Bodnar RJ. Endogenous opioids and feeding behavior: a 30-year historical perspective. Peptides. 2004;25:697–725. [PubMed]
  18. Bruce A, Holsen L, Chambers R, Martin L, Brooks W, Zarcone J, et al. Obese children show hyperactivation to food pictures in brain networks linked to motivation, reward, and cognitive control. International Journal of Obesity. 2010;34:1494–1500. [PubMed]
  19. Burger KS, Stice E. Frequent ice cream consumption is associated with reduced striatal response to receipt of an ice cream-based milkshake. Am J Clin Nutr. 2012;95(4):810–7. [PMC free article] [PubMed]
  20. Cantin L, Lenoir M, Augier E, Vanhille N, Dubreucq S, Serre F, Vouillac C, Ahmed SH. Cocaine is low on the value ladder of rats: possible evidence for resilience to addiction. PLoS One. 2010;5:e11592. [PMC free article] [PubMed]
  21. Carelli RM, Ijames SG, Crumling AJ. Evidence that separate neural circuits in the nucleus accumbens encode cocaine versus “natural” (water and food) reward. J Neurosci. 2000;20:4255–4266. [PubMed]
  22. Carroll ME, Meisch RA. Increased drug-reinforced behavior due to food deprivation. Advances in Behavioral Pharmacology. 1984;4:47–88.
  23. Carroll ME, Morgan AD, Lynch WJ, Campbell UC, Dess NK. Intravenous cocaine and heroin self-administration in rats selectively bred for differential saccharin intake: phenotype and sex differences. Psychopharmacol. (2002;161:304–13. [PubMed]
  24. Center for Disease Control (CDC website) [accessed 7/30/2012];
  25. Chang GQ, Karatayev O, Barson JR, Chang SY, Leibowitz SF. Increased enkephalin in brain of rats prone to overconsuming a fat-rich diet. Physiol Behav. 2010;101:360–9. [PMC free article] [PubMed]
  26. Childress A, Mozley P, McElgin W, Fitzgerald J, Reivich M, O’Brien CP. Limbic activation during cue-induced cocaine craving. The American Journal of Psychiatry. 1999;156:11–18. [PMC free article] [PubMed]
  27. Colantuoni C, Rada P, McCarthy J, Patten C, Avena NM, Chadeayne A, Hoebel BG. Evidence that intermittent, excessive sugar intake causes endogenous opioid dependence. Obes Res. 2002;10:478–488. [PubMed]
  28. Colantuoni C, Schwenker J, McCarthy J, Rada P, Ladenheim B, Cadet JL, Schwartz GJ, Moran TH, Hoebel BG. Excessive sugar intake alters binding to dopamine and mu-opioid receptors in the brain. Neuroreport. 2001;12:3549–52. [PubMed]
  29. Corwin RL, Avena NM, Boggiano MM. Feeding and reward: perspectives from three rat models of binge eating. Physiol Behav. 2011;104:87–97. [PMC free article] [PubMed]
  30. Cunningham KA, Fox RG, Anastasio NC, Bubar MJ, Stutz SJ, Moeller FG, Gilbertson SR, Rosenzweig-Lipson S. Selective serotonin 5-HT(2C) receptor activation suppresses the reinforcing efficacy of cocaine and sucrose but differentially affects the incentive-salience value of cocaine- vs. sucrose-associated cues. Neuropharmacology. 2011;61:513–523. [PMC free article] [PubMed]
  31. Degenhardt L, Bohnert KM, Anthony JC. Assessment of cocaine and other drug dependence in the general population: “Gated” versus “ungated” approaches. Drug and Alcohol Dependence. 2008;93:227–232. [PMC free article] [PubMed]
  32. D’Anci KE, Kanarek RB, Marks-Kaufman R. Beyond sweet taste: saccharin, sucrose, and polycose differ in their effects upon morphine-induced analgesia. Pharmacol Biochem Behav. 1997;56:341–5. [PubMed]
  33. Davis CA, Levitan RD, Reid C, Carter JC, Kaplan AS, Patte KA, King N, Curtis C. Dopamine for “wanting” and opioids for “liking”: a comparison of obese adults with and without binge eating. Obesity. 2009;17:1220–1225. [PubMed]
  34. Davis C, Zai C, Levitan RD, Kaplan AS, Carter JC, Reid-Westoby C, Curtis C, Wight K, Kennedy JL. Opiates, overeating and obesity: a psychogenetic analysis. Int J Obesity. 2011a;35:1347–1354. [PubMed]
  35. Davis JF, Choi DL, Schurdak JD, Fitzgerald MF, Clegg DJ, Lipton JW, Figlewicz DP, Benoit SC. Leptin regulates energy balance and motivation through action at distinct neural circuits. Biological Psychiatry. 2011b;69:668–674. [PMC free article] [PubMed]
  36. Davis JF, Tracy AL, Schurdak JD, Tschop MH, Clegg DJ, Benoit SC, Lipton JW. Exposure to elevated levels of dietary fat attenuates psychostimulant reward and mesolimbic dopamine turnover in the rat. Behavioral Neuroscience, 2008;122:1257–1263. [PMC free article] [PubMed]
  37. Dayas C, Liu X, Simms J, Weiss F. Distinct patterns of neural activation associated with ethanol seeking: Effects of naltrexone. Biological Psychiatry. 2007;61:8979–8989. [PMC free article] [PubMed]
  38. DeSousa NJ, Bush DE, Vaccarino FJ. Self-administration of intravenous amphetamine is predicted by individual differences in sucrose feeding in rats. Psychopharmacol. 2000;148:52–8. [PubMed]
  39. de Weijer B, van de Giessen E, van Amelsvoort T, Boot E, Braak B, Janssen I, et al. Lower striatal dopamine D2/3 receptor availability in obese compared with non-obese subjects. EJNMMI.Res. 2011;1:37. [PMC free article] [PubMed]
  40. de Zwaan M, Mitchell JE. Opiate antagonists and eating behavior in humans: a review. J Clin Pharmacol. 1992;1992;(32):1060–1072. [PubMed]
  41. Di Chiara G. Nucleus accumbens shell and core dopamine: Differential role in behavior and addiction. Behavioral Brain Research. 2002;137:75–114. [PubMed]
  42. Due DL, Huettel SA, Hall WG, Rubin DC. Activation in mesolimbic and visuospatial neural circuits elicited by smoking cues: Evidence from functional magnetic resonance imaging. The American Journal of Psychiatry. 2002;159:954–960. [PubMed]
  43. Farooqi IS, Bullmore E, Keogh J, Gillard J, O’Rahilly S, Fletcher PC. Leptin regulates striatal regions and human eating behavior. Science. 2007;317:1355. [PMC free article] [PubMed]
  44. Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010. Jama. 2012;307:491–497. [PubMed]
  45. Figlewicz DP, Bennett JL, Aliakbari S, Zavosh A, Sipols AJ. Insulin acts at different CNS sites to decrease acute sucrose feeding and sucrose self-administration in rats. American Journal of Physiology. 2008;295:388–R394. [PMC free article] [PubMed]
  46. Figlewicz DP, Bennett J, Evans SB, Kaiyala K, Sipols AJ, Benoit SC. Intraventricular insulin and leptin reverse place preference conditioned with high fat diet in rats. Behavioral Neuroscience. 2004;118:479–487. [PubMed]
  47. Figlewicz DP, Bennett JL, Naleid AM, Davis C, Grimm JW. Intraventricular insulin and leptin decrease sucrose self-administration in rats. Physiology and Behavior. 2006;89:611–616. [PubMed]
  48. Figlewicz DP, Benoit SB. Insulin, leptin, and food reward: Update 2008. American Journal of Physiology. 2009;296:9–R19. [PMC free article] [PubMed]
  49. Figlewicz Lattemann D, Sanders NMNM, Sipols AJ. Peptides in Energy Balance and Obesity. CAB International; 2009. Energy regulatory signals and food reward; pp. 285–308.
  50. Figlewicz DP, Sipols AJ. Energy regulatory signals and food reward. Pharmacology, Biochemistry, and Behavior. 2010;97:15–24. [PMC free article] [PubMed]
  51. Figlewicz DP, Bennett-Jay JL, Kittleson S, Sipols AJ, Zavosh A. Sucrose self-administration and CNS activation in the rat. American Journal of Physiology. 2011;300:876. [PMC free article] [PubMed]
  52. Figlewicz DP, Jay JL, Acheson MA, Magrisso IJ, West CH, Zavosh A, Benoit SC, Davis JF. Moderate high fat diet increases sucrose self-administration in young rats. Appetite. 2012 in press (available online) [PMC free article] [PubMed]
  53. Finkelstein EA, Trogdon JG, Cohen JW, Dietz W. Annual medical spending attributable to obesity: payer-and service-specific estimates. Health Aff (Millwood) 2009;28:822–831. [PubMed]
  54. Fletcher PJ, Chintoh AF, Sinyard J, Higgins GA. Injection of the 5-HT2C receptor agonist Ro60-0175 into the ventral tegmental area reduces cocaine-induced locomotor activity and cocaine self-administration. Neuropsychopharmacology. 2004;29:308–318. [PubMed]
  55. Floresco SB, McLaughlin RJ, Haluk DM. Opposing roles for the nucleus accumbens core and shell in cue-induced reinstatement of food-seeking behavior. Neuroscience. 2008;154:877–884. [PubMed]
  56. Foley KA, Fudge MA, Kavaliers M, Ossenkopp KP. Quinpirole-induced behavioral sensitization is enhanced by prior scheduled exposure to sucrose: A multi-variable examination of locomotor activity. Behav Brain Res. 2006;167:49–56. [PubMed]
  57. George M, Anton R, Bloomer C, Teneback C, Drobes D, Lorberbaum J, et al. Activation of prefrontal cortex and anterior thalamus in alcoholic subjects on exposure to alcohol-specific cues. Archives of General Psychiatry. 2001;58:345–352. [PubMed]
  58. Gosnell BA. Sucrose intake enhances behavioral sensitization produced by cocaine. Brain Research. 2005;1031:194–201. [PubMed]
  59. Gosnell BA, Lane KE, Bell SM, Krahn DD. Intravenous morphine self-administration by rats with low versus high saccharin preferences. Psychopharmacol. 1995;117:248–252. [PubMed]
  60. Gosnell BA, Levine AS. Stimulation of ingestive behavior by preferential and selective opioid agonists. In: Cooper SJ, Clifton PG, editors. Drug Receptor Subtypes and Ingestive Behavior. Academic Press; San Diego, CA: 1996. pp. 147–166.
  61. Gosnell BA, Levine AS. Reward systems and food intake: role of opioids. Int J Obes. 2009;33(2):S54–8. [PubMed]
  62. Grill HJ. Leptin and the systems neuroscience of meal size control. Frontier in Neuroendocrinology. 2010;31:61–78. [PMC free article] [PubMed]
  63. Grimm JW, Barnes J, North K, Collins S, Weber R. A general method for evaluating incubation of sucrose craving in rats. J Vis Exp, 2011:e3335. [PMC free article] [PubMed]
  64. Grimm JW, Hope BT, Wise RA, Shaham Y. Neuroadaptation. Incubation of cocaine craving after withdrawal. Nature. 2001;412:141–142. [PMC free article] [PubMed]
  65. Grusser SM, Wrase J, Klein S, Hermann D, Smolka MN, et al. Cue-induced activation of the striatum and medial prefrontal cortex is associated with subsequent relapse in abstinent alcoholics. Psychopharmacology. 2004;175:296–302. [PubMed]
  66. Guy EG, Choi E, Pratt WE. Nucleus accumbens dopamine and mu-opioid receptors modulate the reinstatement of food-seeking behavior by food-associated cues. Behav Brain Res. 2011;219:265–272. [PubMed]
  67. Heinz A, Siessmeier R, Wrase J, Hermann D, Klein S, Gruzzer S, et al. Correlation betweeen dopamine D2 receptors in the ventral striatum and central processing of alcohol cues and craving. American Journal of Psychiatry. (2004;161:1783–1789. [PubMed]
  68. Hoebel BG. Brain-stimulation reward and aversion in relation to behavior. In: Wauquier A, Rolls ET, editors. Brain-stimulation Reward. North Holland Press; 1976. pp. 335–372.
  69. Imperato A, Obinu MC, Casu MA, Mascia MS, Carta G, Gessa GL. Chronic morphine increases hippocampal acetylcholine release: Possible relevance in drug dependence. Eur J Pharmacol. 1996;302:21–26. [PubMed]
  70. Ito R, Dalley JW, Robbins TW, Everitt BJ. Dopamine release in the dorsal striatum during cocaine-seeking behavior under the control of a drug-associated cue. J. Neurosci. 2002;22:6247–6253. [PubMed]
  71. Janes A, Pizzagalli D, Richardt S, Frederick B, Chuzi S, Pachas G, et al. Brain reactivity to smoking cues prior to smoking cessation predicts ability to maintain tobacco abstinence. Biological Psychiatry. 2010;67:722–729. [PMC free article] [PubMed]
  72. Jewett DC, Grace MK, Levine AS. Chronic sucrose ingestion enhances mu-opioid discriminative stimulus effects. Brain Res. 2005;1050:48–52. [PubMed]
  73. Kalivas P, O’Brian C. Drug addiction as a pathology of staged neuroplasticity. Neuropsychopharmacology. 2008;33:166–180. [PubMed]
  74. Kampov-Polevoy A, Garbutt JC, Janowsky D. Evidence of preference for a high-concentration sucrose solution in alcoholic men. Am J Psychiatry. 1997;154:269–70. [PubMed]
  75. Kampov-Polevoy AB, Garbutt JC, Janowsky DS. Association between preference for sweets and excessive alcohol intake: a review of animal and human studies. Alcohol Alcohol. 1999;34:386–95. [PubMed]
  76. Kampov-Polevoy AB, Garbutt JC, Khalitov E. Family history of alcoholism and response to sweets. Alcohol Clin Exp Res. 2003;27:1743–9. [PubMed]
  77. Kelley AE. Memory and addiction: shared neural circuitry and molecular mechanisms. Neuron. 2004;44:161–179. [PubMed]
  78. Kelley AE, Bakshi VP, Haber SN, Steininger TL, Will MJ, Zhang M. Opioid modulation of taste hedonics within the ventral striatum. Physiol Behav. 2002;76:365–377. [PubMed]
  79. Kelley AE, Berridge KC. The neuroscience of natural rewards: relevance to addictive drugs. J Neurosci. 2002;22:3306–3311. [PubMed]
  80. Kelley AE, Baldo BA, Pratt WE, Will MJ. Corticostriatal-hypothalamic circuitry and food motivation: integration of energy, action and reward. Physiol Behav. 2005a;86:773–795. [PubMed]
  81. Kelley AE, Schiltz CA, Landry CF. Neural systems recruited by drug- and food-related cues: studies of gene activation in corticolimbic regions. Physiol Behav. 2005b;86:11–14. [PubMed]
  82. Kelley AE, Will MJ, Steininger TL, Zhang M, Haber SN. Restricted daily consumption of a highly palatable food (chocolate Ensure(R)) alters striatal enkephalin gene expression. Eur J Neurosci. 2003;18:2592–8. [PubMed]
  83. Kenny P, Chen S, Kitamura O, Markou A, Koob G. Conditioned withdrawal drives heroin consumption and decreases reward sensitivity. Journal of Neuroscience. 2006;26:5894–5900. [PubMed]
  84. Koob G, Bloom F. Cellular and molecular mechanisms of drug dependence. Science. 1988;242:715–723. [PubMed]
  85. Kosten T, Scanley B, Tucker K, Oliveto A, Prince C, Sinha R, et al. Cue-induced brain activity changes and relapse in cocaine-dependent patients. Neuropsychopharmacology. 2006;31:644–650. [PubMed]
  86. Krahn D, Grossman J, Henk H, Mussey M, Crosby R, Gosnell B. Sweet intake, sweet-liking, urges to eat, and weight change: Relationship to alcohol dependence and abstinence. Addictive Behaviors. 2006;31:622–631. [PubMed]
  87. Kranzler HR, Sandstrom KA, Van Kirk J. Sweet taste as a risk factor for alcohol dependence. Am J Psychiatry. 2001;158:813–5. [PubMed]
  88. Kringelbach ML, O’Doherty J, Rolls ET, Andrews C. Activation of the human orbitofrontal cortex to a liquid food stimulus is correlated with its subjective pleasantness. Cerebral Cortex. 2003;13:1064–1071. [PubMed]
  89. Krashes MJ, Koda S, Ye CP, Rogan SC, Adams AC, Cusher DS, Maratos-Flier E, Roth BL, Lowell BB. Rapid reversible activation of AgRP neurons drives feeding behavior in mice. Journal of Clinical Investigation. 2011;121:1424–1428. [PMC free article] [PubMed]
  90. Laaksonen E, Lahti J, Sinclair JD, Heinälä P, Alho H. Predictors for the efficacy of naltrexone treatment in alcohol dependence: sweet preference. Alcohol Alcohol. 2011;46:308–11. [PubMed]
  91. Le Merrer J, Becker JA, Befort K, Kieffer BL. Reward processing by the opioid system in the brain. Physiol Rev. 2009;89:1379–412. [PMC free article] [PubMed]
  92. Lett BT. Ingestion of sweet water enhances the rewarding effect of morphine in rats. Psychobiol. 1989;17:191–4.
  93. Maas LC, Lukas SE, Kaufman MJ, Weiss RD, Daniels SL, Rogers VW, et al. Renshaw PF. Functional magnetic resonance imaging of human brain activation during cue-induced cocaine craving. The American Journal of Psychiatry. 1998;155:124–126. [PubMed]
  94. Mahler SV, Smith RJ, Moorman DE, Sartor GC, Aston-Jones G. Multiple roles for orexin/hypocretin in addiction. Progress in Brain Research. 2012;198:79–121. [PMC free article] [PubMed]
  95. Margules DL, Olds J. Identical ‘feeding’ and ‘rewarding’ systems in the lateral hypothalamus of rats. Science. 1962;135:374–375. [PubMed]
  96. Martin LE, Hosen LM, Chambers RJ, Bruce AS, Brooks WM, Zarcone JR, et al. Neural mechanisms associated with food motivation in obese and healthy weight adults. Obesity. 2009;18:254–260. [PubMed]
  97. Martinez D, Narendran R, Foltin R, Slifstein M, Hwang D, Broft A, et al. Amphetamine-induced dopamine release: Markedly blunted in cocaine dependence and predictive of the choice to self-administer cocaine. American Journal of Psychiatry. 2007;164:622–629. [PubMed]
  98. Mebel DM, Wong JCY, Dong YJ, Bogland SL. Insulin in the ventral tegmental area reduces hedonic feeding and suppresses dopamine concentration via increased uptake. European Journal of Neuroscience. 2012;36:2236–2246. [PubMed]
  99. Mena JD, Sadeghian K, Baldo BA. Induction of hyperphagia and carbohydrate intake by mu-opioid receptor stimulation in circumscribed regions of frontal cortex. J Neurosci. 2011;31:3249–3260. [PMC free article] [PubMed]
  100. Mitra A, Gosnell BA, Schioth HB, Grace MK, Klockars A, Olszewski PK, Levine AS. Chronic sugar intake dampens feeding-related activity of neurons synthesizing a satiety mediator, oxytocin. Peptides. 2010;31:1346–52. [PMC free article] [PubMed]
  101. Mogenson GJ, Jones DL, Yim CY. From motivation to action: functional interface between the limbic system and the motor system. Prog Neurobiol. 1980;14:69–97. [PubMed]
  102. Morabia A, Fabre J, Chee E, Zeger S, Orsat E, Robert A. Diet and opiate addiction: a quantitative assessment of the diet of non-institutionalized opiate addicts. Br J Addict. 1989;84:173–80. [PubMed]
  103. Myrick H, Anton RF, Li X, Henderson S, Drobes D, Voronin K, George MS. Differential Brain Activity in Alcoholics and Social Drinkers to Alcohol Cues: Relationship to Craving. Neuropsychopharmacology. 2004;29:393–402. [PubMed]
  104. Nader MA, Morgan D, Gage H, Nader SH, Calhoun TL, Buchheimer N, et al. PET imaging of dopamine D2 receptors during chronic cocaine self-administration in monkeys. Nature Neuroscience. 2006;9:1050–1056. [PubMed]
  105. Nair SG, Adams-Deutsch T, Epstein DH, Shaham Y. The neuropharmacology of relapse to food seeking: methodology, main findings, and comparison with relapse to drug seeking. Prog Neurobiol. 2009;89:18–45. [PMC free article] [PubMed]
  106. Nathan PJ, O’Neill BV, Bush MA, Koch A, Tao WX, Maltby K, Napolitano A, Brooke AC, Skeggs AL, Herman CS, Larkin AL, Ignar DM, Richards DB, Williams PM, Bullmore ET. Opioid receptor modulation of hedonic taste preference and food intake: a single-dose safety, pharmacokinetic, and pharmacodynamic investigation with GSK1521498, a novel μ-opioid receptor inverse agonist. J Clin Pharmacol. 2012;52:464–74. [PubMed]
  107. Ng J, Stice E, Yokum S, Bohon C. An fMRI study of obesity, food reward, and perceived caloric density. Does a low-fat label make food less appealing? Appetite. 2011;57:65–72. [PMC free article] [PubMed]
  108. Nummenmaa L, Hirvonen J, Hannukainen J, Immonen H, Lindroos M, Salminen P, et al. Dorsal striatum and its limbic connectivity mediate abnormal anticipatory reward processing in obesity. PLoS ONE. 2012;7:e31089. [PMC free article] [PubMed]
  109. O’Brian C, Volkow N, Li T. What’s in a word? Addiction vs dependence in DSM-V. American Journal of Psychiatry. 2006;163:764–765. [PubMed]
  110. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of obesity and trends in body mass index among US children and adolescents, 1999-2010. Jama. 2012;07:483–490. [PubMed]
  111. Olds J, Allan WS, Briese E. Differentiation of hypothalamic drive and reward centers. Am J Physiol. 1971;221:368–375. [PubMed]
  112. Olszewski PK, Grace MK, Fard SS, Le Greves M, Klockars A, Massi M, Schioth HB, Levine AS. Central nociceptin/orphanin FQ system elevates food consumption by both increasing energy intake and reducing aversive responsiveness. Am J Physiol Regul Integr Comp Physiol. 2010;99:655–63. [PMC free article] [PubMed]
  113. Olszewski PK, Fredriksson R, Olszewska AM, Stephansson O, Alsio J, Radomska KJ, et al. Hypothalamic FTO is associated with the regulation of energy intake not feeding reward. BMC Neurosci. 2009;10:129. [PMC free article] [PubMed]
  114. Olszewski PK, Levine AS. Central opioids and consumption of sweet tastants: when reward outweighs homeostasis. Physiol Behav. 2007;91:506–12. [PubMed]
  115. Olszewski PK, Shi Q, Billington CJ, Levine AS. Opioids affect acquisition of LiCl-induced conditioned taste aversion: involvement of OT and VP systems. Am J Physiol Regul Integr Comp Physiol. 2000;279:R1504–11. [PubMed]
  116. Overduin J, Figlewicz DP, Bennett J, Kittleson S, Cummings DE. Ghrelin increases the motivation to eat but does not alter food palatability. American Journal of Physiology. 2012 in press. [PMC free article] [PubMed]
  117. Paulus M, Tapert S, Schuckit M. Neural activation patterns of methamphetamine-dependent subjects during decision making predict relapse. Archives of General Psychiatry. 2005;62:761–768. [PubMed]
  118. Perelló M, Zigman JM. The role of ghrelin in reward-based eating. Biological Psychiatry. 2012;72:347–353. [PMC free article] [PubMed]
  119. Phillips AG, Fibiger HC. Dopaminergic and noradrenergic substrates of positive reinforcement: differential effects of d- and l-amphetamine. Science. 1973;179:575–577. [PubMed]
  120. Pickens CL, Cifani C, Navarre BM, Eichenbaum H, Theberge FR, Baumann MH, Calu DJ, Shaham Y. Effect of fenfluramine on reinstatement of food seeking in female and male rats: implications for the predictive validity of the reinstatement model. Psychopharmacology (Berl) 2012;221:341–353. [PMC free article] [PubMed]
  121. Porrino LJ, Lyons D, Smith HR, Daunais JB, Nader MA. Cocaine Self-Administration Produces a Progressive Involvement of Limbic, Association, and Sensorimotor Striatal Domains. The Journal of Neuroscience. 2004;24:3554–3562. [PubMed]
  122. Pratt WE, Choi E, Guy EG. An examination of the effects of subthalamic nucleus inhibition or mu-opioid receptor stimulation on food-directed motivation in the non-deprived rat. Behav Brain Res. 2012;230:365–373. [PMC free article] [PubMed]
  123. Rabiner EA, Beaver J, Makwana A, Searle G, Long C, Nathan PJ, Newbould RD, Howard J, Miller SR, Bush MA, Hill S, Reiley R, Passchier J, Gunn RN, Matthews PM, Bullmore ET. Pharmacological differentiation of opioid receptor antagonists by molecular and functional imaging of target occupancy and food reward-related brain activation in humans. Mol Psychiatry. 2011;16:826–835. [PMC free article] [PubMed]
  124. Roberts DC, Corcoran ME, Fibiger HC. On the role of ascending catecholaminergic systems in intravenous self-administration of cocaine. Pharmacology, Biochemistry, and Behavior. 1977;6:615–620. [PubMed]
  125. Rogers PJ, Smit HJ. Food craving and food “addiction”: a critical review of the evidence from a biopsychosocial perspective. Pharmacol Biochem Behav. 2000;66:3–14. [PubMed]
  126. Rothemund Y, Preuschhof C, Bohner G, Bauknecht HC, Klingebiel R, Flor H, et al. Differential activation of the dorsal striatum by high-calorie visual food stimuli in obese individuals. Neuroimage. 2007;37:410–421. [PubMed]
  127. Rouaud T, Lardeux S, Panayotis N, Paleressompoulle D, Cador M, Baunez C. Reducing the desire for cocaine with subthalamic nucleus deep brain stimulation. Proc Natl Acad Sci U S A. 2010;107:1196–1200. [PMC free article] [PubMed]
  128. Sabatier N. alpha-Melanocyte-stimulating hormone and oxytocin: a peptide signalling cascade in the hypothalamus. Neuroendocrinol. 2006;18:703–10. [PubMed]
  129. Schultz W, Apicella P, Ljungberg T. Responses of monkey dopamine neurons to reward and conditioned stimuli during successive steps of learning a delayed response task. Journal of Neuroscience. 1993;13:900–913. [PubMed]
  130. Scinska A, Bogucka-Bonikowska A, Koros E, Polanowska E, Habrat B, Kukwa A, Kostowski W, Bienkowski P. Taste responses in sons of male alcoholics. Alcohol Alcohol. 2001;36:79–84. [PubMed]
  131. Sclafani A, Rinaman L, Vollmer RR, Amico JA. Oxytocin knockout mice demonstrate enhanced intake of sweet and nonsweet carbohydrate solutions. Am J Physiol Regul Integr Comp Physiol. 2007;292:R1828–33. [PMC free article] [PubMed]
  132. Small DM, Jones-Gotman M, Dagher A. Feeding-induced dopamine release in dorsal striatum correlates with meal pleasantness ratings in healthy human volunteers. Neuroimage. 2003;19:1709–1715. [PubMed]
  133. Small DM, Zatorre RJ, Dagher A, Evans AC, Jones-Gotman M. Changes in brain activity related to eating chocolate: From pleasure to aversion. Brain. 2001;124:1720–1733. [PubMed]
  134. Smith KS, Berridge KC. Opioid limbic circuit for reward: interaction between hedonic hotspots of nucleus accumbens and ventral pallidum. J Neurosci. 2007;27:1594–1605. [PubMed]
  135. Smith SL, Harrold JA, Williams G. Diet-induced obesity increases mu opioid receptor binding in specific regions of the rat brain. Brain Res. 2002;953:215–22. [PubMed]
  136. Stanhope KL. Role of fructose-containing sugars in the epidemics of obesity and the metabolic syndrome. Ann Rev Med. 2012;63:329–43. [PubMed]
  137. Stice E, Spoor S, Bohon C, Veldhuizen MG, Small DM. Relation of Reward From Food Intake and Anticipated Food Intake to Obesity: A Functional Magnetic Resonance Imaging Study. Journal of Abnormal Psychology. 2008;117:924–935. [PMC free article] [PubMed]
  138. Stice E, Yokum S, Burger K. Elevated reward region responsivity predicts future substance use onset but not overweight/obesity onset. Biological Psychiatry. in press. [PMC free article] [PubMed]
  139. Stice E, Yokum S, Bohon C, Marti N, Smolen A. Reward circuitry responsivity to food predicts future increases in body mass: Moderating effects of DRD2 and DRD4. Neuroimage. 2010;50:1618–1625. [PMC free article] [PubMed]
  140. Stoeckel LE, Weller RE, Cook EW, Twieg DB, Knowlton RC, Cox JE. Widespread reward-system activation in obese women in response to pictures of high-calorie foods. Neuroimage. 2008;41:636–647. [PubMed]
  141. Tapert SF, Cheung EH, Brown GG, Frank LR, Paulus MP, Schweinsburg AD, Meloy MJ, Brown SA. Neural response to alcohol stimuli in adolescents with alcohol use disorder. Archives of General Psychiatry. 2003;60:727–735. [PubMed]
  142. Tang DW, Fellows LK, Small DM, Dagher A. Food and drug cues activate similar brain regions: A meta-analysis of functional MRI studies. Physiology & Behavior. 2012 doi: 10.1016/j.physbeh.2012.03.009. [PubMed]
  143. Thanos PK, Michaelides M, et al. Food restriction markedly increases dopamine D2 receptor (D2R) in a rat model of obesity as assessed with in-vivo muPET imaging ([11C] raclopride) and in-vitro ([3H] spiperone) autoradiography. Synapse. 2008;62:50–61. [PubMed]
  144. Unterwald EM, Kreek MJ, Cuntapay M. The frequency of cocaine administration impacts cocaine-induced receptor alterations. Brain Res. 2001;900:103–109. [PubMed]
  145. Uslaner JM, Yang P, Robinson TE. Subthalamic nucleus lesions enhance the psychomotor-activating, incentive motivational, and neurobiological effects of cocaine. J Neurosci. 2005;25:8407–8415. [PubMed]
  146. Vanderschuren LJ, Kalivas PW. Alterations in dopaminergic and glutamatergic transmission in the induction and expression of behavioral sensitization: a critical review of preclinical studies. Psychopharmacology (Berl) 2000;151:99–120. [PubMed]
  147. Volkow ND, Chang L, Wang G, Fowler JS, Ding Y, Sedler M, et al. Low level of brain dopamine D2 receptors in methamphetamine abusers: Association with metabolism in the orbitofrontal cortex. The American Journal of Psychiatry. 2001;158:2015–2021. [PubMed]
  148. Volkow ND, Fowler JS, Wang GJ, Goldstein RZ. Role of dopamine, the frontal cortex and memory circuits in drug addiction: Insight from imaging studies. Neurobiology of Learning and Memory. 2002;78:610–624. [PubMed]
  149. Volkow ND, Wang G, Fowler JS, Logan J. Measuring age-related changes in dopamine D2 receptors with -2-2C-raclopride and -2-8F-N-methylspiroperidol. Psychiatry Research: Neuroimaging. 1996;67:11–16. [PubMed]
  150. Volkow ND, Wang G, Fowler JS, Logan J. Effects of methylphenidate on regional brain glucose metabolism in humans: Relationship to dopamine D2 receptors. The American Journal of Psychiatry. 1997;154:50–55. [PubMed]
  151. Volkow N, Wang G, Ma Y, Fowler J, Wong C, Ding Y, et al. Activation of orbital and medial prefrontal cortex by methylphenidate in cocaine-addicted subjects but not in controls: Relevance to additction. Journal of Neuroscience. 2005;25:3932–3939. [PubMed]
  152. Volkow ND, Wang G, Telang F, Fowler JS, Logan J, Childress A, et al. Cocaine Cues and Dopamine in Dorsal Striatum: Mechanism of Craving in Cocaine Addiction. The Journal of Neuroscience. 2006;26:6583–6588. [PubMed]
  153. Volkow ND, Wang GJ, Telang F, Fowler JS, Thanos PK, Logan J, et al. Low dopamine striatal D2 receptors are associated with prefrontal metabolism in obese subjects: Possible contributing factors. Neuroimage. 2008;42:1537–1543. [PMC free article] [PubMed]
  154. Wang G, Volkow ND, Fowler JS, Logan J. Dopamine D2 receptor availability in opiate-dependent subjects before and after naloxone-precipitated withdrawal. Neuropsychopharmacology. 1997;16:174–182. [PubMed]
  155. Wang G-J, Volkow ND, Logan J, et al. Brain dopamine and obesity. Lancet. 2001;357:354–357. [PubMed]
  156. Wang GJ, et al. Enhanced striatal dopamine release during food stimulation in binge eating disorder. Obesity (Silver Spring) 2011;19(8):1601–8. [PMC free article] [PubMed]
  157. Weiss G. Food fantasies of incarcerated drug users. Int J Addict. 1982;17:905–12. [PubMed]
  158. Willenbring ML, Morley JE,, Krahn DD, Carlson GA, Levine AS, Shafer RB. Psychoneuroendocrine effects of methadone maintenance. Psychoneuroendocrinol. 1989;14:371–91. [PubMed]
  159. World Health Organization (WHO) [accessed 7/30/2012]; website,
  160. Yeomans MR, Gray RW. Opioid peptides and the control of human ingestive behavior. Neurosci Biobehav Rev. 2002;26:713–728. [PubMed]
  161. Yokum S, Ng J, Stice E. Attentional bias to food images associated with elevated weight and future weight gain: an fMRI study. Obesity. 2011;19:775–1783. [PMC free article] [PubMed]
  162. Zador D, Lyons Wall PM, Webster I. High sugar intake in a group of women on methadone maintenance in South Western Sydney, Australia. Addiction. 1996;91:1053–61. [PubMed]
  163. Ziauddeen H, Farooqi IS, Fletcher PC. Obesity and the brain: how convincing is the addiction model? Nat Rev Neurosci. 2012;13:279–286. [PubMed]