Linking drug and food addiction: an overview of the shared neural circuits and behavioral phenotype
Alice Passeri1,2† 
Diana Municchi1,2† 
Giulia Cavalieri2 
Lucy Babicola1 
Rossella Ventura2,3*‡ 
Matteo Di Segni1,2‡- 1IRCCS Fondazione Santa Lucia, Rome, Italy
- 2Department of Psychology and Center “Daniel Bovet”, Sapienza University, Rome, Italy
- 3IRCCS San Raffaele, Rome, Italy
Despite a lack of agreement on its definition and inclusion as a specific diagnosable disturbance, the food addiction construct is supported by several neurobiological and behavioral clinical and preclinical findings. Recognizing food addiction is critical to understanding how and why it manifests. In this overview, we focused on those as follows: 1. the hyperpalatable food effects in food addiction development; 2. specific brain regions involved in both food and drug addiction; and 3. animal models highlighting commonalities between substance use disorders and food addiction. Although results collected through animal studies emerged from protocols differing in several ways, they clearly highlight commonalities in behavioral manifestations and neurobiological alterations between substance use disorders and food addiction characteristics. To develop improved food addiction models, this heterogeneity should be acknowledged and embraced so that research can systematically investigate the role of specific variables in the development of the different behavioral features of addiction-like behavior in preclinical models.
1. Introduction
Eating is a multifaceted behavior determined by physiological and motivational drives and modulated by several mechanisms that include environmental, emotional, social, and cultural factors (Emilien and Hollis, 2017). Eating behavior can also lead to disabling conditions such as eating disorders (EDs), which are characterized by complex biological and environmental interactions (Bulik et al., 2022). Recently, clinical and preclinical studies have focused on the environmental risk factors for the development of dysfunctional eating behaviors and, specifically, on the nutrient composition of high-calorie, high-fat, high-sugar, and highly processed foods (Gibney et al., 2017; Monteiro et al., 2019; Hecht et al., 2022; Wiss, 2022).
These foods, alternatively referred to as hyperpalatable, highly processed, and highly rewarding foods (HPFs), can trigger those brain areas controlling gratification processing (liking) and attribution of salience (wanting), as proposed by the incentive sensitization theory, developed as a framework for SUDs’ interpretation (Berridge et al., 2010; Gearhardt et al., 2011; Volkow et al., 2012; Schulte et al., 2015; Berridge and Robinson, 2016; Robinson et al., 2016; Cameron et al., 2017; Devoto et al., 2018; Lindgren et al., 2018; Volkow et al., 2019; Stice and Yokum, 2021). According to the recent NOVA classification (Monteiro et al., 2010), even if ultra-processed foods and drinks (UPFDs) provide calories, they are poor sources of micronutrients and possess low satiating power (Monteiro et al., 2018). In addition, increased consumption of these foods is strongly associated with obesity, diet-related diseases, and adverse mental health symptoms (Gearhardt and Schulte, 2021; Hecht et al., 2022).
There is a consensual definition of UPFDs as highly palatable and gratifying foods, whose organoleptic features can affect physiological mechanisms involved in satiety and appetite regulation, which may promote excessive consumption and manifest as a true “addiction” (Gibney et al., 2017). Food addiction (FA) (Randoph, 1956) has been described in a range of terms including eating addiction (Hebebrand et al., 2014), sugar addiction (Avena et al., 2008), fat addiction (Sarkar et al., 2019), HPF addiction (Gearhardt et al., 2011), salted FA (Cocores and Gold, 2009), and, recently, UPFDs addiction (Wiss, 2022). Disagreement upon the terminology belies a debate concerning the validity of the FA construct and its mechanisms (Ziauddeen et al., 2012; Salamone and Correa, 2013; Ziauddeen and Fletcher, 2013; Hebebrand et al., 2014; Westwater et al., 2016; Finlayson, 2017; Rogers, 2017; Fletcher and Kenny, 2018; Lacroix et al., 2018; Gearhardt and Hebebrand, 2021a).
Researchers have argued that there is a strong overlap between clinical features of FA and binge eating disorder (BED) and that human studies assessing neurobiological mechanisms of FA are not convincing. In addition, animal models of FA seem to lack ecological validity (Fletcher and Kenny, 2018). Therefore, some authors support the behavioral addiction hypothesis (eating addiction) based on the argument that substances of abuse act as agonists of specific brain receptors and have a direct effect on the reward system. This is not the case for food. Moreover, eating is necessary for survival and intrinsically rewarding (Hebebrand et al., 2014; Gearhardt and Hebebrand, 2021a). However, other authors support the FA hypothesis, emphasizing behavioral and neurobiological similarities between HPF consumption and substance use disorders (SUDs) (Meule and Gearhardt, 2014; Gordon et al., 2018; Wiss et al., 2018; Gearhardt and Schulte, 2021). They strongly support FA as an independent clinical entity characterized by a specific behavioral pattern, including compulsive overeating [(Davis, 2017), for extensive reviews, see, Gearhardt and Hebebrand (2021a,b) and Hebebrand and Gearhardt (2021)]. Nevertheless, it has been proposed that the psychological constructs related to overeating (e.g., binge eating, food addiction, food craving, and hedonic hunger) share phenotypic, genetic, and environmental features that could be enclosed under the umbrella term “uncontrolled eating,” conceptualized as high food reward sensitivity combined with poor self-control, thus distancing it from the addiction hypothesis (Vainik et al., 2019, 2020). According to the DSM-5-TR (American Psychiatric Association, 2022), the diagnosis of SUD is based on pathological behaviors related to substance use. It identifies different forms of substance-related and addictive disorders and “non-substance-related addictions,” which refer only to gambling disorders. Even if FA is not recognized as a diagnosable pathology, its clinical features—especially loss of control and craving, risky use, tolerance, and withdrawal—seem to fit with the diagnostic criteria for SUDs. Indeed, these criteria have been used for the development and validation of tools to assess FA in humans, including the “Yale Food Addiction Scale,” the “Three Factors Eating Questionnaire,” the “Power of Food Scale,” and the “Loss of Control over Eating Scale” (Stunkard and Messick, 1985; Lowe et al., 2009; Gearhardt et al., 2011, 2016; Latner et al., 2014; Pursey et al., 2015; Schulte et al., 2015; de Vries and Meule, 2016; Burrows et al., 2017; Markus et al., 2017; Ayaz et al., 2018; Lemeshow et al., 2018; Carter et al., 2019; Tran et al., 2020; Sanchez et al., 2022). Interestingly, both clinical and preclinical studies have suggested how the mesolimbic dopamine (DA) system, mediating reward-related stimuli, learning, motivational, and executive control processes (Wang et al., 2004; Stice et al., 2008; Belin et al., 2009; Wise, 2009; Volkow et al., 2012; Tomasi and Volkow, 2013; Furlong et al., 2014; Volkow et al., 2017; Novelle and Diéguez, 2018; Volkow et al., 2019; Ndiaye et al., 2020) is involved both in SUDs and FA. Repeated stimulation of the DA-reward pathway is believed to foster the sensitization of the mesolimbic system both to the substance itself and its associated cues (Berridge and Robinson, 2016) and to promote neurobiological adaptations that result in the development of pathological behaviors such as binging (Furlong et al., 2014), craving (Krasnova et al., 2014; Madangopal et al., 2022), use despite negative consequences (Latagliata et al., 2010), withdrawal, and tolerance (Avena et al., 2005, 2008; Iemolo et al., 2012; Sharma et al., 2013).
2. The mesoaccumbens dopamine system involvement in drug and food addiction
HPF and drugs of abuse can impact the function of similar brain circuits, including the mesoaccumbens DA system (Latagliata et al., 2010; Volkow et al., 2017; Fletcher and Kenny, 2018). It is worth pointing out how the “reward” system responds to both rewarding and aversive motivational stimuli (Salamone and Correa, 2012). Therefore, alteration of this system could result in various psychopathologies characterized by impaired motivational stimuli processing, such as depression, schizophrenia, Parkinson’s disease, and addiction-like disorders (Salamone et al., 2016). Interestingly, it seems that both natural rewards and drugs of abuse exert initial reinforcing effects by targeting brain regions of this circuit, such as the nucleus accumbens (NAc). However, addiction results from the transition from hedonic intake to an uncontrolled one, which requires long-lasting adaptations within the reward system and associated circuits (Domingo-Rodriguez et al., 2020).
2.1. The prefrontal cortex
The prefrontal cortex (PFC) is involved in the regulation of cognitive flexibility, decision-making, and inhibitory control. It plays a crucial role in the transition to and persistence of addictive behavior (Domingo-Rodriguez et al., 2020). An impairment in executive functions is likely to contribute to the poor control and high compulsivity seen in addicted subjects (Volkow and Baler, 2014; Volkow et al., 2019).
PFC regions are activated when cocaine abusers are exposed to craving-inducing stimuli, and the increase in metabolic activity in the orbitofrontal cortex (OFC) and anterior cingulate cortex (ACC) is associated with the intensity of the craving (Volkow and Baler, 2014; Volkow et al., 2019). Neuroimaging studies show inhibition of metabolic activity in OFC (Volkow and Baler, 2014; Koob and Volkow, 2016) and ACC (Koob and Volkow, 2016) in cocaine abusers when they are asked to inhibit craving after exposure to cocaine cues (Volkow and Baler, 2014; Koob and Volkow, 2016).
Interestingly, a similar metabolic inhibition can be observed in obese patients when they are asked to inhibit craving for food after they have been exposed to food cues (Volkow and Baler, 2014). In human studies, subjects with BED and bulimia nervosa show weakened functional connectivity between the left lateral OFC, which is implicated in the inhibitory suppression of rewarded choices (Mar et al., 2011; Gourley et al., 2016) and the right dorsolateral PFC (DLPFC) (Ahn et al., 2022), which mediates the relationship between motor urgency and response inhibition (Hu et al., 2016). When exposed to high-calorie food stimuli, individuals with BED display an overactivation of the OFC (Schienle et al., 2009; Hone-Blanchet and Fecteau, 2014; Meng et al., 2020; Celeghin et al., 2023). Notably, lateral OFC is crucial for goal-directed behavior. A recent study showed how in a mouse model of obesity, lateral OFC-dependent impairments in devaluation (mediated by GABAergic transmission) may alter the ability to use the value of the outcome to guide behavior (Seabrook et al., 2023). Increased activation of OFC is also evident in drug-addicted subjects in response to drug-related cues (Sell et al., 2000; Wang et al., 2007; Kufahl et al., 2008; Goldstein and Volkow, 2011; Ceceli et al., 2022), and it is considered an index of craving (Volkow et al., 2010).
Food- and drug-addicted subjects demonstrate executive function impairment during recovery and relapse (Basso et al., 2022), similar brain activation during craving (Gearhardt et al., 2011) with specific and predictive neuromarkers (“neurobiological craving signature”) (Koban et al., 2023), and the transition from goal-directed action to habits (DiFeliceantonio et al., 2018). Furthermore, the modulation of craving and consumption of alcohol, nicotine, drugs, or food by excitatory neuromodulation interventions of DLPFC has been suggested (Song et al., 2022).
Preclinical studies have also shown similar cortical alterations between drug abuse and FA (Chen et al., 2013; Limpens et al., 2015; Newmyer et al., 2019; Domingo-Rodriguez et al., 2020; Amissah et al., 2021; Navandar et al., 2021). In addition, vulnerability to drug addiction and FA shares several transcriptional signatures in mPFC (Navandar et al., 2021). The activity of the prelimbic cortex, implicated in response inhibition (Chen et al., 2013; Limpens et al., 2015), seems to correlate with compulsive seeking of both drugs and food (Chen et al., 2013; Domingo-Rodriguez et al., 2020). Furthermore, the medial insula plays a critical role in cravings for food, cocaine, and nicotine (Mar et al., 2011; Volkow and Baler, 2014). Insular reactivity has been proposed as a potential biomarker for relapse risk and a target for addiction treatments (Volkow et al., 2019). Imaging studies have reported differential activation of the insula during craving, possibly reflecting interoceptive cues and the activation of corticotropin-releasing factor (Mar et al., 2011). The OFC-anterior insular cortex pathway is also involved in cocaine addiction (Chen et al., 2022) and, interestingly, using a continuous versus intermittent cocaine self-administration paradigm, it has been found that the latter was able to induce greater cocaine-taking behavior during withdrawal (Luo et al., 2021). The same effect, mediated by an intermittent (but not continuous) self-administration paradigm, has been reported for HPF (Spierling et al., 2020).
2.2. The nucleus accumbens
The NAc is a central area of the reward circuit and an important driver of goal-directed and goal-associated actions (Volkow et al., 2019). It is involved in several addiction-related processes, such as memory, learning, and response inhibition (Volkow and Baler, 2014). One of the changes related to the increased responsiveness to drug-predictive cues in addiction is the balance between D1 and D2 receptors (D1R, D2R) signaling in the ventral striatum. Preclinical studies support the idea that strengthening of D1R-medium spiny neurons (MSNs) in NAc enhances cocaine reward, whereas strengthening of D2R-MSNs suppresses it (Volkow et al., 2019). Similarly, mice fed with a high-fat diet show enhanced activity of NAc D1R-MSNs during food seeking, which is linked to increased excitatory synaptic drive in the same neurons (Matikainen-Ankney et al., 2023). Moreover, blocking synaptic transmission from D1R-MSNs, but not D2R, reduces lever-pressing force during food seeking and attenuates HPF-induced weight gain (Matikainen-Ankney et al., 2023). However, despite recent evidence supporting the dichotomy between NAc D2R and D1R-containing neurons in driving motivation toward reinforcing stimuli such as drugs or food (Gerfen, 2023; Sandoval-Rodríguez et al., 2023; Swinford-Jackson et al., 2023), several studies indicated a non-canonical common role of NAc D1R and D2R in encoding positive valence/reward responses to drugs of abuse and food (Soares-Cunha et al., 2016; Gallo et al., 2018; Soares-Cunha et al., 2020; Joshi et al., 2021; Tan et al., 2022).
Glutamatergic plasticity in the NAc plays a key role in mediating the enhanced motivation for both food and drugs (Wolf and Tseng, 2012; Alonso-Caraballo et al., 2021). Imbalance in glutamatergic receptor expression is also a key feature of silent synapses, markers of synaptic reorganization. Recent studies have revealed that sucrose/junk food and cocaine increase the number of MSNs silent synapses in NAc (Alonso-Caraballo et al., 2021; Bijoch et al., 2023). Overall, these data suggest strong similarities between food- and drug-induced synaptic changes in NAc (Graziane et al., 2016; Terrier et al., 2016).
2.3. The ventral tegmental area
Every drug with abuse potential directly or indirectly acting on DA neurons in the ventral tegmental area (VTA) causes increased DA in the NAc (Volkow et al., 2019). In the context of eating behaviors, the hyperactive VTA DA-ergic projections lead to enhanced incentive salience or craving for food (Jerlhag et al., 2009). Food can act through the neural input from the taste buds and hormones released by the digestion and absorption of food (Alonso-Alonso et al., 2015). However, recent findings support the notion that direct stimulation of the gastrointestinal tract with nutrients or optical activation of gut-innervating vagal sensory neurons is sufficient to induce DA release in brain circuits controlling food intake. Interestingly, the changes in extracellular DA levels reflect the caloric load of the substance, even in the absence of taste receptor signaling (de Araujo et al., 2008; Han et al., 2018; Schatzker et al., 2020). VTA neurons express receptors for several peptides and hormones regulating homeostatic signals and influencing the responses to drugs. Among these, ghrelin has been reported to affect VTA DA-neuron firing rate and to increase the intake of HPF, the cocaine-induced locomotion, and conditioned place preference; by contrast, antagonism of ghrelin receptors reduces the development of nicotine and cocaine sensitization (Abizaid et al., 2006; Jerlhag et al., 2009; Skibicka et al., 2011; Wellman et al., 2011; Schuette et al., 2013; Cepko et al., 2014; Dunn et al., 2019).
Leptin, an adipose-derived hormone, modulates DA neurotransmission in the mesoaccumbens pathway acting on its receptors in VTA. This decreases the incentive value of both palatable food and substances of abuse such as cocaine and heroin (Figlewicz et al., 2003; Hommel et al., 2006; Morton et al., 2009; Shen et al., 2011; Meye and Adan, 2014; D’Cunha et al., 2020). Insulin inhibits dopaminergic VTA-NAc projections through the activation of the Akt–mTOR pathway and retrograde endocannabinoid signaling. This suppresses glutamate release and increases DA reuptake thereby upregulating DA transporter (DAT) and attenuating reward for HPF and drug (Iniguez et al., 2008; Bruijnzeel et al., 2011; Kenny, 2011; Mebel et al., 2012; Labouèbe et al., 2013; Tiedemann et al., 2017; Naef et al., 2019). In addition, signaling of peptides such as GLP-1 (involved in glucose regulation) and orexin (engaged in feeding behaviors) have been involved in reward regulation and dysfunctional responses toward food and drugs of abuse (Merchenthaler et al., 1999; Rinaman, 2010; Alhadeff et al., 2012; Erreger et al., 2012; Egecioglu et al., 2013; Graham et al., 2013; Shirazi et al., 2013; Engel and Jerlhag, 2014; Bentzley and Aston-Jones, 2015; Saad et al., 2019; Jamali et al., 2021). Overconsumption of HPFs can also induce dopaminergic adaptations within the VTA, such as a reduction of TH (both mRNA and protein levels), catechol-O-methyl transferase (DA degrading enzyme), and DAT, together with D1R and D2R expression (Vucetic et al., 2012; Carlin et al., 2013; Sharma and Fulton, 2013; Decarie-Spain et al., 2016).
2.4. The amygdala
The amygdala is primarily involved in memory, decision-making, and emotional response. As for NAc MSNs, stimulation or increased neuronal activity of D1R central amygdala (CeA) neurons enhances food seeking and is associated with incubation of drug seeking. Conversely, D2R stimulation suppresses food seeking and its reduced activity is associated with the incubation of drug craving (Kim et al., 2017; Venniro et al., 2017). Many of the long-term emotional disturbances associated with the withdrawal/negative stage of the addiction cycle have been related to dysfunctional activity of the CeA, which processes painful and pleasurable experiences (Roberto et al., 2017; Horseman and Meyer, 2019).
Negative emotional states and withdrawal symptoms are crucial factors of relapse. Incubation of drug seeking during abstinence has been observed in humans and animal models, and several studies outlined the involvement of the amygdala in mediating these behaviors (See et al., 2003; Lu et al., 2005; Smith and Aston-Jones, 2008; Li et al., 2015; Roura-Martínez et al., 2020; Pagano et al., 2023). Interestingly, blocking CB1 receptor signaling in the CeA can precipitate a negative emotional state in rats withdrawn from chronic intermittent access to HPF. This is similar to that seen in cannabinoid- and opiate-dependent subjects (Blasio et al., 2013), which suggests a link between compulsive eating and drug taking. Indeed, neural stimulation of CeA can strongly increase incentive motivation for natural and drug rewards (Tom et al., 2019; Warlow et al., 2020; Warlow and Berridge, 2021). It has been reported that kinase Cδ-expressing neurons mediate negative valence, satiation, and conditioned taste aversion, while prepronociceptin-expressing cells are suggested to be involved in assigning positive valence and enhanced motivation to HPF (Hardaway et al., 2019).
3. Modeling of food addiction in rodents
Modeling human psychiatric disorders in animals is challenging, particularly in the addiction field where the validity of rodent models has been argued to be restricted to “face” similarities (Hebebrand et al., 2014; Hebebrand and Gearhardt, 2021). This is even more evident in the FA research due to the debate on construct validity which leads to a non-univocal interpretation of the collected results (Salamone and Correa, 2013; Rogers, 2017; Sarkar et al., 2019; American Psychiatric Association, 2022). Nevertheless, literature so far collected in preclinical models suggests how specific foods (Berridge and Robinson, 2016; Wiss, 2022) can induce, under specific conditions, pathological manifestations accepted as valid measures of SUD symptoms (Deroche-Gamonet et al., 2004; Hone-Blanchet and Fecteau, 2014; Shriner and Gold, 2014). Along with the conceptual framework borrowed from SUDs, many of the behavioral tests used to investigate addiction-like eating behavior in rodents are modified tests of pathological drug use that use food as a primary reinforcer (Moore et al., 2019; Brown and James, 2023).
The earliest preclinical findings on food addiction-like behaviors derive from studies aimed primarily at the manipulation of the energy-homeostatic and metabolic aspects of feeding in the context of the study of obesity, which is not included among EDs but is clinically often associated with them (Berridge et al., 2010). Studies using prolonged free access (i.e., ad libitum) to HPFs have shown escalation in consumption beyond homeostatic needs (Valdivia et al., 2015; Kreisler et al., 2017; Wiss et al., 2018) that parallels escalation in drug addiction (Deroche-Gamonet et al., 2004; Johnson and Kenny, 2010). Similarly, free extended access to a palatable diet has been shown to induce behavioral and neurobiological alterations of tolerance induced by repeated or prolonged exposure to drugs of abuse (Ahmed et al., 2000; Dimitriou et al., 2000; Ahmed et al., 2002; Avena, 2010; la Fleur et al., 2011; Wojnicki et al., 2015; Parnarouskis and Gearhardt, 2022).
Continuous access to HPFs also produces an increase in body weight, complicating the distinction between overweight and overeating behavior (Corwin, 2006; Davis, 2013). Manipulations that provide alternating, intermittent exposures to HPFs aim to overcome this issue (Cottone et al., 2008; Emilien and Hollis, 2017; American Psychiatric Association, 2022). Intermittent or limited access to specific food rewards has been shown to promote a gradual escalation of preferred food intake across time, culminating in consumption of larger amounts during the first period in which food is available again (Avena et al., 2005; Cottone et al., 2008).
Intermittent access to substances/food produces more robust behavioral addiction-like manifestations than continuous access (Dimitriou et al., 2000; Kinzig et al., 2008; Corwin et al., 2011; Patrono et al., 2015; Wojnicki et al., 2015; Garcia et al., 2020; Vazquez-Herrera et al., 2021). Addiction-like increased consumption in the first period following re-exposure has been reported in rodents when they had intermittent period access shorter than 1 h daily (Corwin, 2004; Cottone et al., 2008; Giuliano et al., 2012; Halpern et al., 2013; Schulte et al., 2015; Wojnicki et al., 2015; Lee et al., 2020). This is similar to substance-induced behaviors in which more pronounced effects were observed with brief and limited access than with extended access (Kreisler et al., 2017; Spierling et al., 2020). Interestingly, “sporadic” exposure (2 h once weekly) to HPF in the absence of physiological stress induces a pathological phenotype after some weeks (Czyzyk et al., 2010), an observation also reported for nicotine (Miller et al., 2001) or ketamine (Trujillo et al., 2008).
Despite the difficulty in comparing results from these models due to diversities in the schedule of exposure (frequency and duration), intervening variables (e.g., concomitant slight food deprivation), and the type of test used, these models suggest a possible presence of incubation underlying the shift from a normal to a dysfunctional feeding behavior. In SUD models, this effect can be due to a hyper-evaluation of the palatable food when unavailable as well as devaluation of the less preferred alternative when a stable alternation has been acquired. Accordingly, food seeking in mice increases following prolonged abstinence from palatable food during self-administration training (Grimm et al., 2005; Krasnova et al., 2014; Darling et al., 2016; Madangopal et al., 2022). Uncertainty about the availability of the desired food may contribute to addiction-like behaviors by engaging in stress response (Cottone et al., 2009; Corwin et al., 2011). Interestingly, behavioral signs of a negative emotional state and increased stress responsivity are documented in animals that have access to high-fat food (Sharma et al., 2013), sucrose solutions (Galic and Persinger, 2002; Avena et al., 2005; Pickering et al., 2009; Yakovenko et al., 2011), or a combination of both (Teegarden and Bale, 2007) withdrawn, resembling the “deprivation effects” observed in models of intermittent drug and alcohol access (Rodd et al., 2004; Wang et al., 2004; George et al., 2007).
Abstinence from HPFs produces an anhedonic state and increased anxiety-like behaviors in rodents (Colantuoni et al., 2002; Yakovenko et al., 2011; Sharma et al., 2013; Ulrich-Lai et al., 2015; Spierling et al., 2020). Other reports also demonstrate an increase in responding to cues previously paired with high-fat foods, sucrose, and saccharin after abstinence (Aoyama et al., 2014; Darling et al., 2016; Dingess et al., 2017), parallel to response to drug-paired cues observed after abstinence (Epstein et al., 2016; Grimm, 2020).
The escalation in consumption has been proposed to be sustained by different mechanisms, not mutually exclusive, such as tolerance (as increased reward threshold) and opponent processes engagement (aversive state), suggesting that increased wanting is not sufficient to define the addiction (Cottone et al., 2009; Berridge and Robinson, 2016; Koob and Volkow, 2016; Parnarouskis and Gearhardt, 2022).
As for drugs (Volkow and Morales, 2015), the link with the stress system is further strengthened by evidence that exposure to environmental conditions, including shock (Hagan et al., 2002, 2003), isolation rearing (Blanco-Gandía et al., 2018), consume frustration (Cifani et al., 2009; Micioni Di Bonaventura et al., 2017; Anversa et al., 2020), forced swimming (Consoli et al., 2009), chronic variable stress (Pankevich et al., 2010; Thompson et al., 2015), and reduced maternal care early in life (Jahng, 2013) coupled with shock (Hancock et al., 2005) can powerfully influence the behavioral approach to palatable food. In turn, either continuous or intermittent palatable food intake blunts acute stress responses both in human and rodent studies (Pecoraro et al., 2004; Kinzig et al., 2008; Ulrich-Lai et al., 2015), supporting the hypothesis that palatable food has “comforting” effects that may promote its intake and relapse behaviors after abstinence (Avena et al., 2008; Cottone et al., 2009; Ulrich-Lai et al., 2010; Parylak et al., 2011).
Food restriction has been widely used in different models because it represents both an environmental source of stress able to influence addiction-like behaviors (Sinha and Jastreboff, 2013) and a condition mimicking certain aspects of diet regulation reported in humans, typically consisting of limitation of caloric intake (Stice and Burger, 2015). Boggiano’s model shows how cycles of energy restriction/refeeding (as with foot shock at the end of the final cycle) promote in rats more HPF consumption than foot shock or a history of restriction alone (Hagan et al., 2003; Chandler-Laney et al., 2007; Blanco-Gandía et al., 2018).
Many binging behavior models use modified versions of this protocol, with changes in the length of each component of the cycle, the type of binge food, the kind of acute stress administered, and the species of rodent (Hancock et al., 2005; Cifani et al., 2009; Consoli et al., 2009; Pankevich et al., 2010). In the model proposed by Hoebel, however, animals received palatable food during a period of mild food deprivation and showed an enhanced response to rewarding food as evidenced by the short-term (1 h) intake. The intake is higher than rats that received the palatable food only twice (Avena et al., 2008).
Evidence from rodent models also demonstrates the possibility to investigate eating despite negative consequences, a hallmark characteristic of SUD behaviors (Deroche-Gamonet et al., 2004; Vanderschuren and Everitt, 2004; Boggiano and Chandler, 2006; Everitt et al., 2008). Johnson and Kenny (2010) reported that rats with unrestricted access to a cafeteria diet continued to compulsively consume it despite the presence of an aversive conditioned stimulus (foot-shock-paired light), whereas rats previously fed with only regular chow and/or given restricted access to the high-fat/high-sugar diet significantly decreased their palatable food consumption in the presence of the aversive conditioned stimulus.
Oswald et al. (2011), Krasnova et al. (2014), and Rossetti et al. (2014) demonstrated how rats that developed binge-like intake after alternate HPF exposure persisted in self-administration despite the harmful consequences (foot shock). Similarly, rats withdrawing from intermittent access to a palatable diet compulsively sought and consumed a sugary diet while they were facing aversive conditions (the enlightened aversive compartment in a light/dark conflict box) (Calvez and Timofeeva, 2016). Work from our group has investigated the willingness to risk (shock-paired light presence) in order to consume a rewarding food after an alternated prolonged food exposure, evidencing in mice a critical role for genotype (Latagliata et al., 2010; Patrono et al., 2015).
4. Discussion
Differences and similarities between food and drug responses have sparked debate about whether FA could be a valid construct to define a clinical disorder. Due to the clinical evidence of the capability of HPF to promote specific features of SUDs, such as loss of control, craving, risky use, tolerance, and withdrawal, diagnostic tools aim to shed light on this issue. Moreover, preclinical studies modeling FA have attempted to investigate the interaction between biological and environmental factors in maladaptive behaviors toward drugs of abuse and food and have identified some common neurobiological substrates and alterations that could be coherently framed within the incentive salience theory of addiction. To clearly define FA as a disorder per se, however, including as a non-substance-related addiction, it is critical to understand how and why it emerges. The heterogeneity of results obtained by FA models should therefore be acknowledged and embraced, systematically investigating the role of specific variables on the development of the different behavioral features that compose drug addiction-like behaviors. Reaching these goals could lead to the development of specific and effective treatments for FA.
Author contributions
AP, DM, and GC selected literature. AP, DM, GC, LB, RV, and MD wrote the manuscript. All the authors provide approval for publication of the content.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
Abizaid, A., Liu, Z. W., Andrews, Z. B., Shanabrough, M., Borok, E., Elsworth, J. D., et al. (2006). Ghrelin modulates the activity and synaptic input organization of midbrain dopamine neurons while promoting appetite. J. Clin. Invest. 116, 3229–3239. doi: 10.1172/JCI29867
Ahmed, S. H., Kenny, P. J., Koob, G. F., and Markou, A. (2002). Neurobiological evidence for hedonic allostasis associated with escalating cocaine use. Nat. Neurosci. 5, 625–626. doi: 10.1038/nn872
Ahmed, S. H., Walker, J. R., and Koob, G. F. (2000). Persistent increase in the motivation to take heroin in rats with a history of drug escalation. Neuropsychopharmacology 22, 413–421. doi: 10.1016/S0893-133X(99)00133-5
Ahn, J., Lee, D., Lee, J. E., and Jung, Y. C. (2022). Orbitofrontal cortex functional connectivity changes in patients with binge eating disorder and bulimia nervosa. PLoS One 17:e0279577. doi: 10.1371/journal.pone.0279577
Alhadeff, A. L., Rupprecht, L. E., and Hayes, M. R. (2012). GLP-1 neurons in the nucleus of the solitary tract project directly to the ventral tegmental area and nucleus accumbens to control for food intake. Endocrinology 153, 647–658. doi: 10.1210/en.2011-1443
Alonso-Alonso, M., Woods, S. C., Pelchat, M., Grigson, P. S., Stice, E., Farooqi, S., et al. (2015). Food reward system: current perspectives and future research needs. Nutr. Rev. 73, 296–307. doi: 10.1093/nutrit/nuv002
Alonso-Caraballo, Y., Fetterly, T. L., Jorgensen, E. T., Nieto, A. M., Brown, T. E., and Ferrario, C. R. (2021). Sex specific effects of “junk-food” diet on calcium permeable AMPA receptors and silent synapses in the nucleus accumbens core. Neuropsychopharmacology 46, 569–578. doi: 10.1038/s41386-020-0781-1
American Psychiatric Association (2022). Diagnostic and statistical manual of mental disorders. 5th Edn. Washington: American Psychiatric Association.
Amissah, R. Q., Basha, D., Bukhtiyarova, O., Timofeeva, E., and Timofeev, I. (2021). Neuronal activities during palatable food consumption in the reward system of binge-like eating female rats. Physiol. Behav. 242:113604. doi: 10.1016/j.physbeh.2021.113604
Anversa, R. G., Campbell, E. J., Ch’ng, S. S., Gogos, A., Lawrence, A. J., and Brown, R. M. (2020). A model of emotional stress-induced binge eating in female mice with no history of food restriction. Genes Brain Behav. 19:e12613. doi: 10.1111/gbb.12613
Aoyama, K., Barnes, J., and Grimm, J. W. (2014). Incubation of saccharin craving and within-session changes in responding for a cue previously associated with saccharin. Appetite 72, 114–122. doi: 10.1016/j.appet.2013.10.003
Avena, N. M. (2010). The study of food addiction using animal models of binge eating. Appetite 55, 734–737. doi: 10.1016/j.appet.2010.09.010
Avena, N. M., Long, K. A., and Hoebel, B. G. (2005). Sugar-dependent rats show enhanced responding for sugar after abstinence: evidence of a sugar deprivation effect. Physiol. Behav. 84, 359–362. doi: 10.1016/j.physbeh.2004.12.016
Avena, N. M., Rada, P., and Hoebel, B. G. (2008). Evidence for sugar addiction: behavioral and neurochemical effects of intermittent, excessive sugar intake. Neurosci. Biobehav. Rev. 32, 20–39. doi: 10.1016/j.neubiorev.2007.04.019
Ayaz, A., Nergiz-Unal, R., Dedebayraktar, D., Akyol, A., Pekcan, A. G., Besler, H. T., et al. (2018). How does food addiction influence dietary intake profile? PLoS One 13:e0195541. doi: 10.1371/journal.pone.0195541
Basso, J. C., Satyal, M. K., Athamneh, L., and Bickel, W. K. (2022). Changes in temporal discounting, hedonic hunger, and food addiction during recovery from substance misuse. Appetite 169:105834. doi: 10.1016/j.appet.2021.105834
Belin, D., Jonkman, S., Dickinson, A., Robbins, T. W., and Everitt, B. J. (2009). Parallel and interactive learning processes within the basal ganglia: relevance for the understanding of addiction. Behav. Brain Res. 199, 89–102. doi: 10.1016/j.bbr.2008.09.027
Bentzley, B. S., and Aston-Jones, G. (2015). Orexin-1 receptor signaling increases motivation for cocaine-associated cues. Eur. J. Neurosci. 41, 1149–1156. doi: 10.1111/ejn.12866
Berridge, K. C., Ho, C. Y., Richard, J. M., and DiFeliceantonio, A. G. (2010). The tempted brain eats: pleasure and desire circuits in obesity and eating disorders. Brain Res. 1350, 43–64. doi: 10.1016/j.brainres.2010.04.003
Berridge, K. C., and Robinson, T. E. (2016). Liking, wanting, and the incentive-sensitization theory of addiction. Am. Psychol. 71, 670–679. doi: 10.1037/amp0000059
Bijoch, Ł., Klos, J., Pawłowska, M., Wiśniewska, J., Legutko, D., Szachowicz, U., et al. (2023). Whole-brain tracking of cocaine and sugar rewards processing. Transl. Psychiatry 13:20. doi: 10.1038/s41398-023-02318-4
Blanco-Gandía, M. C., Montagud-Romero, S., Aguilar, M. A., Miñarro, J., and Rodríguez-Arias, M. (2018). Housing conditions modulate the reinforcing properties of cocaine in adolescent mice that binge on fat. Physiol. Behav. 183, 18–26. doi: 10.1016/j.physbeh.2017.10.014
Blasio, A., Iemolo, A., Sabino, V., Petrosino, S., Steardo, L., Rice, K. C., et al. (2013). Rimonabant precipitates anxiety in rats withdrawn from palatable food: role of the central amygdala. Neuropsychopharmacology 38, 2498–2507. doi: 10.1038/npp.2013.153
Boggiano, M. M., and Chandler, P. C. (2006). Binge eating in rats produced by combining dieting with stress. Curr. Protoc. Neurosci. 36:Unit9.23A. doi: 10.1002/0471142301.ns0923as36
Brown, R. M., and James, M. H. (2023). Binge eating, overeating and food addiction: approaches for examining food overconsumption in laboratory rodents. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 123:110717. doi: 10.1016/j.pnpbp.2023.110717
Bruijnzeel, A. W., Corrie, L. W., Rogers, J. A., and Yamada, H. (2011). Effects of insulin and leptin in the ventral tegmental area and arcuate hypothalamic nucleus on food intake and brain reward function in female rats. Behav. Brain Res. 219, 254–264. doi: 10.1016/j.bbr.2011.01.020
Bulik, C. M., Coleman, J. R. I., Hardaway, J. A., Breithaupt, L., Watson, H. J., Bryant, C. D., et al. (2022). Genetics and neurobiology of eating disorders. Nat. Neurosci. 25, 543–554. doi: 10.1038/s41593-022-01071-z
Burrows, T., Hides, L., Brown, R., Dayas, C. V., and Kay-Lambkin, F. (2017). Differences in dietary preferences, personality and mental health in Australian adults with and without food addiction. Nutrients 9:285. doi: 10.3390/nu9030285
Calvez, J., and Timofeeva, E. (2016). Behavioral and hormonal responses to stress in binge-like eating prone female rats. Physiol. Behav. 157, 28–38. doi: 10.1016/j.physbeh.2016.01.029
Cameron, J. D., Chaput, J. P., Sjödin, A. M., and Goldfield, G. S. (2017). Brain on fire: incentive salience, hedonic hot spots, dopamine, obesity, and other hunger games. Annu. Rev. Nutr. 37, 183–205. doi: 10.1146/annurev-nutr-071816-064855
Carlin, J., Hill-Smith, T. E., Lucki, I., and Reyes, T. M. (2013). Reversal of dopamine system dysfunction in response to high-fat diet. Obesity 21, 2513–2521. doi: 10.1002/oby.20374
Carter, J. C., Van Wijk, M., and Rowsell, M. (2019). Symptoms of 'food addiction' in binge eating disorder using the Yale food addiction scale version 2.0. Appetite 133, 362–369. doi: 10.1016/j.appet.2018.11.032
Ceceli, A. O., Bradberry, C. W., and Goldstein, R. Z. (2022). The neurobiology of drug addiction: cross-species insights into the dysfunction and recovery of the prefrontal cortex. Neuropsychopharmacology 47, 276–291. doi: 10.1038/s41386-021-01153-9
Celeghin, A., Palermo, S., Giampaolo, R., Di Fini, G., Gandino, G., and Civilotti, C. (2023). Brain correlates of eating disorders in response to food visual stimuli: a systematic narrative review of FMRI studies. Brain Sci. 13:465. doi: 10.3390/brainsci13030465
Cepko, L. C., Selva, J. A., Merfeld, E. B., Fimmel, A. I., Goldberg, S. A., and Currie, P. J. (2014). Ghrelin alters the stimulatory effect of cocaine on ethanol intake following mesolimbic or systemic administration. Neuropharmacology 85, 224–231. doi: 10.1016/j.neuropharm.2014.05.030
Chandler-Laney, P. C., Castaneda, E., Pritchett, C. E., Smith, M. L., Giddings, M., Artiga, A. I., et al. (2007). A history of caloric restriction induces neurochemical and behavioral changes in rats consistent with models of depression. Pharmacol. Biochem. Behav. 87, 104–114. doi: 10.1016/j.pbb.2007.04.005
Chen, Y., Wang, G., Zhang, W., Han, Y., Zhang, L., Xu, H., et al. (2022). An orbitofrontal cortex-anterior insular cortex circuit gates compulsive cocaine use. Sci. Adv. 8:5745. doi: 10.1126/sciadv.abq5745
Chen, B. T., Yau, H. J., Hatch, C., Kusumoto-Yoshida, I., Cho, S. L., Hopf, F. W., et al. (2013). Rescuing cocaine-induced prefrontal cortex hypoactivity prevents compulsive cocaine seeking. Nature 496, 359–362. doi: 10.1038/nature12024
Cifani, C., Polidori, C., Melotto, S., Ciccocioppo, R., and Massi, M. (2009). A preclinical model of binge eating elicited by yo-yo dieting and stressful exposure to food: effect of sibutramine, fluoxetine, topiramate, and midazolam. Psychopharmacology 204, 113–125. doi: 10.1007/s00213-008-1442-y
Cocores, J. A., and Gold, M. S. (2009). The salted food addiction hypothesis may explain overeating and the obesity epidemic. Med. Hypotheses 73, 892–899. doi: 10.1016/j.mehy.2009.06.049
Colantuoni, C., Rada, P., McCarthy, J., Patten, C., Avena, N. M., Chadeayne, A., et al. (2002). Evidence that intermittent, excessive sugar intake causes endogenous opioid dependence. Obes. Res. 10, 478–488. doi: 10.1038/oby.2002.66
Consoli, D., Contarino, A., Tabarin, A., and Drago, F. (2009). Binge-like eating in mice. Int. J. Eat. Disord. 42, 402–408. doi: 10.1002/eat.20637
Corwin, R. L. (2004). Binge-type eating induced by limited access in rats does not require energy restriction on the previous day. Appetite 42, 139–142. doi: 10.1016/j.appet.2003.08.010
Corwin, R. L. (2006). Bingeing rats: a model of intermittent excessive behavior? Appetite 46, 11–15. doi: 10.1016/j.appet.2004.09.002
Corwin, R. L., Avena, N. M., and Boggiano, M. M. (2011). Feeding and reward: perspectives from three rat models of binge eating. Physiol. Behav. 104, 87–97. doi: 10.1016/j.physbeh.2011.04.041
Cottone, P., Sabino, V., Roberto, M., Bajo, M., Pockros, L., Frihauf, J. B., et al. (2009). CRF system recruitment mediates dark side of compulsive eating. Proc. Natl. Acad. Sci. U. S. A. 106, 20016–20020. doi: 10.1073/pnas.0908789106
Cottone, P., Sabino, V., Steardo, L., and Zorrilla, E. P. (2008). Intermittent access to preferred food reduces the reinforcing efficacy of chow in rats. Am. J. Physiol. Regul. Integr. Comp. Physiol. 295, R1066–R1076. doi: 10.1152/ajpregu.90309.2008
Czyzyk, T. A., Sahr, A. E., and Statnick, M. A. (2010). A model of binge-like eating behavior in mice that does not require food deprivation or stress. Obesity 18, 1710–1717. doi: 10.1038/oby.2010.46
D’Cunha, T. M., Chisholm, A., Hryhorczuk, C., Fulton, S., and Shalev, U. (2020). A role for leptin and ghrelin in the augmentation of heroin seeking induced by chronic food restriction. Psychopharmacology 237, 787–800. doi: 10.1007/s00213-019-05415-9
Darling, R. A., Dingess, P. M., Schlidt, K. C., Smith, E. M., and Brown, T. E. (2016). Incubation of food craving is independent of macronutrient composition. Sci. Rep. 6:30900. doi: 10.1038/srep30900
Davis, C. (2013). From passive overeating to "food addiction": a spectrum of compulsion and severity. ISRN Obes. 15:435027. doi: 10.1155/2013/435027
Davis, C. (2017). A commentary on the associations among 'food addiction', binge eating disorder, and obesity: overlapping conditions with idiosyncratic clinical features. Appetite 115, 3–8. doi: 10.1016/j.appet.2016.11.001
de Araujo, I. E., Oliveira-Maia, A. J., Sotnikova, T. D., Gainetdinov, R. R., Caron, M. G., Nicolelis, M. A., et al. (2008). Food reward in the absence of taste receptor signaling. Neuron 57, 930–941. doi: 10.1016/j.neuron.2008.01.032
de Vries, S. K., and Meule, A. (2016). Food addiction and bulimia nervosa: new data based on the Yale food addiction scale 2.0. Eur. Eat. Disord. Rev. 24, 518–522. doi: 10.1002/erv.2470
Decarie-Spain, L., Hryhorczuk, C., and Fulton, S. (2016). Dopamine signalling adaptations by prolonged high-fat feeding. Curr. Opin. Behav. Sci. 9, 136–143. doi: 10.1016/j.cobeha.2016.03.010
Deroche-Gamonet, V., Belin, D., and Piazza, P. V. (2004). Evidence for addiction-like behavior in the rat. Science 305, 1014–1017. doi: 10.1126/science.1099020
Devoto, F., Zapparoli, L., Bonandrini, R., Berlingeri, M., Ferrulli, A., Luzi, L., et al. (2018). Hungry brains: a meta-analytical review of brain activation imaging studies on food perception and appetite in obese individuals. Neurosci. Biobehav. Rev. 94, 271–285. doi: 10.1016/j.neubiorev.2018.07.017
DiFeliceantonio, A. G., Coppin, G., Rigoux, L., Edwin Thanarajah, S., Dagher, A., Tittgemeyer, M., et al. (2018). Supra-additive effects of combining fat and carbohydrate on food reward. Cell Metab. 28, 33–44.e3. doi: 10.1016/j.cmet.2018.05.018
Dimitriou, S. G., Rice, H. B., and Corwin, R. L. (2000). Effects of limited access to a fat option on food intake and body composition in female rats. Int. J. Eat. Disord. 28, 436–445. doi: 10.1002/1098-108X(200012)28:4<436::AID-EAT12>3.0.CO;2-P
Dingess, P. M., Darling, R. A., Derman, R. C., Wulff, S. S., Hunter, M. L., Ferrario, C. R., et al. (2017). Structural and functional plasticity within the nucleus Accumbens and prefrontal cortex associated with time-dependent increases in food Cue-seeking behavior. Neuropsychopharmacology 42, 2354–2364. doi: 10.1038/npp.2017.57
Domingo-Rodriguez, L., Ruiz de Azua, I., Dominguez, E., Senabre, E., Serra, I., Kummer, S., et al. (2020). A specific prelimbic-nucleus accumbens pathway controls resilience versus vulnerability to food addiction. Nat. Commun. 11:782. doi: 10.1038/s41467-020-14458-y
Dunn, D. P., Bastacky, J. M., Gray, C. C., Abtahi, S., and Currie, P. J. (2019). Role of mesolimbic ghrelin in the acquisition of cocaine reward. Neurosci. Lett. 709:134367. doi: 10.1016/j.neulet.2019.134367
Egecioglu, E., Engel, J. A., and Jerlhag, E. (2013). The glucagon-like peptide 1 analogue Exendin-4 attenuates the nicotine-induced locomotor stimulation, accumbal dopamine release, conditioned place preference as well as the expression of locomotor sensitization in mice. PLoS One 8:e77284. doi: 10.1371/journal.pone.0077284
Emilien, C., and Hollis, J. H. (2017). A brief review of salient factors influencing adult eating behaviour. Nutr. Res. Rev. 30, 233–246. doi: 10.1017/S0954422417000099
Engel, J. A., and Jerlhag, E. (2014). Role of appetite-regulating peptides in the pathophysiology of addiction: implications for pharmacotherapy. CNS Drugs 28, 875–886. doi: 10.1007/s40263-014-0178-y
Epstein, D. H., Kennedy, A. P., Furnari, M., Heilig, M., Shaham, Y., Phillips, K. A., et al. (2016). Effect of the CRF1-receptor antagonist pexacerfont on stress-induced eating and food craving. Psychopharmacology 233, 3921–3932. doi: 10.1007/s00213-016-4424-5
Erreger, K., Davis, A. R., Poe, A. M., Greig, N. H., Stanwood, G. D., and Galli, A. (2012). Exendin-4 decreases amphetamine-induced locomotor activity. Physiol. Behav. 106, 574–578. doi: 10.1016/j.physbeh.2012.03.014
Everitt, B. J., Belin, D., Economidou, D., Pelloux, Y., Dalley, J. W., and Robbins, T. W. (2008). Review. Neural mechanisms underlying the vulnerability to develop compulsive drug-seeking habits and addiction. Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci. 363, 3125–3135. doi: 10.1098/rstb.2008.0089
Figlewicz, D. P., Evans, S. B., Murphy, J., Hoen, M., and Baskin, D. G. (2003). Expression of receptors for insulin and leptin in the ventral tegmental area/substantia nigra (VTA/SN) of the rat. Brain Res. 964, 107–115. doi: 10.1016/S0006-8993(02)04087-8
Finlayson, G. (2017). Food addiction and obesity: unnecessary medicalization of hedonic overeating. Nat. Rev. Endocrinol. 13, 493–498. doi: 10.1038/nrendo.2017.61
Fletcher, P. C., and Kenny, P. J. (2018). Food addiction: a valid concept? Neuropsychopharmacology 43, 2506–2513. doi: 10.1038/s41386-018-0203-9
Furlong, T. M., Jayaweera, H. K., Balleine, B. W., and Corbit, L. H. (2014). Binge-like consumption of a palatable food accelerates habitual control of behavior and is dependent on activation of the dorsolateral striatum. J. Neurosci. 34, 5012–5022. doi: 10.1523/JNEUROSCI.3707-13.2014
Galic, M. A., and Persinger, M. A. (2002). Voluminous sucrose consumption in female rats: increased “nippiness” during periods of sucrose removal and possible oestrus periodicity. Psychol. Rep. 90, 58–60. doi: 10.2466/pr0.2002.90.1.58
Gallo, E. F., Meszaros, J., Sherman, J. D., Chohan, M. O., Teboul, E., Choi, C. S., et al. (2018). Accumbens dopamine D2 receptors increase motivation by decreasing inhibitory transmission to the ventral pallidum. Nat. Commun. 9:1086. doi: 10.1038/s41467-018-03272-2
Garcia, A. F., Webb, I. G., Yager, L. M., Seo, M. B., and Ferguson, S. M. (2020). Intermittent but not continuous access to cocaine produces individual variability in addiction susceptibility in rats. Psychopharmacology 237, 2929–2941. doi: 10.1007/s00213-020-05581-1
Gearhardt, A. N., Corbin, W. R., and Brownell, K. D. (2016). Development of the Yale food addiction scale version 2.0. Psychol. Addict. Behav. 30, 113–121. doi: 10.1037/adb0000136
Gearhardt, A. N., Davis, C., Kuschner, R., and Brownell, K. D. (2011). The addiction potential of hyperpalatable foods. Curr. Drug Abuse Rev. 4, 140–145. doi: 10.2174/1874473711104030140
Gearhardt, A. N., and Hebebrand, J. (2021a). The concept of "food addiction" helps inform the understanding of overeating and obesity: debate consensus. Am. J. Clin. Nutr. 113, 274–276. doi: 10.1093/ajcn/nqaa345
Gearhardt, A. N., and Hebebrand, J. (2021b). The concept of "food addiction" helps inform the understanding of overeating and obesity: YES. Am. J. Clin. Nutr. 113, 263–267. doi: 10.1093/ajcn/nqaa343
Gearhardt, A. N., and Schulte, E. M. (2021). Is food addictive? A review of the science. Annu. Rev. Nutr. 41, 387–410. doi: 10.1146/annurev-nutr-110420-111710
Gearhardt, A. N., Yokum, S., Orr, P. T., Stice, E., Corbin, W. R., and Brownell, K. D. (2011). Neural correlates of food addiction. Arch. Gen. Psychiatry 68, 808–816. doi: 10.1001/archgenpsychiatry.2011.32
George, O., Ghozland, S., Azar, M. R., Cottone, P., Zorrilla, E. P., Parsons, L. H., et al. (2007). CRF-CRF1 system activation mediates withdrawal-induced increases in nicotine self-administration in nicotine-dependent rats. Proc. Natl. Acad. Sci. U. S. A. 104, 17198–17203. doi: 10.1073/pnas.0707585104
Gerfen, C. R. (2023). Segregation of D1 and D2 dopamine receptors in the striatal direct and indirect pathways: an historical perspective. Front. Synaptic. Neurosci. 14:1002960. doi: 10.3389/fnsyn.2022.1002960
Gibney, M. J., Forde, C. G., Mullally, D., and Gibney, E. R. (2017). Ultra-processed foods in human health: a critical appraisal. Am. J. Clin. Nutr. 106, 717–724. doi: 10.3945/ajcn.117.160440
Giuliano, C., Robbins, T. W., Nathan, P. J., Bullmore, E. T., and Everitt, B. J. (2012). Inhibition of opioid transmission at the μ-opioid receptor prevents both food seeking and binge-like eating. Neuropsychopharmacology 37, 2643–2652. doi: 10.1038/npp.2012.128
Goldstein, R. Z., and Volkow, N. D. (2011). Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications. Nat. Rev. Neurosci. 12, 652–669. doi: 10.1038/nrn3119
Gordon, E. L., Ariel-Donges, A. H., Bauman, V., and Merlo, L. J. (2018). What is the evidence for "food addiction?" a systematic review. Nutrients 10:477. doi: 10.3390/nu10040477
Gourley, S. L., Zimmermann, K. S., Allen, A. G., and Taylor, J. R. (2016). The medial orbitofrontal cortex regulates sensitivity to outcome value. J. Neurosci 36, 4600–4613. doi: 10.1523/JNEUROSCI.4253-15.2016
Graham, D. L., Erreger, K., Galli, A., and Stanwood, G. D. (2013). GLP-1 analog attenuates cocaine reward. Mol. Psychiatry 18, 961–962. doi: 10.1038/mp.2012.141
Graziane, N. M., Sun, S., Wright, W. J., Jang, D., Liu, Z., Huang, Y. H., et al. (2016). Opposing mechanisms mediate morphine-and cocaine-induced generation of silent synapses. Nat. Neurosci. 19, 915–925. doi: 10.1038/nn.4313
Grimm, J. W. (2020). Incubation of food craving in rats: a review. J. Exp. Anal. Behav. 113, 37–47. doi: 10.1002/jeab.561
Grimm, J. W., Fyall, A. M., and Osincup, D. P. (2005). Incubation of sucrose craving: effects of reduced training and sucrose pre-loading. Physiol. Behav. 84, 73–79. doi: 10.1016/j.physbeh.2004.10.011
Hagan, M. M., Chandler, P. C., Wauford, P. K., Rybak, R. J., and Oswald, K. D. (2003). The role of palatable food and hunger as trigger factors in an animal model of stress induced binge eating. Int. J. Eat. Disord. 34, 183–197. doi: 10.1002/eat.10168
Hagan, M. M., Wauford, P. K., Chandler, P. C., Jarrett, L. A., Rybak, R. J., and Blackburn, K. (2002). A new animal model of binge eating: key synergistic role of past caloric restriction and stress. Physiol. Behav. 77, 45–54. doi: 10.1016/S0031-9384(02)00809-0
Halpern, C. H., Tekriwal, A., Santollo, J., Keating, J. G., Wolf, J. A., Daniels, D., et al. (2013). Amelioration of binge eating by nucleus accumbens shell deep brain stimulation in mice involves D2 receptor modulation. J. Neurosci. 33, 7122–7129. doi: 10.1523/JNEUROSCI.3237-12.2013
Han, W., Tellez, L. A., Perkins, M. H., Perez, I. O., Qu, T., Ferreira, J., et al. (2018). A neural circuit for gut-induced reward. Cells 175, 665–678. doi: 10.1016/j.cell.2018.08.049
Hancock, S. D., Menard, J. L., and Olmstead, M. C. (2005). Variations in maternal care influence vulnerability to stress-induced binge eating in female rats. Physiol. Behav. 85, 430–439. doi: 10.1016/j.physbeh.2005.05.007
Hardaway, J. A., Halladay, L. R., Mazzone, C. M., Pati, D., Bloodgood, D. W., Kim, M., et al. (2019). Central amygdala prepronociceptin-expressing neurons mediate palatable food consumption and reward. Neuron 102, 1037–1052. doi: 10.1016/j.neuron.2019.03.037
Hebebrand, J., Albayrak, Ö., Adan, R., Antel, J., Dieguez, C., de Jong, J., et al. (2014). "eating addiction", rather than "food addiction", better captures addictive-like eating behavior. Neurosci. Biobehav. Rev. 47, 295–306. doi: 10.1016/j.neubiorev.2014.08.016
Hebebrand, J., and Gearhardt, A. N. (2021). The concept of "food addiction" helps inform the understanding of overeating and obesity: NO. Am. J. Clin. Nutr. 113, 268–273. doi: 10.1093/ajcn/nqaa344
Hecht, E. M., Rabil, A., Martinez Steele, E., Abrams, G. A., Ware, D., Landy, D. C., et al. (2022). Cross-sectional examination of ultra-processed food consumption and adverse mental health symptoms. Public Health Nutr. 25, 3225–3234. doi: 10.1017/S1368980022001586
Hommel, J. D., Trinko, R., Sears, R. M., Georgescu, D., Liu, Z. W., Gao, X. B., et al. (2006). Leptin receptor signaling in midbrain dopamine neurons regulates feeding. Neuron 51, 801–810. doi: 10.1016/j.neuron.2006.08.023
Hone-Blanchet, A., and Fecteau, S. (2014). Overlap of food addiction and substance use disorders definitions: analysis of animal and human studies. Neuropharmacology 85, 81–90. doi: 10.1016/j.neuropharm.2014.05.019
Horseman, C., and Meyer, A. (2019). Neurobiology of addiction. Clin. Obstet. Gynecol. 62, 118–127. doi: 10.1097/GRF.0000000000000416
Hu, S., Ide, J. S., Zhang, S., and Chiang-shan, R. L. (2016). The right superior frontal gyrus and individual variation in proactive control of impulsive response. J. Neurosci. 36, 12688–12696. doi: 10.1523/JNEUROSCI.1175-16.2016
Iemolo, A., Valenza, M., Tozier, L., Knapp, C. M., Kornetsky, C., Steardo, L., et al. (2012). Withdrawal from chronic, intermittent access to a highly palatable food induces depressive-like behavior in compulsive eating rats. Behav. Pharmacol. 23, 593–602. doi: 10.1097/FBP.0b013e328357697f
Iniguez, S. D., Warren, B. L., Neve, R. L., Nestler, E. J., Russo, S. J., and Bolanos-Guzman, C. A. (2008). Insulin receptor substrate-2 in the ventral tegmental area regulates behavioral responses to cocaine. Behav. Neurosci. 122, 1172–1177. doi: 10.1037/a0012893
Jahng, J. W. (2013). “Stressful experiences in early life and subsequent food intake” in Animal models of eating disorders. Neuromethods. ed. N. M. Avena , 127–153.
Jamali, S., Zarrabian, S., and Haghparast, A. (2021). Similar role of mPFC orexin-1 receptors in the acquisition and expression of morphine- and food-induced conditioned place preference in male rats. Neuropharmacology 198:108764. doi: 10.1016/j.neuropharm.2021.108764
Jerlhag, E., Egecioglu, E., Landgren, S., Salomé, N., Heilig, M., Moechars, D., et al. (2009). Requirement of central ghrelin signaling for alcohol reward. PNAS 106, 11318–11323. doi: 10.1073/pnas.0812809106
Johnson, P. M., and Kenny, P. J. (2010). Dopamine D2 receptors in addiction-like reward dysfunction and compulsive eating in obese rats. Nat. Neurosci. 13, 635–641. doi: 10.1038/nn.2519
Joshi, A., Kool, T., Diepenbroek, C., Koekkoek, L. L., Eggels, L., Kalsbeek, A., et al. (2021). Dopamine D1 receptor signalling in the lateral shell of the nucleus accumbens controls dietary fat intake in male rats. Appetite 167:105597. doi: 10.1016/j.appet.2021.105597
Kenny, P. J. (2011). Common cellular and molecular mechanisms in obesity and drug addiction. Nat. Rev. Neurosci. 12, 638–651. doi: 10.1038/nrn3105
Kim, J., Zhang, X., Muralidhar, S., LeBlanc, S. A., and Tonegawa, S. (2017). Basolateral to central amygdala neural circuits for appetitive behaviors. Neuron 93, 1464–1479. doi: 10.1016/j.neuron.2017.02.034
Kinzig, K. P., Hargrave, S. L., and Honors, M. A. (2008). Binge-type eating attenuates corticosterone and hypophagic responses to restraint stress. Physiol. Behav. 95, 108–113. doi: 10.1016/j.physbeh.2008.04.026
Koban, L., Wager, T. D., and Kober, H. (2023). A neuromarker for drug and food craving distinguishes drug users from non-users. Nat. Neurosci. 26, 316–325. doi: 10.1038/s41593-022-01228-w
Koob, G. F., and Volkow, N. D. (2016). Neurobiology of addiction: a Neurocircuitry analysis. Lancet Psychiatry 3, 760–773. doi: 10.1016/S2215-0366(16)00104-8
Krasnova, I. N., Marchant, N. J., Ladenheim, B., McCoy, M. T., Panlilio, L. V., Bossert, J. M., et al. (2014). Incubation of methamphetamine and palatable food craving after punishment-induced abstinence. Neuropsychopharmacology 39, 2008–2016. doi: 10.1038/npp.2014.50
Kreisler, A. D., Garcia, M. G., Spierling, S. R., Hui, B. E., and Zorrilla, E. P. (2017). Extended vs. brief intermittent access to palatable food differently promote binge-like intake, rejection of less preferred food, and weight cycling in female rats. Physiol. Behav. 177, 305–316. doi: 10.1016/j.physbeh.2017.03.039
Kufahl, P., Li, Z., Risinger, R., Rainey, C., Piacentine, L., Wu, G., et al. (2008). Expectation modulates human brain responses to acute cocaine: a functional magnetic resonance imaging study. Biol. Psychiatry 63, 222–230. doi: 10.1016/j.biopsych.2007.03.021
la Fleur, S. E., Luijendijk, M. C., van Rozen, A. J., Kalsbeek, A., and Adan, R. A. (2011). A free-choice high-fat high-sugar diet induces glucose intolerance and insulin unresponsiveness to a glucose load not explained by obesity. Int. J. Obes. 35, 595–604. doi: 10.1038/ijo.2010.164
Labouèbe, G., Liu, S., Dias, C., Zou, H., Wong, J. C., Karunakaran, S., et al. (2013). Borgland SL insulin induces long-term depression of ventral tegmental area dopamine neurons via endocannabinoids. Nat. Neurosci. 16, 300–308. doi: 10.1038/nn.3321
Lacroix, E., Tavares, H., and von Ranson, K. M. (2018). Moving beyond the "eating addiction" versus "food addiction" debate: comment on Schulte et al. (2017). Appetite 130, 286–292. doi: 10.1016/j.appet.2018.06.025
Latagliata, E. C., Patrono, E., Puglisi-Allegra, S., and Ventura, R. (2010). Food seeking in spite of harmful consequences is under prefrontal cortical noradrenergic control. BMC Neurosci. 11:15. doi: 10.1186/1471-2202-11-15
Latner, J. D., Mond, J. M., Kelly, M. C., Haynes, S. N., and Hay, P. J. (2014). The loss of control over eating scale: development and psychometric evaluation. Int. J. Eat. Disord. 47, 647–659. doi: 10.1002/eat.22296
Lee, H. S., Giunti, E., Sabino, V., and Cottone, P. (2020). Consummatory, feeding microstructural, and metabolic effects induced by limiting access to either a high-sucrose or a high-fat diet. Nutrients 12:1610. doi: 10.3390/nu12061610
Lemeshow, A. R., Rimm, E. B., Hasin, D. S., Gearhardt, A. N., Flint, A. J., Field, A. E., et al. (2018). Food and beverage consumption and food addiction among women in the Nurses' health studies. Appetite 121, 186–197. doi: 10.1016/j.appet.2017.10.038
Li, X., Zeric, T., Kambhampati, S., Bossert, J. M., and Shaham, Y. (2015). The central amygdala nucleus is critical for incubation of methamphetamine craving. Neuropsychopharmacology 40, 1297–1306. doi: 10.1038/npp.2014.320
Limpens, J. H., Damsteegt, R., Broekhoven, M. H., Voorn, P., and Vanderschuren, L. J. (2015). Pharmacological inactivation of the prelimbic cortex emulates compulsive reward seeking in rats. Brain Res. 1628, 210–218. doi: 10.1016/j.brainres.2014.10.045
Lindgren, E., Gray, K., Miller, G., Tyler, R., Wiers, C. E., Volkow, N. D., et al. (2018). Food addiction: a common neurobiological mechanism with drug abuse. Front. Biosci. 23, 811–836. doi: 10.2741/4618
Lowe, M. R., Butryn, M. L., Didie, E. R., Annunziato, R. A., Thomas, J. G., Crerand, C. E., et al. (2009). The power of food scale. A new measure of the psychological influence of the food environment. Appetite 53, 114–118. doi: 10.1016/j.appet.2009.05.016
Lu, L., Hope, B. T., Dempsey, J., Liu, S. Y., Bossert, J. M., and Shaham, Y. (2005). Central amygdala ERK signaling pathway is critical to incubation of cocaine craving. Nat. Neurosci. 8, 212–219. doi: 10.1038/nn1383
Luo, Y. X., Huang, D., Guo, C., and Ma, Y. Y. (2021). Limited versus extended cocaine intravenous self-administration: behavioral effects and electrophysiological changes in insular cortex. CNS Neurosci. Ther. 2, 196–205. doi: 10.1111/cns.13469
Madangopal, R., Szelenyi, E. R., Nguyen, J., Brenner, M. B., Drake, O. R., Pham, D. Q., et al. (2022). Incubation of palatable food craving is associated with brain-wide neuronal activation in mice. Proc. Natl. Acad. Sci. 119:e2209382119. doi: 10.1073/pnas.2209382119
Mar, A. C., Walker, A. L., Theobald, D. E., Eagle, D. M., and Robbins, T. W. (2011). Dissociable effects of lesions to orbitofrontal cortex subregions on impulsive choice in the rat. J. Neurosci. 31, 6398–6404. doi: 10.1523/JNEUROSCI.6620-10.2011
Markus, C. R., Rogers, P. J., Brouns, F., and Schepers, R. (2017). Eating dependence and weight gain; no human evidence for a 'sugar-addiction' model of overweight. Appetite 114, 64–72. doi: 10.1016/j.appet.2017.03.024
Matikainen-Ankney, B. A., Legaria, A. A., Pan, Y., Vachez, Y. M., Murphy, C. A., Schaefer, R. F., et al. (2023). Nucleus Accumbens D1 receptor–expressing spiny projection neurons control food motivation and obesity. Biol. Psychiatry 93, 512–523. doi: 10.1016/j.biopsych.2022.10.003
Mebel, D. M., Wong, J. C. Y., Dong, Y. J., and Borgland, S. L. (2012). Insulin in the ventral tegmental area reduces hedonic feeding and suppresses dopamine concentration via increased reuptake. Eur. J. Neurosci. 36, 2336–2346. doi: 10.1111/j.1460-9568.2012.08168.x
Meng, X., Huang, D., Ao, H., Wang, X., and Gao, X. (2020). Food cue recruits increased reward processing and decreased inhibitory control processing in the obese/overweight: an activation likelihood estimation meta-analysis of fMRI studies. Obes. Res. Clin. Pract. 14, 127–135. doi: 10.1016/j.orcp.2020.02.004
Merchenthaler, I., Lane, M., and Shughrue, P. (1999). Distribution of pre-pro-glucagon and glucagon-like peptide-1 receptor messenger RNAs in the rat central nervous system. J. Comp. Neurol. 403, 261–280. doi: 10.1002/(SICI)1096-9861(19990111)403:2<261::AID-CNE8>3.0.CO;2-5
Meule, A., and Gearhardt, A. N. (2014). Food addiction in the light of DSM-5. Nutrients 6, 3653–3671. doi: 10.3390/nu6093653
Meye, F. J., and Adan, R. A. (2014). Feelings about food: the ventral tegmental area in food reward and emotional eating. Trends Pharmacol. Sci. 35, 31–40. doi: 10.1016/j.tips.2013.11.003
Micioni Di Bonaventura, M. V., Lutz, T. A., Romano, A., Pucci, M., Geary, N., Asarian, L., et al. (2017). Estrogenic suppression of binge-like eating elicited by cyclic food restriction and frustrative-nonreward stress in female rats. Int. J. Eat. Disord. 50, 624–635. doi: 10.1002/eat.22687
Miller, D. K., Wilkins, L. H., Bardo, M. T., Crooks, P. A., and Dwoskin, L. P. (2001). Once weekly administration of nicotine produces long-lasting locomotor sensitization in rats via a nicotinic receptor-mediated mechanism. Psychopharmacology 156, 469–476. doi: 10.1007/s002130100747
Monteiro, C. A., Cannon, G., Levy, R. B., Moubarac, J. C., Louzada, M. L., Rauber, F., et al. (2019). Ultra-processed foods: what they are and how to identify them. Public Health Nutr. 22, 936–941. doi: 10.1017/S1368980018003762
Monteiro, C. A., Cannon, G., Moubarac, J. C., Levy, R. B., Louzada, M. L. C., and Jaime, P. C. (2018). The UN decade of nutrition, the NOVA food classification and the trouble with ultra-processing. Public Health Nutr. 21, 5–17. doi: 10.1017/S1368980017000234
Monteiro, C. A., Levy, R. B., Claro, R. M., Castro, I. R., and Cannon, G. (2010). A new classification of foods based on the extent and purpose of their processing. Cad. Saude Publica 26, 2039–2049. doi: 10.1590/S0102-311X2010001100005
Moore, C. F., Cheng, J. E., Sabino, V., and Cottone, P. (2019). “Modeling and testing compulsive eating behaviors in animals” in Compulsive eating behavior and food addiction: Emerging pathological constructs. eds. P. Cottone, V. Sabino, C. F. Moore, and G. F. Koob (Cambridge, MA: Elsevier Academic Press), 359–388.
Morton, G. J., Blevins, J. E., Kim, F., Matsen, M., and Figlewicz, D. P. (2009). The action of leptin in the ventral tegmental area to decrease food intake is dependent on Jak-2 signaling. Am. J. Physiol. Endocrinol. Metab. 297, E202–E210. doi: 10.1152/ajpendo.90865.2008
Naef, L., Seabrook, L., Hsiao, J., Li, C., and Borgland, S. L. (2019). Insulin in the ventral tegmental area reduces cocaine-evoked dopamine in the nucleus accumbens in vivo. Eur. J. Neurosci. 50, 2146–2155. doi: 10.1111/ejn.14291
Navandar, M., Martín-García, E., Maldonado, R., Lutz, B., Gerber, S., and Ruiz de Azua, I. (2021). Transcriptional signatures in prefrontal cortex confer vulnerability versus resilience to food and cocaine addiction-like behavior. Sci. Rep. 11:9076. doi: 10.1038/s41598-021-88363-9
Ndiaye, F. K., Huyvaert, M., Ortalli, A., Canouil, M., Lecoeur, C., Verbanck, M., et al. (2020). The expression of genes in top obesity-associated loci is enriched in insula and substantia nigra brain regions involved in addiction and reward. Int. J. Obes. 44, 539–543. doi: 10.1038/s41366-019-0428-7
Newmyer, B. A., Whindleton, C. M., Klein, P. M., Beenhakker, M. P., Jones, M. K., and Scott, M. M. (2019). VIPergic neurons of the infralimbic and prelimbic cortices control palatable food intake through separate cognitive pathways. JCI Insight 4:6283. doi: 10.1172/jci.insight.126283
Novelle, M. G., and Diéguez, C. (2018). Food addiction and binge eating: lessons learned from animal models. Nutrients 10:71. doi: 10.3390/nu10010071
Oswald, K. D., Murdaugh, D. L., King, V. L., and Boggiano, M. M. (2011). Motivation for palatable food despite consequences in an animal model of binge eating. Int. J. Eat. Disord. 44, 203–211. doi: 10.1002/eat.20808
Pagano, R., Salamian, A., Zielinski, J., Beroun, A., Nalberczak-Skóra, M., Skonieczna, E., et al. (2023). Arc controls alcohol cue relapse by a central amygdala mechanism. Mol. Psychiatry 28, 733–745. doi: 10.1038/s41380-022-01849-4
Pankevich, D. E., Teegarden, S. L., Hedin, A. D., Jensen, C. L., and Bale, T. L. (2010). Caloric restriction experience reprograms stress and orexigenic pathways and promotes binge eating. J. Neurosci. 30, 16399–16407. doi: 10.1523/JNEUROSCI.1955-10.2010
Parnarouskis, L., and Gearhardt, A. N. (2022). Preliminary evidence that tolerance and withdrawal occur in response to ultra-processed foods. Curr. Addict. Rep. 9, 282–289. doi: 10.1007/s40429-022-00425-8
Parylak, S. L., Koob, G. F., and Zorrilla, E. P. (2011). The dark side of food addiction. Physiol. Behav. 104, 149–156. doi: 10.1016/j.physbeh.2011.04.063
Patrono, E., Di Segni, M., Patella, L., Andolina, D., Valzania, A., Latagliata, E. C., et al. (2015). When chocolate seeking becomes compulsion: gene-environment interplay. PLoS One 10:e0120191. doi: 10.1371/journal.pone.0120191
Pecoraro, N., Reyes, F., Gomez, F., Bhargava, A., and Dallman, M. F. (2004). Chronic stress promotes palatable feeding, which reduces signs of stress: feedforward and feedback effects of chronic stress. Endocrinology 145, 3754–3762. doi: 10.1210/en.2004-0305
Pickering, C., Alsiö, J., Hulting, A. L., and Schiöth, H. B. (2009). Withdrawal from free-choice high-fat high-sugar diet induces craving only in obesity-prone animals. Psychopharmacology 204, 431–443. doi: 10.1007/s00213-009-1474-y
Pursey, K. M., Collins, C. E., Stanwell, P., and Burrows, T. L. (2015). Foods and dietary profiles associated with 'food addiction' in young adults. Addict. Behav. Rep. 2, 41–48. doi: 10.1016/j.abrep.2015.05.007
Randoph, T. G. (1956). The descriptive features of food addiction; addictive eating and drinking. Q. J. Stud. Alcohol 17, 198–224. doi: 10.15288/qjsa.1956.17.198
Rinaman, L. (2010). Ascending projections from the caudal visceral nucleus of the solitary tract to brain regions involved in food intake and energy expenditure. Brain Res. 1350, 18–34. doi: 10.1016/j.brainres.2010.03.059
Roberto, M., Spierling, S., Kirson, D., and Zorrilla, E. (2017). Corticotropin releasing factor (CRF) and addictive behaviors. Int. Rev. Neurobiol. 136, 5–51. doi: 10.1016/bs.irn.2017.06.004
Robinson, M. J., Fischer, A. M., Ahuja, A., Lesser, E. N., and Maniates, H. (2016). Roles of "wanting" and "liking" in motivating behavior: gambling, food, and drug addictions. Curr. Top. Behav. Neurosci. 27, 105–136. doi: 10.1007/7854_2015_387
Rodd, Z. A., Bell, R. L., Sable, H. J., Murphy, J. M., and McBride, W. J. (2004). Recent advances in animal models of alcohol craving and relapse. Pharmacol. Biochem. Behav. 79, 439–450. doi: 10.1016/j.pbb.2004.08.018
Rogers, P. J. (2017). Food and drug addictions: similarities and differences. Pharmacol. Biochem. Behav. 153, 182–190. doi: 10.1016/j.pbb.2017.01.001
Rossetti, C., Spena, G., Halfon, O., and Boutrel, B. (2014). Evidence for a compulsive-like behavior in rats exposed to alternate access to highly preferred palatable food. Addict. Biol. 19, 975–985. doi: 10.1111/adb.12065
Roura-Martínez, D., Ucha, M., Orihuel, J., Ballesteros-Yáñez, I., Castillo, C. A., Marcos, A., et al. (2020). Central nucleus of the amygdala as a common substrate of the incubation of drug and natural reinforcer seeking. Addict. Biol. 25:e12706. doi: 10.1111/adb.12706
Saad, L., Sartori, M., Pol Bodetto, S., Romieu, P., Kalsbeek, A., Zwiller, J., et al. (2019). Regulation of brain DNA methylation factors and of the Orexinergic system by cocaine and food self-administration. Mol. Neurobiol. 56, 5315–5331. doi: 10.1007/s12035-018-1453-6
Salamone, J. D., and Correa, M. (2012). The mysterious motivational functions of mesolimbic dopamine. Neuron 76, 470–485. doi: 10.1016/j.neuron.2012.10.021
Salamone, J. D., and Correa, M. (2013). Dopamine and food addiction: lexicon badly needed. Biol. Psychiatry 73, 15–24. doi: 10.1016/j.biopsych.2012.09.027
Salamone, J. D., Pardo, M., Yohn, S. E., López-Cruz, L., SanMiguel, N., and Correa, M. (2016). Mesolimbic dopamine and the regulation of motivated behavior. Curr. Top. Behav. Neurosci. 27, 231–257. doi: 10.1007/7854_2015_383
Sanchez, I., Lucas, I., Munguía, L., Camacho-Barcia, L., Giménez, M., Sánchez-González, J., et al. (2022). Food addiction in anorexia nervosa: implications for the understanding of crossover diagnosis. Eur. Eat. Disord. Rev. 30, 278–288. doi: 10.1002/erv.2897
Sandoval-Rodríguez, R., Parra-Reyes, J. A., Han, W., Rueda-Orozco, P. E., Perez, I. O., de Araujo, I. E., et al. (2023). D1 and D2 neurons in the nucleus accumbens enable positive and negative control over sugar intake in mice. Cell Rep. 42:2190. doi: 10.1016/j.celrep.2023.112190
Sarkar, S., Kochhar, K. P., and Khan, N. A. (2019). Fat addiction: psychological and physiological trajectory. Nutrients 11:2785. doi: 10.3390/nu11112785
Schatzker, M., de Araujo, I. E., and Small, D. M. (2020). Rethinking food reward. Annu. Rev. Psychol. 71, 139–164. doi: 10.1146/annurev-psych-122216-011643
Schienle, A., Schafer, A., Hermann, A., and Vaitl, D. (2009). Binge-eating disorder: reward sensitivity and brain activation to images of food. Biol. Psychiatry 65, 654–661. doi: 10.1016/j.biopsych.2008.09.028
Schuette, L. M., Gray, C. C., and Currie, P. J. (2013). Microinjection of ghrelin into the ventral tegmental area potentiates cocaine-induced conditioned place preference. J. Behav. Brain Sci. 3:276. doi: 10.4236/jbbs.2013.38060
Schulte, E. M., Avena, N. M., and Gearhardt, A. N. (2015). Which foods may be addictive? The roles of processing, fat content, and glycemic load. PLoS One 10:e0117959. doi: 10.1371/journal.pone.0117959
Seabrook, L. T., Naef, L., Baimel, C., Judge, A. K., Kenney, T., Ellis, M., et al. (2023). Disinhibition of the orbitofrontal cortex biases decision-making in obesity. Nat. Neurosci. 26, 92–106. doi: 10.1038/s41593-022-01210-6
See, R. E., Fuchs, R. A., Ledford, C. C., and McLaughlin, J. (2003). Drug addiction, relapse, and the amygdala. Ann. N. Y. Acad. Sci. 985, 294–307. doi: 10.1111/j.1749-6632.2003.tb07089.x
Sell, L. A., Morris, J. S., Bearn, J., Frackowiak, R. S. J., Friston, K. J., and Dolan, R. J. (2000). Neural responses associated with cue evoked emotional states and heroin in opiate addicts. Drug Alcohol Depend 60, 207–216. doi: 10.1016/S0376-8716(99)00158-1
Sharma, S., Fernandes, M. F., and Fulton, S. (2013). Adaptations in brain reward circuitry underlie palatable food cravings and anxiety induced by high-fat diet withdrawal. Int. J. Obes. 37, 1183–1191. doi: 10.1038/ijo.2012.197
Sharma, S., and Fulton, S. (2013). Diet-induced obesity promotes depressive-like behaviour that is associated with neural adaptations in brain reward circuitry. Int. J. Obes. 37, 382–389. doi: 10.1038/ijo.2012.48
Shen, H., Moussawi, K., Zhou, W., Toda, S., and Kalivas, P. W. (2011). Heroin relapse requires long-term potentiation-like plasticity mediated by NMDA2b-containing receptors. Proc. Natl. Acad. Sci. U. S. A. 108, 19407–19412. doi: 10.1073/pnas.1112052108
Shirazi, R. H., Dickson, S. L., and Skibicka, K. P. (2013). Gut peptide GLP-1 and its analogue, exendin-4, decrease alcohol intake and reward. PLoS One 8:e61965. doi: 10.1371/journal.pone.0061965
Shriner, R., and Gold, M. (2014). Food addiction: an evolving nonlinear science. Nutrients 6, 5370–5391. doi: 10.3390/nu6115370
Sinha, R., and Jastreboff, A. M. (2013). Stress as a common risk factor for obesity and addiction. Biol. Psychiatry 73, 827–835. doi: 10.1016/j.biopsych.2013.01.032
Skibicka, K. P., Hansson, C., Alvarez-Crespo, M., Friberg, P. A., and Dickson, S. L. (2011). Ghrelin directly targets the ventral tegmental area to increase food motivation. Neuroscience 180, 129–137. doi: 10.1016/j.neuroscience.2011.02.016
Smith, R. J., and Aston-Jones, G. (2008). Noradrenergic transmission in the extended amygdala: role in increased drug-seeking and relapse during protracted drug abstinence. Brain Struct. Funct. 213, 43–61. doi: 10.1007/s00429-008-0191-3
Soares-Cunha, C., Coimbra, B., David-Pereira, A., Borges, S., Pinto, L., Costa, P., et al. (2016). Activation of D2 dopamine receptor-expressing neurons in the nucleus accumbens increases motivation. Nat. Commun. 23:11829. doi: 10.1038/ncomms11829
Soares-Cunha, C., de Vasconcelos, N. A., Coimbra, B., Domingues, A. V., Silva, J. M., Loureiro-Campos, E., et al. (2020). Nucleus accumbens medium spiny neurons subtypes signal both reward and aversion. Mol. Psychiatry 25, 3241–3255. doi: 10.1038/s41380-019-0484-3
Song, S., Zilverstand, A., Gui, W., Pan, X., and Zhou, X. (2022). Reducing craving and consumption in individuals with drug addiction, obesity or overeating through neuromodulation intervention: a systematic review and meta-analysis of its follow-up effects. Addiction 117, 1242–1255. doi: 10.1111/add.15686
Spierling, S., de Guglielmo, G., Kirson, D., Kreisler, A., Roberto, M., George, O., et al. (2020). Insula to ventral striatal projections mediate compulsive eating produced by intermittent access to palatable food. Neuropsychopharmacology 4, 579–588. doi: 10.1038/s41386-019-0538-x
Stice, E., and Burger, K. (2015). “Dieting as a risk factor for eating disorders” in The Wiley handbook of eating disorders. eds. L. Smolak and M. P. Levine, 312–323.
Stice, E., Spoor, S., Bohon, C., and Small, D. M. (2008). Relation between obesity and blunted striatal response to food is moderated by TaqIA A1 allele. Science 322, 449–452. doi: 10.1126/science.1161550
Stice, E., and Yokum, S. (2021). Neural vulnerability factors that predict future weight gain. Curr. Obes. Rep. 10, 435–443. doi: 10.1007/s13679-021-00455-9
Stunkard, A. J., and Messick, S. (1985). The three-factor eating questionnaire to measure dietary restraint, disinhibition and hunger. J. Psychosom. Res. 29, 71–83. doi: 10.1016/0022-3999(85)90010-8
Swinford-Jackson, S. E., Huffman, P. J., Knouse, M. C., Thomas, A. S., Rich, M. T., Mankame, S., et al. (2023). High frequency DBS-like optogenetic stimulation of nucleus accumbens dopamine D2 receptor-containing neurons attenuates cocaine reinstatement in male rats. Neuropsychopharmacology 48, 459–467. doi: 10.1038/s41386-022-01495-y
Tan, B., Nöbauer, T., Browne, C. J., Nestler, E. J., Vaziri, A., and Friedman, J. M. (2022). Dynamic processing of hunger and thirst by common mesolimbic neural ensembles. Proc. Natl. Acad. Sci. U. S. A. 119:e2211688119. doi: 10.1073/pnas.2211688119
Teegarden, S. L., and Bale, T. L. (2007). Decreases in dietary preference produce increased emotionality and risk for dietary relapse. Biol. Psychiatry 61, 1021–1029. doi: 10.1016/j.biopsych.2006.09.032
Terrier, J., Lüscher, C., and Pascoli, V. (2016). Cell-type specific insertion of GluA2-lacking AMPARs with cocaine exposure leading to sensitization, cue-induced seeking, and incubation of craving. Neuropsychopharmacology 41, 1779–1789. doi: 10.1038/npp.2015.345
Thompson, A. K., Fourman, S., Packard, A. E., Egan, A. E., Ryan, K. K., and Ulrich-Lai, Y. M. (2015). Metabolic consequences of chronic intermittent mild stress exposure. Physiol. Behav. 150, 24–30. doi: 10.1016/j.physbeh.2015.02.038
Tiedemann, L. J., Schmid, S. M., Hettel, J., Giesen, K., Francke, P., Büchel, C., et al. (2017). Central insulin modulates food valuation via mesolimbic pathways. Nat. Commun. 8:16052. doi: 10.1038/ncomms16052
Tom, R. L., Ahuja, A., Maniates, H., Freeland, C. M., and Robinson, M. J. (2019). Optogenetic activation of the central amygdala generates addiction-like preference for reward. Eur. J. Neurosci. 50, 2086–2100. doi: 10.1111/ejn.13967
Tomasi, D., and Volkow, N. D. (2013). Striatocortical pathway dysfunction in addiction and obesity: differences and similarities. Crit. Rev. Biochem. Mol. Biol. 48, 1–19. doi: 10.3109/10409238.2012.735642
Tran, H., Poinsot, P., Guillaume, S., Delaunay, D., Bernetiere, M., Bégin, C., et al. (2020). Food addiction as a proxy for anorexia nervosa severity: new data on the Yale food addiction scale 2.0. Psychiatry Res. 293:113472. doi: 10.1016/j.psychres.2020.113472
Trujillo, K. A., Zamora, J. J., and Warmoth, K. P. (2008). Increased response to ketamine following treatment at long intervals: implications for intermittent use. Biol. Psychiatry 63, 178–183. doi: 10.1016/j.biopsych.2007.02.014
Ulrich-Lai, Y. M., Christiansen, A. M., Ostrander, M. M., Jones, A. A., Jones, K. R., Choi, D. C., et al. (2010). Pleasurable behaviors reduce stress via brain reward pathways. Proc. Natl. Acad. Sci. U. S. A. 107, 20529–20534. doi: 10.1073/pnas.1007740107
Ulrich-Lai, Y. M., Fulton, S., Wilson, M., Petrovich, G., and Rinaman, L. (2015). Stress exposure, food intake and emotional state. Stress 18, 381–399. doi: 10.3109/10253890.2015.1062981
Vainik, U., García-García, I., and Dagher, A. (2019). Uncontrolled eating: a unifying heritable trait linked with obesity, overeating, personality and the brain. Eur. J. Neurosci. 50, 2430–2445. doi: 10.1111/ejn.14352
Vainik, U., Misic, B., Zeighami, Y., Michaud, A., Mõttus, R., and Dagher, A. (2020). Obesity has limited behavioural overlap with addiction and psychiatric phenotypes. Nat. Hum. Behav. 4, 27–35. doi: 10.1038/s41562-019-0752-x
Valdivia, S., Cornejo, M. P., Reynaldo, M., De Francesco, P. N., and Perello, M. (2015). Escalation in high fat intake in a binge eating model differentially engages dopamine neurons of the ventral tegmental area and requires ghrelin signaling. Psychoneuroendocrinology 60, 206–216. doi: 10.1016/j.psyneuen.2015.06.018
Vanderschuren, L. J., and Everitt, B. J. (2004). Drug seeking becomes compulsive after prolonged cocaine self-administration. Science 305, 1017–1019. doi: 10.1126/science.1098975
Vazquez-Herrera, N. V., Zepeda-Ruiz, W. A., and Velazquez-Martinez, D. N. (2021). Binge eating behavior and incentive motivation with a cafeteria diet. Behav. Process. 190:104447. doi: 10.1016/j.beproc.2021.104447
Venniro, M., Caprioli, D., Zhang, M., Whitaker, L. R., Zhang, S., Warren, B. L., et al. (2017). The anterior insular cortex→central amygdala glutamatergic pathway is critical to relapse after contingency management. Neuron 96, 414–427.e8. doi: 10.1016/j.neuron.2017.09.024
Volkow, N. D., and Baler, R. D. (2014). Addiction science: uncovering neurobiological complexity. Neuropharmacology 76, 235–249. doi: 10.1016/j.neuropharm.2013.05.007
Volkow, N. D., Fowler, J. S., Wang, G. J., Telang, F., Logan, J., Jayne, M., et al. (2010). Cognitive control of drug craving inhibits brain reward regions in cocaine abusers. NeuroImage 49, 2536–2543. doi: 10.1016/j.neuroimage.2009.10.088
Volkow, N. D., Michaelides, M., and Baler, R. (2019). The neuroscience of drug reward and addiction. Physiol. Rev. 99, 2115–2140. doi: 10.1152/physrev.00014.2018
Volkow, N. D., and Morales, M. (2015). The brain on drugs: from reward to addiction. Cells 162, 712–725. doi: 10.1016/j.cell.2015.07.046
Volkow, N. D., Wang, G. J., Fowler, J. S., Tomasi, D., and Baler, R. (2012). Food and drug reward: overlapping circuits in human obesity and addiction. Curr. Top. Behav. Neurosci. 11, 1–24. doi: 10.1007/7854_2011_169
Volkow, N. D., Wise, R. A., and Baler, R. (2017). The dopamine motive system: implications for drug and food addiction. Nat. Rev. Neurosci. 18, 741–752. doi: 10.1038/nrn.2017.130
Vucetic, Z., Carlin, J. L., Totoki, K., and Reyes, T. M. (2012). Epigenetic dysregulation of the dopamine system in diet-induced obesity. J. Neurochem. 120, 891–898. doi: 10.1111/j.1471-4159.2012.07649.x
Wang, Z., Faith, M., Patterson, F., Tang, K., Kerrin, K., Wileyto, E. P., et al. (2007). Neural substrates of abstinence-induced cigarette cravings in chronic smokers. J. Neurosci. 27, 14035–14040. doi: 10.1523/JNEUROSCI.2966-07.2007
Wang, G. J., Volkow, N. D., Thanos, P. K., and Fowler, J. S. (2004). Similarity between obesity and drug addiction as assessed by neurofunctional imaging: a concept review. J. Addict. Dis. 23, 39–53. doi: 10.1300/J069v23n03_04
Warlow, S. M., and Berridge, K. C. (2021). Incentive motivation: ‘wanting’ roles of central amygdala circuitry. Behav. Brain Res. 411:113376. doi: 10.1016/j.bbr.2021.113376
Warlow, S. M., Naffziger, E. E., and Berridge, K. C. (2020). The central amygdala recruits mesocorticolimbic circuitry for pursuit of reward or pain. Nat. Commun. 11:2716. doi: 10.1038/s41467-020-16407-1
Wellman, P. J., Clifford, P. S., Rodriguez, J., Hughes, S., Eitan, S., Brunel, L., et al. (2011). Pharmacologic antagonism of ghrelin receptors attenuates development of nicotine induced locomotor sensitization in rats. Regul. Pept. 172, 77–80. doi: 10.1016/j.regpep.2011.08.014
Westwater, M. L., Fletcher, P. C., and Ziauddeen, H. (2016). Sugar addiction: the state of the science. Eur. J. Nutr. 55, 55–69. doi: 10.1007/s00394-016-1229-6
Wise, R. A. (2009). Roles for nigrostriatal--not just mesocorticolimbic--dopamine in reward and addiction. Trends Neurosci. 32, 517–524. doi: 10.1016/j.tins.2009.06.004
Wiss, D. (2022). Clinical considerations of ultra-processed food addiction across weight classes: an eating disorder treatment and care perspective. Curr. Addict. Rep. 9, 255–267. doi: 10.1007/s40429-022-00411-0
Wiss, D. A., Avena, N., and Rada, P. (2018). Sugar addiction: from evolution to revolution. Front. Psych. 9:545. doi: 10.3389/fpsyt.2018.00545
Wojnicki, F. H., Johnson, D. S., Charny, G., and Corwin, R. L. (2015). Development of bingeing in rats altered by a small operant requirement. Physiol. Behav. 152, 112–118. doi: 10.1016/j.physbeh.2015.09.009
Wolf, M. E., and Tseng, K. Y. (2012). Calcium-permeable AMPA receptors in the VTA and nucleus accumbens after cocaine exposure: when, how, and why. Front. Mol. Neurosci. 5:72. doi: 10.3389/fnmol.2012.00072
Yakovenko, V., Speidel, E. R., Chapman, C. D., and Dess, N. K. (2011). Food dependence in rats selectively bred for low versus high saccharin intake. Implications for "food addiction". Appetite 57, 397–400. doi: 10.1016/j.appet.2011.06.002
Ziauddeen, H., Farooqi, I., and Fletcher, P. C. (2012). Obesity and the brain: how convincing is the addiction model? Nat. Rev. Neurosci. 13, 279–286. doi: 10.1038/nrn3212
Keywords: animal models, eating disorders, food addiction, substance use disorder, eating addiction
Citation: Passeri A, Municchi D, Cavalieri G, Babicola L, Ventura R and Di Segni M (2023) Linking drug and food addiction: an overview of the shared neural circuits and behavioral phenotype. Front. Behav. Neurosci. 17:1240748. doi: 10.3389/fnbeh.2023.1240748
Edited by:
James G. Pfaus, Charles University, CzechiaReviewed by:
Alfonso Abizaid, Carleton University, CanadaKent Berridge, University of Michigan, United States
Copyright © 2023 Passeri, Municchi, Cavalieri, Babicola, Ventura and Di Segni. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Rossella Ventura, rossella.ventura@uniroma1.it
†These authors share first authorship
‡These authors share last authorship