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    Chapter 4: The Propensity to Attribute Incentive Salience to Drug Cues and Poor Cognitive Control Combine to Render Sign-Trackers Susceptible to Addiction

    Terry E. Robinson*, Crystal Carr, and Alex B. Kawa

    Department of Psychology (Biopsychology), the University of Michigan

    Corresponding Author:

    Terry E. Robinson, PhD, East Hall, University of Michigan, 530 Church St., Ann Arbor, Michigan 48109; e-mail: ter@umich.edu; phone: (734) 358-8055.

    Abstract
    There are at least two major psychological factors thought to contribute to the development of problematic drug use and addiction. On one hand, drugs and drug cues acquire pathological motivational value, which leads to excessive drug “wanting” and a high propensity to relapse, especially in the presence of drug cues. On the other hand, poor cognitive/attentional control over behavior can result in impulsivity and difficulty in inhibiting drug-seeking and taking behavior when faced with temptations. The former psychological process—incentive salience attribution—is mediated by “bottom-up” dopamine-dependent neural systems, whereas cognitive control involves the activity of “top-down” acetylcholine-dependent neural systems. In this chapter, we discuss how individual variation in these neuropsychological processes combine and interact to influence vulnerability to addiction. It is suggested that animals that are especially prone to attribute incentive salience to drug cues (“sign-trackers”) also have relatively weak cognitive/attentional control over their behavior, and this “double-whammy” results in an endophenotype with a high propensity to transition from experimental/recreational patterns of drug use to those that define addiction.
    Keywords: acetylcholine; addiction; attention; autoshaping; dopamine; goal-tracking; incentive salience; motivation; Pavolvian learning;  prefrontal cortex; sensitization; sign-tracking

    Introduction

    Each day we are constantly faced with choices concerning what goals to pursue in a given moment. Some choices may be adaptive, promoting our welfare (e.g., obtaining food), and others, although desired in the moment, may be maladaptive (taking drugs). Some choices may be conscious and deliberative and others made quickly, without much awareness (Kahneman, 2011). The choices we make are influenced to a considerable degree by cues in the environment that in the past have been associated with different outcomes, even if we are unaware of their influence on our behavior (Johansson et al., 2006; Childress et al., 2008). Indeed, cues that predict the receipt or availability of biologically important objects, such as food, can come to acquire some of the properties formally associated only with the biologically important object. This form of learning, which guides us toward objects of desire and away from those that may harm us, is called Pavlovian learning, named after the famous Russian scientist who conducted the first systematic studies on this topic (Pavlov, 1927). The biologically important object is called the unconditioned stimulus (US) and the cue associated with it is called the conditioned stimulus (CS). In the case of Pavlov’s seminal studies presentation of the US (meat) caused dogs to salivate (an unconditioned response, UR), and presentation of a sound initially did not. However, if presentation of the sound (CS) came to reliably predict receipt of the US, the CS itself began to evoke salivation (the conditioned response, CR). Although Pavlov mostly studied relatively reflexive CRs, such as salivation, it is now known that Pavlovian learning has far more profound effects on behavior and psychological function than this. As put by the American learning theorist, Robert Rescorla (1988), Pavlovian conditioning involves “the learning of relations among events so as to allow the organism to represent its environment” (p. 151), and it “is intimately involved in the control of central psychological processes, such as emotions and motivations” (p. 157).

    Pavlovian Conditioned Motivation

    Indeed, Pavlovian CSs do not only evoke simple CRs, but they can come to generate complex emotional and motivational states that can exert considerable control over our behavior, if CSs are attributed with incentive salience and thus additionally acquire the properties of an incentive stimulus (Berridge, 2001; Bindra, 1978; Lajoie and Bindra, 1976; Rescorla, 1988). An incentive is defined as “something that arouses feeling, or incites to action; an exciting cause or motive; an incitement, provocation, spur” (Oxford English Dictionary). Importantly, a Pavlovian CS, capable of evoking a CR, does not always additionally acquire the motivational properties of an incentive stimulus; that is, a perfectly effective CS does not necessarily function as an incentive stimulus. It turns out that there is a great deal of individual variation in the extent to which CSs are attributed with incentive salience (for reviews see Saunders and Robinson, 2013; Robinson et al., 2014; and other chapters in this book).

    How does one tell if a CS also has incentive motivational properties in a nonhuman animal? Barry Everitt and his colleagues (Everitt et al., 2001; Cardinal et al., 2002; Milton and Everitt, 2010) have nicely defined the three fundamental properties of an incentive stimulus and procedures that can be used to assess if a stimulus has these properties. An incentive stimulus has three defining properties. One, it is attention-grabbing (e.g., Hickey and Peelen, 2015) and attractive, which can promote approach into close proximity with it. In nonhuman animals approach is typically measured using procedure in which presentation of a discrete cue (CS, often a lever) predicts food delivery at a different location. The extent to which the lever-CS (“sign”) produces approach and engagement with it is taken as an indicator that the lever-CS is attractive and thus has acquired incentive value. Interestingly, when a group of animals are tested using this procedure, some animals do indeed begin to approach and engage a lever-CS, that is, they develop what is called a sign-tracking (ST) CR. However, other animals do not, but instead, when the lever-CS is presented, they move toward the location where food will soon be delivered. This is called a goal-tracking (GT) CR. Yet other animals are ambivalent, making both ST and GT CRs (Boakes, 1977; Zener, 1937). Thus, only in some animals (STs) does a cue acquire this property of an incentive stimulus (Flagel et al., 2009).

    The second defining property of an incentive stimulus is that it becomes an object of desire itself, in the sense that animals will work to obtain just the reward-associated cue (CS), even in the absence of the reward. That is, the cue comes to act as what is called a conditioned or secondary reinforcer (the food reward is called the primary reinforcer). Thus, in a conditioned reinforcement test one assesses the extent to which animals will work for a CS, or even learn new actions to get it. The ability of a CS to act as a conditioned reinforcer is another measure of the extent to which the cue functions as an incentive stimulus.

    Third, an incentive stimulus can generate a conditioned motivational state whereby it instigates or invigorates seeking for the associated reward. This “craving” state (which can operate outside conscious awareness) can be quantified by assessing the extent to which a Pavlovian cue reinstates seeking behavior or energizes ongoing instrumental responding (so-called Pavlovian to Instrumental Transfer [PIT] effects).

    If a CS acquires these properties, as in the case of STs, it is considered to not only act as a CS, evoking a CR, but also an incentive stimulus that has emotional and motivational value. Importantly, although these three properties collectively define an incentive stimulus, they are themselves psychologically and neurobiologically dissociable (Cardinal et al., 2002).

    Individual Variation in Incentive Salience Attribution

    As alluded earlier, animals vary considerably in the extent to which a food cue (a lever-CS) comes to act as an incentive stimulus when it is paired with delivery of a food reward (US), based on the three measures discussed earlier. In a series of studies we have quantified Pavlovian conditioned approach behavior in a very large sample of rats (over 6,000). With this procedure, an animal is classed as a sign-tracker (ST) if it makes twice as many ST CRs as GT CRs and as a goal-tracker (GT) if this is reversed. The rest of the animals, which vacillate between making ST and GT CRs, are called Intermediates (INs). In this large sample about 1/3 of the rats were STs, 1/3 GTs, and 1/3 INs, indicating that in only about 1/3 of the population does the CS acquire strong motivational properties—although this is a continuous distribution from a high to low propensity to attribute incentive salience to a food cue. There are not marked sex differences in approach behavior, although on average, female rats are biased toward sign-tracking (Pitchers et al., 2015). The idea that STs preferentially attribute incentive salience to a food cue is further supported by studies showing that a food cue is also a more effective conditioned reinforcer in STs than GTs and is also more effective in instigating seeking behavior (Robinson and Flagel, 2009; Yager and Robinson, 2010; Flagel et al., 2011). In summary, there is now considerable evidence that many species (including humans; Mahler and de Wit, 2010; Styn et al., 2013; Garofalo and di Pellegrino, 2015) vary in the extent to which cues that are fully predictive of reward, and act as effective CSs, also acquire the properties of an incentive stimulus, and thus the ability to arouse feelings, incite to action, provoke, spur and motivate behavior (Robinson et al., 2014; Flagel and Robinson, 2017; Pitchers et al., 2018; and other chapters in this book).

    Of course, if cues that predict rewards act as incentives, this will increase the probability one will be motivated to approach and obtain them, and given they are necessary for survival, as in the case of obtaining food or a mate, this will often be advantageous. However, such cues can in some situations lead to maladaptive behavior. For example, our modern environment is laden with cues signaling the availability of high calorie, high fat foods, and when they generate excessive motivation for them this can lead to overeating, which may be a contributing factor to obesity (e.g., Berridge et al., 2010).

    Dopamine, Drug Cues, and Incentive Motivation

    Another situation where reward cues may contribute to maladaptive behavior is when cues predict the availability of drugs of abuse. Indeed, the importance of drug cues in maintaining drug-taking behavior and in producing relapse in otherwise abstinent drug users has long been recognized. As put by Jane Stewart and colleagues in 1984, “need and drive views of motivation are gradually being replaced by a view that ascribes a primary role to incentive stimuli as the generators of motivational states and elicitors of actions” (p. 251). They went on to state that it is “the drug itself, or the presentation of a stimulus previously paired with the drug, [that] acts to create a motivational state that facilitates drug-seeking behavior” (p. 256) (Stewart et al., 1984; also see Robinson and Berridge, 1993). However, given the large individual variation in the extent to which food cues acquire motivational properties, as described earlier, an obvious question is whether there is similar variation in the extent to which drug cues come to act as incentive stimuli, as this could contribute to vulnerability to addiction (Flagel et al., 2009). That is the topic of the remainder of this chapter. We first address the question: to what extent does the propensity to attribute incentive salience to a food cue predict the extent to which drug cues acquire motivational value?

    The way we have approached this issue is to ask whether STs and GTs differ in the extent to which they attribute a drug cue with each of the defining properties of an incentive stimulus, as described earlier. As put by Milton and Everitt, (2010) the features of an incentive stimulus provide “three routes to relapse,” as each feature can contribute to relapse, individually, or they can combine. The ability of an incentive stimulus to attract attention to it, and to elicit approach behavior, could draw an addict into close proximity to places where drugs are to be found, or to devices used to administer drugs. The ability of a drug cue to act as a conditioned reinforcer can maintain high levels of drug-seeking behavior even in the absence of the drug. And lastly, the ability of drug cues to generate conditioned motivational craving states can instigate drug-seeking and relapse (Epstein et al., 2009; Preston et al., 2009), and such cues may be especially potent under stressful conditions (Preston et al., 2018). Therefore, we will discuss each of these features in turn.

    Conditioned Approach

    The first studies showing that rats would approach a cue associated with a drug, that is, show a ST CR, used alcohol as the US (Tomie, 2001; Krank, 2003; Tomie et al., 2003; Krank et al., 2008; Srey et al., 2015). More recently, Kruse et al. (2017) reported that exposure to alcohol in adolescence also increases the probability that rats later develop a ST CR to a food cue. Although these initial studies noted there was considerable individual variation in the degree to which rats would approach an alcohol cue, they did not explicitly compare STs and GTs. However, more recently, Villaruel and Chaudhri (2016) have reported that an alcohol cue is more attractive and a more effective conditioned reinforcer in STs than GTs.

    In studies with alcohol, the drug is administered orally, but for many other drugs of abuse addicts prefer routes of administration that result in drugs reaching the brain very rapidly, such as intravenous injection or smoking (Samaha and Robinson, 2005; Allain et al., 2015). The first report that rats would come to approach a cue that signaled an intravenous injection of a drug, cocaine, was by Uslaner et al. (2006). More recently, Reilly et al. (2016) reported that rhesus monkeys trained to self-administer cocaine also come to avidly approach a light cue associated with cocaine delivery—touching and biting it. This behavior was seen in the absence of any response-drug contingency, and so presumably represented a Pavlovian ST CR, although it occurred at even higher levels when cocaine delivery was made contingent upon a response, as emphasized by Tomie (1996). These initial studies did not examine STs and GTs, but there are now a number of reports that STs approach a discrete cocaine cue (e.g., a light or a lever) much more avidly than GTs (Flagel et al., 2010; Yager and Robinson, 2013; Pitchers et al., 2017c). Using a different procedure, Meyer et al. (2012b) reported that STs were also more likely to approach a tactile cue associated with cocaine and made more positive ultrasonic vocalizations (USVs) in the presence of this cue. Interestingly, cocaine administration produces more positive USVs in STs and with repeated administration this sensitizes (Tripi et al., 2017). Furthermore, individuals showing the greatest number of USVs when initially exposed to cocaine are most likely to be later identified as STs (Tripi et al., 2017; also see Meyer and Tripi, this book). Finally, Yager et al. (2015) reported that STs are also more likely than GTs to approach a cue that predicts the intravenous delivery of an opioid drug, remifentanil.

    Of course, when intravenous drug is used as a US there is no “goal” (e.g., food cup) to approach, so one cannot see GT CRs. This raises the possibility that GTs do not approach a drug cue because they fail to learn the CS-US association, rather than because the CS does not acquire sufficient motivational value to attract GTs toward it. However, in addition to quantifying sign-tracking, Yager and Robinson (2013) and Yager et al. (2015) also measured the extent to which rats learned a conditioned orienting response to a drug cue, and they found that both STs and GTs learned this CR equally well, as is also the case when food is used as the US (Zener, 1937; Yager and Robinson, 2013). This dissociation between conditioned approach and conditioned orienting, which was recently replicated by Pitchers et al. (2017a), establishes that GTs in fact learned the CS-US(drug) association. This supports the interpretation that the reason GTs did not approach a cocaine or opioid cue was because it lacked sufficient incentive value to act as a “motivational magnet,” drawing them into close proximity to it, not because they failed to learn the CS-US association.

    Conditioned Reinforcement

    There are a number of studies showing that STs will work more avidly than GTs for presentation of a food cue; that is, a food cue is a more effective conditioned reinforcer in STs than GTs (e.g., Robinson and Flagel, 2009; Yager and Robinson, 2010; Lomanowska et al., 2011; Meyer et al., 2012b). The question here is whether this is also the case for drug cues. This question has been approached using a number of different procedures. In some experiments, rats were allowed to self-administer a drug, and thus presentation of both the drug and the cue were contingent on the animal making an instrumental action, such as a nose poke. In other experiments, Pavlovian procedures were used and drug injections were given independent of the animal’s behavior and were paired with presentation of a cue. The test for whether the drug cue acquired conditioned reinforcing properties was conducted by determining whether rats would work for the cue alone, sometimes using traditional extinction-reinstatement (conditioned reinforcement) procedures (e.g., Shaham et al., 2003). A cue associated with cocaine (Saunders and Robinson, 2010; Yager and Robinson, 2013), with nicotine (Yager and Robinson, 2015; Versaggi et al., 2016), with alcohol (Villaruel and Chaudhri, 2016), or with remifentanil (Yager et al., 2015) is a more effective conditioned reinforcer in STs than GTs. Furthermore, during cocaine self-administration omission of the cue attenuates self-administration behavior to a greater extent in STs than GTs (Saunders and Robinson, 2010). Importantly, in all these studies the drug cue consisted of either a discrete light or a lever-CS. In contrast, a tone-CS is reported to reinstate cocaine-seeking behavior to the same extent in STs and GTs (Pitchers et al., 2017c). A tone-CS also does not attract rats to it and functions as a relatively weak incentive stimulus (Meyer et al., 2014; Beckmann and Chow, 2015; Chow et al., 2016; Singer et al., 2016a; also see Holland et al., 2014). Compared to levers and lights a tone CS is also relatively ineffective in engaging brain motive circuits (Singer et al., 2016a; Cogan et al., 2018), indicating that the form of the CS is an important determinant of its ability to acquire incentive motivational properties.

    Conditioned Motivation

    In addition to eliciting approach behavior and acting as a conditioned reinforcer, the third “route to relapse” described by Milton and Everitt (2010) refers to the ability of reward cues to generate Pavlovian conditioned motivational states that then influence instrumental actions (Rescorla and Solomon, 1967; Bindra, 1968; Berridge, 2001). This is Bindra’s (1968) “central motive state,” which can influence ongoing behavior implicitly, outside of conscious awareness (e.g., Childress et al., 2008), or, if it rises to the level of conscious awareness, it is perceived as a state of desire. The former is akin to what Robinson and Berridge (1993) have termed “wanting” (in quotation marks) and the latter to wanting (without quotation marks), or craving. This action of a Pavlovian cue is typically measured by assessing its ability to instigate reward-seeking behavior and/or to invigorate ongoing-seeking behavior; that is, to produce so-called Pavlovian to instrumental (PIT) action effects (Estes, 1943; Lovibond, 1983; Holmes et al., 2010). Typically, in a test for PIT, a cue (usually a tone) is paired with receipt of a reward in some sessions (the Pavlovian part), while in other sessions an animal is trained to make an instrumental action (lever press or nose poke) to receive a reward (the instrumental part). On the test day, usually conducted under extinction conditions, the Pavlovian cue is periodically presented. If the Pavlovian cue increases the rate of instrumental responding, it indicates that it was able to generate a burst of motivation for the associated reward, as reflected by its influence on seeking behavior.

    Although there are many studies of PIT using a food reward, there are very few that have used this procedure to assess the extent to which a drug cue generates a Pavlovian conditioned motivational state, and most of these used alcohol as the US (e.g., Krank et al., 2008b; Lamb et al., 2016b). However, in one study using cocaine, LeBlanc et al. (2012) reported that presentation of a cocaine cue did increase the rate of ongoing self-administration behavior, both during the “seeking” and “taking” phases of the self-administration schedule. Such PIT effects have been associated with a surge in DA in the core of the nucleus accumbens (Ito et al., 2000; Wassum et al., 2013; Aitken et al., 2016). Nevertheless, as pointed out by Lamb et al. (2016), evidence for PIT effects using Pavlovian drug cues is scarce, and there are a number of procedural difficulties in conducting such studies.

    We are not aware of any studies using a traditional PIT procedure to ask whether STs and GTs differ in the ability of a drug cue to energize an ongoing instrumental action, perhaps because the design of such a study is fraught with problems. In PIT studies typically an auditory stimulus is used as the Pavlovian cue, and it is presented while animals are making an instrumental response. However, as reviewed earlier, in rats, an auditory stimulus is not attributed with incentive salience to the same degree as a light or lever. Furthermore, if a localizable stimulus were used as the Pavlovian cue it could elicit approach toward it, as has been described by Krank (Krank, 2003; Krank et al., 2008), and presumably this would be most pronounced in STs. Indeed, in tests of conditioned reinforcement, in which STs make an action for presentation of a lever-CS, we have frequently seen that as soon as the lever is presented they disengage from the instrumental manipulandum (nose port) and run to the lever-CS and engage with it, even when it is presented for only 2 sec (Robinson and Flagel, 2009; Fraser et al., 2016). Obviously, this competes with performance of the instrumental response and would thus interfere with the ability to see a PIT effect.

    Nevertheless, there are studies suggesting that a Pavlovian cue does generate greater conditioned motivation in STs than GTs. To circumvent the problem with traditional PIT procedures described earlier, Saunders et al. (2013) modified a protocol developed by Cooper et al. (2007) to examine the ability of a cocaine cue (a light) to instigate an instrumental action (rather than energize an ongoing action). With this procedure, after rats acquired stable cocaine self-administration behavior, the front two-thirds of the chamber (where the nose port was located) was electrified, such that rats had to walk across the electrified floor to take drug. The current was initially very weak, but it was increased each day, until a point where animals stopped taking drug—they became abstinent because of the negative consequences of continuing to take drug. On the test day, the light cue was periodically flashed to see if it created a motivational state sufficient to compel the rats to cross the still electrified floor to seek drug, although no drug was available during this test. It did so, but more effectively in STs than GTs. In addition, the degree to which the rats approached the food cue when they were screened for sign-tracking and goal-tracking predicted the ability of the cocaine cue to reinstate self-administration behavior (r2=0.253). Saunders et al. (2013) argued that this effect was due to the cocaine cue generating a conditioned motivational state, and not to Pavlovian attraction (see the paper for discussion), and also showed that it was blocked by injection of a DA antagonist into the core of the nucleus accumbens. One shortcoming of this study is that the cocaine cue acquired its motivational properties in the instrumental (self-administration) setting, and it would be good to know if a similar effect were seen with a Pavlovian-trained cue.

    Another line of evidence that suggests drug cues produce greater conditioned motivation for drug in STs than GTs comes from studies on the effects of exposure to the drug itself. It has long been known that the drug itself (a “taste” of drug) can evoke craving and relapse in addicts (e.g., Jaffe et al., 1989; de Wit and Chutuape, 1993), and in animals a drug “prime” can reinstate drug-seeking behavior following extinction of self-administration behavior (de Wit and Stewart, 1981; Venniro et al., 2016 for review). One interpretation of this effect is that the drug produces a variety of interoceptive effects, and with experience some of these become associated with the unconditioned motivational effects of the drug, such that even a small dose of drug can produce a conditioned motivational state that promotes further drug-seeking behavior.

    The first experiment to ask whether the interoceptive effects of cocaine have different motivational value in STs and GTs was by Saunders and Robinson (2011), who assessed motivation for drug using a progressive ratio (PR) schedule and by the ability of a drug prime to reinstate drug-seeking behavior. To better isolate the motivational effects of the drug itself, no environmental cue (CS; e.g., light or tone) was explicitly paired with drug injections, either during self-administration training, the PR test or the reinstatement test. It was found that STs were more motivated to self-administer cocaine than GTs, as they had higher breakpoints on the PR schedule, and the drug prime reinstated more drug-seeking in STs than GTs during the reinstatement test. Consistent with this, STs also choose cocaine over a food reward more frequently than GTs (Tunstall and Kearns, 2015). Kawa et al. (2016) recently confirmed that, at least after relatively limited drug experience, STs are more motivated to self-administer cocaine than GTs. Kawa et al. (2016) used a behavioral economic “threshold” procedure in which the “price” (responses/mg) required to obtain cocaine was progressively increased. It was found that STs were willing to pay a higher price for cocaine (in effort) than GTs—they had a higher Pmax—and the cocaine demand curve was less elastic in STs (they had a lower alpha than GTs). Interestingly, STs and GTs did not differ on Qo, which is a measure of the preferred level of drug consumption when cost is negligible, and may reflect the hedonic effects of the drug. If that is true, it suggests that interoceptive cocaine cues may have greater incentive motivational value in STs than GTs, at least when animals have had only limited drug experience (see sections below for more discussion of this issue), but cocaine produces similar hedonic effects in STs and GTs, consistent with the notion that “wanting” and “liking” are dissociable processes (Robinson and Berridge, 1993; Berridge et al., 2009; Olney et al., 2018).

    In summary, as with food cues, there is now considerable evidence that cues associated with drugs of abuse are attributed with greater motivational value in STs than GTs, which could predispose STs to addiction (see sections below for more discussion of this issue).

    Acetylcholine and Variation in the Top-Down Executive Control over Behavior

    Earlier we have emphasized that the greater drug cue reactivity of STs may make them vulnerable to addiction and relapse, but there is a general consensus that this is only one of a number of “vulnerability factors,” as stressed by so-called dual-systems formulations of behavioral control. One system is often referred to as an automatic, impulsive system in which behavior is strongly controlled by incentive stimuli, in the moment; what Sarter and Phillips (2018) refer to as a “bottom-up, cue-driven cognitive-motivational style.” The other system is described as a more deliberative, executive (cognitive) control system that allows for inhibitory control over behavior (e.g., Jentsch and Taylor, 1999; Mcclure and Bickel, 2014; Bickel et al., 2016); what Sarter and Phillips (2018) refer to as a “top-down goal-driven attentional control” system. Although everyone possesses both of these behavioral control systems, they may compete with one another, and one or the other may dominate in any given individual. Thus, addictive behavior is thought to not only be promoted by hyperreactivity to drugs and drug cues but also relatively poor executive (attentional) control over behavior, especially in the presence of reward cues. It is important to emphasize, therefore, that not only are STs more prone than GTs to attribute incentive salience to drug cues, but they also have relatively poor top-down executive control over their behavior (Flagel et al., 2009; Meyer et al., 2012a; Haight et al., 2015, 2017; Sarter and Phillips, 2018), which may account for the fact that they are impulsive (Lovic et al., 2011).

    Martin Sarter and his colleagues have conducted an extensive series of studies on the neural systems involved in executive/attentional control over behavior, using a Sustained Attention Task (SAT) designed to tax such processes, in both rats and humans (Sarter and Paolone, 2011). Paolone et al. (2013) used the SAT to assess executive/attentional control in STs and GTs and found that STs performed poorly on this task, relative to GTs. STs could perform the task, and at times performed as well as GTs, but their performance was highly variable, fluctuating between periods of good performance and periods of very poor performance. This is thought to reflect “relatively poor cognitive or ‘top-down’ control of attention in STs, including a relatively lower capacity for maintaining task rules and behavioral goals in working memory (or ‘on-line’),” as well as, “poorer levels of performance monitoring, specifically error monitoring” (Paolone et al., 2013, p. 8332). In addition, the performance of STs on the SAT is slower to recover after disruption by a distractor (Sarter and Phillips, 2018).

    The idea that STs have relatively poor top-down control over their behavior is also supported by studies using stimuli that indicate what rules are operative at any given time. For example, stimuli that signal reward availability can “set the occasion” for appropriate responding and this is thought to require cognitive control to override the tendency to unthinkably respond to a CS. STs are relatively insensitive to such stimuli, compared to GTs, and are slow to modify their behavior in an appropriate fashion as circumstances change. Thus, STs may be biased to respond impulsively to cues, even when it is no longer appropriate, because they have poor cognitive control over attention, which is required to “suppress prepotent responses,” “to maintain task rules,” “to monitor performance and weigh outcomes,” and to “filter distractors” (see Sarter and Paolone, 2011). Ahrens et al. (2016b) demonstrated the inflexibility of STs by alternating periods of reward and non-reward. In the presence of a signal of non-reward GTs immediately modified their behavior, by ceasing conditioned responding (goal-tracking). However, it took several days before STs discriminated between periods of reward versus non-reward, as they persisted in approaching a food cue (sign-tracking) even during periods of non-reward, and it was difficult to extinguish this response to the cue, relative to GTs.

    Changes in context also often provide information about whether a reward is available or not, and animals thus modify their behavior according to the context they find themselves. For example, if rats are trained to self-administer a drug in one context (context A) but then undergo extinction training in a different context (context B), during which time their previously reinforced action no longer produces drug, they stop self-administering in context B. However, if, after extinction, they are placed back into context A they immediately resume drug-seeking behavior, in part because that context still signals drug availability (Crombag et al., 2008). The processing of such higher-order signals of reward availability or non-availability is thought to require the executive (cognitive) control system that dominates in GTs, as described earlier. It is interesting, therefore, that when placed back into a context that was previously associated with cocaine self-administration GTs reinstate cocaine-seeking behavior more avidly than STs (Saunders et al., 2014). That is, they more readily modify their behavior depending on the context they find themselves in (also see Morrow et al., 2011).

    Stimuli that signal reward availability (occasion-setters or discriminative stimuli) are thought to share many properties of contextual stimuli (Weiss, 2005; Trask et al., 2017). Consistent with this, Pitchers et al. (2017b) reported that a discriminative stimulus that signaled cocaine availability evoked greater cocaine-seeking behavior in GTs than STs. It appears, therefore, that cues that control behavior by more “top-down” hierarchical processes (Rescorla, 1988) are more influential in GTs than STs. It is still not entirely clear how to interpret these findings (see additional discussion in sections below), but it is consistent with the idea that different learning/cognitive processes dominate control of behavior in STs and GTs. That is, STs are more susceptible to control by bottom-up, cue-driven processes whereas GTs are more likely to employ top-down executive (cognitive) control processes that allow them to more readily adapt their behavior as circumstances change (Flagel et al., 2009; Clark et al., 2012; Meyer et al., 2012a; Haight et al., 2015, 2017; Sarter and Phillips, 2018).

    Research on which ascending neuromodulatory neurotransmitter systems dominate in STs and GTs supports this kind of distinction. Studies by Sarter and colleagues (e.g., Sarter and Paolone, 2011; also see Kuhn et al., this book) have established that the high levels of attentional control necessary for optimal performance on the SAT require increased acetylcholine (ACh) neurotransmission in the prefrontal cortex while performing the task. However, during performance on the SAT prefrontal extracellular ACh levels, assessed with microdialysis, rise much less in STs than GTs. This may account for their relatively poor performance because “systemic administration of the partial nAChR agonist ABT-089 improved SAT performance in STs and abolished the difference between SAT-associated ACh levels in STs and GTs” (Paolone et al., 2013). This difference between STs and GTs may be because in STs the choline transporter, which is required to elevate ACh under demanding conditions, is remarkably unresponsive (Koshy Cherian et al., 2017). Interestingly, inhibition of choline transport, which limits stimulated ACh release in the cortex, also shifts behavior away from goal-tracking and toward sign-tracking (Koshy Cherian et al., 2017). In addition, the ability of a discriminative stimulus that signals cocaine availability to preferentially reinstate drug-seeking behavior in GTs (relative to STs) is abolished by an immunotoxic lesion of the basal forebrain that decreases cortical ACh levels (Pitchers et al., 2017b). Finally, there is a double dissociation in the effects of presentation of a cue previously paired with an IV injection of cocaine on DA and ACh in the prefrontal cortex. A cocaine cue (CS) increases extracellular DA (but not ACh) in the prefrontal cortex of STs, and the magnitude of this effect predicts how avidly STs approach the cue. This cue did not increase DA in GTs, nor did they approach the cue (although they oriented to it). On the other hand, the cocaine cue increased prefrontal ACh in GTs, but not STs. This double dissociation is consistent with the idea that the top-down executive control system, which requires ACh neurotransmission in the prefrontal cortex, may dominate in GTs, whereas in STs a dopaminergic incentive system dominates (Pitchers et al., 2017a; Sarter and Phillips, 2018).

    Susceptibility to Addiction

    As reviewed earlier, there is now considerable evidence indicating that STs and GTs represent the extremes of two complex endophenotypes that differ on a number of behavioral/psychological dimensions, such that different “cognitive-motivational styles” (Sarter and Phillips, 2018) dominate control of behavior in STs and GTs (Flagel et al., 2009; Clark et al., 2012; Robinson et al., 2014; Beckmann and Chow, 2015). Although these endophenotypes are labeled by the terms ST and GT, this should not be confused with a ST or GT CR, which narrowly refers to the tendency to approach the CS or the location of reward delivery in a Pavlovian conditioned approach task, respectively. As described earlier, the ST and GT endophenotypes involve much more complex and multifaceted constellations of interacting traits.

    We originally hypothesized that STs are more susceptible to addiction than GTs, based primarily on their propensity to attribute incentive salience to discrete drug cues (Flagel et al., 2009; Saunders and Robinson, 2013). We still think the ST endophenotype represents a vulnerability factor for addiction, although, as described next, more recent research has forced a reevaluation as to how this is conceptualized (Robinson et al., 2014; Kawa et al., 2016; Pitchers et al., 2018). Dual-systems models postulate that addiction and relapse result from an interaction between: (1) hyperreactive “bottom-up” neural systems that attribute incentive motivational value to reward cues, resulting in a hypersensitivity to drugs and drug cues, and, (2) hypoactive “top-down” neural systems that confer executive (cognitive) control over behavior, resulting in poor inhibitory control, especially in the presence of drugs and drug cues (e.g., Jentsch and Taylor, 1999; Mcclure and Bickel, 2014; Bickel et al., 2016; Sarter and Phillips, 2018). By this formulation, STs suffer a “double-whammy,” in that they are not only especially prone to attribute undue incentive salience to drugs and drug cues, but they also have relatively poor executive or attentional control over behavior, which can, of course, contribute to why they are biased toward cues in the first place (Robinson et al., 2014; Flagel and Robinson, 2017; Sarter and Phillips, 2018; Pitchers et al., 2018). We hypothesize, therefore, that individuals with a ST endophenotype may be more vulnerable to undergo a transition from recreational/casual patterns of drug use to addiction for the following reasons (also see Kuhn et al., this book).

    1. Upon initial use the interoceptive effects of cocaine are more motivating in STs than GTs (Saunders and Robinson, 2011).
    2. STs are especially susceptible to the motivating effects of discrete drug cues (Saunders and Robinson, 2010; Saunders et al., 2013).
    3. STs are more impulsive than GTs (Tomie et al., 2008; Lovic et al., 2011).
    4. The motivational effects of Pavlovian reward cues are more difficult to extinguish in STs than GTs (Beckmann and Chow, 2015; Ahrens et al., 2016b).
    5. Relative to GTs, STs are more likely to choose drug (cocaine) over a non-drug reward (Tunstall and Kearns, 2015).
    6. Reward (including drug) cues more effectively engage brain systems that confer incentive motivational value to such cues in STs than GTs (Flagel et al., 2011; Yager et al., 2015; Ahrens et al., 2016a; Singer et al., 2016b; Flagel and Robinson, 2017, for review).
    7. STs have relatively poor executive (attentional) control over behavior, which is due, at least in part, to unresponsive cortical choline transporters, which limits their ability to increase acetylcholine neurotransmission under cognitively demanding conditions (Paolone et al., 2013; Sarter and Phillips, 2018, for review).

    As put by Kawa et al. (2016), “All of these characteristics would increase the probability that individuals with a ST phenotype, after initial casual drug use, continue to use drugs, which would eventually expose them to incentive-sensitization and addiction (Robinson and Berridge, 1993).”

    Context

    The interpretation of individual variation in the motivational properties of context cues and discriminative stimuli requires special comment. As noted earlier, studies using reinstatement procedures have found that context cues and discriminative stimuli reinstate cocaine-seeking behavior more effectively in GTs than STs (Saunders et al., 2014; Pitchers et al., 2017b). One interpretation of these findings was provided by Robinson et al. (2014), who said: “different individuals may be sensitive to different ‘triggers’ capable of motivating behavior and producing relapse. That is, STs and GTs may process motivationally salient information in quite different ways, and thus vary in their sensitivity to different classes of drug-associated stimuli. It may be, therefore, that STs are not more susceptible to addiction than GTs, but that for different individuals there are different pathways to addiction.”

    However, the recent studies by Martin Sarter and his colleagues on attentional control in STs and GTs (Sarter and Phillips, 2018, for review) suggest a very different interpretation. The ability to appropriately modify behavior based on the information provided by higher-order cues that signal the availability (or non-availability) of reward, such as context cues and discriminative stimuli, is much more cognitively demanding than the processing of CSs. Thus, the greater reinstatement produced by such cues in GTs may reflect their superior ability to appropriately incorporate such information in guiding their behavior, and conversely, the ability of STs to do this is compromised because of their limited capacity for executive (cognitive) control. Indeed, this may also be why GTs are less impulsive than STs. By this interpretation, the effects of context cues in GTs could be interpreted as reflecting better “top-down” executive control, which could be protective in terms of susceptibility to addiction. Conversely, the fact that STs have difficulty incorporating such information to appropriately modulate their behavior represents another risk factor that increases the probability they transition from casual drug use to problematic use and eventually addiction. This issue will clearly require further study.

    Individual Variation in Incentive-Sensitization

    Earlier we itemize the features of the ST endophenotype that may render them more likely than GTs to transition from casual drug use to addiction. However, Robinson and Berridge (1993, 2008; Berridge and Robinson, 2016) have argued that the repeated intermittent exposure to drugs of abuse can change brain reward systems in ways that render animals hypersensitive to drugs and drug cues, and that this process of incentive-sensitization is both central in the transition from casual patterns of drug use to those that characterize addiction, as well as maintaining pathological motivation for drugs in addicts, contributing to high rates of relapse, even after long periods of abstinence. An important question, therefore, is whether STs and GTs differ in their susceptibility to incentive sensitization. The GT endophenotype may be protective in that it decreases the probability that initial use will lead to more sustained use that could then result in escalation of intake and the adoption of routes of drug administration with greater addiction liability, such as intravenous administration or smoking (e.g., Allain et al., 2015). But what if, for any reason, individuals with a GT endophenotype do progress to problematic patterns of drug use? Will they be protected from incentive-sensitization? There is one study that suggests perhaps not (Kawa et al., 2016).

    Kawa et al. (2016) first assessed motivation for cocaine in STs and GTs using behavioral economic measures of cocaine demand and found that after limited drug experience STs showed greater motivation for cocaine than GTs, consistent with earlier studies using different measures (Saunders and Robinson, 2010, 2011). However, after this, all rats were allowed to self-administer cocaine over 36 days using an Intermittent Access (IntA) schedule, which has been shown to promote the development of addiction-like behavior (Zimmer et al., 2012; Allain et al., 2015, 2017; Singer et al., 2018), and during this time cocaine demand was periodically reassessed. As predicted, there was a progressive development of addiction-like behavior as a function of IntA experience, including escalation of intake, increasing motivation for drug, increasing willingness to endure an adverse consequence to procure drug and very robust cue-induced reinstatement of drug-seeking behavior. Importantly, both STs and GTs underwent this process of incentive-sensitization such that after IntA self-administration experience they no longer differed on any measure of addiction-like behavior. Furthermore, in such a situation sustained exposure to drugs may also impair frontal cortical function, diminishing cognitive control, even in GTs (Briand et al., 2008). Thus, although having a GT endophenotype may be protective in that it could decrease the probability of continued drug use following initial experimentation with drugs, should such an individual in fact continue to use drugs they may be just as susceptible to incentive-sensitization, and addiction, as those with a ST endophenotype. In addition, female rats appear to undergo incentive-sensitization more readily than males (Kawa and Robinson, 2017), consistent with reports that female humans escalate to problematic drug use more quickly than males (Becker and Koob, 2016, for review).

    Conclusion

    The behavior of animals with a ST versus GT endophenotype is dominated by very different “cognitive-motivational styles” (Sarter and Phillips, 2018) (see Fig. 4.1). STs are very sensitive to the influence of reward cues processed by bottom-up, cue-driven, dopamine-dependent incentive motivational systems, and they have relative poor executive (attentional) control over their behavior, and thus they have difficulty resisting such cues. GTs, on the other hand, are less susceptible to the motivational properties of reward cues and also have greater executive (attentional) control over behavior, mediated in part by prefrontal cortical cholinergic signaling, and therefore are better able to resist such cues. It is hypothesized, therefore, that a ST endophenotype will increase the likelihood that an individual will progress from casual/experimental patterns of drug use to patterns characteristic of addiction, relative individuals with a GT endophenotype (see other chapters in this book). However, although much more research is required, the available evidence suggests that should, for any reason, drug use escalate, a GT endophenotype may not protect from incentive-sensitization (Kawa et al., 2016), or drug-induced alterations in frontal cortical function (e.g., Jentsch and Taylor, 1999). Thus, under conditions of continued and escalating drug use both STs and GTs may undergo a transition to addiction.

    Acknowledgments

    We thank all the former members of the Robinson lab who contributed to many of the studies discussed herein, as well as members of the Sarter lab for their studies on ACh and cognitive control. The research was supported by grants from the National Institute on Drug Abuse to TER (PO1 DA031656 and T32 DA007281).

    Figure 4.1. A highly simplified graphic illustration of two endophenotypes, sign-trackers and goal-trackers, in which different neuromodulatory systems and psychological processes dominate in the control of behavior. The width of the arrows represent the relative strength of functional, not anatomical, relationships (see text).: Left. “Sign-Trackers” (STs) are animals in which bottom-up, dopamine (DA)-mediated incentive salience motivational processes dominate control of behavior (red arrows), as indicated by a propensity to attribute incentive salience to discrete reward cues, and by strong functional activity in dopaminergic projections from the ventral tegmental area (VTA) to the prefrontal cortex (PFC) and nucleus accumbens (NAc; ventral striatum), and between the NAc and its main target, the ventral pallidum (VP). In these animals, the activity of cholinergic inputs to the PFC under conditions of attentional demand is relatively muted. Under such conditions, increased cholinergic activity in the PFC is required for strong top-down cognitive (attentional) control over behavior, which is presumably one reason that STs have poor cognitive control over their behavior (blue arrows). The PFC projects to many brain regions that participate in cognitive control (as indicated by the dashed lines), including projections back to the VTA, NAc and basal forebrain, and many others (see Kuhn et al., this volume; Haight and Flagel, 2014; Haight et al., 2017; Sarter and Phillips, 2018). How these different brain regions interact to reciprocally modulate one another in the control of behavior is not well understood.
    Figure 4.1. A highly simplified graphic illustration of two endophenotypes, sign-trackers and goal-trackers, in which different neuromodulatory systems and psychological processes dominate in the control of behavior. The width of the arrows represent the relative strength of functional, not anatomical, relationships (see text).

    Left. “Sign-Trackers” (STs) are animals in which bottom-up, dopamine (DA)-mediated incentive salience motivational processes dominate control of behavior (red arrows), as indicated by a propensity to attribute incentive salience to discrete reward cues, and by strong functional activity in dopaminergic projections from the ventral tegmental area (VTA) to the prefrontal cortex (PFC) and nucleus accumbens (NAc; ventral striatum), and between the NAc and its main target, the ventral pallidum (VP). In these animals, the activity of cholinergic inputs to the PFC under conditions of attentional demand is relatively muted. Under such conditions, increased cholinergic activity in the PFC is required for strong top-down cognitive (attentional) control over behavior, which is presumably one reason that STs have poor cognitive control over their behavior (blue arrows). The PFC projects to many brain regions that participate in cognitive control (as indicated by the dashed lines), including projections back to the VTA, NAc and basal forebrain, and many others (see Kuhn et al., this volume; Haight and Flagel, 2014; Haight et al., 2017; Sarter and Phillips, 2018). How these different brain regions interact to reciprocally modulate one another in the control of behavior is not well understood.

    Right. “Goal-Trackers” (GTs) are animals in which functional activity in dopaminergic projections from the VTA to PFC and NAc, and between the NAc and VP, are weaker than in STs, which is presumably why they are less prone to attribute incentive salience to discrete reward cues than STs. In contrast, GTs show greater ACh activity in the PFC in response to reward cues and under conditions that tax attentional processes, which presumably contributes to their superior cognitive (attentional) control over behavior, and diminished impulsivity. See the text for references to studies that support these assertions.

    Finally, the term “Basal Forebrain” is used here narrowly, to refer to the brain regions where cholinergic neurons that project to the cortex are located, which includes the nucleus basalis of Meynert, substantia innominata, and the horizontal limb of the diagonal band.

    References

    • Ahrens, A. M., Meyer, P. J., Ferguson, L. M., Robinson, T. E., & Aldridge, J. W. (2016a). Neural activity in the ventral pallidum encodes variation in the incentive value of a reward cue. Journal of Neuroscience 36, 7957–7970.
    • Ahrens, A. M., Singer, B. F., Fitzpatrick, C. J., Morrow, J. D., & Robinson, T. E. (2016b). Rats that sign-track are resistant to Pavlovian but not instrumental extinction. Behavioural Brain Research 296, 418–430.
    • Aitken, T. J., Greenfield, V. Y., & Wassum, K. M. (2016). Nucleus accumbens core dopamine signaling tracks the need-based motivational value of food-paired cues. Journal of Neurochemistry 136, 1026–1036.
    • Allain F., Minogianis, E-A, Roberts, D. C. S., & Samaha, A. N. (2015). How fast and how often: The pharmacokinetics of drug use are decisive in addiction. Neuroscience & Biobehavioral Review 56, 166–179.
    • Allain, F., Roberts, D. C. S., Lévesque, D., & Samaha, A. N. (2017). Intermittent intake of rapid cocaine injections promotes robust psychomotor sensitization, increased incentive motivation for the drug and mGlu2/3 receptor dysregulation. Neuropharmacology 117, 227–237.
    • Becker, J. B., & Koob, G. F. (2016). Sex differences in animal models: Focus on addiction. Pharmacological Reviews 68, 242–263.
    • Beckmann, J. S., & Chow, J. J. (2015). Isolating the incentive salience of reward-associated stimuli: Value, choice, and persistence. Learning & Memory 22, 116–127.
    • Berridge, K. C. (2001). Reward learning: Reinforcement, incentives, and expectations. In D. L. Medlin (Ed.), The psychology of learning and motivation (pp. 223–278). New York, NY: Academic Press.
    • Berridge, K. C., Ho, C-Y., Richard, J. M., & DiFeliceantonio, A. G. (2010). The tempted brain eats: Pleasure and desire circuits in obesity and eating disorders. Brain Research 1350, 43–64.
    • Berridge, K. C., & Robinson, T. E. (2016). Liking, wanting, and the incentive-sensitization theory of addiction. American Psychologidt 71, 670–679.
    • Berridge, K. C., Robinson, T. E., & Aldridge, J. W. (2009). Dissecting components of reward: “liking,” “wanting,” and learning. Current Opinion in Pharmacology 9, 65–73.
    • Bickel, W. K., Snider, S. E., Quisenberry, A. J., Stein, J. S., & Hanlon, C. A. (2016). Competing neurobehavioral decision systems theory of cocaine addiction: From mechanisms to therapeutic opportunities. Progress in Brain Research 223, 269–293.
    • Bindra, D. (1968). Neuropsychological interpretation of the effects of drive and incentive-motivation on general activity and instrumental behavior. Psychological Review 75, 1–22.
    • Bindra, D. (1978). How adaptive behavior is produced: A perceptual-motivational alternative to response reinforcements. Behavioral and Brain Sciences 1, 41.
    • Boakes, R. (1977). Performance on learning to associate a stimulus with positive reinforcement. In H. Davis & H.M.B. Hurwitz (Eds.), Operant-Pavlovian Interactions (pp. 67–97). New York, NY: Erlbaum Associates.
    • Briand, L. A., Flagel, S. B., Garcia-Fuster, M. J., Watson, S. J., Akil, H., Sarter, M., & Robinson, T. E. (2008). Persistent alterations in cognitive function and prefrontal dopamine D2 receptors following extended, but not limited, access to self-administered cocaine. Neuropsychopharmacology 33, 2969–2980.
    • Cardinal, R. N., Parkinson, J. A., Hall, J., & Everitt, B. J. (2002). Emotion and motivation: The role of the amygdala, ventral striatum, and prefrontal cortex. Neuroscience & Biobehavioral Reviews 26, 321–352.
    • Childress, A. R., Ehrman, R. N., Wang, Z., Li, Y., Sciortino, N., Hakun, J., Jens, W., Suh, J., Listerud, J., Marquez, K., Franklin, T., Langleben, D., Detre, J., & O’Brien, C. P. (2008). Prelude to passion: Limbic activation by “unseen” drug and sexual cues. PLoS One 3, e1506.
    • Chow, J. J., Nickell, J. R., Darna, M., & Beckmann, J. S. (2016). Toward isolating the role of dopamine in the acquisition of incentive salience attribution. Neuropharmacology 109, 320–331.
    • Clark, J. J., Hollon, N. G., & Phillips, P. E. M. (2012). Pavlovian valuation systems in learning and decision making. Current Opinion in Neurobiology 22, 1054–1061.
    • Cogan, E. S., Shapses, M. A., Robinson, T. E., & Tronson, N. C. (May 3, 2018). Disrupting reconsolidation in rats: Memory erasure or blunting of emotional/motivational value? Neuropsychopharmacology. doi: 10.1038/s41386-018-0082-0. [Epub ahead of print].
    • Cooper, A., Barnea-Ygael, N., Levy, D., Shaham, Y., & Zangen, A. (2007). A conflict rat model of cue-induced relapse to cocaine seeking. Psychopharmacology (Berl) 194, 117–125.
    • Crombag, H. S., Bossert, J. M., Koya, E., & Shaham, Y. (2008). Context-induced relapse to drug seeking: A review. Philosophical Transactions of the Royal Society B Biological Sciences 363, 3233–3243.
    • de Wit, H., & Chutuape, M. a. (1993). Increased ethanol choice in social drinkers following ethanol preload. Behavioural Pharmacology 4, 29–36.
    • de Wit, H., & Stewart, J. (1981). Reinstatement of cocaine-reinforced responding in the rat. Psychopharmacology (Berl) 75, 134–143.
    • Epstein, D. H., Willner-Reid, J., Vahabzadeh, M., Mezghanni, M., Lin, J. L., & Preston, K. L. (2009). Real-time electronic diary reports of cue exposure and mood in the hours before cocaine and heroin craving and use. Archive of General Psychiatry 66, 88.
    • Estes, W. K. (1943). Discriminative conditioning. I. A discriminative property of conditioned anticipation. Journal of Experimental Psychology 32, 150–155.
    • Everitt, B. J., Dickinson, A., & Robbins, T. W. (2001). The neuropsychological basis of addictive behaviour. Brain Research Reviews 36, 129–138.
    • Flagel, S. B., Akil, H., & Robinson, T. E. (2009). Individual differences in the attribution of incentive salience to reward-related cues: Implications for addiction. Neuropharmacology 1, 139–148.
    • Flagel, S. B., Cameron, C. M., Pickup, K. N., Watson, S. J., Akil, H., & Robinson, T. E. (2011). A food predictive cue must be attributed with incentive salience for it to induce c-fos mRNA expression in cortico-striatal-thalamic brain regions. Neuroscience 196, 80–96.
    • Flagel, S. B., & Robinson, T. E. (2017). Neurobiological basis of individual variation in stimulus-reward learning. Current Opinion in Behavioral Sciences 13, 178–185.
    • Flagel, S. B., Robinson, T. E., Clark, J. J., Clinton, S. M., Watson, S. J., Seeman, P., Phillips, P. E. M., & Akil, H. (2010). An animal model of genetic vulnerability to behavioral disinhibition and responsiveness to reward-related cues: Implications for addiction. Neuropsychopharmacology 35, 388–400.
    • Fraser, K. M., Haight, J. L., Gardner, E. L., & Flagel, S. B. (2016). Examining the role of dopamine D2 and D3 receptors in Pavlovian conditioned approach behaviors. Behavioral Brain Research 305, 87–99.
    • Garofalo, S., & di Pellegrino, G. (2015). Individual differences in the influence of task-irrelevant Pavlovian cues on human behavior. Frontiers in Behavioral Neuroscience 9, 1–11.
    • Haight, J. L., & Flagel, S. B. (2014). A potential role for the paraventricular nucleus of the thalamus in mediating individual variation in Pavlovian conditioned responses. Frontiers in Behavioral Neuroscience 8, 79.
    • Haight, J. L., Fraser, K. M., Akil, H., & Flagel, S. B. (2015). Lesions of the paraventricular nucleus of the thalamus differentially affect sign- and goal-tracking conditioned responses. European Journal of Neuroscience 42, 2478–2488.
    • Haight, J. L., Fuller, Z. L., Fraser, K. M., & Flagel, S. B. (2017). A food-predictive cue attributed with incentive salience engages subcortical afferents and efferents of the paraventricular nucleus of the thalamus. Neuroscience 340, 135–152.
    • Hickey, C., & Peelen, M. V. (2015). Neural mechanisms of incentive salience in naturalistic human vision. Neuron 85, 512–518.
    • Holland, P. C., Asem, J. S. A., Galvin, C. P., Keeney, C. H., Hsu, M., Miller, A., & Zhou, V. (2014). Blocking in autoshaped lever-pressing procedures with rats. Learning & Behavior 42, 1–21.
    • Holmes, N. M., Marchand, A. R., & Coutureau, E. (2010). Pavlovian to instrumental transfer: A neurobehavioural perspective. Neuroscience & Biobehavioral Reviews 34, 1277–1295.
    • Ito, R., Dalley, J. W., Howes, S. R., Robbins, T. W., & Everitt, B. J. (2000). Dissociation in conditioned dopamine release in the nucleus accumbens core and shell in response to cocaine cues and during cocaine-seeking behavior in rats. Journal of Neuroscience 20, 7489–7495.
    • Jaffe, J. H., Cascella, N. G., Kumor, K. M., & Sherer, M. A. (1989). Cocaine-induced cocaine craving. Psychopharmacology (Berl) 97, 59–64.
    • Jentsch, J. D., & Taylor, J. R. (1999). Impulsivity resulting from frontostriatal dysfunction in drug abuse: Implications for the control of behavior by reward-related stimuli. Psychopharmacology (Berl) 146, 373–390.
    • Johansson, P., Hall, L., Sikström, S., Tärning, B., & Lind, A. (2006). How something can be said about telling more than we can know: On choice blindness and introspection. Conscious Cognition 15, 673–92–9.
    • Kahneman, D. (2011). Thinking, fast and slow. New York, NY: Farrar, Straus and Giroux.
    • Kawa, A. B., Bentzley, B. S., & Robinson, T. E. (2016). Less is more: Prolonged intermittent access cocaine self-administration produces incentive-sensitization and addiction-like behavior. Psychopharmacology (Berl) 233, 3587–3602.
    • Kawa, A. B., & Robinson, T. E. (2017). Using the intermittent access self-administration procedure to assess sex difference in the motivation for cocaine. Abstract presented at 2017 SfN annual meeting.
    • Koshy Cherian, A., Kucinski, A., Pitchers, K., Yegla, B., Parikh, V., Kim, Y., Valuskova, P., Gurnani, S., Lindsley, C. W., Blakely, R. D., & Sarter, M. (2017). Unresponsive choline transporter as a trait neuromarker and a causal mediator of bottom-up attentional biases. Journal of Neuroscience 37, 2947–2959.
    • Krank, M. D. (2003). Pavlovian conditioning with ethanol: Sign-tracking (autoshaping), conditioned incentive, and ethanol self-administration. Alcoholism: Clinical and Experimental Research 27, 1592–1598.
    • Krank, M. D., O’Neill, S., Squarey, K., & Jacob, J. (2008). Goal- and signal-directed incentive: Conditioned approach, seeking, and consumption established with unsweetened alcohol in rats. Psychopharmacology (Berl) 196, 397–405.
    • Kruse, L. C., Schindler, A. G., Williams, R. G., Weber, S. J., & Clark, J. J. (2017). Maladaptive decision making in adults with a history of adolescent alcohol use, in a preclinical model, is attributable to the compromised assignment of incentive value during stimulus-reward learning. Frontiers in Behavioral Neuroscience 11, 134.
    • Lajoie, J., & Bindra, D. (1976) An interpretation of autoshaping and related phenomena in terms of stimulus-incentive contingencies alone. Canadian Journal of Psychology, 30, 157–173.
    • Lamb, R. J., Schindler, C. W., & Pinkston, J. W. (2016). Conditioned stimuli’s role in relapse: Preclinical research on Pavlovian-Instrumental-Transfer. Psychopharmacology (Berl) 233, 1933–1944.
    • LeBlanc, K. H., Ostlund, S. B., & Maidment, N. T. (2012). Pavlovian-to-instrumental transfer in cocaine seeking rats. Behavioral Neuroscience 126, 681–689.
    • Lomanowska, A. M., Lovic, V., Rankine, M. J., Mooney, S. J., Robinson, T. E., & Kraemer, G. W. (2011). Inadequate early social experience increases the incentive salience of reward-related cues in adulthood. Behavioral Brain Research 220, 91–99.
    • Lovibond, P. F. (1983). Facilitation of instrumental behavior by a Pavlovian appetitive conditioned stimulus. Journal of Experimental Psychology Animal Behavior Processes 9, 225–247.
    • Lovic, V., Saunders, B. T., Yager, L. M., & Robinson, T. E. (2011). Rats prone to attribute incentive salience to reward cues are also prone to impulsive action. Behavioral Brain Research 223, 255–261.
    • Mahler, S. V., & de Wit, H. (2010). Cue-reactors: Individual differences in cue-induced craving after food or smoking abstinence. PLoS One 5, e15475.
    • Mcclure, S. M., & Bickel, W. K. (2014). A dual-systems perspective on addiction: Contributions from neuroimaging and cognitive training. Annals of the New York Academy of Sciences 1327, 62–78.
    • Meyer, P. J., Cogan, E. S., & Robinson, T. E. (2014). The form of a conditioned stimulus can influence the degree to which it acquires incentive motivational properties. PLoS One 9, e98163.
    • Meyer, P. J., Lovic, V., Saunders, B. T., Yager, L. M., Flagel, S. B., Morrow, J. D., & Robinson, T. E. (2012a). Quantifying individual variation in the propensity to attribute incentive salience to reward cues. PLoS One 7, e38987.
    • Meyer, P. J., Ma, S. T., & Robinson, T. E. (2012b). A cocaine cue is more preferred and evokes more frequency-modulated 50-kHz ultrasonic vocalizations in rats prone to attribute incentive salience to a food cue. Psychopharmacology (Berl) 219, 999–1009.
    • Milton, A. L., & Everitt, B. J. (2010). The psychological and neurochemical mechanisms of drug memory reconsolidation: Implications for the treatment of addiction. European Journal of Neuroscience 31, 2308–2319.
    • Morrow, J. D., Maren, S., & Robinson, T. E. (2011). Individual variation in the propensity to attribute incentive salience to an appetitive cue predicts the propensity to attribute motivational salience to an aversive cue. Behavioral Brain Research 220, 238–243.
    • Olney, J. J., Warlow, S. M., Naffziger, E. E., & Berridge, K. C. (2018). Current perspectives on incentive salience and applications to clinical disorders. Current Opinion in Behavioral Sciences 22, 59–69.
    • Paolone, G., Angelakos, C. C., Meyer, P. J., Robinson, T. E., & Sarter, M. (2013). Cholinergic control over attention in rats prone to attribute incentive salience to reward cues. Journal of Neuroscience 33, 8321–8335.
    • Pavlov, P. I. (1927). Conditioned reflexes: An investigation of the physiological activity of the cerebral cortex. London: Oxford University Press.
    • Pitchers, K. K., Flagel, S. B., O’Donnell, E. G., Woods, L. C. S., Sarter, M., & Robinson, T. E. (2015). Individual variation in the propensity to attribute incentive salience to a food cue: Influence of sex. Behavioral Brain Research 278, 462–469.
    • Pitchers, K. K., Kane, L. F., Kim, Y., Robinson, T. E., & Sarter, M. (2017a). “Hot” vs. “cold” behavioural-cognitive styles: motivational-dopaminergic vs. cognitive-cholinergic processing of a Pavlovian cocaine cue in sign- and goal-tracking rats. European Journal of Neuroscience 46, 2768–2781.
    • Pitchers, K. K., Phillips, K. B., Jones, J. L., Robinson, T. E., & Sarter, M. (2017b). Diverse roads to relapse: A Discriminative cue signaling cocaine availability is more effective in renewing cocaine seeking in goal trackers than sign trackers and depends on basal forebrain cholinergic activity. Journal of Neuroscience 37, 7198–7208.
    • Pitchers, K. K., Sarter, M., & Robinson, T. E. (2018). The hot ‘n’ cold of cue-induced drug relapse. Learning & Memory (in press).
    • Pitchers, K. K., Wood, T. R., Skrzynski, C. J., Robinson, T. E., & Sarter, M, (2017c). The ability for cocaine and cocaine-associated cues to compete for attention. Behavioral Brain Research 320, 302–315.
    • Preston, K. L., Kowalczyk, W. J., Phillips, K. A., Jobes, M. L., Vahabzadeh, M., Lin, J. L., Mezghanni, M., & Epstein, D. H. (2018). Exacerbated craving in the presence of stress and drug cues in drug-dependent patients. Neuropsychopharmacology 43, 859–867.
    • Preston, K. L., Vahabzadeh, M., Schmittner, J., Lin, J-L., Gorelick, D. A., & Epstein, D. H. (2009). Cocaine craving and use during daily life. Psychopharmacology (Berl) 207, 291–301.
    • Reilly, M. P., Berndt, S. I., & Woods, J. H. (2016). On the nature of directed behavior to drug-associated light cues in rhesus monkeys (Macaca mulatta). Behavior Analysis Res Practice 16, 200–209.
    • Rescorla, R. A. (1988). Pavlovian conditioning. It’s not what you think it is. American Psychology 43, 151–160.
    • Rescorla, R. A., & Solomon, R. L. (1967). Two-process learning theory: Relationships between Pavlovian conditioning and instrumental learning. Psychological Review 74, 151–182.
    • Robinson, T. E., & Berridge, K. C. (1993). The neural basis of drug craving: an incentive-sensitization theory of addiction. Brain Research Review 18, 247–291.
    • Robinson, T. E., & Berridge, K. C. (2008). Review. The incentive sensitization theory of addiction: Some current issues. Philosophical Transactions of the Royal Society of London B Biological Science 363, 3137–3146.
    • Robinson, T. E., & Flagel, S. B. (2009). Dissociating the predictive and incentive motivational properties of reward-related cues through the study of individual differences. Biological Psychiatry 65, 869–873.
    • Robinson, T. E., Yager, L. M., Cogan, E. S., & Saunders, B. T. (2014). On the motivational properties of reward cues: Individual differences. Neuropharmacology 76, 450–459.
    • Samaha, A-N., & Robinson, T. E. (2005). Why does the rapid delivery of drugs to the brain promote addiction? Trends in Pharmacological Sciences 26, 82–87.
    • Sarter, M., & Paolone, G. (2011). Deficits in attentional control: Cholinergic mechanisms and circuitry-based treatment approaches. Behavioral Neuroscience 125, 825–835.
    • Sarter, M., & Phillips, K. B. (2018). The neuroscience of cognitive-motivational styles: Sign- and goal-trackers as animal models. Behavioral Neuroscience 132, 1–12.
    • Saunders, B. T., O’Donnell, E. G., Aurbach, E. L., & Robinson, T. E. (2014). A cocaine context renews drug seeking preferentially in a subset of individuals. Neuropsychopharmacology 39, 2816–2823.
    • Saunders, B. T., & Robinson, T. E. (2010). A cocaine cue acts as an incentive stimulus in some but not others: Implications for addiction. Biological Psychiatry 67, 730–736.
    • Saunders, B. T., & Robinson, T. E. (2011). Individual variation in the motivational properties of cocaine. Neuropsychopharmacology 36, 1668–1676.
    • Saunders, B. T., & Robinson, T. E. (2013). Individual variation in resisting temptation: Implications for addiction. Neuroscience & Biobehavioral Review 37, 1955–1975.
    • Saunders, B. T., Yager, L. M., & Robinson, T. E. (2013). Cue-evoked cocaine “craving”: Role of dopamine in the accumbens core. Journal of Neuroscience 33, 13989–14000.
    • Shaham, Y., Shalev, U., Lu, L., de Wit, H., & Stewart, J. (2003). The reinstatement model of drug relapse: History, methodology and major findings. Psychopharmacology (Berl) 168, 3–20.
    • Singer, B. F., Bryan, M. A., Popov, P., Scarff, R., Carter, C., Wright, E., Aragona, B. J., & Robinson, T. E. (2016a). The sensory features of a food cue influence its ability to act as an incentive stimulus and evoke dopamine release in the nucleus accumbens core. Learning & Memory 23, 595–606.
    • Singer, B. F., Fadanelli, M., Kawa, A. B., & Robinson, T. E. (2018). Are cocaine-seeking “habits” necessary for the development of addiction-like behavior in rats? Journal of Neuroscience 38, 60–73.
    • Singer, B. F., Guptaroy, B., Austin, C. J., Wohl, I., Lovic, V., Seiler, J. L., Vaughan, R. A., Gnegy, M. E., Robinson, T. E., & Aragona, B. J. (2016b). Individual variation in incentive salience attribution and accumbens dopamine transporter expression and function. European Journal of Neuroscience 43, 662–670.
    • Srey, C. S., Maddux, J. M. N., & Chaudhri, N. (2015). The attribution of incentive salience to Pavlovian alcohol cues: A shift from goal-tracking to sign-tracking. Frontiers in Behavioral Neuroscience 9, 1–13.
    • Stewart, J., de Wit, H., Eikelboom, R., de Wit, H., & Eikelboom, R. (1984). Role of unconditioned and conditioned drug effects in the self-administration of opiates and stimulants. Psychological Review 91, 251–268.
    • Styn, M. A., Bovbjerg, D. H., Lipsky, S., & Erblich, J. (2013). Cue-induced cigarette and food craving: A common effect? Addictive Behaviors 38, 1840–1843.
    • Tomie, A. (1996). Locating reward cue at response manipulandum (CAM) induces symptoms of drug abuse. Neuroscience & Biobehavioral Reviews 20, 505–535.
    • Tomie, A. (2001). Autoshaping and drug-taking. In R. R. Mowrer & S. B. Klein (Eds.), Handbook of contemporary learning theories, (Vol. 1, pp. 409–439). New York, NY: Psychology Press.
    • Tomie, A., Festa, E. D., Sparta, D. R., & Pohorecky, L. A. (2003). Lever conditioned stimulus—directed autoshaping induced by saccharin—ethanol unconditioned stimulus solution: Effects of ethanol concentration and trial spacing. Alcohol 30, 35–44.
    • Tomie, A., Grimes, K. L., & Pohorecky, L. A. (2008) Behavioral characteristics and neurobiological substrates shared by Pavlovian sign-tracking and drug abuse. Brain Research Reviews 58, 121–135.
    • Trask, S., Thrailkill, E. A., & Bouton, M. E. (2017). Occasion setting, inhibition, and the contextual control of extinction in Pavlovian and instrumental (operant) learning. Behavioural Processes 137, 64–72.
    • Tripi, J. A., Dent, M. L., & Meyer, P. J. (2017). Individual differences in food cue responsivity are associated with acute and repeated cocaine-induced vocalizations, but not cue-induced vocalizations. Psychopharmacology (Berl) 234, 437–446.
    • Tunstall, B. J., & Kearns, D. N. (2015). Sign-tracking predicts increased choice of cocaine over food in rats. Behavioral Brain Research 281, 222–228.
    • Uslaner, J. M., Acerbo, M. J., Jones, S. A., & Robinson, T. E. (2006). The attribution of incentive salience to a stimulus that signals an intravenous injection of cocaine. Behavioral Brain Research 169, 320–324.
    • Venniro, M., Caprioli, D., & Shaham, Y. (2016). Animal models of drug relapse and craving: From drug priming-induced reinstatement to incubation of craving after voluntary abstinence. Progress in Brain Research 224, 25–52.
    • Versaggi, C. L., King, C. P., & Meyer, P. J. (2016). The tendency to sign-track predicts cue-induced reinstatement during nicotine self-administration, and is enhanced by nicotine but not ethanol. Psychopharmacology (Berl) 233, 2985–2997.
    • Villaruel, F. R., & Chaudhri, N. (2016). Individual differences in the attribution of incentive salience to a Pavlovian alcohol cue. Frontiers in Behavioral Neuroscience 10, 1–13.
    • Wassum, K. M., Ostlund, S. B., Loewinger, G. C., & Maidment, N. T. (2013). Phasic mesolimbic dopamine release tracks reward seeking during expression of pavlovian-to-instrumental transfer. Biological Psychiatry 73, 747–755.
    • Weiss, F. (2005). Neurobiology of craving, conditioned reward and relapse. Current Opinion in Pharmacology 5, 9–19.
    • Yager, L. M., Pitchers, K. K., Flagel, S. B., & Robinson, T. E. (2015). Individual variation in the motivational and neurobiological effects of an opioid cue. Neuropsychopharmacology 40, 1269–1277.
    • Yager, L. M., & Robinson, T. E. (2010). Cue-induced reinstatement of food seeking in rats that differ in their propensity to attribute incentive salience to food cues. Behavioral Brain Research 214, 30–34.
    • Yager, L. M., & Robinson, T. E. (2013). A classically conditioned cocaine cue acquires greater control over motivated behavior in rats prone to attribute incentive salience to a food cue. Psychopharmacology (Berl) 226, 217–228.
    • Yager, L. M., & Robinson, T. E. (2015). Individual variation in the motivational properties of a nicotine cue: Sign-trackers vs. goal-trackers. Psychopharmacology (Berl), 3149–3160.
    • Zener, K. (1937). The significance of behavior accompanying conditioned salivary secretion for theories of the conditioned response. American Journal of Psychology 50, 384–403.
    • Zimmer, B. A., Oleson, E. B., & Roberts, D. C. (2012). The motivation to self-administer is increased after a history of spiking brain levels of cocaine. Neuropsychopharmacology 37, 1901–1910.
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