PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Neurosci Biobehav Rev. Author manuscript; available in PMC 2011 November 1.
Published in final edited form as:
PMCID: PMC2955797
NIHMSID: NIHMS212204

Individual Differences in Prefrontal Cortex Function and the Transition from Drug Use to Drug Dependence

Abstract

Several neuropsychological hypotheses have been formulated to explain the transition to addiction, including hedonic allostasis, incentive salience, and the development of habits. A key feature of addiction that remains to be explored is the important individual variability observed in the propensity to self-administer drugs, the sensitivity to drug-associated cues, the severity of the withdrawal state, and the ability to quit. In this review, we suggest that the concept of self-regulation, combined with the concept of modularity of cognitive function, may aid in the understanding of the neural basis of individual differences in the vulnerability to drugs and the transition to addiction. The thesis of this review is that drug addiction involves a failure of the different subcomponents of the executive systems controlling key cognitive modules that process reward, pain, stress, emotion, habits, and decision-making. A subhypothesis is that the different patterns of drug addiction and individual differences in the transition to addiction may emerge from differential vulnerability in one or more of the subcomponents.

Keywords: Stress, module, individual differences, cognitive, prefrontal, loss of control, emotion, pain, reward, incentive salience, habits

Background

Addiction

Drug addiction is a chronic relapsing disorder characterized by increased motivation to seek drugs and is characterized in the human condition by increased drug intake, loss of control over drug intake, and compulsive drug taking and drug seeking. Three major components of the addiction cycle have been identified—binge/intoxication, withdrawal/negative affect, and preoccupation/anticipation (craving)—and incorporate the constructs of impulsivity and compulsivity with varying contributions of positive and negative reinforcement (Koob and Le Moal, 2008; Koob et al., 2008). From a theoretical perspective, the increased motivation to seek drugs has been hypothesized to involve counteradaptive mechanisms (Solomon and Corbit, 1974; Wikler, 1973), increases in incentive salience (Robinson and Berridge, 1993), or a combination of both constructs in the form of an allostatic change in hedonic set point (Ahmed and Koob, 1998; Koob and Le Moal, 1997, 2001).

The counteradaptive theory states that two opposing processes control affect and the motivational changes observed after chronic drug use. The initial rewarding effect of the drug (a-process) will trigger a delayed aversive effect (b-process) that gets larger with chronic drug use and will counteract the a-process to maintain homeostasis. This model has been proposed to explain tolerance, withdrawal, and the aversive craving state observed during abstinence (Solomon and Corbit, 1974; Laulin et al., 1999). Allostasis, in the context of addiction, is the process of maintaining apparent reward function stability through changes in brain reward and stress mechanisms (Koob and Le Moal, 2001). The allostatic state represents a chronic deviation of reward set point that is mostly observed during abstinence and not observed when the individual is actively taking drug. Thus, the allostatic view extends counteradaptive theory by stating that not only the b-process gets larger with chronic drug use but the reward set point from which the a-process and b-process are anchored progressively shifts downward, creating an allostatic state. This model has been proposed to explain the persistent changes in motivation in drug-dependent individuals.

Although drug addiction is often viewed as one disorder, it is important to note that different drugs produce different patterns of addiction that engage different components of the addiction cycle (Koob et al., 2008). Opioid and alcohol addictions are characterized by an intense withdrawal/negative affect stage with profound dysphoria and physical and emotional pain often followed by intoxication during the binge/intoxication stage, thus representing one of the main driving forces for compulsive drug seeking and drug taking. Profound tolerance occurs to the intoxication associated with alcohol and opioids, but some intoxication always remains. Nicotine addiction is not associated with major intoxication but is instead characterized by highly compulsive titrated intake of the drug to the point that daily activities (e.g., social contact, meals, and sleep) are perturbed and constrained by the patterns of nicotine intake. Nicotine addiction is also associated with intense dysphoria, irritability, sleep disturbances, and craving during abstinence. Marijuana addiction shares aspects of both opioid and nicotine addiction, with an initial intense binge/intoxication stage that progressively transitions to regular and titrated marijuana intake during the day and dysphoria during abstinence. Cocaine and amphetamine addiction are characterized by major binge/intoxication and preoccupation/anticipation stages, with an intense craving for the drug and binges that can last hours or days and are usually followed by intense dysphoria during acute withdrawal and protracted abstinence associated with anxiety, dysphoria, and intense craving. Again, profound tolerance develops to the intoxication associated with the drug during a binge.

Important individual differences in the different stages of addiction, as well as in the vulnerability to the transition to addiction, have been observed in humans and animals (Anthony et al., 1994; Crowley et al., 1998; de Wit et al., 1986; Deroche-Gamonet et al., 2004). Significant individual differences have been observed in (i) the sensitivity to the pharmacological effects of the drug, (ii) the propensity to self-administer the drug, (iii) resistance to extinction, (iv) sensitivity to drug-associated cues, (v) relapse, and (vi) cognitive functions critical for the development of addiction, such as working memory, attention, reward evaluation, emotion, pain, and stress. It is important to note that the construct of individual difference here encompasses normal variations in function and dysfunction (or vulnerability). For the purpose of this review, we will not dissociate the contribution of the individual from the contribution of the situation in the development of individual differences because both can lead to dysregulated behavior and increased risk for the development of drug dependence.

Different types of drug users also exist. For example, different types of tobacco users have been identified, including individuals who initially limit their intake but progressively escalate their intake and develop a strong dependence on tobacco; individuals who smoke regularly but who will always limit their tobacco intake (defined as nondependent “chippers”); and individuals who limit their intake but who will experience periods of high intake and high dependence on tobacco (Kassel et al., 1994). These different patterns of drug use and addiction suggest that the addiction process is not a unitary process and that different neuropsychobiological mechanisms may explain different drug use patterns that may ultimately lead to compulsive drug seeking and drug taking.

Animal Models

Animal models of the major components of the addiction cycle have been established and validated. The binge/intoxication stage can be modeled by acquisition of drug self-administration under limited access conditions (Piazza and Le Moal, 1996), brain stimulation reward (Kornetsky and Esposito, 1979), conditioned place preference (Carboni and Vacca, 2003), and drug discrimination (Holtzman, 1990). The withdrawal/negative affect stage can be modeled by intracranial self-stimulation (Epping-Jordan et al., 1998), conditioned place aversion (Stinus et al., 1990), drug discrimination (Holtzman, 1990), and drug self-administration in dependent subjects (Denoble and Begleiter, 1976; Gellert and Sparber, 1977). The preoccupation/anticipation stage can be modeled by drug self-administration and different paradigms, such as resistance to extinction (Schuster and Woods, 1968), drug-, stress-, or cue-induced reinstatement (Shaham et al., 2003), protracted abstinence (Roberts et al., 2000), conditioned withdrawal (Wikler and Pescor, 1967), and second-order schedules of reinforcement (Katz and Goldberg, 1991). Moreover, animal models of the transition to addiction that incorporate these three stages have also been developed and validated. These models include escalation in drug self-administration with extended access to the drug (Ahmed and Koob, 1998), the alcohol and nicotine deprivation effect (George et al., 2007; Koob, 2000), and drug seeking and drug taking in the presence of negative consequences (Deroche-Gamonet et al., 2004; Vanderschuren and Everitt, 2004).

Control and Cognitive Modules in Addictions

At the social psychology level, failure of self-regulation has been argued to be one of the main causes of psychosocial pathologies, including addiction (Baumeister, 2003b). Failure of self-regulation represents a deficit in information-processing, attention, planning, reasoning, self-monitoring, or inhibition of a specific brain function or behavior (Baumeister et al., 1994; Giancola et al., 1996a, b). Depending on the different stages of the addiction cycle, failure of self-regulation may lead to an increased risk of exposure to the drug, increased drug seeking and drug taking, increased relapse, or increased vulnerability to the transition to addiction. Failure of self-regulation is hypothesized to result at the neurobiological level in a loss of control of a brain structure over specific neural systems underlying relatively independent brain functions, such as stress, anxiety, reward, pain, habits, and decision-making. This loss of control has often been attributed to a dysfunction of the frontal lobes or hypofrontality (Bechara, 2005; Mishkin, 1964; Pribram, 1956) and subsequent dysregulation of the different subcortical cognitive systems controlled by the prefrontal cortex. For instance, deficits in frontal cortex regulation in children or young adolescents predict later drug and alcohol consumption, especially for children raised in families with drug and biobehavioral disorders histories (Dawes et al., 1997; Aytaclar et al., 1999).

Cognition and its neural representations have been hypothesized to be organized into a set of modules that are specialized for distinct cognitive processes and different types of information processing (Fodor, 1983). The theory of “modularity of mind” describes mind as composed of several insulated modules that are relatively independent in their functioning. These modules have separate classes of input and information processing inside each module and theoretically cannot be influenced by the activity of another module (Fodor, 1983). Imaging, brain lesion, and neuropharmacological studies have demonstrated in both humans and animals the modularity of cognition. Classical examples of modularity are the high specificity of activation of cortical areas during the presentation of words, colors, faces, or places (Gazzaniga et al., 2000) or the dissociation between conditioning and declarative knowledge after lesions of the amygdala and hippocampus (Bechara et al., 1995). The modularity of mind theory has also been reinforced by brain lesion studies demonstrating double and even triple dissociations between different brain functions, such as explicit vs. implicit memory (Cohen et al., 1980), conditioning and declarative knowledge (Bechara et al., 1995), memory vs. fear vs. anxiety (Bannerman et al., 2004), pain affect and sensation (Ploner et al., 1998), and reward vs. motivation (Berridge et al. 2009). It is now well established that sensation, perception, motor action, or even different types of memories represent different cognitive modules with different neural systems that are more or less independent in their functioning. Flexible, goal-directed behavior requires an adapted cognitive control system for organizing, selecting, and consolidating information that derives from the different modules into a coherent and unified experience. The prefrontal cortex and its different subregions have been hypothesized to represent this cognitive control system (Baddeley, 1996; Robbins, 2000; Ridderinkhof et al., 2004).

The prefrontal cortex sends projections to most cortical and subcortical structures and targets the main sources of major diffiuse neurotransmitter systems, including the dopaminergic, noradrenergic, serotoninergic, and cholinergic neurons in the basal forebrain and brainstem (Goldman-Rakic, 1987; Gabbot et al., 2005). Moreover, neuroanatomical, brain lesion, and site-specific pharmacological modulation studies of the prefrontal cortex have revealed the heterogeneity of the prefrontal cortex (Robbins, 2000).

As explained above, there are important individual differences in the different stages of addiction and in key brain functions critical for the development of addiction, such as attention, decision-making, reward, emotion, pain, and stress (Crowley et al., 1998; de Wit et al., 1986; Deroche-Gamonet et al., 2004). We suggest that the concept of self-regulation, combined with the concept of modularity of cognitive function, may help one understand the neural basis of the individual differences in the vulnerability to drug addiction. Indeed, dysfunction of a specific subregion of the prefrontal cortex may lead to a loss of control over a specific neurobiological system, leading, for instance, to a sensitization of insentive salience in one individual and to a hyperreactivity of the stress system in another individual. Therefore, the failure of a specific module may differ from one individual to another and may represent a neuropsychobiological mechanism underlying individual differences in the vulnerability to drug addiction.

Neural Systems and Cognitive Modules

Numerous reports have demonstrated a role for the dopamine, corticotropin-releasing factor (CRF), opioid, serotonin, γ-aminobutyric acid (GABA), cholinergic, adrenergic, glutamatergic, and peptidergic systems in drug addiction (Koob and Le Moal 2006). Many reports have also demonstrated a role for the ventral tegmental area (VTA), central (CeA) and basolateral (BLA) nuclei of the amygdala, bed nucleus of the stria terminalis (BNST), dorsal and ventral striatum (nucleus accumbens), ventral pallidum, hypothalamus, and prefrontal cortex in drug addiction (Koob and Volkow 2010). The identification of drug addiction as a brain disease has oriented research in the addiction field toward a search for a common final pathway to explain the transition to addiction. Significant breakthroughs have been made, suggesting that there are common neurobiological mechanisms in all types of addictions. Converging lines of evidence suggest that a dysregulation of the dopaminergic system, CRF system, or ΔFosB may mediate the transition to addiction (for review, see Everitt and Robbins, 2005; Koob and Le Moal, 2008; Nestler, 2001; Robinson and Berridge, 1993). However, the number of neurotransmitter systems, brain structures, and different physiological, psychological, and cognitive mechanisms involved in the addiction process suggests that understanding individual differences in the transition to addiction may require a more integrated modular view of the neuropsychological mechanisms of addiction.

The thesis of this review is that drug addiction involves a failure of the different subcomponents of the executive systems controlling key systems that process reward, pain, stress, dysphoria, and habits. A subhypothesis is that the different patterns of drug addiction and individual differences in the transition to addiction may emerge from differential vulnerability in one or more of the subcomponents. A multi-system framework with a focus on different psychological and computational vulnerabilities has been recently formulated to explain patterns of addiction across drugs and individuals (Redish et al., 2008). The focus of the present review is instead on the elaboration of a multi-system framework with a focus on the different neurobiological systems that may be differentially involved in the addiction process. In the following sections we will briefly review the neuroanatomy and function of the modules and review how individual differences in the functioning of these modules may explain individual differences in the transition to addiction. It is important to note that the modules described here are not Fodorian in the sense that they are not fully encapsulated (Fodor 1983). However, they share many properties of Fodorian modules, such as domain specificity, mandatory operation, limited accessibility, fast processing, and fixed neural architecture, and they exhibit specific breakdown patterns (see examples of double dissociation described above).

Incentive Salience and the Mesolimbic Dopamine Module

Neuroanatomy and Function

The mesolimbic dopamine system is formed by dopaminergic cell bodies in the VTA and their projections to the ventral striatum (Fig. 1). The VTA also possesses a population of GABAergic neurons that provide inhibitory inputs to dopamine cells and influence other structures, such as the pedunculopontine tegmental nucleus and glutamatergic neurons (Dobi et al., 2010). The VTA receives its main excitatory glutamatergic and cholinergic inputs from the ventromedial prefrontal cortex (ventral prelimbic, infralimbic, dorsal peduncular cortices), ventral subiculum, subthalamic nucleus, parabrachial nucleus, pedunculopontine tegmental nucleus, and laterodorsal tegmental nucleus (Kalivas, 1993). The VTA also receives prominent inputs from the nucleus accumbens shell and the ventromedial ventral pallidum (Oades and Halliday 1987). Dopamine and GABA neurons in the VTA have been shown to be critical for the rewarding properties of psychostimulants, and with the possible exception of opioids, all drugs of abuse when self-administered acutely stimulate the dopaminergic system and increase dopamine release in the nucleus accumbens (Volkow et al., 2002). The pattern of firing of dopaminergic neurons in the VTA in response to drugs of abuse has been hypothesized to encode drug reward, attribution of incentive salience, and establishment of response habits (Wise, 1980, 1987, 2002). Attribution of incentive salience refers to a process that transforms sensory information about reward into attractive incentives (Robinson and Berridge, 1993). Individual differences in incentive salience may represent a key mechanism to explain individual differences in the vulnerability to addiction, and excessive attribution of incentive salience to drug-related cues may contribute to excessive drug intake, compulsive behavior, and relapse.

Figure 1
Anatomical functional differences in the prefrontal cortex in the rat

Individual Differences

There are considerable individual differences in the reinforcing properties of drugs of abuse in humans and animals (de Wit et al., 1986; O’Brien CP, 1986). The acute rewarding effects of drugs of abuse are critical in nondependent users and represent a powerful source of positive reinforcement for the initiation and maintenance of drug self-administration. Individual differences in the mesolimbic dopamine system have been observed in humans and have been related to differential anticipation and reward-seeking behavior. Individual differences in dopamine D2 receptor binding in the ventral/dorsal striatum suggest differential activity of the mesolimbic dopamine system (Volkow et al., 1993). Individual differences in amphetamine-induced dopamine release are associated with increased drug-induced “wanting” and novelty-seeking (Leyton et al., 2002). Higher ratings of positive amphetamine effects are also associated with greater dopamine release in the ventral striatum, dorsal putamen, and dorsal caudate (Oswald et al., 2005). Baseline D2 receptor availability in the striatum negatively predicts rates of cocaine self-administration in monkeys (Nader et al., 2006).

Individual differences in the sensitivity of the VTA to electrical self-stimulation has been observed and related to differential sensitivity of the reward system (Druhan et al., 1990). Moreover, rats that show increased novelty-seeking and increased cocaine self-administration also show dysregulation of tyrosine hydroxylase and cholecystokinin in the VTA (Lucas et al., 1998), increased basal firing rates of dopamine neurons in the VTA (Marinelli and White, 2000), and increased basal or drug-induced dopamine release in the nucleus accumbens (Bradberry et al., 1991; Hooks et al., 1992; Piazza et al., 1991b; Rouge-Pont et al., 1998). Furthermore, individual differences in dopamine transporters in the VTA and dopamine and serotonin levels in the striatum have been associated with individual differences in behavioral sensitization to amphetamine (Antoniou et al., 2008; Dietz et al., 2008; Piazza et al., 1991b). These results suggest that the mesolimbic dopamine system and the ventral striatum may represent a key system for the vulnerability to the positive reinforcing effects of drugs and the initiation and maintenance of drug self-administration.

Stress and the Hypothalamic-Pituitary-Adrenal Axis

Neuroanatomy and Function

The hypothalamic-pituitary-adrenal (HPA) axis is defined by three major structures: the paraventricular nucleus of the hypothalamus (PVN), the anterior lobe of the pituitary gland, and the adrenal gland (for review, see Turnbull and Rivier, 1997). Neurosecretory neurons in the medial parvocellular subdivision of the PVN synthesize and release CRF into the portal blood vessels that enter the anterior pituitary gland. Binding of CRF to the CRF1 receptor on pituitary corticotropic cells induces the release of adrenocorticotropic hormone (ACTH) into the systemic circulation (Fig. 1). ACTH, in turn, stimulates glucocorticoid synthesis and secretion from the adrenal cortex. Vasopressin released from parvocellular neurons of the PVN produces synergistic effects on ACTH release that are mediated by vasopressin V1b receptors (Scott and Dinan, 1998). The HPA axis is finely tuned via negative feedback from circulating glucocorticoids that act on the glucocorticoid receptor, a cytosolic protein that acts via the nucleus on transcriptional mechanisms in two main brain areas: the PVN and the hippocampus (Herman et al., 1996). The hypophysiotropic neurons of the PVN are innervated by numerous afferent projections from the brainstem, other hypothalamic nuclei, and forebrain limbic structures. The medial prefrontal cortex in the rat possesses a large number of glucocorticoid receptor-positive neurons that can bidirectionally control stress reactivity of the HPA axis through activation of the prelimbic or infralimbic cortex (Radley et al., 2006). Lesions of the prelimbic cortex increase ACTH and corticosterone responses to stress, whereas lesions of the infralimbic cortex have an opposite effect (Radley et al., 2006). This differential control is attributable to differential projections of the prelimbic and infralimbic cortex to structures mediating either stress inhibition (ventrolateral preoptic area, dorsomedial hypothalamus, and PVN) and stress activation (anterior BNST, medial nucleus of the amygdala; CeA, and nucleus of the tractus solitarus), respectively (Radley et al., 2006).

The HPA axis plays a key role in mediating the reinforcing effects of drugs of abuse and stress-induced relapse. Drugs of abuse acutely activate the HPA axis, and dependence dysregulates the HPA axis (Piazza and le Moal 1996). Stressors facilitate the acquisition of cocaine and amphetamine self-administration, and rats with heightened reactivity to stress acquire drug self-administration faster and at lower doses (Piazza et al., 1989; Piazza and Le Moal, 1998; Piazza et al., 1991a; Piazza et al., 1996). Moreover, corticosterone facilitates the acquisition of cocaine self-administration (Mantsch et al., 1998; Piazza et al., 1991a). The effect of glucocorticoids on the reinforcing effects of drugs is hypothesized to be attributable to activation of dopamine neurons in the VTA and increased dopamine release in the nucleus accumbens (Barrot et al., 2001; Barrot et al., 2000; Piazza and Le Moal, 1998). Furthermore, excessive drug intake and possibly the transition to dependence are associated with tolerance of the HPA axis response to stress and overactivation and persistent dysregulation during early withdrawal and protracted abstinence (Mantsch et al., 2003; Zhou et al., 2003a; Zhou et al., 2003b). Interestingly, the HPA axis also interacts with the extended amygdala. High circulating levels of glucocorticoids can activate the CRF and norepinephrine systems in the CeA and BLA through a positive feedback mechanism (Imaki et al., 1991; Makino et al., 1994; Swanson and Simmons, 1989). These results suggest that the HPA axis may be involved in both the initial positive reinforcing effects of the drug and on the vulnerability to relapse after protracted abstinence, particularly during stressful events (Erb et al., 1996, 1998; Martin-Fardon et al., 2000).

Individual Differences

Individual differences in the responsivity of the HPA axis to stress are very well understood. Sensation-seeking and novelty-seeking are personality traits that have been associated with higher propensity to self-administer drugs and dysregulation of the HPA axis in humans and rodents (Piazza and Le Moal, 1998). Animal models for these traits include the characterization of high vs. low responders by measuring locomotor activity in an inescapable novel environment (Piazza et al., 1989). High responders are more sensitive to cocaine, amphetamine-induced locomotor activity, and amphetamine self-administration. This increased sensitivity to drugs of abuse in high responder rats has been shown to be dependent on the HPA axis. High responder rats exhibit an exaggerated corticosterone response to stress, and this increased corticosterone drives in part the increased activation of the VTA and dopamine release in the nucleus accumbens (Piazza and Le Moal, 1998; Piazza et al., 1991a). Individual differences in the HPA axis are then likely to confer vulnerability to the initial positive reinforcing effects of drugs, at least during initial drug exposure and the acquisition of self-administration, but not necessarily vulnerability to dependence per se. Indeed, recent reports suggest that although heightened reactivity of the HPA axis is associated with a vertical shift in the cocaine dose-response curve and increased self-administration during acquisition, it is not associated with increased compulsive cocaine intake (Belin et al., 2008; Deroche-Gamonet et al., 2004). Moreover, the effect of stress on relapse does not appear to be directly mediated by the HPA axis but rather indirectly by the extrahypothalamic CRF system through a CRF-CRF1 receptor connection between the CeA and ventral BNST (Erb et al., 1998; Erb and Stewart, 1999; Le et al., 2002; Le et al., 2000; Shaham et al., 1997; Shalev et al., 2009) and the noradrenergic system through a nucleus accumbens-β-adrenergic receptor connection between the lateral tegmental nucleus and BNST (Erb et al., 2000; Shaham et al., 2000). Dysregulation of the HPA axis may represent a key factor in the vulnerability to addiction by modulating two key modules. Heightened reactivity of the HPA axis may facilitate both the positive reinforcing effects of drugs via modulation of the mesolimbic dopamine system and the negative reinforcing effects of drugs by activating the extended amygdala and thus may be involved in the initiation, maintenance, and relapse of drug self-administration.

Negative Emotional States and the Extended Amygdala Module

Neuroanatomy and Function

The extended amygdala is a neuroanatomical macrostructure in the basal forebrain that shares similarities in morphology, neurochemistry, and connectivity (Fig. 1). It is composed of the BNST, CeA, MeA, and a transition zone in the posterior medial part (shell) of the nucleus accumbens (Koob and Le Moal, 2001). This system receives afferents from limbic and olfactory cortices. Key inputs are the insular cortex and the ventral medial prefrontal cortex (ventral prelimbic, infralimbic, and dorsal peduncular cortices), lateral hypothalamus, parabrachial nucleus, lateral tegmental nucleus, and BLA either through direct or indirect projections via the GABAergic intercalated cell mass (Gray et al., 1993; Reynolds and Zham, 2005; Alheid and Heimer, 1998; Koob et al., 1998) (Fig. 1). The extended amygdala projects heavily to the lateral hypothalamus, ventral pallidum (posterior medial), VTA, pedunculopontine tegmental nucleus, parabrachial nucleus, lateral tegmental nucleus, and other midbrain structures (Gray et al., 1993; Reynolds and Zham, 2005; Alheid and Heimer, 1998; Koob et al., 1998). As such, the extended amygdala links the basal forebrain to the classic reward systems of the lateral hypothalamus via the medial forebrain bundle reward system. Key elements of the extended amygdala include neurotransmitters of the brain stress systems associated with the negative reinforcement of dependence, such as CRF and norepinephrine (Koob and Le Moal, 2005). Studies on fear and anxiety have identified the amygdala as a central component of the processing of fear, threats, and anxiety in humans and animals (Koob and Le Moal, 2008; LeDoux, 2000). The extended amygdala is hypothesized to engage the organism in fight or flight responses and to encode negative emotional states. Dysregulation of the extended amygdala has been hypothesized to play a key role in disorders related to stress and negative emotional states, such as posttraumatic stress disorder, general anxiety disorder, phobias, and affective disorders (Shin and Liberzon, 2010). Neuroadaptive changes in this extended amygdala circuit may also lead to the aversive effects and dysregulated reward system hypothesized to be the motivation for the transition to drug addiction (Koob and Le Moal, 2008).

Individual Differences

Converging evidence suggests that there are major individual differences in the response of the extended amygdala to emotional stimuli (Beaver et al., 2008; Bishop et al., 2004; Canli, 2004; Canli and Gabrieli, 2004; Hamann and Canli, 2004; Mather et al., 2004). Individual differences in a personality trait linked to the drive to gain reward (increased reward-drive) correlate positively with activation of the amygdala and negatively correlated with activity in the ventromedial prefrontal cortex (Beaver et al., 2008). A heightened predisposition to aggression is also associated with an increased amygdala response to aggressive facial displays (Coccaro et al., 2007; Passamonti et al., 2008). The CeA (dorsal amygdala in humans) is also recruited during conscious processing of fearful faces in healthy volunteers, and individual differences in trait anxiety predict the response of a key input to the CeA, the BLA, to unconsciously processed fearful faces (Etkin et al., 2004). The amygdala is also activated during affective judgment and during the expression of emotional responses when viewing affective pictures (Phan et al., 2003; Taylor et al., 2003). Moreover, the amygdala is activated during drug craving (Childress et al., 1999; Kilts et al., 2001; Volkow et al., 1999; Wang et al., 1999; Wexler et al., 2001), and decreased amygdala volumes (Makris et al., 2004) and abnormalities in the fiber tracts connecting the orbitofrontal cortex and anterior cingulate cortex to the amygdala have been observed in some cocaine addicts (Lim et al., 2002). Interestingly, the changes in amygdala volume in cocaine addicts were observed even in subjects recently exposed to cocaine (<1–2 years), suggesting that decreased amygdala volume represents either early drug-induced impairment or an individual developmental predisposition (Lim et al., 2002).

Individual differences have also been observed in rodents. Differences in anxiety-like behavior have been related to differential levels of vasopressin and androgen receptors (Linfoot et al., 2009), glucocorticoid receptors, and cholecystokinin-B receptors (Wunderlich et al., 2002) in the extended amygdala. Individuals with increased anxiety-like responding exhibited a downregulation of amygdala cholecystokinin-B receptor binding, possibly reflecting compensation for increased cholecystokinin activity (Wunderlich et al., 2002). Individual differences in the sensitivity of the CeA to inactivation by a GABAA receptor agonist have also been observed in rats self-administrating amphetamine. Inactivation of the CeA only decreased amphetamine self- administration in rats with excessive drug intake, suggesting that individual differences in the recruitment of the CeA might predispose an individual to excessive drug intake (Cain et al., 2008). Altogether, these results demonstrate that individual differences in the activity of the extended amygdala may predispose individuals to heightened anxiety, stress, and a negative emotional state and represent a key factor in the transition from positive to negative reinforcement and the transition to addiction.

Pain and the Opioid Spinomesothalamocortical Module

Neuroanatomy and Function

Pain is a subjective experience that has a powerful influence on decision-making and can dramatically alter the reinforcing effects of drugs of abuse, particularly opiates, and facilitate the transition to drug addiction (Miller and Gold 2007). Pain is a multidimensional phenomenon that includes acute pain, chronic pain, and emotional pain as well as different types of pain based on different noxious stimuli (e.g., chemical, heat, mechanical). The neural substrates of acute and chronic pain have been extensively studied using imaging techniques in humans and rodents (Peyron et al., 2000; Porro, 2003; Vogt, 2005). Key areas involved in the processing of acute and chronic pain involve the spinoreticular, spinomesencephalic, and spinothalamic tract, parabrachial nuclei, periaqueductal gray area (PAG), rostroventromedial medulla, medial and ventroposterolateral thalamus, centrolateral, centromedian, and parafascicular nucleus of the thalamus, amygdala, somatosensory cortex, insular cortex, and anterior cingulate cortex (Fig. 1) (Peyron et al., 2000; Porro, 2003; Vogt, 2005). Pain is associated with activation of a primary afferent nociceptor that transmits pain signals to a second-order neuron in the dorsal horn that crosses contralaterally and sends efferents to the brainstem, thalamus, and neocortex. Some have argued that the classic pain pathway (spinothalamocortical) mediates physical pain, whereas the affective component of pain is mediated by the extra-spinothalamocortical pathway (Besson, 1999; Price, 2000). Key regions in the processing of emotional pain in this pathway are the parabrachial nucleus, CeA, PAG, insula, and anterior cingulate cortex (Besson, 1999; Price, 2000). Chronic and acute pain is associated with hyperactivity of the dorsal horn and spinothalamic tract, resulting in activation of the neocortex as well as hyperactivity of the parabrachial nucleus and CeA (Han and Neugebauer, 2004). Moreover, the CeA can control pain through a descending projection to the PAG and rostroventromedial medulla that can modulate nociceptive relay neurons in the dorsal horn (Gaurieau and Bernard, 2002). The main neurotransmitter mediating control over pain signals through the descending pathways is the endogenous opioid enkephalin. Enkephalin acts through activation of the μ-opioid receptor, and μ-opioid-induced analgesia is hypothesized to be mediated at different levels of the descending pathways (hypothalamus, amygdala, and PAG) (Fields, 2000). Interactions between pain and the motivation to obtain drugs have been demonstrated, particularly for opiate and alcohol addiction. For example, in rats with hypersensitivity of the hindpaw to mechanical stimulation, only heroin doses that produce a reversal of hypersensitivity maintained heroin self-administration following nerve injury, whereas lower doses were only effective in maintaining drug self-administration in control rats (Martin et al., 2007), suggesting that the driving force for the motivation to self-administer drugs in individuals with a sensitized pain system may be seeking relief of chronic pain.

Individual Differences

Individual differences have been well described in pain studies. Pain thresholds greatly vary with gender, age, and the subject’s behavioral state (Fillingim et al., 2009; Gibson and Helme, 2001; Nielsen et al., 2009). For instance, under great emotion or intense concentration, people often report few signs of pain despite severe injuries (Fields, 2004). Imaging studies have shown that activity in the midbrain, medial thalamus, and cortical nociceptive-receiving areas such as the insula and anterior cingulate cortex correlate with pain intensity (Casey, 2000). Individuals with low pain thresholds exhibit higher activation of the primary somatosensory cortex, anterior cingulate cortex, and prefrontal cortex than individuals with high pain thresholds (Coghill et al., 2003). Interestingly, individual differences did not correlate with differential activation of the thalamus despite its key involvement in the encoding of nociceptive information (Coghill et al., 2003). Moreover, the impact of perceived controllability on pain perception varies highly between individuals and is correlated with differential activation of the anterior cingulate cortex, insula, and ventrolateral prefrontal cortex (Salomons et al., 2007). Activity in the anterior cingulate cortex, dorsolateral prefrontal cortex, insular cortex, nucleus accumbens, thalamus, and PAG correlated with the magnitude of placebo analgesia in humans (Wager et al., 2004; Zubieta et al., 2005) and is mediated in part via activation of the endogenous opioid system, specifically activation of μ-opioid receptors (Zubieta et al., 2005). Abnormal pain perceptions have been reported in opiate addiction during the development, maintenance, and withdrawal periods (Compton, 1994; Compton et al., 2000; Compton and Estepa, 2000; Doverty et al., 2001a; Doverty et al., 2001b), and preexisting pain problems are a key factor in the transition to opiate abuse and addiction (Brands et al., 2004). Altogether, these results suggest that dysregulation of the pain system, particularly the insula, anterior cingulate cortex, and CeA, because of the cross between “affective” pain pathways there and negative emotional states, might confer vulnerability to drug addiction in some individuals.

Habits and the Striatal Module

Neuroanatomy

The striatum in rodents can be divided into several components, including the ventral striatum (nucleus accumbens shell and core) and dorsal striatum (dorsomedian and dorsolateral) (Fig. 1). The striatum is composed of inhibitory GABAergic cells projecting to the pallidum (95% of striatal cells) and the brainstem and local cholinergic interneurons (5% of striatal cells) (Gerfen, 1992). The connectivity of the striatum is organized on a ventromedial to dorsolateral axis (Voorn et al., 2004). The nucleus accumbens shell receives dopaminergic inputs from the VTA and glutamatergic inputs from the ventromedial ventral PFC (ventral prelimbic, infralimbic, dorsal peduncular cortices) and insular cortex and projects to the ventromedial part of the ventral pallidum and VTA (Reynolds and Zahm 2005; Gabbot et al., 2005). The nucleus accumbens core receives dopaminergic inputs from the VTA and glutamatergic inputs from the dorsomedial prefrontal cortex (dorsal prelimbic, anterior cingulate cortex) and insular and orbital frontal cortices and projects to the dorsolateral part of the ventral pallidum and dorsomedial substantia nigra (Reynolds and Zahm 2005; Gabbot et al., 2005). The dorsomedial and dorsolateral striatum receives glutamatergic inputs from the orbitofrontal cortex, anterior cingulate cortex, and sensory and motor cortices and projects to the globus pallidus and ventrolateral substantia nigra (Reynolds and Zahm 2005; Gabbot et al., 2005). The striatum and cortico-striato-pallido-thalamic loops have generally been studied for their role in locomotor activity, attention, reward, goal-directed behavior, and habits. These loops have inputs from the mesolimbic and mesostriatal systems and are partially overlapping and organized in a ventral-to-dorsal manner (Voorn et al., 2004). Recent reports suggest that these striatal loops are involved in the maintenance of drug-seeking behavior under a second-order schedule of reinforcement and might be important for addiction (Belin and Everitt, 2008). A ventral system, including the ventral striatum and its inputs from the orbitofrontal cortex, infralimbic cortex, hippocampus, amygdala, and VTA, is key for the acquisition of instrumental responding, such as the acquisition of cocaine self-administration (Belin et al., 2009). A dorsomedial system, including the dorsomedial striatum and inputs from the anterior cingulate cortex and prelimbic cortex, and premotor cortices may be key for goal-directed behavior in general. A dorsolateral system, including the dorsolateral striatum and its somatosensory inputs and connections with the mesostriatal dopaminergic system, may underlie habit responding (Belin et al., 2009). Recent studies suggest that the transition to drug dependence is associated with a progressive dysregulation of the ventral, dorsomedial, and dorsolateral striatal systems mediating the transition from impulsive to compulsive drug-seeking and drug-taking (Belin and Everitt, 2008).

Individual Differences

Individual differences have been largely reported at the behavioral level in the acquisition of instrumental behavior, goal-directed behavior, and habit responding (Boakes, 1977; Tomie et al., 2000; Zener, 1937) and have been related to individual differences in dopamine levels and D1 receptor mRNA in the dorsal and ventral striatum (Cheng and Feenstra, 2006; Flagel et al., 2008; Tomie et al., 2000). Individual differences have been observed not only in terms of quantitative but also qualitative differences. Indeed, subjects can adopt different strategies for solving problems (goal-directed vs. habit) to reach similar performance levels in behavioral tasks even when both strategies are successful. When constrained to only one strategy, important performance differences can be observed, suggesting individual differences in the functioning of the striatum and corticostriatopallidothalamic loops (Flagel et al., 2007).

Impulsivity, escalation, and compulsivity are hypothesized to represent the different steps of a continuum of behavioral alterations that are observed during the transition to addiction, reflected in the development of the inflexible and habit-like behavior associated with drug seeking in nondependent subjects and drug taking in dependent subjects, respectively (Dalley et al., 2007). Low D2 receptor binding in the ventral striatum predicts the magnitude of cocaine intake escalation and compulsive cocaine intake when rats are given extended but not limited access to cocaine (Dalley et al., 2007a). Moreover, detoxified drug abusers exhibit decreased D2 receptor binding in the ventral striatum that correlates with self-reported preference for methylphenidate (Volkow et al., 1999). In compulsive cocaine users, individual differences in craving after methylphenidate injection in cocaine abusers have also been demonstrated and correlate with increased metabolic activity in the striatum and orbitofrontal cortex (Volkow et al., 1999). Individual differences in D2 binding in the striatum have also been reported between subordinate and dominant monkeys, and there appears to be an inverse relationship between D2 receptor levels and vulnerability to the reinforcing effects of cocaine (Nader et al., 2005). Subordinate monkeys exhibit lower D2 receptor binding (Grant et al., 1998; Morgan et al., 2002) and increased cocaine intake (Morgan et al., 2002). Altogether, these results suggest that individual differences in the ventral and dorsal striatum may underlie both the vulnerability to the positive reinforcing effects of the drug and the vulnerability to the transition from goal-directed to compulsive drug seeking.

Decision-Making and the Prefrontal Cortex Module

Neuroanatomy

The prefrontal cortex in rodents can be dissociated into medial, lateral, and ventral parts (Fig. 2) (Robbins, 2000). The medial PFC is composed of a dorsal section with the anterior cingulate, precentral, and dorsal prelimbic cortices and a ventral section with the ventral prelimbic, infralimbic, dorsal peduncular, and medial orbital cortices. The lateral PFC is composed of the orbitofrontal cortex and the dorsal and ventral anterior insular cortices. The ventral PFC is composed of the ventral orbital and ventral lateral orbital cortices. The main output of the prefrontal cortex is composed of excitatory glutamatergic pyramidal neurons (Goldman-Rakic, 1987). Pyramidal neurons are under tight control by local GABAergic inhibitory interneurons (Wilson et al., 1994; Rao et al., 2000). The different subregions of the prefrontal cortex send and receive highly organized connections with the basal ganglia through the cortico-striato-pallido-thalamo-cortical and cortico-pallido-nigro-thalamo-cortical loops (Groenewegen et al., 1997; Voorn et al., 2004). Through its different subregions, the PFC can control virtually all of the subcortical structures through the modulation of the cholinergic, dopaminergic, adrenergic, and serotonergic systems by activating basal forebrain and brainstem nuclei through a direct glutamatergic projection or by inhibiting the same structures via activation of local inhibitory GABAergic interneurons.

Figure 2
Neurocircuitry of addiction

The prefrontal cortex has a key role in cognitive functions involved in decision-making, including, but not limited to, memory, attention, emotion, working memory, outcome expectation, and planning. Impairment of decision-making is a key feature of addiction. Compulsive drug taking can also be viewed as an aberrant behavior resulting from poorly modulated decisions due to the inability to learn from the negative consequences of drug use. The prelimbic and infralimbic cortices in rats maintain stimulus representation during delays (working memory) and are critical for inhibition of behavior during extinction of a Pavlovian conditioned response to allow motivationally based decision-making (Morgan and LeDoux, 1999; Narayanan et al., 2006; Sakurai and Sugimoto, 1985). The prelimbic cortex is also important for detecting action-outcome contingencies and thus goal-directed actions (Balleine and Dickinson, 1998), whereas the infralimbic cortex may be important for learning stimulus-response associations or habit behavior (Killcross and Coutureau, 2003). Studies in humans have also demonstrated that the medial prefrontal cortex (including Brodman’s Areas 10, 32, and 25) is a critical structure in the neural system subserving risky decision-making (Damasio et al., 1994; Glimcher and Rustichini, 2004). Moreover, two systems can be identified: the ventral medial prefrontal cortex (which encodes decisions based on reward value) and the dorsal medial prefrontal cortex (which encodes decisions based on risk). The orbitofrontal cortex is critical in guiding behavior by signaling outcome expectancy when representation of the value of the expected outcome needs to be compared to an alternative response or needs to be held in memory (Schoenbaum et al., 2006).

Individual Differences

Individual differences in functioning of the prefrontal cortex and decision-making have been observed using behavioral testing, imaging, and neurochemistry techniques in humans and animals. Converging evidence shows that individual differences in prefrontal cortex activity and dopamine, acetylcholine, norepinephrine, and serotonin tone in the prefrontal cortex correlate with working memory, visual attention, and impulsivity in rats (for review, see Dalley et al., 2004). Imaging studies in humans have shown that individual differences in decision-making under risk correlate with activity in the ventromedial prefrontal cortex (Tom et al., 2007), and individual risk preference in a risky decision-making task negatively correlates with activity in the dorsal medial prefrontal cortex and positively correlates with activity in the ventral medial prefrontal cortex (Xue et al., 2009). Individuals with strong activation of the dorsal medial prefrontal cortex are more sensitive to risk and therefore less likely to make risky decisions, whereas individuals with strong activation of the ventromedial prefrontal cortex are more sensitive to reward and more likely to make risky choices (Xue et al., 2009). Individual differences in preferred strategies in a decision-making task (i.e., maximizing gain or minimizing losses) can be predicted by activation of the ventromedial prefrontal cortex and anterior insula, respectively (Venkatraman et al., 2009). Moreover, suppression of cortical excitability in the right dorsolateral prefrontal cortex using transcranial magnetic stimulation induces risky behavior (Knoch et al., 2006), and the interhemispheric balance of activity across the dorsolateral prefrontal cortex may mediate poor decision-making in individuals involved in risky behavior (Fecteau et al., 2007a; Fecteau et al., 2007b). These results suggest that individual vulnerability in the prefrontal cortex may lead to impaired decision-making and facilitate the initiation and maintenance of drug self-administration.

Loss of Control and the Prefrontal Cortex Module

Loss of control over drug use is a hallmark feature of drug addiction. Loss of control has been attributed to a dysfunction of the prefrontal cortex, based on neuroimaging studies in humans (London et al., 2000; Koob and Volkow 2010). Studies in rats show that loss of control over drug use is progressively established after extended access to self-administration (Ahmed and Koob, 1998; Deroche-Gamonet et al., 2004) and can be predicted by high impulsivity (Belin et al., 2008; Dalley et al., 2007a). Despite accumulating evidence that limited drug exposure induces neuronal changes in the prefrontal cortex (Ben-Shahar et al., 2007; Bowers et al., 2004; Crespo et al., 2002), there was little evidence, until recently, of long-lasting neuronal adaptations of the prefrontal cortex in animal models of the loss of control over drug use (Ben-Shahar et al., 2007; Ferrario et al., 2005; Seiwell et al., 2007). Moreover, recent reports demonstrated that at least in one model of loss of control (i.e., extended access to cocaine self-administration) there were no long-lasting impairments of prefrontal cortex cognitive function, such as response inhibition and sustained attention (Dalley et al., 2005; Dalley et al., 2007b). An alternative hypothesis is that extended access to cocaine produces deficits in other cognitive functions relevant to decision-making mediated by the prefrontal cortex that are operating under high cognitive demand and high-incentive conditions. A condition with high cognitive demand in this context refers to an experimental paradigm in which the cognitive processes necessary to solve a task reach their limit or capacity, whereas a high-incentive condition refers to an experimental paradigm that motivates a high degree of approach behavior due to the high attractiveness of the positive reinforcer. These conditions may particularly challenge the dorsomedial prefrontal cortex and orbitofrontal cortex. Moreover, working memory under a high-incentive condition has been shown to be a sensitive measure of the integrity of the prefrontal cortex (Krawczyk et al., 2007; Taylor et al., 2004).

Recent studies using animal models of compulsive drug use demonstrated that independent of any premorbid condition, a history of drug dependence induced persistent impairments in working memory (George et al., 2008) and sustained attention (Briand et al., 2008) that correlated with decreased density of neurons and oligodendrocytes but not astrocytes in the dorsomedial and orbital prefrontal cortex (George et al., 2008), dopamine D2 receptor mRNA in the medial and orbital prefrontal cortex, and D2 receptor protein in the medial prefrontal cortex (Briand et al., 2008). Additionally, long-lasting alterations in N-methyl-D-aspartate (NMDA) function have also been observed in these models (Ben-Shahar et al., 2009). Interestingly, working memory impairments were only observed under high cognitive demands and high incentive conditions, suggesting an imbalance between a hypoactive cognitive system that controls decision-making under high cognitive demands and an overactive incentive salience system (Bechara, 2005). An intriguing finding was that working memory impairments were not predicted by the amount of cocaine intake but rather by the relative increase in excessive cocaine intake compared with baseline self-administration under limited access conditions (George et al., 2008). These results suggested that prefrontal cortex dysfunction may not only be a simple consequence of drug use but may also contribute to a feed-forward mechanism in the loss of control over drug intake during the transition to drug dependence.

Loss of control and failure of self-regulation have been hypothesized to be significant contributory causes of many psychosocial pathologies, including depression, anxiety, chronic pain, posttraumatic stress disorder, eating disorders, gambling, obsessive compulsive disorders, and addiction (Baumeister, 2003). Considering the relative independence of these disorders and the differential involvement of the stress, pain, emotion, habits, decision-making, and reward systems in these disorders, it is likely that loss of control is not a unitary mechanism mediated by the prefrontal cortex. The heterogeneity of the prefrontal cortex and the segregated anatomical connections between the prefrontal cortex and the subcortical modules described above suggest that there may be multiple mechanisms of loss of control mediated by a failure of different subregions of the prefrontal cortex in controlling subcortical structures. Loss of control over stress, anxiety, reward, pain, habits, and decision-making during the different stages of addiction may lead to an increased risk of exposure to the drug, increased drug seeking and drug taking, increased relapse, and increased vulnerability to the transition to addiction.

Loss of Control Over Stress

Stress reactivity is highly dependent on whether the stress can be controlled. Stressful and aversive events are much less detrimental when the individual has control over the stress. Lack of control over stress may be a key factor in the development of anxiety, depression, posttraumatic stress disorder, and drug addiction (Amat et al., 2005). Many studies in animals have demonstrated the key role of brainstem nuclei, such as the dorsal raphe and locus coeruleus, in encoding the response to uncontrollable stress, but control over these stress circuits may be achieved by the prefrontal cortex through a glutamatergic projection from the infralimbic and prelimbic cortex onto local GABAergic neurons in the dorsal raphe leading to powerful inhibition of serotonin neurons (Amat et al., 2005). Pharmacological inhibition of the prelimbic and infralimbic cortices in rats blocks the inhibition of dorsal raphe neurons observed under controllable stress as well as the behavioral consequence of a controllable stress, demonstrating the role of the prefrontal cortex in the control of stress (Amat et al., 2005). Individual differences in the strength of the connection between the prefrontal cortex and brainstem nuclei involved in the autonomic, psychological, and behavioral responses to stress might represent a key mechanism whereby loss of control over stress may lead to increased vulnerability to anxiety, depression, posttraumatic stress disorder, and addiction. The medial prefrontal cortex in rats has a large number of glucocorticoid receptor-positive neurons that can bidirectionally control stress reactivity of the HPA axis through activation of the anterior cingulate, prelimbic, or infralimbic cortices (Diorio et al., 1993; Figueiredo et al., 2003a; Figueiredo et al., 2003b; Sullivan and Gratton, 1999). Lesions of the prelimbic cortex increase ACTH and corticosterone responses to stress, whereas lesions of the infralimbic cortex have the opposite effect. This differential control is attributed to differential projections of the prelimbic and infralimbic cortices to structures mediating either stress inhibition (ventrolateral preoptic area, dorsomedial hypothalamus, and peri PVN; Hurley, 1991; Sesack,et al., 1989) and stress activation (anterior BNST, MeA, CeA, and the nucleus of the tractus solitarus; Hurley et al., 1991; Takagishi and Chiba, 1991), respectively. Moreover, lesions of the prelimbic cortex enhance stress-induced c-fos expression and CRF mRNA expression in neurosecretory neurons (related to the HPA axis) of the PVN, whereas lesions of the infralimbic cortex had opposite effects but also increased Fos induction in autonomic neurons (sympathoadrenal) of the PVN (Radley et al., 2006). Altogether, these results suggest that the dorsal prefrontal (prelimbic) cortex exerts inhibitory control over the HPA axis, whereas the ventral prefrontal cortex exerts positive control over the HPA axis while exerting inhibitory control over central autonomic responses. With regard to the control of the prefrontal cortex over the dorsal raphe, the control of the prelimbic cortex over the PVN is mediated by a GABAergic relay in the anterior BNST (Radley et al., 2009). Moreover, loss of control over the HPA axis may contribute, through a feed-forward mechanism, to hyperactivation of CRF and norepinephrine systems in the extended amygdala to produce a negative emotional state that characterizes the withdrawal/negative affect stage of addiction.

Loss of Control Over Emotion

Emotion plays a key role in adaptation as well as influences cognitive function and behavioral responses in a variety of situations. Emotion is often viewed as a bottom-up modulator of decision-making, learning, and memory or even pain and perception, but often neglected is the fact that processing of emotional information can also be regulated via top-down mechanisms such as suppression or reappraisal (Johnstone et al., 2007; Ochsner et al., 2002, 2004; Phan et al., 2005). Such cognitive control may downregulate neural, physiological, and behavioral responses to emotion-eliciting stimuli (Jackson et al., 2000). It is well established that recruitment of a prefrontal network, including the dorsal and ventral prefrontal cortex and orbitofrontal cortex, is necessary to reduce activation of the amygdala by emotion-eliciting stimuli (Urry et al., 2006; Johnstone et al., 2007). Glutamatergic neurons in the ventral prefrontal cortex project to GABAergic inhibitory neurons in the capsular division of the CeA and inhibit the output of the CeA (Royer and Pare, 2002). Numerous studies have demonstrated that negative emotional states can lead to impulsive aggressive behavior, that important individual differences exist in the capacity of the individual to suppress aggressive thoughts, and that this effect is under the control of the prefrontal cortex, particularly the orbitofrontal cortex, ventromedial prefrontal cortex, and dorsolateral prefrontal cortex in humans (Davidson et al., 2000). One mechanism to explain the control of the prefrontal cortex over aggressive behavior is a powerful inhibition of the amygdala by the prefrontal cortex. Individuals who use more emotion regulation strategies, such as spontaneous reappraisal, have a lower negative emotional state and greater physical and psychological well being (Drabant et al., 2009). Individual differences in emotion regulation strategies and failure of control over emotion through hypofunction of the prefrontal cortex may represent a key neuropsychological mechanism responsible for increased vulnerability to anxiety, depression, and addiction.

Loss of Control Over Incentive Salience

Incentive salience represents a powerful mechanism that transforms neutral cues into powerful motivational magnets eliciting approach and guiding drug-related behavior (Robinson and Berridge, 1993). Intense incentive motivation attribution is considered to have a major role in different psychopathologies. Executive control over incentive salience is essential to maintain goal-directed behavior and flexibility of stimulus-response associations. The prefrontal cortex sends glutamatergic projections directly to mesocortical dopamine neurons in the VTA, exerting excitatory control on dopamine in the prefrontal cortex. Interestingly, the prefrontal cortex does not project directly onto mesolimbic dopamine neurons (Sesack and Carr, 2002). In contrast, prefrontal cortex neurons inhibit mesolimbic dopamine neurons through activation of GABAergic relay neurons in the VTA or nucleus accumbens (Carr and Sesack, 2000; Sesack and Pickel, 1992). Thus, the prefrontal cortex is in a good position to inhibit incentive salience and suppress conditioned behavior when a salient cue is presented to the subject. Consistent with this notion, it has been shown that appetitive stimuli activate the prefrontal cortex and that lesions of the prefrontal cortex induce impulsivity (Bechara et al., 2000; Jentsch and Taylor, 1999). Withdrawal from cocaine is associated with decreased prefrontal activity (Goldstein and Volkow, 2002) and extrasynaptic glutamate release as well as decreased dopamine release in the nucleus accumbens (Moussawi et al., 2009; Weiss et al., 1992). In contrast, cue-induced reinstatement of drug seeking-behavior induces a dramatic increase in prefrontal activity and glutamate release in the nucleus accumbens (Moussawi et al., 2009). The lower basal tone of the prefrontal-glutamatergic system associated with an exaggerated phasic response during relapse combined with reduced basal dopaminergic tone elicits a dramatic glutamatergic response that may mediate compulsive drug seeking by disinhibiting the control of behavior by reward-associated cues. Individual differences in prefrontal cortical control of incentive salience may represent a key mechanism to explain individual differences in the vulnerability to addiction, and excessive attribution of incentive salience to drug-related cues may lead to excessive drug intake, compulsive behavior, and relapse.

Loss of Control Over Pain

Self-regulation is a key mechanism involved in the control of both acute and chronic pain (Morley et al., 2005; Perez-Pareja et al., 2005; Solberg Nes et al., 2009). Control over pain is a key evolutionary advantage because it allows individuals to disengage from pain to fight or escape in the presence of injury. Converging evidence suggests that the prefrontal cortex mediates the control of pain. Electrical stimulation of the prefrontal cortex in rats induces antinociceptive effects (Cooper, 1975; Zhang et al., 1998), and pain stimuli and the expectancy of pain activate the prefrontal cortex (Casey et al., 1996; Iadarola et al., 1998; Peyron et al., 2000; Ploghaus et al., 1999). Key prefrontal structures involved in the control of pain are the anterior cingulate cortex and insular cortex. Both regions express a high number of opioid receptor-positive neurons and project to the amygdala and PAG, two downstream structures mediating opioid-mediated analgesia and whose activation leads to a suppression of pain-related behavior and the subjective effects of pain. The prefrontal cortex is also hypothesized to control the midbrain-thalamic-cingulate nociceptive pathway though descending fibers (Lorenz et al., 2003).

Loss of Control Over Habits and Decision-Making

The concept of self-control in decision-making is a complex cognitive process that requires parallel analysis of multiple sources of information, evaluation of outcomes, and selection of motor patterns. Loss of control in decision-making leads to unadapted behavior and is particularly prominent in situations with high incentives and high cognitive demand (George et al., 2008). Two key control mechanisms in decision-making are the ability to shift between different behavioral strategies, such as habit and goal-directed behavior, and attentional set-shifting to disengage from a once relevant stimulus dimension to a new set of stimuli that are potentially more relevant after a change in environmental conditions. The development of habit behavior is a particularly efficient strategy when environmental conditions do not change because habitual responses do not require evaluation of outcomes. Moreover, habit responses can be triggered by conditioned stimuli and require very limited cognitive resources, but inhibition of habits in favor of goal-directed behavior is critical when environmental conditions change to ensure adapted behaviors. A key structure mediating control over decision-making is the dorsolateral prefrontal cortex in humans and the dorsomedial prefrontal cortex in rodents (anterior cingulate cortex, prelimbic cortex; Dias-Ferreira et al., 2009; Hare et al., 2009; Birrell and Brown, 2000; Block et al., 2007; Dias et al., 1997; Ragozzino et al., 2003). Genetic variation at the serotonin transporter-linked polymorphism region has been associated with impaired amygdala control by the prefrontal cortex and may lead to poor decision-making (Roiser et al., 2009). Individual differences in the ability of the dorsolateral prefrontal cortex to modulate the ventromedial prefrontal cortex might be due to differences within the dorsolateral prefrontal cortex or to differences in connectivity between the dorsolateral prefrontal cortex and the subregions of the prefrontal cortex and the striatum. Particularly interesting for the control of decision-making is the fact that the prefrontal cortex contains a high number of GABAergic inhibitory interneurons and that pyramidal neurons can make both pyramidal-pyramidal connections and pyramidal-interneuron connections through extensive horizontal connections (Goldman-Rakic, 1995; Tanaka, 1999). Thus, pyramidal neurons can simultaneously activate and inactivate different corticocortical and corticostriatal circuits and facilitate behavioral flexibility by shifting attentional focus and selecting different motor patterns to adopt new strategies.

Conclusions

Important individual differences in the different stages of the addiction process, as well as in the vulnerability to the transition to addiction, have been observed in humans and animals. We reviewed studies demonstrating that the concept of self-regulation combined with the concept of modularity of cognitive function may help to understand individual differences in the vulnerability to drugs and to the transition to addiction. As explained above, there are important individual differences in the different stages of addiction as well as in key brain functions critical for the development of addiction, such as attention, decision-making, reward, emotion, pain, and stress (Crowley et al., 1998; de Wit et al., 1986; Deroche-Gamonet et al., 2004). Flexible, goal-directed behaviors require an adapted cognitive control system for organizing, selecting, and consolidating information resulting from the different modules into a coherent and unified experience (Treisman, 1996). Neuroanatomical, brain lesion, and site-specific pharmacological modulation studies of the prefrontal cortex have revealed the heterogeneity of the prefrontal cortex and the high functional specialization of its different subregions (Robbins, 2000). The prefrontal cortex and its different subregions target the main sources of all neurotransmitter systems and have been hypothesized to represent this cognitive control system (Baddeley, 1996; Robbins, 2000; Ridderinkhof et al., 2004, Goldman-Rakic, 1987).

We suggest that the concept of self-regulation, combined with the concept of modularity of cognitive function, may help to understand the neural basis of the individual differences in the vulnerability to drug addiction. Indeed, dysfunction of a specific subregion of the prefrontal cortex may lead to loss of control over a specific module, leading, for instance, to a sensitization of insentive salience in one individual and to a hyperreactivity of the stress system in another individual. Therefore, the failure of a specific module may differ from one individual to another and may represent a neuropsychobiological mechanism underlying individual differences in the vulnerability to drug addiction.

Several key potential modules may be identified, including the incentive salience mesolimbic dopamine system module, stress/HPA axis module, habit/striatum module, negative emotional state/extended amygdala module, pain/spinothalamocortical module, and the decision-making/prefrontal cortex module. Such modules are driven by bottom-up signals from both the external world and interoceptive signals and by top-down signals from higher-order system mediating cognitive control. It is important to note that the modules described in this review do not correspond fully to the concept originally defined by Jerry Fodor (1983). One of the essential defining features of a Fodorian module is functional autonomy; that is, its function is little, if any, controlled by top-down cognitive control. In contrast, the brain systems identified here are hypothesized to be under tight top-down control by the prefrontal cortex, at least initially before the transition to addiction. These systems are not modular in the strong sense defined by Fodor but begin to resemble to Fodorian modules only after the transition to addiction.

The present multi-system framework may be useful to better understand the different patterns of drug addiction across different individuals and different drugs. It can be hypothesized that individuals with increased sensitivity of the incentive salience mesolimbic dopamine system module and the habit/striatum system may be particularly vulnerable to cocaine and methampetamine abuse through an overvaluation of drug reward and drug-related cues during the binge/intoxication and preoccupation/anticipation stages Wise 2002; Jentsch and Taylor 1999). Individual differences in the function of the incentive salience mesolimbic dopamine system and the habit/striatum modules may be particularly important for craving-type 1 (or reward craving) defined as craving for the rewarding effects of drugs and usually induced by stimuli that have been paired with drug self-administration such as environmental cues, as opposed to craving-type 2 (or withdrawal relief craving) which is conceptualized as an excessive motivation for the drug to obtain relief from a state change characterized by anxiety and dysphoria after protracted abstinence (Heinz et al., 2003). Individual differences in the pain/spinothalamocortical module may be key for the transition to opiate and alcohol dependence. Decreased sensitivity of the pain system is associated with a higher vulnerability for opiate dependence (Lehofer et al., 1997), whereas hyperactivity of the pain system may predict cue-induced craving in abstinent opiate abusers (Ren et al., 2009). Moreover, considering the importance of the endogenous opiate system in alcoholism, it is likely that vulnerability of the pain/spinothalamocortical or spinoparabrachial module (Besson, 1999) might be a risk factor for the development of alcoholism and dependence on other drugs (Herz, 1997). Hyperactivity of the negative emotional state/extended amygdala module is associated with increased emotional pain and stress and might be a risk factor for drug use as a self-medication for emotional pain, dysphoria, and stress (Khantzian et al., 1997). Vulnerability in the pain/spinothalamocortical module may lead to increased physical and emotional pain during withdrawal and intense craving-type 2, thus contributing to the preponderant role of the withdrawal/negative affect stage that characterizes opiate and alcohol addiction. Increased reactivity of the stress/HPA axis module may be critical in the initiation of drug intake and for the maintenance of drugs that have little initial rewarding value, such as nicotine, as it potentiates the reinforcing effects of drugs (Piazza and Le Moal, 1998). Vulnerability of the stress/HPA axis and the negative emotional state/extended amygdala module may contribute to the different patterns of tobacco smoking behavior. Indeed, individuals who smoke regularly but who will always limit their tobacco intake (“chippers”) show no signs of withdrawal and report less stress and better stress coping responses than subjects dependent on tobacco (Shiffman, 1989) suggesting that hyperaactivity of the stress/HPA axis and the negative emotional state/extended amygdala module may underlie the differences between chippers and dependent smokers. Finally, hypoactivity of the decision-making/prefrontal cortex module may lead to a loss of control over drug intake despite negative consequence because of impaired inhibitory control and decision-making leading to choices of immediate rewards over delayed rewards (Goldstein and Volkow, 2002). Although the initial failure of a specific module might be specific to one stage of the addiction cycle and to a specific drug, in a given individual the transition to addiction is ultimately likely to be associated with a progressive and generalized loss of control over many, if not all, cognitive modules.

Acknowledgments

This is publication number 20330 from The Scripps Research Institute. This work was supported by National Institutes of Health grants DA04398, DA10072, DA04343, and DA023597 from the National Institute on Drug Abuse, AA08459 and AA06420 from the National Institute on Alcohol Abuse and Alcoholism, and the Pearson Center for Alcoholism and Addiction Research. The authors would like to thank Taryn Grieder and Prof. Michel Le Moal for helpful comments on the manuscript and Michael Arends for his editorial assistance.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

References

  • Ahmed SH, Koob GF. Transition from moderate to excessive drug intake: change in hedonic set point. Science. 1998;282:298–300. [PubMed]
  • Alheid GF, Heimer L. New perspectives in basal forebrain organization of special relevance for neuropsychiatric disorders: the striatopallidal, amygdaloid, and corticopetal components of substantia innominata. Neuroscience. 1988;27:1–39. [PubMed]
  • Amat J, Baratta MV, Paul E, Bland ST, Watkins LR, Maier SF. Medial prefrontal cortex determines how stressor controllability affects behavior and dorsal raphe nucleus. Nat Neurosci. 2005;8:365–371. [PubMed]
  • Anthony JC, Warner LA, Kessler RC. Comparative epidemiology of dependence on tobacco, alcohol, controlled substances, and inhalants, Basic findings from the National Comorbidity Survey. Experimental and Clinical Psychopharmacology. 1994;2:244–268.
  • Antoniou K, Papathanasiou G, Papalexi E, Hyphantis T, Nomikos GG, Spyraki C, Papadopoulou-Daifoti Z. Individual responses to novelty are associated with differences in behavioral and neurochemical profiles. Behav Brain Res. 2008;187:462–472. [PubMed]
  • Aytaclar S, Tarter RE, Kirisci L, Lu S. Association between hyperactivity and executive cognitive functioning in childhood and substance use in early adolescence. Journal of the American Academy of Child and Adolescent Psychiatry. 1999;38:172–178. [PubMed]
  • Baddeley A. The fractionation of working memory. Proc Natl Acad Sci U S A. 1996;93(24):13468–72. [PubMed]
  • Balleine BW, Dickinson A. Goal-directed instrumental action: contingency and incentive learning and their cortical substrates. Neuropharmacology. 1998;37:407–419. [PubMed]
  • Bannerman DM, Rawlins JN, McHugh SB, Deacon RM, Yee BK, Bast T, Zhang WN, Pothuizen HH, Feldon J. Regional dissociations within the hippocampus--memory and anxiety. Neurosci Biobehav Rev. 2004;28:273–283. [PubMed]
  • Barrot M, Abrous DN, Marinelli M, Rouge-Pont F, Le Moal M, Piazza PV. Influence of glucocorticoids on dopaminergic transmission in the rat dorsolateral striatum. Eur J Neurosci. 2001;13:812–818. [PubMed]
  • Barrot M, Marinelli M, Abrous DN, Rouge-Pont F, Le Moal M, Piazza PV. The dopaminergic hyper-responsiveness of the shell of the nucleus accumbens is hormone-dependent. Eur J Neurosci. 2000;12:973–979. [PubMed]
  • Baumeister RF, Heatherton TF, Tice DM, editors. Losing Control: How and Why People Fail at Self-Regulation. Academic Press; San Diego: 1994.
  • Baumeister RD, Heatherton TF, Tice DM. Losing Control. New York: Academic Press; 2003.
  • Beaver JD, Lawrence AD, Passamonti L, Calder AJ. Appetitive motivation predicts the neural response to facial signals of aggression. J Neurosci. 2008;28:2719–2725. [PubMed]
  • Bechara A. Decision making, impulse control and loss of willpower to resist drugs: a neurocognitive perspective. Nat Neurosci. 2005;8:1458–1463. [PubMed]
  • Bechara A, Tranel D, Damasio H. Characterization of the decision-making deficit of patients with ventromedial prefrontal cortex lesions. Brain. 2000;123 ( Pt 11):2189–2202. [PubMed]
  • Bechara A, Tranel D, Damasio H, Adolphs R, Rockland C, Damasio AR. Double dissociation of conditioning and declarative knowledge relative to the amygdala and hippocampus in humans. Science. 1995;269:1115–1118. [PubMed]
  • Belin D, Everitt BJ. Cocaine seeking habits depend upon dopamine-dependent serial connectivity linking the ventral with the dorsal striatum. Neuron. 2008;57:432–441. [PubMed]
  • Belin D, Jonkman S, Dickinson A, Robbins TW, Everitt BJ. Parallel and interactive learning processes within the basal ganglia: relevance for the understanding of addiction. Behav Brain Res. 2009;199:89–102. [PubMed]
  • Belin D, Mar AC, Dalley JW, Robbins TW, Everitt BJ. High impulsivity predicts the switch to compulsive cocaine-taking. Science. 2008;320:1352–1355. [PMC free article] [PubMed]
  • Ben-Shahar O, Keeley P, Cook M, Brake W, Joyce M, Nyffeler M, Heston R, Ettenberg A. Changes in levels of D1, D2, or NMDA receptors during withdrawal from brief or extended daily access to IV cocaine. Brain Res. 2007;1131:220–228. [PMC free article] [PubMed]
  • Ben-Shahar O, Obara I, Ary AW, Ma N, Mangiardi MA, Medina RL, Szumlinski KK. Extended daily access to cocaine results in distinct alterations in Homer 1b/c and NMDA receptor subunit expression within the medial prefrontal cortex. Synapse. 2009;63:598–609. [PMC free article] [PubMed]
  • Berridge KC, Robinson TE, Aldridge JW. Dissecting components of reward: ‘liking’, ‘wanting’, and learning. Curr Opin Pharmacol. 2009;9:65–73. [PMC free article] [PubMed]
  • Besson JM. The neurobiology of pain. The Lancet. 1999;353:1610–1615. [PubMed]
  • Birrell JM, Brown VJ. Medial frontal cortex mediates perceptual attentional set shifting in the rat. J Neurosci. 2000;20:4320–4324. [PubMed]
  • Bishop SJ, Duncan J, Lawrence AD. State anxiety modulation of the amygdala response to unattended threat-related stimuli. J Neurosci. 2004;24:10364–10368. [PubMed]
  • Block AE, Dhanji H, Thompson-Tardif SF, Floresco SB. Thalamic-prefrontal cortical-ventral striatal circuitry mediates dissociable components of strategy set shifting. Cereb Cortex. 2007;17:1625–1636. [PubMed]
  • Bowers MS, McFarland K, Lake RW, Peterson YK, Lapish CC, Gregory ML, Lanier SM, Kalivas PW. Activator of G protein signaling 3: a gatekeeper of cocaine sensitization and drug seeking. Neuron. 2004;42:269–281. [PMC free article] [PubMed]
  • Bradberry CW, Gruen RJ, Berridge CW, Roth RH. Individual differences in behavioral measures: correlations with nucleus accumbens dopamine measured by microdialysis. Pharmacol Biochem Behav. 1991;39:877–882. [PubMed]
  • Brands B, Blake J, Sproule B, Gourlay D, Busto U. Prescription opioid abuse in patients presenting for methadone maintenance treatment. Drug Alcohol Depend. 2004;73:199–207. [PubMed]
  • Briand LA, Flagel SB, Garcia-Fuster MJ, Watson SJ, Akil H, Sarter M, Robinson TE. Persistent alterations in cognitive function and prefrontal dopamine D2 receptors following extended, but not limited, access to self-administered cocaine. Neuropsychopharmacology. 2008;33:2969–2980. [PMC free article] [PubMed]
  • Cain ME, Denehy ED, Bardo MT. Individual differences in amphetamine self-administration: the role of the central nucleus of the amygdala. Neuropsychopharmacology. 2008;33:1149–1161. [PMC free article] [PubMed]
  • Canli T. Functional brain mapping of extraversion and neuroticism: learning from individual differences in emotion processing. J Pers. 2004;72:1105–1132. [PubMed]
  • Canli T, Gabrieli JD. Imaging gender differences in sexual arousal. Nat Neurosci. 2004;7:325–326. [PubMed]
  • Carboni E, Vacca C. Conditioned place preference: a simple method for investigating reinforcing properties in laboratory animals. In: Wang JQ, editor. Drugs of Abuse: Neurological Reviews and Protocols (series title: Methods in Molecular Medicine, vol. 79) Humana Press; Totowa NJ: 2003. pp. 481–498. [PubMed]
  • Carr DB, Sesack SR. Projections from the rat prefrontal cortex to the ventral tegmental area: target specificity in the synaptic associations with mesoaccumbens and mesocortical neurons. J Neurosci. 2000;20:3864–3873. [PubMed]
  • Casey KL. Concepts of pain mechanisms: the contribution of functional imaging of the human brain. Prog Brain Res. 2000;129:277–287. [PubMed]
  • Casey KL, Minoshima S, Morrow TJ, Koeppe RA. Comparison of human cerebral activation pattern during cutaneous warmth, heat pain, and deep cold pain. J Neurophysiol. 1996;76:571–581. [PubMed]
  • Cheng J, Feenstra MG. Individual differences in dopamine efflux in nucleus accumbens shell and core during instrumental learning. Learn Mem. 2006;13:168–177. [PubMed]
  • Childress AR, Mozley PD, McElgin W, Fitzgerald J, Reivich M, O’Brien CP. Limbic activation during cue-induced cocaine craving. Am J Psychiatry. 1999;156:11–18. [PMC free article] [PubMed]
  • Coccaro EF, McCloskey MS, Fitzgerald DA, Phan KL. Amygdala and orbitofrontal reactivity to social threat in individuals with impulsive aggression. Biol Psychiatry. 2007;62:168–178. [PubMed]
  • Coghill RC, McHaffie JG, Yen YF. Neural correlates of interindividual differences in the subjective experience of pain. Proc Natl Acad Sci U S A. 2003;100:8538–8542. [PubMed]
  • Cohen NJ, Squire LR. Preserved learning and retention of pattern-analyzing skill in amnesia: dissociation of knowing how and knowing that. Science. 1980;210(4466):207–10. [PubMed]
  • Cohen NJ, Squire LR. Preserved learning and retention of pattern-analyzing skill in amnesia: dissociation of knowing how and knowing that. Science. 1980;210:207–210. [PubMed]
  • Compton MA. Cold-pressor pain tolerance in opiate and cocaine abusers: correlates of drug type and use status. J Pain Symptom Manage. 1994;9:462–473. [PubMed]
  • Compton P, Estepa CA. Addiction in patients with chronic pain. Lippincotts Prim Care Pract. 2000;4:254–272. [PubMed]
  • Compton P, Charuvastra VC, Kintaudi K, Ling W. Pain responses in methadone-maintained opioid abusers. J Pain Symptom Manage. 2000;20:237–245. [PubMed]
  • Cooper SJ. Anaesthetisation of prefrontal cortex and response to noxious stimulation. Nature. 1975;254:439–440. [PubMed]
  • Crespo JA, Oliva JM, Ghasemzadeh MB, Kalivas PW, Ambrosio E. Neuroadaptive changes in NMDAR1 gene expression after extinction of cocaine self-administration. Ann N Y Acad Sci. 2002;965:78–91. [PubMed]
  • Crowley TJ, Macdonald MJ, Whitmore EA, Mikulich SK. Cannabis dependence, withdrawal, and reinforcing effects among adolescents with conduct symptoms and substance use disorders. Drug Alcohol Depend. 1998;50:27–37. [PubMed]
  • Dalley JW, Cardinal RN, Robbins TW. Prefrontal executive and cognitive functions in rodents: neural and neurochemical substrates. Neurosci Biobehav Rev. 2004;28:771–784. [PubMed]
  • Dalley JW, Fryer TD, Brichard L, Robinson ES, Theobald DE, Laane K, Pena Y, Murphy ER, Shah Y, Probst K, et al. Nucleus accumbens D2/3 receptors predict trait impulsivity and cocaine reinforcement. Science. 2007a;315:1267–1270. [PMC free article] [PubMed]
  • Dalley JW, Laane K, Pena Y, Theobald DE, Everitt BJ, Robbins TW. Attentional and motivational deficits in rats withdrawn from intravenous self-administration of cocaine or heroin. Psychopharmacology (Berl) 2005;182:579– 587. [PubMed]
  • Dalley JW, Laane K, Theobald DE, Pena Y, Bruce CC, Huszar AC, Wojcieszek M, Everitt BJ, Robbins TW. Enduring deficits in sustained visual attention during withdrawal of intravenous methylenedioxymethamphetamine self-administration in rats: results from a comparative study with d-amphetamine and methamphetamine. Neuropsychopharmacology. 2007b;32:1195–1206. [PubMed]
  • Damasio H, Grabowski T, Frank R, Galaburda AM, Damasio AR. The return of Phineas Gage: clues about the brain from the skull of a famous patient. Science. 1994;264:1102–1105. [PubMed]
  • Davidson RJ, Putnam KM, Larson CL. Dysfunction in the neural circuitry of emotion regulation--a possible prelude to violence. Science. 2000;289:591–594. [PubMed]
  • Dawes MA, Tarter RE, Kirisci L. Behavioral selfregulation: correlates and 2 year follow-ups for boys at risk for substance abuse. Drug and Alcohol Dependence. 1997;45:165–176. [PubMed]
  • de Wit H, Uhlenhuth EH, Johanson CE. Individual differences in the reinforcing and subjective effects of amphetamine and diazepam. Drug Alcohol Depend. 1986;16:341–360. [PubMed]
  • Denoble U, Begleiter H. Response suppression on a mixed schedule of reinforcement during alcohol withdrawal. Pharmacology Biochemistry and Behavior. 1976;5:227–229. [PubMed]
  • Deroche-Gamonet V, Belin D, Piazza PV. Evidence for addiction-like behavior in the rat. Science. 2004;305:1014–1017. [PubMed]
  • Dias-Ferreira E, Sousa JC, Melo I, Morgado P, Mesquita AR, Cerqueira JJ, Costa RM, Sousa N. Chronic stress causes frontostriatal reorganization and affects decision-making. Science. 2009;325:621–625. [PubMed]
  • Dias R, Robbins TW, Roberts AC. Dissociable forms of inhibitory control within prefrontal cortex with an analog of the Wisconsin Card Sort Test: restriction to novel situations and independence from “on-line” processing. J Neurosci. 1997;17:9285–9297. [PubMed]
  • Dietz DM, Dietz KC, Moore S, Ouimet CC, Kabbaj M. Repeated social defeat stress-induced sensitization to the locomotor activating effects of d-amphetamine: role of individual differences. Psychopharmacology (Berl) 2008;198:51–62. [PubMed]
  • Diorio D, Viau V, Meaney MJ. The role of the medial prefrontal cortex (cingulate gyrus) in the regulation of hypothalamic-pituitary-adrenal responses to stress. J Neurosci. 1993;13:3839–3847. [PubMed]
  • Dobi A, Margolis EB, Wang HL, Harvey BK, Morales M. Glutamatergic and nonglutamatergic neurons of the ventral tegmental area establish local synaptic contacts with dopaminergic and nondopaminergic neurons. J Neurosci. 2010;30:218–229. [PMC free article] [PubMed]
  • Doverty M, Somogyi AA, White JM, Bochner F, Beare CH, Menelaou A, Ling W. Methadone maintenance patients are cross-tolerant to the antinociceptive effects of morphine. Pain. 2001a;93:155–163. [PubMed]
  • Doverty M, White JM, Somogyi AA, Bochner F, Ali R, Ling W. Hyperalgesic responses in methadone maintenance patients. Pain. 2001b;90:91–96. [PubMed]
  • Drabant EM, McRae K, Manuck SB, Hariri AR, Gross JJ. Individual differences in typical reappraisal use predict amygdala and prefrontal responses. Biol Psychiatry. 2009;65:367–373. [PMC free article] [PubMed]
  • Druhan JP, Fibiger HC, Phillips AG. Amphetamine-like stimulus properties produced by electrical stimulation of reward sites in the ventral tegmental area. Behav Brain Res. 1990;38:175–184. [PubMed]
  • Epping-Jordan MP, Watkins SS, Koob GF, Markou A. Dramatic decreases in brain reward function during nicotine withdrawal. Nature. 1998;393:76–79. [PubMed]
  • Erb S, Stewart J. A role for the bed nucleus of the stria terminalis, but not the amygdala, in the effects of corticotropin-releasing factor on stress-induced reinstatement of cocaine seeking. J Neurosci. 1999;19:RC35. [PubMed]
  • Erb S, Hitchcott PK, Rajabi H, Mueller D, Shaham Y, Stewart J. Alpha-2 adrenergic receptor agonists block stress-induced reinstatement of cocaine seeking. Neuropsychopharmacology. 2000;23:138–150. [PubMed]
  • Erb S, Shaham Y, Stewart J. Stress reinstates cocaine-seeking behavior after prolonged extinction and a drug-free period. Psychopharmacology (Berl) 1996;128:408–412. [PubMed]
  • Erb S, Shaham Y, Stewart J. The role of corticotropin-releasing factor and corticosterone in stress- and cocaine-induced relapse to cocaine seeking in rats. J Neurosci. 1998;18:5529–5536. [PubMed]
  • Etkin A, Klemenhagen KC, Dudman JT, Rogan MT, Hen R, Kandel ER, Hirsch J. Individual differences in trait anxiety predict the response of the basolateral amygdala to unconsciously processed fearful faces. Neuron. 2004;44:1043–1055. [PubMed]
  • Everitt BJ, Robbins TW. Neural systems of reinforcement for drug addiction: from actions to habits to compulsion. Nat Neurosci. 2005;8:1481–1489. [PubMed]
    Exp Physiol. 87(2):251–8. [PubMed]
  • Fecteau S, Knoch D, Fregni F, Sultani N, Boggio P, Pascual-Leone A. Diminishing risk-taking behavior by modulating activity in the prefrontal cortex: a direct current stimulation study. J Neurosci. 2007a;27:12500–12505. [PubMed]
  • Fecteau S, Pascual-Leone A, Zald DH, Liguori P, Theoret H, Boggio PS, Fregni F. Activation of prefrontal cortex by transcranial direct current stimulation reduces appetite for risk during ambiguous decision making. J Neurosci. 2007b;27:6212–6218. [PubMed]
  • Ferrario CR, Gorny G, Crombag HS, Li Y, Kolb B, Robinson TE. Neural and behavioral plasticity associated with the transition from controlled to escalated cocaine use. Biol Psychiatry. 2005;58:751–759. [PubMed]
  • Fields H. State-dependent opioid control of pain. Nat Rev Neurosci. 2004;5:565–575. [PubMed]
  • Fields HL. Pain modulation: expectation, opioid analgesia and virtual pain. Prog Brain Res. 2000;122:245–253. [PubMed]
  • Figueiredo HF, Bodie BL, Tauchi M, Dolgas CM, Herman JP. Stress integration after acute and chronic predator stress: differential activation of central stress circuitry and sensitization of the hypothalamo-pituitary-adrenocortical axis. Endocrinology. 2003a;144:5249–5258. [PubMed]
  • Figueiredo HF, Bruestle A, Bodie B, Dolgas CM, Herman JP. The medial prefrontal cortex differentially regulates stress-induced c-fos expression in the forebrain depending on type of stressor. Eur J Neurosci. 2003b;18:2357–2364. [PubMed]
  • Fillingim RB, King CD, Ribeiro-Dasilva MC, Rahim-Williams B, Riley JL., 3rd Sex, gender, and pain: a review of recent clinical and experimental findings. J Pain. 2009;10:447–485. [PMC free article] [PubMed]
  • Flagel SB, Watson SJ, Akil H, Robinson TE. Individual differences in the attribution of incentive salience to a reward-related cue: influence on cocaine sensitization. Behav Brain Res. 2008;186(1):48–56. [PMC free article] [PubMed]
  • Flagel SB, Watson SJ, Akil H, Robinson TE. Individual differences in the attribution of incentive salience to a reward-related cue: influence on cocaine sensitization. Behav Brain Res. 2008;186:48–56. [PMC free article] [PubMed]
  • Fodor J. The Modularity of Mind (Cambridge) 1983
  • Gabbott PL, Warner TA, Jays PR, Salway P, Busby SJ. Prefrontal cortex in the rat: projections to subcortical autonomic, motor, and limbic centers. J Comp Neurol. 2005;492(2):145–77. [PubMed]
  • Gabrieli JDE, Fleischman DA, Keane MM, Reminger SL, Morrell F. Double dissociation between memory systems underlying explicit and implicit memory in the human brain. Psycholog Sci. 1995;6:76–82.
  • Gauriau C, Bernard JF. Pain pathways and parabrachial circuits in the rat 2002 [PubMed]
  • Gazzaniga MS, editor. The New Cognitive Neurosciences. MIT Press; Cambridge, Massachusetts: 2000.
  • Gellert VF, Sparber SB. A comparison of the effects of naloxone upon body weight loss and suppression of fixed-ratio operant behavior in morphine-dependent rats. Journal of Pharmacology and Experimental Therapeutics. 1977;201:44–54. [PubMed]
  • George O, Ghozland S, Azar MR, Cottone P, Zorrilla EP, Parsons LH, O’Dell LE, Richardson HN, Koob GF. CRF-CRF1 system activation mediates withdrawal-induced increases in nicotine self-administration in nicotine-dependent rats. Proc Natl Acad Sci U S A. 2007;104:17198–17203. [PubMed]
  • George O, Mandyam CD, Wee S, Koob GF. Extended access to cocaine self-administration produces long-lasting prefrontal cortex-dependent working memory impairments. Neuropsychopharmacology. 2008;33:2474–2482. [PMC free article] [PubMed]
  • Gerfen CR. The neostriatal mosaic: multiple levels of compartmental organization. Trends Neurosci. 1992;15:133–139. [PubMed]
  • Giancola PR, Moss HB, Martin CS, Kirisci L, Tarter RE. Executive cognitive functioning predicts reactive aggression in boys at high risk for substance abuse: a prospective study. Alcoholism: Clinical and Experimental Research. 1996a;20:740–744. [PubMed]
  • Giancola PR, Zeichner A, Yarnell JE, Dickson KE. Relation between executive cognitive functioning and the adverse consequences of alcohol use in social drinkers. Alcoholism: Clinical and Experimental Research. 1996b;20:1094–1098. [PubMed]
  • Gibson SJ, Helme RD. Age-related differences in pain perception and report. Clin Geriatr Med. 2001;17:433–456. v–vi. [PubMed]
  • Glimcher PW, Rustichini A. Neuroeconomics: the consilience of brain and decision. Science. 2004;306:447–452. [PubMed]
  • Goldman-Rakic PS. Circuitry of primate prefrontal cortex and the regulation of behavior by representational memory. In: Plum E, Mountcastle V, editors. Handbook of Physiology. Vol. 5. American Physiological Society; Bethesda, MD: 1987. pp. 373–417.
  • Goldman-Rakic PS. Cellular basis of working memory. Neuron. 1995;14:477–485. [PubMed]
  • Goldstein RZ, Volkow ND. Drug addiction and its underlying neurobiological basis: neuroimaging evidence for the involvement of the frontal cortex. Am J Psychiatry. 2002;159:1642–1652. [PMC free article] [PubMed]
  • Gray TS, Piechowski RA, Yracheta JM, Rittenhouse PA, Bethea CL, Van de Kar LD. Ibotenic acid lesions in the bed nucleus of the stria terminalis attenuate conditioned stress-induced increases in prolactin, ACTH and corticosterone. Neuroendocrinology. 1993;57:517–524. [PubMed]
  • Groenewegen HJ, Wright CI, Uylings HB. The anatomical relationships of the prefrontal cortex with limbic structures and the basal ganglia. J Psychopharmacol. 1997;11:99–106. [PubMed]
  • Hamann S, Canli T. Individual differences in emotion processing. Curr Opin Neurobiol. 2004;14:233–238. [PubMed]
  • Han JS, Neugebauer V. Synaptic plasticity in the amygdala in a visceral pain model in rats. Neurosci Lett. 2004;361:254–257. [PubMed]
  • Hare TA, Camerer CF, Rangel A. Self-control in decision-making involves modulation of the vmPFC valuation system. Science. 2009;324:646–648. [PubMed]
  • Heinz A, Löber S, Georgi A, Wrase J, Hermann D, Rey ER, Wellek S, Mann K. Reward craving and withdrawal relief craving: assessment of different motivational pathways to alcohol intake. Alcohol Alcohol. 2003;38:35–39. [PubMed]
  • Herman JP, Prewitt CM, Cullinan WE. Neuronal circuit regulation of the hypothalamo-pituitary-adrenocortical stress axis. Crit Rev Neurobiol. 1996;10(3–4):371–94. [PubMed]
  • Herman JP, Prewitt CM, Cullinan WE. Neuronal circuit regulation of the hypothalamo-pituitary-adrenocortical stress axis. Crit Rev Neurobiol. 1996;10:371–394. [PubMed]
  • Herz A. Endogenous opioid systems and alcohol addiction. Psychopharmacology. 1997;129:99–111. [PubMed]
  • Holtzman SG. Discriminative stimulus effects of drugs: relationship to potential for abuse. In: Adler MW, Cowan A, editors. Testing and Evaluation of Drugs of Abuse (series title: Modern Methods in Pharmacology, vol. 6) Wiley; New York: 1990. pp. 193–210.
  • Hooks MS, Colvin AC, Juncos JL, Justice JB., Jr Individual differences in basal and cocaine-stimulated extracellular dopamine in the nucleus accumbens using quantitative microdialysis. Brain Res. 1992;587:306–312. [PubMed]
  • Hurley KM, Herbert H, Moga MM, Saper CB. Efferent projections of the infralimbic cortex of the rat. J Comp Neurol. 1991;308:249–276. [PubMed]
  • Iadarola MJ, Berman KF, Zeffiro TA, Byas-Smith MG, Gracely RH, Max MB, Bennett GJ. Neural activation during acute capsaicin-evoked pain and allodynia assessed with PET. Brain. 1998;121 ( Pt 5):931–947. [PubMed]
  • Imaki T, Nahan JL, Rivier C, Sawchenko PE, Vale W. Differential regulation of corticotropin-releasing factor mRNA in rat brain regions by glucocorticoids and stress. J Neurosci. 1991;11:585–599. [PubMed]
  • Jackson DC, Malmstadt JR, Larson CL, Davidson RJ. Suppression and enhancement of emotional responses to unpleasant pictures. Psychophysiology. 2000;37(4):515–22. [PubMed]
  • Jentsch JD, Taylor JR. Impulsivity resulting from frontostriatal dysfunction in drug abuse: implications for the control of behavior by reward-related stimuli. Psychopharmacology (Berl) 1999;146:373–390. [PubMed]
  • Johnstone T, van Reekum CM, Urry HL, Kalin NH, Davidson RJ. Failure to regulate: counterproductive recruitment of top-down prefrontal-subcortical circuitry in major depression. J Neurosci. 2007;27(33):8877–84. [PubMed]
  • Kalivas PW. Neurotransmitter regulation of dopamine neurons in the ventral tegmental area. Brain Res Brain Res Rev. 1993;18(1):75–113. [PubMed]
  • Kalivas PW. Neurotransmitter regulation of dopamine neurons in the ventral tegmental area. Brain Res Brain Res Rev. 1993;18:75–113. [PubMed]
  • Kassel JD, Shiffman S, Gnys M, Paty J, Zettler-Segal M. Psychosocial and personality differences in chippers and regular smokers. Addict Behav. 1994;19:565–575. [PubMed]
  • Katz JL, Goldberg SR. Second-order schedules of drug injection: implications for understanding reinforcing effects of abused drugs. Advances in Substance Abuse. 1991;4:205–223.
  • Khantzian EJ. The self-medication hypothesis of substance use disorders: a reconsideration and recent applications. Harvard Review of Psychiatry. 1997;4:231–244. [PubMed]
  • Killcross S, Coutureau E. Coordination of actions and habits in the medial prefrontal cortex of rats. Cereb Cortex. 2003;13:400–408. [PubMed]
  • Kilts CD, Schweitzer JB, Quinn CK, Gross RE, Faber TL, Muhammad F, Ely TD, Hoffman JM, Drexler KP. Neural activity related to drug craving in cocaine addiction. Arch Gen Psychiatry. 2001;58:334–341. [PubMed]
  • Knoch D, Gianotti LR, Pascual-Leone A, Treyer V, Regard M, Hohmann M, Brugger P. Disruption of right prefrontal cortex by low-frequency repetitive transcranial magnetic stimulation induces risk-taking behavior. J Neurosci. 2006;26:6469–6472. [PubMed]
  • Koob GF, Le Moal M. Neurobiology of addiction. China: Elsevier; 2006.
  • Koob GF. Animal models of craving for ethanol. Addiction. 2000;95(Suppl 2):S73–81. [PubMed]
  • Koob GF, Le Moal M. Drug abuse: hedonic homeostatic dysregulation. Science. 1997;278:52–58. [PubMed]
  • Koob GF, Le Moal M. Plasticity of reward neurocircuitry and the ‘dark side’ of drug addiction. Nat Neurosci. 2005;8:1442–1444. [PubMed]
  • Koob GF, Le Moal M. Addiction and the Brain Antireward System. Annual Review of Psychology. 2008;59:29–53. [PubMed]
  • Koob GF, Volkow ND. Neurocircuitry of addiction. Neuropsychopharmacology. 2010;35:217–238. [erratum: 35, 1051] [PMC free article] [PubMed]
  • Koob GF, Sanna PP, Bloom FE. Neuroscience of addiction. Neuron. 1998;21:467–476. [PubMed]
  • Kornetsky C, Esposito RU. Euphorigenic drugs: Effects on the reward pathways of the brain. Federation Proceedings. 1979;38:2473–2476. [PubMed]
  • Krawczyk DC, Gazzaley A, D’Esposito M. Reward modulation of prefrontal and visual association cortex during an incentive working memory task. Brain Res. 2007;1141:168–177. [PubMed]
  • Laulin JP, Celerier E, Larcher A, Le Moal M, Simonnet G. Opiate tolerance to daily heroin administration: An apparent phenomenon associated with enhanced pain sensitivity. Neuroscience. 1999;89:631–636. [PubMed]
  • Le AD, Harding S, Juzytsch W, Fletcher PJ, Shaham Y. The role of corticotropin-releasing factor in the median raphe nucleus in relapse to alcohol. J Neurosci. 2002;22:7844–7849. [PubMed]
  • Le AD, Harding S, Juzytsch W, Watchus J, Shalev U, Shaham Y. The role of corticotrophin-releasing factor in stress-induced relapse to alcohol-seeking behavior in rats. Psychopharmacology (Berl) 2000;150:317–324. [PubMed]
  • LeDoux JE. Emotion circuits in the brain. Annu Rev Neurosci. 2000;23:155–184. [PubMed]
  • Leyton M, Boileau I, Benkelfat C, Diksic M, Baker G, Dagher A. Amphetamine-induced increases in extracellular dopamine, drug wanting, and novelty seeking: a PET/[11C]raclopride study in healthy men. Neuropsychopharmacology. 2002;27:1027–1035. [PubMed]
    Life Sci. 62(22):1985–98. [PubMed]
  • Lim KO, Choi SJ, Pomara N, Wolkin A, Rotrosen JP. Reduced frontal white matter integrity in cocaine dependence: a controlled diffusion tensor imaging study. Biological Psychiatry. 2002;51:890–895. [PubMed]
  • Linfoot I, Gray M, Bingham B, Williamson M, Pinel JP, Viau V. Naturally occurring variations in defensive burying behavior are associated with differences in vasopressin, oxytocin, and androgen receptors in the male rat. Prog Neuropsychopharmacol Biol Psychiatry 2009 [PubMed]
  • London ED, Ernst M, Grant S, Bonson K, Weinstein A. Orbitofrontal cortex and human drug abuse: functional imaging. Cereb Cortex. 2000;10:334–342. [PubMed]
  • Lorenz J, Minoshima S, Casey KL. Keeping pain out of mind: the role of the dorsolateral prefrontal cortex in pain modulation. Brain. 2003;126:1079–1091. [PubMed]
  • Lucas LR, Angulo JA, Le Moal M, McEwen BS, Piazza PV. Neurochemical characterization of individual vulnerability to addictive drugs in rats. Eur J Neurosci. 1998;10:3153–3163. [PubMed]
  • Makino S, Gold PW, Schulkin J. Corticosterone effects on corticotropin-releasing hormone mRNA in the central nucleus of the amygdala and the parvocellular region of the paraventricular nucleus of the hypothalamus. Brain Res. 1994;640:105–112. [PubMed]
  • Makris N, Gasic GP, Seidman LJ, Goldstein JM, Gastfriend DR, Elman I, Albaugh MD, Hodge SM, Ziegler DA, Sheahan FS, et al. Decreased absolute amygdala volume in cocaine addicts. Neuron. 2004;44:729–740. [PubMed]
  • Mantsch JR, Saphier D, Goeders NE. Corticosterone facilitates the acquisition of cocaine self-administration in rats: opposite effects of the type II glucocorticoid receptor agonist dexamethasone. J Pharmacol Exp Ther. 1998;287:72–80. [PubMed]
  • Mantsch JR, Yuferov V, Mathieu-Kia AM, Ho A, Kreek MJ. Neuroendocrine alterations in a high-dose, extended-access rat self-administration model of escalating cocaine use. Psychoneuroendocrinology. 2003;28:836–862. [PubMed]
  • Marinelli M, White FJ. Enhanced vulnerability to cocaine self-administration is associated with elevated impulse activity of midbrain dopamine neurons. J Neurosci. 2000;20:8876–8885. [PubMed]
  • Martin-Fardon R, Ciccocioppo R, Massi M, Weiss F. Nociceptin prevents stress-induced ethanol- but not cocaine-seeking behavior in rats. Neuroreport. 2000;11:1939–1943. [PubMed]
  • Martin TJ, Kim SA, Buechler NL, Porreca F, Eisenach JC. Opioid self-administration in the nerve-injured rat: relevance of antiallodynic effects to drug consumption and effects of intrathecal analgesics. Anesthesiology. 2007;106:312–322. [PubMed]
  • Mather M, Canli T, English T, Whitfield S, Wais P, Ochsner K, Gabrieli JD, Carstensen LL. Amygdala responses to emotionally valenced stimuli in older and younger adults. Psychol Sci. 2004;15:259–263. [PubMed]
  • Miller NS, Gold MS. Opiate prescription medication dependence and pain perceptions. J Addict Dis. 2007;26(Suppl 1):65–71. [PubMed]
  • Mishkin M. Perseveration of central sets after frontal lesions in man. In: Alkert JMWK, editor. The frontal granular cortex and behavior. New York: McGraw-Hill; 1964. pp. 219–294.
  • Morgan MA, LeDoux JE. Contribution of ventrolateral prefrontal cortex to the acquisition and extinction of conditioned fear in rats. Neurobiol Learn Mem. 1999;72:244–251. [PubMed]
  • Morley S, Davies C, Barton S. Possible selves in chronic pain: self-pain enmeshment, adjustment and acceptance. Pain. 2005;115:84–94. [PubMed]
  • Moussawi K, Pacchioni A, Moran M, Olive MF, Gass JT, Lavin A, Kalivas PW. N-Acetylcysteine reverses cocaine-induced metaplasticity. Nat Neurosci. 2009;12:182–189. [PMC free article] [PubMed]
  • Nader MA, Morgan D, Gage HD, Nader SH, Calhoun TL, Buchheimer N, Ehrenkaufer R, Mach RH. PET imaging of dopamine D2 receptors during chronic cocaine self-administration in monkeys. Nat Neurosci. 2006;9:1050–1056. [PubMed]
  • Narayanan NS, Horst NK, Laubach M. Reversible inactivations of rat medial prefrontal cortex impair the ability to wait for a stimulus. Neuroscience. 2006;139:865–876. [PubMed]
  • Nestler EJ. Molecular basis of long-term plasticity underlying addiction. Nat Rev Neurosci. 2001;2:119–128. [PubMed]
  • Nielsen CS, Staud R, Price DD. Individual differences in pain sensitivity: measurement, causation, and consequences. J Pain. 2009;10:231–237. [PubMed]
  • O’Brien CPER, Terns JN. Classical conditioning in human opioid dependence. In: Goldeberg SR, editor. Behavioral analysis of drug dependence S.I. New York: Academic; 1986. pp. 329–335.
  • Oades RD, Halliday GM. Ventral tegmental (A10) system: Neurobiology. 1. Anatomy and connectivity. Brain Res. 1987;434:117–165. [PubMed]
  • Ochsner KN, Bunge SA, Gross JJ, Gabrieli JD. Rethinking feelings: an FMRI study of the cognitive regulation of emotion. J Cogn Neurosci. 2002;14(8):1215–29. [PubMed]
  • Oswald LM, Wong DF, McCaul M, Zhou Y, Kuwabara H, Choi L, Brasic J, Wand GS. Relationships among ventral striatal dopamine release, cortisol secretion, and subjective responses to amphetamine. Neuropsychopharmacology. 2005;30:821–832. [PubMed]
  • Passamonti L, Rowe JB, Ewbank M, Hampshire A, Keane J, Calder AJ. Connectivity from the ventral anterior cingulate to the amygdala is modulated by appetitive motivation in response to facial signals of aggression. Neuroimage. 2008;43:562–570. [PMC free article] [PubMed]
  • Perez-Pareja J, Borras C, Sese A, Palmer A. Pain perception and fibromyalgia. Actas Esp Psiquiatr. 2005;33:303–310. [PubMed]
  • Peyron R, Laurent B, Garcia-Larrea L. Functional imaging of brain responses to pain. A review and meta-analysis (2000) Neurophysiol Clin. 2000;30:263–288. [PubMed]
  • Phan KL, Fitzgerald DA, Nathan PJ, Moore GJ, Uhde TW, Tancer ME. Neural substrates for voluntary suppression of negative affect: a functional magnetic resonance imaging study. Biol Psychiatry. 2005;57(3):210–9. [PubMed]
  • Phan KL, Taylor SF, Welsh RC, Decker LR, Noll DC, Nichols TE, Britton JC, Liberzon I. Activation of the medial prefrontal cortex and extended amygdala by individual ratings of emotional arousal: a fMRI study. Biol Psychiatry. 2003;53:211–215. [PubMed]
  • Piazza PV, Le Moal ML. Pathophysiological basis of vulnerability to drug abuse: Role of an interaction between stress, glucocorticoids, and dopaminergic neurons. Annual Review of Pharmacology and Toxicology. 1996;36:359–378. [PubMed]
  • Piazza PV, Le Moal M. The role of stress in drug self-administration. Trends Pharmacol Sci. 1998;19:67–74. [PubMed]
  • Piazza PV, Deminiere JM, Le Moal M, Simon H. Factors that predict individual vulnerability to amphetamine self-administration. Science. 1989;245:1511–1513. [PubMed]
  • Piazza PV, Maccari S, Deminiere JM, Le Moal M, Mormede P, Simon H. Corticosterone levels determine individual vulnerability to amphetamine self-administration. Proc Natl Acad Sci U S A. 1991a;88:2088–2092. [PubMed]
  • Piazza PV, Rouge-Pont F, Deminiere JM, Kharoubi M, Le Moal M, Simon H. Dopaminergic activity is reduced in the prefrontal cortex and increased in the nucleus accumbens of rats predisposed to develop amphetamine self-administration. Brain Res. 1991b;567:169–174. [PubMed]
  • Piazza PV, Rouge-Pont F, Deroche V, Maccari S, Simon H, Le Moal M. Glucocorticoids have state-dependent stimulant effects on the mesencephalic dopaminergic transmission. Proc Natl Acad Sci U S A. 1996;93:8716–8720. [PubMed]
  • Ploghaus A, Tracey I, Gati JS, Clare S, Menon RS, Matthews PM, Rawlins JN. Dissociating pain from its anticipation in the human brain. Science. 1999;284:1979–1981. [PubMed]
  • Ploner M, Freund HJ, Schnitzler A. Pain affect without pain sensation in a patient with a postcentral lesion. Pain. 1999;81:211–214. [PubMed]
  • Porro CA. Functional imaging and pain: behavior, perception, and modulation. Neuroscientist. 2003;9:354–369. [PubMed]
  • Pribram KH, Mishkin M. Analysis of the effects of frontal lesions in monkey. III. Object alternation. Journal of Comparative Physiology and Psychology. 1956:41–45. [PubMed]
  • Price DD. Psychological and Neural Mechanisms of the Affective Dimension of Pain. Science. 2000;288:1769–1772. [PubMed]
  • Oades RD, Hallidaya GM. Ventral tegmental (A10) system: neurobiology. 1. Anatomy and connectivity. Brain Research Reviews. 1987;12(2):117–165. [PubMed]
  • Radley JJ, Arias CM, Sawchenko PE. Regional differentiation of the medial prefrontal cortex in regulating adaptive responses to acute emotional stress. J Neurosci. 2006;26:12967–12976. [PubMed]
  • Radley JJ, Gosselink KL, Sawchenko PE. A discrete GABAergic relay mediates medial prefrontal cortical inhibition of the neuroendocrine stress response. J Neurosci. 2009;29:7330–7340. [PMC free article] [PubMed]
  • Ragozzino ME, Kim J, Hassert D, Minniti N, Kiang C. The contribution of the rat prelimbic-infralimbic areas to different forms of task switching. Behav Neurosci. 2003;117:1054–1065. [PubMed]
  • Rao SG, Williams GV, Goldman-Rakic PS. Destruction and creation of spatial tuning by disinhibition: GABA(A) blockade of prefrontal cortical neurons engaged by working memory. J Neurosci. 2000;20:485–494. [PubMed]
  • Redish AD, Jensen S, Johnson A. A unified framework for addiction: vulnerabilities in the decision process. Behav Brain Sci. 2008;31(4):415–37. discussion 437–87. [PMC free article] [PubMed]
  • Reynolds SM, Zahm DS. Specificity in the projections of prefrontal and insular cortex to ventral striatopallidum and the extended amygdala. J Neurosci. 2005;25:11757–11767. [PubMed]
  • Ridderinkhof KR, Ullsperger M, Crone EA, Nieuwenhuis S. The role of the medial frontal cortex in cognitive control. Science. 2004;306(5695):443–7. [PubMed]
  • Robbins TW. From arousal to cognition: the integrative position of the prefrontal cortex. Prog Brain Res. 2000;126:469–83. [PubMed]
  • Roberts AJ, Heyser CJ, Cole M, Griffin P, Koob GF. Excessive ethanol drinking following a history of dependence: Animal model of allostasis. Neuropsychopharmacology. 2000a;22:581–594. [PubMed]
  • Robinson TE, Berridge KC. The neural basis of drug craving: an incentive-sensitization theory of addiction. Brain Res Brain Res Rev. 1993;18:247–291. [PubMed]
  • Roiser JP, de Martino B, Tan GC, Kumaran D, Seymour B, Wood NW, Dolan RJ. A genetically mediated bias in decision making driven by failure of amygdala control. J Neurosci. 2009;29:5985–5991. [PMC free article] [PubMed]
  • Rouge-Pont F, Deroche V, Le Moal M, Piazza PV. Individual differences in stress-induced dopamine release in the nucleus accumbens are influenced by corticosterone. Eur J Neurosci. 1998;10:3903–3907. [PubMed]
  • Royer S, Pare D. Bidirectional synaptic plasticity in intercalated amygdala neurons and the extinction of conditioned fear responses. Neuroscience. 2002;115:455–462. [PubMed]
  • Sakurai Y, Sugimoto S. Effects of lesions of prefrontal cortex and dorsomedial thalamus on delayed go/no-go alternation in rats. Behav Brain Res. 1985;17:213–219. [PubMed]
  • Salomons TV, Johnstone T, Backonja MM, Shackman AJ, Davidson RJ. Individual differences in the effects of perceived controllability on pain perception: critical role of the prefrontal cortex. J Cogn Neurosci. 2007;19:993–1003. [PubMed]
  • Schoenbaum G, Roesch MR, Stalnaker TA. Orbitofrontal cortex, decision-making and drug addiction. Trends Neurosci. 2006;29:116–124. [PMC free article] [PubMed]
  • Schuster CR, Woods JH. The conditioned reinforcing effects of stimuli associated with morphine reinforcement. International Journal of the Addictions. 1968;3:223–230.
  • Scott LV, Dinan TG. Vasopressin and the regulation of hypothalamic-pituitary-adrenal axis function: implications for the pathophysiology of depression 1998 [PubMed]
  • Scott LV, Dinan TG. Vasopressin and the regulation of hypothalamic-pituitary-adrenal axis function: implications for the pathophysiology of depression. Life Sci. 1998;62:1985–1998. [PubMed]
  • Seiwell AP, Reveron ME, Duvauchelle CL. Increased accumbens Cdk5 expression in rats after short-access to self-administered cocaine, but not after long-access sessions. Neurosci Lett. 2007;417:100–105. [PMC free article] [PubMed]
  • Sesack SR, Deutch AY, Roth RH, Bunney BS. Topographical organization of the efferent projections of the medial prefrontal cortex in the rat: an anterograde tract-tracing study with Phaseolus vulgaris leucoagglutinin. J Comp Neurol 1989. 1989 Dec 8;290(2):213–42. [PubMed]
  • Sesack SR, Carr DB. Selective prefrontal cortex inputs to dopamine cells: implications for schizophrenia. Physiol Behav. 2002;77:513–517. [PubMed]
  • Sesack SR, Pickel VM. Prefrontal cortical efferents in the rat synapse on unlabeled neuronal targets of catecholamine terminals in the nucleus accumbens septi and on dopamine neurons in the ventral tegmental area. J Comp Neurol. 1992;320:145–160. [PubMed]
  • Shaham Y, Erb S, Leung S, Buczek Y, Stewart J. CP-154,526, a selective, non-peptide antagonist of the corticotropin-releasing factor1 receptor attenuates stress-induced relapse to drug seeking in cocaine- and heroin-trained rats. Psychopharmacology. 1998;137:184–190. [PubMed]
  • Shaham Y, Funk D, Erb S, Brown TJ, Walker CD, Stewart J. Corticotropin-releasing factor, but not corticosterone, is involved in stress-induced relapse to heroin-seeking in rats. J Neurosci. 1997;17:2605–2614. [PubMed]
  • Shaham Y, Highfield D, Delfs J, Leung S, Stewart J. Clonidine blocks stress-induced reinstatement of heroin seeking in rats: an effect independent of locus coeruleus noradrenergic neurons. Eur J Neurosci. 2000;12:292–302. [PubMed]
  • Shalev U, Erb S, Shaham Y. Role of CRF and other neuropeptides in stress-induced reinstatement of drug seeking. Brain Res 2009 [PMC free article] [PubMed]
  • Shiffman S. Tobacco “chippers”--individual differences in tobacco dependence. Psychopharmacology (Berl) 1989;97(4):539–47. [PubMed]
  • Shin LM, Liberzon I. The neurocircuitry of fear, stress, and anxiety disorders. Neuropsychopharmacology. 2010;35:169–191. [PMC free article] [PubMed]
  • Solberg Nes L, Roach AR, Segerstrom SC. Executive functions, self- regulation, and chronic pain: a review. Ann Behav Med. 2009;37:173–183. [PubMed]
  • Solomon RL, Corbit JD. An opponent-process theory of motivation. I. Temporal dynamics of affect. Psychol Rev. 1974;81:119–145. [PubMed]
  • Stinus L, Le Moal M, Koob GF. Nucleus accumbens and amygdala are possible substrates for the aversive stimulus effects of opiate withdrawal. Neuroscience. 1990;37:767–773. [PubMed]
  • Sullivan RM, Gratton A. Lateralized effects of medial prefrontal cortex lesions on neuroendocrine and autonomic stress responses in rats. J Neurosci. 1999;19:2834–2840. [PubMed]
  • Swanson LW, Simmons DM. Differential steroid hormone and neural influences on peptide mRNA levels in CRH cells of the paraventricular nucleus: a hybridization histochemical study in the rat. J Comp Neurol. 1989;285:413–435. [PubMed]
  • Takagishi M, Chiba T. Efferent projections of the infralimbic (area 25) region of the medial prefrontal cortex in the rat: an anterograde tracer PHA-L study. Brain Res. 1991;566:26–39. [PubMed]
  • Tanaka S. Architecture and dynamics of the primate prefrontal cortical circuit for spatial working memory. Neural Netw. 1999;12:1007–1020. [PubMed]
  • Taylor SF, Phan KL, Decker LR, Liberzon I. Subjective rating of emotionally salient stimuli modulates neural activity. Neuroimage. 2003;18:650–659. [PubMed]
  • Taylor SF, Welsh RC, Wager TD, Phan KL, Fitzgerald KD, Gehring WJ. A functional neuroimaging study of motivation and executive function. Neuroimage. 2004;21:1045–1054. [PubMed]
  • Tom SM, Fox CR, Trepel C, Poldrack RA. The neural basis of loss aversion in decision-making under risk. Science. 2007;315:515–518. [PubMed]
  • Tomie A, Aguado AS, Pohorecky LA, Benjamin D. Individual differences in pavlovian autoshaping of lever pressing in rats predict stress-induced corticosterone release and mesolimbic levels of monoamines. Pharmacol Biochem Behav. 2000;65:509–517. [PubMed]
  • Treisman A. The binding problem. Curr Opin Neurobiol. 1996;6(2):171–8. [PubMed]
  • Turnbull AV, Rivier C. Corticotropin-releasing factor (CRF) and endocrine responses to stress: CRF receptors, binding protein, and related peptides. Proc Soc Exp Biol Med. 1997;215:1–10. [PubMed]
  • Urry HL, van Reekum CM, Johnstone T, Kalin NH, Thurow ME, Schaefer HS, Jackson CA, Frye CJ, Greischar LL, Alexander AL, Davidson RJ. Amygdala and ventromedial prefrontal cortex are inversely coupled during regulation of negative affect and predict the diurnal pattern of cortisol secretion among older adults. J Neurosci. 2006;26:4415–4425. [PubMed]
  • Vanderschuren LJ, Everitt BJ. Drug seeking becomes compulsive after prolonged cocaine self-administration. Science. 2004;305:1017–1019. [PubMed]
  • Venkatraman V, Payne JW, Bettman JR, Luce MF, Huettel SA. Separate neural mechanisms underlie choices and strategic preferences in risky decision making. Neuron. 2009;62:593–602. [PMC free article] [PubMed]
  • Vogt BA. Pain and emotion interactions in subregions of the cingulate gyrus. Nat Rev Neurosci. 2005;6:533–544. [PMC free article] [PubMed]
  • Volkow ND, Fowler JS, Wang GJ. Role of dopamine in drug reinforcement and addiction in humans: results from imaging studies. Behavioural Pharmacology. 2002;13:355–366. [PubMed]
  • Volkow ND, Fowler JS, Wang GJ, Dewey SL, Schlyer D, MacGregor R, Logan J, Alexoff D, Shea C, Hitzemann R, et al. Reproducibility of repeated measures of carbon-11-raclopride binding in the human brain. J Nucl Med. 1993;34:609–613. [PubMed]
  • Volkow ND, Wang GJ, Fischman MW, Foltin RW, Fowler JS, Abumrad NN, Vitkun S, Logan J, Gatley SJ, Pappas N, et al. Relationship between subjective effects of cocaine and dopamine transporter occupancy. Nature. 1997a;386:827–830. [PubMed]
  • Volkow ND, Wang GJ, Fowler JS, Hitzemann R, Angrist B, Gatley SJ, Logan J, Ding YS, Pappas N. Association of methylphenidate-induced craving with changes in right striato-orbitofrontal metabolism in cocaine abusers: implications in addiction. Am J Psychiatry. 1999;156:19–26. [PubMed]
  • Volkow ND, Wang GJ, Fowler JS, Logan J, Angrist B, Hitzemann R, Lieberman J, Pappas N. Effects of methylphenidate on regional brain glucose metabolism in humans: relationship to dopamine D2 receptors. Am J Psychiatry. 1997b;154:50–55. [PubMed]
  • Volkow ND, Wang GJ, Fowler JS, Logan J, Gatley SJ, Hitzemann R, Chen AD, Dewey SL, Pappas N. Decreased striatal dopaminergic responsiveness in detoxified cocaine-dependent subjects. Nature. 1997c;386:830–833. [PubMed]
  • Voorn P, Vanderschuren LJ, Groenewegen HJ, Robbins TW, Pennartz CM. Putting a spin on the dorsal-ventral divide of the striatum. Trends Neurosci. 2004;27:468–474. [PubMed]
  • Wager TD, Rilling JK, Smith EE, Sokolik A, Casey KL, Davidson RJ, Kosslyn SM, Rose RM, Cohen JD. Placebo-induced changes in FMRI in the anticipation and experience of pain. Science. 2004;303:1162–1167. [PubMed]
  • Wang GJ, Volkow ND, Fowler JS, Cervany P, Hitzemann RJ, Pappas NR, Wong CT, Felder C. Regional brain metabolic activation during craving elicited by recall of previous drug experiences. Life Sci. 1999;64:775–784. [PubMed]
  • Weiss F, Markou A, Lorang MT, Koob GF. Basal extracellular dopamine levels in the nucleus accumbens are decreased during cocaine withdrawal after unlimited-access self-administration. Brain Res. 1992;593:314–318. [PubMed]
  • Wexler BE, Gottschalk CH, Fulbright RK, Prohovnik I, Lacadie CM, Rounsaville BJ, Gore JC. Functional magnetic resonance imaging of cocaine craving. Am J Psychiatry. 2001;158:86–95. [PubMed]
  • Wikler A. Dynamics of drug dependence. Implications of a conditioning theory for research and treatment. Arch Gen Psychiatry. 1973;28:611–616. [PubMed]
  • Wilson FA, O’Scalaidhe SP, Goldman-Rakic PS. Functional synergism between putative gamma-aminobutyrate-containing neurons and pyramidal neurons in prefrontal cortex. Proc Natl Acad Sci U S A. 1994;91:4009–4013. [PubMed]
  • Wilson SJ, Sayette MA, Fiez JA. Prefrontal responses to drug cues: a neurocognitive analysis. Nat Neurosci. 2004;7:211–214. [PMC free article] [PubMed]
  • Wise RA. Action of drugs of abuse on brain reward systems. Pharmacol Biochem Behav. 1980;13(Suppl 1):213–223. [PubMed]
  • Wise RA. The role of reward pathways in the development of drug dependence. Pharmacol Ther. 1987;35:227–263. [PubMed]
  • Wise RA. Brain reward circuitry: insights from unsensed incentives. Neuron. 2002;36:229–240. [PubMed]
  • Wunderlich GR, Raymond R, DeSousa NJ, Nobrega JN, Vaccarino FJ. Decreased CCK(B) receptor binding in rat amygdala in animals demonstrating greater anxiety-like behavior. Psychopharmacology (Berl) 2002;164:193–199. [PubMed]
  • Xue G, Lu Z, Levin IP, Weller JA, Li X, Bechara A. Functional dissociations of risk and reward processing in the medial prefrontal cortex. Cereb Cortex. 2009;19:1019–1027. [PMC free article] [PubMed]
  • Zhang S, Tang JS, Yuan B, Jia H. Inhibitory effects of electrical stimulation of ventrolateral orbital cortex on the rat jaw-opening reflex. Brain Res. 1998;813:359–366. [PubMed]
  • Zhou Y, Spangler R, Ho A, Kreek MJ. Increased CRH mRNA levels in the rat amygdala during short-term withdrawal from chronic ‘binge’ cocaine. Brain Res Mol Brain Res. 2003a;114:73–79. [PubMed]
  • Zhou Y, Spangler R, Schlussman SD, Ho A, Kreek MJ. Alterations in hypothalamic-pituitary-adrenal axis activity and in levels of proopiomelanocortin and corticotropin-releasing hormone-receptor 1 mRNAs in the pituitary and hypothalamus of the rat during chronic ‘binge’ cocaine and withdrawal. Brain Res. 2003b;964:187–199. [PubMed]
  • Zubieta JK, Bueller JA, Jackson LR, Scott DJ, Xu Y, Koeppe RA, Nichols TE, Stohler CS. Placebo effects mediated by endogenous opioid activity on mu-opioid receptors. J Neurosci. 2005;25:7754–7762. [PubMed]