Neuroscience and Biobehavioral Reviews€¦ · Module Individual differences Cognitive Prefrontal...

Neuroscience and Biobehavioral Reviews 35 (2010) 232–247

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Neuroscience and Biobehavioral Reviews

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Review

Individual differences in prefrontal cortex function and the transition from druguse to drug dependence

Olivier George ∗, George F. KoobCommittee on the Neurobiology of Addictive Disorders, The Scripps Research Institute, 10550 North Torrey Pines Road, SP30-2400, La Jolla, CA 92037, USA

a r t i c l e i n f o

Keywords:StressModuleIndividual differencesCognitivePrefrontalLoss of controlEmotionPain

a b s t r a c t

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 addictionthat 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 theability to quit. In this review, we suggest that the concept of self-regulation, combined with the conceptof modularity of cognitive function, may aid in the understanding of the neural basis of individual differ-ences in the vulnerability to drugs and the transition to addiction. The thesis of this review is that drugaddiction involves a failure of the different subcomponents of the executive systems controlling key cog-

RewardIncentive salience

nitive modules that process reward, pain, stress, emotion, habits, and decision-making. A subhypothesisis that the different patterns of drug addiction and individual differences in the transition to addiction

Habits may emerge from differential vulnerability in one or more of the subcomponents.© 2010 Elsevier Ltd. All rights reserved.

Contents

1. Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2331.1. Addiction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233

2. Animal models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2333. Control and cognitive modules in addictions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2344. Neural systems and cognitive modules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2345. Incentive salience and the mesolimbic dopamine module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235

5.1. Neuroanatomy and function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2355.2. Individual differences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236

6. Stress and the hypothalamic–pituitary–adrenal axis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2366.1. Neuroanatomy and function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2366.2. Individual differences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236

7. Negative emotional states and the extended amygdala module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2377.1. Neuroanatomy and function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2377.2. Individual differences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237

8. Pain and the opioid spinomesothalamocortical module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2378.1. Neuroanatomy and function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2378.2. Individual differences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238

9. Habits and the striatal module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238
9.1. Neuroanatomy and function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2389.2. Individual differences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238
10. Decision-making and the prefrontal cortex module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23910.1. Neuroanatomy and function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23910.2. Individual differences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239

∗ Corresponding author. Tel.: +1 858 784 7102; fax: +1 858 784 7405.E-mail address: [email protected] (O. George).

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11.5. Loss of control over habits and decision-making . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24212. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243. . . . . .

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References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. Background

.1. Addiction

Drug addiction is a chronic relapsing disorder characterizedy increased motivation to seek drugs and is characterized inhe human condition by increased drug intake, loss of controlver drug intake, and compulsive drug taking and drug seek-ng. Three major components of the addiction cycle have beendentified — binge/intoxication, withdrawal/negative affect, and pre-ccupation/anticipation (craving) — and incorporate the constructsf impulsivity and compulsivity with varying contributions of pos-tive and negative reinforcement (Koob and Le Moal, 2008; Koobnd Le Moal, 2008). From a theoretical perspective, the increasedotivation to seek drugs has been hypothesized to involve coun-

eradaptive mechanisms (Solomon and Corbit, 1974; Wikler, 1973),ncreases in incentive salience (Robinson and Berridge, 1993), or aombination of both constructs in the form of an allostatic changen hedonic set point (Ahmed and Koob, 1998; Koob and Le Moal,997, 2001).

The counteradaptive theory states that two opposing processesontrol affect and the motivational changes observed after chronicrug use. The initial rewarding effect of the drug (a-process) willrigger a delayed aversive effect (b-process) that gets larger withhronic drug use and will counteract the a-process to maintainomeostasis. This model has been proposed to explain tolerance,ithdrawal, and the aversive craving state observed during absti-ence (Solomon and Corbit, 1974; Laulin et al., 1999). Allostasis,

n the context of addiction, is the process of maintaining appar-nt reward function stability through changes in brain reward andtress mechanisms (Koob and Le Moal, 2001). The allostatic stateepresents a chronic deviation of reward set point that is mostlybserved during abstinence and not observed when the individuals actively taking drug. Thus, the allostatic view extends counter-daptive theory by stating that not only the b-process gets largerith chronic drug use but the reward set point from which the

-process and b-process are anchored progressively shifts down-ard, creating an allostatic state. This model has been proposed

o explain the persistent changes in motivation in drug-dependentndividuals.

Although drug addiction is often viewed as one disorder, it ismportant to note that different drugs produce different patternsf addiction that engage different components of the addictionycle (Koob and Le Moal, 2008). Opioid and alcohol addictionsre characterized by an intense withdrawal/negative affect stageith profound dysphoria and physical and emotional pain often

ollowed by intoxication during the binge/intoxication stage, thusepresenting one of the main driving forces for compulsive drugeeking and drug taking. Profound tolerance occurs to the intoxi-ation associated with alcohol and opioids, but some intoxication
lways remains. Nicotine addiction is not associated with majorntoxication but is instead characterized by highly compulsiveitrated intake of the drug to the point that daily activities (e.g.,ocial contact, meals, and sleep) are perturbed and constrained byhe patterns of nicotine intake. Nicotine addiction is also associ-
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243

ated with intense dysphoria, irritability, sleep disturbances, andcraving during abstinence. Marijuana addiction shares aspectsof both opioid and nicotine addiction, with an initial intensebinge/intoxication stage that progressively transitions to regularand titrated marijuana intake during the day and dysphoria duringabstinence. Cocaine and amphetamine addiction are characterizedby major binge/intoxication and preoccupation/anticipation stages,with an intense craving for the drug and binges that can lasthours or days and are usually followed by intense dysphoria dur-ing acute withdrawal and protracted abstinence associated withanxiety, dysphoria, and intense craving. Again, profound tolerancedevelops to the intoxication associated with the drug during abinge.

Important individual differences in the different stages of addic-tion, as well as in the vulnerability to the transition to addictionhave 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) thepropensity to self-administer the drug, (iii) resistance to extinc-tion, (iv) sensitivity to drug-associated cues, (v) relapse, and (vi)cognitive functions critical for the development of addiction, suchas working memory, attention, reward evaluation, emotion, pain,and stress. It is important to note that the construct of individualdifference here encompasses normal variations in function and dys-function (or vulnerability). For the purpose of this review, we willnot dissociate the contribution of the individual from the contribu-tion of the situation in the development of individual differencesbecause both can lead to dysregulated behavior and increased riskfor the development of drug dependence.

Different types of drug users also exist. For example, differenttypes of tobacco users have been identified, including individu-als who initially limit their intake but progressively escalate theirintake and develop a strong dependence on tobacco; individualswho smoke regularly but who will always limit their tobacco intake(defined as non-dependent “chippers”); and individuals who limittheir intake but who will experience periods of high intake andhigh dependence on tobacco (Kassel et al., 1994). These differ-ent patterns of drug use and addiction suggest that the addictionprocess is not a unitary process and that different neuropsychobi-ological mechanisms may explain different drug use patterns thatmay ultimately lead to compulsive drug seeking and drug taking.

2. Animal models

Animal models of the major components of the addictioncycle have been established and validated. The binge/intoxicationstage can be modeled by acquisition of drug self-administrationunder limited access conditions (Piazza and Le Moal, 1996), brain

O. George, G.F. Koob / Neuroscience and Biobehavioral Reviews 35 (2010) 232–247 233

11. Loss of control and the prefrontal cortex module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23911.1. Loss of control over stress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24111.2. Loss of control over emotion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24111.3. Loss of control over incentive salience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24211.4. Loss of control over pain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242

stimulation reward (Kornetsky and Esposito, 1979), conditionedplace preference (Carboni and Vacca, 2003), and drug discrimi-nation (Holtzman, 1990). The withdrawal/negative affect stage canbe modeled by intracranial self-stimulation (Epping-Jordan et al.,1998), conditioned place aversion (Stinus et al., 1990), drug dis-

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rimination (Holtzman, 1990), and drug self-administration inependent subjects (Denoble and Begleiter, 1976; Gellert andparber, 1977). The preoccupation/anticipation stage can be mod-led by drug self-administration and different paradigms, such asesistance to extinction (Schuster and Woods, 1968), drug-, stress-or cue-induced reinstatement (Shaham et al., 2003), protractedbstinence (Roberts et al., 2000), conditioned withdrawal (Wiklernd Pescor, 1967), and second-order schedules of reinforcementKatz and Goldberg, 1991). Moreover, animal models of the transi-ion to addiction that incorporate these three stages have also beeneveloped and validated. These models include escalation in drugelf-administration with extended access to the drug (Ahmed andoob, 1998), the alcohol and nicotine deprivation effect (Georget al., 2007; Koob, 2000), and drug seeking and drug taking in theresence of negative consequences (Deroche-Gamonet et al., 2004;anderschuren and Everitt, 2004).

. Control and cognitive modules in addictions

At the social psychology level, failure of self-regulation has beenrgued to be one of the main causes of psychosocial pathologies,ncluding addiction (Baumeister et al., 2003). Failure of self-egulation represents a deficit in information-processing, attention,lanning, reasoning, self-monitoring, or inhibition of a specificrain function or behavior (Baumeister et al., 1994; Giancola et al.,996a,b). Depending on the different stages of the addiction cycle,ailure of self-regulation may lead to an increased risk of expo-ure to the drug, increased drug seeking and drug taking, increasedelapse, or increased vulnerability to the transition to addiction.ailure of self-regulation is hypothesized to result at the neurobi-logical level in a loss of control of a brain structure over specificeural systems underlying relatively independent brain functions,uch as stress, anxiety, reward, pain, habits, and decision-making.his loss of control has often been attributed to a dysfunction ofhe frontal lobes or hypofrontality (Bechara, 2005; Mishkin, 1964;ribram and Mishkin, 1956) and subsequent dysregulation of theifferent subcortical cognitive systems controlled by the prefrontalortex. For instance, deficits in frontal cortex regulation in childrenr young adolescents predict later drug and alcohol consumption,specially for children raised in families with drug and biobehav-oral disorders histories (Dawes et al., 1997; Aytaclar et al., 1999).

Cognition and its neural representations have been hypothe-ized to be organized into a set of modules that are specializedor distinct cognitive processes and different types of informa-ion processing (Fodor, 1983). The theory of “modularity of mind”escribes mind as composed of several insulated modules that areelatively independent in their functioning. These modules haveeparate classes of input and information processing inside eachodule and theoretically cannot be influenced by the activity of

nother module (Fodor, 1983). Imaging, brain lesion, and neu-opharmacological studies have demonstrated in both humans andnimals the modularity of cognition. Classical examples of modu-arity are the high specificity of activation of cortical areas duringhe presentation of words, colors, faces, or places (Gazzaniga, 2000)r the dissociation between conditioning and declarative knowl-dge after lesions of the amygdala and hippocampus (Becharat al., 1995). The modularity of mind theory has also been rein-orced by brain lesion studies demonstrating double and even tripleissociations between different brain functions, such as explicits. implicit memory (Cohen and Squire, 1980), conditioning and
eclarative knowledge (Bechara et al., 1995), memory vs. fear vs.nxiety (Bannerman et al., 2004), pain affect and sensation (Plonert al., 1999), and reward vs. motivation (Berridge et al., 2009). Its now well established that sensation, perception, motor action,r even different types of memories represent different cogni-
ehavioral Reviews 35 (2010) 232–247

tive modules with different neural systems that are more or lessindependent in their functioning. Flexible, goal-directed behav-ior requires an adapted cognitive control system for organizing,selecting, and consolidating information that derives from the dif-ferent modules into a coherent and unified experience (Treisman,1996). The prefrontal cortex and its different subregions have beenhypothesized to represent this cognitive control system (Baddeley,1996; Robbins, 2000; Ridderinkhof et al., 2004).

The prefrontal cortex sends projections to most cortical andsubcortical structures and targets the main sources of majordiffuse neurotransmitter systems, including the dopaminergic,noradrenergic, serotoninergic, and cholinergic neurons in the basalforebrain and brainstem (Goldman-Rakic, 1987; Gabbott et al.,2005). Moreover, neuroanatomical, brain lesion, and site-specificpharmacological modulation studies of the prefrontal cortex haverevealed the heterogeneity of the prefrontal cortex (Robbins, 2000).

As explained above, there are important individual differencesin the different stages of addiction and in key brain functions criticalfor the development of addiction, such as attention, decision-making, reward, emotion, pain, and stress (Crowley et al., 1998; deWit et al., 1986; Deroche-Gamonet et al., 2004). We suggest that theconcept of self-regulation, combined with the concept of modular-ity of cognitive function, may help one understand the neural basisof the individual differences in the vulnerability to drug addiction.Indeed, dysfunction of a specific subregion of the prefrontal cortexmay lead to a loss of control over a specific neurobiological sys-tem, leading, for instance, to a sensitization of incentive saliencein one individual and to a hyperreactivity of the stress system inanother individual. Therefore, the failure of a specific module maydiffer from one individual to another and may represent a neu-ropsychobiological mechanism underlying individual differencesin the vulnerability to drug addiction.

4. Neural systems and cognitive modules

Numerous reports have demonstrated a role for the dopamine,corticotropin-releasing factor (CRF), opioid, serotonin, �-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 ventraltegmental area (VTA), central (CeA) and basolateral (BLA) nucleiof the amygdala, bed nucleus of the stria terminalis (BNST), dorsaland ventral striatum (nucleus accumbens), ventral pallidum,hypothalamus, and prefrontal cortex in drug addiction (Koob andVolkow, 2010). The identification of drug addiction as a braindisease has oriented research in the addiction field toward a searchfor a common final pathway to explain the transition to addiction.Significant breakthroughs have been made, suggesting that thereare common neurobiological mechanisms in all types of addictions.Converging lines of evidence suggest that a dysregulation of thedopaminergic system, CRF system, or �FosB may mediate thetransition 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, brainstructures, and different physiological, psychological, and cog-nitive mechanisms involved in the addiction process suggeststhat understanding individual differences in the transition toaddiction may require a more integrated modular view of theneuropsychological mechanisms of addiction.

The thesis of this review is that drug addiction involves a failureof the different subcomponents of the executive systems control-
ling key systems that process reward, pain, stress, dysphoria, andhabits. A subhypothesis is that the different patterns of drug addic-tion and individual differences in the transition to addiction mayemerge from differential vulnerability in one or more of the sub-components. A multi-system framework with a focus on different

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sychological and computational vulnerabilities has been recentlyormulated to explain patterns of addiction across drugs and indi-iduals (Redish et al., 2008). The focus of the present review isnstead on the elaboration of a multi-system framework with aocus on the different neurobiological systems that may be differ-ntially involved in the addiction process. In the following sectionse will briefly review the neuroanatomy and function of the mod-les and review how individual differences in the functioning ofhese modules may explain individual differences in the transitiono addiction. It is important to note that the modules described herere not Fodorian in the sense that they are not fully encapsulatedFodor, 1983). However, they share many properties of Fodorian

odules, such as domain specificity, mandatory operation, lim-ted accessibility, fast processing, and fixed neural architecture, andhey exhibit specific breakdown patterns (see examples of doubleissociation described above).

. Incentive salience and the mesolimbic dopamine module

.1. Neuroanatomy and function

The mesolimbic dopamine system is formed by dopaminer-ic cell bodies in the VTA and their projections to the ventral

ig. 1. Anatomical functional differences in the prefrontal cortex in the rat. The prefronedial prefrontal cortex (PFC) is composed of a dorsal section with the anterior cingula

ection with the ventral prelimbic (PLv), infralimbic (IL), dorsal peduncular (DP), and medorsolateral (DLO) cortices, the dorsal and ventral anterior insular cortices (AID, AIV), andVO) and ventral lateral orbital (VLO) cortices. The prefrontal cortex can be subdivided inorsal mPFC, ventral mPFC, OFC, and insula. It is important to note that these four regioellular architectonics and specific projections.

ehavioral Reviews 35 (2010) 232–247 235

striatum (Fig. 1). The VTA also possesses a population of GABAer-gic neurons that provide inhibitory inputs to dopamine cells andinfluence other structures, such as the pedunculopontine tegmen-tal nucleus and glutamatergic neurons (Dobi et al., 2010). TheVTA receives its main excitatory glutamatergic and cholinergicinputs from the ventromedial prefrontal cortex (ventral prelimbic,infralimbic, dorsal peduncular cortices), ventral subiculum, subtha-lamic nucleus, parabrachial nucleus, pedunculopontine tegmentalnucleus, and laterodorsal tegmental nucleus (Kalivas, 1993). TheVTA also receives prominent inputs from the nucleus accum-bens shell and the ventromedial ventral pallidum (Oades andHalliday, 1987). Dopamine and GABA neurons in the VTA havebeen shown to be critical for the rewarding properties of psy-chostimulants, and with the possible exception of opioids, alldrugs of abuse when self-administered acutely stimulate thedopaminergic system and increase dopamine release in the nucleusaccumbens (Volkow et al., 2002). The pattern of firing of dopamin-ergic neurons in the VTA in response to drugs of abuse has
been hypothesized to encode drug reward, attribution of incen-tive salience, and establishment of response habits (Wise, 1980,1987, 2002). Attribution of incentive salience refers to a processthat transforms sensory information about reward into attractiveincentives (Robinson and Berridge, 1993). Individual differences
tal cortex in rats can be dissociated into medial, lateral, and ventral regions. Thete cortex (ACC), precentral cortex, and dorsal prelimbic cortex (PLd) and a ventralial orbital (MO) cortices. The lateral PFC is composed of the lateral orbital (LO) andthe granular insular cortex (GI). The ventral PFC is composed of the ventral orbitalto four main regions based on differential anatomical connections and functions:

ns are not homogeneous and can be further dissociated into subregions based on

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n incentive salience may represent a key mechanism to explainndividual differences in the vulnerability to addiction, and exces-ive attribution of incentive salience to drug-related cues mayontribute to excessive drug intake, compulsive behavior, andelapse.

.2. Individual differences

There are considerable individual differences in the reinforc-ng properties of drugs of abuse in humans and animals (de Witt al., 1986; O’Brien and Terns, 1986). The acute rewarding effectsf drugs of abuse are critical in non-dependent users and repre-ent a powerful source of positive reinforcement for the initiationnd maintenance of drug self-administration. Individual differ-nces in the mesolimbic dopamine system have been observedn humans and have been related to differential anticipation andeward-seeking behavior. Individual differences in dopamine D2eceptor binding in the ventral/dorsal striatum suggest differen-ial activity of the mesolimbic dopamine system (Volkow et al.,993). Individual differences in amphetamine-induced dopamineelease are associated with increased drug-induced “wanting” andovelty-seeking (Leyton et al., 2002). Higher ratings of positivemphetamine effects are also associated with greater dopamineelease in the ventral striatum, dorsal putamen, and dorsal cau-ate (Oswald et al., 2005). Baseline D2 receptor availability in thetriatum negatively predicts rates of cocaine self-administration inonkeys (Nader et al., 2006).Individual differences in the sensitivity of the VTA to electrical

elf-stimulation has been observed and related to differential sen-itivity of the reward system (Druhan et al., 1990). Moreover, ratshat show increased novelty-seeking and increased cocaine self-dministration also show dysregulation of tyrosine hydroxylasend cholecystokinin in the VTA (Lucas et al., 1998), increased basalring rates of dopamine neurons in the VTA (Marinelli and White,000), and increased basal or drug-induced dopamine release inhe nucleus accumbens (Bradberry et al., 1991; Hooks et al., 1992;iazza et al., 1991b; Rouge-Pont et al., 1998). Furthermore, individ-al differences in dopamine transporters in the VTA and dopaminend serotonin levels in the striatum have been associated withndividual differences in behavioral sensitization to amphetamineAntoniou et al., 2008; Dietz et al., 2008; Piazza et al., 1991b). Theseesults suggest that the mesolimbic dopamine system and the ven-ral striatum may represent a key system for the vulnerability to theositive reinforcing effects of drugs and the initiation and mainte-ance of drug self-administration.

. Stress and the hypothalamic–pituitary–adrenal axis


The hypothalamic–pituitary–adrenal (HPA) axis is defined byhree major structures: the paraventricular nucleus of the hypotha-amus (PVN), the anterior lobe of the pituitary gland, and thedrenal gland (for review, see Turnbull and Rivier, 1997). Neurose-retory neurons in the medial parvocellular subdivision of the PVNynthesize and release CRF into the portal blood vessels that enterhe anterior pituitary gland. Binding of CRF to the CRF1 receptorn pituitary corticotropic cells induces the release of adrenocor-icotropic hormone (ACTH) into the systemic circulation (Fig. 1).CTH, in turn, stimulates glucocorticoid synthesis and secretion

rom the adrenal cortex. Vasopressin released from parvocellular
eurons of the PVN produces synergistic effects on ACTH releasehat are mediated by vasopressin V1b receptors (Scott and Dinan,998). The HPA axis is finely tuned via negative feedback from cir-ulating glucocorticoids that act on the glucocorticoid receptor, aytosolic protein that acts via the nucleus on transcriptional mech-

anisms in two main brain areas: the PVN and the hippocampus(Herman et al., 1996). The hypophysiotropic neurons of the PVNare innervated by numerous afferent projections from the brain-stem, other hypothalamic nuclei, and forebrain limbic structures.The medial prefrontal cortex in the rat possesses a large numberof glucocorticoid receptor-positive neurons that can bidirection-ally control stress reactivity of the HPA axis through activation ofthe prelimbic or infralimbic cortex (Radley et al., 2006). Lesions ofthe prelimbic cortex increase ACTH and corticosterone responsesto stress, whereas lesions of the infralimbic cortex have an oppositeeffect (Radley et al., 2006). This differential control is attributableto differential projections of the prelimbic and infralimbic cortex tostructures mediating either stress inhibition (ventrolateral preop-tic area, dorsomedial hypothalamus, and PVN) and stress activation(anterior BNST, medial nucleus of the amygdala; CeA, and nucleusof the tractus solitarus), respectively (Radley et al., 2006).

The HPA axis plays a key role in mediating the reinforcingeffects of drugs of abuse and stress-induced relapse. Drugs of abuseacutely activate the HPA axis, and dependence dysregulates theHPA axis (Piazza and Le Moal, 1996). Stressors facilitate the acquisi-tion of cocaine and amphetamine self-administration, and rats withheightened reactivity to stress acquire drug self-administrationfaster and at lower doses (Piazza et al., 1989, 1991a, 1996; Piazzaand Le Moal, 1998). Moreover, corticosterone facilitates the acqui-sition of cocaine self-administration (Mantsch et al., 1998; Piazza etal., 1991a). The effect of glucocorticoids on the reinforcing effects ofdrugs is hypothesized to be attributable to activation of dopamineneurons in the VTA and increased dopamine release in the nucleusaccumbens (Barrot et al., 2001; Barrot et al., 2000; Piazza and LeMoal, 1998). Furthermore, excessive drug intake and possibly thetransition to dependence are associated with tolerance of the HPAaxis response to stress and overactivation and persistent dysregu-lation during early withdrawal and protracted abstinence (Mantschet al., 2003; Zhou et al., 2003a,b). Interestingly, the HPA axis alsointeracts with the extended amygdala. High circulating levels ofglucocorticoids can activate the CRF and norepinephrine systems inthe CeA and BLA through a positive feedback mechanism (Imaki etal., 1991; Makino et al., 1994; Swanson and Simmons, 1989). Theseresults suggest that the HPA axis may be involved in both the ini-tial positive reinforcing effects of the drug and on the vulnerabilityto relapse after protracted abstinence, particularly during stressfulevents (Erb et al., 1996, 1998; Martin-Fardon et al., 2000).

6.2. Individual differences

Individual differences in the responsivity of the HPA axis tostress are very well understood. Sensation-seeking and novelty-seeking are personality traits that have been associated with higherpropensity to self-administer drugs and dysregulation of the HPAaxis in humans and rodents (Piazza and Le Moal, 1998). Animalmodels for these traits include the characterization of high vs.low responders by measuring locomotor activity in an inescapablenovel environment (Piazza et al., 1989). High responders are moresensitive to cocaine, amphetamine-induced locomotor activity,and amphetamine self-administration. This increased sensitivityto drugs of abuse in high responder rats has been shown tobe dependent on the HPA axis. High responder rats exhibit anexaggerated corticosterone response to stress, and this increasedcorticosterone drives in part the increased activation of the VTAand dopamine release in the nucleus accumbens (Piazza and LeMoal, 1998; Piazza et al., 1991a). Individual differences in the HPA
axis are then likely to confer vulnerability to the initial positivereinforcing effects of drugs, at least during initial drug exposureand the acquisition of self-administration, but not necessarily vul-nerability to dependence per se. Indeed, recent reports suggest thatalthough heightened reactivity of the HPA axis is associated with

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vertical shift in the cocaine dose-response curve and increasedelf-administration during acquisition, it is not associated withncreased compulsive cocaine intake (Belin et al., 2008; Deroche-amonet et al., 2004). Moreover, the effect of stress on relapse doesot appear to be directly mediated by the HPA axis but rather indi-ectly by the extrahypothalamic CRF system through a CRF-CRF1eceptor connection between the CeA and ventral BNST (Erb et al.,998; Erb and Stewart, 1999; Le et al., 2002, 2000; Shaham et al.,997; Shalev et al., 2009) and the noradrenergic system throughnucleus accumbens-�-adrenergic receptor connection between

he lateral tegmental nucleus and BNST (Erb et al., 2000; Shaham etl., 2000). Dysregulation of the HPA axis may represent a key factorn the vulnerability to addiction by modulating two key modules.eightened reactivity of the HPA axis may facilitate both the posi-

ive reinforcing effects of drugs via modulation of the mesolimbicopamine system and the negative reinforcing effects of drugs byctivating the extended amygdala and thus may be involved in thenitiation, maintenance, and relapse of drug self-administration.

. Negative emotional states and the extended amygdalaodule


The extended amygdala is a neuroanatomical macrostructuren the basal forebrain that shares similarities in morphology, neu-ochemistry, and connectivity (Fig. 1). It is composed of the BNST,eA, MeA, and a transition zone in the posterior medial part (shell)f the nucleus accumbens (Koob and Le Moal, 2001). This systemeceives afferents from limbic and olfactory cortices. Key inputs arehe insular cortex and the ventral medial prefrontal cortex (ven-ral prelimbic, infralimbic, and dorsal peduncular cortices), lateralypothalamus, parabrachial nucleus, lateral tegmental nucleus,nd BLA either through direct or indirect projections via theABAergic intercalated cell mass (Gray et al., 1993; Reynolds andahm, 2005; Alheid and Heimer, 1988; Koob et al., 1998) (Fig. 1).he extended amygdala projects heavily to the lateral hypothala-us, ventral pallidum (posterior medial), VTA, pedunculopontine

egmental nucleus, parabrachial nucleus, lateral tegmental nucleus,nd other midbrain structures (Gray et al., 1993; Reynolds andahm, 2005; Alheid and Heimer, 1988; Koob et al., 1998). Asuch, the extended amygdala links the basal forebrain to the clas-ic reward systems of the lateral hypothalamus via the medialorebrain bundle reward system. Key elements of the extendedmygdala include neurotransmitters of the brain stress systemsssociated with the negative reinforcement of dependence, suchs CRF and norepinephrine (Koob and Le Moal, 2005). Studies onear and anxiety have identified the amygdala as a central compo-ent of the processing of fear, threats, and anxiety in humans andnimals (Koob and Le Moal, 2008; LeDoux, 2000). The extendedmygdala is hypothesized to engage the organism in fight or flightesponses and to encode negative emotional states. Dysregulationf the extended amygdala has been hypothesized to play a key rolen disorders related to stress and negative emotional states, suchs posttraumatic stress disorder, general anxiety disorder, phobias,nd affective disorders (Shin and Liberzon, 2010). Neuroadaptivehanges in this extended amygdala circuit may also lead to theversive effects and dysregulated reward system hypothesized toe the motivation for the transition to drug addiction (Koob and Leoal, 2008).


Converging evidence suggests that there are major individualifferences in the response of the extended amygdala to emotional


stimuli (Beaver et al., 2008; Bishop et al., 2004; Canli, 2004; Canliand Gabrieli, 2004; Hamann and Canli, 2004; Mather et al., 2004).Individual differences in a personality trait linked to the driveto gain reward (increased reward-drive) correlate positively withactivation of the amygdala and negatively correlated with activ-ity in the ventromedial prefrontal cortex (Beaver et al., 2008). Aheightened predisposition to aggression is also associated with anincreased amygdala response to aggressive facial displays (Coccaroet al., 2007; Passamonti et al., 2008). The CeA (dorsal amygdalain humans) is also recruited during conscious processing of fear-ful faces in healthy volunteers, and individual differences in traitanxiety predict the response of a key input to the CeA, the BLA,to unconsciously processed fearful faces (Etkin et al., 2004). Theamygdala is also activated during affective judgment and duringthe expression of emotional responses when viewing affective pic-tures (Phan et al., 2003; Taylor et al., 2003). Moreover, the amygdalais 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 abnor-malities in the fiber tracts connecting the orbitofrontal cortex andanterior cingulate cortex to the amygdala have been observed insome cocaine addicts (Lim et al., 2002). Interestingly, the changesin amygdala volume in cocaine addicts were observed even in sub-jects recently exposed to cocaine (<1–2 years), suggesting thatdecreased amygdala volume represents either early drug-inducedimpairment or an individual developmental predisposition (Lim etal., 2002).

Individual differences have also been observed in rodents.Differences in anxiety-like behavior have been related to differ-ential levels of vasopressin and androgen receptors (Linfoot et al.,2009), glucocorticoid receptors, and cholecystokinin-B receptors(Wunderlich et al., 2002) in the extended amygdala. Individualswith increased anxiety-like responding exhibited a downregu-lation of amygdala cholecystokinin-B receptor binding, possiblyreflecting compensation for increased cholecystokinin activity(Wunderlich et al., 2002). Individual differences in the sensitiv-ity of the CeA to inactivation by a GABAA receptor agonist havealso been observed in rats self-administrating amphetamine (Cainet al., 2008). Inactivation of the CeA only decreased amphetamineself-administration in rats with excessive drug intake, suggestingthat individual differences in the recruitment of the CeA might pre-dispose an individual to excessive drug intake (Cain et al., 2008).Altogether, these results demonstrate that individual differencesin the activity of the extended amygdala may predispose individ-uals to heightened anxiety, stress, and a negative emotional stateand represent a key factor in the transition from positive to negativereinforcement and the transition to addiction.

8. Pain and the opioid spinomesothalamocortical module

8.1. Neuroanatomy and function

Pain is a subjective experience that has a powerful influence ondecision-making and can dramatically alter the reinforcing effectsof drugs of abuse, particularly opiates, and facilitate the transition todrug addiction (Miller and Gold, 2007). Pain is a multidimensionalphenomenon that includes acute pain, chronic pain, and emotionalpain as well as different types of pain based on different noxiousstimuli (e.g., chemical, heat, mechanical). The neural substrates ofacute and chronic pain have been extensively studied using imag-ing techniques in humans and rodents (Peyron et al., 2000; Porro,
2003; Vogt, 2005). Key areas involved in the processing of acute andchronic pain involve the spinoreticular, spinomesencephalic, andspinothalamic tract, parabrachial nuclei, periaqueductal gray area(PAG), rostroventromedial medulla, medial and ventropostero-lateral thalamus, centrolateral, centromedian, and parafascicular

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ucleus of the thalamus, amygdala, somatosensory cortex, insu-ar cortex, and anterior cingulate cortex (Fig. 1) (Peyron et al.,000; Porro, 2003; Vogt, 2005). Pain is associated with activationf a primary afferent nociceptor that transmits pain signals to aecond-order neuron in the dorsal horn that crosses contralater-lly and sends efferents to the brainstem, thalamus, and neocortex.ome have argued that the classic pain pathway (spinothalamo-ortical) mediates physical pain, whereas the affective componentf pain is mediated by the extra-spinothalamocortical pathwayBesson, 1999; Price, 2000). Key regions in the processing of emo-ional pain in this pathway are the parabrachial nucleus, CeA, PAG,nsula, and anterior cingulate cortex (Besson, 1999; Price, 2000).hronic and acute pain is associated with hyperactivity of the dorsalorn and spinothalamic tract, resulting in activation of the neocor-ex as well as hyperactivity of the parabrachial nucleus and CeAHan and Neugebauer, 2004). Moreover, the CeA can control painhrough a descending projection to the PAG and rostroventrome-ial medulla that can modulate nociceptive relay neurons in theorsal horn (Gauriau and Bernard, 2002). The main neurotrans-itter mediating control over pain signals through the descending

athways is the endogenous opioid enkephalin. Enkephalin actshrough activation of the �-opioid receptor, and �-opioid-inducednalgesia is hypothesized to be mediated at different levels of theescending pathways (hypothalamus, amygdala, and PAG) (Fields,000). Interactions between pain and the motivation to obtainrugs have been demonstrated, particularly for opiate and alcoholddiction. For example, in rats with hypersensitivity of the hind-aw to mechanical stimulation, only heroin doses that produce aeversal of hypersensitivity maintained heroin self-administrationollowing nerve injury, whereas lower doses were only effective in

aintaining drug self-administration in control rats (Martin et al.,007), suggesting that the driving force for the motivation to self-dminister drugs in individuals with a sensitized pain system maye seeking relief of chronic pain.


Individual differences have been well described in pain stud-es. Pain thresholds greatly vary with gender, age, and the subject’sehavioral state (Fillingim et al., 2009; Gibson and Helme, 2001;ielsen et al., 2009). For instance, under great emotion or intenseoncentration, people often report few signs of pain despite severenjuries (Fields, 2004). Imaging studies have shown that activity inhe midbrain, medial thalamus, and cortical nociceptive-receivingreas such as the insula and anterior cingulate cortex correlateith pain intensity (Casey, 2000). Individuals with low pain thresh-

lds exhibit higher activation of the primary somatosensory cortex,nterior cingulate cortex, and prefrontal cortex than individualsith high pain thresholds (Coghill et al., 2003). Interestingly, indi-

idual differences did not correlate with differential activation ofhe thalamus despite its key involvement in the encoding of noci-eptive information (Coghill et al., 2003). Moreover, the impact oferceived controllability on pain perception varies highly between

ndividuals and is correlated with differential activation of the ante-ior cingulate cortex, insula, and ventrolateral prefrontal cortexSalomons et al., 2007). Activity in the anterior cingulate cortex,orsolateral prefrontal cortex, insular cortex, nucleus accumbens,halamus, and PAG correlated with the magnitude of placebo anal-esia in humans (Wager et al., 2004; Zubieta et al., 2005) and isediated in part via activation of the endogenous opioid system,

pecifically activation of �-opioid receptors (Zubieta et al., 2005).
bnormal pain perceptions have been reported in opiate addictionuring the development, maintenance, and withdrawal periodsCompton, 1994; Compton et al., 2000; Compton and Estepa, 2000;overty et al., 2001a,b), and preexisting pain problems are a key
actor in the transition to opiate abuse and addiction (Brands et al.,


2004). Altogether, these results suggest that dysregulation of thepain system, particularly the insula, anterior cingulate cortex, andCeA, because of the cross between “affective” pain pathways thereand negative emotional states, might confer vulnerability to drugaddiction in some individuals.

9. Habits and the striatal module


The striatum in rodents can be divided into several compo-nents, including the ventral striatum (nucleus accumbens shell andcore) and dorsal striatum (dorsomedian and dorsolateral) (Fig. 1).The striatum is composed of inhibitory GABAergic cells project-ing to the pallidum (95% of striatal cells) and the brainstem andlocal cholinergic interneurons (5% of striatal cells) (Gerfen, 1992).The connectivity of the striatum is organized on a ventromedialto dorsolateral axis (Voorn et al., 2004). The nucleus accumbensshell receives dopaminergic inputs from the VTA and glutamatergicinputs from the ventromedial ventral PFC (ventral prelimbic, infral-imbic, dorsal peduncular cortices) and insular cortex and projectsto the ventromedial part of the ventral pallidum and VTA (Reynoldsand Zahm, 2005; Gabbott et al., 2005). The nucleus accumbenscore receives dopaminergic inputs from the VTA and glutamatergicinputs from the dorsomedial prefrontal cortex (dorsal prelimbic,anterior cingulate cortex) and insular and orbital frontal corticesand projects to the dorsolateral part of the ventral pallidum anddorsomedial substantia nigra (Reynolds and Zahm, 2005; Gabbottet al., 2005). The dorsomedial and dorsolateral striatum receivesglutamatergic inputs from the orbitofrontal cortex, anterior cin-gulate cortex, and sensory and motor cortices and projects to theglobus pallidus and ventrolateral substantia nigra (Reynolds andZahm, 2005; Gabbott et al., 2005). The striatum and cortico-striato-pallido-thalamic loops have generally been studied for their role inlocomotor activity, attention, reward, goal-directed behavior, andhabits. These loops have inputs from the mesolimbic and mesos-triatal systems and are partially overlapping and organized in aventral-to-dorsal manner (Voorn et al., 2004). Recent reports sug-gest that these striatal loops are involved in the maintenance ofdrug-seeking behavior under a second-order schedule of reinforce-ment and might be important for addiction (Belin and Everitt,2008). A ventral system, including the ventral striatum and itsinputs from the orbitofrontal cortex, infralimbic cortex, hippocam-pus, amygdala, and VTA, is key for the acquisition of instrumentalresponding, such as the acquisition of cocaine self-administration(Belin et al., 2009). A dorsomedial system, including the dorso-medial striatum and inputs from the anterior cingulate cortexand prelimbic cortex, and premotor cortices may be key for goal-directed behavior in general. A dorsolateral system, including thedorsolateral striatum and its somatosensory inputs and connec-tions with the mesostriatal dopaminergic system, may underliehabit responding (Belin et al., 2009). Recent studies suggest thatthe transition to drug dependence is associated with a progressivedysregulation of the ventral, dorsomedial, and dorsolateral striatalsystems mediating the transition from impulsive to compulsivedrug-seeking and drug-taking (Belin and Everitt, 2008).


Individual differences have been largely reported at the behav-ioral 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 indopamine levels and D1 receptor mRNA in the dorsal and ventralstriatum (Cheng and Feenstra, 2006; Flagel et al., 2008; Tomie et al.,2000). Individual differences have been observed not only in terms

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trategy, important performance differences can be observed, sug-esting individual differences in the functioning of the striatum andorticostriatopallidothalamic loops (Flagel et al., 2009).

Impulsivity, escalation, and compulsivity are hypothesized toepresent the different steps of a continuum of behavioral alter-tions that are observed during the transition to addiction, reflectedn the development of the inflexible and habit-like behavior associ-ted with drug seeking in non-dependent subjects and drug takingn dependent subjects, respectively (Dalley et al., 2007a,b). Low

2 receptor binding in the ventral striatum predicts the magni-ude of cocaine intake escalation and compulsive cocaine intakehen rats are given extended but not limited access to cocaine

Dalley et al., 2007a). Moreover, detoxified drug abusers exhibitecreased D2 receptor binding in the ventral striatum that corre-

ates with self-reported preference for methylphenidate (Volkowt al., 1999). In compulsive cocaine users, individual differences inraving after methylphenidate injection in cocaine abusers havelso been demonstrated and correlate with increased metabolicctivity in the striatum and orbitofrontal cortex (Volkow et al.,999). Individual differences in D2 binding in the striatum havelso been reported between subordinate and dominant monkeys,nd there appears to be an inverse relationship between D2 recep-or levels and vulnerability to the reinforcing effects of cocaineNader et al., 2006). Subordinate monkeys exhibit lower D2 recep-or binding (Grant et al., 1998; Morgan et al., 2002) and increasedocaine intake (Morgan et al., 2002). Altogether, these results sug-est that individual differences in the ventral and dorsal striatumay underlie both the vulnerability to the positive reinforcing

ffects of the drug and the vulnerability to the transition fromoal-directed to compulsive drug seeking.

0. Decision-making and the prefrontal cortex module


The prefrontal cortex in rodents can be dissociated into medial,ateral, and ventral parts (Fig. 2) (Robbins, 2000). The medial PFCs composed of a dorsal section with the anterior cingulate, pre-entral, and dorsal prelimbic cortices and a ventral section withhe ventral prelimbic, infralimbic, dorsal peduncular, and medialrbital cortices. The lateral PFC is composed of the orbitofrontal cor-ex and the dorsal and ventral anterior insular cortices. The ventralFC is composed of the ventral orbital and ventral lateral orbitalortices. The main output of the prefrontal cortex is composedf excitatory glutamatergic pyramidal neurons (Goldman-Rakic,987). Pyramidal neurons are under tight control by local GABAer-ic inhibitory interneurons (Wilson et al., 1994; Rao et al., 2000).he different subregions of the prefrontal cortex send and receiveighly organized connections with the basal ganglia through theortico-striato-pallido-thalamo-cortical and cortico-pallido-nigro-halamo-cortical loops (Groenewegen et al., 1997; Voorn et al.,004). Through its different subregions, the PFC can control virtu-lly all of the subcortical structures through the modulation of theholinergic, dopaminergic, adrenergic, and serotonergic systems byctivating basal forebrain and brainstem nuclei through a directlutamatergic projection or by inhibiting the same structures viactivation of local inhibitory GABAergic interneurons.

The prefrontal cortex has a key role in cognitive functionsnvolved in decision-making, including, but not limited to, mem-ry, attention, emotion, working memory, outcome expectation,nd planning. Impairment of decision-making is a key feature ofddiction. Compulsive drug taking can also be viewed as an aber-


rant behavior resulting from poorly modulated decisions due tothe inability to learn from the negative consequences of drug use.The prelimbic and infralimbic cortices in rats maintain stimulusrepresentation during delays (working memory) and are criticalfor inhibition of behavior during extinction of a Pavlovian con-ditioned response to allow motivationally based decision-making(Morgan and LeDoux, 1999; Narayanan et al., 2006; Sakurai andSugimoto, 1985). The prelimbic cortex is also important for detect-ing action-outcome contingencies and thus goal-directed actions(Balleine and Dickinson, 1998), whereas the infralimbic cortexmay be important for learning stimulus–response associations orhabit behavior (Killcross and Coutureau, 2003). Studies in humanshave also demonstrated that the medial prefrontal cortex (includ-ing Brodman’s Areas 10, 32, and 25) is a critical structure in theneural system subserving risky decision-making (Damasio et al.,1994; Glimcher and Rustichini, 2004). Moreover, two systemscan be identified: the ventral medial prefrontal cortex (whichencodes decisions based on reward value) and the dorsal medialprefrontal cortex (which encodes decisions based on risk). Theorbitofrontal cortex is critical in guiding behavior by signaling out-come expectancy when representation of the value of the expectedoutcome needs to be compared to an alternative response or needsto be held in memory (Schoenbaum et al., 2006).


Individual differences in functioning of the prefrontal cor-tex and decision-making have been observed using behavioraltesting, imaging, and neurochemistry techniques in humans andanimals. Converging evidence shows that individual differencesin prefrontal cortex activity and dopamine, acetylcholine, nore-pinephrine, and serotonin tone in the prefrontal cortex correlatewith working memory, visual attention, and impulsivity in rats(for review, see Dalley et al., 2004). Imaging studies in humanshave shown that individual differences in decision-making underrisk 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 medialprefrontal cortex and positively correlates with activity in the ven-tral medial prefrontal cortex (Xue et al., 2009). Individuals withstrong activation of the dorsal medial prefrontal cortex are moresensitive to risk and therefore less likely to make risky decisions,whereas individuals with strong activation of the ventromedial pre-frontal cortex are more sensitive to reward and more likely to makerisky choices (Xue et al., 2009). Individual differences in preferredstrategies in a decision-making task (i.e., maximizing gain or min-imizing losses) can be predicted by activation of the ventromedialprefrontal cortex and anterior insula, respectively (Venkatramanet al., 2009). Moreover, suppression of cortical excitability in theright dorsolateral prefrontal cortex using transcranial magneticstimulation induces risky behavior (Knoch et al., 2006), and theinterhemispheric balance of activity across the dorsolateral pre-frontal cortex may mediate poor decision-making in individualsinvolved in risky behavior (Fecteau et al., 2007a,b). These resultssuggest that individual vulnerability in the prefrontal cortex maylead to impaired decision-making and facilitate the initiation andmaintenance of drug self-administration.

11. 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 ofthe prefrontal cortex, based on neuroimaging studies in humans(London et al., 2000; Koob and Volkow, 2010). Studies in rats showthat loss of control over drug use is progressively established afterextended access to self-administration (Ahmed and Koob, 1998;

240 O. George, G.F. Koob / Neuroscience and Biobehavioral Reviews 35 (2010) 232–247

Fig. 2. Neurocircuitry of addiction. Schematic representation of the prefrontal cortex and its connections with the different subcortical systems or modules mediating negativeemotional states (orange), stress (red), pain (yellow), incentive salience (green), habits (beige), and decision-making (blue). The incentive salience/mesolimbic dopamine systemmodule includes the dopamine neurons in the VTA projecting to the nucleus accumbens shell. Key processes are incentive salience, reward, and prediction error. The decision-making/prefrontal cortex module includes bidirectional connections of the PL, IL, AAC, and OFC. Key cognitive processes include working memory, reward evaluation andexpectation, motor planning, and attention. The habit/striatal module receives and sends segregated connections with the prefrontal cortex and pallidum, respectively.Key processes in this module are action-outcome associations, reward (NAC shell, VP), expression of sensitization and conditioned reward (NAC shell), stimulus responseassociations, habits (NAC core and DS), approach behavior, retrieval and reconsolidation of drug associated memory (NAC core), and orienting and attention (DS). The negativeemotional state/extended amygdala module represents a series of densely interconnected structures (CeA, BNST, NAC shell) with important connections with the brainstem,BLA, and hypothalamus. Key processes in the extended amygdala are the expression of conditioned responses, fear (CeA), the stress response, HPA control, negative emotionalstates, extinction of drug-seeking (CeA, BNST), stress-induced reinstatement (BNST), and autonomic responses (CeA, BNST). The stress/HPA axis module includes the PVN, aPit,and adrenals. Key processes include stress responses, immune suppression, energy storage and expenditure, and emotions. The pain/spinothalamocortical module includes thespinoreticulo-mesencephalo-thalamic tract, PB, PAG, RVM, VPL, CL, CM, PF, and CeA. Key processes include nociception, negative emotional state, pain expectancy (PAG, ACC),analgesia, and conditioned analgesia. These modules are interconnected but relatively independent in their functioning. Some structures are implicated in different modules,but it is important to note that segregated neuronal populations with different neuronal connections may be involved. Connections ending with an arrow are mainly excitatory,whereas connections with a dot are inhibitory. In many cases, such as with the VTA and CeA, the prefrontal cortex connects with local interneurons (that are not represented)that change the excitatory connection to an inhibitory connection onto the output neurons of the given structure. Abbreviations: Prefrontal cortex (PFC): prelimbic cortex(PL), infralimbic cortex (IL), orbitofrontal (OFC), anterior cingulate cortex (ACC), dorsal peduncular cortex (DP), agranular insular cortex (AI). Basal ganglia: globus pallidus(GP), ventral pallidum (VP), dorsal striatum (DS), nucleus accumbens (NAC), subthalamic nucleus (STN), substantia nigra pars compacta (SNc), substantia nigra pars reticulata(SNr). Hypothalamus: suprachiasmatic nucleus (SCN), dorsomedial hypothalamus (DMH), perifornical area (PfA), lateral hypothalamus (HTL), paraventricular nucleus of thehypothalamus (PVN). Extended amygdala: central nucleus of the amygdala (CeA), bed nucleus of the stria terminalis (BNST), intercalated cell mass (ICM), basolateral amygdala(BLA). Thalamus: mediodorsal nucleus (MD), ventral anterior (VA) and ventral lateral (VL), centromedian (CM), central lateral (CeL), paracentral (PaC), parafascicular (PF),intermediodorsal (IMD), paraventricular (PV), ventroposteromedian (VPM), ventroposterolateral (VPL), medial geniculate nucleus (MGm), posterior intralaminar nucleus( s (PPn prima( ), infe

DsetClmFd

PIN). Brainstem: ventral tegmental area (VTA), pedunculopontine tegmental nucleuucleus (LTg), parabrachial nucleus (PB), rostroventromedial medulla (RVM). Other:S1), secondary somatosensory cortex (S2), subiculum (Sub), superior colliculus (SC

eroche-Gamonet et al., 2004) and can be predicted by high impul-ivity (Belin et al., 2008; Dalley et al., 2007a). Despite accumulatingvidence that limited drug exposure induces neuronal changes inhe prefrontal cortex (Ben-Shahar et al., 2007; Bowers et al., 2004;
respo et al., 2002), there was little evidence, until recently, of
ong-lasting neuronal adaptations of the prefrontal cortex in animalodels of the loss of control over drug use (Ben-Shahar et al., 2007;

errario et al., 2005; Seiwell et al., 2007). Moreover, recent reportsemonstrated that at least in one model of loss of control (i.e.,

T), laterodorsal tegmental nucleus (LDTLTD), raphe nucleus (RN), lateral tegmentalry motor cortex (M1), secondary motor cortex (M2), primary somatosensory cortexrior colliculus (IC), anterior pituitary (aPit).

extended access to cocaine self-administration) there were no long-lasting impairments of prefrontal cortex cognitive function, suchas response inhibition and sustained attention (Dalley et al., 2005,2007b). 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 underhigh cognitive demand and high-incentive conditions. A conditionwith high cognitive demand in this context refers to an experimen-tal paradigm in which the cognitive processes necessary to solve a

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ask reach their limit or capacity, whereas a high-incentive con-ition refers to an experimental paradigm that motivates a highegree of approach behavior due to the high attractiveness of theositive reinforcer. These conditions may particularly challenge theorsomedial prefrontal cortex and orbitofrontal cortex. Moreover,orking memory under a high-incentive condition has been shown

o be a sensitive measure of the integrity of the prefrontal cortexKrawczyk et al., 2007; Taylor et al., 2004).

Recent studies using animal models of compulsive drug useemonstrated that independent of any premorbid condition, aistory of drug dependence induced persistent impairments inorking memory (George et al., 2008) and sustained attention

Briand et al., 2008) that correlated with decreased density ofeurons and oligodendrocytes but not astrocytes in the dorsome-ial and orbital prefrontal cortex (George et al., 2008), dopamine2 receptor mRNA in the medial and orbital prefrontal cortex,nd D2 receptor protein in the medial prefrontal cortex (Briandt al., 2008). Additionally, long-lasting alterations in N-methyl--aspartate (NMDA) function have also been observed in theseodels (Ben-Shahar et al., 2009). Interestingly, working memory

mpairments were only observed under high cognitive demandsnd high incentive conditions, suggesting an imbalance between aypoactive cognitive system that controls decision-making underigh cognitive demands and an overactive incentive salience sys-em (Bechara, 2005). An intriguing finding was that working

emory impairments were not predicted by the amount of cocainentake but rather by the relative increase in excessive cocaine intakeompared with baseline self-administration under limited accessonditions (George et al., 2008). These results suggested that pre-rontal cortex dysfunction may not only be a simple consequencef drug use but may also contribute to a feed-forward mechanismn the loss of control over drug intake during the transition to drugependence.

Loss of control and failure of self-regulation have been hypoth-sized to be significant contributory causes of many psychosocialathologies, including depression, anxiety, chronic pain, post-raumatic stress disorder, eating disorders, gambling, obsessiveompulsive disorders, and addiction (Baumeister et al., 2003).onsidering the relative independence of these disorders andhe differential involvement of the stress, pain, emotion, habits,ecision-making, and reward systems in these disorders, it is likelyhat loss of control is not a unitary mechanism mediated by the pre-rontal cortex. The heterogeneity of the prefrontal cortex and theegregated anatomical connections between the prefrontal cortexnd the subcortical modules described above suggest that thereay be multiple mechanisms of loss of control mediated by a fail-

re of different subregions of the prefrontal cortex in controllingubcortical structures. Loss of control over stress, anxiety, reward,ain, habits, and decision-making during the different stages ofddiction may lead to an increased risk of exposure to the drug,ncreased drug seeking and drug taking, increased relapse, andncreased vulnerability to the transition to addiction.

1.1. Loss of control over stress

Stress reactivity is highly dependent on whether the stress cane controlled or not. Stressful and aversive events are much lessetrimental when the individual has control over the stress. Lackf control over stress may be a key factor in the development of anx-ety, depression, posttraumatic stress disorder, and drug addictionAmat et al., 2005). Many studies in animals have demonstrated
he key role of brainstem nuclei, such as the dorsal raphe and locusoeruleus, in encoding the response to uncontrollable stress, butontrol over these stress circuits may be achieved by the prefrontalortex through a glutamatergic projection from the infralimbic andrelimbic 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 infralim-bic cortices in rats blocks the inhibition of dorsal raphe neuronsobserved under controllable stress as well as the behavioral con-sequence of a controllable stress, demonstrating the role of theprefrontal cortex in the control of stress (Amat et al., 2005). Indi-vidual differences in the strength of the connection between theprefrontal cortex and brainstem nuclei involved in the autonomic,psychological, and behavioral responses to stress might representa key mechanism whereby loss of control over stress may lead toincreased vulnerability to anxiety, depression, posttraumatic stressdisorder, and addiction. The medial prefrontal cortex in rats has alarge number of glucocorticoid receptor-positive neurons that canbidirectionally control stress reactivity of the HPA axis through acti-vation of the anterior cingulate, prelimbic, or infralimbic cortices(Diorio et al., 1993; Figueiredo et al., 2003a,b; Sullivan and Gratton,1999). Lesions of the prelimbic cortex increase ACTH and corticos-terone responses to stress, whereas lesions of the infralimbic cortexhave the opposite effect. This differential control is attributed todifferential projections of the prelimbic and infralimbic cortices tostructures mediating either stress inhibition (ventrolateral preop-tic area, dorsomedial hypothalamus, and peri PVN; Hurley et al.,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, lesionsof the prelimbic cortex enhance stress-induced c-fos expressionand CRF mRNA expression in neurosecretory neurons (related tothe HPA axis) of the PVN, whereas lesions of the infralimbic cortexhad opposite effects but also increased Fos induction in autonomicneurons (sympathoadrenal) of the PVN (Radley et al., 2006). Alto-gether, these results suggest that the dorsal prefrontal (prelimbic)cortex exerts inhibitory control over the HPA axis, whereas theventral prefrontal cortex exerts positive control over the HPA axiswhile exerting inhibitory control over central autonomic responses.With regard to the control of the prefrontal cortex over the dorsalraphe, the control of the prelimbic cortex over the PVN is medi-ated 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 andnorepinephrine systems in the extended amygdala to produce anegative emotional state that characterizes the withdrawal/negativeaffect stage of addiction.

11.2. Loss of control over emotion

Emotion plays a key role in adaptation as well as influencescognitive function and behavioral responses in a variety of sit-uations. Emotion is often viewed as a bottom-up modulator ofdecision-making, learning, and memory or even pain and percep-tion, but often neglected is the fact that processing of emotionalinformation can also be regulated via top-down mechanisms suchas suppression or reappraisal (Johnstone et al., 2007; Ochsner etal., 2002, 2004; Phan et al., 2005). Such cognitive control maydownregulate neural, physiological, and behavioral responses toemotion-eliciting stimuli (Jackson et al., 2000). It is well estab-lished that recruitment of a prefrontal network, including the dorsaland ventral prefrontal cortex and orbitofrontal cortex, is necessaryto reduce activation of the amygdala by emotion-eliciting stimuli(Urry et al., 2006; Johnstone et al., 2007). Glutamatergic neuronsin the ventral prefrontal cortex project to GABAergic inhibitoryneurons in the capsular division of the CeA and inhibit the out-
put of the CeA (Royer and Pare, 2002). Numerous studies havedemonstrated that negative emotional states can lead to impulsiveaggressive behavior, that important individual differences exist inthe capacity of the individual to suppress aggressive thoughts, andthat this effect is under the control of the prefrontal cortex, partic-

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larly the orbitofrontal cortex, ventromedial prefrontal cortex, andorsolateral prefrontal cortex in humans (Davidson et al., 2000).ne mechanism to explain the control of the prefrontal cortexver aggressive behavior is a powerful inhibition of the amygdalay the prefrontal cortex. Individuals who use more emotion reg-lation strategies, such as spontaneous reappraisal, have a loweregative emotional state and greater physical and psychologicalell being (Drabant et al., 2009). Individual differences in emotion

egulation strategies and failure of control over emotion throughypofunction of the prefrontal cortex may represent a key neu-opsychological mechanism responsible for increased vulnerabilityo anxiety, depression, and addiction.

1.3. Loss of control over incentive salience

Incentive salience represents a powerful mechanism thatransforms neutral cues into powerful motivational magnets elic-ting approach and guiding drug-related behavior (Robinson anderridge, 1993). Intense incentive motivation attribution is consid-red to have a major role in different psychopathologies. Executiveontrol over incentive salience is essential to maintain goal-irected behavior and flexibility of stimulus-response associations.he prefrontal cortex sends glutamatergic projections directly toesocortical dopamine neurons in the VTA, exerting excitatory

ontrol on dopamine in the prefrontal cortex. Interestingly, the pre-rontal cortex does not project directly onto mesolimbic dopamineeurons (Sesack and Carr, 2002). In contrast, prefrontal cortex neu-ons inhibit mesolimbic dopamine neurons through activation ofABAergic relay neurons in the VTA or nucleus accumbens (Carrnd Sesack, 2000; Sesack and Pickel, 1992). Thus, the prefrontal cor-ex is in a good position to inhibit incentive salience and suppressonditioned behavior when a salient cue is presented to the subject.onsistent with this notion, it has been shown that appetitive stim-li activate the prefrontal cortex and that lesions of the prefrontalortex induce impulsivity (Bechara et al., 2000; Jentsch and Taylor,999). Withdrawal from cocaine is associated with decreased pre-rontal activity (Goldstein and Volkow, 2002) and extrasynapticlutamate release as well as decreased dopamine release in theucleus accumbens (Moussawi et al., 2009; Weiss et al., 1992).

n contrast, cue-induced reinstatement of drug seeking-behaviornduces a dramatic increase in prefrontal activity and glutamateelease in the nucleus accumbens (Moussawi et al., 2009). Theower basal tone of the prefrontal-glutamatergic system associated

ith an exaggerated phasic response during relapse combined witheduced basal dopaminergic tone elicits a dramatic glutamatergicesponse that may mediate compulsive drug seeking by disinhibit-ng the control of behavior by reward-associated cues. Individualifferences in prefrontal cortical control of incentive salience mayepresent a key mechanism to explain individual differences in theulnerability to addiction, and excessive attribution of incentivealience to drug-related cues may lead to excessive drug intake,ompulsive behavior, and relapse.

1.4. Loss of control over pain

Self-regulation is a key mechanism involved in the control ofoth acute and chronic pain (Morley et al., 2005; Perez-Pareja etl., 2005; Solberg Nes et al., 2009). Control over pain is a key evolu-ionary advantage because it allows individuals to disengage fromain to fight or escape in the presence of injury. Converging evi-ence suggests that the prefrontal cortex mediates the control of
ain. Electrical stimulation of the prefrontal cortex in rats inducesntinociceptive effects (Cooper, 1975; Zhang et al., 1998), and paintimuli and the expectancy of pain activate the prefrontal cor-ex (Casey et al., 1996; Iadarola et al., 1998; Peyron et al., 2000;loghaus et al., 1999). Key prefrontal structures involved in the con-

trol of pain are the anterior cingulate cortex and insular cortex. Bothregions express a high number of opioid receptor-positive neuronsand project to the amygdala and PAG, two downstream struc-tures mediating opioid-mediated analgesia and whose activationleads to a suppression of pain-related behavior and the subjectiveeffects of pain. The prefrontal cortex is also hypothesized to con-trol the midbrain-thalamic-cingulate nociceptive pathway thoughdescending fibers (Lorenz et al., 2003).

11.5. Loss of control over habits and decision-making

The concept of self-control in decision-making is a complex cog-nitive process that requires parallel analysis of multiple sourcesof information, evaluation of outcomes, and selection of motorpatterns. Loss of control in decision-making leads to unadaptedbehavior and is particularly prominent in situations with highincentives and high cognitive demand (George et al., 2008). Twokey control mechanisms in decision-making are the ability to shiftbetween different behavioral strategies, such as habit and goal-directed behavior, and attentional set-shifting to disengage froma once relevant stimulus dimension to a new set of stimuli that arepotentially more relevant after a change in environmental condi-tions. The development of habit behavior is a particularly efficientstrategy when environmental conditions do not change becausehabitual responses do not require evaluation of outcomes. More-over, habit responses can be triggered by conditioned stimuli andrequire very limited cognitive resources, but inhibition of habitsin favor of goal-directed behavior is critical when environmentalconditions change to ensure adapted behaviors. A key structuremediating control over decision-making is the dorsolateral pre-frontal cortex in humans and the dorsomedial prefrontal cortex inrodents (anterior cingulate cortex, prelimbic cortex; Dias-Ferreiraet al., 2009; Hare et al., 2009; Birrell and Brown, 2000; Block etal., 2007; Dias et al., 1997; Ragozzino et al., 2003). Genetic vari-ation at the serotonin transporter-linked polymorphism regionhas been associated with impaired amygdala control by the pre-frontal cortex and may lead to poor decision-making (Roiser etal., 2009). Individual differences in the ability of the dorsolateralprefrontal cortex to modulate the ventromedial prefrontal cor-tex might be due to differences within the dorsolateral prefrontalcortex or to differences in connectivity between the dorsolateralprefrontal cortex and the subregions of the prefrontal cortex andthe striatum. Particularly interesting for the control of decision-making is the fact that the prefrontal cortex contains a high numberof GABAergic inhibitory interneurons and that pyramidal neuronscan make both pyramidal-pyramidal connections and pyramidal-interneuron connections through extensive horizontal connections(Goldman-Rakic, 1995; Tanaka, 1999). Thus, pyramidal neurons cansimultaneously activate and inactivate different corticocortical andcorticostriatal circuits and facilitate behavioral flexibility by shift-ing attentional focus and selecting different motor patterns to adoptnew strategies.

12. Conclusions

Important individual differences in the different stages of theaddiction process, as well as in the vulnerability to the transition toaddiction have been observed in humans and animals. We reviewedstudies demonstrating that the concept of self-regulation combinedwith the concept of modularity of cognitive function may help tounderstand individual differences in the vulnerability to drugs and
to the transition to addiction. As explained above, there are impor-tant individual differences in the different stages of addiction aswell as in key brain functions critical for the development of addic-tion, such as attention, decision-making, reward, emotion, pain, andstress (Crowley et al., 1998; de Wit et al., 1986; Deroche-Gamonet et

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l., 2004). Flexible, goal-directed behaviors require an adapted cog-itive control system for organizing, selecting, and consolidating

nformation resulting from the different modules into a coherentnd unified experience (Treisman, 1996). Neuroanatomical, brainesion, and site-specific pharmacological modulation studies of therefrontal cortex have revealed the heterogeneity of the prefrontalortex and the high functional specialization of its different sub-egions (Robbins, 2000). The prefrontal cortex and its differentubregions target the main sources of all neurotransmitter systemsnd have been hypothesized to represent this cognitive controlystem (Baddeley, 1996; Robbins, 2000; Ridderinkhof et al., 2004;oldman-Rakic, 1987).

We suggest that the concept of self-regulation, combined withhe concept of modularity of cognitive function, may help tonderstand the neural basis of the individual differences in theulnerability to drug addiction. Indeed, dysfunction of a specificubregion of the prefrontal cortex may lead to loss of control overspecific module, leading, for instance, to a sensitization of incen-

ive salience in one individual and to a hyperreactivity of the stressystem in another individual. Therefore, the failure of a specificodule may differ from one individual to another and may rep-

esent a neuropsychobiological mechanism underlying individualifferences in the vulnerability to drug addiction.

Several key potential modules may be identified, includ-ng the incentive salience mesolimbic dopamine system

odule, stress/HPA axis module, habit/striatum mod-le, negative emotional state/extended amygdala module,ain/spinothalamocortical module, and the decision-aking/prefrontal cortex module. Such modules are driven

y bottom-up signals from both the external world and intero-eptive signals and by top-down signals from higher order systemediating cognitive control. It is important to note that the mod-

les described in this review do not correspond fully to the conceptriginally defined by Fodor (1983). One of the essential definingeatures of a Fodorian module is functional autonomy; that is, itsunction is little, if any, controlled by top-down cognitive control.n contrast, the brain systems identified here are hypothesized toe under tight top-down control by the prefrontal cortex, at least

nitially before the transition to addiction. These systems are notodular in the strong sense defined by Fodor but begin to resemble

o Fodorian modules only after the transition to addiction.The present multi-system framework may be useful to better

nderstand the different patterns of drug addiction across differentndividuals and different drugs. It can be hypothesized that individ-als with increased sensitivity of the incentive salience mesolimbicopamine system module and the habit/striatum system may bearticularly vulnerable to cocaine and methampetamine abusehrough an overvaluation of drug reward and drug-related cuesuring the binge/intoxication and preoccupation/anticipation stagesWise, 2002; Jentsch and Taylor, 1999). Individual differences inhe function of the incentive salience mesolimbic dopamine sys-em and the habit/striatum modules may be particularly importantor craving-type 1 (or reward craving) defined as craving for theewarding effects of drugs and usually induced by stimuli that haveeen paired with drug self-administration such as environmentalues, as opposed to craving-type 2 (or withdrawal relief craving)hich is conceptualized as an excessive motivation for the drug

o obtain relief from a state change characterized by anxiety andysphoria after protracted abstinence (Heinz et al., 2003). Individ-al differences in the pain/spinothalamocortical module may beey for the transition to opiate and alcohol dependence. Decreased
ensitivity of the pain system is associated with a higher vul-erability for opiate dependence (Lehofer et al., 1997), whereasyperactivity of the pain system may predict cue-induced craving
n abstinent opiate abusers (Ren et al., 2009). Moreover, consider-ng the importance of the endogenous opiate system in alcoholism,


it is likely that vulnerability of the pain/spinothalamocorticalor spinoparabrachial module (Besson, 1999) might be a riskfactor for the development of alcoholism and dependence onother drugs (Herz, 1997). Hyperactivity of the negative emotionalstate/extended amygdala module is associated with increasedemotional pain and stress and might be a risk factor for druguse as a self-medication for emotional pain, dysphoria, and stress(Khantzian, 1997). Vulnerability in the pain/spinothalamocorticalmodule may lead to increased physical and emotional pain dur-ing withdrawal and intense craving-type 2, thus contributing tothe preponderant role of the withdrawal/negative affect stage thatcharacterizes opiate and alcohol addiction. Increased reactivity ofthe stress/HPA axis module may be critical in the initiation of drugintake and for the maintenance of drugs that have little initialrewarding value, such as nicotine, as it potentiates the reinforc-ing effects of drugs (Piazza and Le Moal, 1998). Vulnerability ofthe stress/HPA axis and the negative emotional state/extendedamygdala module may contribute to the different patterns oftobacco smoking behavior. Indeed, individuals who smoke regu-larly but who will always limit their tobacco intake (“chippers”)show no signs of withdrawal and report less stress and bet-ter stress coping responses than subjects dependent on tobacco(Shiffman, 1989) suggesting that hyperaactivity of the stress/HPAaxis and the negative emotional state/extended amygdala mod-ule may underlie the differences between chippers and dependentsmokers. Finally, hypoactivity of the decision-making/prefrontalcortex module may lead to a loss of control over drug intake despitenegative consequence because of impaired inhibitory control anddecision-making leading to choices of immediate rewards overdelayed rewards (Goldstein and Volkow, 2002). Although the ini-tial failure of a specific module might be specific to one stage ofthe addiction cycle and to a specific drug, in a given individual thetransition to addiction is ultimately likely to be associated with aprogressive and generalized loss of control over many, if not all,cognitive modules.

Acknowledgements

This is publication number 20330 from The Scripps ResearchInstitute. This work was supported by National Institutes of Healthgrants DA04398, DA10072, DA04343, and DA023597 from theNational Institute on Drug Abuse, AA08459 and AA06420 from theNational Institute on Alcohol Abuse and Alcoholism, and the Pear-son Center for Alcoholism and Addiction Research. The authorswould like to thank Taryn Grieder and Prof. Michel Le Moal forhelpful comments on the manuscript and Michael Arends for hiseditorial assistance.

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