PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of ascpBioMed CentralBiomed Central Web Sitesearchsubmit a manuscriptregisterthis articleAddiction Science & Clinical Practice
 
Addict Sci Clin Pract. 2010 December; 5(2): 4–14.
PMCID: PMC3120118

Addiction and Cognition

Abstract

The brain regions and neural processes that underlie addiction overlap extensively with those that support cognitive functions, including learning, memory, and reasoning. Drug activity in these regions and processes during early stages of abuse foster strong maladaptive associations between drug use and environmental stimuli that may underlie future cravings and drug-seeking behaviors. With continued drug use, cognitive deficits ensue that exacerbate the difficulty of establishing sustained abstinence. The developing brain is particularly susceptible to the effects of drugs of abuse; prenatal, childhood, and adolescent exposures produce long-lasting changes in cognition. Patients with mental illness are at high risk for substance abuse, and the adverse impact on cognition may be particularly deleterious in combination with cognitive problems related to their mental disorders.

Drug addiction manifests clinically as compulsive drug seeking, drug use, and cravings that can persist and recur even after extended periods of abstinence. From a psychological and neurological perspective, addiction is a disorder of altered cognition. The brain regions and processes that underlie addiction overlap extensively with those that are involved in essential cognitive functions, including learning, memory, attention, reasoning, and impulse control. Drugs alter normal brain structure and function in these regions, producing cognitive shifts that promote continued drug use through maladaptive learning and hinder the acquisition of adaptive behaviors that support abstinence.

In a 2005 review, Steven Hyman stated the current neurological conception of drug abuse concisely: Characterizing addiction as a disease of “pathological learning,” he wrote, “[A]ddiction represents a pathological usurpation of the neural mechanisms of learning and memory that under normal circumstances serve to shape survival behaviors related to the pursuit of rewards and the cues that predict them.”

This article reviews current knowledge on the cognitive effects of drugs and their neurological underpinnings. These effects may be particularly disruptive when individuals are exposed to drugs during brain development, which lasts from the prenatal period through adolescence, and in individuals with mental disorders. An understanding of these issues will help substance abuse clinicians identify and respond to cognitive changes that affect patients’ responses to treatment.

A MULTISTAGE PROCESS

Recent reviews characterize addiction as a two-stage process. In the first stage, the individual’s occasional drug taking becomes increasingly chronic and uncontrolled. The neurological source of these symptoms is drug-induced deregulation of the brain’s reward system (Feltenstein and See, 2008). Normally, increased dopamine signaling within this system—specifically, in the ventral striatum or nucleus accumbens (NAc)—produces pleasurable feelings that orient organisms to seek and perform life-sustaining conditions and activities, such as locating supportive environments, eating, and having sex. Drugs of abuse hyperactivate this system, triggering abrupt and large increases in NAc dopamine signaling, producing intense sensations that motivate additional drug taking, and promoting the formation of maladaptive drug-stimulus associations (Feltenstein and See, 2008).

Individuals in the second stage of the addictive process present additional clinical features, including withdrawal symptoms during early abstinence, persistent vulnerability to relapse, and alterations in decisionmaking and other cognitive processes. Although modification of the dopaminergic reward system remains important at this stage, it probably is not sufficient to maintain these complex and long-lasting changes. Kalivas and Volkow (2005) summarize evidence implicating drug-induced alterations in signals carried by the neurotransmitter glutamate from the brain area that is primarily associated with judgment—the prefrontal cortex—to the NAc. Le Moal and Koob (2007) emphasize changes in brain stress circuits and negative reinforcement (i.e., effects that motivate drug taking by causing discomfort during abstinence, such as the onset of withdrawal symptoms). Thus, whereas early drug use fosters maladaptive drug-stimulus associations that contribute to drug seeking and use, later stages disrupt cognitive and other processes that are important for successful abstinence.

The full extent of drugs’ impacts on cognition is not yet known, but research indicates that addicted individuals have alterations in brain regions including the striatum, prefrontal cortex, amygdala, and hippocampus (Jones and Bonci, 2005; Kalivas and Volkow, 2005; Kelley, 2004; Le Moal and Koob, 2007). These same regions underlie declarative memory—the memories that define an individual, without which it would be difficult to generate and maintain a concept of self (Cahill and McGaugh, 1998; Eichenbaum, 2000; Kelley, 2004; Setlow, 1997). Drugs’ capacity to act upon the substrates of declarative memory suggests that their impact on cognition is potentially extremely far-reaching.

COGNITIVE EFFECTS OF ACUTE DRUG ADMINISTRATION

Clinicians often observe that patients undergoing treatment for addiction become highly vulnerable to relapse when they return to contexts or environments where their addiction developed (Hyman, 2005; See, 2005). Clinical research confirms that cues associated with substance abuse elicit physiological responses and cravings for drugs (Franklin et al., 2007). Laboratory animals, too, develop powerful associations and cue-response behaviors in the presence of drug-related stimuli. For example, animals given a drug in one compartment of a double cage subsequently will gravitate to that compartment more than to the alternative compartment. This phenomenon, known as conditioned place preference, has been demonstrated in studies using nicotine, ethanol, amphetamine, methamphetamine, cocaine, morphine, cannabis, and caffeine (Bardo and Bevins, 2000).

The Formation of Drug-Stimulus Associations

The multistage model of addiction attributes addicted individuals’ strong responses to drug cues to a learning process that inculcates powerful drug-stimulus associations (e.g., Robinson and Berridge, 2000). In this view, the individual taking a drug perceives his or her present surroundings as highly significant (salient) and makes exceptionally strong mental connections between features of those surroundings and the intense pleasure of the drug. Subsequently, when he or she re-encounters those features, the powerful associations reassert themselves, consciously or subconsciously, and are experienced as prompts for drug seeking and drug taking. Consistent with this account, exposing addicted individuals to cues that they associate with substance abuse elicits, along with physiological responses and drug cravings, changes in the activity levels of brain regions involved in learning and memory (i.e., striatum, amygdala, orbitofrontal cortex, hippocampus, thalamus, and left insula) (Franklin et al., 2007; Volkow et al., 2006).

The acute effects of amphetamine, nicotine, and cocaine fit straightforwardly into this scenario. Each of these drugs has been shown to acutely enhance learning and/or attention (Del et al., 2007; Kenney and Gould, 2008; Mattay, 1996). For example, the idea that smoking is a cognitive enhancer is well accepted by researchers and the general public. Numerous studies have confirmed that laboratory animals’ cognitive processes improve immediately following administration of nicotine (Kenney and Gould, 2008). Similar findings in early studies with human smokers were not conclusive, because the study participants were smokers who had received nicotine following a period of abstinence. The observed enhancements might have reflected the reversal of withdrawal effects, rather than improvements over their normal cognitive powers. A subsequent review of the literature, however, suggests that acute nicotine enhances reaction time and attention in nicotine-naïve individuals (Swan and Lessov-Schlaggar, 2007). Cocaine produced similar effects in a study of rats that were treated with the drug and then exposed to a sensory stimulus; the animals exhibited enhanced neural activation when later re-exposed to the stimulus (Devonshire, Mayhew, and Overton, 2007).

Although all drugs of abuse foster the learning of strong drug-stimulus associations and cue-induced drug seeking, some appear to have mixed effects on other types of learning and cognition. For example, a clinical study of the acute effects of morphine and oxycodone concluded that these drugs have variable impacts on cognition: Both improved men’s recall of prose just slightly, but morphine slightly impaired both sexes’ performance on a test of working memory in which they were asked to repeat a set of digits in reverse order (Friswell et al., 2008). In another study, mice were given morphine or saline and trained to run away when a light signaled that a foot shock was impending; although the morphine-treated mice scored higher on the frequency and quickness with which they avoided shocks, the researchers attributed this to increased motor activity rather than enhanced learning (Aguilar, Miñarro, and Simón, 1998). In contrast to the effects of opioids on cognition, those of alcohol are clear, though bidirectional: High doses disrupt cognitive processes (Ryback, 1971), while low doses can enhance learning (Gulick and Gould, 2007; Hernández, Valentine, and Powell, 1986).

The Persistence of Drug-Stimulus Associations

Recent research has sought to account for the strikingly long-lasting ability of maladaptive drug-stimulus associations to influence behavior and provoke relapse. Studies have shown that many abused substances can reshape the communication pathways between neurons (synaptic plasticity), which could contribute to both the formation and the persistence of maladaptive drug-stimulus associations.

Cocaine and nicotine can directly induce one form of synaptic plasticity, the strengthening of neural connections via a process known as long-term potentiation (LTP; see Learning in the Mind and Brain on page 8 and Table 1) (Argilli et al., 2008; Kenney and Gould, 2008). Amphetamine can enhance LTP (Delanoy, Tucci, and Gold, 1983). Marijuana activates the endocannabinoid system, resulting in inhibition in some instances and facilitation in others of both LTP and long-term depression (LTD), another form of synaptic plasticity in which connections between neurons become less responsive (Carlson, Wang, and Alger, 2002; Nugent and Kauer, 2008; Sullivan, 2000). Ethanol consistently disrupts LTP while enhancing LTD (Yin et al., 2007). Morphine inhibits LTP of neurons that exhibit inhibitory control of neural activity via the neurotransmitter gamma-aminobutyric acid (GABA) (Nugent and Kauer, 2008). Inhibition of GABA activity could lead to an overall increase in neural activity throughout the brain, which might lead to the formation of stronger associations than would normally occur, including maladaptive drug-context associations.

TABLE 1
Drug Effects on Synaptic Plasticity

Strengthening the evidence that drugs foster long-lasting drug-stimulus associations by affecting synaptic plasticity, studies have demonstrated that the same proteins that participate in the sequential biochemical reactions (cell signaling cascades) that control synaptic plasticity (see Figure 1) come into play in drug-seeking behaviors. For example, in one experiment, researchers showed that when rats went to a cage area that they had been trained to associate with cocaine, the levels of proteins associated with learning—extracellular signal-regulated protein kinase (ERK), cyclic AMP response element-binding (CREB), Elk-1, and Fos—increased in their NAc (Miller and Marshall, 2005). Moreover, when the rats were treated with a compound that suppresses ERK, they stopped preferring that cage area over one in which they had received saline and showed a decrease in three biochemical participants in LTP (CREB, Elk-1, and Fos) in the NAc.

FIGURE 1
A Cell Signaling Cascade in Learning and Memory

COGNITIVE DEFICITS IN CHRONIC DRUG ABUSE

Drug abusers who progress to the second stage of addiction are subject to withdrawal when they initiate abstinence. Many drugs produce cognition-related withdrawal symptoms that may make abstinence more difficult. These include:

Nicotine provides a familiar example of cognitive changes in withdrawal. In both chronic smokers and animal models of nicotine addiction, cessation of nicotine administration is associated with deficits in working memory, attention, associative learning, and serial addition and subtraction (Bell et al., 1999; Blake and Smith, 1997; Davis et al., 2005; Hughes, Keenan, and Yellin, 1989; Jacobsen et al., 2006; Mendrek et al., 2006; Raybuck and Gould, 2009; Semenova, Stolerman, and Markou, 2007). Moreover, it has been shown that the severity of decreases in cognitive performance during periods of smoking abstinence predicts relapse (Patterson et al., 2010; Rukstalis et al., 2005). Although these deficits usually dissipate with time, a dose of nicotine will rapidly ameliorate them (Davis et al., 2005)—a situation that may contribute to some relapses. Thus, chronic substance abuse can lead to cognitive deficits that are particularly pronounced during early periods of abstinence.

While the cognitive deficits associated with withdrawal from drugs are often temporary, long-term use can also lead to lasting cognitive decline. The nature of deficits varies with the specific drug, the environment, and the user’s genetic makeup (see Genes, Drugs, and Cognition on page 11). In general, however, they impair the ability to learn new patterns of thought and behavior that are conducive to successful response to treatment and recovery.

For example, long-term cannabis users have impaired learning, retention, and retrieval of dictated words, and both long-term and short-term users show deficits in - time estimation (Solowij et al., 2002), although how long these deficits persist is not yet known. As another example, chronic amphetamine and heroin users show a deficits in a range of cognitive skills, including verbal fluency, pattern recognition, planning, and the ability to shift attention from one frame of reference to another (Ornstein et al., 2000). The decisionmaking deficits resembled those observed in individuals with damage - to the prefrontal cortex, suggesting that both drugs alter function in that brain area (Rogers et al., 1999).

A pair of recent studies suggests that some meth- amphetamine-induced cognitive losses may be partially recouped with extended abstinence (Volkow et al., 2001; Wang et al., 2004). Evaluated when abstinent for less than 6 months, chronic methamphetamine abusers scored lower than unexposed controls on tests of motor function, memory for spoken words, and other neuropsychological tasks. The deficits were associated with a comparative scarcity of dopamine transporters (proteins that regulate dopamine) and reduced cellular activity (metabolism) in the thalamus and NAc. When retested after 12 to 17 months of abstinence, the drug abusers’ motor function and verbal memory had risen to levels that approached those of the control group, and the gains correlated with a return toward normal transporter levels in the striatum and metabolic levels in the thalamus; however, other neuropsychological deficits remained, along with depressed metabolism in the NAc.

In another study, abusers of 3,4-methylenedioxy-methamphetamine (MDMA, ecstasy) continued to score relatively poorly in tests of immediate and delayed recall of spoken words even after 2.5 years of abstinence (Thomasius et al., 2006). In a study of polydrug abusers who had stated a primary preference for either cocaine or heroin, deficits in executive function—defined as changes in fluency, working memory, reasoning, response inhibition, cognitive flexibility, and decisionmaking—remained after up to 5 months of abstinence (Verdejo-García, and Pérez-García, 2007).

An important question is whether nicotine’s cognitive benefit persists as smoking shifts from sporadic to chronic. In some studies with animals, chronic nicotine administration improved cognitive capacities such as attention, but other studies found that initial improvements waned with chronic treatment (Kenney and Gould, 2008). Furthermore, several recent studies have shown that smoking and a past smoking history are associated with cognitive decline. For example, in one study with middle-aged men and women, smokers’ cognitive speed declined nearly twice as much as non-smokers’ over 5 years; in addition, declines in smokers’ cognitive flexibility and global cognition occurred at 2.4 times and 1.7 times the respective rates of nonsmokers (Nooyens, van Gelder, and Verschuren, 2008). Recent quitters’ scores in these areas were similar to smokers’, and ex-smokers performed at levels intermediate between smokers and nonsmokers.

Similarly, in another study, smokers’ performance deteriorated more over 10 years than nonsmokers’ on tests of verbal memory and speed of visual searching; ex-smokers’ visual search speed slowed more than non-smokers’ as well (Richards et al., 2003). Although some early studies suggested that smoking might retard the cognitive decline associated with Alzheimer’s disease (van Duijn and Hofman, 1991), followup studies failed to confirm this, and others correlated smoking quantity and duration with higher risk for Alzheimer’s disease (Swan and Lessov-Schlaggar, 2007).

Laboratory studies have demonstrated nicotine-related alterations in neuronal functioning that could underlie cognitive decline that persists even after prolonged abstinence. For example, rats’ self-administration of nicotine was associated with a decrease in cell adhesion molecules, a decrease in new neuron production, and an increase in cell death in the hippocampus (Abrous et al., 2002). Such changes could result in long-lasting cognitive changes that contribute to poor decisionmaking and addiction.

DRUGS OF ABUSE AND THE DEVELOPING BRAIN

The human brain continues to develop and consolidate important neural pathways from the prenatal period through adolescence. Throughout these years, the brain is highly malleable, and drug-induced alterations of neural plasticity may deflect the normal course of brain maturation.

Prenatal Exposures

The consequences of prenatal alcohol exposure are well-known: Fetal alcohol spectrum disorders are the leading cause of mental retardation in the United States (Centers for Disease Control and Prevention, 2009). In addition, fetal alcohol exposure increases susceptibility to later substance abuse problems (Yates et al., 1998).

Prenatal exposures to a number of other drugs have significant deleterious effects on cognition and behavior that may not rise to the level of mental retardation. In one study, 5-year-olds whose mothers had used alcohol, cocaine, and/or opiates while pregnant ranked below unexposed controls in language skills, impulse control, and visual attention. There were no significant differences between the two groups of children in intelligence, visual/manual dexterity, or sustained attention; however, both groups placed below the normative means on these measures (Pulsifer et al., 2008). Another study documented memory deficits in 10-year-old children who had been exposed prenatally to alcohol or marijuana (Richardson et al., 2002).

Clinical and laboratory research has implicated pre-natal exposure to methamphetamine in both cognitive deficits and altered brain structure. For example, one study correlated shorter attention span and delayed memory with reduced volume in the putamen (−18 percent), globus pallidus (−27 to −30 percent), and hippocampus (−19 to −20 percent) among 15 children aged 3 to 16 years who were prenatally exposed to the stimulant, compared with controls (Chang et al., 2004). The drug-exposed children also exhibited poorer long-term spatial memory and visual/motor integration. Another study documented structural changes in the frontal and parietal cortex of 3- and 4-year-old children who had been exposed prenatally to methamphetamine (Cloak et al., 2009). In laboratory studies, rats that were treated with methamphetamine during pregnancy gave birth to pups that, when they reached adulthood, were slow to learn spatial relationships and exhibited spatial memory impairment (Acuff-Smith et al., 1996; Slamberová et al., 2005).

The effects of prenatal tobacco exposure are particularly concerning because so many expectant mothers smoke—by one estimate, over 10 percent in the United States (Hamilton et al., 2007). In utero exposure to tobacco byproducts has been linked to cognitive deficits in laboratory animals and human adolescents (Dwyer, Broide, and Leslie, 2008). Some studies suggest that such exposure can lower general intelligence; for example, one found a 12-point gap in full-scale IQ between exposed and unexposed middle-class adolescents (e.g., Fried, Watkinson, and Gray, 2003). In another study, the odds of having attention deficit hyperactivity disorder (ADHD) were more than three times as great for adolescents whose mothers smoked during pregnancy compared with children of nonsmoking mothers (Pauly and Slotkin, 2008).

Cognitive deficits following prenatal exposure to smoking may reflect structural brain changes. In one study, prenatally exposed adolescent smokers had greater visuospatial memory deficits in conjunction with changes in parahippocampal and hippocampal function compared with adolescent smokers not prenatally exposed (Jacobsen et al., 2006). Brain imaging of adolescent smokers and nonsmokers who were prenatally exposed to smoking has revealed reduced cortical thickness (Toro et al., 2008) and structural alterations in cortical white matter (Jacobsen et al., 2007). Furthermore, in rats, prenatal exposure to nicotine decreased memory-related neural activity in the hippocampus and resulted in deficits in active avoidance learning, with male and female prenatally exposed rats showing significantly fewer correct responses as young adults (Vaglenova et al., 2008). These deficits persisted into later adulthood among the male rats, but not the females.

Among the adverse consequences of prenatal drug exposure is a heightened risk of becoming a drug abuser in later life (Fergusson, Woodward, and Horwood, 1998). This is troubling, as it may lead to a downward spiral that manifests across generations and destroys family structures. Multiple factors could contribute to the increased risk of future substance abuse, including the effects of prenatal drug exposure on cognition. As already reviewed, the risk of developing ADHD is greatly increased in adolescents whose mothers smoked during pregnancy (Pauly and Slotkin, 2008). ADHD is often comorbid with substance abuse (Biederman et al., 2008; Molina and Pelham, 2003), suggesting a link between such changes in cognition and future drug abuse. Further work is needed to understand the mechanisms that underlie the increased risk of drug abuse associated with prenatal exposure.

Adolescent Exposure

Adolescence is a high-risk period for substance abuse. Most addicted smokers first formed the habit during adolescence (Khuder, Dayal, and Mutgi, 1999). Adolescent smoking strongly affects cognition. Adolescent smokers scored worse than age-matched nonsmokers on tests of working memory, verbal comprehension, oral arithmetic, and auditory memory (Fried, Watkinson, and Gray, 2006; Jacobsen et al., 2005). These deficits resolved upon cessation of smoking with the exceptions of working memory and arithmetic performance, which remained at comparatively low levels. In rats, nicotine exposure during adolescence was associated with visuospatial attention deficits, increased impulsivity, and increased sensitivity of medial prefrontal cortical dopamine terminals in adulthood (Counotte et al., 2009). In addition, adolescent rats treated with nicotine had long-lasting changes in the sensitivity of the adenylyl cyclase cell signaling cascade (see Figure 1), a second messenger pathway involved in many processes, including learning and memory (Slotkin et al., 2008). These findings fit well with studies demonstrating that nicotine initially can enhance some cognitive processes, but with continued use adaptation can occur, leading to dissipation of these effects and even deficits (for review, see Kenney and Gould, 2008).

Adolescent smoking can foster cognitive decline indirectly, through the promotion of other disorders. For example, adolescent cigarette use is associated with later episodes of depression (Choi et al., 1997), a malady which in turn is associated with negative effects on cognition (Thomas and O’Brien, 2008). A laboratory investigation shed light on this relationship: Adult rats that had been exposed to nicotine during their adolescence proved less sensitive than controls to rewarding/appetitive stimuli and more responsive to stress and anxiogenic stimuli (Iñiguez et al., 2009).

Adolescent exposures to other substances of abuse, such as alcohol, cannabis, and MDMA, also cause persistent disruptions of cognition (Brown et al., 2000; O’Shea, McGregor, and Mallet, 2006; Piper and Meyer, 2004; Stiglick and Kalant, 1982). These findings indicate that the adolescent brain, which is still developing, is susceptible to insult from drug use and abuse, and such insult can result in long-lasting changes in affect and cognition.

DRUGS OF ABUSE AND MENTAL ILLNESS

Drug-related cognitive deficits may be particularly detrimental to the well-being of individuals whose cognitive performance is already compromised by a mental disorder. Moreover, individuals who suffer from mental disorders abuse drugs at higher rates than the general population. Substance abuse is almost twice as prevalent among adults with serious psychological distress or major depressive episodes as among age-matched controls (SAMHSA, 2007, p. 85), and it is estimated that over half of U.S. individuals with drug disorders (excluding alcohol) also have mental disorders (Regier et al., 1990). In a 1986 study, smoking rates approximated 30 percent in population-based controls, 47 percent in patients with anxiety disorder or major depressive disorder, 78 percent in patients with mania, and 88 percent in patients with schizophrenia (Hughes et al., 1986).

The case of smoking and schizophrenia provides one example of a mental disorder that features cognitive deficits in combination with abuse of a drug that causes cognitive decline. As with many comorbidities, effective treatment will likely require untangling the reasons why the two conditions so frequently co-occur:

  • Some evidence suggests that patients with schizophrenia smoke to self-medicate. For example, smoking reverses schizophrenic patients’ deficits in the brain’s ability to adapt its responses to stimuli (sensory gating), which could reduce the capacity to filter information, and might account for some of the cognitive disruption seen in the mental disorder. Researchers have traced this feature of schizophrenia to a variant of the gene for the α7 nicotinic acetylcholinergic receptor subunit (Leonard et al., 2001). Consistent with this viewpoint is an observation that patients smoke less when given the antipsychotic clozapine, which independently alleviates this deficit, than when given haloperidol, which does not (McEvoy, Freudenreich, and Wilson, 1999).
  • It has also been proposed that patients with schizophrenia smoke to alleviate side effects of antipsychotic medication (Goff, Henderson, and Amico, 1992). An observation that supports this idea is that patients with schizophrenia smoke more after receiving the antipsychotic haloperidol than when unmedicated (McEvoy et al., 1995).
  • Another suggested explanation for the link between smoking and schizophrenia is that smoking itself may precipitate schizophrenia in people predisposed to develop the disease. Among schizophrenics, smokers have an earlier onset of illness, require hospital admissions more frequently, and receive higher doses of antipsychotic medications (Goff, Henderson, and Amico, 1992; Kelly and McCreadie, 1999; Ziedonis et al., 1994).

Another cognitive disorder that is strongly associated with smoking is ADHD. Interestingly, the cognitive symptoms associated with ADHD are similar to those displayed during nicotine withdrawal, and both have been attributed to alterations in the acetylcholinergic system (Beane and Marrocco, 2004; Kenney and Gould, 2008). The high prevalence of smoking among individuals with ADHD (Lambert and Hartsough, 1998; Pomerleau et al., 2003) may be an attempt to self-medicate, because acute nicotine use can reverse some ADHD attentional deficits (Conners et al., 1996). The desire to avoid withdrawal may be a particularly strong motivation for continued smoking in this population, as individuals with ADHD suffer more severe withdrawal symptoms than age-matched controls without the disorder (Pomerleau et al., 2003), and increases in ADHD symptoms following smoking cessation are associated with a greater risk of relapse (Rukstalis et al., 2005). As noted above, however, continued smoking in itself can lead to cognitive decline (Nooyens, van Gelder, and Verschuren, 2008; Richards et al., 2003), and hence might exacerbate ADHD-related symptoms.

Along with nicotine, ADHD is also associated with abuse of stimulants, such as amphetamine and cocaine, and psychoactive drugs, such as cannabis (Elkins, McGue, and Iacono, 2007; Galéra et al., 2008; Tang et al., 2007). Such abuse may also represent attempts at self-medication, as stimulants are used to treat ADHD symptoms (Dopheide and Pliszka, 2009; Kollins, 2008) such as deficits in attention and working memory (Beane and Marrocco, 2004). Some of the distress of ADHD may reflect a reduction in dopaminergic function (Volkow et al., 2009), which might be partially compensated by drugs of abuse (Feltenstein and See, 2008).

CLINICAL IMPLICATIONS

The literature reviewed here highlights the importance of considering past and present cognitive function when treating patients for addiction, as drug-related cognitive changes may bias patients toward responses and actions that contribute to the cycle of addiction. Clinicians face the challenge of helping patients master adaptive strategies to overcome the strong associations that contribute to relapse when patients return to environments associated with their prior substance use. In addition, cognitive deficits may hinder patients’ ability to benefit from counseling, and more sessions and/or reminders may be necessary to aid these patients in incorporating abstinence-sustaining strategies into their daily routines.

Research into the changes in cognition that accompany addiction and the neural substrates of learning and addiction is still in its infancy but has potential to reshape views on addiction. For example, a recent discovery that has generated excitement in the addiction field is that smokers who suffered damage to the insula often lost their desire to smoke (Naqvi et al., 2007). The authors of this finding proposed that the insula is involved in the conscious urge to smoke and that therapies that modulate insula function may facilitate smoking cessation. It may also be that damage to the insula will have a similar effect on the desire to use other drugs of abuse (for a review see Goldstein et al., 2009).

A better understanding of how substances of abuse change cognitive processes is needed to develop new therapeutic agents to treat addiction and ameliorate cognitive deficits. This is a complex issue, however, as different drugs of abuse appear to alter different cognitive processes and cell signaling pathways. Even among users of the same drug, cognitive impacts will differ depending on variations in environmental factors and genetics. Understanding the influence of an individual’s genetic background on the manifestation of symptoms is a critical area for future research, holding the promise of informing more effective treatments that can be tailored to the individual’s genotype. Finally, understanding how prenatal exposure to drugs of abuse changes neural development should be a high priority, as prenatal exposure increases the new generation’s susceptibility to addiction and other problems.

LEARNING IN THE MIND AND BRAIN

A mind learns: It captures and stores information and impressions and discovers relationships between them. For the mind to learn, events must occur in the brain. Among the most compelling pieces of evidence for this idea are many cases of individuals who suffered drastic reductions of their ability to learn after incurring brain injuries. The most famous, perhaps, is Henry Molaison, who, after surgical removal of extensive brain tissue at age 27 to control his epilepsy, entirely lost his long-term declarative memory (Penfield and Milner, 1958) so that for the remaining 55 years of his life he could not call to mind anything that happened to him more than a few minutes earlier.

Neuroscience research has correlated learning with the elaboration of neural networks in the brain. Many experiments have established that, as learning takes place, selected neurons increase their levels of activity and form new connections, or strengthen established connections, with networks of other neurons. Moreover, experimental techniques that prevent neuronal activity and networking inhibit learning.

Neuroscience research with animals is elucidating how the brain constructs and maintains the neural networks that support learning. One process identified, long-term potentiation (LTP), has features that parallel key aspects of learning.

  • Once we learn to associate two ideas or sensations, the occurrence of one is likely to invoke remembrance of the other. Similarly, in LTP, a neuron that receives strong, or high-frequency, stimulation from another neuron responds by becoming more sensitive to future stimulation from the same source;
  • Newly learned material enters our short-term memory and may or may not subsequently become established in our long-term memory. Similarly, LTP has an early phase during which short-term physiological processes support the above-mentioned increase in neuronal sensitivity and a late phase involving more long-lasting physiological processes;
  • Animal studies have implicated some of the same sequences of biochemical changes (cell signaling cascades) in LTP and learning. For example, researchers showed that suppressing production of an enzyme (protein kinase A) in the hippocampi of mice prevented LTP and inhibited the animals’ ability to retain previously learned information about a maze (Abel et al., 1997).

Although LTP has not been observed in every brain region, it has been demonstrated in the nucleus accumbens, prefrontal cortex, hippocampus, and amygdala—all regions involved in both addiction and learning (Kenney and Gould, 2008; Kombian and Malenka, 1994; Maren, 2005; Otani et al., 2003).

GENES, DRUGS, AND COGNITION

An individual’s genetic makeup can influence the degree to which a drug of abuse alters his or her cognitive processes. For instance, an individual’s cognitive response to acute amphetamine depends in part on which of the alternative forms of the catechol-O-methyltransferase (COMT) gene he or she has inherited.

This gene encodes a protein that metabolizes dopamine and norepinephrine, among other molecules. A person inherits two copies of the gene, one from each parent, and each copy has either a valine or a methionine DNA triplet at codon 158: thus, a person may have two valine (Val/Val), two methionine (Met/Met), or a mixed pair (Val/Met or Met/Val) of codons at this location. Administration of acute amphetamine to individuals with the Val/Val pairing improved their performance on the Wisconsin Card Sorting Task (a test of cognitive flexibility that activates the dorsolateral prefrontal cortex) and increased efficiency in their prefrontal cortical function, as measured by increased regional cerebral blood flow in the inferior frontal lobe (Mattay et al., 2003). However, acute amphetamine did not produce those advantages in individuals with either the Val/Met or Met/Met pairing. Interestingly, the Val/Val pairing is also associated with increased impulsivity, a trait associated with addiction (Boettiger et al., 2007).

Furthermore, smokers with the Val/Val pairing were more sensitive to the disruptive effects of nicotine withdrawal on working memory and exhibited a greater cognitive response to tobacco (Loughead et al., 2009). These results are important not only because they demonstrate a link between the effects of drugs of abuse on cognition and behavioral traits associated with addiction, but also because they provide examples of how genotype contributes to the addictive phenotype.

ACKNOWLEDGMENTS

The author would like to thank Dr. Sheree Logue and members of the Gould Laboratory for critically reading an earlier version of this review and also to acknowledge support by grants from the National Institute on Alcohol Abuse and Alcoholism, the National Institute on Drug Abuse, and the National Cancer Institute (AA015515, DA017949, DA024787, and P50 CA143187) for some of the studies reviewed.

REFERENCES

  • Abel T, et al. Genetic demonstration of a role for PKA in the late phase of LTP and in hippocampus-based long-term memory. Cell. 1997;88(5):615–626. [PubMed]
  • Abel T, Lattal KM. Molecular mechanisms of memory acquisition, consolidation and retrieval. Current Opinion in Neurobiology. 2001;11(2):180–187. [PubMed]
  • Abrous DN, et al. Nicotine self-administration impairs hippocampal plasticity. Journal of Neuroscience. 2002;22(9):3656–3662. [PubMed]
  • Acuff-Smith KD, et al. Stage-specific effects of prenatal d-methamphetamine exposure on behavioral and eye development in rats. Neurotoxicology and Teratology. 1996;18(2):199–215. [PubMed]
  • Aguilar MA, Miñarro J, Simón VM. Dose-dependent impairing effects of morphine on avoidance acquisition and performance in male mice. Neurobiology of Learning and Memory. 1998;69(2):92–105. [PubMed]
  • Argilli E, et al. Mechanism and time course of cocaine-induced long-term potentiation in the ventral tegmental area. Journal of Neuroscience. 2008;28(37):9092–9100. [PMC free article] [PubMed]
  • Bardo MT, Bevins RA. Conditioned place preference: What does it add to our preclinical understanding of drug reward? Psychopharmacology (Berl) 2000;153(1):31–43. [PubMed]
  • Beane M, Marrocco RT. Norepinephrine and acetylcholine mediation of the components of reflexive attention: Implications for attention deficit disorders. Progress in Neurobiology. 2004;74(3):167–181. [PubMed]
  • Bell SL, et al. Smoking after nicotine deprivation enhances cognitive performance and decreases tobacco craving in drug abusers. Nicotine & Tobacco Research. 1999;1(1):45–52. [PubMed]
  • Biederman J, et al. Familial risk analyses of attention deficit hyperactivity disorder and substance use disorders. American Journal of Psychiatry. 2008;165(1):107–115. [PubMed]
  • Blake J, Smith A. Effects of smoking and smoking deprivation on the articulatory loop of working memory. Human Psychopharmacology: Clinical and Experimental. 1997;12:259–264.
  • Boettiger CA, et al. Immediate reward bias in humans: Fronto-parietal networks and a role for the catechol-O-methyltransferase 158(Val/Val) genotype. Journal of Neuroscience. 2007;27(52):14383–14391. [PubMed]
  • Brown SA, et al. Neurocognitive functioning of adolescents: Effects of protracted alcohol use. Alcoholism: Clinical and Experimental Research. 2000;24(2):164–171. [PubMed]
  • Cahill L, McGaugh JL. Mechanisms of emotional arousal and lasting declarative memory. Trends in Neurosciences. 1998;21(7):294–299. [PubMed]
  • Carlson G, Wang Y, Alger BE. Endocannabinoids facilitate the induction of LTP in the hippocampus. Nature Neuroscience. 2002;5(8):723–724. [PubMed]
  • Centers for Disease Control and Prevention. Fetal Alcohol Spectrum Disorders (FASDs) Retrieved November 6, 2009 from www.cdc.gov/ncbddd/fas/fasask.htm.
  • Chang L, et al. Smaller subcortical volumes and cognitive deficits in children with prenatal methamphetamine exposure. Psychiatry Research: Neuroimaging. 2004;132(2):95–106. [PubMed]
  • Choi WS, et al. Cigarette smoking predicts development of depressive symptoms among U.S. adolescents. Annals of Behavioral Medicine. 1997;19(1):42–50. [PubMed]
  • Cloak CC, et al. Lower diffusion in white matter of children with prenatal methamphetamine exposure. Neurology. 2009;72(24):2068–2075. [PMC free article] [PubMed]
  • Conners CK, et al. Nicotine and attention in adult attention deficit hyperactivity disorder (ADHD) Psychopharmacology Bulletin. 1996;32(1):67–73. [PubMed]
  • Counotte DS, et al. Long-lasting cognitive deficits resulting from adolescent nicotine exposure in rats. Neuropsychopharmacology. 2009;34(2):299–306. [PubMed]
  • Dalley JW, et al. Cognitive sequelae of intravenous amphetamine self-administration in rats: Evidence for selective effects on attentional performance. Neuropsychopharmacology. 2005;30(3):525–537. [PubMed]
  • Davis JA, et al. Withdrawal from chronic nicotine administration impairs contextual fear conditioning in C57BL/6 mice. Journal of Neuroscience. 2005;25(38):8708–8713. [PMC free article] [PubMed]
  • Del ON, et al. Cocaine self-administration improves performance in a highly demanding water maze task. Psychopharmacology (Berl) 2007;195(1):19–25. [PubMed]
  • Delanoy RL, Tucci DL, Gold PE. Amphetamine effects on long term potentiation in dentate granule cells. Pharmacology Biochemistry and Behavior. 1983;18(1):137–139. [PubMed]
  • Devonshire IM, Mayhew JE, Overton PG. Cocaine preferentially enhances sensory processing in the upper layers of the primary sensory cortex. Neuroscience. 2007;146(2):841–851. [PubMed]
  • Dopheide JA, Pliszka SR. Attention-deficit-hyperactivity disorder: An update. Pharmacotherapy. 2009;29(6):656–679. [PubMed]
  • Dwyer JB, Broide RS, Leslie FM. Nicotine and brain development. Birth Defects Research Part C: Embryo Today: Reviews. 2008;84(1):30–44. [PubMed]
  • Eichenbaum H. A cortical-hippocampal system for declarative memory. Nature Reviews Neuroscience. 2000;1(1):41–50. [PubMed]
  • Elkins IJ, McGue M, Iacono WG. Prospective effects of attention-deficit/hyperactivity disorder, conduct disorder, and sex on adolescent substance use and abuse. Archives of General Psychiatry. 2007;64(10):1145–1152. [PubMed]
  • Feltenstein MW, See RE. The neurocircuitry of addiction: An overview. British Journal of Pharmacology. 2008;154(2):261–274. [PMC free article] [PubMed]
  • Fergusson DM, Woodward LJ, Horwood LJ. Maternal smoking during pregnancy and psychiatric adjustment in late adolescence. Archives of General Psychiatry. 1998;55(8):721–727. [PubMed]
  • Franklin TR, et al. Limbic activation to cigarette smoking cues independent of nicotine withdrawal: A perfusion fMRI study. Neuropsychopharmacology. 2007;32(11):2301–2309. [PubMed]
  • Fried PA, Watkinson B, Gray R. Differential effects on cognitive functioning in 13- to 16-year-olds prenatally exposed to cigarettes and marihuana. Neurotoxicology and Teratology. 2003;25(4):427–436. [PubMed]
  • Fried PA, Watkinson B, Gray R. Neurocognitive consequences of cigarette smoking in young adults—a comparison with pre-drug performance. Neurotoxicology and Teratology. 2006;28(4):517–525. [PubMed]
  • Friswell J, et al. Acute effects of opioids on memory functions of healthy men and women. Psychopharmacology (Berl) 2008;198(2):243–250. [PubMed]
  • Galéra C, et al. Hyperactivity-inattention symptoms in childhood and substance use in adolescence: The youth GAZEL cohort. Drug and Alcohol Dependence. 2008;94(1–3):30–37. [PubMed]
  • Goff DC, Henderson DC, Amico E. Cigarette smoking in schizophrenia: Relationship to psychopathology and medication side effects. American Journal of Psychiatry. 1992;149(9):1189–1194. [PubMed]
  • Goldstein RZ, et al. The neurocircuitry of impaired insight in drug addiction. Trends in Cognitive Sciences. 2009;13(9):372–380. [PMC free article] [PubMed]
  • Gulick D, Gould TJ. Acute ethanol has biphasic effects on short- and long-term memory in both foreground and background contextual fear conditioning in C57BL/6 mice. Alcoholism: Clinical and Experimental Research. 2007;31(9):1528–1537. [PMC free article] [PubMed]
  • Hamilton BE, et al. Annual summary of vital statistics: 2005. Pediatrics. 2007;119(2):345–360. [PubMed]
  • Hernández LL, Valentine JD, Powell DA. Ethanol enhancement of Pavlovian conditioning. Behavioral Neuroscience. 1986;100(4):494–503. [PubMed]
  • Hughes JR, et al. Prevalence of smoking among psychiatric outpatients. American Journal of Psychiatry. 1986;143(8):993–997. [PubMed]
  • Hughes JR, Keenan RM, Yellin A. Effect of tobacco withdrawal on sustained attention. Addictive Behaviors. 1989;14(5):577–580. [PubMed]
  • Hyman SE. Addiction: A disease of learning and memory. American Journal of Psychiatry. 2005;162(8):1414–1422. [PubMed]
  • Iñiguez SD, et al. Nicotine exposure during adolescence induces a depression-like state in adulthood. Neuropsychopharmacology. 2009;34(6):1609–1624. [PMC free article] [PubMed]
  • Jacobsen LK, et al. Effects of smoking and smoking abstinence on cognition in adolescent tobacco smokers. Biological Psychiatry. 2005;57(1):56–66. [PubMed]
  • Jacobsen LK, et al. Visuospatial memory deficits emerging during nicotine withdrawal in adolescents with prenatal exposure to active maternal smoking. Neuropsychopharmacology. 2006;31(7):1550–1561. [PubMed]
  • Jacobsen LK, et al. Prenatal and adolescent exposure to tobacco smoke modulates the development of white matter microstructure. Journal of Neuroscience. 2007;27(49):13491–13498. [PubMed]
  • Jones S, Bonci A. Synaptic plasticity and drug addiction. Current Opinion in Pharmacology. 2005;5(1):20–25. [PubMed]
  • Kalivas PW, Volkow ND. The neural basis of addiction: A pathology of motivation and choice. American Journal of Psychiatry. 2005;162(8):1403–1413. [PubMed]
  • Kelley AE. Memory and addiction: Shared neural circuitry and molecular mechanisms. Neuron. 2004;44(1):161–179. [PubMed]
  • Kelley BJ, et al. Cognitive impairment in acute cocaine withdrawal. Cognitive and Behavioral Neurology. 2005;18(2):108–112. [PMC free article] [PubMed]
  • Kelly C, McCreadie RG. Smoking habits, current symptoms, and premorbid characteristics of schizophrenic patients in Nithsdale, Scotland. American Journal of Psychiatry. 1999;156(11):1751–1757. [PubMed]
  • Kenney JW, Gould TJ. Modulation of hippocampus-dependent learning and synaptic plasticity by nicotine. Molecular Neurobiology. 2008;38(1):101–121. [PMC free article] [PubMed]
  • Khuder SA, Dayal HH, Mutgi AB. Age at smoking onset and its effect on smoking cessation. Addictive Behaviors. 1999;24(5):673–677. [PubMed]
  • Kollins SH. ADHD, substance use disorders, and psychostimulant treatment: Current literature and treatment guidelines. Journal of Attention Disorders. 2008;12(2):115–125. [PubMed]
  • Kombian SB, Malenka RC. Simultaneous LTP of non-NMDA- and LTD of NMDA-receptor-mediated responses in the nucleus accumbens. Nature. 1994;368(6468):242–246. [PubMed]
  • Lambert NM, Hartsough CS. Prospective study of tobacco smoking and substance dependencies among samples of ADHD and non-ADHD participants. Journal of Learning Disabilities. 1998;31(6):533–544. [PubMed]
  • Le Moal M, Koob GF. Drug addiction: Pathways to the disease and pathophysiological perspectives. European Neuropsychopharmacology. 2007;17(6–7):377–393. [PubMed]
  • Leonard S, et al. Smoking and mental illness. Pharmacology Biochemistry and Behavior. 2001;70(4):561–570. [PubMed]
  • Loughead J, et al. Effect of abstinence challenge on brain function and cognition in smokers differs by COMT genotype. Molecular Psychiatry. 2009;14(8):820–826. [PubMed]
  • Lyvers M, Yakimoff M. Neuropsychological correlates of opioid dependence and withdrawal. Addictive Behaviors. 2003;28(3):605–611. [PubMed]
  • Maren S. Synaptic mechanisms of associative memory in the amygdala. Neuron. 2005;47(6):783–786. [PubMed]
  • Mattay VS. Dextroamphetamine enhances “neural network-specific” physiological signals: A positron-emission tomography rCBF study. Journal of Neuroscience. 1996;16(15):4816–4822. [PubMed]
  • Mattay VS, et al. Catechol O-methyltransferase val158-met genotype and individual variation in the brain response to amphetamine. Proceedings of the National Academy of Sciences of the United States of America. 2003;100(10):6186–6191. [PubMed]
  • McEvoy JP, et al. Haloperidol increases smoking in patients with schizophrenia. Psychopharmacology (Berl) 1995;119(1):124–126. [PubMed]
  • McEvoy JP, Freudenreich O, Wilson WH. Smoking and therapeutic response to clozapine in patients with schizophrenia. Biological Psychiatry. 1999;46:125–129. [PubMed]
  • Mendrek A, et al. Working memory in cigarette smokers: Comparison to non-smokers and effects of abstinence. Addictive Behaviors. 2006;31(5):833–844. [PMC free article] [PubMed]
  • Miller C, Marshall JF. Molecular substrates for retrieval and reconsolidation of cocaine-associated contextual memory. Neuron. 2005;47(6):873–884. [PubMed]
  • Molina BS, Pelham WE., Jr Childhood predictors of adolescent substance use in a longitudinal study of children with ADHD. Journal of Abnormal Psychology. 2003;112(3):497–507. [PubMed]
  • Moriyama Y, et al. Family history of alcoholism and cognitive recovery in subacute withdrawal. Psychiatry and Clinical Neuroscience. 2006;60(1):85–89. [PubMed]
  • Naqvi NH, et al. Damage to the insula disrupts addiction to cigarette smoking. Science. 2007;315(5811):531–534. [PubMed]
  • Nooyens AC, van Gelder BM, Verschuren WM. Smoking and cognitive decline among middle-aged men and women: The Doetinchem Cohort Study. American Journal of Public Health. 2008;98(12):2244–2250. [PubMed]
  • Nugent FS, Kauer JA. LTP of GABAergic synapses in the ventral tegmental area and beyond. Journal of Physiology Online. 2008;586(6):1487–1493. [PubMed]
  • Ornstein TJ, et al. Profiles of cognitive dysfunction in chronic amphetamine and heroin abusers. Neuropsychopharmacology. 2000;23(2):113–126. [PubMed]
  • O’Shea M, McGregor IS, Mallet PE. Repeated cannabinoid exposure during perinatal, adolescent or early adult ages produces similar longlasting deficits in object recognition and reduced social interaction in rats. Journal of Psychopharmacology. 2006;20(5):611–621. [PubMed]
  • Otani S, et al. Dopaminergic modulation of long-term synaptic plasticity in rat prefrontal neurons. Cerebral Cortex. 2003;13(11):1251–1256. [PubMed]
  • Patterson F, et al. Working memory deficits predict short-term smoking resumption following brief abstinence. Drug and Alcohol Dependence. 2010;106(1):61–64. [PMC free article] [PubMed]
  • Pauly JR, Slotkin TA. Maternal tobacco smoking, nicotine replacement and neurobehavioural development. Acta Paediatrica. 2008;97(10):1331–1337. [PubMed]
  • Penfield W, Milner B. Memory deficit produced by bilateral lesions in the hippocampal zone. AMA Archives of Neurology and Psychiatry. 1958;79(5):475–497. [PubMed]
  • Piper BJ, Meyer JS. Memory deficit and reduced anxiety in young adult rats given repeated intermittent MDMA treatment during the periadolescent period. Pharmacology Biochemistry and Behavior. 2004;79(4):723–731. [PubMed]
  • Pomerleau CS, et al. Smoking patterns and abstinence effects in smokers with no ADHD, childhood ADHD, and adult ADHD symptomatology. Addictive Behaviors. 2003;28(6):1149–1157. [PubMed]
  • Pope HG, Jr, Gruber AJ, Yurgelun-Todd D. Residual neuropsychologic effects of cannabis. Current Psychiatry Reports. 2001;3(6):507–512. [PubMed]
  • Pulsifer MB, et al. Prenatal drug exposure: Effects on cognitive functioning at 5 years of age. Clinical Pediatrics. 2008;47(1):58–65. [PMC free article] [PubMed]
  • Raybuck JD, Gould TJ. Nicotine withdrawal-induced deficits in trace fear conditioning in C57BL/6 mice—a role for high-affinity beta2 subunit-containing nicotinic acetylcholine receptors. European Journal of Neuroscience. 2009;29(2):377–387. [PMC free article] [PubMed]
  • Regier DA, et al. Comorbidity of mental disorders with alcohol and other drug abuse. Results from the Epidemiologic Catchment Area (ECA) Study. JAMA. 1990;264(19):2511–2518. [PubMed]
  • Richards M, et al. Cigarette smoking and cognitive decline in midlife: Evidence from a prospective birth cohort study. American Journal of Public Health. 2003;93(6):994–998. [PubMed]
  • Richardson GA, et al. Prenatal alcohol and marijuana exposure: Effects on neuropsychological outcomes at 10 years. Neurotoxicology and Teratology. 2002;24(3):309–320. [PubMed]
  • Robinson TE, Berridge KC. The psychology and neurobiology of addiction: An incentive-sensitization view. Addiction. 2000;95(Suppl 2):S91–117. [PubMed]
  • Rogers RD, et al. Dissociable deficits in the decision-making cognition of chronic amphetamine abusers, opiate abusers, patients with focal damage to prefrontal cortex, and tryptophan-depleted normal volunteers: Evidence for monoaminergic mechanisms. Neuropsychopharmacology. 1999;20(4):322–339. [PubMed]
  • Rukstalis M, et al. Increases in hyperactive-impulsive symptoms predict relapse among smokers in nicotine replacement therapy. Journal of Substance Abuse Treatment. 2005;28(4):297–304. [PubMed]
  • Ryback RS. The continuum and specificity of the effects of alcohol on memory. A review. Quarterly Journal of Studies on Alcohol. 1971;32(4):995–1016. [PubMed]
  • See RE. Neural substrates of cocaine-cue associations that trigger relapse. European Journal of Pharmacology. 2005;526(1–3):140–146. [PubMed]
  • Semenova S, Stolerman IP, Markou A. Chronic nicotine administration improves attention while nicotine withdrawal induces performance deficits in the 5-choice serial reaction time task in rats. Pharmacology Biochemistry and Behavior. 2007;87(3):360–368. [PMC free article] [PubMed]
  • Setlow B. The nucleus accumbens and learning and memory. Journal of Neuroscience Research. 1997;49(5):515–521. [PubMed]
  • Slamberová R, et al. Learning in the Place navigation task, not the New-learning task, is altered by prenatal methamphetamine exposure. Developmental Brain Research. 2005;157:217–219. [PubMed]
  • Slotkin TA, et al. Adolescent nicotine administration changes the responses to nicotine given subsequently in adulthood: Adenylyl cyclase cell signaling in brain regions during nicotine administration and withdrawal, and lasting effects. Brain Research Bulletin. 2008;76(5):522–530. [PubMed]
  • Solowij N, et al. Cognitive functioning of long-term heavy cannabis users seeking treatment. JAMA. 2002;287(9):1123–1131. [PubMed]
  • Stiglick A, Kalant H. Learning impairment in the radial-arm maze following prolonged cannabis treatment in rats. Psychopharmacology (Berl) 1982;77(2):117–123. [PubMed]
  • Substance Abuse and Mental Health Services Administration (SAMHSA) DHHS Pub. No. SMA 07-4343. Rockville, MD: SAMHSA; 2007. Results from the 2006 National Survey on Drug Use and Health: National Findings. Available at: www.oas.samhsa.gov/NSDUH/2k6NSDUH/2k6results.cfm#8.1.3.
  • Sullivan JM. Cellular and molecular mechanisms underlying learning and memory impairments produced by cannabinoids. Learning & Memory. 2000;7(3):132–139. [PubMed]
  • Swan GE, Lessov-Schlaggar CN. The effects of tobacco smoke and nicotine on cognition and the brain. Neuropsychology Review. 2007;17(3):259–273. [PubMed]
  • Tang YL, et al. Comorbid psychiatric diagnoses and their association with cocaine-induced psychosis in cocaine-dependent subjects. American Journal on Addictions. 2007;16(5):343–351. [PubMed]
  • Thomas AJ, O’Brien JT. Depression and cognition in older adults. Current Opinion in Psychiatry. 2008;21(1):8–13. [PubMed]
  • Thomasius R, et al. Mood, cognition and serotonin transporter availability in current and former ecstasy (MDMA) users: The longitudinal perspective. Journal of Psychopharmacology. 2006;20(2):211–225. [PubMed]
  • Toro R, et al. Prenatal exposure to maternal cigarette smoking and the adolescent cerebral cortex. Neuropsychopharmacology. 2008;33(5):1019–1027. [PubMed]
  • Vaglenova J, et al. Long-lasting teratogenic effects of nicotine on cognition: Gender specificity and role of AMPA receptor function. Neurobiology of Learning and Memory. 2008;90(3):527–536. [PubMed]
  • van Duijn CM, Hofman A. Relation between nicotine intake and Alzheimer’s disease. BMJ. 1991;302(6791):1491–1494. [PMC free article] [PubMed]
  • Verdejo-García A, Pérez-García M. Profile of executive deficits in cocaine and heroin polysubstance users: Common and differential effects on separate executive components. Psychopharmacology (Berl) 2007;190(4):517–530. [PubMed]
  • Volkow ND, et al. Loss of dopamine transporters in methamphetamine abusers recovers with protracted abstinence. Journal of Neuroscience. 2001;21(23):9414–9418. [PubMed]
  • Volkow ND, et al. Cocaine cues and dopamine in dorsal striatum: Mechanism of craving in cocaine addiction. Journal of Neuroscience. 2006;26(24):6583–6588. [PubMed]
  • Volkow ND, et al. Evaluating dopamine reward pathway in ADHD: Clinical implications. JAMA. 2009;302(10):1084–1091. [PMC free article] [PubMed]
  • Wang GJ, et al. Partial recovery of brain metabolism in methamphetamine abusers after protracted abstinence. American Journal of Psychiatry. 2004;161(2):242–248. [PubMed]
  • Yates WR, et al. Effect of fetal alcohol exposure on adult symptoms of nicotine, alcohol, and drug dependence. Alcoholism: Clinical and Experimental Research. 1998;22(4):914–920. [PubMed]
  • Yin HH, et al. Ethanol reverses the direction of long-term synaptic plasticity in the dorsomedial striatum. European Journal of Neuroscience. 2007;25(11):3226–3232. [PubMed]
  • Ziedonis DM, et al. Nicotine dependence and schizophrenia. Hospital & Community Psychiatry. 1994;45(3):204–206. [PubMed]

Articles from Addiction Science & Clinical Practice are provided here courtesy of BioMed Central