Sage Journals: Discover world-class research

Abstract

The purpose of the present review is to describe the neuropsychological correlates of long-term substance abuse and to discuss the findings within the context of premorbid vulnerabilities, comorbidity and adolescent neurodevelopment. The authors critically review key findings from the neuropsychological literature related to the long-term sequelae of alcohol, cannabis, inhalant, opiates, psychostimulants and ecstasy use. Leading electronic databases such as PubMed were searched to identify relevant studies published in the past 20 years. References identified from bibliographies of pertinent articles and books in the field were also collected and selectively reviewed. Across substances, individuals with long-term abuse consistently demonstrate neuropsychological impairments of executive (inhibitory) control, working memory and decision making, together with neurobiological abnormalities involving frontotemporal and basal ganglia circuits. In some instances these deficits are dose dependent, implying that they are a direct consequence of prolonged drug exposure. However, comorbid behavioural, personality and mental health problems are common among drug-using populations and are associated with similar neuropsychological deficits. Presented herein is a neuropsychological model of addictive behaviour that highlights the complex interplay between cognition, brain maturation, psychopathology and drug exposure.

Keywords

brain cognition drug imaging vulnerability

‘Addiction’, derived from the Latin verb addicere (meaning ‘to enslave’), is characterized by an apparent loss of control or autonomy over one's behaviour. Indeed, the continued abuse of substances by addicted individuals, despite an apparent awareness of associated adverse consequences, suggests that addictive behaviour may involve deficits in inhibitory control, decision-making and the regulation of affect [1–7]. In line with this, recent neuroimaging studies across a variety of substance-using populations have implicated impairments in frontal cortical networks [6–10]. However, an question is whether these frontally mediated executive control deficits relate to the use of specific substances or are common across the major classes of drugs.

In the present paper we critically review the neuropsychological literature related to the long-term sequelae of alcohol, cannabis, inhalants, opiates, psychostimulants and ecstasy in humans. Leading electronic databases such as PubMed were searched to identify relevant studies written in English and published in the past 20 years. References identified from bibliographies of pertinent articles and books in the field were also collected and reviewed. Studies examining the acute effects of these substances were not included in this review because the focus is on the long-term sequelae. It was not our intention to comprehensively review all studies identified in our searches, but to selectively focus on key exemplary research to highlight methodological issues and determine the primary and most consistent findings across this broad literature. We discuss these findings in the context of premorbid neuropsychological vulnerabilities and comorbid personality traits and disorders (e.g. medical, neurological or psychiatric). We also discuss the neural and functional changes that occur in the adolescent brain and their relevance to the neuropsychological outcomes observed.

Neuropsychological sequelae of specific drugs

Alcohol

The most consistent findings of neuropsychological impairment in heavy and long-term drinkers are in the domains of attention, short-term memory, visuospatial abilities, postural stability and executive functions (such as problem-solving, mental flexibility, judgement, working memory, response inhibition and decision-making), with a relative sparing of declarative memory, language skills and primary motor and perceptual abilities [11–14]. The link between lifetime exposure and the development of cognitive problems is unclear. While some research findings suggest that cognitive performance worsens in direct proportion to the frequency and duration of drinking [15, 16], other studies suggest that cognitive deficits may be detectable only in those who have been drinking regularly for at least 10 years [17, 18]. Some researchers even suggest that neuropsychological impairments are not related to alcohol at all, but rather are a direct consequence of head trauma associated with drinking [19]. These contrasting findings highlight the need for further research to determine how patterns of alcohol use are related to cognitive impairment, especially in light of some evidence to suggest that long-term, light-to-moderate social drinkers may also have cognitive deficits [15].

The nature of the neuropsychological deficits observed in long-term drinkers is consistent with disruption to frontotemporal, frontoparietal and cerebellar brain systems. Indeed, structural magnetic resonance imaging (MRI) indicates a consistent association between heavy drinking and structural neuronal injury and volume loss that is more extensive in the frontal lobe, temporal lobe, and cerebellum [20, 21]. Results of autopsy studies show that individuals with a history of chronic alcohol consumption have smaller, lighter and more shrunken brains than non-alcoholic adults of the same age and gender [22, 23].

Perhaps the strongest evidence for a direct relationship between chronic substance abuse and neuropsychological/neurobiological impairments comes from observations of a dose–response relationship and longitudinal studies demonstrating progressive changes in such measures with ongoing abstinence or continued use. To this end, some alcohol-related cognitive impairment and structural brain deficits can be reversed with abstinence over a period of several months to years [14]. Abstinence-associated improvements have been documented in neuropsychological functions such as working memory, visuospatial functioning, and attention, accompanied by significant increases in brain volume, compared with alcoholics who subsequently relapsed [24–26].

Cannabis

Despite inconsistent findings from early studies and a small meta-analysis [27], recent well-controlled neuropsychological studies of chronic cannabis users in the non-intoxicated state have now demonstrated impaired performance on a variety of attention, memory, and executive function tasks [28–33]. Deficits have variously been attributed to duration of cannabis use [33], frequency of cannabis use [31] or cumulative dosage effects [32]. Performance on executive tests, such as the Stroop task [34], is not consistently impaired in cannabis users, but performance decrements have nevertheless been shown to be related to duration of use [33], or dose interacting with lower IQ [32]. Few studies have sought to specifically tease out differential impairments associated with varying patterns of cannabis use (e.g. heavy daily use for short periods vs light weekly use for long periods). Solowij showed that the ability to focus attention and filter out irrelevant information was progressively impaired with increasing years of cannabis use, while speed of information processing was impaired with increasing frequency of use (days per month) [35].

Recent neuroimaging studies of cannabis users demonstrate impaired performance in attention, verbal memory [36], working memory [37], response inhibition [34, 38, 39] and decision-making tasks [40], with concomitant alterations in blood flow, activation or brain tissue density primarily in prefrontal cortical, anterior cingulate, basal ganglia, cerebellar and hippocampal regions. For example, Matochik et al. found grey and white matter density changes in 28 day abstinent cannabis users in the medial temporal regions, and some of the density changes were associated with duration of cannabis use [41]. Our own study used high-resolution MRI to examine a well-characterized sample of long-term (>10 years of regular use) and very heavy cannabis users (5–7 joints per day over many years). We found robust reductions of 12.0% in the hippocampus and 7.1% in the amygdala of users relative to well-matched healthy control participants. Additionally, left hippocampal volume was negatively associated with cumulative dose of exposure to cannabis. While some studies found no structural brain alterations in cannabis users [36, 42], our findings corroborate the animal literature in human subjects suggesting that long-term heavy cannabis use is associated with significant and localized medial temporal reductions that are related to cumulative cannabis dosage [Yucel M, Solowij N, Respondek C et al: unpublished data, 2007]. Moreover, altered frontal cortical activation is apparent in cannabis users despite normal Stroop task performance [34, 39], suggesting that there may be disturbances in brain physiology that are not as yet apparent behaviourally.

The extent of persistence of effects or recovery of function following abstinence is also uncertain, with some studies suggesting no recovery after 25–28 days abstinence [32, 34, 40], while others report full recovery after 28 days abstinence [31] and partial early recovery after 2 years abstinence [35].

Inhalants

While the toxic effects of chronic inhalant abuse are well described [43], there is only a small research literature examining the neurobiological and neuropsychological effects of voluntary inhalant exposure [44, 45]. One early study demonstrated that inhalant abusers (mainly those abusing metallic paints) had deficits in motor coordination, learning, memory, executive functioning and overall verbal intelligence [46]. One of the largest investigations examining the effects of inhalant use on neuropsychological functioning in adolescents was conducted by Chadwick et al. [47]. Those who had used volatile substances performed significantly worse on tests of vocabulary and impulsivity, and had significantly lower verbal and full-scale IQ. However, these differences were no longer significant when background social disadvantage was taken into account, although it is important to note that the inhalant group consisted of primarily experimental or recreational users. Other studies suggest that solvent-abusing groups tend to perform worse on a range of neuropsychological tasks, especially those involving memory and executive functioning [48]. However, these individuals typically lack the motivation to perform well on such tasks and invariably present with complex problems, such as psychosocial disadvantages (e.g. unstable and dysfunctional families, state-based care, school absenteeism, trauma and abuse, forensic issues), and histories of comorbid drug use and mental health problems – issues that play a major role in neuropsychological outcomes [48].

From a neurobiological perspective there is more conclusive evidence that inhalant exposure is associated with adverse consequences. A recent study comparing 55 inhalant abusers (mean age 30 years) and 61 cocaine abusers (mean age 29 years) found substantial brain abnormalities (especially in subcortical and white matter regions) and cognitive impairment within both groups [45]. However, the structural brain abnormalities were more common (44% vs 25%) and more extensive in the inhalant-using group. In addition, the inhalant group performed significantly worse on tests of working memory and tests requiring focused attention, planning, and problem solving. Similar findings have been observed in other neurobiological and neuroimaging studies of chronic solvent exposure in occupational settings [49, 50].

Very few studies have specifically investigated recovery of function after prolonged exposure to inhalants. Cairney et al. found significant improvements in previously identified neurobehavioural impairments following 2 years abstinence from petrol sniffing [51, 52]. In fact, in many cases these deficits normalized completely. However, although those with the greatest levels of impairment showed the greatest degree of improvement with abstinence, they were less likely to recover completely. A handful of studies in solvent-abusing individuals have also reassessed their cases with further neuropsychological and/or neuroimaging investigations and found either greater impairments with continued solvent use [53, 54] or significant improvements with long-term abstinence [55]. Other studies have found associations between the parameters of solvent use (e.g. duration and extent) and MRI abnormalities [56, 57]. While these studies support the notion that solvent abuse directly leads to adverse outcomes, and that recovery of function is possible through abstinence, one study failed to find any significant improvement in MRI or neuropsychological measures following 5 months of abstinence [58]. Worryingly, another study found no improvements in MRI measures of brain pathology following an extended period (18 months) of abstinence [59].

Opiates

Research on the long-term neuropsychological effects of chronic opiate abuse has been relatively limited. Davis et al. reported that 60% of individuals currently abusing opiates had impairments of at least two standard deviations below published norms on two or more neuropsychological tests, a significantly higher incidence than found in matched controls with no history of drug abuse [60]. In particular, deficits were identified in impulse control in those with a history of ≥5 years of heroin use. Similarly, Pau et al. examined the impact of heroin on frontal executive functioning in three cognitive domains, namely attention, impulse control and mental flexibility [61]. They found that heroin abuse has adverse effects on impulse control but not attention or mental flexibility. Other studies have reported more diffuse deficits across the domains of attention, working memory, memory and executive function in chronic opiate abusers [61–65]. Ornstein et al. found that heroin addicts were impaired on performance of cognitive tasks (e.g. learning, spatial working memory, strategic thinking) known to be sensitive to cortical damage (including selective lesions of the temporal and frontal lobes) [63]. Darke et al. reported that methadone-maintained heroin addicts performed more poorly on all neuropsychological domains tested, including attention (information processing speed, attentional capacity), memory (visual and verbal learning and memory) and executive functioning (problem solving) compared with matched controls [66]. However, Darke et al. noted that the methadone group had high rates of polysubstance use, overdose, head injury and comorbid psychopathology [66]. They found that the neuropsychological deficits identified were more characteristic of those with associated comorbidities, further raising issues regarding the specificity of findings reported.

Chronic opiate users have been shown to have disturbances in prefrontal cortical activity when performing a reward-based decision task [67]. Moreover, this disturbance was observed in a group of drug users who had been abstinent for at least 1 year. Further support for prefrontal dysfunction comes from the large structural imaging study of Lyoo et al., which investigated grey matter density in 63 opiate-dependent subjects and 46 matched controls [68]. They found that relative to controls, the opiate-dependent group exhibited significantly decreased grey-matter in the prefrontal, as well as superior temporal cortex, insula and fusiform gyrus. Another study by Kivisaari et al. in long-term opiate users found that the sylvan fissures and ventricles were wider in opiate-dependent subjects than in controls, which may be related to brain atrophy within frontal and temporal lobes [69].

Our own multimodal neuroimaging study of long-term opiate users also found abnormalities in the neural substrates of inhibitory control [9, 10]. Specifically, opiate addicts (i) exhibited significantly reduced concentrations of the neuronal marker N-acetylaspartate (NAA) and glutamate/glutamine within the dorsal anterior cingulate cortex (d-ACC); (ii) failed to show the normal association between d-ACC activity and behavioural performance demonstrated by healthy controls; and (iii) had relatively increased task-related activation of frontoparietal and cerebellar regions. These findings suggest that neuronal abnormalities and a breakdown of normal brain–behaviour relationships within the d-ACC of chronic opiate users may result in the recruitment of a compensatory and inadequate network of brain regions when required to exercise inhibitory control.

Studies evaluating the persistence of cognitive deficits among abstinent opiate addicts remain mixed. A number of studies have found that abstinent groups of recovering addicts have no significant cognitive deficits [60, 62]. Guerra et al. reported that individuals with current heroin abuse demonstrated deficits in attention, working memory, episodic memory and verbal fluency, which normalized 7–14 days following rapid detoxification [62]. However, two other studies of abstinent heroin users (8 and 14 months, respectively) reported ongoing deficits in executive function [61, 65]. Using a more sophisticated battery of experimental neuropsychological tests, Ersche et al. reported that opiate-dependent individuals demonstrated marked impairments in spatial planning, paired associate learning and visual pattern recognition compared with matched controls [70]. Performance of former opiate users (abstinent for 8 years on average) was not statistically different from current users on any measure, suggesting that the deficits observed did not simply reflect the current effects of drug use. These findings are in keeping with other studies describing prefrontal dysfunction in chronic drug users [1, 3, 5–7].

Psychostimulants (cocaine, amphetamine/methamphetamine)

Few studies have comprehensively examined cognitive functioning among methamphetamine users. Some researchers point to studies that suggest memory and executive problems, while others maintain that no firm evidence for a link exists [71]. Recent studies of chronic amphetamine/methamphetamine abusers have shown that they perform poorly on decision-making tasks that involve regions of the frontal cortex (specifically the ventromedial prefrontal cortex), such that they make disadvantageous decisions that reflect valuing short-term gain over longer term losses [64, 72]. Methamphetamine users also appear to be more distractible and are unable to suppress processing task-irrelevant information [72], which is consistent with their clinical presentation. Other work has also shown cognitive deficits related to processing speed, learning, delayed recall and inhibitory control and working memory [73–75]. Another recent study found methamphetamine abuse to be associated with deficient strategic (i.e. executive) control of verbal encoding and retrieval, which is consistent with proposed prefrontostriatal circuit neurotoxicity [76]. Interestingly, comorbid cannabis does not appear to exacerbate methamphetamine neurotoxicity, but rather has been suggested to have neuroprotective effects [75].

Neuropsychological studies of chronic cocaine users, as in chronic amphetamine users, also demonstrate higher order cognitive impairments (e.g. inhibitory dysregulation) that is consistent with abnormal blood flow in frontal brain regions [77]. Several studies have reported that cocaine abuse is associated with decrements on neurobehavioural tests measuring executive control, visuoperception, psychomotor speed, manual dexterity, verbal learning, and memory [78, 79]. Ardila et al. found that neuropsychological test scores were correlated with lifetime amount of cocaine used, suggesting a direct relationship between cocaine abuse and cognitive impairment [80].

Neuroimaging studies of methamphetamine users have shown abnormalities of brain structure and function relative to healthy controls including alterations of frontal, temporal and subcortical metabolism [81–86]. Changes in neuronal biochemistry suggestive of neuronal injury have also been found in the frontal cortex and basal ganglia structures [87]. Using proton magnetic resonance spectroscopy (1H-MRS), Ernst et al. reported abnormally low levels of the neuronal marker NAA in the basal ganglia of abstinent methamphetamine-dependent subjects [87]. They also observed an inverse association between prefrontal white-matter NAA values and years of use, implying direct effects of this drug on the neuronal integrity of prefrontal tissue. Similar findings have been reported in the anterior cingulate cortex [88, 89]. Recent neuroimaging studies have shown that frontal and temporal lobe white matter continues to increase into the fifth decade of life [90]. However, Bartzokis et al. found that cocaine-dependent subjects (aged 19–47) do not demonstrate the normal pattern of age-related increases in white matter within these brain regions [90], suggesting that continued cocaine use may arrest normal white matter maturation.

Examination of cognitive function in abstinent cocaine-dependent individuals after both 6 weeks and 6 months abstinence shows persistent cognitive impairment across a wide range of functions compared to controls at both time-points. Further, a close relationship between the degree of neuropsychological impairments and dosage (i.e. quantity and dosage of peak usage) has also been reported [91]. Consistent with these neuropsychological findings, Fein et al. also found that cocaine-induced brain volumetric reduction in the prefrontal cortex persisted after 6 weeks abstinence [92].

3, 4 methylendioxymethamphetamine (MDMA, ecstasy)

A number of persisting cognitive problems have been attributed to regular N-methyl-3,4-methylenedioxy-amphetamine (MDMA) use and suggest underlying serotonergic dysfunction [93–95]. For example, impairments in memory (both visual and verbal) have been shown to correlate with in vivo measurements of brain serotonin function and levels of 5-hydroxyindoleacetic acid (5-HIAA) in cerebrospinal fluid, as well as relating to the level of previous MDMA use (i.e. are dose related) [96]. Other neuropsychological deficits that have been reported in regular ecstasy users include impairments of executive function and self-control (i.e. decreased inhibitory control and increased impulsivity) [97, 98]. McCardle et al. found that MDMA users exhibit difficulties in coding information into long-term memory, have impaired verbal learning, are more easily distracted, and are less efficient at focussing attention on complex tasks [97]. Interestingly, Spatt et al. have described a case of profound amnesia, associated with bilateral brain changes on MRI, following a single exposure to MDMA [99].

Although cognitive deficits among MDMA users have been well documented, little is known of the neurobiological sequelae of MDMA use. In one study, MDMA use in adolescence was associated with difficulties in the ability to focus and divide attention, as well as abnormal hippocampal activity during performance of a working memory task [100]. Other functional MRI studies have found abnormal frontotemporal, parietal and subcortical activity during performance of working memory tasks [101–104]. Additionally, Daumann et al. found that relative to a group of controls and currently abstinent but previously moderate users, the currently abstinent but previously heavy users showed more prominent frontal and temporal lobe activation abnormalities during performance of a working memory task [104]. Structural MRI findings among MDMA polydrug users includes evidence of diffuse grey matter reductions across the cortex, cerebellum and brainstem structures [105].

Little is known about the possible persistent neuropsychological effects of extensive MDMA use. However, there is tentative evidence that these cognitive deficits persist for at least 6 months after abstinence, whereas anxiety and hostility remit after 1 year of abstinence [93, 106]. Morgan et al. compared four groups of participants: current regular recreational MDMA users; ex-regular MDMA users who had abstained from using the drug for an average of 2 years; polydrug users who had never taken MDMA; and drug-naive controls [106]. They found that both current and ex-MDMA users exhibited elevated psychopathology and behavioural impulsivity compared with polydrug users and drug-naive controls, but current MDMA users exhibited a broader range of psychopathology than ex-users. Both groups of MDMA users also exhibited impaired working memory and verbal recall performance compared with drug-naive controls. These findings suggest that selective impairments of neuropsychological performance associated with regular MDMA use are not reversed by prolonged abstinence. This is consistent with evidence that MDMA may affect brain serotonergic systems in human users. Other studies have also found altered neural activations suggestive of prefrontal neuronal injury in abstinent MDMA users during performance of working memory tasks [102].

Summary

This selective review of the available literature suggests that chronic abuse of a wide range of addictive substances can adversely affect neuropsychological functioning. However, it is also clear that there is marked inter-individual variability in the patterns of substance use (e.g. duration, frequency, dosage, type) and, with the exception of a few studies, most researchers were not able to definitively isolate the effects of a specific drug due to a history of polysubstance use. An under-investigated issue is whether concurrent use of different substances (e.g. cannabis and alcohol) may potentiate the long-term adverse effects of each drug. While synergistic or additive effects are plausible, there is also speculation that use of some substances may mask or protect against the neurocognitive sequelae of other substances. For example, it has been hypothesized that the neuroprotective properties of cannabinoids may fortify against neurotoxic effects of MDMA or amphetamines in general to preserve cognition in Ecstasy users [93] or amphetamine users [75]. Working memory-related neural activation in cannabis users was found to be deficient only during nicotine withdrawal (but not in tobacco users during nicotine withdrawal), suggesting that nicotine may mask neuropsychological deficits associated with cannabis [107]. Nonetheless, there is consistent evidence that almost all substances affect the domains of attention, learning and memory, visuospatial abilities and executive functioning. However, the more robust findings relate to impairment in inhibitory control (variously referred to as response inhibition, inhibitory regulation, self-control or impulsivity), working memory and decision-making. Accordingly, the neurobiological findings from structural, functional and spectroscopic MRI studies suggest dysfunction in neural systems that subserve these functions, particularly frontotemporal and basal ganglia circuitry.

Nevertheless, the pathways into addiction are invariably complex, making it difficult to disentangle the neuropsychological effects of substance exposure from associated risk factors. While in some instances, reported deficits have been found to be dose dependent (implying direct effects of drug exposure), the fact that most studies are cross-sectional in nature means that it is not possible to categorically determine whether the identified deficits are a consequence of the drugs specifically, relate to pre-existing vulnerabilities, or are a combination of both. Specifically, it is not clear how broader individual characteristics (e.g. developmental stage, psychopathology, genetic polymorphisms) may affect neuropsychological functioning and contribute to the observed deficits.

Executive control deficits: broader individual considerations

Young people who have behavioural problems early (e.g. a difficult temperament in infancy or childhood oppositional, aggressive or impulsive behaviours) are at increased risk of developing substance use disorders [108]. Indeed, childhood diagnoses of oppositional defiant disorder, conduct disorder and attention deficit hyperactivity disorder are well-established risk factors [109–112]. In addition, a number of mental health disorders are associated with high rates of comorbid substance use, such as depression, anxiety, schizophrenia, bipolar disorder and obsessive–compulsive disorder [113–116]. Given that deficits in inhibitory control and affect regulation are found across many of these disorders, together with disruption to brain regions subserving these functions (e.g. prefrontal and temporal areas), it is possible that they form a key component of liability to not only behavioural and mental health disorders, but also to addictive behaviour.

Certain personality characteristics may also influence an individual's decision to use drugs, as well as their liability to develop problematic use. Indeed, inhibitory-control and affect-regulation difficulties may also be components of a premorbid personality style rather than the result of state-related cognitive–affective processes. To this end, there is a growing literature on temperament and personality as risk factors for substance use disorders and addiction. These studies highlight a relationship between measures of impulsivity and related constructs (such as risk-taking, sensation-seeking) in childhood and the development of later substance use disorders in adulthood [117]. In fact, studies of both adolescents and adults consistently report an association between impulsivity (e.g. acting in a sudden and unplanned manner, acting without having all the necessary information or failing to think through the pros and cons of a decision) and substance-related problems [118–120]. Other personality traits such as negative affectivity/neuroticism have also been identified as risk factors for substance use disorders. Negative affect/neuroticism is characterized by a general tendency to experience life as more negative and a difficulty in controlling one's mood (i.e. difficulties with affect regulation) and/or being less tolerant to stressful life events. There is growing evidence to suggest that adolescent substance use disorders may not only result in disinhibited behaviour or impulsivity (reviewed here), but may in fact reflect an attempt to reduce negative affectivity [121, 122]. From a neurobiological and neuropsychological perspective, this inability to internally regulate moods and the over-reliance upon external agents, such as psychoactive substances, suggests inappropriate neural (particularly prefrontal) and cognitive modulation of emotions [123].

Another issue is that of premorbid neuropsychological vulnerabilities. To this end, Tarter et al. and Kirisci et al. recently conducted a cross-sectional and longitudinal analysis of children at low and high risk of substance use (on the basis of parental substance use history) and found that deficits in behavioural regulation (referred to as ‘neurobehavioural inhibition’) at age 16 in high-risk children predicted a substance use disorder at age 19 with 85% accuracy [117, 124]. Their measure of behavioural regulation was derived using primarily prefrontal tests of cognition (e.g. Stroop interference task, Porteus mazes, motor restraint), affect (a temperament survey) and behaviour (number of behavioural disorder symptoms). The indices derived from these areas converge with other evidence to suggest that behavioural dysregulation is a key component of liability to drug addiction.

The initiation of substance use typically occurs during adolescence, a critical period of neural, cognitive, emotional, and social development. Notably, adolescence is a period during which there is increased affective reactivity together with significant but more protracted neural maturation [125–129] in areas associated with core executive and self-regulatory skills, including inhibitory control and affect regulation [129]. Given that the frontotemporal regions undergo dramatic developmental changes from adolescence to adulthood, drug exposure during adolescence may disrupt the functional maturation of these regions (i.e. inhibitory control and affect regulation). Indeed, there is growing evidence that adolescent rodents appear to be more vulnerable than adults to the adverse neuropsychological and neurobiological effects of addictive substances [130, 131], although studies in human subjects have been limited to date [132–136].

Finally, genetic factors appear to account for 30–60% of the overall variance in risk for developing a drug addiction [137]. While the precise mechanisms underlying this relationship remain unclear, recent work implicates the role of specific genetic polymorphisms. For example, the methionine polymorphism of the catechol O-methyltransferase (COMT) gene results in a slower breakdown of prefrontal dopamine, and is associated with better prefrontal cortical function (including working memory and inhibitory control) in both children [138] and adults [139, 140]. This polymorphism is less common in drug-addicted populations, thereby potentially increasing vulnerability to prefrontally mediated cognitive deficits with chronic drug use [141, 142].

Pathways into drug addiction: implications for neuropsychological interrelations

Long-term substance abuse is associated with significant and persistent neuropsychological impairments and neurobiological abnormalities, involving frontotemporal and basal ganglia circuits. However, it is not clear how broader individual characteristics that are common to addicted populations (e.g. psychopathology, genetic polymorphisms, head injury), and that also affect neuropsychological functioning, contribute to the reported findings. Age of onset of substance use is also clearly important given the plasticity of the developing brain, and may further accentuate the magnitude of neuropsychological and neurobiological impairments. We suggest that future neuropsychological evaluations of long-term substance abusing populations consider the potential influence of such factors.

As illustrated in Figure 1, the pathways leading to drug addiction are likely to be both multifaceted and complex. There is likely to be an intricate relationship between pre-existing neuropsychological vulnerabilities, the age of initiation of substance use (or neurodevelopmental maturity), patterns of substance use (type, dosage, duration, frequency) and associated adverse events (head injury, overdose, suicide). This latter issue is exemplified by Darke et al., who found that these associated adverse events increased the likelihood of neuropsychological impairment in drug-using groups [66]. Similarly, Solomon and Malloy critically reviewed how a head injury can modulate the relationship between substance use and neuropsychological functioning [19]. Clearly, each of these areas can confound the association between substance use and neuropsychological impairment, as well as impact upon the development and functional integrity of prefrontal circuitry, which is postulated to play an important role in the initiation and maintenance of drug-use behaviours. These adverse effects are likely to render the individual at increased risk for making decisions that are impulsive, focused on short-term gains, and lack inhibitory control. Such impairments may underpin difficulties regulating drug-seeking/taking behaviour, as well as increase the risk for the development of comorbid disorders. However, the integrity of prefrontal circuitry is also likely to depend on a number of individual factors, ranging from genetic polymorphisms through to psychosocial variables. Such relationships need further investigation, especially as few prospective, longitudinal neuropsychological studies have been conducted to date, and most previous studies have sought to specifically exclude such confounds rather than examine potential interactions.

Figure 1.

Neuropsychological model illustrating how substance-associated neuropsychological sequelae may interact with adolescent neurodevelopment and pre-existing neuropsychological vulnerabilities to increase risk for addictive disorders. PFC, Prefrontal Cortex.

In closing, it should be noted that the selective review of studies highlighted in the present paper may have biased reporting toward positive findings with regard to neuropsychological sequelae of the major substances of abuse. Nevertheless, we endeavoured to maintain a balance by also acknowledging negative findings. A systematic and comprehensive review that covers all of the published literature on neuropsychological sequelae of substance use in humans was beyond the scope of this paper but would be a welcome addition to the literature and would enable a more rigorous exploration of the hypotheses we pose here.

Footnotes

Acknowledgements

Dr Murat Yücel is supported by an NHMRC Program Grant (ID 350241). Melbourne Neuropsychiatry Centre is supported by the Department of Psychiatry, University of Melbourne and Melbourne Health. Dr Dan I. Lubman and Assoc. Professor Warrick J. Brewer are supported by the Colonial Foundation. Assoc. Professor Warrick J. Brewer is supported by an NHMRC Clinical Career Development Award.

References

1. Bechara

Dolan

Denburg

Hindes

Anderson

Nathan

. Decision-making deficits, linked to a dysfunctional ventromedial prefrontal cortex, revealed in alcohol and stimulant abusers. Neuropsychologia 2001; 39: 376–389.

2. Fillmore

. Drug abuse as a problem of impaired control: current approaches and findings. Behav Cogn Neurosci Rev 2003; 2: 179–197.

3. Goldstein

Volkow

. Drug addiction and its underlying neurobiological basis: neuroimaging evidence for the involvement of the frontal cortex. Am J Psychiatry 2002; 159: 1642–1652.

4. Grant

Contoreggi

London

. Drug abusers show impaired performance in a laboratory test of decision making. Neuropsychologia 2000; 38: 1180–1187.

5. Jentsch

Taylor

. Impulsivity resulting from frontostriatal dysfunction in drug abuse: implications for the control of behavior by reward-related stimuli. Psychopharmacology (Berl) 1999; 146: 373–390.

6. Lubman

Yucel

Pantelis

. Addiction, a condition of compulsive behaviour? Neuroimaging and neuropsychological evidence of inhibitory dysregulation. Addiction 2004; 99: 1491–1502.

7. Yucel

Lubman

. Neurocognitive and neuroimaging evidence of behavioural dysregulation in human drug addiction: implications for diagnosis, treatment and prevention. Drug Alcohol Rev 2007; 26: 33–39.

8. Volkow

Hitzemann

Wang

. Long-term frontal brain metabolic changes in cocaine abusers. Synapse 1992; 11: 184–190.

9. Yucel

Lubman

Harrison

. A combined spectroscopic and functional MRI investigation of the dorsal anterior cingulate region in opiate addiction. Mol Psychiatry 2007; 12: 691–702.

10.

10. Yucel

Lubman

Harrison

. Neuronal, physiological and brain-behavioural abnormalities in opiate-addicted individuals. Mol Psychiatry 2007; 12: 611.

11.

11. Fishbein

Herman-Stahl

Eldreth

. Mediators of the stress-substance-use relationship in urban male adolescents. Prev Sci 2006; 7: 113–126.

12.

12. Bowden-Jones

McPhillips

Rogers

Hutton

Joyce

. Risk-taking on tests sensitive to ventromedial prefrontal cortex dysfunction predicts early relapse in alcohol dependency: a pilot study. J Neuropsychiatry Clin Neurosci 2005; 17: 417–420.

13.

13. Scheurich

. Neuropsychological functioning and alcohol dependence. Curr Opin Psychiatry 2005; 18: 319–323.

14.

14. Corral-Varela

Cadaveira

. Neuropsychological aspects of alcohol dependence: the nature of brain damage and its reversibility]. Rev Neurol 2002; 35: 682–687.

15.

15. Parsons

. Neurocognitive deficits in alcoholics and social drinkers: a continuum?. Alcohol Clin Exp Res 1998; 22: 954–961.

16.

16. Beatty

Tivis

Stott

Nixon

Parsons

. Neuropsychological deficits in sober alcoholics: influences of chronicity and recent alcohol consumption. Alcohol Clin Exp Res 2000; 24: 149–154.

17.

17. Parsons

Nixon

. Cognitive functioning in sober social drinkers: a review of the research since 1986. J Stud Alcohol 1998; 59: 180–190.

18.

18. Eckardt

File

Gessa

. Effects of moderate alcohol consumption on the central nervous system. Alcohol Clin Exp Res 1998; 22: 998–1040.

19.

19. Solomon

Malloy

. Alcohol, head injury, and neuropsychological function. Neuropsychol Rev 1992; 3: 249–280.

20.

20. Mann

Agartz

Harper

. Neuroimaging in alcoholism: ethanol and brain damage. Alcohol Clin Exp Res 2001; 25: 104S–109S.

21.

21. Pfefferbaum

Sullivan

Mathalon

Lim

. Frontal lobe volume loss observed with magnetic resonance imaging in older chronic alcoholics. Alcohol Clin Exp Res 1997; 21: 521–529.

22.

22. Hommer

Momenan

Kaiser

Rawlings

. Evidence for a gender-related effect of alcoholism on brain volumes. Am J Psychiatry 2001; 158: 198–204.

23.

23. Hommer

Momenan

Rawlings

. Decreased corpus callosum size among alcoholic women. Arch Neurol 1996; 53: 359–363.

24.

24. Sullivan

Rosenbloom

Lim

Pfefferbaum

. Longitudinal changes in cognition, gait, and balance in abstinent and relapsed alcoholic men: relationships to changes in brain structure. Neuropsychology 2000; 14: 178–188.

25.

25. Sullivan

Rosenbloom

Pfefferbaum

. Pattern of motor and cognitive deficits in detoxified alcoholic men. Alcohol Clin Exp Res 2000; 24: 611–621.

26.

26. Volkow

Wang

Hitzemann

. Recovery of brain glucose metabolism in detoxified alcoholics. Am J Psychiatry 1994; 151: 178–183.

27.

27. Grant

Gonzalez

Carey

Natarajan

Wolfson

. Non-acute (residual) neurocognitive effects of cannabis use: a meta-analytic study. J Int Neuropsychol Soc 2003; 9: 679–689.

28.

28. Fletcher

Page

Francis

. Cognitive correlates of long-term cannabis use in Costa Rican men. Arch Gen Psychiatry 1996; 53: 1051–1057.

29.

29. Pope

Jr Yurgelun-Todd

. The residual cognitive effects of heavy marijuana use in college students. JAMA 1996; 275: 521–527.

30.

30. Pope

Jr Gruber

Hudson

Cohane

Huestis

Yurgelun-Todd

. Early-onset cannabis use and cognitive deficits: what is the nature of the association?. Drug Alcohol Depend 2003; 69: 303–310.

31.

31. Pope

Jr Gruber

Hudson

Huestis

Yurgelun-Todd

. Neuropsychological performance in long-term cannabis users. Arch Gen Psychiatry 2001; 58: 909–915.

32.

32. Bolla

Brown

Eldreth

Tate

Cadet

. Dose-related neurocognitive effects of marijuana use. Neurology 2002; 59: 1337–1343.

33.

33. Solowij

Stephens

Roffman

. Cognitive functioning of long-term heavy cannabis users seeking treatment. JAMA 2002; 287: 1123–1131.

34.

34. Eldreth

Matochik

Cadet

Bolla

. Abnormal brain activity in prefrontal brain regions in abstinent marijuana users. Neuroimage 2004; 23: 914–920.

35.

35. Solowij

. Cannabis and cognitive functioning. Cambridge University Press, Cambridge 1998.

36.

36. Block

O'Leary

Ehrhardt

. Effects of frequent marijuana use on brain tissue volume and composition. Neuroreport 2000; 11: 491–496.

37.

37. Kanayama

Rogowska

Pope

Gruber

Yurgelun-Todd

. Spatial working memory in heavy cannabis users: a functional magnetic resonance imaging study. Psychopharmacology (Berl) 2004; 176: 239–247.

38.

38. Smith

Fried

Hogan

Cameron

. The effects of prenatal and current marijuana exposure on response inhibition: a functional magnetic resonance imaging study. Brain Cogn 2004; 54: 147–149.

39.

39. Gruber

Yurgelun-Todd

. Neuroimaging of marijuana smokers during inhibitory processing: a pilot investigation. Brain Res Cogn Brain Res 2005; 23: 107–118.

40.

40. Bolla

Eldreth

Matochik

Cadet

. Neural substrates of faulty decision-making in abstinent marijuana users. Neuroimage 2005; 26: 480–492.

41.

41. Matochik

Eldreth

Cadet

Bolla

. Altered brain tissue composition in heavy marijuana users. Drug Alcohol Depend 2005; 77: 23–30.

42.

42. Tzilos

Cintron

Wood

. Lack of hippocampal volume change in long-term heavy cannabis users. Am J Addict 2005; 14: 64–72.

43.

43. Brust

. Neurological aspects of substance abuse. Butterworth-Heinemann, Boston 1993.

44.

44. Lubman

Hides

Yucel

. Inhalant misuse in youth: time for a coordinated response. Med J Aust 2006; 185: 327–330.

45.

45. Rosenberg

Grigsby

Dreisbach

Busenbark

Grigsby

. Neuropsychologic impairment and MRI abnormalities associated with chronic solvent abuse. J Toxicol Clin Toxicol 2002; 40: 21–34.

46.

46. Maruff

Burns

Tyler

Currie

. Neurological and cognitive abnormalities associated with chronic petrol sniffing. Brain 1998; 121(Pt 10)1903–1917.

47.

47. Chadwick

Anderson

Bland

Ramsey

. Neuropsychological consequences of volatile substance abuse: a population based study of secondary school pupils. BMJ 1989; 298: 1679–1683.

48.

48. Takagi

, Lubman

, Yücel

. Interpreting neuropsychological impairment amongst adolescent inhalant users: two case reports Acta Neuropsychiatr (in press).

49.

49. Yamanouchi

Okada

Kodama

. White matter changes caused by chronic solvent abuse. AJNR Am J Neuroradiol 1995; 16: 1643–1649.

50.

50. Yamanouchi

Okada

Kodama

. Effects of MRI abnormalities on WAIS-R performance in solvent abusers. Acta Neurol Scand 1997; 96: 34–39.

51.

51. Cairney

Maruff

Burns

Currie

. Saccade dysfunction associated with chronic petrol sniffing and lead encephalopathy. J Neurol Neurosurg Psychiatry 2004; 75: 472–476.

52.

52. Cairney

Maruff

Burns

Currie

. Neurological and cognitive recovery following abstinence from petrol sniffing. Neuropsychopharmacology 2005; 30: 1019–1027.

53.

53. Caldemeyer

Pascuzzi

Moran

Smith

. Toluene abuse causing reduced MR signal intensity in the brain. AJR Am J Roentgenol 1993; 161: 1259–1261.

54.

54. Ehyai

Freemon

. Progressive optic neuropathy and sensorineural hearing loss due to chronic glue sniffing. J Neurol Neurosurg Psychiatry 1983; 46: 349–348.

55.

55. Ryu

Lee

Yoon

Jeon

Kim

Shin

. Cerebral perfusion impairment in a patient with toluene abuse. J Nucl Med 1998; 39: 632–633.

56.

56. Aydin

Sencer

Ogel

Genchellac

Demir

Minareci

. Single-voxel proton MR spectroscopy in toluene abuse. Magn Reson Imaging 2003; 21: 777–785.

57.

57. Filley

Heaton

Rosenberg

. White matter dementia in chronic toluene abuse. Neurology 1990; 40: 532–534.

58.

58. Deleu

Hanssens

. Toluene induced postural tremor. J Neurol Neurosurg Psychiatry 2000; 68: 118.

59.

59. Rosenberg

Kleinschmidt-DeMasters

Davis

Dreisbach

Hormes

Filley

. Toluene abuse causes diffuse central nervous system white matter changes. Ann Neurol 1988; 23: 611–614.

60.

60. Davis

Liddiard

McMillan

. Neuropsychological deficits and opiate abuse. Drug Alcohol Depend 2002; 67: 105–108.

61.

61. Pau

Lee

Chan

. The impact of heroin on frontal executive functions. Arch Clin Neuropsychol 2002; 17: 663–670.

62.

62. Guerra

Sole

Cami

Tobena

. Neuropsychological performance in opiate addicts after rapid detoxification. Drug Alcohol Depend 1987; 20: 261–270.

63.

63. Ornstein

Iddon

Baldacchino

. Profiles of cognitive dysfunction in chronic amphetamine and heroin abusers. Neuropsychopharmacology 2000; 23: 113–126.

64.

64. Rogers

Everitt

Baldacchino

. 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: 322–339.

65.

65. Lee

Pau

. Impulse control differences between abstinent heroin users and matched controls. Brain Inj 2002; 16: 885–889.

66.

66. Darke

Sims

McDonald

Wickes

. Cognitive impairment among methadone maintenance patients. Addiction 2000; 95: 687–695.

67.

67. Ersche

Fletcher

Lewis

. Abnormal frontal activations related to decision-making in current and former amphetamine and opiate dependent individuals. Psychopharmacology (Berl) 2005; 180: 612–623.

68.

68. Lyoo

Pollack

Silveri

. Prefrontal and temporal gray matter density decreases in opiate dependence. Psychopharmacology (Berl) 2006; 184: 139–144.

69.

69. Kivisaari

Kahkonen

Puuskari

Jokela

Rapeli

Autti

. Magnetic resonance imaging of severe, long-term, opiate-abuse patients without neurologic symptoms may show enlarged cerebrospinal spaces but no signs of brain pathology of vascular origin. Arch Med Res 2004; 35: 395–400.

70.

70. Ersche

Clark

London

Robbins

Sahakian

. Profile of executive and memory function associated with amphetamine and opiate dependence. Neuropsychopharmacology 2006; 31: 1036–1047.

71.

71. Maxwell

. Emerging research on methamphetamine. Curr Opin Psychiatry 2005; 18: 235–242.

72.

72. Nordahl

Salo

Leamon

. Neuropsychological effects of chronic methamphetamine use on neurotransmitters and cognition: a review. J Neuropsychiatry Clin Neurosci 2003; 15: 317–325.

73.

73. Rippeth

Heaton

Carey

. Methamphetamine dependence increases risk of neuropsychological impairment in HIV infected persons. J Int Neuropsychol Soc 2004; 10: 1–14.

74.

74. Salo

Nordahl

Possin

. Preliminary evidence of reduced cognitive inhibition in methamphetamine-dependent individuals. Psychiatry Res 2002; 111: 65–74.

75.

75. Gonzalez

Rippeth

Carey

. Neurocognitive performance of methamphetamine users discordant for history of marijuana exposure. Drug Alcohol Depend 2004; 76: 181–190.

76.

76. Woods

Rippeth

Conover

. Deficient strategic control of verbal encoding and retrieval in individuals with methamphetamine dependence. Neuropsychology 2005; 19: 35–43.

77.

77. Strickland

Mena

Villanueva-Meyer

. Cerebral perfusion and neuropsychological consequences of chronic cocaine use. J Neuropsychiatry Clin Neurosci 1993; 5: 419–427.

78.

78. Bolla

Rothman

Cadet

. Dose-related neurobehavioral effects of chronic cocaine use. J Neuropsychiatry Clin Neurosci 1999; 11: 361–369.

79.

79. Rogers

Robbins

. Investigating the neurocognitive deficits associated with chronic drug misuse. Curr Opin Neurobiol 2001; 11: 250–257.

80.

80. Ardila

Rosselli

Strumwasser

. Neuropsychological deficits in chronic cocaine abusers. Int J Neurosci 1991; 57: 73–79.

81.

81. Gouzoulis-Mayfrank

Schreckenberger

Sabri

. Neurometabolic effects of psilocybin, 3,4-methylenedioxyethylamphetamine (MDE) and d-methamphetamine in healthy volunteers. A double-blind, placebo-controlled PET study with [18F]FDG. Neuropsychopharmacology 1999; 20: 565–581.

82.

82. Iyo

Namba

Yanagisawa

Hirai

Yui

Fukui

. Abnormal cerebral perfusion in chronic methamphetamine abusers: a study using 99MTc-HMPAO and SPECT. Prog Neuropsychopharmacol Biol Psychiatry 1997; 21: 789–796.

83.

83. Volkow

Chang

Wang

. Low level of brain dopamine D2 receptors in methamphetamine abusers: association with metabolism in the orbitofrontal cortex. Am J Psychiatry 2001; 158: 2015–2021.

84.

84. Volkow

Chang

Wang

. Loss of dopamine transporters in methamphetamine abusers recovers with protracted abstinence. J Neurosci 2001; 21: 9414–9418.

85.

85. Volkow

Chang

Wang

. Association of dopamine transporter reduction with psychomotor impairment in methamphetamine abusers. Am J Psychiatry 2001; 158: 377–382.

86.

86. Thompson

Hayashi

Simon

. Structural abnormalities in the brains of human subjects who use methamphetamine. J Neurosci 2004; 24: 6028–6036.

87.

87. Ernst

Chang

Leonido-Yee

Speck

. Evidence for long-term neurotoxicity associated with methamphetamine abuse: a 1H MRS study. Neurology 2000; 54: 1344–1349.

88.

88. Nordahl

Salo

Natsuaki

. Methamphetamine users in sustained abstinence: a proton magnetic resonance spectroscopy study. Arch Gen Psychiatry 2005; 62: 444–452.

89.

89. Nordahl

Salo

Possin

. Low N-acetyl-aspartate and high choline in the anterior cingulum of recently abstinent methamphetamine-dependent subjects: a preliminary proton MRS study. Magnetic resonance spectroscopy. Psychiatry Res 2002; 116: 43–52.

90.

90. Bartzokis

Beckson

. Age-related brain volume reductions in amphetamine and cocaine addicts and normal controls: implications for addiction research. Psychiatry Res 2000; 98: 93–102.

91.

91. Di Sclafani

Tolou-Shams

Price

Fein

. Neuropsychological performance of individuals dependent on crack-cocaine, or crack-cocaine and alcohol, at 6 weeks and 6 months of abstinence. Drug Alcohol Depend 2002; 66: 161–171.

92.

92. Fein

Di Sclafani

Meyerhoff

. Prefrontal cortical volume reduction associated with frontal cortex function deficit in 6-week abstinent crack-cocaine dependent men. Drug Alcohol Depend 2002; 68: 87–93.

93.

93. Gouzoulis-Mayfrank

Daumann

. Neurotoxicity of methylenedioxyamphetamines (MDMA; ecstasy) in humans: how strong is the evidence for persistent brain damage?. Addiction 2006; 101: 348–361.

94.

94. McGuire

. Long term psychiatric and cognitive effects of MDMA use. Toxicol Lett 2000; 112–113: 153–156.

95.

95. Montoya

Sorrentino

Lukas

Price

. Long-term neuropsychiatric consequences of “ecstasy” (MDMA): a review. Harv Rev Psychiatry 2002; 10: 212–220.

96.

96. Bolla

McCann

Ricaurte

. Memory impairment in abstinent MDMA (“Ecstasy”) users. Neurology 1998; 51: 1532–1537.

97.

97. McCardle

Luebbers

Carter

Croft

Stough

. Chronic MDMA (ecstasy) use, cognition and mood. Psychopharmacology (Berl) 2004; 173: 434–439.

98.

98. Morgan

Impallomeni

Pirona

Rogers

. Elevated impulsivity and impaired decision-making in abstinent Ecstasy (MDMA) users compared to polydrug and drug-naive controls. Neuropsychopharmacology 2006; 31: 1562–1573.

99.

99. Spatt

Glawar

Mamoli

. A pure amnestic syndrome after MDMA (“ecstasy”) ingestion. J Neurol Neurosurg Psychiatry 1997; 62: 418–419.

100.

100. Jacobsen

Mencl

Pugh

Skudlarski

Krystal

. Preliminary evidence of hippocampal dysfunction in adolescent MDMA (“ecstasy”) users: possible relationship to neurotoxic effects. Psychopharmacology (Berl) 2004; 173: 383–390.

101.

101. Daumann

Fischermann

Heekeren

Henke

Thron

Gouzoulis-Mayfrank

. Memory-related hippocampal dysfunction in poly-drug ecstasy (3,4-methylenedioxymethamphetamine) users. Psychopharmacology (Berl) 2005; 180: 607–611.

102.

102. Daumann

Jr Fischermann

Heekeren

Thron

Gouzoulis-Mayfrank

. Neural mechanisms of working memory in ecstasy (MDMA) users who continue or discontinue ecstasy and amphetamine use: evidence from an 18-month longitudinal functional magnetic resonance imaging study. Biol Psychiatry 2004; 56: 349–355.

103.

103. Daumann

Pelz

Becker

Tuchtenhagen

Gouzoulis-Mayfrank

. Psychological profile of abstinent recreational Ecstasy (MDMA) users and significance of concomitant cannabis use. Hum Psychopharmacol 2001; 16: 627–633.

104.

104. Daumann

Schnitker

Weidemann

Schnell

Thron

Gouzoulis-Mayfrank

. Neural correlates of working memory in pure and polyvalent ecstasy (MDMA) users. Neuroreport 2003; 14: 1983–1987.

105.

105. Cowan

Lyoo

Sung

. Reduced cortical gray matter density in human MDMA (Ecstasy) users: a voxel-based morphometry study. Drug Alcohol Depend 2003; 72: 225–235.

106.

106. Morgan

McFie

Fleetwood

Robinson

. Ecstasy (MDMA): are the psychological problems associated with its use reversed by prolonged abstinence?. Psychopharmacology (Berl) 2002; 159: 294–303.

107.

107. Jacobsen

Pugh

Constable

Westerveld

Mencl

. Functional correlates of verbal memory deficits emerging during nicotine withdrawal in abstinent adolescent cannabis users. Biol Psychiatry 2007; 61: 31–40.

108.

108. Lewinsohn

Hops

Roberts

Seeley

Andrews

. Adolescent psychopathology: I. Prevalence and incidence of depression and other DSM-III-R disorders in high school students. J Abnorm Psychol 1993; 102: 133–144.

109.

109. Hasin

Goodwin

Stinson

Grant

. Epidemiology of major depressive disorder: results from the National Epidemiologic Survey on Alcoholism and Related Conditions. Arch Gen Psychiatry 2005; 62: 1097–1106.

110.

110. Button

Hewitt

Rhee

Young

Corley

Stallings

. Examination of the causes of covariation between conduct disorder symptoms and vulnerability to drug dependence. Twin Res Hum Genet 2006; 9: 38–45.

111.

111. Conway

Compton

Stinson

Grant

. Lifetime comorbidity of DSM-IV mood and anxiety disorders and specific drug use disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. J Clin Psychiatry 2006; 67: 247–257.

112.

112. Kantojarvi

Veijola

Laksy

. Co-occurrence of personality disorders with mood, anxiety, and substance use disorders in a young adult population. J Pers Disord 2006; 20: 102–112.

113.

113. Hides

Lubman

Dawe

. Models of co-occurring substance misuse and psychosis: are personality traits the missing link?. Drug Alcohol Rev 2004; 23: 425–432.

114.

114. Swartz

Wagner

Swanson

. Substance use in persons with schizophrenia: baseline prevalence and correlates from the NIMH CATIE study. J Nerv Ment Dis 2006; 194: 164–172.

115.

115. Bogenschutz

Nurnberg

. Theoretical and methodological issues in psychiatric comorbidity. Harv Rev Psychiatry 2000; 8: 18–24.

116.

116. Brady

Sinha

. Co-occurring mental and substance use disorders: the neurobiological effects of chronic stress. Am J Psychiatry 2005; 162: 1483–1493.

117.

117. Tarter

Kirisci

Mezzich

. Neurobehavioral disinhibition in childhood predicts early age at onset of substance use disorder. Am J Psychiatry 2003; 160: 1078–1085.

118.

118. Acton

. Measurement of impulsivity in a hierarchical model of personality traits: implications for substance use. Subst Use Misuse 2003; 38: 67–83.

119.

119. Stepp

Trull

Sher

. Borderline personality features predict alcohol use problems. J Pers Disord 2005; 19: 711–722.

120.

120. Dawe

Gullo

Loxton

. Reward drive and rash impulsiveness as dimensions of impulsivity: implications for substance misuse. Addict Behav 2004; 29: 1389–1405.

121.

121. Chassin

Fora

King

. Trajectories of alcohol and drug use and dependence from adolescence to adulthood: the effects of familial alcoholism and personality. J Abnorm Psychol 2004; 113: 483–498.

122.

122. Chassin

Pillow

Curran

Molina

Barrera

M Jr

. Relation of parental alcoholism to early adolescent substance use: a test of three mediating mechanisms. J Abnorm Psychol 1993; 102: 3–19.

123.

123. Whittle

Allen

Lubman

Yucel

. The neurobiological basis of temperament: towards a better understanding of psychopathology. Neurosci Biobehav Rev 2006; 30: 511–525.

124.

124. Kirisci

Tarter

Vanyukov

Reynolds

Habeych

. Relation between cognitive distortions and neurobehavior disinhibition on the development of substance use during adolescence and substance use disorder by young adulthood: a prospective study. Drug Alcohol Depend 2004; 76: 125–133.

125.

125. Giedd

Blumenthal

Jeffries

. Brain development during childhood and adolescence: a longitudinal MRI study. Nat Neurosci 1999; 2: 861–863.

126.

126. Gogtay

Giedd

Lusk

. Dynamic mapping of human cortical development during childhood through early adulthood. Proc Natl Acad Sci USA 2004; 101: 8174–8179.

127.

127. Paus

Zijdenbos

Worsley

. Structural maturation of neural pathways in children and adolescents: in vivo study. Science 1999; 283: 1908–1911.

128.

128. Paus

. Mapping brain maturation and cognitive development during adolescence. Trends Cogn Sci 2005; 9: 60–68.

129.

129. Steinberg

. Cognitive and affective development in adolescence. Trends Cogn Sci 2005; 9: 69–74.

130.

130. Scheier

Botvin

. Effects of early adolescent drug use on cognitive efficacy in early-late adolescence: a developmental structural model. J Subst Abuse 1995; 7: 379–404.

131.

131. Lubman

, Yücel

, Hall

. Substances and the adolescent brain: a toxic combination? J Psychopharmacol (in press).

132.

132. De Bellis

Clark

Beers

. Hippocampal volume in adolescent-onset alcohol use disorders. Am J Psychiatry 2000; 157: 737–744.

133.

133. De Bellis

Narasimhan

Thatcher

Keshavan

Soloff

Clark

. Prefrontal cortex, thalamus, and cerebellar volumes in adolescents and young adults with adolescent-onset alcohol use disorders and comorbid mental disorders. Alcohol Clin Exp Res 2005; 29: 1590–1600.

134.

134. Wilson

Mathew

Turkington

Hawk

Coleman

Provenzale

. Brain morphological changes and early marijuana use: a magnetic resonance and positron emission tomography study. J Addict Dis 2000; 19: 1–22.

135.

135. Medina

Schweinsburg

Cohen-Zion

Nagel

Tapert

. Effects of alcohol and combined marijuana and alcohol use during adolescence on hippocampal volume and asymmetry. Neurotoxicol Teratol 2007; 29: 141–152.

136.

136. Tapert

Cheung

Brown

. Neural response to alcohol stimuli in adolescents with alcohol use disorder. Arch Gen Psychiatry 2003; 60: 727–735.

137.

137. Kreek

Nielsen

Butelman

LaForge

. Genetic influences on impulsivity, risk taking, stress responsivity and vulnerability to drug abuse and addiction. Nat Neurosci 2005; 8: 1450–1457.

138.

138. Diamond

Briand

Fossella

Gehlbach

. Genetic and neurochemical modulation of prefrontal cognitive functions in children. Am J Psychiatry 2004; 161: 125–132.

139.

139. Egan

Goldberg

Kolachana

. Effect of COMT Val108/158 Met genotype on frontal lobe function and risk for schizophrenia. Proc Natl Acad Sci USA 2001; 98: 6917–6922.

140.

140. Malhotra

Kestler

Mazzanti

Bates

Goldberg

Goldman

. A functional polymorphism in the COMT gene and performance on a test of prefrontal cognition. Am J Psychiatry 2002; 159: 652–654.

141.

141. Beuten

Payne

. Significant association of catechol-O-methyltransferase (COMT) haplotypes with nicotine dependence in male and female smokers of two ethnic populations. Neuropsychopharmacology 2006; 31: 675–684.

142.

142. Li

Chen

. Association analysis of the DRD4 and COMT genes in methamphetamine abuse. Am J Med Genet B Neuropsychiatr Genet 2004; 129: 120–124.

Understanding Drug Addiction: A Neuropsychological Perspective

Abstract

Keywords

Neuropsychological sequelae of specific drugs

Alcohol

Cannabis

Inhalants

Opiates

Psychostimulants (cocaine, amphetamine/methamphetamine)

3, 4 methylendioxymethamphetamine (MDMA, ecstasy)

Summary

Executive control deficits: broader individual considerations

Pathways into drug addiction: implications for neuropsychological interrelations

Footnotes

Acknowledgements

References