Download VolkowandLi Drug Addiction.2004

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SCIENCE AND SOCIETY
Drug addiction: the neurobiology of
behaviour gone awry
Nora D. Volkow and Ting-Kai Li
Abstract | Drug addiction manifests as a
compulsive drive to take a drug despite
serious adverse consequences. This
aberrant behaviour has traditionally been
viewed as bad ‘choices’ that are made
voluntarily by the addict. However, recent
studies have shown that repeated drug use
leads to long-lasting changes in the brain that
undermine voluntary control. This, combined
with new knowledge of how environmental,
genetic and developmental factors contribute
to addiction, should bring about changes in
our approach to the prevention and
treatment of addiction.
Drugs, both legal (for example, alcohol and
nicotine) and illegal (such as cocaine, methamphetamine, heroin and marijuana) are
misused for various reasons, including for
pleasurable effects, the alteration of mental
state, to improve performance and, in certain
instances, for self-medication of a mental
disorder. Repeated drug use can result in
addiction, which is manifested as an intense
desire for the drug with an impaired ability to
control the urges to take that drug, even at the
expense of serious adverse consequences. To
avoid confusion with physical dependence, the
term ‘drug addiction’ is used here instead of
‘drug dependence’, which is the clinical term
favoured by the Diagnostic and Statistical
Manual of Mental Disorders (fourth edition;
DSM-IV). Physical dependence results in withdrawal symptoms when drugs, such as alcohol
and heroin, are discontinued, but the adaptations that are responsible for these effects are
different from those that underlie addiction.
NATURE REVIEWS | NEUROSCIENCE
The aberrant behavioural manifestations
that occur during addiction have been
viewed by many as ‘choices’ of the addicted
individual, but recent imaging studies have
revealed an underlying disruption to brain
regions that are important for the normal
processes of motivation, reward and inhibitory control in addicted individuals1. This
provides the basis for a different view: that
drug addiction is a disease of the brain, and
the associated abnormal behaviour is the
result of dysfunction of brain tissue, just as
cardiac insufficiency is a disease of the heart
and abnormal blood circulation is the result
of dysfunction of myocardial tissue2 (FIG. 1).
Therefore, although initial drug experimentation and recreational use might be volitional, once addiction develops this control is
markedly disrupted. Although imaging studies consistently show specific abnormalities
in the brain function of addicted individuals, not all addicted individuals show these
abnormalities. This highlights the need for
further research to delineate other neurobiological processes that are involved in
addiction.
Chronic exposure to drugs of abuse is
required for drug addiction, and its expression involves complex interactions between
biological and environmental factors. This
might explain why some individuals become
addicted and others do not, and why attempts
to understand addiction as a purely biological
or a purely environmental disease have been
largely unsuccessful. Recently, important discoveries have increased our knowledge of
how drugs affect gene expression, protein
products and neuronal circuits3, and how
these biological factors might affect human
behaviour. This sets the stage for a better
understanding of how different environmental factors interact with biological factors and
contribute to patterns of behaviour that lead
to addiction.
Here, we summarize how new methodologies that allow us to study genes, molecular
biology and the human brain are providing us
with a greater understanding of drug addiction, and the implications of these findings for
the prevention and treatment of addiction.
Addiction: a developmental disorder
Normal developmental processes might
result in a higher risk of drug use at certain
times in life than others. Experimentation
often starts in adolescence, as does the process
of addiction4 (FIG. 2). Normal adolescentspecific behaviours (such as risk-taking,
novelty-seeking and response to peer pressure) increase the propensity to experiment
with legal and illegal drugs5, which might
reflect incomplete development of brain
regions (for example, myelination of frontal
lobe regions)6 that are involved in the processes of executive control and motivation. In
addition, studies indicate that drug exposure
during adolescence might result in different
neuroadaptations from those that occur
during adulthood. For example, in rodents,
exposure to nicotine during the period that
corresponds to adolescence, but not during
adulthood, led to significant changes in
nicotine receptors and an increased reinforcement value for nicotine later in life7.
Future research might allow us to clarify
whether this is the reason that adolescents
seem to become addicted to nicotine after
less nicotine exposure than adults8. Similarly,
further studies might enable us to determine
whether the increased neuroadaptations to
alcohol that occur during adolescence, compared with those that occur during adulthood9 explain the greater vulnerability to
alcoholism in individuals who start using
alcohol early in life10.
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a Brain
High
Healthy brain
Addicted brain
b Heart
Low
Healthy heart
Myocardial infarction
Figure 1 | Drug addiction as a disease of the brain. Images of the brain (a) in a healthy control and in an
individual addicted to a drug, and parallel images of the heart (b) in a healthy control and in an individual with
a myocardial infarction. The images were obtained with positron emission tomography (PET) and [18F]fluoro2-deoxyglucose (FDG–PET) to measure glucose metabolism, which is a sensitive indicator of damage to
the tissue in the brain and the heart. Note the decreased glucose metabolism in the OFC (orbitofrontal
cortex; arrow) of the addicted person and the decreased metabolism in the myocardial tissue (arrow) in the
person with a myocardial infarct. Damage to the OFC will result in improper inhibitory control and
compulsive behaviour, and damage to the myocardium will result in improper blood circulation. Although
abnormalities in the OFC are some of the most consistent findings in imaging studies of addicted individuals
(including alcoholics), they are not detected in all addicted individuals. This implies that disruption of this
frontal region is not the only mechanism that underlies the addictive process. Heart images courtesy of
H. Schelbert, University of California at Los Angeles.
Neurobiology of drugs of abuse
Many neurotransmitters, including GABA
(γ-aminobutyric acid), glutamate, acetylcholine, dopamine, serotonin and endogenous
opioid peptides, have been implicated in the
effects of the various types of drugs of abuse.
Of these, dopamine has been consistently
associated with the reinforcing effects of most
drugs of abuse. Drugs of abuse increase extracellular dopamine concentrations in limbic
regions, including the nucleus accumbens
(NAc)11,12. Specifically, it seems that the reinforcing effects of drugs of abuse are due to
their ability to surpass the magnitude and
duration of the fast dopamine increases that
occur in the NAc when triggered by natural
reinforcers such as food and sex13. Drugs such
as cocaine, amphetamine, methamphetamine
and ecstasy increase dopamine by inhibiting
dopamine reuptake or promoting dopamine
release through their effects on dopamine
transporters14. Other drugs, such as nicotine,
alcohol, opiates and marijuana, work indirectly
by stimulating neurons (GABA-mediated or
glutamatergic) that modulate dopamine cell
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with the drug become salient. These previously
neutral stimuli then increase dopamine by
themselves and elicit the desire for the drug 21.
This explains why the addicted person is
at risk of relapsing when exposed to an environment where he/she has previously taken
the drug.
If natural reinforcers increase dopamine,
why do they not lead to addiction? The difference might be due to qualitative and quantitative differences in the increases in dopamine
induced by drugs, which are greater in magnitude (at least five- to tenfold) and duration
than those induced by natural reinforcers13. In
addition, whereas the dopamine increases
produced by natural reinforcers in the NAc
undergo habituation, those induced by drugs
of abuse do not12. Non-decremental dopamine stimulation of the NAc from repeated
drug use strengthens the motivational properties of the drug, which does not occur for
natural reinforcers.
firing through their effects on nicotine, GABA,
mu opiate or cannabinoid CB1 receptors,
respectively15.
It seems that increases in dopamine are
not directly related to reward per se, as was
previously believed, but rather to the prediction of reward16 and for salience17. Salience
refers to stimuli or environmental changes
that are arousing or that elicit an attentional–
behavioural switch18. Salience, which, in
addition to reward, applies to aversive, new
and unexpected stimuli, affects the motivation to seek the anticipated reward and facilitates conditioned learning19,20. This provides a
different perspective about drugs, as it implies
that drug-induced increases in dopamine will
inherently motivate further procurement of
more drug (regardless of whether or not the
effects of the drug are consciously perceived
to be pleasurable). Indeed, some addicted
individuals report that they seek the drug
even though its effects are no longer pleasurable. Drug-induced increases in dopamine
will also facilitate conditioned learning, so
previously neutral stimuli that are associated
Neurobiology of drug addiction
Addiction probably results from neurobiological changes that are associated with
chronic and intermittent supraphysiological
perturbations in the dopamine system, which
occur in the same circuits that affect biologically important functions1. We and others
have postulated that adaptations in these
dopaminergic circuits make the addicted
individual more responsive to the supraphysiological increases in dopamine that are
produced by drugs of abuse and less sensitive
to the physiological increases in dopamine
produced by natural reinforcers22. Recent
advances in both molecular biology and
imaging have increased our insight into how
these neural adaptations occur.
At a cellular level, drugs have been
reported to alter the expression of certain
transcription factors (nuclear proteins that
bind to regulatory regions of genes, thereby
regulating their transcription into mRNA), as
well as a wide variety of proteins involved in
neurotransmission in brain regions that are
regulated by dopamine17. The long-lasting
changes that occur in the transcription factors δFosB and cAMP responsive element
binding protein (CREB) after chronic drug
administration are of particular interest
because they modulate the synthesis of proteins that are involved in synaptic plasticity3.
Indeed, chronic drug exposure alters the morphology of neurons in dopamine-regulated
circuits. For example, in rodents, chronic
cocaine or amphetamine administration
increases neuronal dendritic branching and
spine density in the NAc and prefrontal cortex
— an adaptation that is thought to participate
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dopamine release in the NAc25. The adaptations in this pathway seem to be involved in the
relapse that occurs after drug withdrawal in
animals previously trained to self-administer a
drug when they are again exposed to the drug,
a drug stimulus or stress25.
At the circuit level, there is clear evidence
that adaptations in the mesocortical circuit
(including the OFC and CG) cause compulsive
drug administration and poor inhibitory
control, and they probably participate in
relapse. However, adaptations also seem to
occur in the mesolimbic circuit (including the
NAc, amygdala and hippocampus), which
probably cause the enhanced saliency value of
the drug and drug stimuli, and the decreased
sensitivity to natural reinforcers26. Furthermore, adaptations have also been reported in
the nigrostriatal circuit (including the dorsal
striatum), which might underlie habits that
are linked to the rituals of drug consumption27.
80
70
Percent of initiates
60
50
40
30
20
10
0
Child
<12
Teen
12–17
Young
adult
18–25
Adult
>25
Figure 2 | Age at which marijuana use is first
initiated. Data from the National Survey of Drug
Use and Health57.
in the enhanced incentive motivational value
of the drug (a process that results in increased
‘wanting’ in contrast to just ‘liking’ the drug)
in the addicted person23.
At the neurotransmitter level, addictionrelated adaptations have been documented
not only for dopamine, but also for glutamate,
GABA, opiates, serotonin and various neuropeptides. These changes contribute to the
abnormal function of brain circuits. For
example, in individuals who are addicted to
cocaine, imaging studies have documented
that disrupted dopamine activity in the brain
(shown by reductions in dopamine D2 receptors) is associated with abnormal activity
in the orbitofrontal cortex (OFC) and in the
anterior cingulate gyrus (CG) — brain regions
that are involved in salience attribution and
inhibitory control24 (FIG. 3). Abnormal function
of these cortical regions has been particularly
revealing in furthering our understanding of
addiction , as their disruption is linked to
compulsive behaviour (OFC) and disinhibition24 (CG). Therefore, the abnormalities in
these frontal regions could underlie the compulsive nature of drug administration in
addicted individuals and their inability to control their urges to take the drug when they are
exposed to it. In addition, animal studies have
shown that drug-related adaptations in these
frontal regions result in enhanced activity
in the glutamatergic pathway that regulates
NATURE REVIEWS | NEUROSCIENCE
Vulnerability to addiction
Genetic factors. It is estimated that 40–60% of
the vulnerability to addiction is attributable to
genetic factors28. In animal studies, several
genes have been identified that are involved
in drug responses, and their experimental
modifications markedly affect drug selfadministration29. In humans, several chromosomal regions have been linked to drug abuse,
but only a few specific genes have been identified with polymorphisms (alleles) that either
predispose to or protect from drug addiction28.
Some of these polymorphisms interfere with
drug metabolism. For example, specific alleles
for the genes that encode alcohol dehydrogenases ADH1B and ALDH2 (enzymes involved
in the metabolism of alcohol) are reportedly
protective against alcoholism30. Similarly,
polymorphisms in the gene that encodes
cytochrome P-450 2A6 (an enzyme that is
involved in nicotine metabolism) are reportedly protective against nicotine addiction31.
Furthermore, genetic polymorphisms in the
cytochrome P-450 2D6 gene (an enzyme that
is involved in conversion of codeine to morphine) seem to provide a degree of protection
against codeine abuse 32.
Some polymorphisms in receptor genes
that mediate drug effects have also been
associated with a higher risk of addiction. For
example, there is an association between
alcoholism and the genes for the GABA type A
(GABAA) receptors GABRG3 (REF. 33) and
GABRA2 (REF. 34). D2-receptor polymorphisms
have been linked to a higher vulnerability to
drug addiction, although some studies have
failed to replicate this finding28. Replication of
many of the genetic findings in substance
abuse and addiction is still pending.
Environmental factors. Environmental factors
that have been consistently associated with
the propensity to self-administer drugs
include low socio-economic class, poor
parental support and drug availability. Stress
might be a common feature in a wide variety
of environmental factors that increase the risk
for drug abuse. The mechanisms responsible
for stress-induced increases in vulnerability to
drug use and to relapse in people who are
addicted are not yet well understood, but
there is evidence that the stress-responsive
neuropeptide corticotropin-releasing factor is
involved through its effects in the amygdala
and the pituitary–adrenal axis35.
Imaging techniques now allow us to
investigate how environmental factors affect
the brain and how these, in turn, affect the
behavioural responses to drugs of abuse. For
example, in non-human primates, social
status affects D2-receptor expression in the
brain, which in turn affects the propensity for
cocaine self-administration36. Animals that
achieve a dominant status in the group show
increased numbers of D2 receptors and are
reluctant to administer cocaine, whereas
animals that are subordinate have lower
D2-receptor numbers and readily administer
cocaine. As animal studies have shown that
increasing D2 receptors in NAc markedly
decreases drug consumption (which has been
shown for alcohol37), this could provide a
mechanism by which a social stressor could
modify the propensity to self-administer
drugs.
Co-morbidity with mental illness. The risk
for substance abuse and addiction in individuals with mental illness is significantly higher
than for the general population. The high
co-morbidity probably reflects, in part, overlapping environmental, genetic and neurobiological factors that influence drug abuse
and mental illness38.
It is likely that different neurobiological
factors are involved in co-morbidity depending on the temporal course of its development (that is, mental illness followed by drug
abuse or vice versa). In some instances, the
mental illness and addiction seem to cooccur independently39, but in others there
might be a sequential dependency. It has
been proposed that co-morbidity might be
due to the use of the abused drugs to selfmedicate the mental illness in cases in which
the onset of mental illness is followed by
abuse of some types of drug. But, when
drug abuse is followed by mental illness, the
chronic exposure could lead to neurobiological changes, which might explain the increased
risk of mental illness38. For example, the high
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a Dopamine D2 receptors
c
70
Orbitofrontal cortex (OFC)
Metabolism
(micromol/100g/min)
65
60
55
50
45
40
35
30
Control
Cocaine abuser
1.5
2
2.5
3
3.5
4
4.5
4
4.5
D2-receptor availability
b Brain glucose metabolism
70
Cingulate gyrus (CG)
Metabolism
(micromol/100g/min)
65
OFC
60
55
50
45
40
35
Control
Cocaine abuser
1.5
2
2.5
3
3.5
D2-receptor availability
Figure 3 | Dopamine D2 receptors and glucose metabolism in addiction. a,b | Positron emission
tomography (PET) images showing dopamine D2 receptors and brain glucose metabolism in the OFC
(orbitofrontal cortex) in controls and in individuals who abuse cocaine. Note that the individuals abusing
cocaine have reductions in D2 receptors and in OFC metabolism. c | Correlation between measures of D2
receptors and brain glucose metabolism in the OFC and anterior cingulate gyrus (CG). The lower the D2receptor expression, the lower the metabolism in the OFC and CG. Decreased activity in the OFC, a brain
region that is implicated in salience attribution and whose disruption results in compulsive behaviour, could
underlie the compulsive drug administration that occurs in addiction. Decreased activity in the CG, a brain
region that is involved in inhibitory control, could underlie the inability to restrain from taking the drug when
the addicted person is exposed to them58.
prevalence of smoking that is initiated after
individuals experience depression could
reflect, in part, the antidepressant effects of
nicotine as well as the antidepressant effects
of monoamine oxidase A and B (MAO-A
and -B) inhibition by cigarette smoke40. On
the other hand, the reported risk for depression with early drug abuse41 could reflect
neuroadaptations in dopamine systems that
might make individuals more vulnerable to
depression.
The higher risk of drug abuse in individuals with mental illnesses highlights the relevance of the early evaluation and treatment
of mental diseases as an effective strategy
to prevent drug addiction that starts as
self-medication.
Strategies to combat addiction
The knowledge of the neurobiology of drugs
and the adaptive changes that occur with
addiction is guiding new strategies for prevention and treatment, and identifying areas
in which further research is required.
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Preventing addiction. The greater vulnerability of adolescents to experimentation with
drugs of abuse and to subsequent addiction
underscores why prevention of early exposure
is such an important strategy to combat drug
addiction. Epidemiological studies show that
the prevalence of drug use in adolescents has
changed significantly over the past 30 years,
and some of the decreases seem to be related
to education about the risks of drugs. For
example, for marijuana, the prevalence rates
of use in the United States in 1979 were as
high as 50%, whereas in 1992 they were as low
as 20% (REF. 42) (FIG. 4). This changing pattern
of marijuana use seems to be related in part to
the perception of the risks associated with the
drug; when adolescents perceived the drug to
be risky, the rate of use was low, whereas when
they did not, the rate of use was high (FIG. 4).
Similarly, the significant decreases in ecstasy
use as well as cigarette smoking in adolescents
seem to partly reflect effective educational
campaigns43. These results show that, despite
the fact that adolescents are at a stage in their
lives when they are more likely to take risks,
interventions that educate them about the
harmful effects of drugs with age-appropriate
messages can decrease the rate of drug use44,45.
However, not all media campaigns and
school-based educational programmes have
been successful46. Tailored interventions that
take into account socio-economic, cultural,
age and gender characteristics of children and
adolescents are more likely to improve the
effectiveness of the interventions.
At present, prevention strategies include
not only educational interventions based on
comprehensive school-based programmes and
effective media campaigns and strategies that
decrease access to drugs and alcohol, but also
strategies that provide supportive community
activities that engage adolescents in productive
and creative ways. However, as we begin to
understand the neurobiological consequences
that underlie the adverse environmental factors that increase the risks for drug use and for
addiction, we will be able to develop interventions to counteract these changes. Similarly, in
the future, as we gain knowledge of the genes
and the proteins that they encode that make a
person more or less vulnerable to taking drugs
and to addiction, more targets will be available
to tailor interventions for those at higher risk.
Treating addiction. The adaptations in the
brain that result from chronic drug exposure
are long lasting; therefore, addiction must be
viewed as a chronic disease. Long-term treatment will be required for most cases, just as
for other chronic diseases (such as hypertension, diabetes and asthma)47. This perspective
modifies our expectations of treatment and
provides a new understanding of relapse.
First, discontinuation of treatment, as for
other chronic diseases, is likely to result in
relapse. Also, as for other chronic medical
conditions, relapse should not be interpreted
as a failure of treatment (as is the view in
most cases of addiction), but instead as a
temporary setback due to lack of compliance
or tolerance to an effective treatment47. Indeed,
the rates of relapse and recovery in the treatment of drug addiction are equivalent to those
of other medical diseases47.
The involvement of multiple brain circuits
(reward, motivation, learning, inhibitory
control and executive function) and their
associated disruption of behaviour indicate
the need for a multimodal approach in the
treatment of the addicted individual. Therefore, interventions should not be limited to
inhibiting the rewarding effects of a drug, but
should also include strategies to enhance the
saliency value of natural reinforcers (including
social support), strengthen inhibitory control,
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PERSPECTIVES
Percentage of 18–19 year olds
(such as 12-step programmes (self-help support groups whose members attempt recovery
from addiction, in part, by ‘admitting’ that they
have a problem and by sharing experiences))
would be more effective if complemented with
medications that could help the patient remain
drug free.
Past year use
Perceived risk
50
40
30
20
10
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
Year
Figure 4 | Use and risk perception of marijuana. The prevalence rate for marijuana use in the past
12 months and the perception of marijuana as a dangerous drug in 12th graders (18–19 years old) from
1979 to 2003 (REF. 42). When teenagers perceived marijuana as dangerous, the prevalence of drug use
was low and vice versa.
decrease conditioned responses and improve
mood if disrupted. The most obvious multimodal approach is the combination of pharmacological and behavioural interventions,
which might target different underlying factors and therefore have synergistic effects. For
example, it might be predicted that addiction
treatments that use behavioural interventions
Pharmacological intervention. Pharmacological interventions can be grouped into two
classes. First, there are those that interfere with
the reinforcing effects of drugs of abuse (that is,
medications that interfere with the binding of
the drug, drug-induced dopamine increase,
postsynaptic responses or with the drug’s
delivery to the brain, or medications that
trigger aversive responses). Second, there are
those that compensate for the adaptations that
either pre-dated or developed after long-term
use (that is, medications that decrease the
prioritized motivational value of the drug,
enhance the saliency value of natural reinforcers, interfere with conditioned responses,
interfere with stress-induced relapse or interfere with physical withdrawal). The usefulness
Table 1 | Medications for Treating Drug and Alcohol Addiction*
Clinical target
Medication
Biological target
Disulfiram (Antabuse; Wyeth-Ayerst)
Naltrexone
Acamprosate
‡
Topiramate61 (Topamax; Ortho-McNeil)
‡
Valproate62
Ondansetron63
Nalmefene64
Baclofen65 (Lioresal; Novartis)
Pyrrolopyrimidine compound66 (Antalarmin;
George Chrousos et al.)
Rimonabant (Acomplia; Sanofi-Synthelabo)67
Aldehyde dehydrogenase (triggers aversive response)
Mu opioid receptor (antagonist; interferes with reinforcement)
Glutamate related
GABA/glutamate
GABA/glutamate
5-HT3 receptor
Mu opioid receptor (antagonist)
GABAB receptor (agonist)
CRF1 receptor (inhibits stress-triggered responses)
Nicotine replacement
Bupropion
Deprenyl69
Rimonabant (Acomplia; Sanofi-Synthelabo)67
Methoxsalen70
Nicotine conjugate vaccine71 (NicVax;
Nabi Biopharmaceuticals)
Nicotinic receptor (substitution with different pharmacokinetics)
DA transporter blocker (amplifies DA signals)
MAO-B inhibitor (inhibits metabolism of DA)
CB1-receptor (antagonist)
CYP2A6 (inhibits nicotine metabolism)
Blocks entry into brain
Alcoholism
FDA approved60
Under investigation
CB1 receptor (antagonist)
Nicotine addiction
FDA approved68
Under investigation
Heroin/opiate addiction
FDA approved72
Naltrexone
Methadone
Buprenorphine
Mu opioid receptor (antagonist)
Mu opioid receptor (substitution with different
pharmacokinetics)
Mu opioid receptor (substitution)
Topiramate73 (Topamax; Ortho-McNeil)
γ-vinyl GABA (GVG)74 (Sabril; Hoechst Marion Roussel)
‡
Gabapentin75 (Neurontin; Parke-Davis)
‡
Tiagabine76 (Gabitril; Abbott)
Baclofen77 (Lioresal; Novartis)
Modafinil78
Disulfiram79 (Antabuse; Wyeth-Ayerst)
Cocaine vaccine71 (TA-CD; Xenova)
GABA (agonist)
GABA transaminase (inhibits GABA metabolism)
GABA/glutamate (synthesis)
GABA transporter (inhibitor)
GABAB receptor (agonist)
Glutamate (?)
Unknown for cocaine
Blocks entry into brain
Cocaine addiction
Under investigation
‡
‡
*Medications used for physical withdrawal are not included. ‡Antiepileptic drugs that have been shown to decrease both drug-induced dopamine
(DA) increases and conditioned responses. FDA, Food and Drug Administration; GABA, γ-aminobutyric acid; GABAB, GABA type B; 5-HT3,
5-hydroxytryptamine (serotonin) receptor subtype 3; MAO-B, monoamine oxidase B.
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Challenges for society
Brain
Lungs
Heart
Liver
Kidneys
Non-smoker
Smoker
Figure 5 | Monoamine oxidase B concentration and cigarette smoking. Positron emission
tomography (PET) images of the concentration of the enzyme MAO-B (monoamine oxidase B) in the
body of a healthy control and of a cigarette smoker. There are significant decreases in the concentration
of the enzyme throughout the body of the smoker. Reproduced, with permission, from REF. 59 © (2003)
National Academy of Sciences, USA.
of some of the medications for drug addiction has been clearly validated; for others the
data are still preliminary, and for most the
results are limited to promising preclinical
findings. TABLE 1 summarizes proven medications as well as medications for which there
are preliminary clinical data. Many of these
promising new medications target different
neurotransmitters (such as GABA, cannabinoids or glutamate) from the older drugs,
offering a wider range of therapeutic options.
Cognitive–behavioural intervention. In a
similar fashion, behavioural interventions
can be classified by their intended remedial
function, such as to strengthen inhibitory
control circuits, to provide alternative reinforcers and to strengthen executive function.
Traditionally, behavioural therapy has focused
on symptom-based targets rather than
underlying causes of addiction. However, for
other brain disorders, new views of brain
plasticity, which recognize the capacity of
neurons in the adult brain to increase synaptic connections and in certain instances to
regenerate48, have resulted in more focused
cognitive–behavioural interventions designed
to increase the efficiency of dysfunctional
brain circuits. This has been applied in
attempts to improve reading in children with
learning disabilities49 and to facilitate motor
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and memory rehabilitation after brain
injury50, but has not yet been applied to the
remediation of brain circuits altered by drug
abuse. Dual approaches that pair cognitive–
behavioural strategies with medications to
compensate or counteract the neurobiological
changes induced by chronic drug exposure
might, in the future, provide more robust
and longer lasting treatments for addiction
than either given in isolation.
Treating co-morbidities. Abuse of multiple
substances, such as alcohol and nicotine or
alcohol and cocaine, should be considered
in the proper management of the addicted
individual. Similarly, co-morbidities with
mental illness will require treatment for
the mental illness concurrent with treatment
for drug abuse.
As drugs of abuse adversely affect many
organs in the body (FIG. 5), uncontrolled consumption contributes to the burden of many
medical diseases, including cancer, cardiovascular and pulmonary diseases, HIV/AIDS and
hepatitis C, as well as to accidents and violence. Therefore, substance-abuse treatment
will help to prevent or improve the outcome
for medical diseases. For example, drug abuse
is a leading contributor to the spread of HIV/
AIDS, and treatment of addiction in some
instances prevents its dissemination51,52.
In most cases, drug abuse and addiction
alienates the individual from both family
and community, increasing isolation and
interfering with treatment and recovery. As
both the family and the community provide
integral aspects of effective treatment and
recovery, this identifies an important challenge: to reduce the stigma of addiction that
interferes with intervention and proper
rehabilitation.
Effective treatment of drug addiction in
many individuals requires consideration of
social policy, such as the treatment of drug
addiction in the criminal justice system, the
role of unemployment in vulnerability to
the use of drugs and family dysfunctions
that contribute to stress and that might
block the efficacy of otherwise effective
interventions. For example, studies have
shown that providing drug treatment to
prisoners who were substance abusers and
continuing the treatment after they left the
prison dramatically reduced not only their
rate of relapse to drugs, but also their rate of
re-incarceration53,54. Similarly, drug courts
in the United States, which incorporate drug
treatment into the judicial system, have
proved to be beneficial in decreasing drug
use and arrests of offenders who are
involved in drug-taking55. However, despite
these preliminary positive results, there are
still many unanswered questions that future
research should address. For example, what
are the active ingredients in the treatment of
the drug offender? How does the system
deal with the fact that few offenders stay
in treatment long enough to receive the
minimally required services? What are the
implications of these findings for pre-trial
diversion laws, post-prison re-entry initiatives
and so on?
The recognition of addiction as a disease
that affects the brain might be essential for
large-scale prevention and treatment programmes that require the participation of the
medical community. Engagement of paediatricians and family physicians (including the
teaching of addiction medicine as part of
medical students’ training) might facilitate
early detection of drug abuse in childhood
and adolescence. Moreover, screening for
drug use could help clinicians better manage
medical diseases that are likely to be adversely
affected by the concomitant use of drugs,
such as cardiac and pulmonary diseases.
Unfortunately, physicians, nurses, psychologists and social workers receive little training in the management of addiction, despite
it being one of the most common chronic
disorders.
www.nature.com/reviews/neuro
PERSPECTIVES
The participation of the medical community in many countries, including the
United States, is further curtailed by the lack
of reimbursement by most private medical
insurance policies for the evaluation or
treatment of drug abuse and addiction. This
lack of reimbursement limits the treatment
infrastructure and the choices that the
addicted person has with respect to their
treatment. It also sends a negative message
to medical students who are interested in
clinical practice, discouraging them from
choosing a speciality for which the reimbursement of their services is limited by the
lack of parity.
Another considerable obstacle in the
treatment of addiction is the limited involvement of the pharmaceutical industry in the
development of new medications. Issues
such as stigma, lack of reimbursement for
drug-abuse treatment and the lack of a large
market all contribute to the limited involvement of the pharmaceutical industry in the
development of medications to treat drug
addiction. The importance of this issue
was identified by the Institute of Medicine of
the United States, which recommended a
programme to provide incentives to the
pharmaceutical industry as a way of helping
to address this problem56.
The translation of scientific findings in
drug abuse into prevention and treatment
initiatives clearly requires partnership with
federal agencies such as the Substance Abuse
and Mental Health Services Administration
(SAMHSA, which is responsible for U.S. programmes to prevent and treat drug abuse)
and the Office of National Drug Control
Policy (ONDCP, which is responsible for
U.S. programmes to control availability and
reduce demand for drugs of abuse). Furthermore, improved prevention and treatment
programmes could result from collaborations with other agencies and groups, such
as the Department of Education (which can
bring prevention interventions into the school
environment), the Department of Justice
(which can implement treatment strategies
that will minimize the chances of recidivism
and re-incarceration of inmates with
drug-abuse problems) and state and local
agencies (which can bring evidence-based
and science-based treatments into the
communities).
As we learn more about the neurobiology
of normal and pathological human behaviour, a challenge for society will be to use this
knowledge to effectively guide public policy.
For example, as we understand the neurobiological substrates that underlie voluntary
actions, how will society define the boundaries
NATURE REVIEWS | NEUROSCIENCE
of personal responsibility in those individuals
who have impairments in these brain circuits?
This will have implications not only for the
management of drug offenders, but also of
other offenders with diagnoses such as antisocial personality disorder or conduct disorder.
At present, critics of the medical model of
addiction argue that this model removes the
responsibility of the addicted individual from
his/her behaviour. However, the value of the
medical model of addiction as a public policy
guide is not to excuse the behaviour of the
addicted individual, but to provide a framework to understand it and to treat it more
effectively.
1.
Summary
9.
Remarkable scientific advances have been
made in genetics, molecular biology, behavioural neuropharmacology and brain imaging that offer new insights into how the
human brain works and moulds behaviour.
In the case of addiction, we can now investigate questions that were previously inaccessible, such as how environmental factors and
genes affect the responses of the brain to
drugs and produce neural adaptations that
lead to the aberrant behavioural manifestations of addiction. This new knowledge is
helping us to understand why drug addicts
relapse even in the face of threats such as
divorce, loss of child custody and incarceration, even when, in some cases, the drug is no
longer perceived as pleasurable, and is changing how we should approach prevention and
treatment of addiction.
The field is at a crossroads where major
advances in understanding the neurobiology of addiction have helped identify
promising new medications, but where the
translation of these findings into clinical
practice is limited by several factors, including the limited involvement of the medical
community in the treatment of addiction,
the restricted involvement of the pharmaceutical industry, the lack of reimbursement
by private insurance policies and the
stigma associated with drug addiction. One of
the main challenges for agencies like the
National Institute on Drug Abuse (NIDA)
and the National Institute on Alcohol Abuse
and Alcoholism (NIAAA) is to develop
knowledge that will help to overcome these
obstacles.
Nora Volkow is at the National Institute on Drug
Abuse, Bethesda, Maryland 20892, USA.
Ting-Kai Li is at the National Institute on Alcohol
Abuse and Alcoholism, Bethesda, Maryland
20892, USA.
e-mail: [email protected]
doi:1038/nrn1539
2.
3.
4.
5.
6.
7.
8.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
Volkow, N. D., Fowler, J. S. & Wang, G. J. The addicted
human brain: insights from imaging studies. J. Clin.
Invest. 111, 1444–1451 (2003).
Leshner, A. I. Addiction is a brain disease, and it matters.
Science 278, 45–47 (1997).
Nestler, E. J. Molecular basis of long-term plasticity
underlying addiction. Nature Rev. Neurosci. 2, 119–128
(2001).
Wagner, F. A. & Anthony, J. C. From first drug use to drug
dependence: developmental periods of risk for
dependence upon marijuana, cocaine, and alcohol.
Neuropsychopharmacology 26, 479–488 (2002).
Spear, L. P. The adolescent brain and age-related
behavioral manifestations. Neurosci. Biobehav. Rev. 24,
417–463 (2000).
Sowell, E. R. et al. Mapping cortical change across the
human life span. Nature Neurosci. 6, 309–315
(2003).
Adriani, W. et al. Evidence for enhanced neurobehavioral
vulnerability to nicotine during periadolescence in rats.
J. Neurosci. 23, 4712–4716 (2003).
Kandel, D. B. & Chen, K. Extent of smoking and nicotine
dependence in the United States: 1991–1993. Nicotine.
Tob. Res. 2, 263–274 (2000).
Slawecki, C. J. & Roth, J. Comparison of the onset of
hypoactivity and anxiety-like behavior during alcohol
withdrawal in adolescent and adult rats. Alcohol Clin.
Exp. Res. 28, 598–607 (2004).
Grant, B. F., Stinson, F. S. & Harford, T. C. Age at onset of
alcohol use and DSM-IV alcohol abuse and dependence:
a 12-year follow-up. J. Subst. Abuse 13, 493–504 (2001).
Koob, G. F. & Bloom, F. E. Cellular and molecular
mechanisms of drug dependence. Science 242,
715–723 (1988).
Di Chiara, G. Nucleus accumbens shell and core
dopamine: differential role in behavior and addiction.
Behav. Brain Res. 137, 75–114 (2002).
Wise, R. A. Brain reward circuitry: insights from unsensed
incentives. Neuron 36, 229–240 (2002).
Madras, B. K., Fahey, M. A., Bergman, J., Canfield, D. R.
& Spealman, R. D. Effects of cocaine and related drugs in
nonhuman primates. I. [3H]cocaine binding sites in
caudate-putamen. J. Pharmacol. Exp. Ther. 251,
131–141 (1989).
Kreek, M. J., LaForge, K. S. & Butelman, E.
Pharmacotherapy of addictions. Nature Rev. Drug
Discov. 1, 710–726 (2002).
Schultz, W., Tremblay, L. & Hollerman, J. R. Reward
processing in primate orbitofrontal cortex and basal
ganglia. Cereb. Cortex 10, 272–284 (2000).
Lu, L., Grimm, J. W., Shaham, Y. & Hope, B. T. Molecular
neuroadaptations in the accumbens and ventral
tegmental area during the first 90 days of forced
abstinence from cocaine self-administration in rats.
J. Neurochem. 85, 1604–1613 (2003).
Horvitz, J. C. Mesolimbocortical and nigrostriatal
dopamine responses to salient non-reward events.
Neuroscience 96, 651–656 (2000).
McClure, S. M., Daw, N. D. & Montague, P. R.
A computational substrate for incentive salience. Trends
Neurosci. 26, 423–428 (2003).
Schultz, W. Reward signaling by dopamine neurons.
Neuroscientist 7, 293–302 (2001).
Ito, R., Dalley, J. W., Howes, S. R., Robbins, T. W. &
Everitt, B. J. Dissociation in conditioned dopamine
release in the nucleus accumbens core and shell in
response to cocaine cues and during cocaine-seeking
behavior in rats. J. Neurosci. 20, 7489–7495 (2000).
Volkow, N. D., Fowler, J. S., Wang, G. J. & Swanson, J. M.
Dopamine in drug abuse and addiction: results from
imaging studies and treatment implications. Mol.
Psychiatry 9, 557–569 (2004).
Robinson, T. E., Gorny, G., Mitton, E. & Kolb, B. Cocaine
self-administration alters the morphology of dendrites
and dendritic spines in the nucleus accumbens and
neocortex. Synapse 39, 257–266 (2001).
Volkow, N. D. & Fowler, J. S. Addiction, a disease of
compulsion and drive: involvement of the orbitofrontal
cortex. Cereb. Cortex 10, 318–325 (2000).
McFarland, K., Davidge, S. B., Lapish, C. C. & Kalivas, P. W.
Limbic and motor circuitry underlying footshock-induced
reinstatement of cocaine-seeking behavior. J. Neurosci.
24, 1551–1560 (2004).
Martin-Soelch, C. et al. Changes in reward-induced brain
activation in opiate addicts. Eur. J. Neurosci. 14,
1360–1368 (2001).
Porrino, L. J., Lyons, D., Smith, H. R., Daunais, J. B. &
Nader, M. A. Cocaine self-administration produces a
progressive involvement of limbic, association, and
sensorimotor striatal domains. J. Neurosci. 24,
3554–3562 (2004).
VOLUME 5 | DECEMBER 2004 | 9 6 9
PERSPECTIVES
28. Uhl, G. R. & Grow, R. W. The burden of complex genetics
in brain disorders. Arch. Gen. Psychiatry 61, 223–229
(2004).
29. Laakso, A., Mohn, A. R., Gainetdinov, R. R. & Caron, M. G.
Experimental genetic approaches to addiction. Neuron
36, 213–228 (2002).
30. Chen, C. C. et al. Interaction between the functional
polymorphisms of the alcohol-metabolism genes in
protection against alcoholism. Am. J. Hum. Genet. 65,
795–807 (1999).
31. Rao, Y. et al. Duplications and defects in the CYP2A6
gene: identification, genotyping, and in vivo effects on
smoking. Mol. Pharmacol. 58, 747–755 (2000).
32. Kathiramalainathan, K. et al. Inhibition of cytochrome
P450 2D6 modifies codeine abuse liability. J. Clin.
Psychopharmacol. 20, 435–444 (2000).
33. Dick, D. M. et al. Association of GABRG3 with alcohol
dependence. Alcohol Clin. Exp. Res. 28, 4–9 (2004).
34. Edenberg, H. J. et al. Variations in GABRA2, encoding
the α2 subunit of the GABAA receptor, are associated
with alcohol dependence and with brain oscillations.
Am. J. Hum. Genet. 74, 705–714 (2004).
35. Koob, G. F. Stress, corticotropin-releasing factor, and
drug addiction. Ann. NY Acad. Sci. 897, 27–45 (1999).
36. Morgan, D. et al. Social dominance in monkeys:
dopamine D2 receptors and cocaine self-administration.
Nature Neurosci. 5, 169–174 (2002).
37. Thanos, P. K. et al. Overexpression of dopamine D2
receptors reduces alcohol self-administration.
J. Neurochem. 78, 1094–1103 (2001).
38. Markou, A., Kosten, T. R. & Koob, G. F. Neurobiological
similarities in depression and drug dependence: a selfmedication hypothesis. Neuropsychopharmacology 18,
135–174 (1998).
39. Grant, B. F. et al. Prevalence and co-occurrence of
substance use disorders and independent mood and
anxiety disorders: results from the National Epidemiologic
Survey on Alcohol and Related Conditions. Arch. Gen.
Psychiatry 61, 807–816 (2004).
40. Fowler, J. S., Logan, J., Wang, G. J. & Volkow, N. D.
Monoamine oxidase and cigarette smoking.
Neurotoxicology 24, 75–82 (2003).
41. Brook, D. W., Brook, J. S., Zhang, C., Cohen, P. &
Whiteman, M. Drug use and the risk of major depressive
disorder, alcohol dependence, and substance use
disorders. Arch. Gen. Psychiatry 59, 1039–1044 (2002).
42. Johnston, L. D., O’Malley, P. M. & Bachman, J. G.
Monitoring the future national survey results on drug use,
1975–2002. Volume I: Secondary school students. National
Institutes of Health Publication No. 03-5375, (2003).
43. Johnston, L. D., O’Malley, P. M., Bachman, J. G. &
Schulenberg, J. E. Monitoring the future national survey
results on drug use, 1975–2003. Volume I: Secondary
school students. National Institutes of Health Publication
No. 04-5507, 1–545 (2004).
44. Block, L. G., Morwitz, V. G., Putsis, W. P., Jr & Sen, S. K.
Assessing the impact of antidrug advertising on
adolescent drug consumption: results from a behavioral
economic model. Am. J. Public Health 92, 1346–1351
(2002).
45. Flynn, B. S. et al. Long-term responses of higher and
lower risk youths to smoking prevention interventions.
Prev. Med. 26, 389–394 (1997).
46. Gruber, A. J. & Pope, H. G., Jr Marijuana use among
adolescents. Pediatr. Clin. North Am. 49, 389–413
(2002).
47. McLellan, A. T., Lewis, D. C., O’Brien, C. P. & Kleber, H. D.
Drug dependence, a chronic medical illness: implications
for treatment, insurance, and outcomes evaluation.
JAMA 284, 1689–1695 (2000).
48. Schaffer, D. V. & Gage, F. H. Neurogenesis and
neuroadaptation. Neuromolecular Med. 5, 1–9 (2004).
49. Kujala, T. et al. Plastic neural changes and reading
improvement caused by audiovisual training in readingimpaired children. Proc. Natl Acad. Sci. USA 98,
10509–10514 (2001).
50. Fraser, C. et al. Driving plasticity in human adult motor
cortex is associated with improved motor function after
brain injury. Neuron 34, 831–840 (2002).
51. Kelley, M. S. & Chitwood, D. D. Effects of drug treatment
for heroin sniffers: a protective factor against moving to
injection? Soc. Sci. Med. 58, 2083–2092 (2004).
52. Treatment for cocaine use may have HIV benefits. Study
shows how to achieve best results. Aids Alert 18,
118–119 (2003).
53. Butzin, C. A., Martin, S. S. & Inciardi, J. A. Evaluating
component effects of a prison-based treatment
continuum. J. Subst. Abuse Treat. 22, 63–69 (2002).
54. Hiller, M. L., Knight, K. & Simpson, D. D. Prison-based
substance abuse treatment, residential aftercare and
recidivism. Addiction 94, 833–842 (1999).
970
| DECEMBER 2004 | VOLUME 5
55. Fielding, J. E., Tye, G., Ogawa, P. L., Imam, I. J. & Long,
A. M. Los Angeles County drug court programs: initial
results. J. Subst. Abuse Treat. 23, 217–224 (2002).
56. Fulco, C. E., Liverman, C. T. & Earley, L. E. (eds)
Development of Medications for the Treatment of Opiate
and Cocaine Addictions: Issues for the Government and
Private Sector (Institute of Medicine). (National Academy
Press, Washington DC, 1995).
57. Gfroerer, J. C., Wu, L.-T. & Penne, M. A. Initiation of
marijuana use: trends, patterns and implications. SMA
02-3711. Analytic Series A–17. Substance Abuse and
Mental Health Services Administration, Office of Applied
Studies, Rockville, Maryland (2002).
58. Goldstein, R. Z. & Volkow, N. D. Drug addiction and its
underlying neurobiological basis: neuroimaging evidence
for the involvement of the frontal cortex. Am. J.
Psychiatry 159, 1642–1652 (2002).
59. Fowler, J. S. et al. Low monoamine oxidase B in
peripheral organs in smokers. Proc. Natl Acad. Sci. USA
100, 11600–11605 (2003).
60. Anton, R. F. Pharmacologic approaches to the
management of alcoholism. J. Clin. Psychiatry 62
(Suppl. 20), 11–17 (2001).
61. Johnson, B. A. et al. Oral topiramate for treatment of
alcohol dependence: a randomised controlled trial.
Lancet 361, 1677–1685 (2003).
62. Salloum, I. M. et al. Efficacy of valproate maintenance in
bipolar alcoholics: a double blind placebo controlled
study. Arch. Gen. Psychiatry (in the press).
63. Johnson, B. A. et al. Ondansetron for reduction of
drinking among biologically predisposed alcoholic
patients: a randomized controlled trial. JAMA 284,
963–971 (2000).
64. Mason, B. J., Salvato, F. R., Williams, L. D., Ritvo, E. C. &
Cutler, R. B. A double-blind, placebo-controlled study of
oral nalmefene for alcohol dependence. Arch. Gen.
Psychiatry 56, 719–724 (1999).
65. Addolorato, G. et al. Baclofen efficacy in reducing alcohol
craving and intake: a preliminary double-blind
randomized controlled study. Alcohol Alcohol. 37,
504–508 (2002).
66. Webster, E. L. et al. In vivo and in vitro characterization of
antalarmin, a nonpeptide corticotropin-releasing
hormone (CRH) receptor antagonist: suppression of
pituitary ACTH release and peripheral inflammation.
Endocrinology 137, 5747–5750 (1996).
67. Fernandez, J. R. & Allison, D. B. Rimonabant SanofiSynthelabo. Curr. Opin. Investig. Drugs 5, 430–435
(2004).
68. George, T. P. & O’Malley, S. S. Current pharmacological
treatments for nicotine dependence. Trends Pharmacol.
Sci. 25, 42–48 (2004).
69. George, T. P. et al. A preliminary placebo-controlled trial
of selegiline hydrochloride for smoking cessation. Biol.
Psychiatry 53, 136–143 (2003).
70. Sellers, E. M., Ramamoorthy, Y., Zeman, M. V.,
Djordjevic, M. V. & Tyndale, R. F. The effect of
71.
72.
73.
74.
75.
76.
77.
78.
79.
methoxsalen on nicotine and 4-(methylnitrosamino)-1(3-pyridyl)-1-butanone (NNK) metabolism in vivo.
Nicotine Tob. Res. 5, 891–899 (2003).
Kosten, T. R. & Biegel, D. Therapeutic vaccines for
substance dependence. Expert Rev. Vaccines 1,
363–371 (2002).
Krupitsky, E. M. et al. Naltrexone for heroin dependence
treatment in St. Petersburg, Russia. J. Subst. Abuse
Treat. 26, 285–294 (2004).
Kampman, K. M. et al. A pilot trial of topiramate for the
treatment of cocaine dependence. Drug Alcohol Depend.
75, 233–240 (2004).
Brodie, J. D., Figueroa, E. & Dewey, S. L. Treating
cocaine addiction: from preclinical to clinical trial
experience with γ-vinyl GABA. Synapse 50, 261–265
(2003).
Raby, W. N. & Coomaraswamy, S. Gabapentin reduces
cocaine use among addicts from a community clinic
sample. J. Clin. Psychiatry 65, 84–86 (2004).
Gonzalez, G. et al. Tiagabine increases cocaine-free
urines in cocaine-dependent methadone-treated
patients: results of a randomized pilot study. Addiction
98, 1625–1632 (2003).
Shoptaw, S. et al. Randomized placebo-controlled trial of
baclofen for cocaine dependence: preliminary effects for
individuals with chronic patterns of cocaine use. J. Clin.
Psychiatry 64, 1440–1448 (2003).
Dackis, C. & O’Brien, C. Glutamatergic agents for
cocaine dependence. Ann. NY Acad. Sci. 1003,
328–345 (2003).
Carroll, K. M. et al. Efficacy of disulfiram and cognitive
behavior therapy in cocaine-dependent outpatients:
a randomized placebo-controlled trial. Arch. Gen.
Psychiatry 61, 264–272 (2004).
Acknowledgments
The authors thank T. Condon, M. Egli, J. Fowler, C. Kassed,
R. Litten, A. Noronha and J. Swanson for thoughtful comments
and editorial assistance.
Competing interests statement
The authors declare no competing financial interests.
Online links
FURTHER INFORMATION
Encyclopedia of Life Sciences: http://www.els.net/
Addiction | Adaptations: meanings | Alcoholism | Cocaine and
amphetamines | Opiates
National Institute on Drug Abuse:
http://www.drugabuse.gov/NIDAHome.html
Office of National Drug Control Policy:
http://www.whitehousedrugpolicy.gov/
Substance Abuse and Mental Health Services
Administration: http://www.samhsa.gov/index.aspx
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Fallacies in behavioural interpretation of auditory cortex plasticity
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