Before humans began farming, our species foraged for safe and nutritious plants. Among the many plants that humans sampled, a small number produced changes in perception, mood, cognition, or arousal. Of these, a smaller subset—opium poppies, coca, tobacco, hemp, and products of fermented plant matter—contained substances that proved strongly rewarding, even though they lacked any nutritional value. Humans learned to purify these substances and later to synthesize related compounds for use as medicines.
For example, morphine, purified from the opium poppy, was chemically modified in attempts to produce compounds with greater specificity for analgesia. Among these was diacetylmorphine, or heroin, which was mistakenly marketed as a nonaddictive treatment for pain and cough. Other drugs, such as the amphetamines and sedative-hypnotics, are wholly synthetic compounds developed for a variety of medical indications.
Addictive drugs include some with approved medical uses (eg, morphine, amphetamines, and benzodiazepines), some that are legal but lacking in medical usefulness (eg, alcohol and tobacco), and some that are illegal in many countries (eg, marijuana). The term drug abuse refers to the use of drugs outside of medical supervision and in a manner that is potentially harmful or illegal. The addictive drugs listed in Table 49–1 produce reward; thus, individuals willingly use them and tend to take them repetitively. Herein lies the central danger of these drugs. When used repetitively they initiate molecular changes in the brain that promote continued drug-taking, behavior that becomes increasingly difficult to control. Individuals who regularly use these drugs impair their health and their ability to function.
Table 49–1Major Classes of Addictive Drugs ||Download (.pdf) Table 49–1 Major Classes of Addictive Drugs
|Class ||Source ||Molecular target ||Examples |
|Opiates ||Opium poppy ||μ opioid receptor (agonist) ||Morphine, methadone, oxycodone, heroin |
|Sedative-hypnotics ||Synthetic ||GABAA receptor (agonist) ||Barbiturates, benzodiazepines |
|Psychomotor stimulants ||Coca leaf Synthetic ||Dopamine transporter (antagonist) ||Cocaine Amphetamines |
|Phencyclidine-like drugs ||Synthetic ||NMDA-type glutamate receptor (antagonist) ||Phencyclidine (PCP, "angel dust") |
|Cannabinoids ||Cannabis ||CB1 cannabinoid receptors (agonist) ||Marijuana |
|Nicotine ||Tobacco ||Nicotinic acetylcholine receptor (agonist) ||Tobacco |
|Ethyl alcohol ||Fermentation ||GABAA receptor (agonist), NMDA-type glutamate receptor (antagonist), and multiple other targets ||Various beverage products |
In people who are vulnerable as a result of genetic and nongenetic risk factors, drug use may progress to addiction, which is defined as compulsive drug use despite significantly negative consequences. The addicted person loses control over drug use—obtaining and using drugs come to dominate all other life goals. Addiction tends to persist despite attempts to limit drug use and despite serious negative consequences for the user, his family, and society.
Perhaps the most challenging and frustrating aspect of addiction is its persistence. Not only is it difficult to interrupt active drug use, but even when a person has successfully stopped using drugs the risk of relapse remains high for many years and in some cases for a lifetime. Even after long periods of abstinence, exposure to reminders (cues) of drug use, such as drug paraphernalia or people or places associated with prior drug use, may trigger intense drug urges and relapse into use. Cue-initiated relapses may occur even in individuals who have strongly resolved never to use drugs again, illustrating that addiction impairs the voluntary control of behavior.
In the laboratory, drug-associated cues elicit drug urges that correlate with physiologic responses, for example, activation of the sympathetic nervous system. Functional brain imaging has revealed that cue-conditioned drug responses activate medial regions of the prefrontal cortex; the amygdala, a structure that is thought to play a role in the consolidation of emotionally charged stimulus-reward associations (see Chapters 48 and 66); and the nucleus accumbens, a component of the brain reward circuitry (Figure 49–5).
PET imaging reveals neural correlates of cue-induced cocaine craving.
A. Subjects were shown neutral or cocaine-related cues and asked, "Do you have a craving or urge for cocaine?" The mean score (horizontal bar) is significantly higher for exposure to cocaine-related cues than for exposure to neutral stimuli, even though the magnitude of the response across individuals varies considerably. Two subjects identified by red and blue dots represent high-level and low-level craving, respectively.
B. Changes in self-reported craving are correlated with changes in metabolic rate in the dorsolateral prefrontal cortex and medial temporal lobe during exposure to cocaine-related cues. Metabolic rate is measured as the regional cerebral metabolic rate for glucose (rCMRglc). The ordinate represents the difference between the average of the responses to the question, "Do you have a craving or urge for cocaine?" in separate sessions with neutral and cocaine-related cues. (Each session lasted 30 minutes, and in each session the question was asked three times.) The abscissa represents the difference in metabolic rate between the two sessions (activity with cocaine cues minus activity with neutral cues).
C. When subjects report a craving for cocaine metabolic activity increases in the dorsolateral prefrontal cortex (DLPFC) and in two medial temporal lobe structures, the amygdala (Am) and parahippocampal gyrus (Ph). Pseudocolored PET images of metabolic activity are spatially aligned with high-resolution structural magnetic resonance images. Metabolic rate markedly increased in the amygdala and parahippocampal gyrus in one subject who reported a large increase in craving during presentation of cocaine-related cues (red dot in parts A and B). This effect is not evident in a subject who reported no increase in craving while exposed to the cocaine-related cues (blue dot in parts A and B). Metabolic activity outside the dorsolateral prefrontal cortex and medial temporal lobe is not shown. (Adapted, with permission, from Grant et al. 1996.)
Addictive Drugs Recruit the Brain's Reward Circuitry
As discussed above, the dopaminergic projections from the ventral tegmental area to the nucleus accumbens and other forebrain structures (Figure 49–4) are a central component of reward circuitry. The major dopamine receptor types in both the dorsal striatum and nucleus accumbens are the D1 and D2 G protein-coupled receptors. The D1 receptors predominate in the prefrontal cortex. A dopamine transporter located on presynaptic neurons terminates the actions of the synaptically released dopamine by pumping it back into the presynaptic terminal (Figure 49–6).
Dopamine and glutamate interact at synaptic spines in nucleus accumbens neurons.
Glutamatergic neurons carrying sensorimotor information from the cerebral cortex and dopaminergic neurons carrying reward-related information from the ventral tegmental area form connections with the same medium spiny neurons in the dorsal striatum and nucleus accumbens. The glutamatergic neurons make excitatory synapses on the heads of dendritic spines and the dopaminergic neurons make en passant connections at the necks of spines.
Both pharmacological studies and analyses of lesions in animals confirm the importance of dopaminergic pathways in brain reward. Behavioral studies of the rewarding properties of drugs, using such paradigms as conditioned place preference or self-administration of drugs (Box 49–2), have found that drugs that block D1 and D2 dopamine receptors diminish the incentive properties of natural rewards and drugs. Similar conclusions have been reached in studies using other experimental disruptions of dopaminergic pathways.
Box 49–2 Animal Models of Drug Addiction
Animal models have played an important role in understanding how addictive drugs produce reward. Two of the most commonly used in research are conditioned place preference and self-administration. Conditioned Place Preference
Animals learn to associate a particular environment with passive exposure to drugs; for example, a rodent may spend more time on the side of a box where it was given cocaine than on the side where it received saline. In experiments using this paradigm animals learn to associate a neutral cue, such as the features of one side of a box, with a reward. This paradigm is believed to demonstrate the strong cue-conditioned effects of addictive drugs and to provide an indirect measure of drug reward. Self-Administration of Drugs
The reinforcing effects of a drug can be demonstrated in experiments in which a specific behavior produces the drug. For example, an animal may be taught that it will receive an injection of a drug every time it presses a particular lever in its cage. The drug acts as a reinforcer if it increases the occurrence of the behavior (pressing the lever) that leads to acquisition of the drug.
In this paradigm the amount of work an animal does to gain access to a given amount of drug indicates the reinforcing strength of the drug. The strength with which different drugs reinforce behavior in animals correlates well with the tendency of each drug to reinforce drug-seeking behavior in humans. Laboratory animals exposed to cocaine readily learn behaviors necessary to self-administer this drug and some of them will give up necessities, such as food and water, or work excessively, even to the point of death, to gain access to cocaine.
Changes in extracellular dopamine levels within the nucleus accumbens and other brain structures can be measured in vivo using a microdialysis catheter. Although this method cannot measure dopamine within individual synapses, it can yield quantitative estimates that are thought to correlate with synaptic release of dopamine. This method demonstrates that all addictive drugs increase extracellular dopamine levels in the nucleus accumbens. Thus psychotropic drugs that do not produce significant dopamine release in the nucleus accumbens are not addictive.
There is one important caveat to what is often called the dopamine hypothesis of reward. Some drugs such as opiates also have receptors in reward pathways that are either parallel with or downstream of dopaminergic synapses. Thus opiates produce reward by both dopamine-dependent and dopamine-independent mechanisms. Mice that are genetically engineered to lack dopamine do not find cocaine to be rewarding but appear to gain significant residual reward from morphine.
Although the ability to increase synaptic dopamine is a shared property of all addictive drugs, they do so by different mechanisms. Psychostimulants, which include cocaine and amphetamines, act on the presynaptic terminals of dopaminergic neurons, and they do so in two different ways. Cocaine binds to and blocks the dopamine transporter on the membrane of presynaptic terminals, causing extracellular dopamine to accumulate to high levels following release. Amphetamines enter the presynaptic terminals of dopaminergic neurons through the dopamine transporter. Once in the cytoplasm they cause reverse transport of dopamine out of storage vesicles through the vesicular transporter and out of the neuron into the synapse through the membrane transporter. Thus the action of cocaine depends on normal vesicular release of dopamine by neurons of the ventral tegmental area, whereas the action of amphetamine does not.
Cocaine and amphetamines have analogous actions on the norepinephrine and serotonin transporters, causing increases in extracellular levels of those neurotransmitters as well. However, pharmacologic blockade and lesion experiments demonstrate that dopamine, not these other neurotransmitters, plays the key role in the rewarding properties of these drugs.
The effects of opiates on reward are more complex than those of the psychostimulants because opiates use both dopamine-dependent and dopamine-independent mechanisms. There are three classes of opioid receptors, μ, δ, and κ, and a structurally related receptor, ORL-1. The morphine-like opiates, including heroin (which is metabolized into morphine), methadone, and oxycodone, bind with highest affinity to μ receptors. The μ receptors are found in several regions of the brain and spinal cord where they serve different functions. In the brain stem and spinal cord they play a critical role in modulating pain information (Chapter 24). In other brain stem regions they play a role in controlling respiration, which is why opiates can cause respiratory arrest in overdose.
The μ receptors are also found throughout brain reward circuitry. In the ventral tegmental area they are found on GABA-ergic interneurons that tonically inhibit the dopaminergic neurons that project to the nucleus accumbens and prefrontal cortex. Opiate binding to these μ receptors inhibits the interneurons, resulting in disinhibition of the dopaminergic neurons and dopamine release. Because μ receptors are also expressed by nucleus accumbens neurons, opiates can also exert rewarding effects independent of dopamine inputs.
Microdialysis demonstrates that nicotine, ethyl alcohol, tetrahydrocannabinol, and phencyclidine all cause dopamine to be released in the nucleus accumbens. In addition to their shared effect—increasing synaptic dopamine in the nucleus accumbens—each family of addictive drugs has unique properties based on the receptors with which they interact (Table 49–1). For example, both morphine and cocaine are rewarding and addictive, morphine-like opiates are analgesic and sedating, and cocaine stimulates arousal.
Addictive Drugs Alter the Long-Term Functioning of the Nervous System
In addition to producing short-term reward and other acute pharmacologic effects, addictive drugs can produce long-term alterations in the functioning of the nervous system. Repeated use of addictive drugs can produce tolerance, dependence, withdrawal, and sensitization to differing degrees, as well as addiction. In humans tolerance, dependence, and withdrawal can all contribute to altered behavior. The behavioral consequences of sensitization, a phenomenon well established in animal models, are less clear for human drug users. None of these states is equivalent to addiction, which is defined as compulsive drug use despite significant negative consequences.
Tolerance refers to the diminishing effect of a drug after repeated ingestion of the drug at a constant dose, or alternatively the need to increase the dose to produce a constant effect. For example, the amount of alcohol needed to get drunk increases with regular use. Tolerance results from homeostatic responses of cells to excessive drug stimulation—molecular and cellular adaptations alter normal physiology to counterbalance the effects of the drug. One mechanism of tolerance is pharmacokinetic, in which induction of hepatic metabolic enzymes increase the rate of metabolic clearance of a drug. Pharmacokinetic adaptation plays almost no role in tolerance for addictive drugs other than alcohol. A second mechanism is pharmacodynamic: The action of a drug within the brain that produces habituation.
Dependence is inferred when withdrawal symptoms occur after drug use is curtailed. Whereas tolerance results from homeostatic mechanisms those associated with dependence alter the basal physiological state of cells and circuits. As long as drug use continues, this altered physiology is masked and symptoms do not occur. Cessation of drug use unmasks the abnormal physiological state, resulting in withdrawal symptoms.
When effects grow stronger with repeated drug use they are said to undergo sensitization. For example, the locomotor activity produced by amphetamine or cocaine increases with repeated use of the drug. In general the stimulant effects of a drug are more likely to increase (sensitization), whereas depressant effects tend to diminish (tolerance).
The mechanisms by which opiates produce tolerance, dependence, and a withdrawal syndrome have been elucidated in studies of the behavior of neurons in the locus ceruleus, the major noradrenergic nucleus in the brain. Acute administration of opiates to rats or mice slows the basal firing rate of locus ceruleus neurons because μ opioid receptors activate a K+ channel that reduces the firing rate. Over time, however, the neurons develop tolerance; their firing rate becomes more normal as the μ receptors become partly uncoupled from channel activation.
Chronic opiate administration also produces dependence that sets the stage for withdrawal. Following chronic opiate administration, blockade of μ receptors by the opioid receptor antagonist naloxone produces a dramatic withdrawal syndrome. (This is observed in laboratory rats, which exhibit such withdrawal symptoms as "wet dog" shakes, as well as in opiate-dependent humans given naloxone to reverse respiratory arrest.) One mechanism that contributes to dependence is the strengthening of a Na+ conductance in locus ceruleus neurons; this adaptation can act to balance the efflux of K+ produced by μ receptor stimulation. The relative excess of Na+ influx following naloxone inhibition of μ receptor-mediated K+ efflux renders the neurons hyperexcitable. This results in burst firing that correlates with withdrawal behaviors.
Historically, dependence and physical withdrawal were thought to be cardinal features of addiction. We now know that they are neither necessary nor sufficient. First, some drugs such as cocaine and amphetamines that readily cause compulsive, "out of control" use may produce little or no dependence and do not produce physical withdrawal. More importantly, the risk of relapse into drugs that can produce physical withdrawal, such as opiates and alcohol, can persist for years after drug use has stopped and withdrawal symptoms have resolved.
If dependence and withdrawal were the central mechanisms of addiction, we could successfully treat addicted people by sequestering them until they were well past the period of withdrawal. Unfortunately this is not the case, as stress or drug-related cues can readily cause relapse. Based on the important role of drug-associated cues in drug-seeking and relapse, some clinical investigators have emphasized the need to consider the neural mechanisms of associative learning as central to addiction.
Dopamine May Act As a Learning Signal
An earlier view of the function of dopamine was that it conveyed "hedonic signals" in the brain and that in humans it was directly responsible for subjective pleasure. From this point of view addiction would reflect the habitual choice of short-term pleasure despite a host of long-term life problems. However, the hedonic principle cannot easily explain the persistence of drug use by addicted persons as negative consequences mount.
In fact, the effects of dopamine have proven to be far more complex than was first thought. Dopamine can be released by stressful as well as by rewarding stimuli. Moreover, rodents lacking dopamine—rats in which dopamine is depleted by 6-hydroxydopamine and mice genetically engineered so that they cannot produce dopamine—continue to exhibit hedonic responses to sucrose.
Wolfram Schultz and his colleagues discovered that dopaminergic neurons have a complex and changing pattern of responses to rewards during learning. In one experiment Schultz trained monkeys to expect juice at a fixed interval after a visual or auditory cue. Before the monkeys learned the predictive cues, the appearance of the juice was unexpected and produced a transient increase above basal levels of firing in dopaminergic neurons. As the monkeys learned that certain cues predict the juice, the timing of the firing changed. The neurons no longer fired in response to presentation of the juice—the reward—but earlier, in response to the predictive visual or auditory cue. If a cue was presented but the reward was withheld, firing paused at the time the reward would have been presented. In contrast, if a reward exceeded expectation or was unexpected, because it appeared without a prior cue, firing was enhanced (Figure 49–7).
Dopaminergic neurons report an error in reward prediction.
Graphs show firing rates recorded from midbrain dopaminergic neurons in awake, active monkeys. Top: A drop of sweet liquid is delivered without warning to a monkey. The unexpected reward (R) elicits a response in the neurons. The reward can thus be construed as a positive error in reward prediction. Middle: The monkey has been trained that a conditioned stimulus (CS) predicts a reward. In this record the reward occurs according to the prediction and does not elicit a response in the neurons because there is no error in the prediction of reward. The neurons are activated by the first appearance of a predicting stimulus but not by the reward. Bottom: A conditioned stimulus predicts a reward that fails to occur. The dopaminergic neurons show a decrease in firing at the time the reward would have occurred. (Reproduced, with permission, from Schultz et al. 1997.)
These observations suggest that dopamine release in the forebrain serves not as a pleasure signal but as a prediction-error signal. A burst of dopamine would signify a reward or reward-related stimulus that had not been predicted; pauses would signify that the predicted reward is less than expected or absent. If a reward is just as expected based on environmental cues, dopaminergic neurons would maintain their tonic (baseline) firing rates. Alterations in dopamine release are thought to modify future responses to stimuli to maximize the likelihood of obtaining rewards and to minimize fruitless pursuits. For natural rewards, like the sweet juice consumed by the monkeys in Schultz's experiments, once the environmental cues for a reward are learned, dopaminergic neuron firing returns toward baseline levels. Schultz has interpreted this to mean that as long as nothing changes in the environment, there is nothing more to learn and therefore no need to alter behavioral responses.
Addictive drugs differ from natural rewards in that they cause dopamine release in the reward circuitry no matter how often they are consumed. Dopamine is released even when these drugs do not produce subjective pleasure. To the brain, consumption of addictive drugs would thus always signal "better than expected" and in this way would continue to influence behavior to maximize drug-seeking and drug-taking. If this idea is correct, it might explain why drug- seeking and consumption become compulsive and why the life of the addicted person becomes focused on drug-taking at the expense of all other pursuits.
These experiments, combined with the importance of cues in promoting drug taking, have suggested that learning and memory might play a central role in addiction. For example, drug-seeking is often initiated by drug-related cues—the people, paraphernalia, bodily sensations, and smells associated with prior drug use. Such cues must, of course, be stored in memory and associated with specific behaviors. Interestingly, dopamine has been implicated in the formation of long-term memories in hippocampal and cerebral cortical circuits (Chapters 66 and 67).
These considerations have led to the idea that when someone uses addictive drugs the release of dopamine strengthens the associative memories that bind drug-related cues to drug urges and drug-seeking. The brain reward circuitry that normally reinforces the pursuit of goals with positive survival value is usurped by drug-related goals.
If dopamine-dependent associative memory processes are involved in the pathogenesis of addiction, what cellular and molecular mechanisms might be involved? Long-term change in synaptic function is a fundamental property of neural circuits involved in learning. The best characterized physiologic mechanisms of such long-term changes in the mammalian brain are long-term potentiation and long-term depression (Chapters 66 and 67). These mechanisms are thought to underlie many different types of learning and memory. Indeed, drug use can lead to synaptic changes similar to long-term potentiation and depression in the striatum and nucleus accumbens, as well as in the midbrain dopaminergic neurons themselves.
Activation of the dopaminergic pathways also resembles learning in that these pathways are capable of initiating many changes in gene expression. Relating these changes to learning-related alterations in synaptic connections and circuit function remains an important challenge. For example, dopamine action at the D1 receptors leads to the activation of the transcription factor cyclic AMP response element binding protein (CREB). CREB has been implicated in diverse memory processes in a variety of species, including the Drosophila fly, the marine snail Aplysia, and mice (Figure 49–8, and see Chapters 66 and 67). In the dorsal striatum and nucleus accumbens, psychostimulants produce phosphorylation of CREB through activation of the D1 receptors and the second messenger cyclic AMP. This leads to activation of the cAMP-dependent protein kinase, which then phosphorylates CREB, leading to its activation. A large number of CREB-regulated genes are thus induced by dopamine and psychostimulants.
Intracellular signaling pathways activated by dopamine and glutamate.
NMDA-type glutamate receptors permit Ca2+ entry, which binds calmodulin. The Ca2+ /calmodulin complex activates two Ca2+ /calmodulin-dependent protein kinases, CaMKII in the cytoplasm and CaMKIV in the cell nucleus. D1 dopamine receptors activate a stimulatory G protein that in turn activates the adenylyl cyclase to produce cyclic adenosine monophosphate (AMP). The cyclic AMP-dependent protein kinase (protein kinase A or PKA) catalytic subunit can enter the nucleus. In this diagram PKA and CaMKIV phosphorylate and thus activate the cyclic AMP response element binding protein (CREB). CREB recruits CREB-binding protein (CBP) and thus activates the RNA polymerase II-dependent transcription of many genes, giving rise to proteins that can alter cellular function. Arc and Homer are localized in synaptic regions; Fos and FosB are transcription factors; and dynorphin gives rise to a family of endogenous opioid peptides. These proteins are thought to contribute both to homeostatic responses to excessive dopamine stimulation and to the remodeling of synapses associated with memory formation. (NMDA, N-methyl-D-aspartate; POL 2, RNA polymerase 2; TBP, TATA binding protein.)