2013 年全國藥物濫用防治研討會
楊鳳霞 Hada Fong-ha Ieong
Literature Review
Craving: the Neurotoxic and Social-cognitive Effects of
Drugs Consumptions of Adults, Adolescences, including
Prenatal Exposure to Drugs of Abuse
Author: Hada Fong-ha Ieong1
MSc, Forensic Toxicology, Department of Forensics Vet Medicine/Forensics
Pharmacy, Health Science Center, University of Florida, USA
Abstract: Substances of abuse affect cognition in a number of ways. One of its indirect
effects include craving, which has been an important factor to relapse to substance abuse.
Peer-induced craving is a powerful form of this construct. The brain mechanisms
involved in drug craving or the urge have been studied in recent years. As the social
contagion and wrong association in peer groups are the main causes to substance abuse
and relapse, understanding the mechanisms involved in processing a peer’s thought and
behavior will be beneficial in the rehabilitation treatment. This literature review
highlights the short-term neurotoxicity of drugs of abuse and its long-term consequence
of cognitive deficits in the brain and mind of abusers, including adults, adolescences and
prenatal exposure of drugs of abuse, as well as the genetic factors associated. The review
also provides a window into complex social-cognitive relations in which drug abusers not
only try to think of what the other abusers are thinking or behaving, but also attempt to
measure and seek craving responses to external and internal related stimuli – i.e. why and
what the others’ craving reaction affect one’s thoughts and behaviors.
Keywords: addiction; craving; cognition; neurotoxicity; social cognition
Date: 15 August 2013
Table of Contents
1 Author for correspondence ([email protected])
Note: This review is to present on The 8th Mainland, Hong Kong and Macau Conference on Prevention of Drug
Abuse - 29 October – 1 November 2013 (Grants: Activity A2013500610 – Social Welfare Bureau).
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Abstract ………………………………………………………………………………
1
Table of Contents ……………………………………………………………….……. 2
CHATPER 1 ………………………………………………………………………….
3
Introduction …………………………………………………………………………..
3
General statement ………………………………………………………………...
3
Statement of Problem …………………………………………………………….
3
Statement of Purpose ……………………………………………………………..
4
Assumptions and Limitations …………………………………………………….
5
CHAPTER 2 ………………………………………………………………………….
6
Literature Review …………………………………………………………………….
6
History of Measuring Drug Craving in Addiction ……………….………………
6
Reward and reinforcement: the “Dopamine Hypothesis” ………………………..
10
Neurotoxic Effects of Acute Drug Administration …………...………………………
11
Cognitive Deficits in Chronic Drug Abuse …………………………………………..
15
Cognition: the Pre-frontal cortex …………………………………………………
16
Drugs of Abuse and the Development Brain …………………………………………
17
Prenatal exposure ………………………………………………………………… 17
Adolescent exposure .. …………………………………………………………… 18
Gene, Drugs and Cognition …………………………………………………………..
19
Pre-clinical Research and Clinical Treatment ………………………………………..
20
Acknowledgement ……………………………………………………………………
22
References ……………………………………………………………………………
23
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楊鳳霞 Hada Fong-ha Ieong
CHATPER 1
Introduction
General statement
Drugs such as heroin are highly addictive substances. Drug craving has been an
important factor to relapse to its abuse, and peer-induced craving is a powerful form of
this construct. To watch a person to inject an illicit drug by a syringe and a needle may
not be a pleasurable experience for most people. However, it may be contagious for drug
addicts. That is, accurately knowing what another is feeling and experiencing for
something, anticipating of its reinforcing effects being felt by another, and feeling an urge
to follow the same behaviors to experience similar effects are elements of craving
(Tiffany, 1990), and they could create a phenomenon of social contagion (Ennett,
Flewelling, Lindrooth & Norton, 1997), as well as chronic vulnerability to relapse (Weiss,
2010). But is the mechanism of the desire or craving the same, when the target is
intrinsically versus extrinsically triggered?
Statement of Problem
The term “craving” should be defined in this study. Prior neuroscientific studies
on craving in addiction among researchers have had diverse definitions of craving. Some
investigators restrict its definition to a desire for drug use, while others define craving
somewhat differently. For example, some have defined craving as behavioral intention to
use a drug is the target (Buydens-Branchey et al., 1997); whereas others, like West &
Schneider (1987) restricted craving to an experience characterized by extreme desire.
One the other hand, some investigators argue that the term “craving” encompasses a more
broad range of phenomena, including the expectation of a drug’s reinforcing effects,
intention to engage in drug use and the desire for the drug (Tiffany & Drobes, 1991).
Marlatt (1985) suggested that the term “craving” be restricted to the desire for the effects
of a drug while using the term “urge” could be used to describe its behavioral intention.
Previous studies on craving have also focused less on its classification as distinct
from mental or psychological obsession (Silkworth, 2013; Baker, 1998; Pelchat, 2009). A
computational neuroscience study (Redish & Johnson, 2007) suggested that a model of
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craving is based on the recognition of a path to a high-value outcome, whereas, obsession
is based on a value-induced limitation of the search process. Craving is considered to be a
subjective, internal feeling or experience when one is aware of a desire (Niaura et al.,
1988; Kassel & Shiffman, 1992), and may or may not always be reflected in external
action, i.e. the high-value outcome (expectation) can only occur in the planning system
but not the habit system (Redish & Johnson, 2007). However, craving could then lead to
a recurring search of the planning system, which would appear as cognitive blinding or
obsession – requiring a forward search component and a memory retrieval process.
Perhaps as a result of such differing definitions of craving, brain regions of interests (ROI)
in craving similarly vary in previous studies.
Statement of Purpose
Understanding the changes in the brain which occur during craving and obsessive
thoughts while processing the addictive behavior of others as a stimulus not only has
major implications in the rehabilitation treatment therapy and the prediction of relapse,
but also for a better understanding of addictive behaviors because of its emphasis on
active cognitive processing, conscious reasoning, and decision-making in using drugs,
quitting drugs, and relapsing to drug use (Niaura, 2000).
The first two reasons of drug abuse are reported to be the lack of restraint or
boundaries in the abuser’s life and the wrong associations with peers who themselves
promote destructive behavior (Maisto & O’Farrell, 1988; Carbb, 2011; Norregaard,
Tonnesen & Petersen, 1993). According to the central tenets of cognitive social learning
theory (CSLT) as they apply to addictive behaviors, human beings live in a social and
cognitive world where behavior is largely associated with the ability to manipulate
cognitively and store symbolic representations of the environment (Bandura, 1977;
Campbell, 1963; Niaura, 2000) – i.e. what and how we think affects what and how we
behave – described as reciprocal determinism (Bandura, 1969; Bandura, 1986), and what
we believe also affects what we think of the others’ thoughts – i.e. Theory of Mind (ToM),
whose neural network includes bilateral temporo-parietal junctions (TPJ), precuneus (PC),
and medial prefrontal cortex (mPFC) regions (Saxe & Kanwisher, 2003). Regions of ToM
are recruited when thinking about others’ mental experience.
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Assumptions and Limitations
One assumption is that there is an overlap between the regions of ToM and the
neural and neuroendocrine mechanisms implicated in drug desire evoked by drug cues
and stress in the complex cognitive functioning.
The limitation is that there is not yet a study in measuring epigenetic and
proteomic changes in living human brains. In terms of molecular and epigenetic studies,
more animal studies are needed to investigate the correlation between genes, proteins and
subtracts associated with addiction. In terms of cognitive functions, brain-imaging
techniques are suggested.
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CHAPTER 2
Literature Review
History of the Measuring Drug Craving in Addiction
Researchers have long posited a relationship between craving and addiction
(Wilker, 1948; World Health Organization, 1995). However the critical elements of this
relationship, and the very nature and validity of craving as a construct, have been
vigorously debated (Mello, 1978; Tiffany, 1990; Kassel & Shiffman, 1992). There has
been a recent increase in the study of craving from a variety of biological and
psychological perspectives (Pickens & Johanson, 1992; Lowman et al., 2000).
Nevertheless, the manner in which craving is measured does not receive sufficient
attention, in addition with the further advancement in craving research is hampered by
divergent conceptualizations and inconsistent measures (Kozlowki & Wilkinson, 1987).
Because there is not a standardized measure of craving, the challenge is to select the
optimal measure(s) for a particular research or clinical application. This review begins
with a brief summary of the principal definitions of craving and related conceptual issues,
the historical self-report measures approaches, mainly the non-verbal measures such as
neurobiological responding and cognitive processing. Second, we review the neurotoxic
effects of acute drug administration. Included in this section is a review of the “Dopamine
hypothesis” in regarding the neurotransmitter dopamine, reward, and learning. Third, we
explore the cognitive deficits in chronic drug abuse regarding cognition in the frontal
lobe and emotion in the mesolimbic lobe. Further, this review includes the findings of
drugs of abuse and the development brain, including prenatal and adolescent exposures.
Finally, factors that may influence the choice of drug use are addressed in hope of
seeking better understanding of the brain network and better treatment.
Although drug craving has been defined in many ways, it is generally been
regarded as a desire to use a drug (Sayette et al., 2000). Craving is usually considered to
be a subjective experience, that is, one must be aware of a desire in order to crave (Niaura
et al., 1988; Kassel & Shiffman, 1992). With few exceptions, like Tiffany (1992), craving
has been conceptualized as “reflecting a drug drug-acquisitive state which motivates drug
use”. In spite of the general appeal of craving as a construct, there are a number of issues
defining craving (Sayette et al., 2000). They are:
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
楊鳳霞 Hada Fong-ha Ieong
Different scope of craving definitions among researchers (BuydensBranchey et al., 1997; Marlatt, 1985; Tiffany & Drobes, 1991; Kozlowshi
et al., 1996)

Debatable time frame of a craving experience (West, Hajek & Belcher,
1989; Anton, Moak & Latham, 1995; Gawin, 1991; Shiffman et al., 1996)

Different characterizations in assessments to craving - a broad continuum
of desire or restriction to extreme desire (West & Schneider, 1987)

Debatable the fact that craving might exist in the absence of awareness
(Miller & Gold, 1994; Berridge & Robinson, 1995)

The degree to which craving and drug use should be associated (Sayette
et al., 2000)
Nearly all conceptualizations of craving assume that drug-motivational can be
indexed through self-report measures of subjective experience (Sayette et al., 2000). As a
matter of fact, the measures are popular due to their high displayed degree of face validity,
and they can easily to be collected.
However, it is problematic to view self-reports of craving, whose interpretation
of the meaning has been described as the correspondence view of test meaning
(Buchwald, 1961; Wiggens, 1973), as providing a direct readout of a person’s craving
state, assuming that a one-to-one mapping of verbal reports to hypothetical internal states.
As noted by Wiggens (1973), in order to achieve “accurate” measurement from the
perspective of the correspondence view, four conditions should be hold. They are:

Craving item(s) have common meaning among participants and between
participants and researchers.

The participant must be able to accurately assess his/her internal state.

The participant must report their internal states honestly to the tester.

The craving item(s) is related to the concept of “craving” as used by the
researcher.
If self-reports of craving are considered to be the gold standard for assessment, six
non-verbal responses, as researcher Sayette (2000) argues, should be considered merely
as behaviors or reactions that are associated with (self-reported) craving. The non-verbal
measures of craving used in research have included reinforcement “proxies”, drug self7
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administration, psychophysiological responding, neurobiological responding, cognitive
processing, and expressive behavior (Sayette et al., 2000).
Drug Reinforcement proxies. For researchers who consider carving as to
motivation to engage in drug use, the degree to which anticipated drug use is perceived to
be reinforcing can be used as a parameter. It often involves assessment of choice
behavior leading to drug administration. Historically craving has been inferred by
determining the cost, such as the amount of work or pain, that an animal or human will
assume in order to obtain a desired drug (Garden & Lowinson, 1993).
Drug self-administration. For researchers who consider craving primarily to
reflect a behavioral intention to use a drug, direct assessment of drug use may be
advisable to self-report measures of craving (Hughes. 1987). Researchers like Berridge &
Robinson (1995) also emphasize measures of drug self-administration in studies where
drug use can be influenced by other forces other than drug craving. For example, one
may experience a strong craving but if the drug is unavailable, or if one wants to quite,
drug use may be ensue. Conversely, one might use a drug in the absence of a craving.
Psychophysiological responding. Changes in heart rate, skin temperature, blood
pressure, skin conductance and salivation have been included in craving studies. Because
these responses have often differed (Niaura et al., 1988; Glautier, Drummond &
Remington, 1992; Carter & Tiffany, 1999), these measures are presumably less
vulnerable to conscious control and thus may be more sensitive than self-report measures
to detecting craving (Bake & Brandon, 1990).
Neurobiological responding. Prior studies have been using both animals and
human to investigate brain structures and processes that may underlie craving (Wise,
1988; Robinson & Berridge, 1993). Measures of glucose metabolism with human
subjects reveal metabolic increases during craving manipulations in particular brain
structures associated with both emotional (e.g. amygdala) and cognitive (e.g.
hippocampus) aspects of memory (Everitt, 1997). It is to note that imaging studies such
as using positron emission tomography (PET) or functional magnetic resonance imaging
(fMRI) can indicate that a specific craving manipulation produces increases in indices of
brain activation where neurobiological changes ma be correlated with craving (Sayette et
al., 2000), and that it has been a trend in recent years.
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Cognitive processing. Craving and the changes in cognitive processing have a
long history of association (Sorokin, 1942; Key et al., 1950). One approach is to assess
the redistribution of cognitive resources during craving involves divided attention tasks.
The secondary response time (RT) is an example of this approach. RT paradigms have
been used to measure the degree a primary task draws on limited-capacity cognitive
resources by recording performance decrements on a secondary RT task (Sayette et al.,
2000). Studies using both smokers and alcoholic subjects have provided evidence that
there are increases in secondary RTs during peak craving periods, relative to non-craving
baseline periods (Sayette et al., 1994; Sayette & Hufford, 1994; Cepeda-Benito & Tiffany,
199; Juliano & Brandon, 1998).
Another cognitive performance approach to assess craving involves explicit
memory tasks such as cued recall (Sayette et al., 2000). Words, for example, that are
most salient to a person, can be presumably to be recalled readily from a previously
learned list. Researchers like Zeitlan, Potts and Hodder (1994) concludes that consistent
with the formulation, abstinence appears to increase ability to recall already presented
smoking-related words. One argument may be raised form this approach is that increased
recall of drug-related words may be caused by encoding strategies rather than the salience
produced by craving.
Some implicit memory tasks have assessed process associated with craving. The
functions of these tasks are to examine the salience of drug-related messages for
individuals without making them aware of the assessments. For example, stem
completions, perceptual identification, categorization tasks and color-naming variants of
the Stroop task have been used for studies of implicit memory providing conflicted
findings, with drug deprivation leading to facilitation (Litz, Payne & Collett, 1987; Jarvik
et al., 1995; Zeitlin et al., 1994; Gross et al., 1993) as well as inhibition (Zeitlin et al.,
1994) in the selective processing of drug-related information.
Expressive behavior. Interesting enough, analysis of facial expressive behavior is
also considered to be a measuring tool of emotional response (Darwin, 1872; Darwin,
1965; Barlow, 1988). The use of a standard and anatomically based facial coding system
may prove useful for detecting craving because craving itself can be affective in nature
(Baker et al., 1987). Avantages of such objective facial coding systems include the
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capacity to comprehensively measure immediate responses, to assess positive and
negative affects as orthogonal dimensions, and to discriminate between different
emotions (Ekman & Rosenberg, 1997). Sayette and Hufford (1995) found that high
craving ratings could be linked to both positive affect-related signals when expecting to
smoke and negative affect-related signals when not permitted to smoke by using the
Facial Action Coding System (FACS: Ekman & Friesen, 1978) to code subjects’
responses to smoking cues under two experimental condition. The limitations of using
FACS include reliance on expressions visible to humans and the restriction to brief
craving coding intervals. As a matter of fact, future studies may need to identify specific
facial action patterns that are associated with craving.
In sum, cognitive tasks have proven useful in suggesting cognitive processes that
may change during craving as well as memory structures associated with craving. Thus,
the appropriate experimental procedures, in which factors such as drug use history of an
individual, level of drug abstinence and presence of drug-related stimuli are identified,
measured or controlled.
Reward and reinforcement: the “Dopamine Hypothesis’
In 2007, neuroscientist celebrated the 50th anniversary of the discovery of the key
neurotransmitter, dopamine, by Arivid Carlsson who won the Nobel Prize for Medicine in
2000 (Bjorklund & Dunnet, 2007). Dopamine is a central neurotransmitter that serves a
variety of functions, including the fine-tuning of mother control and cognitive function;
modulating the salience of events and attention, learning and memory; bonding and
attachment in relationships; and the planning and motivation of behavior. It is widely
accepted that dopamine also plays a significant role in addiction to most drugs of abuse
(Volkow & Li, 2004). Current researches prove that addiction also involves changes
within a number of neurochemicals and neurotransmitter systems such as the endogenous
opioids, glutamate and gamma-aminobutyric acid (GABA), and thus it appears to exert
their influence through the dopaminergic reward circuits (Goodman, 2008).
Amphetamines, cocaine, alcohol, nicotine and cannabis act on a forebrain
structure known as the nucleus accumbens (NAcc) producing large and rapid release of
dopamine (DA) (Robbins et al., 2007). The effects produced by these drugs originate in
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the neurons of the midbrain ventral tegmental area (VTA), which deliver DA into
synapses into the NAcc (Wise & Bozarth, 1987; Koob & Bloom, 1988; Di Chiara, 1998).
Cocaine, amphetamines, and ecstasy directly increase the amount DA available for postsynaptic cleft by increasing the release or by reducing dopamine reuptake from the
synapse (Hutcheson et al., 2001); whereas alcohol, cannabis and nicotine increase DA
activity indirectly by signaling neurons that influence dopaminergic neurons (Koob & Le
Moal, 1997; Nisell et al., 1994).
The neural system involved in learning, reward and motivation has important
association with the NAcc. Addictive drugs produce over 10 times more dopamine in the
NAcc than natural reinforces, in which this excess release of DA by the drugs is
suggested to make drug abuse more appealing than everyday rewarding activities
(Hyman, 2005). Imaging of brain function during intoxication shows that the increase in
DA signaling in the NAcc was believed to give drugs their euphoric or rewarding affects
(Volkow et al., 2004a), that is the greater the DA release in the NAcc, the greater the
euphoria that is reported (Laruelle et al., 1995; Drevets et al., 2001). However, it does not
always happen. Some studies conducted by Robinson and Berirdge (2000) also reflects
that there is a poor correlation between subjective state of pleasure and drug-taking
behavior.
Neurotoxic Effects of Acute Drug Administration
Neurotransmission-associated neurotoxicity. Neurotransmission constitutes an
important part of the functioning central (CNS) and peripheral nervous system (PNS)
through connection of two neurons or nerves via a synapse. Release of chemical signaling
molecules, commonly called neurotransmitters, causes not only signal transduction but
also diverse actions that might alter the physiological response. Interference with
neurotransmission is possible on multiple levels. Moreover, the sole interaction between
the toxicant with the neurotransmitter receptor might not correspond to the resulting
neurotoxicity.
Nicotine is widely available in tobacco products and as a pesticide and as such
causes a significant number of neurotoxicity. It is the main sympathetic and
parasympathetic neurotransmitter in the CNS by binding as an agonist to nicotinic
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acetylcholine receptors. It also is responsible for signal transduction on the
neuromuscular junction in the PNS controlling muscle contractions. The rare occurrence
of acute nicotine overdose therefore results in widespread disturbances of the nervous
system with confusion, reduced heart rate, hypotension, and further may lead to coma and
death by respiratory paralysis. Low chronic exposures on the other hand are a
considerable epidemiologic concern due to the widespread use of tobacco products but it
has been difficult to separate specific nicotine effects from the other substances contained
in tobacco smoke. Cancer, respiratory disorders, cardiovascular diseases, and attention
deficit disorders in children have been associated with tobacco smoke. Exposures of
tobacco smoke components after inhalation by the mother to the fetus may result in
complex neurological disorders or even result in loss of the fetus (Klaassen, 2008).
Cocaine and amphetamines are widely abused and mostly illegal drugs (cocaine
has a few special therapeutically applications). It is a central stimulant that increases heart
rate and leads to vasoconstriction by inhibiting the reuptake of the sympathetic
neurotransmitters dopamine and norepinephrine (a stress neurotransmitter and hormone
released from the sympathetic neurons to affect the brain and heart) as well as serotonin
(a neurotransmitter associates with mood, sleep, well-being and awareness). The high
degree of addiction and feeling of euphoria mainly result from the stimulation of
dopamine release and its action on post-synaptic dopamine D1 receptors. Due to the
stimulatory effects, cocaine abusers are at a greater risk of developing cardiovascular
complications as well as suffering from strokes and intracranial hemorrhage due to
increased cerebrovascular resistance and development of neurodegenerative disorders in
chronic abusers. Similar to cocaine, amphetamines are CNS stimulants that prevent
reuptake of neurotransmitters but in addition directly damage both dopaminergic and
serotonergic axons causing distal axotomy of such neurons. The mechanism of
amphetamine-induced neurodegeneration is not known in detail, but the generation of
reactive species as a consequence of excess dopamine that is oxidized to a Quinone that
might lead to damage and loss of neurons as is the case in Parkinson’s disease (Klaassen,
2008).
N-methyl-D-aspartate (NMDA) receptor or kainic acid (KA) receptor have been
implicated in neural and behavioral plasticity ranging from development to learning
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(Trujillo & Akil, 1995). Excitatory amino acids mainly acidic amino acids similar to
glutamate, the main excitatory neurotransmitter in the brain and also an additive in many
food products to enhance and preserve taste. The effects of glutamate are mediated
through binding to ion channels or G-protein coupled receptors. Specific agonists have
defined the name of the specific receptor such as KA receptor or NMDA receptor.
Glutamate entry into the brain is controlled by active transporter processes in the bloodbrain barrier but in addition it can enter the brain through the circumventricular organs.
Within this susceptible area glutamate damages and kills neurons through activation of
ion channels and therefore leads to uncontrolled leakage of glutamate into the brain. KA
is a potent excitotoxin through activation of specific glutamate receptors and selective
damage to dendrites and neurons. Chronic damage and loss of neurons may result from
such highly specific glutamate receptor agonists that lead to selected cell death which
progresses with loss of memory and ultimately complete neurodegeneration due to the
widespread glutamate receptor distribution in the brain. Other excitotoxins have been
identified as food poisonings and require chronic ingestion to cause the
neurodegenerative disorders observed.
Not surprisingly, it has been well reported that clinicians often observed that
patients undergoing treatment for addiction become highly vulnerable to relapse when
they return to environments where they develop addiction (Hyman, 2005; see 2005).
Clinical studies indicate that cues associated with substance abuse elicit physiological
responses and cravings for drugs (Franklin et al., 2007). Laboratory animals also develop
strong associations and cue-response behaviors in the presence of drug-related stimuli. A
phenomenon called conditioned place preference has been demonstrated in studies using
nicotine, ethanol, amphetamine, methamphetamine, cocaine, morphine, cannabis, and
caffeine – showing the animals given a drug in one compartment of a double cage
subsequently will gravitate to that compartment more than to the alternative compartment
(Bardo & Bevin, 2000). And thus, it is important to understand the formation of drugstimulus association and the persistence of drug-stimulus associations in addiction (Gould,
2010).
The formation of drug-stimulus association. Addiction as mentioned above in the
dopamine hypothesis where NAcc produces rewarding experience caused by a drug,
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attributes addicted individuals’ strong responses to drug cues to a learning process that
inculcates powerful drug-stimulus associations (Robinson & Berridge, 2000). In this view,
the individual taking a drug perceives his or her present surroundings as highly
significant (salient) and makes exceptionally strong mental connections between features
of those surroundings and the intense rewarding experience of the drug. And thus when
the individual re-encounters those features, the strong and powerful association reassert
themselves, are experienced as prompts for drug seeking and drug taking. Studies
conducted by Franklin and his colleagues (2007) and Volkow (2006) suggest that
exposing addicted individuals to cues that they associate with drug abuse elicits changes
in the activity levels of brain regions involved in learning and memory (i.e., stratum,
amygdala, orbitofrontal cortex, hippocampus, thalamus, and left insula). The acute effects
of amphetamine, nicotine, and cocaine fit straightforwardly into this scenario.
The persistence of drug-Stimulus association. Recent research has brought to
lights to the strikingly long-lasting ability of maladaptive drug-stimulus associations to
influence behavior and provoke relapse. Studies have shown that many abused substances
can reshape the communication pathways between neurons (synaptic plasticity) –
contributing to both the formation and the persistence of maladaptive drug-stimulus
associations. Cocaine and nicotine can directly induce one form of synaptic plasticity, the
strengthening of neural connections via a process known as long-term potentiation (LTP)
(Argilli et al., 2008; Kenny & Gould, 2008). Amphetamine can enhance LTP (Delanoy,
Tucci & Gold, 1983). Marijuana activates the endocannabinoid system, resulting in
inhibition in some instances and facilitation in others of loth LTP and long-term
depression (LTD), another form of synaptic plasticity in which connections between
neurons become less responsive (Carlso, Wang & Alger, 2002; Nugent & Kauer, 2008;
Sullivan, 2000). Morphine inhibits LTP of neurons that exhibit inhibitory control of
neural activity via GABA (Nugent & Kauer, 2008), whose activities could lead to a net
increase in neural activity throughout the brain – leading to the formation of stronger
associations including maladaptive drug-context associations (Gould, 2010).
Cognitive Deficits in Chronic Drug Abuse
Drug addicts progress to the withdrawal stage when they initiate abstinence.
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Many drugs produce cognition-related withdrawal symptoms that may make abstinence
harder (Gould, 2010). These include:

Opioids – deficits in cognitive flexibility (Lyvers & Yakimoff, 2003);

Cocaine – deficits in cognitive flexibility (Kelley et al., 2005);

Amphetamine – deficits in attention and impulse control (Dalley et al.,
2005);

Alcohol – deficits in working memory and attention (Moriyama et al.,
2006);

Nicotine – deficits in working memory and declarative learning (Kenney
& Gould, 2008).
While the cognitive deficits associated with withdrawal from dugs are often
temporary, long-term use can also lead to lasting cognitive decline. Long-term cannabis
users have impaired learning, retention, and retrieval of dictated words, and both longterm and short-term users show deficits in time estimation (Solowij et al.,2002), although
how long these deficits persist is unknown. Chronic amphetamine and heroin users, on
the other hand, show deficits in a range of cognitive skills, including verbal fluency,
pattern recognition, planning, and the ability to shift attention from one frame of
reference to another (Ornstein et al., 2000). The deficits in decision-making resembled
those observed in individuals with impairment of the prefrontal cortex, suggesting that
both drugs alter function in the brain area (Rogers et al., 1999).
A pair of neuropsychological studies suggests that some methamphetamineinduced cognitive loss may be partially recouped with extended abstinence (Volkow et al.,
2001; Wang et al., 2004). Evaluated when abstinent for less than 6 months, chronic
methamphetamine abusers scored lower than unexposed controls on motor function
testing, memory for spoken words, and other cognitive tasks. The deficits were believed
to associated with a comparative scarcity of DA transporters and reduced cellular activity
in the thalamus and NAcc. When being retested after twelve to seventeen months of
abstinence, the drug abusers’ motor function and verbal memory had risen back to control
group’s level, and the gains correlated with a return toward normal transporter levels in
the striatum and metabolic levels in the thalamus; nevertheless, along with depressed
activity in the NAcc, other neuropsychological deficits remained.
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In another study, abusers of ecstasy continued to score relative poorly in tests of
immediate and delayed recall of spoken words even after two and a half years of
abstinence (Thomasius et al., 2006). In a study of cocaine-and-heroin abusers, it shows
that it causes deficits in executive functions (e.g. changes in fluency, working memory,
reasoning, response inhibition, cognitive flexibility, and decision-making) remained after
up to five months of abstinence (Verdejo Carcia & Perez-Garcia, 2007).
An important question is thus raised: does an abuse drug’s cognitive deficit
persists as the addictive behaviors shifts from sporadic to chronic?
In some studies with animals, chronic nicotine administration improved cognitive
capacities such as attention, but other found that initial improvement waned with chronic
treatment (Kenny & Gound, 2008). Furthermore, other recent studies have shown that
smoking and a past smoking history are associated with cognitive decline (Nooyen, van
Gelder & Verschuren, 2008). Laboratory studies have also demonstrated nicotine-related
alterations in neuronal functioning that could underlie cognitive decline that persists even
after prolonged abstinence. For example, rats’ self-administration of nicotine was
associated with a decrease in cell adhesion molecules, a decrease in new neuron
production, and an increase in cell death in the hippocampus (Abrous et al., 2002). Such
changes could lead to long-lasting cognitive changes that contribute to poor decisionmaking and addiction.
Cognition: the Pre-frontal Cortex
Brain regions of interests (ROI) vary in previous studies. Drugs abused by
humans increase dopamine in the reward circuit, conditioning and habit formation (Wise,
1996; Chiara & Imperato, 1988; Goldstein & Volkow, 2011), and thus many clinical
studies in addiction pay more attention on the brain area involved reward, including the
midbrain dopamine area, i.e. the ventral tegmental area (VTA) and substantia nigra, and
the basal ganglia, i.e. the ventral and the dorsal striata. Moreover, some investigators
suggested that the central to theories of drug addiction have been involved the nucleus
accumbens (NAcc) and amygdala, which are responsible to functions of reward and
emotion, may be crucial to initiate drug self-administration (Volkow & Fowler, 2000).
More advanced current studies have brought to light to clarify the role of the
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prefrontal cortex (PFC), which is involved in a whole range of high level cognitive
functions such as decision-making, planning, social interaction, understanding other
people, and self awareness (Blakemore & Frith, 2005), and it is the last part of the human
brain to develop maturely (Gogtay, 2004; Blakemore, 2007). More particularly, the brain
regions of interest (ROI) in PFC, including the anterior cingulated cortex (aCC), the
dorsolateral prefrontal cortex (DLPFC), and the orbitofrontal cortex (OFC) have been
selected and highlighted based on the preclinical literature on drug-seeking behavior and
the current addictive cue studies (Robinson & Berridge, 1993; Wise, 1988; Galvan et al.,
2005; Brody et al., 2002; Childress et al., 1999; Smolka et al., 2006; Due et al., 2002;
Goldstein & Volkow, 2002; Goldstein et al., 2007; Wilson, Sayette & Fiez, 2004; Volkow
et al., 2009). That helps explain the disruption of PFC in addiction could negatively affect
a wide range of behaviors such as im/com-pulsivity, risk taking, reduced satiety,
enhanced stress reactivity and inability to suppress emotional intensity, impaired selfmonitoring, drug-related anticipation, and choice of immediate reward over delayed
gratification (Goldstein & Volkow, 2011).
Drugs of Abuse and the Development Brain
The human brain continues to develop and learn important neural pathways from
the prenatal period through adolescence. Throughout these years, the brain is highly
vulnerable and susceptible to the insult of drugs, and drug-induced alterations of neural
plasticity may deflect the normal course of brain maturation.
Prenatal exposure
Prenatal exposures to a number of drugs have significant deleterious effects on
cognition and behavior that may not rise to the level of mental retardation. A study shows
a 5-year-olds whose mothers had used alcohol, cocaine, and/or opiates while pregnant
ranked below unexposed controls in language skills, impulse control and visual attention,
although there were no significant difference between the two groups of children in
intelligence, visual/manual dexterity, or sustained attention, both groups placed below the
normative means on these measures (Pulsifer et al., 2008). Another similar study
documented memory deficits in 10-year-old children who had been exposed prenatally to
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楊鳳霞 Hada Fong-ha Ieong
alcohol or marijuana (Richardson et al., 2002).
Clinical and laboratory research has implicated prenatal exposure to
methamphetamine in both cognitive deficits and altered brain structure. One study
correlated shorted attention span and delayed memory with reduced volume in the
putamen (-18%), globus pallidus (-27 to -30%), and hippocampus (-19 to -20%) among
15 children who were 3 to 16 years prenatally exposed to the stimulant, compared with
controls (Chang et al., 2004).
Cognitive deficits following prenatal exposure to smoking may reflect structural
brain changes. In one study, prenatally exposed adolescent smokers had greater
visuospatial memory deficits in conjunction with changes in parahippocampal and
hippocampal functions compared with adolescent smokers not prenatally exposed
(Jacobsen et al., 2006). Brain imaging of adolescent smokers and nonsmokers who were
prenatally exposed to smoking has revealed reduced cortical thickness (Toro et al., 2008)
and structural alterations in cortical white matter (Jacobsen et al., 2007). Furthermore, in
rats, prenatal exposure to nicotine decreased memory-related neural activity in the
hippocampus and resulted in deficits in active avoidance learning, with male and female
prenatally exposed rats showing significantly fewer correct responses as young adults
(Vaglenova et al., 2008).
Adolescent exposure
Adolescence is a high-risk period for substance abuse. Most addicted smokers
initial formed the habit during adolescence (Khuder, Dayal & Mutgi, 1991). Some studies
show that adolescent smokers scored worse than age-matched nonsmokers on tests of
working memory, verbal comprehension oral arithmetic, and auditory memory (Fried,
Watkinson & Gray, 2006; Jacobsen et al., 2005). In addition, adolescent rates treated with
nicotine had long-lasting changes in the sensitivity of the adenylyl cyclase cell-signaling
cascade, a second messenger pathway involved in many processes, including learning
and memory (Slotkin et al., 2008).
Adolescent smoking can foster cognitive decline with other disorders. For
example, a study shows that adolescent cigarette use is associated with future episodes of
depression (Choi et al., 1997), a malady which in turn is associated with negative effects
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楊鳳霞 Hada Fong-ha Ieong
on cognition (Thomas & O’Brien, 2008). A laboratory investigation shed light on this
relationship: Adult rats that had been exposed to nicotine during their adolescence proved
less sensitive than controls to rewarding/appetitive stimuli and more responsive to stress
and anxiogenic stimuli (Iniguez et al., 2009).
Moreover, adolescent exposures to alcohol, cannabis, and MDMA also cause
persistent disruption of cognition (Brown et al., 2000; O’Shea, McGregon & Mallet,
2006; Piper & Meyer, 2004; Stiglick & Kalant, 1982). These findings prove that the
adolescent brain is susceptible to insult from drug use and abuse, which can result in
long-lasting changes in cognition.
Gene, Drugs and Cognition
While the cognitive deficits associated with withdrawal from drugs are often
temporary, long-term use can also lead to lasting cognitive decline. The nature of deficits
varies with the specific drug, the environment, and the user’s genetic makeup. For
example, an individual ‘s cognitive response to acute amphetamine depends in part on
which of alternative forms of the catechol-O-methyltransferase (COMT) gene, which is
responsible for the degradation of catecholamines such as dopamine, epinephrine, and
norepinephrine, the person has inherited. This gene encodes a protein that metabolizers
DA and norepinephrine, among other molecules. A person inherits two set of copies of
COMT, one from a father, another from a mother, and each copy has either a valine or a
methionine DMA triplet at codon 158, thus a heterozygous pair (Val/Met), the
homozygous (Met/Met) or (Val/Val) of codons at this location. Administration of acute
amphetamine to individuals with the Val/Val pairing improved their performance on test
of cognitive flexibility that activates the dorsolateral prefrontal cortex and increased
efficiency in their prefrontal cortex function (Mattay et al., 2003). Furthermore, smokers
with the Val/Val pairing were more sensitive to the disruptive effects of nicotine
withdrawal on working memory and exhibited a greater cognitive response to tobacco
(Loughead et al., 2009).
These findings are important not only because they demonstrate a link between
the effects of drugs of abuse on cognition and behavioral traits associated with addiction,
but also because they provide examples of how genotype contributes to the addictive
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楊鳳霞 Hada Fong-ha Ieong
phenotype (Gound, 2010). More research is needed to understand the extent of individual
vulnerabilities in drug addiction versus the effect of cumulative exposure, a greater
understanding of vulnerability phenotypes, as well as the addictive resilient phenotype
that recovers normal plasticity in the NAcc, could ultimately lead to new therapies for
addiction (Piazza, 2013).
Preclinical research and Clinical Implications
The literature reviewed here highlights the importance of considering past,
present and possible future cognitive functions when treating patients for addiction, as
drug-related cognitive changes may cause patients and family bias toward responses and
actions that continue to the cycle of addiction. While clinicians face the challenges of
helping patients master adaptive strategies to overcome the strong association that
contribute to relapse after patients return to environment where they used to associate
with their prior substance use habit, pre-clinical researchers also face the challenges of
understanding the brain networks of drug abusers. As being knowing what another is
feeling and experiencing for something, anticipating of its reinforcing effects being felt
by another, and feeling an urge to follow the same behaviors to experience similar effects
are elements of craving (Tiffany, 1990), whilst having the ability to attribute the mental
states such as beliefs, intents, desire, to oneself and others and to understand that others
have beliefs, desire and intentions that are different from one’s own is called Theory of
mind (ToM) and it is one of the elements of empathy (Batson, 2009).
This review is to provide a window in future research into the complex social
relations in which drug abusers not only try to think of what the other abusers are
thinking or behaving in orders to make sense to themselves, but also attempt to measure
and seek craving responses to external and internal related stimuli – i.e. why and what the
others’ craving reaction affect one’s thoughts, while making a moral judgment, and also a
better understanding in addiction.
This project does not specifically deal with the treatment of craving in addiction;
however, no work such as this can be complete without at least a brief mention of
treatment. Several treatments exist to help drug abusers recover from addiction. These
include cognitive behavioral therapy, medication and behavioral therapy, and
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2013 年全國藥物濫用防治研討會
楊鳳霞 Hada Fong-ha Ieong
motivational interviewing. Easing withdrawal symptoms can be important in the
initiation of treatment; prevent relapse is necessary for maintaining its effects.
The key factor is a continuum of care that includes an effective treatment regimen
to maintain medical and mental health of an individual; but for those who do not, avoid
treatment can have detrimental side-effects that can lead to terrible aftermaths. Follow-up
like community or family recovery support can be crucial to a person’s success in
achieving and maintaining a drug-free lifestyle.
Acknowledgments
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楊鳳霞 Hada Fong-ha Ieong
To Dr. Emile Bruneau, who lighted my passion for cognitive neuroscience and his
heart to guide every one in the world who deserves to be educated. To Dr. Charles Zaroff,
who ignited my passion for research and his advise to my path. To Dr. Ian Tebbett, who
helped me to map my quest. To Dr. John Roll, who gave me encouragement to pursue the
study in substance abuse. To Dr. Wen Chao Bai, who showed me the operation of the
Imaging Department. To my parents Kam-Sen Ieong and Mon Fong Chan for giving me
their unconditional love, and to all the friends who have helped me along the way. I
dedicate my study and future studies to all of you, particularly to those who suffers from
the battle of addiction.
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