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The Journal of Neuroscience, May 1, 2002, 22(9):3306-3311
MINI REVIEW
The Neuroscience of Natural Rewards: Relevance to Addictive
Drugs
Ann E.
Kelley1 and
Kent
C.
Berridge2
1 Department of Psychiatry, University of
Wisconsin-Madison Medical School, Madison, Wisconsin 53719, and
2 Department of Psychology, University of Michigan, Ann
Arbor, Michigan 48109-1109
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ARTICLE |
Addictive drugs act on brain reward
systems, although the brain evolved to respond not to drugs but to
natural rewards, such as food and sex. Appropriate responses to natural
rewards were evolutionarily important for survival, reproduction, and
fitness. In a quirk of evolutionary fate, humans discovered how to
stimulate this system artificially with drugs. Many molecular features
of neural systems instantiating reward, and of those systems affected by addictive drugs, are conserved across species from
Drosophilae to rats to humans and include dopamine (DA),
G-proteins, protein kinases, amine transporters, and transcription
factors such as cAMP response element-binding protein (CREB). A
better understanding of natural brain reward systems will therefore
enhance understanding of the neural causation of addiction.
Reinforcers, drives, and incentive systems
It is first helpful to consider how the field has moved
conceptually in recent decades. Although emotions are unobservable, many objective expressions and behavioral, physiological, and neural
responses to emotional stimuli have been selected by evolution. Studies
of these objective responses in animals and humans provide valuable
windows into brain reward function. Early drive theories held that
hunger and thirst states motivated behavior directly as aversive drive
states and that reinforcers simply reduced those states, strengthening
preceding stimulus-response (S-R) habits or increasing the
probability of operant response emission. Rewards are recognized now to
act at least as importantly as hedonic incentives, causing neural
representations that elicit motivation and goal pursuit, rather than as
mere habit reinforcers. Physiological drive states nevertheless play
important roles in incentive motivation, but primarily by increasing
the perceived hedonic and incentive value of the corresponding reward;
for example, food tastes better when hungry, drink when thirsty, and so
on. Perhaps surprisingly, even drug reward and withdrawal appear to
motivate drug-taking behavior primarily via incentive modulation
principles rather than directly via simple aversive drives (Stewart and
Wise, 1992 ). Accordingly, it behooves affective neuroscientists
to understand the neural basis of incentive properties of rewards.
Mesocorticolimbic dopamine: pleasure, reinforcement, reward
prediction, incentive salience, or what?
It has long been recognized that reward processing depends on
mesocorticolimbic DA systems, comprising DA neurons in the ventral tegmental area (VTA) and their projections to nucleus accumbens (NAc),
amygdala, prefrontal cortex (PFC), and other forebrain regions. Major
efforts have attempted to specify what function this system
contributes. Does mesocorticolimbic DA mediate the pleasure of reward
stimuli? This was originally suggested because mesocorticolimbic
systems are activated by many natural and drug rewards, and their
blockade impairs the behavioral effectiveness of most reinforcers
(Wise, 1985 ). Do mesocorticolimbic projections instead learn and
predict the occurrence of rewards? That influential associative
hypothesis was based on evidence that DA neurons fire to cues that
predict rewards but not to already predicted hedonic rewards (Schultz,
2000 ). Do mesocorticolimbic DA systems mediate the incentive salience
attributed to neural representations of rewards and cues, causing them
to become perceived as "wanted" goals? That incentive "wanting"
hypothesis was based originally on evidence that mesolimbic DA is not
needed to mediate the hedonic impact or "liking" for sweet rewards,
or new learning about them, despite its importance for motivated
behavior to obtain the same rewards (Berridge and Robinson, 1998 ). Or
finally, does mesocorticolimbic DA involvement in reward pursuit
reflect broader functions, such as attention, complex sensorimotor
integration, effort, or switching among behavioral programs? Those
functions were proposed on the basis of various observations that do
not readily fit a pure reward framework (Salamone, 1994 ; Gray et al.,
1999 ; Ikemoto and Panksepp, 1999 ; Redgrave et al., 1999 ; Horvitz,
2000 ). Each hypothesis has its adherents, although there is recognition
that they share important commonalities, and a consensus on
motivational incentive function may now be forming.
Gaining a more correct answer to the question of "what does DA do in
reward" is of great importance to understanding addiction, because
addictive drugs are widely agreed to act primarily, although not
exclusively, on brain mesocorticolimbic systems. For example, hedonic
theories of addiction assume that mesocorticolimbic DA systems chiefly
mediate the intense pleasure of addictive drugs and anhedonia
during withdrawal (Volkow et al., 1999 ; Koob and Le Moal, 2001 ).
Learning-based addiction theories assume sensitized or altered cellular
mechanisms of associative S-R learning, and reward predictions cause
ingrained drug-taking habits (Di Chiara, 1998 ; Kelley, 1999 ;
Berke and Hyman, 2000 ; Everitt et al., 2001 ). The
incentive-sensitization theory of addiction assumes that neural sensitization causes excessive attribution of incentive salience to
drug-associated stimuli and acts, which makes addicts compulsively "want" to take drugs again (Robinson and Berridge, 1993 ,
2000 ; Hyman and Malenka, 2001 ).
Regarding natural reward contributions to addiction neuroscience, it is
notable that all the major hypotheses of mesocorticolimbic DA function
studies were proposed originally on the basis of studies of natural
reward. Therefore, a better understanding of what DA does for natural
rewards will clarify brain mechanisms of drug addiction.
Mesocorticolimbic dopamine: appetitive versus
aversive motivation
Beyond having a role in reward, mesocorticolimbic systems also
participate in negative emotional states and aversive motivation. What
relation could negative motivation (other than withdrawal) have to
addiction? Aversive symptoms of psychosis, paranoia, or anxiety are
sometimes precipitated in human addicts and in animal models by drugs
such as amphetamine or cocaine (Ettenberg and Geist, 1993 ), but how can
a brain "reward system" also mediate negative motivation and
emotion? Some hypotheses suggest that mesocorticolimbic systems mediate
general functions, such as attention or sensorimotor integration, and
not reward or aversion specifically (Salamone, 1994 ; Gray et al., 1999 ;
Horvitz, 2000 ). Another hypothesis is that DA responses to aversive
motivation reflect hidden incentive mechanisms involved in the pursuit
of safety (Rada et al., 1998 ; Ikemoto and Panksepp, 1999 ), drawing on
psychological theories of avoidance learning. In other words, active
pursuit of food when hungry or of safety when in danger could involve
similar mesocorticolimbic incentive processes. However, most
researchers probably support a third hypothesis that certain
mesocorticolimbic systems play an active role in aversive motivation
itself, distinct from DA mediation of reward (Salamone, 1994 ; Berridge
and Robinson, 1998 ; Gray et al., 1999 ).
Several lines of evidence indicate direct mesocorticolimbic mediation
of aversive motivation. Mesocorticolimbic brain systems are activated
in animals and humans by aversive stimuli such as stress, electric
shocks, etc. (Piazza et al., 1996 ; Becerra et al., 2001 ). Amphetamine
administration enhances aversive associative conditioning of behavioral
responses (Gray et al., 1999 ), whereas lesions of the NAc core
disrupt conditioning of aversive responses to Pavlovian cues (Parkinson
et al., 1999 ). Negative motivation versus reward may be mediated by
different mesocorticolimbic channels of information processing.
Neuroanatomical and neurochemical segregation of valence are indicated
by observations that GABAergic microinjections in the NAc shell can
elicit either intense positive motivation or negative motivation,
depending on the shell subregion. GABA agonist microinjections in the
anterior medial shell elicit appetitive eating behavior, but the same
microinjections in the posterior medial shell elicit fearful defensive
treading (Stratford and Kelley, 1999 ; Reynolds and Berridge, 2001 ), a
behavior normally reserved by rodents in the wild for noxious stimuli
such as threatening rattlesnakes (Treit et al., 1981 ; Coss and Owings,
1989 ; Owings and Morton, 1998 ). Further clarification of how
mesocorticolimbic subsystems code positive versus negative motivational
states should be a high priority as a means to shed light on why drugs
of abuse sometimes produce mixed motivational effects, including
anxiety and susceptibility to psychosis.
Natural rewards as windows into reward "liking" versus reward
"wanting"
Although drug addicts want to take drugs more than other
people, they may not proportionately like those drugs more, especially if neuropharmacological tolerance grows to their pleasurable impact; however, distinctions between neural systems of "wanting" reward and "liking" reward have emerged most clearly from studies
of natural rewards, especially sweet taste reward, where it is possible to use affective facial expressions to measure immediate
"liking" or hedonic impact. In human infants (Fig. 1), sucrose
taste elicits a set of facial "liking" expressions (tongue
protrusions, smile, etc), whereas quinine taste elicits facial
"disliking" expressions (gape, etc.) (Steiner et al., 2001 ).
Comparisons of human infant expressions with those of at least 11 great
ape and monkey species indicate that primate expression patterns
for "liking" and "disliking" are characterized by strong
taxonomic continuity across species and by homology of microstructure
features, such as allometric control of component speed (Steiner et
al., 2001 ). Even rats display these reactions to tastes that reflect
core affective processes and hedonic neural mechanisms homologous to
those of humans (Grill and Norgren, 1978 ; Berridge, 2000 ).

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Figure 1.
Naturalistic behavior assays of
reward liking and negative fearful defense. Liking facial expressions
are elicited by the taste of sucrose from newborn human infants,
orangutans, and rats [top left, facial photographs from
Steiner et al. (2001) and Berridge (2000) ]. Disliking expressions are
elicited by the taste of quinine. NAc coronal map of opioid
liking and wanting sites for food reward shows intensity of food
wanting produced by morphine microinjections in the shell
[bottom left, Peciña and Berridge (2000) ].
Accompanying graph shows the increase in sucrose liking
reactions caused by morphine microinjections in the accumbens shell.
Conversely, anxiogenic and psychotic effects of addictive drugs may be
related to natural fearful active defense reactions
(right). Fearful defensive treading is elicited
naturally from rodents by rattlesnake predators and centrally by GABA
agonist microinjections in the caudal accumbens shell [California
ground squirrel photograph by John Cooke from Coss and Owings (1989) ;
rat photograph from Reynolds and Berridge (2001) ]. Bar
graph shows elicitation of fearful defensive treading
along a rostrocaudal gradient in the NAc shell after GABA agonist
microinjections (Reynolds and Berridge, 2001 ). Separate
mesocorticolimbic channels for appetitive and aversive motivational
functions is suggested by sagittal map of NAc shell rostrocaudal
segregation of GABA-elicited positive feeding behavior (anterior
x symbols) versus fearful defensive behavior
(posterior squares).
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Opioid peptide neurotransmission within the NAc modulates the hedonic
impact of food reward (Glass et al., 1999 ; Peciña and Berridge,
2000 ; Kelley et al., 2002 ), providing further support that drugs of
abuse act on systems evolved to mediate such natural pleasures as
sweetness "liking." For example, microinjection of morphine into
NAc shell directly increases rat "liking" orofacial expressions
elicited by sucrose (Peciña and Berridge, 2000 ) and alters intake
consistent with enhanced food palatability (Zhang and Kelley, 2000 ).
Such findings demonstrate the importance of neurochemical systems other
than dopamine in the hedonic impact of rewards.
Originally surprising were findings that mesocorticolimbic DA
manipulations do not change "liking" for the taste of sucrose (Peciña et al., 1997 ; Wyvell and Berridge, 2000 ), despite
their role in incentive "wanting" for these and other rewards. The
neurochemical dissociation of "liking" from "wanting" has
obvious relevance to addiction. The incentive-sensitization theory
suggests that addiction may be characterized by increased "wanting"
of drugs caused by sensitized DA-related systems, even in the absence
of drug "liking" (Robinson and Berridge, 2000 ; Hyman and Malenka, 2001 ).
From nodes to dynamic networks
Reward-related behavior emerges from the dynamic activity of
entire neural networks rather than from any single brain structure. The
functions of NAc, amygdala, etc., in natural reward or addiction can be
understood only in terms of the extended neural system within which
they reside (Fig. 2). Although we now have a working knowledge of key
brain structures of reward, deeper understanding will require
examination of network interactions between subregions of amygdala,
PFC, NAc, and other structures in reward and motivation (Kalivas and
Nakamura, 1999 ; Rolls, 1999 ; Everitt et al., 2000 ; Schultz, 2000 ;
Jackson and Moghaddam, 2001 ). For example, amygdala and orbital
prefrontal cortex may play complementary roles in reward learning
regarding acquisition of cue incentive value versus response selection
(Schoenbaum et al., 1999 ; Baxter et al., 2000 ).

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Figure 2.
Schematic representation of rat brain sagittal
section depicting pathways involved in processing of natural rewards
and in neural plasticity underlying reward-related learning. Circuitry
represented in blue indicates long glutamatergic
pathways between prefrontal cortex (PFC), amygdala
(Amyg), hippocampus (Hipp), ventral
striatum (nucleus accumbens), and ventral tegmental area
(VTA). Red circuitry represents principal
ascending mesocorticolimbic dopamine systems. Green
descending pathways indicate primarily GABAergic descending systems.
Triangles in corresponding colors indicate similar DA,
glutamate, and GABAergic coding in dorsal striatum.
Violet-shaded boxes represent important nodes within
this distributed network where NMDA/D1 receptor-mediated plasticity is
proposed to be a critical substrate for behavioral adaptation and
learning. For purposes of simplicity, not all relevant circuitry is
shown; for example, there are important connections between
hypothalamus and amygdala, and glutamatergic thalamic inputs are not
shown. Drawing of section is based on the atlas of Paxinos and Watson
(1998) . Large arrows indicate flow of effector pathways
converging on viscero-endocrine and autonomic systems (emerging from
hypothalamus and amygdala) and somatic voluntary motor systems
(emerging from basal ganglia and ventral midbrain).
Inset reflects intracellular and genomic mechanisms
hypothesized to govern DA- and glutamate-dependent plasticity within
the indicated (violet shaded) nodes. Such plasticity,
which may result in altered network activity, is hypothesized to
mediate normal learning and memory related to natural rewards but is
also a key component of addiction. AcbC, Accumbens core;
Acb shell, accumbens shell; Cpu,
caudate-putamen; VP, ventral pallidum;
Hypo, hypothalamus; SN, substantia nigra.
Other abbreviations can be found in Paxinos and Watson (1998) .
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A further network feature concerns the efferent projections of NAc to
target structures such as lateral hypothalamus and ventral pallidum.
This outflow appears crucial to NAc mediation of natural appetitive
behavior (Kalivas and Nakamura, 1999 ; Stratford and Kelley, 1999 ; Zahm,
2000 ). Elicitation of eating behavior by inhibition of spiny neurons in
the NAc shell depends on signals to the lateral hypothalamus, which
activates lateral hypothalamic neurons via disinhibition (Rada et al.,
1997 ; Stratford and Kelley, 1999 ). Thus, the NAc shell may gate
corticolimbic information to the lateral hypothalamus and exert
executive control over brain circuits controlling feeding behavior and
related motivation (Kelley, 1999 ; Petrovich et al., 2001 ). This
corticostriatal-hypothalamic-brainstem network deserves to be the
focus of further study, in the contexts of both natural reward and
addiction (Swanson, 2000 ).
Neural ensembles and behavioral selection
Dynamic modulation of incentive value emerges from afferent
network signals that cause variation in the states of individual medium
spiny NAc neurons. For example, these neurons exhibit "bistable" membrane potential states, which depend on phasic excitatory
glutamatergic input from afferent structures such as hippocampus
(O'Donnell and Grace, 1995 ). NAc neurons are depolarized by PFC input
when they are in the hippocampal-gated "up" state, and thus network synchrony arises between NAc and hippocampus (Goto and O'Donnell, 2001 ). Similar gating of NAc neurons may occur between amygdala and
hippocampal inputs (Mulder et al., 1998 ; Floresco et al., 2001b ). DA
input also plays a critical role in the NAc switching and is influenced
in turn by hippocampal glutamatergic input to VTA (Legault and Wise,
2001 ). Thus, dynamic modulation by incoming network signals can control
which NAc motivational ensembles predominate to guide behavior toward
natural or drug rewards.
Network plasticity mediated by DA-glutamate interactions
Addictive drugs induce long-term neuroadaptations at the
structural, cellular, molecular, and genomic levels (Hyman and Malenka, 2001 ), but how does such plasticity relate to natural reward and motivation? An exciting synthesis is emerging from studies of glutamate-DA-mediated plasticity and its transcriptional consequences. Coincident activation of DA D1 receptors and glutamate NMDA receptors plays a critical role in shaping synaptic configurations and neural ensembles involved in motivation and learning.
In both striatum and PFC, D1 activation potentiates NMDA responses
(Seamans et al., 2001 ; Wang and O'Donnell, 2001 ), and long-term potentiation at hippocampal-prefrontal cortex synapses is dependent on
coactivation of NMDA and D1 receptors and on intracellular cascades
involving protein kinase A (Gurden et al., 2000 ). Sensitization by drugs of abuse is facilitated by a related glutamate-dopamine interaction caused when drugs are administered in a novel distinct environment (Uslaner et al., 2001 ). In accumbens neurons, cooperative action of both D1 and NMDA receptors mediates hippocampal-evoked spiking activity (Floresco et al., 2001b ), and a similar synergism is
observed for the amygdalo-accumbens pathway (Floresco et al., 2001a ).
Molecular studies complement these findings, showing NMDA-receptor dependence of D1-mediated phosphorylation of CREB (Konradi et al.,
1996 ; Das et al., 1997 ), a transcription factor thought to be an
evolutionarily conserved modulator of memory processes. Transcriptional
consequences of NMDA and D1 coactivation in the NAc core and PFC are
necessary for appetitive learning about cues, rewards, and behavioral
actions, particularly at early acquisition stages (Baldwin et al.,
2000 , 2002a ,b ; Smith-Roe and Kelley, 2000 ). In sum, coordinated
activation of DA D1 and NMDA systems within corticolimbic-striatal
circuits is an important feature of adaptive reward learning.
This story suggests that drugs of abuse that target DA and
glutamate synapses should enduringly modify basic cellular and molecular functions. Such long-lasting plasticity in reward neurons induced by drugs may contribute to abnormal information processing and
behavior, resulting in poor decision making, loss of control, and the
compulsivity that characterizes addiction. That drugs of abuse induce
D1- and NMDA-mediated neuronal cascades shared with normal reward
learning is an important insight regarding addiction that has emerged
in the past decade.
Reward outside traditional limbic network?
Although little studied, reward may also be significantly
processed in brain structures not traditionally considered
mesocorticolimbic, motivational, or related to addiction. For example,
"motor" regions of caudate-putamen contain neurons that respond to
food and drink reward stimuli, in a manner similar to DAergic or
ventral striatal neurons (Aosaki et al., 1994 ; Schultz, 2000 ). Eating
can be elicited in rats directly by microinjections of opioid agonists
into these same motor regions of dorsal striatum (Zhang and Kelley,
2000 ). Eating is disrupted by DA receptor blockade or lesions in the same dorsal striatal regions (Cousins and Salamone, 1996 ). Sensorimotor regions of striatum undergo dynamic changes during rewarded
"habit" learning (Jog et al., 1999 ), and their damage impairs
learning (Packard and White, 1990 ). Such evidence suggests that
"sensorimotor" structures may participate in natural reward
functions to a surprising degree (White, 1989 ). If so, such extended
neural reward processing has implications for addiction as well.
Conclusion
Drugs can impact natural brain reward systems to produce addiction
in only three ways. (1) Drug rewards might activate the same
brain systems as intense natural rewards. Addiction theories based on
pleasurable drug hedonia or positive reinforcement suppose that drugs
act as natural rewards. (2) Addictive drug rewards might also change
the quantitative scaling of some reward components, fragmenting and
distorting normal reward processes to cause compulsive behavior.
Addiction theories based on sensitization of incentive salience propose
that drugs sensitize mesocorticolimbic substrates of incentive
salience, fractionating natural reward by intensifying "wanting"
disproportionately to cause compulsive drug taking behavior (Robinson
and Berridge, 2000 ; Hyman and Malenka, 2001 ). Addiction theories based
on associative long-term potentiation or alterations in learning
systems propose unusually strong drug-taking S-R habits (O'Brien et
al., 1992 ; Di Chiara, 1998 ; Robbins and Everitt, 1999 ; Berke and Hyman,
2000 ; Everitt et al., 2001 ). (3) Addictive drugs could induce new brain
processes, such as aversive withdrawal states, which may play larger
opponent-process roles for addiction than for normal rewards (Solomon
and Corbit, 1974 ; Koob and Le Moal, 2001 ).
These three possibilities are exhaustive but not mutually exclusive.
Many intriguing facts have been discovered that illuminate their
interaction. Future studies will further clarify how drugs interact
with brain reward systems to produce the compulsive motivation and
relapse that characterize addiction.
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FOOTNOTES |
This work was supported by Grants DA09311, DA04788, and DA13780
from the National Institute on Drug Abuse (A.E.K.) and IBN 0091611 from
the National Science Foundation (K.C.B.). We thank Terry Robinson,
Sheila Reynolds, Matthew Andrzejewski, and Susana Peciña for
helpful suggestions on this manuscript.
Correspondence should be addressed to A. E. Kelley, Department of
Psychiatry, University of Wisconsin-Madison Medical School, 6001 Research Park Boulevard, Madison, WI 53719. E-mail:
aekelley{at}facstaff.wisc.edu.
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