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Neuroscience and Biobehavioral Reviews 36 (2012) 1934–1951

Contents lists available at SciVerse ScienceDirect

Neuroscience and Biobehavioral Reviews

journa l h o me pa g e: www.elsev ier .com/ locate /neubiorev

eview

he roles of the reward system in sleep and dreaming

ampros Perogamvrosa,b, Sophie Schwartzb,c,d,∗

Division of Neuropsychiatry, Department of Psychiatry, University Hospitals of Geneva, Geneva, SwitzerlandDepartment of Neuroscience, University of Geneva, Geneva, SwitzerlandSwiss Center for Affective Sciences, University of Geneva, Geneva, SwitzerlandGeneva Neuroscience Center, University of Geneva, Geneva, Switzerland

r t i c l e i n f o

rticle history:eceived 11 October 2011eceived in revised form 23 May 2012ccepted 25 May 2012

eywords:leepreamingmotionemory

a b s t r a c t

The mesolimbic dopaminergic system (ML-DA) allows adapted interactions with the environment and istherefore of critical significance for the individual’s survival. The ML-DA system is implicated in rewardand emotional functions, and it is perturbed in schizophrenia, addiction, and depression. The ML-DAreward system is not only recruited during wakeful behaviors, it is also active during sleep. Here, weintroduce the Reward Activation Model (RAM) for sleep and dreaming, according to which activation ofthe ML-DA reward system during sleep contributes to memory processes, to the regulation of rapid-eyemovement (REM) sleep, and to the generation and motivational content of dreams. In particular, theengagement of ML-DA and associated limbic structures prioritizes information with high emotional ormotivational relevance for (re)processing during sleep and dreaming. The RAM provides testable predic-

earningopamineesolimbic dopaminergic system

eward systementral tegmental area

tions and has clinical implications for our understanding of the pathogenesis of major depression andaddiction.

© 2012 Elsevier Ltd. All rights reserved.

ippocampusmygdala

ontents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19351.1. The mesolimbic dopaminergic (ML-DA) system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19351.2. Reward processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1936

1.2.1. General information about reward processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19361.2.2. Brain circuits of reward processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1936

2. Introducing the Reward Activation Model (RAM) for sleep and dreaming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19372.1. Activation of the ML-DA reward system during sleep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1937

2.1.1. VTA bursting activity is increased during REM sleep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19372.1.2. Increased activity of the NAcc, PFC, amygdala and ACC during REM sleep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1938
2.1.3. Activation of HC and VS reward-related neurons during
2.1.4. Activation of other reward-related structures and mecha2.2. Sleep deprivation and reward system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Abbreviations: ACC, anterior cingulate cortex; AIM model, activation, input/output, mocid; HC, hippocampus; l-DOPA, precursor to the neurotransmitters known as catecholamn the central nervous system for the clinical treatment of Parkinson’s disease, for examopaminergic system; mPFC, medial prefrontal cortex; MRI, magnetic resonance imaging;leep, non-rapid-eye movement sleep; OFC, orbitofrontal cortex; PET, positron emission tounction, parieto-temporo-occipital junction; RAM, Reward Activation Model; RBD, REM seprivation; SD, sleep deprivation; SLD, sublaterodorsal nucleus; SN, substantia nigra; SNheory; vmPFC, ventromedial prefrontal cortex; VP, ventral pallidum; VS, ventral striatum∗ Corresponding author at: Department of Neuroscience, Faculty of Medicine, Universitel.: +41 22 3795376; fax: +41 22 3795402.

E-mail address: [email protected] (S. Schwartz).

149-7634/$ – see front matter © 2012 Elsevier Ltd. All rights reserved.ttp://dx.doi.org/10.1016/j.neubiorev.2012.05.010

SWS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1939nisms during sleep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1939

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1939

dulation model; dlPFC, dorsolateral prefrontal cortex; GABA, gamma-aminobutyricines, including dopamine. As a drug it is used to increase dopamine concentrationsple.; LH, lateral hypothalamus; LTP, long-term potentiation; ML-DA, mesolimbic

NAcc, nucleus accumbens; N1, N2, N3, stages N1, N2, and N3 of NREM sleep; NREMmography; PFC, prefrontal cortex; PPT, pedunculopontine tegmental nucleus; PTOleep behavior disorder; REM sleep, rapid-eye movement sleep; REMSD, REM sleepc, substantia nigra pars compacta; SWS, slow-wave sleep; TST, threat simulation; VTA, ventral tegmental area.

y of Geneva, rue Michel-Servet 1, 1211 Geneva 4, Switzerland.

dx.doi.org/10.1016/j.neubiorev.2012.05.010

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L. Perogamvros, S. Schwartz / Neuroscience and Biobehavioral Reviews 36 (2012) 1934–1951 1935

3. Reward activation and memory processing during sleep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19393.1. Memory processing leading to reward activation during sleep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19403.2. Reward activation leading to memory formation during sleep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1940

4. Reward activation and REM sleep generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19405. Reward activation and dreaming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1941

5.1. The neural circuits of dreaming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19415.2. ML-DA reward system activation and dream generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19425.3. ML-DA reward system activation and dream content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19425.4. Links of the RAM to other dream theories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1943

5.4.1. Freud’s psychoanalytic theory of dreams and RAM. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19435.4.2. Activation-input-modulation (AIM) model and RAM. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19435.4.3. Threat Simulation Theory (TST) and RAM. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1943

6. Clinical context. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19446.1. Psychosis and dreaming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19446.2. Sleep and emotion regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1944

6.2.1. Insomnia and sleep loss as precursors of depression via alteration of brain reward networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19446.2.2. Evidence from sleep deprivation studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1945

6.3. Sleep and compulsive behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19457. Limitations and testability of the model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19458. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1946

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1946 . . . . . .

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References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. Introduction

‘We have no dreams at all or interesting ones. We should learn tobe awake the same way — not at all or in an interesting manner.’(Friedrich Nietzsche, ‘The Gay Science’, Third Book, aphorism232, 1882)

The mesolimbic dopaminergic (ML-DA) system originates fromhe ventral tegmental area (VTA) of the midbrain and projects toarious diencephalic structures like the nucleus accumbens (NAcc),s well as to the prefrontal cortex (PFC) (Alcaro et al., 2007). The ML-A circuit promotes adapted, goal-directed behaviors by mediatingifferent aspects of reward processing (Haber and Knutson, 2010;chultz, 1998). The ML-DA system is also critical for the develop-ent of instinctual and appetitive drives, a function of the brain

hat permits mammals, including humans, to seek for rewards andevelop search strategies in order to obtain them (Panksepp, 1998).

Several lines of evidence suggest the ML-DA reward system isctivated during sleep. Neurophysiological studies in animals haveevealed that regions of the ML-DA circuit such as the NAcc andhe VTA show increased bursting neural activity during rapid-eye

ovement (REM) sleep (Dahan et al., 2007; Lena et al., 2005), and role of dopamine in the generation of REM sleep has been sug-ested (Dzirasa et al., 2006). It is also striking that brain circuitsodulating sleep–wake states (e.g. hypocretin/orexin system) may

nfluence reward-related responses and neural plasticity in ML-DAegions and amygdala in both animals and humans (Borgland et al.,008; Harris et al., 2005; Ponz et al., 2010a,b). Moreover, neuronalctivity recorded during the encoding of reward-related mem-ry may be spontaneously reactivated during slow-wave sleepSWS) in the ventral striatum and the hippocampus in rodentsLansink et al., 2009). In humans, the replay of elements from wak-ng experience in both sleep (Maquet et al., 2000; Peigneux et al.,004; Rudoy et al., 2009) and dreams (Wamsley et al., 2010) wasound to enhance overnight memory consolidation, and rewardednformation may particularly benefit from sleep-related memoryonsolidation (Fischer and Born, 2009). Finally, elevated dopamineevel in the ML-DA system during sleep has been suggested to playn important role in the generation of dreams (Solms, 2000, 2002).

In this article, we present the Reward Activation Model (RAM),hich proposes that activation of the ML-DA reward system dur-

ng sleep (a) serves learning and memory consolidation functionsy reactivating rewarded or emotionally-relevant memories during

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sleep; (b) influences the regulation of REM sleep; and (c) con-tributes to the generation and the motivational content of dreams.Importantly, these distinct functional roles of ML-DA activationduring sleep involve partially dissociated reward-related mecha-nisms. The RAM also suggests that the reward function of dreamingoffers humans an evolutionary advantage by optimizing wakingbehavior, in particular adapted emotional responses. Our mainaim in developing the RAM is to propose a theoretical frameworkconcerning the roles of the ML-DA system in sleep and reward pro-cesses, that integrates recent data from neurophysiology studies inanimals with behavioral and brain imaging studies in humans. Byaddressing and formalizing the interaction of sleep with rewardand emotional processes, an additional objective of the RAM isto account for some neuropsychiatric symptoms in patients withdopaminergic abnormalities (e.g. schizophrenia, depression, addic-tion). This model thus offers to sleep science a missing link betweensleep neurophysiology, cognition, and dream content.

1.1. The mesolimbic dopaminergic (ML-DA) system

There are two main ascending dopaminergic pathways in thehuman brain: the nigrostriatal pathway and the ML-DA (mesolim-bic or mesocorticolimbic) pathway (Fig. 1; Stahl and Muntner,2008). The nigrostriatal pathway projects from the substantia nigra(SN) of the midbrain to the dorsal striatum (caudate and puta-men). It is mainly implicated in the modulation of cognitive andbehavioral habits, and in procedural aspects of movements; its dys-function is associated with Parkinson’s disease (Jankovic, 2008).The ML-DA pathway originates in the VTA and innervates the lateralhypothalamus (LH), the NAcc and olfactory tubercle of the ventralstriatum (VS), the bed nucleus of stria terminalis, lateral septum,hippocampal complex (HC), amygdala, PFC, and anterior cingu-late cortex (ACC). This system is implicated in motivated behaviors(Alcaro et al., 2007), reward processing (Ikemoto, 2007), emotionalprocessing (Alcaro et al., 2007), and learning (Adcock et al., 2006).Dysfunctions of the ML-DA system are observed in schizophrenia(Epstein et al., 1999; Kapur, 2003; Laruelle, 2000; Meltzer and Stahl,
1976; Sarter et al., 2005; Winterer and Weinberger, 2004), addic-tion (Kauer and Malenka, 2007; Koob, 1992; Koob and Volkow,2010; Thomas et al., 2008), as well as in depression (Dailly et al.,2004; Dunlop and Nemeroff, 2007; Nestler and Carlezon, 2006).

1936 L. Perogamvros, S. Schwartz / Neuroscience and Biobehavioral Reviews 36 (2012) 1934–1951

Box 1: Rewards and punishersRewards are considered as stimuli that positively reinforcebehavior (Schultz, 2006) and that usually (but not always)induce a conscious experience of pleasure. Examples of pri-mary rewards are stimuli like food, water, and sexual stimuli.They reinforce behaviors without having to be learned. Theyderive their value from innate mechanisms, like the hungerand thirst states. Secondary (conditioned) rewards gain theirreward value from a learned association with primary rewards.Money, positive feedback, social interactions, and pleasanttouch are typical secondary rewards. The organism’s inter-action with a reward may implicate two distinct types ofprocesses, i.e. motivational and hedonic processes (Berridgeet al., 2009). The motivational component refers to switch-ing attention and behavior toward reward-related stimuli ornovel cues. Motivated behavior is mainly associated withdopaminergic signaling in mesolimbic structures like the VTA,hypothalamus, amygdala, NAcc, and PFC. On the other hand,the hedonic impact of a reward concerns the pleasurablereaction of the organism to a sensory cue (e.g. the sensorypleasure of sweet tastes), and implicates opioid, cannabinoid,and GABA transmission from the brainstem to the NAcc, ven-tral pallidum, insular cortex and orbitofrontal cortex.Punishers are stimuli that induce withdrawal behavior. Theyfunction as negative reinforcers, by increasing a behavior thatdecreases an aversive outcome. Punishers can induce emo-tional states such as anger or fear.Rewards or punishers are not always of an external or percep-tual origin; they may also correspond to a cognitive, mentalrepresentation or a memory reactivation of a reward (Alcaro

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Box 2: The SEEKING systemThe SEEKING system has been proposed by Panksepp asa “curiosity-interest-expectancy” command system which isassociated with instinctual appetitive craving states (Alcaroand Panksepp, 2011; Panksepp, 1982, 1998). As a psychobehav-ioral emotional and motivational system of the mammalianbrain, the SEEKING system is related to approach behav-iors and to the feeling of anticipation while seeking a reward(actual external stimuli or internal representation of a reward)(Alcaro and Panksepp, 2011). Its core circuits include denseML-DA projections from the VTA to the LH, mediodorsal tha-lamus, medioventral pallidum, NAcc shell, olfactory tubercle,amygdala, anterior limbic cortex, and prefrontal cortex (Fig. 2).Although it resembles the ML-DA system, the SEEKING systemis more extensive, because it includes ascending noradrener-gic and cholinergic excitatory influences, as well as descendingglutamatergic and GABA influences (Panksepp, 1998). Acti-vation of the SEEKING system does not only represent theinternal experience of a reward, but also the emotional antici-patory components of an appetitive search strategy (Panksepp,1998). Interest, curiosity and anticipation, but not pleasure orconsumption, are the feelings related to the activation of theSEEKING system. This system can be sometimes activatedindependently of voluntary goal-seeking behavior. For exam-ple, addictive drugs like cocaine and nicotine directly use and‘abuse’ this system, leading to the perpetuation of associatedactivities, such as the continuous quest for the substance andthe pursuit of the subjective feeling of pleasure induced by itsconsumption. A maladaptive vicious cycle, known as depen-

responses and unconditioned responding (mesolimbic pathway)

and Panksepp, 2011).

.2. Reward processing

.2.1. General information about reward processingReward processing is one of the major functions of the ML-

A reward system. This system is responsible for appropriateesponses to external and internal rewards or punishers, forncentive-based learning, and for the development of goal-directednd adaptive behaviors (Haber and Knutson, 2010). It is regarded as

central component in the development and monitoring of moti-ated behaviors in all mammals (see Box 1). Two main types ofopamine signals may be distinguished within this system: pha-ic versus tonic neural activity. A phasic dopamine signal (burstingctivity) is defined as a brief increase (up to 2 s) in dopamine con-entration in terminal mesolimbic regions (subcortical, like theAcc, or cortical), resulting from a burst firing of one or more VTAeurons (Ikemoto, 2007). Phasic activity is involved in reward pro-essing (Heien and Wightman, 2006; Redgrave et al., 1999; Schultz,010b), and also relates to the process of switching one’s attentionnd behavior toward salient cues in the environment. On the otherand, a tonic signal is defined as a slow change in dopamine concen-ration in the aforementioned regions, lasting from tens of secondso hours or days, and supporting relatively stable or tonic affectivetates and motivation (Ikemoto, 2007).

The term ‘reward’ can have slightly different uses in neu-oscience. On the one hand, reward may primarily refer toeinforcement-learning functions of dopamine signals, such as forxample reward prediction error (Redgrave et al., 1999; Schultz,997, 2002, 2010a; Schultz and Dickinson, 2000). On the otherand, reward may relate to motivational and appetitive functionsf the dopaminergic reward system, such as for example ‘incentivealience’ (Berridge, 2007). In this article, reward processing dur-
ng sleep will specifically concern (a) the spontaneous activationf internally-generated rewards or punishers during sleep, such aslements from memory that are relevant (Montague et al., 2006)
dence, addiction and tolerance is soon installed.

or novel (Wittmann et al., 2007), and (b) the cognitive, affective,or physiological response to these internally-generated rewardingor punishing signals while the organism is asleep. This defini-tion comes close to Panksepp’s concept of the SEEKING disposition(Alcaro and Panksepp, 2011), which corresponds to an instinctualaffective and exploratory drive to seek biologically-important stim-uli in the external or internal (‘intrapsychic’) environment (see Box2 and Fig. 2).

1.2.2. Brain circuits of reward processingThe brain areas activated during reward processing vary as a

function of the type of reward, the behavioral task, and whether areward (or punisher) is being anticipated or delivered (see Box 1).Most of the areas involved during reward processing are inner-vated by ML-DA projections, originating mainly from the VTA(ML-DA reward system; Fig. 1). The VTA, as well as the NAcc,constitutes the core of the reward circuit (Hikosaka et al., 2008;Wise, 2002). However, some non-mesolimbic structures also con-tribute to the processing of rewards, including the orbitofrontalcortex (OFC), the substantia nigra pars compacta (SNc), the supra-mammillary nucleus, the midbrain raphe nuclei, and the dorsalstriatum (Ikemoto, 2010; Schultz, 2010a). In addition, dopamineis not the only neurotransmitter related to reward responses. Glu-tamate (Kenny et al., 2009), GABA (Vlachou and Markou, 2010),serotonin (Higgins and Fletcher, 2003) and acetylcholine (Radaet al., 2000; Sarter et al., 2005) can influence reward processing, byacting either as modulators of dopamine function or independentlyof dopamine.

Recent neurobiological models of reward processing commonlydescribe a transfer of information from ventral to dorsolateralcortico-basal ganglia circuits, which transforms basic reward

into action planning and associative learning (nigrostriatal path-way) (Haber and Knutson, 2010; Ikemoto, 2007). According toIkemoto (2007), mesolimbic projections from the VTA to the NAcc,

L. Perogamvros, S. Schwartz / Neuroscience and Biobehavioral Reviews 36 (2012) 1934–1951 1937

F breviations: ACC: anterior cingulate cortex; HC: hippocampal complex; NAcc: nucleusa

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Fig. 2. The ML-DA component of the SEEKING system. Schematic representationof the ML-DA projections of the SEEKING system originating in the VTA of themidbrain. Electrical or chemical stimulation of the regions in red color inducesexploration and approach behaviors, whereas regions in blue color are involvedin the large-scale organization and diffusion of the SEEKING signal (Alcaro andPanksepp, 2011). Here, anterior limbic regions include the ventromedial prefrontalcortex, orbitofrontal cortex, anterior cingulate cortex, and the insula. Ascendingnoradrenergic/cholinergic and descending glutamatergic/GABA projections of theSEEKING system are not represented in this figure. Abbreviations: ACC: anteriorcingulate cortex; NAcc: nucleus accumbens; VTA: ventral tegmental area. (For inter-

ig. 1. Main ascending mesolimbic and nigrostriatal dopaminergic pathways. Abccumbens; PFC: prefrontal cortex; VTA: ventral tegmental area.

H, and PFC are activated by incentive stimuli and can lead to posi-ive affect and approach learning (‘flexible’ responses). On the otherand, the nigrostriatal projections from the SNc to the dorsal stria-um and from there to globus pallidus and finally to motor regionsn the frontal lobe would be responsible for the initiation of motorctivity and the transient activation of the reward system in well-earned situations, with predictable outcomes (‘habit’ responses).

. Introducing the Reward Activation Model (RAM) forleep and dreaming

Based on the evidence that the ML-DA system is activated dur-ng sleep, the RAM proposes that this activation (a) contributes to

emory consolidation mechanisms by prioritizing the processingf information with high emotional and/or motivational relevance,b) participates in the modulation of REM sleep through projectionso REM generating structures (in particular the sublaterodorsalucleus of the pons), and (c) contributes to the generation of dreamsy means of motivational and affective drives of the SEEKING sys-em (Box 2). These characteristics of the ML-DA system suggesthat dreaming may potentially play a role in learning and mem-ry, including emotion regulation processes. Note however that upo now there is little empirical evidence in support of this latterypothesis.

.1. Activation of the ML-DA reward system during sleep

An increasing number of studies indicate that some key struc-ures of the reward processing circuit, and mainly of the ML-DAeward system, like the VTA and the NAcc are activated duringleep. In Fig. 3, we propose an integrated summary of the findingshat indicate the activation of the ML-DA reward system duringleep.

.1.1. VTA bursting activity is increased during REM sleep
VTA bursting activity is strongly related to reward processing
Kiyatkin, 1995; Yun et al., 2004). The VTA fires bursts of spikesuring reward and punisher anticipation (Carter et al., 2009), asell as in response to stimulus novelty (Bunzeck and Duzel, 2006;

pretation of the references to color in this figure legend, the reader is referred to theweb version of the article.)

Krebs et al., 2011; Wittmann et al., 2007). VTA bursting activityin the rat was first recorded during sleep by Miller et al. (1983),who showed that VTA neurons fire at the same slow frequencyduring SWS, REM sleep and waking, but the firing is more irreg-ular during REM sleep. In 2002, Maloney et al. demonstrated thatin rats dopaminergic neurons in the VTA are more active dur-ing REM and wakefulness than during NREM, and are maximallyactive during REM (Maloney et al., 2002). In 2007, Dahan et al. con-firmed that the VTA has an increased bursting activity during REM
sleep in rats (phasic dopamine signals), inducing a large synap-tic dopamine release in the NAcc shell (Dahan et al., 2007). In thisstudy, the percentage of spikes firing in bursts was significantly


Fig. 3. Schematic illustration of the activation of the ML-DA reward system during sleep. (A) During NREM sleep, the HC–VS activation underlies a spontaneous reactivation(replay) of reward-related neuronal firing patterns in the VS, which involves a transfer of novelty/relevance signal from the HC to the VTA (see main text, Lansink et al., 2008;Lisman and Grace, 2005; Pennartz et al., 2011). VTA is activated during the transition from a NREM episode to REM sleep, with induction of both tonic (HC–VTA projection) andphasic (PPT–VTA) increase of dopamine. Other reward-related structures activated during NREM sleep include the amygdala, the ACC and the insula. (B) During REM sleep,increased bursting activity (phasic response) in the VTA (Dahan et al., 2007) may represent stimulus saliency and could fulfill reward-related functions, like processing ofstimulus-reward associations, novelty-seeking and enhancement of learning procedures. During REM sleep, several VTA projections are activated, including the upward arcof hippocampal–VTA loop (dopaminergic input from the VTA to the HC), the NAcc, the amygdala, the orexin/hypocretin neurons, the ACC, and the PFC. All these regions haves ers). Ap 005).t enta

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trong anatomical and functional links with the hippocampus and VTA (among othlasticity and learning by enhancing long-term potentiation (Lisman and Grace, 2egmental nuclei; VS/NAcc: ventral striatum/nucleus accumbens; VTA: ventral tegm

igher in REM compared to waking and to NREM. The sustainedursting activity was comparable in duration with VTA burstinguring motivated behaviors such as feeding, punishment, or sex.oreover, this VTA activation, which started 10–20 s before the

nset of REM sleep, was as important in intensity as an activationnduced by the consumption of food. Because high phasic dopamineignaling in the midbrain has primarily been linked to reward pro-essing (Schultz, 2010b), strong bursting activity of the VTA beforend during REM sleep may putatively be related to reward-relatedrocesses, as we discuss below.

The increase of VTA bursting activity at the end of an episodef SWS (or NREM sleep) is explained by the activation, duringWS sleep, of several structures that project either directly or indi-ectly to the VTA (pedunculopontine tegmental nucleus, amygdala,C, striatum, hypothalamus, basal forebrain). Studies have focusedainly on two of these projection sites, i.e. the HC and the peduncu-

opontine tegmental nucleus (PPT) (Holmstrand and Sesack, 2011;isman and Grace, 2005). However, it is important to note that themygdala (Fudge and Haber, 2001), as well as sleep-related struc-ures, such as the suprachiasmatic nucleus (Luo and Aston-Jones,009) and orexin/hypocretin neurons in the hypothalamus (Fadelnd Deutch, 2002) also send dense projections to the VTA. As forrexin neurons specifically, their receptors are expressed at theurface of VTA dopaminergic neurons (Marcus et al., 2001; Naritat al., 2006). In addition, the orexin system is involved both in theegulation of sleep and in drug-seeking behaviors and associatedL-DA activity, as observed in animal studies (Borgland et al., 2006;

outrel et al., 2005; Harris et al., 2005) and in neuroimaging stud-es performed on orexin-deficient narcoleptic patients (Ponz et al.,010a; Schwartz et al., 2008).

Lisman and Grace (2005) proposed that the VTA and hippocam-us form a functional loop designed to control the entry of relevant

nformation into long-term memory. Below we introduce the mainomponents of this loop because it constitutes a very useful modeln which we will rely for the integration of existing data about thectivation of the reward system during sleep. In this model, the
ctivation of the VTA induced by novel salient stimuli and requiredor memory consolidation is triggered mainly by the HC and thePT. This hypothesis is based on the observation that novelty-nduced increase in extracellular dopamine levels can be blocked by
ctivation of the upward arc of the hippocampal–VTA loop contributes to synaptic Abbreviations: HC: hippocampus; PFC: prefrontal cortex; PPT: penduculopontinel area.

intra-hippocampal infusion of tetrodotoxin (Legault and Wise,2001). In humans, brain imaging studies also demonstrate that nov-elty activates the amygdala, the VTA and the HC (Bunzeck et al.,2012; Guitart-Masip et al., 2010; Krebs et al., 2011). The HC canactivate VTA dopamine cells via a pathway involving the activationof NAcc, which in turn inhibits the ventral pallidum (VP) leadingto the disinhibition of dopamine cells (Floresco et al., 2003). Thispathway (HC → VTA), which corresponds to the downward arc ofthe ‘hippocampal–VTA loop’ (Lisman and Grace, 2005), increasesthe population activity of dopaminergic neurons, modulates tonicextrasynaptic dopamine levels in the VTA (Floresco et al., 2003),and is related to motivational salience (Lisman and Grace, 2005)(Fig. 3A). The upward arc (dopaminergic input from the VTA tothe HC) is related to synaptic plasticity and learning by enhancinglong-term potentiation (LTP) (Adcock et al., 2006) (Fig. 3B). Fur-thermore, the PPT, which sends direct excitatory inputs to the VTA(Omelchenko and Sesack, 2006) and plays a key role in the gener-ation of REM sleep (Bandyopadhya et al., 2006; Saper et al., 2005),has been shown to be activated specifically by salient stimuli (Panand Hyland, 2005) and to participate in increased bursting activ-ity and phasic synaptic dopamine levels in the VTA (Floresco et al.,2003).

To summarize, several projection circuits may contribute toincrease VTA activation during the transition from a NREMepisode to REM sleep, among which are the downward arc ofthe hippocampal–VTA loop and the PPT (Fig. 3A). The simultane-ous hippocampal–VTA and PPT–VTA activation can induce a 4-foldincrease in the number of dopaminergic neurons firing in bursts(Lodge and Grace, 2006). Note that circadian factors (CLOCK gene)seem also to be implicated in this activation (Roybal et al., 2007).

2.1.2. Increased activity of the NAcc, PFC, amygdala and ACCduring REM sleep

Activity in the NAcc is proportional to the magnitude of antic-ipated reward (Knutson et al., 2001) and is the greatest whensalience (e.g. uncertainty about outcomes) is maximal (Cooper and
Knutson, 2008). Exposure to both primary and secondary rewardsalso increases activity in the PFC, particularly in the ventrome-dial PFC (vmPFC) (Haber and Knutson, 2010). The ACC is anotherimportant component of reward processing as it is related to

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redicting reward, to assigning a positive or negative value to futureutcomes (Takenouchi et al., 1999), and to reward-based decision-aking (Bush et al., 2002). In 2005, Gottesmann’s group showed

hat there was an increase in extracellular levels of dopamine inhe NAcc during REM sleep, not significantly different from waking,ut significantly higher than NREM sleep (Lena et al., 2005). Dur-

ng REM sleep, increased activity is also observed in the PFC (Lenat al., 2005), in the human vmPFC, amygdala, and ACC (Maquett al., 1996, 2000). Dense ML-DA projections from the activatedTA (Dahan et al., 2007) to these sites could, at least in part, explain

hese activations.

.1.3. Activation of HC and VS reward-related neurons duringWS

In 2004, Pennartz’s team demonstrated that a spontaneous reac-ivation (replay) of neuronal firing patterns may occur in the VSuring SWS after a reward searching behavior of the rat (Pennartzt al., 2004). In 2008, the same group confirmed the activation of VSeward-related neurons (sensitive to either the presence or absencef reward) during SWS after a reward searching behavior (Lansinkt al., 2008). This spontaneous reactivation during SWS was astrong as during quiet wakefulness and could not be detected dur-ng REM sleep. It appears to be induced by and temporally alignedo hippocampal ripples (100–300 Hz oscillations) and could con-ribute to linking a memory trace to a motivational value duringleep (Lansink et al., 2009; Pennartz et al., 2011; Singer and Frank,009), as well as to the transfer of a novelty signal from the HC to theTA (Lisman and Grace, 2005). This mechanism may thus use theownward arc of the hippocampal–VTA loop (Fig. 3A). In humans,C and VS activation during NREM sleep has been demonstratedy neuroimaging studies (e.g. Peigneux et al., 2004; Nofzinger et al.,002), although it remains uncertain if activation in both HC andS is temporally coordinated.

It should be noted that, in rats, SWS is synonymous to humanREM sleep (Franken et al., 1998), and is not restricted to humanWS (stage N3). In humans, the hippocampal ripples are tempo-ally coupled with the sleep spindles (Clemens et al., 2007, 2011),hich are most pronounced in stage N2 but also occur in SWS (Deennaro and Ferrara, 2003). Thus, the aforementioned activationsf HC and VS in rats may primarily but not uniquely concern stage2 in humans. For example, a recent study showed that sleepwalk-

ng patients may re-enact during NREM sleep a motor task in whichhey were trained before sleep, thus providing direct evidence forhe off-line replay of newly acquired information during SWS inumans (Oudiette et al., 2011).

.1.4. Activation of other reward-related structures andechanisms during sleep

Apart from the regions already mentioned above, some othereward-related regions are also found to be activated during NREMnd REM sleep. In humans, the posterior insula, ACC (Schabus et al.,007), and the amygdala (Nofzinger et al., 2002) were found to bectivated during NREM sleep. During REM sleep, the amygdala andhe HC are also activated (Braun et al., 1997; Maquet et al., 1996,000; Nofzinger et al., 1997). Activation in the HC is consistentith animal (Popa et al., 2010; Winson, 1972) and human (Cantero

t al., 2003) data showing that the HC exhibits a theta rhythm dur-ng REM sleep. The theta rhythm is common when animals arexploring their environment by sniffing, an exploratory behaviorhich is present during REM sleep (Panksepp, 1998; Seelke andlumberg, 2004). Similar exploratory and instinctual behaviors inumans are observed in parasomnias: locomotion in sleepwalk-

ng, aggression in REM sleep behavior disorder, sexual behaviorsn confusional arousals, and feeding, chewing or swallowing in theleep-related eating disorder (Schenck et al., 2007; Vetrugno et al.,006; Winkelman, 2006). Hence, the specific behaviors observed

obehavioral Reviews 36 (2012) 1934–1951 1939

in these patients provide further support for the activation ofreward-seeking mechanisms during sleep. Moreover, the orexinneurons, which play an important role both in sleep–wake regu-lation (Saper et al., 2005) and in motivated behaviors (Harris et al.,2005; Thompson and Borgland, 2011) have occasional burst dis-charges during REM sleep (Mileykovskiy et al., 2005; Takahashiet al., 2008), with levels comparable to those of quiet waking(Kiyashchenko et al., 2002). This phasic activation, which mightbe related to orexin projections to and from the VTA (Nakamuraet al., 2000), could express motivational and/or emotional process-ing during REM sleep.

2.2. Sleep deprivation and reward system

The role of sleep in reward processing can be proved indirectlyby studies of sleep deprivation (SD). Steiner and Ellman (1972)demonstrated that REM sleep deprivation (REMSD) caused rats toseek more of a previously trained rewarding stimulation. Moreover,after allowing rats to self-stimulate, the typical ‘rebound’ increasein REM sleep following REMSD was decreased. Similarly, acutesleep deprivation in rats increased goal-directed behaviors towardcocaine (Puhl et al., 2009). In humans, SD increases the risk of sub-stance abuse (Shibley et al., 2008; Wong et al., 2009) and appetitivebehavior (Benedict et al., 2012). This increase in impulsivity andreward seeking post-SD may reflect a compensatory mechanism toadjust for the downregulation of D2 and D3 receptors in the ven-tral striatum immediately after SD (Volkow et al., 2012). DecreasedD2/D3 receptor availability (Volkow et al., 2012) and attenuatedrepresentations of parametric value in the SN/VTA, bilateral insula,vmPFC and parietal cortex (Menz et al., 2012), may also accountfor the impairment in performance, reward learning and decisionmaking after SD. In line with this interpretation, Hanlon et al. (2005)demonstrated that REMSD reduces the rate of responding to theacquisition and maintenance of an operant task for food reward inrats, which might be due to a suppression of dopamine activity inthe NAcc during REMSD (Hanlon et al., 2010). In addition, total SDcan disrupt the reconsolidation of morphine reward memory (Shiet al., 2011). In humans, studies have reported that insufficient sleepis associated with changes in reward-related decision making: peo-ple take greater risks (Harrison and Horne, 2000; McKenna et al.,2007), are less concerned with negative consequences of risky deci-sions (Chee and Chuah, 2008; Venkatraman et al., 2007, 2011), andoverestimate positive emotional experiences (Gujar et al., 2011).In 2009, Holm et al. showed that in both reward anticipation andoutcome phases of a card-game, adolescents with fewer minutesasleep and later sleep onset time exhibited less caudate activa-tion (Holm et al., 2009), a structure implicated in linking rewardto behavior and learning (Haber and Knutson, 2010). Collectively,these recent data suggest that less sleep may impact on neuralsystems of reward in ways that exacerbate behavioral problems(e.g. increased risk-taking). Thus, sleep deprivation may have majorhealth implications in adolescents and adults, by altering rewardand emotional processing.

3. Reward activation and memory processing during sleep

The data reviewed above suggest that many components ofthe ML-DA reward system are activated during sleep. What couldbe the functional meaning of activating a system devoted to theprocessing of rewards while the organism sleeps and is thustypically deprived of interactions with its environment? Based
on recent accumulating evidence showing that memory replayand consolidation processes are present during all sleep stages(Diekelmann and Born, 2010; Maquet, 2001; Stickgold, 2005), wesuggest that activation of the ML-DA system during sleep may

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elate to the reprocessing of memories with a high emotionalr motivational relevance (e.g. related to current or future chal-enges). A functional link between memory and reward processess substantiated by strong mutual interactions between the hip-ocampus and the VTA: while memory processing may lead toeward activation (‘memory → reward’ direction), following theownward arc of the HC–VTA loop (Fig. 3A), VTA activity can in turn

ead to the reactivation of memories and learning enhancement‘reward → memory’ direction) through activation of the upwardrc of the HC–VTA loop (Fig. 3B) (Adcock et al., 2006; Fischernd Born, 2009; Lisman and Grace, 2005; Shohamy and Adcock,010).

.1. Memory processing leading to reward activation during sleep

One of the main hypotheses of the RAM is that reward processingnd memory consolidation interact during sleep. During SWS, thisnteraction involves the downward arc of the HC–VTA loop (Fig. 3A).uring this sleep stage, activation of the HC and VS enables the

ormation of a memory trace comprising both contextual and moti-ational components (Lansink et al., 2009) and could be associatedith tonic dopamine release in the VTA (Floresco et al., 2003). The

oordinated reactivation of both HC and VS during SWS provides aossible mechanism for the consolidation of memory-reward asso-iations (Lansink et al., 2009). In particular, the activation of VSeward-related neurons during SWS in rats seems important forelecting memories with a high storage priority (Lansink et al.,008) and may lead to the optimization of adapted behavior duringakefulness. Consistent with this hypothesis, declarative memory

nd skill consolidation observed during sleep seem to be guided bymotional relevance and/or motivational biases (Cohen et al., 2005;ischer and Born, 2009; Pennartz et al., 2004; Sterpenich et al.,007, 2009; Wilhelm et al., 2011). Reciprocally, active memory pro-essing could also explain the reward-related sustained burstingctivity of the VTA (Dahan et al., 2007) and NAcc (Lena et al., 2005)uring REM sleep. The RAM supports that phasic VTA dopamine sig-aling during REM sleep favors an off-line replay of recent memoryraces during this sleep stage (Louie and Wilson, 2001; Peigneuxt al., 2003; Walker and van der Helm, 2009). These memoriesould serve both as salient and novel stimuli for the PPT and VTA,ecause recent relevant memories (e.g. emotional events, currentoncerns) are activated in the absence of associated contextualues from wakefulness, and of cognitive control from dorsolateralFC (dlPFC) during REM sleep (Fosse et al., 2003; Maquet et al.,996; Schwartz, 2003; Schwartz and Maquet, 2002). Moreover,uring REM dreaming, dream elements (including bizarre features

n dreams; Revonsuo and Salmivalli, 1995) could also act as stimulihat potentially drive VTA and NAcc bursting activity.

.2. Reward activation leading to memory formation during sleep

The activation of the VTA (predominantly during REM sleep)ay contribute to long-term potentiation (LTP) and memory for-ation in the HC (Adcock et al., 2006; Lisman and Grace, 2005). Thisechanism, which is considered necessary for associative learning

Adcock et al., 2006), is served mainly by the upward arc of theippocampal–VTA loop, namely dopaminergic projections from theTA to the HC (Fig. 3B). LTP in the HC is dependent on dopamine:

t is blocked by D1 antagonists (Bach et al., 1999) and enhancedy D1 agonists (Li et al., 2003; Swanson-Park et al., 1999). Besides,opamine transmission can regulate gene expression and lead toermanent synaptic changes (Nestler, 2004; Wolf et al., 2003). A
ecent behavioral study in humans showed that sleep can induce
significantly stronger improvement of a motor finger sequencessociated with an anticipated monetary reward (‘sequence to-be-ewarded after sleep’), thus supporting that the mere expectation

obehavioral Reviews 36 (2012) 1934–1951

of a reward can boost offline learning mechanisms during sleep(Fischer and Born, 2009).

4. Reward activation and REM sleep generation

The role of dopamine in the sleep/wake cycle has been stud-ied in rodents since more than 30 years (e.g. Monti et al., 1988).Small doses of a D2 preferring dopamine agonist (apomorphine,bromocriptine, quinpirole or pergolide) decrease wakefulness andincrease the duration of SWS and REM sleep (Dzirasa et al., 2006;Monti et al., 1988, 1989). It has been proposed that these soporificeffects are related to an activation of the D2 autoreceptors inthe VTA (Bagetta et al., 1988), which induces an inhibition in themesolimbic pathway (Szabadi, 2006). On the other hand, moder-ate doses of the D3 agonist pramipexole were found to increaseSWS and REM sleep via D3 receptors (Lagos et al., 1998), whichare not autoreceptors (inhibitory). Similar results have been foundin humans. A small dose of the D2 preferring agonist pergolide(Staedt et al., 1997) or the dopamine reuptake inhibitor, bupro-pion (Nofzinger et al., 1995; Ott et al., 2004) induced an increaseof REM sleep duration and density. A moderate dose of pramipex-ole produced a reduction of sleep latency, an increase of total sleeptime (Micallef et al., 2009), and of time in REM sleep (Jama et al.,2009). Together, these data show that administration of D2 or D3agonists can facilitate sleep (including REM sleep), but the exactunderlying mechanisms are not yet well understood. Actually, in2006, Dzirasa et al. demonstrated that a hyperdopaminergic stateis necessary for the generation of REM sleep. It seems that both D2autoreceptors and D3 postsynaptic receptors are implicated in thismechanism.

Can reward processing also influence the regulation of REMsleep? Low doses of cocaine, a drug that stimulates the ML-DAreward system, can increase REM sleep in rats (Knapp et al.,2007). Moreover, in decerebrate cats the introduction of a tubefor gastric feeding (Villablanca, 1966), or other cutaneous, propri-oceptive and sensory stimuli like repetitive sounds (Jouvet andDelorme, 1965; Villablanca, 2004), can induce REM sleep. Thisphenomenon may bear some analogy to cataplexy in narcolepticpatients. Indeed, episodes of REM-like atonia (cataplexy) duringwakefulness can be triggered by emotional experiences, includ-ing the anticipation of reward (Anic-Labat et al., 1999; Ponz et al.,2010a; Schwartz et al., 2008; Sturzenegger and Bassetti, 2004), andcataplexy is also triggered by feeding, in narcoleptic dogs and orexinknockout mice (Clark et al., 2009; Mitler et al., 1974; Reid et al.,1994).

Based on these findings, we suggest that the activation ofemotionally-relevant information such as reward can potentiallyinfluence the generation of REM sleep. More specifically, increaseddopaminergic activity in the VTA could modulate activity in brainregions that are critical for the generation of REM sleep, in partic-ular the sublaterodorsal nucleus (SLD) of the pons, which is a keystructure for generating REM sleep (Boissard et al., 2002; Clementet al., 2011; Fort et al., 2009). Indeed, VTA provides efferent pro-jections to the SLD, thus potentially gating the onset of REM sleep(Boissard et al., 2003). The RAM supports that, at the end of an NREMepisode, the downward arc of the hippocampal–VTA loop, whichinvolves active memory processing (‘memory → reward’ direction;Fig. 3A), leads to an activation of the VTA, which in turns projectsto SLD and gates the onset of REM sleep. In addition, the LH-to-VTAorexin pathway could also be implicated. Indeed, occasional burstdischarges of orexin neurons during REM sleep (Takahashi et al.,
2008), with their projections to VTA dopaminergic neurons (Fadeland Deutch, 2002), may contribute to reward-driven dopamin-ergic induction or maintenance of REM sleep (a hypothesis thatwould require and may inspire future experimental investigations).

L. Perogamvros, S. Schwartz / Neuroscience and Bi

Fig. 4. Activation of ML-DA reward system during NREM sleep and the generationof REM sleep. According to the RAM, tonic dopamine response induced by the down-ward arc of the hippocampal–VTA loop may contribute to the generation of an REMsleep episode. The downward arc of the hippocampal–VTA loop, which involvesactive memory processing, leads to an activation of the VTA at the end of an NREMepisode. VTA would then provide an excitatory projection to the SLD, which is con-sidered as the REM sleep generator (red dashed arrow). A hyperdopaminergic staterelated to reward processing could thus potentially contribute to the generation ofREM sleep. Projections from orexin neurons or from the amygdala to VTA could alsobe implicated. Abbreviations: HC: hippocampus; REM: rapid eye movement sleep;SLD: sublaterodorsal nucleus VS: ventral striatum; VTA: ventral tegmental area. (Forit

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inally, it was also suggested that projections from the amygdalao SLD may be implicated in emotion-related induction of REM-likeeatures, such as muscle atonia (cataplexy) in narcolepsy (Luppit al., 2011).

The VTA was until recently thought to be a dopaminergic struc-ure predominantly involved in promoting wakefulness (Bagettat al., 1988; Rye, 2004; Szabadi, 2006). However, there is someecent indication that N-methyl-d-aspartate (NMDA)-induced VTAesions in cats produce an increase in wakefulness (rather than anncrease in sleep) (Vetrivelan et al., 2010). Further evidence for theole of the VTA in REM sleep comes from the canine model of cat-plexy: administration of D2/D3 agonists in the VTA of narcolepticogs induced sleep attacks and aggravated cataplexy, whose under-

ying mechanism implicates the activation of REM-on SLD neuronsLuppi et al., 2011; Reid et al., 1996).

Fig. 4 shows how activation of the VTA at the end of a NREMpisode (stage N2 in humans) may result in an enhancement ofEM sleep.

. Reward activation and dreaming

.1. The neural circuits of dreaming

Dreaming is a state of consciousness in which internally-enerated sensory, motor, emotional and cognitive experiencesevelop into actions and imaginary plots (Desseilles et al., 2011).ur knowledge about the neural bases of dreaming derives pri-arily from the study of REM sleep, because this sleep stage has

nitially been linked to dreaming activity (Dement and Kleitman,957). Moreover, dream reports are on average more vivid andizarre, with more complex narratives, i.e. are more ‘dream-like’,fter awakenings from REM than from NREM sleep (Fosse et al.,001; Strauch and Meier, 1996). Early neuroimaging studies haveevealed that the distribution of brain activity during REM sleeps not homogeneous but is characterized by specific activation andeactivation patterns (e.g. Braun et al., 1997; Maquet et al., 1996;ofzinger et al., 1997). More recent studies using imaging meth-
ds with increasingly higher temporal and spatial resolution (e.g.unctional MRI, high-density EEG) have started to describe moreransient changes in brain activity (e.g. Dang-Vu et al., 2008) and

in brain connectivity across all sleep stages (e.g. Massimini et al.,2005, 2010).

The specific pattern of regions activated during REM sleep inhumans is consistent with some main features of dreaming expe-rience, as we briefly review below (Hobson et al., 1998; Schwartz,2004; Schwartz and Maquet, 2002) (Fig. 5).

A first set of activated regions consists of the PPT, thalamus, basalforebrain, as well as of limbic and paralimbic structures, includingbilateral amygdala, hippocampal formation, mPFC and ACC (Braunet al., 1997; Maquet et al., 1996; Nofzinger et al., 1997). Activation ofthe amygdala may reflect intense emotions, in particular fear andanxiety, often experienced in dreams (Smith et al., 2004). Amyg-dala, mPFC and ACC activity could also subserve emotion regulationprocesses (e.g. extinction of fear; Fu et al., 2007; Pace-Schott et al.,2009). Consistent with the RAM, activation of limbic and paralim-bic regions suggests that REM sleep could favor the reactivationand processing of relevant, novel and emotionally salient memo-ries (Sterpenich et al., 2007, 2009; Wagner et al., 2001; Walker andvan der Helm, 2009). This pattern of activation would also allowthe incorporation of recent memories in dreams, which is com-monly observed in dream studies (Schredl and Hofmann, 2003;Schwartz, 2010). When compared to wakefulness, several regionsimplicated in executive and attentional functions during wake-fulness are significantly deactivated during REM sleep, includingthe dlPFC, OFC, posterior cingulate gyrus, precuneus, and the infe-rior parietal cortex (Braun et al., 1997; Maquet et al., 1996, 2000,2005; Nofzinger et al., 1997). Deactivations in these regions maycause disorientation, illogical thinking and impaired working mem-ory in dreaming (Hobson et al., 1998; Schwartz, 2004; Schwartzand Maquet, 2002). Finally, other activated regions comprise asso-ciative sensory regions and the parieto-temporo-occipital (PTO)junction which could contribute to the generation of sensory andspatial imagery in dreams (Braun et al., 1997, 1998), and activa-tion in motor circuits (including the cerebellum and basal ganglia,Braun et al., 1997; Maquet et al., 2000) is consistent with dreamedmotor actions.

Changes in dreaming can also be observed after focal brainlesions. In 1997, Solms established the first nosology of dream dis-orders based on the study of 361 neurological and neurosurgicalpatients (Solms, 1997). Approximately one third of these patientsreported a global cessation of dreaming subsequent to the braindamage, which predominantly involved a lesion in the PTO junction(see also Bischof and Bassetti, 2004; Cathala et al., 1983; Murri et al.,1984). Global cessation of dreaming after a lesion in the PTO regionis consistent with the idea that this region may subserve cognitivefunctions that are necessary for dreaming such as visual imageryand spatial cognition. Cessation of dreaming was also observed ina few patients with lesions in the white matter surrounding thefrontal horns of the lateral ventricles, in about the same regionthat was targeted in prefrontal leucotomy (Bradley et al., 1958).Lesions in this region, which provoke dream cessation but maintainREM sleep (Solms, 2000), disrupt the ML-DA connections from theVTA to the shell of the NAcc, amygdala, HC, ACC and frontal cortex(insular and medial OFC, medial frontal cortex, vmPFC). This cir-cuit corresponds to the mesolimbic circuits of the SEEKING systemas described by Panksepp (Alcaro and Panksepp, 2011; Panksepp,1982; Panksepp, 1998) (see Box 2). Solms proposed that a REMstate is not in itself mandatory for dreaming; instead dreamingwould require the activation of the SEEKING system (Solms, 2000).Several other observations converge to further support the role ofthis system in dreaming. Prefrontal leukotomy targeting the vmPFCin patients with schizophrenia caused anhedonia and cessation of

the administration of dopaminergic agents like l-DOPA (Nausiedaet al., 1982; Sharf et al., 1978), amphetamines (Thompson andPierce, 1999), bupropion (Balon, 1996), and dopamine agonists


Fig. 5. Functional neuroanatomy of human REM sleep. Brain regions more activated during REM sleep are shown in red and less activated in blue. This figure combinest 1996,d ; OFCm the re

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he results from studies using PET imaging (Braun et al., 1997, 1998; Maquet et al.,orsolateral prefrontal cortex; HC: hippocampus; mPFC: medial prefrontal cortexovement sleep. (For interpretation of the references to color in this figure legend,

Pinter et al., 1999; Thompson and Pierce, 1999) can induce vividream-like experiences. By contrast, hypoactivity of this systemor example after administration of D2 antagonists is associatedith a reduction in vivid dreaming (Gaillard and Moneme, 1977),

lthough this finding would need replication. Finally, as we pre-iously mentioned, reward-related components of the SEEKINGystem are active during REM sleep, including the VTA, VS, amyg-ala, HC, ACC, and vmPFC.

However, it should be noted that effects of dopamine on dream-ng may involve interactions with other neuromodulatory systems,ike basal forebrain cholinergic cells that activate cortical and lim-ic structures (Perry and Piggott, 2000). Lesions resulting from

eucotomy may alter not only dopaminergic, but also choliner-ic and noradrenergic efferent and afferent connections (Doricchind Violani, 2000). Finally, dreaming enhancement, as inducedy dopaminergic agents, can also be observed in patients receiv-

ng a noradrenergic beta-receptor blocker (Thompson and Pierce,999) or cholinesterase inhibitors (Zadra, 1996). Consequently, the

nteraction of dopaminergic functions with other neuromodula-ory systems must be taken into consideration when studying theeurobiology of dreaming.

.2. ML-DA reward system activation and dream generation

What force would activate the ML-DA reward system dur-ng sleep and thus induce dreaming? The RAM proposes thatreaming may result from the activation of the reward and emo-ional components of the SEEKING system by ‘off-line’ memorynd cognitive processes during sleep (‘memory → reward’ direc-ion). This is in agreement with Wamsley and Stickgold (2010)ho recently proposed that dreaming may reflect sleep-dependentemory processing during sleep, as well as with models stating

hat dreams are influenced by waking emotional concerns of theleeper (Cartwright et al., 2006; Mancia, 2004; Nielsen and Levin,007; Schredl, 2010). Substantial mesolimbic reward-system acti-ation during REM sleep would thus explain why this stage may beonsidered as a ‘dream facilitator’. On the other hand, activation ofontextual and emotional memories by reward-related structures
uring NREM sleep (amygdala, ACC, hippocampus, ventral stria-um) could also explain NREM dreaming. We do not know yet whathe conditions are for a memory trace to facilitate the productionf a dream. We hypothesize that memories with high emotional
2000; Nofzinger et al., 1997). Abbreviations: ACC: anterior cingulate cortex; dlPFC:: orbitofrontal cortex; PPT: penduculopontine tegmental nuclei; REM: rapid eyeader is referred to the web version of the article.)

and motivational value for the individual are privileged to bereactivated during sleep, and may thus amplify the activation ofthe ML-DA system and of the SEEKING system.

5.3. ML-DA reward system activation and dream content

Lesion studies in cats in which REM sleep atonia was preventedrevealed that these animals exhibit a specific range of behaviorsduring REM sleep, such as exploration, fear, anger, and groom-ing behaviors (‘oneiric behaviors’, Jouvet and Delorme, 1965).Interestingly, these behaviors could be driven by emotional andmotivational components of the SEEKING system (Panksepp, 1998).Similarly, patients with RBD may act out their dreams, often inthe form of aggressive-violent movements mimicking attacks ordefense behaviors, with non-violent behaviors being compara-tively less frequent (e.g. Oudiette et al., 2009). Dream reports alsoappear to be biased toward content with emotional and motiva-tional value (e.g. socializing, fighting, or sexual activity) and lessoriented toward life content with no such particular value. Forexample, daily routine activities such as typing, washing dishes, orbuying food at the supermarket, are not frequent in dream reports(Schredl, 2010).

Sustained activation of the ML-DA reward system (in particularthe VTA) during REM sleep may favor the activation of stimu-lus representations or behaviors of high motivational relevance,which would induce instinctual exploration as well as approachand avoidance behaviors. For example, pleasant and positive con-tent of a dream (e.g. winning a game or having sex) would constitutea rewarding (approach-prone) stimulus, whereas threat-relatedcontent (e.g. being chased or attacked) would be an aversive(avoidance-prone) stimulus. NAcc and VTA may be activated inde-pendently of the emotional valence of the dream content, becauseboth structures are found to be activated during both reward andpunisher anticipation (Carter et al., 2009; Delgado et al., 2008).Motivational and emotional content may be more prominent inREM than in NREM dreaming (Smith et al., 2004). This is consistentwith the finding that several limbic and ML-DA regions are selec-tively activated during REM, with amygdala activity and burst firing
in the VTA being significantly higher in REM compared to NREM.For Smith and collaborators ‘the primary role of the limbic systemduring sleep may be to activate the motivational characteristics ofthe sleep experience’ (Smith et al., 2004, p. 502).

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.4. Links of the RAM to other dream theories

Dreams may fulfill important psychological or cognitive func-ions. Many theories have been proposed in relation to suchunctions of dreaming. Below, we show how the RAM may relatend differ from some of these theories, in particular Freud’s theoryf dreams, Hobson’s AIM theory, and Revonsuo’s threat simulationheory. Note that by confronting the RAM with these theories, ourim is to better characterize some main features of the RAM butot to provide an exhaustive review of theories about dreaming.

While activation of ML-DA circuits during dreaming might beonsistent with some of the most important propositions of theseheories, the RAM places the dopaminergic-driven motivationalnd emotional drives at the center of the dreaming state. We sug-est that activation of the ML-DA system allows the dreamer toecome acquainted with diverse configurations and rewarding val-es of a simulated internal environment and thereby establishealistic and adaptive expectations, which could be used in realife situations. Thus, dreams not only result from the activation of

emory processes during sleep, but they may also contribute toffline memory consolidation and learning. The latter hypothesiss supported by recent studies on dreaming (Wamsley et al., 2010),n the SEEKING system (Alcaro and Panksepp, 2011), and on VTA’sole in memory and learning (Adcock et al., 2006).

.4.1. Freud’s psychoanalytic theory of dreams and RAMIn brief, the theory proposed by Freud in 1900, in his book “The

nterpretation of Dreams” (Freud, 1995), is based on the fundamen-al assumption that the purpose of each dream is a wish-fulfillment:reams are attempts of the unconscious to resolve a, usually dis-urbing, conflict from the recent or distant past. A censorship

echanism renders dreams altered and incomprehensible, becausehe immediate gratification of a wish is usually impossible or coulde unwise or unsafe (‘pleasure principle’ opposing the ‘reality prin-iple’). This mechanism makes anxiety-arousing wishes tolerableor the conscious. Furthermore, because dreams would preserveleep by giving an acceptable form to the satisfaction of a desiremainly sexual) they are considered by Freud to be the ‘guardians’f sleep.

On the one hand, the RAM supports some of Freud’s claimsbout dreaming because it proposes that activation of the SEEKINGeward-related system (urge for Freud) could generate dreamingproduction) and could preserve dream continuation (mainte-ance). In particular, a wish in the Freudian taxonomy couldorrespond to the anticipation of a reward, and a threat could corre-pond to the anticipation of a punisher that would trigger avoidanceehavior or seeking of safety (which may typically fail in night-ares). On the other hand, while many bizarre aspects in dreamsay relate to changes in regional brain activity and in functional

onnectivity between brain regions (see Section 5.1 above), thereudian notion of an active censorship that would transform theriginal or ‘latent’ content of a dream into some ‘apparent’ (usuallyizarre) content lacks neurobiological support. Moreover, unlikehe Freudian model of dreaming, the RAM also implies that dreamsan be potentially related to novel events or to some probabilisticuture, and not only to the past. Although, there is evidence for theresence of past and current waking concerns in the dream con-ent (Cartwright et al., 2006; Schredl and Hofmann, 2003), dreamsre usually novel constructions and rarely reproductions of pastvents (Meier, 1993). Actually, while a large proportion of dreamlements comes from recent memory (Schwartz, 2003), integratedife episodes are incorporated in no more than 1–2% of dreams
eports (Fosse et al., 2003).
The RAM proposes that dreaming, by activation of the rewardystem, exposes and trains the dreamer to motivationally- ormotionally-relevant stimuli, which may relate to instinctual


behaviors or drives (such as feeding, mating, fighting, fleeing, etc.)or to memory elements (such as current concerns), as well as tonovel cues (e.g. novel combinations of elements from memory).Thus, while the RAM supports that the off-line replay of a mem-ory is responsible for the generation of a dream (see Section 5.2), italso claims that the content and function of this very dream doesnot only relate to episodic memories, as suggested by classic psy-choanalytical theories but also, and importantly, to probable and/ornovel experiences. This mechanism would potentially contribute toadaptive behavior by improving future performance and emotionregulation processes.

5.4.2. Activation-input-modulation (AIM) model and RAMThe AIM was introduced by Hobson and offers a charac-

terization of the brain states according to three main factors:activation (total and regional brain activity levels), input–outputgating (external versus internal source), and modulation or infor-mation processing mode (cholinergic versus aminergic) (Hobson,1988, 1999). Within the AIM framework, REM sleep and dream-ing are both characterized by high levels of activation, internalinput, and aminergic modulation. More specifically, dreams resultfrom internally-generated sensory activation originating from thebrainstem (ponto-geniculo-occipital waves), later combined withmemory and cognitive functions. Hence, according to the last revi-sion of this model, “dreaming is an indispensable — if sometimesmisleading — subjective informant about what the brain does dur-ing REM sleep” (Hobson, 2009, p. 805). Moreover, REM sleep anddreaming would provide us with a virtual reality model, which maysupport learning and memory, and may influence the developmentand maintenance of waking consciousness.

Concerning the role of the dopamine system in dreaming, Hob-son has suggested that the relative persistence of dopamine releaseduring REM sleep could explain some of the cognitive character-istics of dreaming (such as visual hallucinations, bizarreness, andlack of self-reflective awareness), which may resemble psychosis inmental illnesses (Scarone et al., 2008). While both models are notincompatible, a main difference between Hobson’s view and ourproposal in the context of the RAM concerns the functional role ofML-DA system activation during sleep. In particular, the RAM pro-vides the first integrated and detailed description of how activationof the dopamine system and limbic circuits during sleep and dream-ing may contribute to important cognitive and affective functionspertaining to memory, emotion, and motivation.

5.4.3. Threat Simulation Theory (TST) and RAMThe Threat Simulation Theory (TST) was initially proposed by

Revonsuo (2000) and then further developed by Revonsuo andValli (2009). According to the TST, the function of dreaming is toallow an organized and selective offline simulation of threaten-ing events that would ultimately promote the development andmaintenance of threat-avoidance skills. Supporting the universal-ity and prevalence of threatening experiences in dreams, beingchased or attacked is the most typical dream theme around theworld (Zadra, 1996). Behaviorally and perceptually realistic threat-ening experiences in a dream would trigger the activation of athreat simulation system, and also underlying brain circuits, inparticular the amygdala. Such a virtual rehearsal during dream-ing would lead to improved performance in real life situations andthis training could be used as learning or maintenance of threatavoidance skills (Valli and Revonsuo, 2009). Support for the the-ory comes from the study of dreams in traumatized populationswho simulate threatening events in their dreams more often than
non-traumatized populations (Valli et al., 2005), as well as from theobservation that REMSD impairs threat avoidance responses in reallife (e.g.Martinez-Gonzalez et al., 2004). The TST therefore suggestsplausible psychological and biological functions for dreaming and is

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onsistent with findings on the predominance of negative emotionsn dreams.

The RAM appears as a useful supplement to the TST because itxplains why emotionally-relevant experiences (including threat-elated information, but not exclusively) have a higher probabilityf being activated during dreaming and have a preferential accesso sleep-related consolidation processes. We propose that thecquaintance of individuals with diverse stimuli and the establish-ent of realistic and adaptive expectations during dreaming are

erved by the SEEKING system. Importantly, this system would alsorotect an animal from aversive stimuli or punishment by promot-

ng the seeking of safety (Alcaro et al., 2007; Alcaro and Panksepp,011; Delgado et al., 2008). Exposure to feared stimuli (e.g. char-cters, situations, thoughts, memories, physical sensations) in aotally safe context during dreaming may resemble exposure ther-py for anxiety disorders (Pace-Schott et al., 2009). Nightmaresould by contrast reflect the failure of an adaptive fear memory

xtinction process, in the presence of temporary (e.g. daily con-erns) or more persistent (e.g. trauma) increases in affect loadNielsen and Levin, 2007).

The RAM is therefore in agreement with the TST and extendst by proposing that one of the main functions of dreaming iso expose the dreamer to rewarding or aversive stimuli, in ordero maintain and improve offline memory consolidation processesnd performance in real life situations, while also contributingo emotion regulation processes. Because it is responsible for theppetitive motivational drives (like sex) and exploratory behav-ors (like exposure to a potentially harmful/rewarding stimulus),he engagement of ML-DA circuits, as modeled in the RAM, offers alausible neurophysiological and neurocognitive model of dream-

ng that integrates and complements the fear-related amygdalaechanisms proposed by the TST.In summary, the three theories of dreaming reviewed here sug-

est important and distinct emotional and cognitive functions toreaming (i.e. wish fulfillment, performance improvement, threatimulation). These functions, including their underlying neurobi-logical mechanisms, can be implemented within the frameworkf the RAM, which thus offers to sleep science an integrative linketween sleep neurophysiology, cognition and dream content.

. Clinical context

Activation of the ML-DA reward system during sleep andreaming may constitute a model for the understanding of someeuropsychiatric disorders such as psychosis, depression, and com-ulsive behaviors.

.1. Psychosis and dreaming

The notion that psychosis and the dream state may share someommon underlying mechanisms has a long history. For example,n the late 19th century, the neurologist Hughlings Jackson claimed:Find out about dreams and you will find out about insanity” (citedn Gottesmann, 2006). Recently, there has been a renewed interestn the notion that the dreaming state could serve as a neurobiologi-al model of psychosis (Gottesmann and Gottesman, 2007; Hobson,004; Noreika et al., 2010; Scarone et al., 2008). Both states presenthenomenological similarities, including sensory hallucinations,izarre imagery, diminished reflectiveness, and intensification ofmotion (Scarone et al., 2008). At the brain level, dreaming andsychosis are characterized by dlPFC deactivation, a breakdown
f cortical connectivity, and specific neurochemical variations (inarticular hyperdopaminergia).
Hyperactivation of the dopaminergic reward system seems toe present in both psychosis and dreams. Kapur (2003) and Corlett


et al. (2007) suggested that a hyperdopaminergic state leads toimpaired computation of prediction errors as well as to an aber-rant assignment of salience to elements from one’s own experience(see Heinz and Schlagenhauf, 2010). Hallucination would reflect thedirect experience of these aberrantly salient experiences, whereasattempts to make sense of those experiences would result in delu-sions.

Is there a link between increased dopaminergic activity in psy-chotic patients and the characteristics of their dreams and theirsleep? Studies addressing this question showed that, in thesepatients, cognitive bizarreness during wakefulness correlates pos-itively with cognitive bizarreness of their dream reports (Scaroneet al., 2008). Note that dream experiences in schizophrenic patientsalso appear to be both more bizarre (Noreika et al., 2010) and moreviolent (Schnetzler and Carbonnel, 1976) than those of healthy con-trol subjects. In addition, REM density and sleep duration correlatenegatively with the global severity of clinical symptoms (measuredby the Brief Psychiatric Rating Scale total score – BPRS) (Poulin et al.,2003), and with positive symptoms (Yang and Winkelman, 2006) indrug-naïve patients with schizophrenia. The study of sleep param-eters (e.g. REM density) and dream content could thus provideuseful insights into the pathophysiology of early-onset psychosisand schizophrenia, and may offer a potential biomarker for the evo-lution of these diseases. Research in this domain has scientific andclinical relevance, and should be encouraged.

6.2. Sleep and emotion regulation

Emotions in dreams (see Section 5.3) as well as the activation ofcerebral regions specialized in emotional processing during sleep(see Section 5.1) lend support to the idea that sleep may contributeto emotion regulation processes (Cartwright et al., 1998; Desseilleset al., 2011; Nielsen and Levin, 2007). Although an exhaustivereview on this contribution is beyond the scope of the presentarticle, below we discuss two instances where sleep relates to emo-tion regulation: the link between insomnia and depression, and theeffects of sleep deprivation on emotional processing.

6.2.1. Insomnia and sleep loss as precursors of depression viaalteration of brain reward networks

Reward-related deficits, such as decreases in the capacity toseek out rewards, in decision-making, and in the ability to experi-ence pleasure, are core characteristics of depression (Der-Avakianand Markou, 2012). A down-regulation of dopamine-related SEEK-ING resources has been hypothesized in major depressive disease(Alcaro and Panksepp, 2011), and a dysfunction in mesolimbic andnon-mesolimbic reward structures and networks has been docu-mented (Blood et al., 2010; Nestler and Carlezon, 2006; Pizzagalliet al., 2009; Tremblay et al., 2005). Insomnia is another main symp-tom of the depressive disorder (Tsuno et al., 2005). Depression maybe considered as a risk factor for insomnia (Ohayon and Roth, 2003),while insomnia was found to represent an independent majorrisk of subsequent onset of major depression (Buysse et al., 2008;Johnson et al., 2006; Riemann and Voderholzer, 2003; Roane andTaylor, 2008). Because of their reciprocal relationships, insomniaand depression are increasingly considered as comorbid conditionsthat would share some common underlying causal mechanisms(Staner, 2010).

Sleep restriction induces neuroendocrine disturbances, in par-ticular HPA (hypothalamic–pituitary–adrenal) axis stimulation(Novati et al., 2008; Spiegel et al., 1999), that are also observed indepression (Holsboer, 2000). Such ‘hyperarousal mechanism’, sim-
ilar to what is usually observed in insomnia, may partially but nottotally explain a direct causality between insomnia and depres-sion. Activation of reward networks during sleep as proposed herecould be a supplementary mechanism explaining why disturbances

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n sleep quality or quantity may precede clinical depression andarticipate in its occurrence. Indeed, chronically disrupted sleepnd insufficient sleep time (<6 h), known to produce cognitive per-ormance deficits (Van Dongen et al., 2003) and negative affectivetates (Banks and Dinges, 2007; Meerlo et al., 2008; Zohar et al.,005), may alter reward processing in a way that would precipitate

depressive, reward-deficient symptomatology (anhedonia, abou-ia, impaired decision making) (Der-Avakian and Markou, 2012).

probable down-regulation of reward and emotional processes,specially during NREM sleep should be further investigated, sinceecreased slow wave sleep and slow wave activity may charac-erize both primary insomnia (Merica et al., 1998) and depressionArmitage, 2007). Longitudinal studies examining the effects ofhronic sleep restriction in reward networks and correlating themith mood disturbances are needed in order to further establish

causal relationship between insomnia and depressive disorder.imilar evidence is also needed for the hypomanic/manic phasesf bipolar disorder, which have been also causally associated withleep disturbances, like sleep reduction (Plante and Winkelman,008; Wehr et al., 1987) and circadian dysregulations (Roybal et al.,007; Harvey, 2008).

.2.2. Evidence from sleep deprivation studiesFurther evidence from SD studies in non-depressed subjects

upports the role of sleep in waking emotion regulation processes.D can lead to reduced disappointment in response to losses in

gambling task, together with decreased activity in the insularortex (Venkatraman et al., 2007), which is thought to processhe emotional significance of a stimulus, including the somaticffective response (e.g. autonomic changes in blood pressure) andntrospective awareness (Critchley, 2005; Ernst and Paulus, 2005;inger et al., 2009). Because the insular cortex is activated duringoth NREM (Nofzinger et al., 2002) and REM sleep (Maquet et al.,000), one could hypothesize that SD interferes with emotionalunctions subserved by the insula. In addition, SD causes an ampli-ed response of amygdala to negative emotional stimuli, paralleledith a hypoactivity of the mPFC, suggesting a failure of top-down

ortical control from the mPFC on the amygdala (Yoo et al., 2007).his latter result indicates that sleep is necessary for the functionalntegrity of amygdala–PFC circuit, which is responsible for adaptedmotional responses during waking life. As a complement to thisnding, a recent study supports that SD amplifies the reactivityf reward networks in healthy volunteers, when exposed to pos-tive emotional stimuli (Gujar et al., 2011). These recent studiesemonstrate that combining behavioral and brain imaging mea-ures significantly improve our understanding for the effects of SDn waking emotional processing and reward functions. These stud-es thus offer a very promising approach for future experiments thatould be applied to both controls and patients.

.3. Sleep and compulsive behaviors

Compulsive behaviors like drug addictions are characterizedy an inability to reduce the occurrence of an approach behav-

or toward a primary or secondary reward (e.g. food, drug), andy a negative emotional state when the access to the reward isrecluded. It is now well established that compulsive behaviorsay relate to a dysregulation of the hedonic (OFC, insula), emo-

ional (amygdala) and motivational (VTA, NAcc) components of theeward networks (Koob, 2009; Koob and Volkow, 2010).

Recent findings suggest that sleep problems like insomniaay developmentally precede and predict early onset of alcohol,

igarette and marijuana use in adolescents and young adults (Roanend Taylor, 2008; Shibley et al., 2008; Wong et al., 2004, 2009).ere, we propose that a disruption of brain reward and SEEKINGetworks, as well as ineffective emotion regulation processes due to


sleep disturbances, could lead to compensatory drug and food seek-ing in vulnerable subjects (Alcaro and Panksepp, 2011; Koob, 2009;Zellner et al., 2011), as shown in animals (Puhl et al., 2009) andhumans (Benedict et al., 2012). Disturbances of circadian (Forbeset al., 2012; Hasler et al., 2012) and neuroendocrine (Van Cauteret al., 2008) mechanisms may also be implicated in these inter-actions. Future longitudinal studies could also be useful to furthersubstantiate and clarify these links between sleep disturbances andcompulsive behaviors like addictions.

7. Limitations and testability of the model

In this article, we propose that reward-related mechanisms con-tribute to the generation of both REM sleep and dreaming. However,we do not claim that the same pathways within the ML-DA systemfulfill both functions, as it is well established that REM sleep anddreaming are dissociated states (Solms, 2000; Oudiette et al., 2012).The REM sleep generator is located in the brainstem (Luppi et al.,2011), whereas the dream generator probably implicates mesolim-bic/mesocortical networks (Solms, 2000). Accordingly, the RAMclaims that the activation of emotionally-relevant information suchas reward can potentially favor the generation of both REM sleepand dreaming, while this most probably happens via dissociatedmechanisms. Whereas dreaming is influenced by ascending ML-DA mechanisms (e.g. SEEKING system; see Section 5.1 and Fig. 2),reward-induced REM sleep would primarily implicate descendingprojections from the hippocampus to the midbrain, and from themidbrain to the REM sleep generator (see Section 4 and Fig. 4).Therefore, we conjecture that disconfirmation of the former mech-anism would not mean disconfirmation of the latter, and vice versa.It should be also noted that, while reward-related dopaminergicactivity would facilitate the generation of REM sleep, it does notseem necessary for REM sleep to occur. Other non-dopaminergicmechanisms and structures (Boissard et al., 2003; Luppi et al.,2011), that are not described in this article, are also implicated inthe generation and maintenance of REM sleep. Similarly, dream-ing is not exclusively dopamine-driven, and may for example alsoimply other components of the SEEKING system, such as ascendingnoradrenergic and descending glutamatergic influences (Panksepp,1998). Moreover, dopamine alone certainly does not account for thewhole range of cognitive and emotional processes occurring dur-ing sleep. Other neuromodulatory systems with many of which thedopamine system interacts also contribute to these functions.

Another limitation of the RAM model is that many of the exper-iments supporting the role of dopamine in sleep/dream generationand the activation of reward structures (VTA, striatum) duringsleep were performed in animals (mainly rodents). However, as wehave shown above, animal data are mostly consistent with existinghuman pharmacological studies (Ferreira et al., 2002; Jama et al.,2009; Micallef et al., 2009; Ott et al., 2004; Pinter et al., 1999; Staedtet al., 1997; Ye et al., 2011), clinical (D’Agostino et al., 2010; Gaillardand Moneme, 1977; Sharf et al., 1978; Solms, 1997), and with SDstudies (Gujar et al., 2011; Holm et al., 2009; McKenna et al., 2007;Menz et al., 2012; Venkatraman et al., 2007; Volkow et al., 2012).More research is thus awaited to further confirm a similar recruit-ment of the reward system in human sleep and its implication indreaming and REM sleep generation.

In this article, we have proposed a model for sleep and dreamingwhich is inspired and supported by a rich and comprehensive set ofexperimental data. Beyond the integration of existing data, the RAMaims at improving our knowledge about the influence of the ML-
DA system on memory, sleep and dreaming processes by fosteringnew research in this domain. The specific hypotheses put forwardin the model are therefore amenable to experimental confirmationor falsification, as we suggest hereafter.

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One central hypothesis of the RAM is that activation of theL-DA reward system during sleep enhances the overnight con-

olidation of rewarded or emotionally-relevant memories. Thisypothesis can be directly addressed by studying the influencef a pharmacological manipulation of dopamine activity duringleep on the consolidation of recent rewarded versus non-rewardedemories in healthy volunteers (e.g. using dopamine D2/D3 recep-

or agonists versus antagonists, Pessiglione et al., 2006; Ye et al.,011). The model predicts that an increase in dopamine activ-

ty boosts (while a decrease would suppress) the advantage ofewarded over non-rewarded stimuli for consolidation duringleep. A similar pharmacological approach could be used to test theypothesis that ML-DA activation influences the regulation of REMleep, by investigating the effects increased or decreased dopamineuring sleep on polysomnographic parameters (e.g. REM densitynd duration).

The notion that motivationally-relevant information is prior-tized for subsequent reprocessing during sleep can be directlyssessed by measuring changes in brain activity or connectivityuring sleep (fMRI or PET) following a learning task involvingewards or not, with the prediction that ML-DA regions and theironnectivity with the hippocampus should be enhanced. This imag-ng approach in humans would somehow mimic the study byansink et al. in rats (Lansink et al., 2008), and is methodologi-ally feasible (e.g. Bergmann et al., 2012; Peigneux et al., 2004; vanongen et al., 2011). A similar brain imaging approach could bepplied to test for the role of the ML-DA activation in the generationnd the motivational content of dreams, for example by performingorrelation analyses at the individual level between dream param-ters (quantity of dream recall, motivational content of the dreameports) and measures of brain activity or connectivity during sleepSchwartz and Maquet, 2002).

The contribution of ML-DA activity during sleep may also benvestigated by studying the effects of SD and insomnia on emo-ional and reward processing. For example, SD and insomnia cannfluence affect and mood (see Section 6.2.1, Banks and Dinges,007; Zohar et al., 2005). Moreover, some recent studies convinc-

ngly demonstrated that SD interferes with emotion regulation andeward-based decision making in healthy volunteers (see Sections.2 and 6.2.2, Gujar et al., 2011; McKenna et al., 2007; Venkatramant al., 2007). These findings thus corroborate the hypothesis thatleep fosters ML-DA functions, as proposed by the RAM.

. Conclusions

In this article, we have introduced the Reward Activation ModelRAM). The RAM is based on recent neurophysiological, neuroimag-ng, and clinical findings that support the activation of the ML-DAeward system during sleep. In the context of the RAM, we suggesthat this activation (a) is implicated in the off-line consolidationf memories with elevated emotional or motivational value, thusnhancing learning and synaptic plasticity; (b) favors the gener-tion of REM sleep via the projection from the VTA to the SLD ofhe pons; and (c) contributes to dream genesis and content. Activa-ion of the ML-DA reward system during sleep creates an internalnvironment of high exploratory excitability and elevated novelty-eeking (i.e. activation of the SEEKING system), which can biasream content toward events that are of motivational relevance,r generate other forms of exploratory behaviors during sleep (e.g.nstinctual and motivational behaviors in parasomnias, sniffing inats).

Importantly, dreaming could offer a virtual reality platform forn acquaintance of the dreamer with diverse stimuli, includingtimuli of high emotional and/or motivational value from the recentast or novel cues. We propose that the activation of the ML-DA


reward system during sleep and dreaming contributes to adaptivememory processes, leading to subsequent performance improve-ment during wakefulness.

By developing a new model for sleep and dreaming, our aimwas to allow the integration of prominent hypotheses about offlinecognitive and emotional processes during sleep, including memoryconsolidation, threat simulation, and performance improvement.In addition, this model can be applied to clinical conditions and pro-vide insights into the pathophysiology of disorders like depression,schizophrenia and addiction. Moreover, because sleep curtailmentemerges as a major health problem, with disastrous socioeconomicand public safety consequences, demonstrating that sleep affectslearning and emotion regulation may be useful to promote mea-sures aiming at preventing sleep restriction (and its consequences),particularly in the most vulnerable populations, such as for examplepsychiatric patients or children.

We think that the RAM provides a timely and useful integra-tion of neurophysiological, clinical, and neuroimaging approachesto sleep and dreaming. This integration has become possible thanksto recent neuroscientific evidence about the activation of the ML-DA system during sleep and reward processing. The RAM thus offersa comprehensive model that combines different levels of descrip-tion, from the basic neurobiology of reward and sleep functionsto affective and cognitive levels encompassing dreaming and con-sciousness in humans.

Acknowledgements

This work is supported by grants from the Swiss National ScienceFoundation, the Swiss Center for Affective Sciences, the MercierFoundation, and the Boninchi Foundation.

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