Abstract
The mesolimbic dopamine (DA) system plays an integral role in incentive motivation and reward seeking and a growing body of evidence identifies signal transduction at cannabinoid receptors as a critical modulator of this system. Indeed, administration of exogenous cannabinoids results in burst firing of DA neurons of the ventral tegmental area and increases extracellular DA in the nucleus accumbens (NAcc). Implementation of fast-scan cyclic voltammetry (FSCV) confirms the ability of cannabinoids to augment DA within the NAcc on a subsecond timescale. The use of FSCV along with newly developed highly selective pharmacological compounds advances our understanding of how cannabinoids influence DA transmission and highlights a role for endocannabinoid-modulated subsecond DAergic activation in the incentive motivational properties of not only external, but also internal reward-predictive cues. For example, our laboratory has recently demonstrated that in mice responding under a fixed-interval (FI) schedule for food reinforcement, fluctuations in NAcc DA signal the principal cue predictive of reinforcer availability – time. That is, as the interval progresses, NAcc DA levels decline leading to accelerated food seeking and the resulting characteristic FI scallop pattern of responding. Importantly, administration of WIN 55,212-2, a synthetic cannabinoid agonist, or JZL184, an indirect cannabinoid agonist, increases DA levels during the interval and disrupts this pattern of responding. Along with a wealth of other reports, these results illustrate the role of cannabinoid receptor activation in the regulation of DA transmission and the control of temporally guided reward seeking. The current review will explore the striatal beat frequency model of interval timing as it pertains to cannabinoid signaling and propose a neurocircuitry through which this system modulates interoceptive time cues.
Introduction
A wealth of psychology research has documented an integral role for environmental stimuli in guiding reward seeking behavior. Stimuli that repeatedly occur in conjunction with the presentation of reinforcers (for the sake of simplicity, “rewards”), themselves gain incentive value as reward predictors and work to motivate behavior (). For example, the neutral auditory stimulus of a can of cat food being opened, through its repeated pairing with food delivery, serves as an incentive stimulus to the cat that is predictive of food-related stimuli (e.g., taste) and energizes the cat’s approach toward the food bowl. Of course, external motivational cues (e.g., sound of the can opener) frequently interact with internal cues (e.g., hunger) to guide behavior – i.e., if the cat is not hungry the likelihood that it will approach the food bowl is greatly reduced (, ). Further, through repeated pairing external cues may gain the ability to elicit internal cues, such as hunger () or the initiation of an internal clock that works to predict reward availability (). While conditioned environmental cues guide advantageous instrumental behaviors, they also may support the development of detrimental behaviors such as drug abuse. Indeed, cues frequently paired with drug use (e.g., drug paraphernalia) develop incentive value that in turn promotes drug seeking and contributes to the relapse [see review in Ref. ()]. Given the formidable influence of incentive cues on both positive and negative behaviors, it is important to better understand the neurobiological mechanisms subserving cue-driven behaviors. One system repeatedly implicated in incentive motivational processes is the mesolimbic dopamine (DA) system ().
DAergic cell bodies resident to the ventral tegmental area (VTA) send their diffuse projections to various cortical and limbic regions such as the prefrontal cortex, amygdala, hippocampus, and the ventral striatum (nucleus accumbens, NAcc) (). Together, this network comprises the mesolimbic DA system, a system that is highly implicated in the development and maintenance of reward seeking behaviors. A wide body of evidence supports a role for mesolimbic DA in reinforcement learning and motivation for incentive stimuli (–). For instance, natural reinforcers such as food and water, as well as drugs of abuse and brain stimulation reward (BSR), support operant behaviors through their ability to activate the mesolimbic system (–). Evidencing this view, DAergic lesions or antagonism attenuate approaches toward, or responding for, these reinforcers (–).
Single-unit recording data show that VTA DAergic neurons fire in two distinct modes: low-frequency (1–5 Hz) tonic activity and high-frequency (≥20 Hz) phasic activity, the latter of which is characterized by transient rapid bursts (<1 s) of cell firing (). In the absence of salient stimuli midbrain DA neurons exhibit tonic pacemaker activity producing a steady DAergic “tone” on high-affinity inhibitory D2-like (D2, D3, D4) DA receptors of the mesolimbic system (–). This baseline DAergic tone is believed to facilitate long-term depression (LTD) at cortico-striatal synapses and suppress activity of the basal ganglia indirect pathway (, ). The presentation of motivationally relevant stimuli such as primary rewards, however, results in rapid burst firing of midbrain DA cells, which increases terminal DA sufficiently to occupy low-affinity excitatory D1-like (D1 and D5) receptors (). D1 receptor activation following reward-related stimuli is proposed to result in enhanced long-term potentiation (LTP) at excitatory synapses and activation of the basal ganglia direct pathway, thereby motivating behavior (). Therefore distinct patterns of DAergic cell activity provide a mechanism through which high- and low-affinity DA receptor populations may be differentially activated resulting in the conveyance of distinct reward-related information.
Interestingly, DA neurons adapt to reward presentations by signaling the difference in value of “expected” versus “received” rewards, or a reward prediction error (, ). In support of this theory, the presentation of an unexpected reward, such as reinforcer delivery in the initial stages of a conditioning paradigm, results in burst firing of midbrain DA neurons. Following repeated presentations, however, this phasic DA signal previously coupled to reward receipt now results from presentation of reward-predictive stimuli that precede reward delivery (, ). The magnitude of burst activity is greater to the reward-predictive cues when the probability of reward is high, but when the probability of reward is low DAergic cell activity is greater during reward receipt. Conversely, midbrain DA neurons cease their firing when no reward or an aversive stimulus is delivered, communicating a negative reward prediction error (). It should be mentioned that non-appetitive auditory, tactile, or visual sensory stimuli can result in burst firing of midbrain DA cells (–), however, these cells appear to fire preferentially to reward-related stimuli (). Thus, phasic activation of midbrain DA neurons transmits information about previous (expectancy) and current reward situations, making this form of signaling particularly important to the development of conditioned reward associations (, ). Indeed, Zweifel et al. () reported that genetic inactivation of N-methyl-d-aspartate (NMDA) glutamate receptors on DA neurons, a treatment that blocks the ability of DA neurons to burst fire, attenuates stimulus-response learning.
Measurement of Extracellular Dopamine Concentrations within the NAcc
While electrophysiological recordings provide valuable information about DAergic cell activity patterns, the relationship between DA cell firing and neurotransmitter release at terminal regions is not linear (). Therefore, techniques that allow for the measurement of extracellular DA concentrations within discrete structures are critical to evaluate functional roles of regional DA release.
Tonic DA levels can be measured using in vivo microdialysis techniques, allowing for neurochemical analysis of brain dialysate with a temporal resolution of minutes [(), for review see Ref. ()]. A wealth of microdialysis data correlate reward-related phenomena with enhanced DA levels at mesolimbic terminal regions, such as the NAcc. For example, DA levels are elevated in target regions of the mesolimbic system following self-administration of either food (, , ), water (), or drugs of abuse (–). However, a sample rate of minutes is insufficient to disentangle DA release related to reward receipt versus cue-evoked DA. Direct assessment of subsecond fluctuations in DA concentration due to phasic firing requires the use of techniques with greater temporal resolution, such as fast-scan cyclic voltammetry (FSCV). FSCV has consistently been utilized to measure subsecond transient changes in DA concentration within distinct brain areas [for review see Ref. ()] of both anesthetized () and behaving animals (, ). However, FSCV cannot readily differentiate between norepinephrine and DA signals. Thus, voltammetric assessment of phasic DA activity is best suited for regions with low noradrenergic input, i.e., the NAcc.
Research employing FSCV demonstrates that stimuli promoting burst activity of DA neurons also produce transient increases in extracellular DA concentration (termed “transients”) at terminal fields of the mesolimbic system. For example, several studies show enhanced DA transient activity within the NAcc coincident with the presentation of a food reward or related reward-predictive cues (–) – stimuli known to result in phasic burst firing of midbrain DA neurons (, , ). Importantly, a wide body of FSCV data support a role for reward-evoked striatal DA as a reward prediction error signal. Indeed, enhanced phasic DA transmission is reliably observed following unexpected reward delivery or, after conditioning, in response to cues that predict reward (, , , , –). Further, in congruence with electrophysiological data, reward omission or administration of an aversive stimulus results in decreased extracellular DA within the ventral striatum (–).
Shifts in midbrain DA neuron activation from tonic low-frequency activity to phasic high-frequency burst firing likely result from changes in synaptic input from glutamate and gamma-aminobutyric (GABA) afferents to VTA DA cells. The VTA receives excitatory afferents from both sensory and cognitive regions, including glutamatergic afferents from the prefrontal cortex, the extended amygdala, and the laterodorsal and pedunculopontine tegmental nuclei (–) and inhibitory GABAergic input from the basal ganglia and rostromedial tegmental nucleus. DAergic neurons in brain slice preparations (i.e., without afferent input) exhibit pacemaker-like tonic activation but do not fire in bursts, thus DA cells are “conditional” rather than “intrinsic” bursters (, ). Indeed, burst firing of DA neurons requires glutamatergic input and the activation of DAergic cell NMDA glutamate receptors (, ). Conversely, GABAergic input to midbrain DA neurons dampens burst firing and returns the cell to baseline pacemaker-like activity (). Thus, the maintenance of midbrain DAergic firing patterns requires a balance between excitatory and inhibitory VTA afferent signals. A key signaling network implicated in the maintenance of this balance is the endocannabinoid system.
A Brief Overview of the Endocannabinoid System
The endocannabinoid system, composed of endogenous cannabinoids (i.e., endocannabinoids), cannabinoid receptors, and the enzymes responsible for endocannabinoid synthesis and degradation, is a neuromodulatory network known to play a role in a number of neural processes, including learning and memory, motivation, reward, operant behavior, and neuroplasticity (–). Cannabinoid receptors were the first components of this system to be discovered. In the early 1990s, Δ9-tetrahydrocannabinol (THC), the primary psychoactive constituent of the cannabis plant, was found to produce its characteristic effects as a partial agonist of a G-protein-coupled receptor (GPCR) (Gi/o) isolated from neural cell lines and later named cannabinoid receptor type 1 (CB1) (, ). A few years after this discovery, a second cannabinoid receptor (cannabinoid receptor type 2; CB2) was identified (). CB1 and CB2 receptors differ in anatomical distribution as well as function. Autoradiography studies show that CB1 is the primary cannabinoid receptor of the central nervous system (CNS) with a wide distribution throughout the brain and periphery and the highest concentrations of CB1 binding found in brain regions implicated in the actions of cannabis (–). Conversely, CB2 is more abundant in the periphery and expressed primarily in immune cells, including microglia of the CNS (), and is thus believed to primarily play a role in immune function (). Recent evidence, however, also supports a role for CB2 in a variety of neurological processes, such as anxiety, pain, and addiction (–). It is important to note that while this review will focus on activity at CB receptors, endocannabinoids also interact with various ligand-gated ion channels (e.g., vanilloid receptor type 1 channels) as well as other GPCRs, such as GPR55 (, ).
The discovery of cannabinoid receptors was followed shortly after by the identification of their primary endogenous ligands – N-arachidonylethanolamine (anandamide; AEA), a partial agonist at CB1 receptors, and 2-arachidonylglycerol (2-AG), a full agonist at both CB1 and CB2 receptors (–). The biosynthesis of AEA is not fully understood, although it is generally agreed that AEA is synthesized from N-arachidonoyl phosphatidylethanolamine (NAPE) in a Ca2+-dependent manner via one of the several possible enzymatic pathways (, ). Conversely, both Ca2+-dependent and Ca2+-independent synthesis pathways for 2-AG have been outlined (illustrated in Figure 1). Following synthesis and release, AEA and 2-AG signaling is quickly terminated through cellular reuptake and hydrolysis primarily by the enzymes fatty acid amide hydrolase (FAAH) and monoacylglycerol lipase (MAGL), respectively [FAAH can also hydrolyze 2-AG ()]. While several additional endocannabinoids have since been discovered, AEA and 2-AG remain the best characterized.
Figure 1
The most prominent physiological role for endocannabinoids is as synaptic retrograde messengers – molecules that transmit messages from post- to presynaptic cells. Indeed, both AEA and 2-AG signal retrogradely. Like all known endocannabinoids, AEA and 2-AG are lipid molecules, which in contrast to classic neurotransmitters, are synthesized and released from neurons “on demand” upon stimulation (, ). These lipophilic messengers diffuse through the postsynaptic membrane and interact with cannabinoid receptors of nearby cells. Both CB1 and CB2 receptors are Gi/o-coupled receptors; therefore, their activation results in a decrease in cAMP activity within the cell and subsequent inhibition of neurotransmitter release, resulting in negative feedback to presynaptic cells (–). When Ca2+-mediated, this process has been termed depolarization-induced suppression of inhibition (DSI) or excitation (DSE) depending on the neurotransmitter system being inhibited (), and works to modulate synaptic plasticity. Research on the individual functions of AEA and 2-AG suggests that 2-AG is the principal endocannabinoid involved in DSI- and DSE-induced plasticity ().
Endocannabinoid Modulation of Dopamine Transmission
Like the discovery of the endocannabinoid system, the ability of endocannabinoids to modulate mesolimbic DA transmission was uncovered through investigations into the effects of THC. All drugs of abuse increase DA neurotransmission in the NAcc (, ) and although some early studies exploring a role for DA in cannabinoid abuse potential yielded incongruent results [e.g., Ref. (, )], today a large body of evidence suggests that marijuana is no exception. Indeed, cannabinoid administration enhances extracellular DA concentrations in the ventral striatum (–). Further, this effect is dependent on CB1 receptor signaling, as pretreatment with the CB1 receptor antagonist/inverse agonist SR141716A (rimonabant) blocks the ability of THC, or the synthetic cannabinoid receptor agonist WIN 55,212-2 (WIN), to enhance striatal DA levels (). Seminal single-unit recording data from French et al. () show that cannabinoids enhance extracellular DA concentrations in the NAcc through increasing both the baseline firing rates and burst frequency of midbrain DA neurons. These enhancements in VTA DA cell firing are also CB1-dependent as they are attenuated by rimonabant ().
Interestingly, while midbrain DA neurons release endocannabinoids during phasic activation, they do not express CB1 receptors (, , , ). This suggests that cannabinoids excite VTA DA cells via an indirect mechanism. Aside from DAergic cell bodies, the VTA also contains GABAergic neurons that inhibit midbrain DA activity through interaction with GABAA receptors on DA cells (). The application of the GABAA agonist bicuculine to VTA-containing slices enhances DAergic cell activity (). Thus, cannabinoids may increase DA neuron burst firing through the inhibition of VTA GABA cells, resulting in disinhibition of midbrain DA neurons (, ). In support of this explanation, Szabo et al. () found that WIN reduces electrically evoked GABAA-mediated inhibitory postsynaptic currents in DA neurons of VTA slices, and these effects are blocked by rimonabant. These data led Lupica and Riegel (, ) to propose a model of endocannabinoid-dopamine system interaction wherein enhanced activation of VTA DA neurons promotes release of endocannabinoids, which then activate presynaptic CB1 receptors on GABA terminals, resulting in DSI (illustrated in Figure 1). In line with this model, rimonabant administration attenuates the typical enhancement of DA transient concentrations in the NAcc seen following cocaine administration ().
The Role of Endocannabinoids in Cue-Motivated Behaviors
As discussed above, burst firing of DAergic neurons plays an integral role in stimulus-response learning (, , , ). Therefore, given the well-documented ability of endocannabinoids to modulate phasic DA signaling, it stands to reason that endocannabinoids are also involved in modulating incentive motivation. Much research utilizing cue-induced reinstatement of operant behaviors illustrates the involvement of the endocannabinoid system in various aspects of cue-induced responding. In this model, an established operant behavior is extinguished and then reinstated following the presentation of stimuli previously paired with reinforcer availability. Thus incentive cues work to reinvigorate reward-seeking in the absence of reward. Utilization of this model shows that while systemic administration of rimonabant does not affect operant responding for palatable stimuli (), it attenuates cue-induced reinstatement of food-seeking behavior (–). Given that rimonabant also blocks the development of conditioned place preference for food (), these data suggest that endocannabinoid signaling at CB1 receptors modulates the incentive value of food-associated stimuli. Indeed, the CB1 receptor antagonist AM251 attenuates cue-maintained responding for food under a second-order schedule of reinforcement (). These effects do not seem to be reinforcer specific as endocannabinoid signaling is critical for cue-induced reinstatement of drug-seeking behavior. Systemic rimonabant attenuates cue-induced reinstatement of cocaine (), heroin (), methamphetamine (), alcohol (), nicotine (), and THC (). Further, the effects of CB1 antagonism on cue-induced reinstatement of reward seeking may be dependent on DAergic mechanisms, as DA antagonism also blocks cue-induced reinstatement of reward seeking behavior (, ).
In recent research from our laboratory, Oleson et al. () employed an intracranial self-stimulation (ICSS) task along with FSCV to investigate endocannabinoid-mediated disinhibition of cue-evoked DA. In this procedure, a light and tone cue signaled reinforcer availability and each operant lever press resulted in the delivery of electrical BSR to the VTA. This work replicated previous findings showing that over the course of operant training as task performance improves, NAcc DA transients time lock to cues that predicted reward (in this case BSR) availability (). However, either intravenous (i.v.) or intra-VTA delivery of rimonabant dose-dependently increased response latency while simultaneously disrupting cue-evoked DA transients within the ventral striatum, supporting a role for specifically midbrain DAergic activity in the encoding of reward-related cues. Further, similar results were found in rats responding for food reward, suggesting that the involvement of endocannabinoids in cued responding is not reinforcer specific. Next, URB597, a FAAH inhibitor, and JZL184, an inhibitor of MAGL, were utilized to increase levels of either AEA or 2-AG, respectively. While pretreatment with URB597 (i.v.) had no effect on cued ICSS responding, both i.v. and intra-VTA administration of JZL184 decreased response latency and enhanced cue-evoked accumbal DA transmission. Further, the effects of JZL184 on ICSS responding and DAergic transmission were blocked by pretreatment with a sub-threshold dose of rimonabant, suggesting efficacy through a CB1-dependent mechanism. Taken together, these data indicate that endocannabinoids, specifically 2-AG, modulate DAergic encoding of environmental cues to control reinforcement-directed behaviors.
Endocannabinoids and Time as a Discriminative Cue
While the perception and processing of external environmental stimuli directs reward-seeking behaviors, organisms also rely on interoceptive cues (e.g., hunger or thirst) in deciding how to interact with their environment. One such internal signal, which has recently received a great deal of attention, is time estimation. Indeed, organisms rely on internal “biological clocks” to coordinate behaviors from the microsecond processing of fluid movements to the daily rhythms of the sleep–wake cycle. Of particular relevance to reward-motivated behaviors is the timing of intervals in the seconds-to-minutes range involved in a number of fundamental behaviors such as reward seeking and decision making (). Like the processing of external reward-predictive stimuli, internal processing of temporal information is mediated by DAergic systems. Disorders that result in disruption of DA function, such as Parkinson’s disease (, ) or Huntington’s disease (), or the administration of DA antagonists (e.g., haloperidol) slows the internal clock resulting in the perception that time is passing much faster (in comparison to internal temporal representations) and consequent overestimation of interval time (–). Conversely, disorders associated with augmented DA levels [e.g., schizophrenia ()], or the administration of drugs that agonize DAergic signaling (e.g., cocaine and amphetamine) speeds up the internal clock leading to the perception that time is passing more slowly and resulting in underestimation of interval time (–). Similarly, cannabis users report a slowing of the subjective experience of time (, ), presumably related to the ability of cannabinoids to enhance DA transmission. These findings have been replicated in animals with both THC and WIN administration decreasing time sensitivity in both temporal discrimination () and estimation () tasks. Importantly, Han and Robinson () found that administration of rimonabant disrupts interval estimation and delays operant responding, suggesting a role for endocannabinoids in interval timing.
Oleson et al. () utilized a fixed-interval (FI) schedule of food reinforcement to uncover the role of endocannabinoid modulation of phasic DA signaling in interval timing. In FI schedules, operant behaviors are reinforced on the basis of time (). These schedules are known to produce a behavioral pattern known as an FI “scallop,” wherein rates of responding accelerate over the course of the interval until reaching a peak response rate just before reward delivery (). In this investigation, Oleson et al. () showed that phasic DA release in the mouse NAcc is inversely related to interval time; i.e., the start of the interval is characterized by a high frequency of phasic DA release events (resulting in enhanced DA concentration) which then gradually decrease in frequency as the interval continues, finally reaching a DA concentration minimum at interval terminus. These data thus support a role for DA in encoding of the principal cue predicting reinforcer availability during FI schedules – time. The endocannabinoid system was subsequently shown to modulate these effects as systemic administration of WIN dose-dependently increased the pattern of DA release and accelerated the temporal pattern of responding. These results were mimicked by intraperitoneal (i.p.) administration of JZL184, but not by i.p. URB597. Further, the effects of JZL184 were CB1-dependent as pretreatment with AM251 blocked 2-AG-induced increases in DA concentration as well as elevations in response rate and thus normalized behavior to the typical FI scallop response pattern. Although both DAergic and endocannabinoid systems have been independently implicated in the temporal control of behavior (, , ), these data represent the first report showing how phasic striatal DA may work to signal interval duration and the crucial role for endocannabinoid signaling in the encoding of this interoceptive time cue.
Oleson et al. () posit that the high DA concentrations seen at the start of the interval and the low DA concentrations observed at interval terminus, promote reinforcement-driven motivation resulting in the initiation of regulated operant responding and increased lever pressing, respectively. Conversely, moderate levels of DA, characteristic of the middle of the interval, promote engagement in adjunctive behaviors – behaviors that do not result in reinforcement delivery, measured as inactive lever presses. Their data align well with current theories on basal ganglia function (). These theories suggest that high concentration DA surges arriving in the NAcc activate D1 receptors on medium spiny neurons (MSNs) comprising the direct pathway and promote action sequences (e.g., lever pressing). Baseline moderate concentration DA signals, however, are believed to activate the indirect pathway through interaction with D2 receptors on MSNs and work to inhibit primary reward-directed action sequences in favor of alternative, perhaps exploratory, adjunctive behaviors (, ). Thus, fluctuations in NAcc DA concentration direct reward-related behavior, likely through the modulation of striatal afferent inputs (, ). Enhancement of CB1 activation through administration of WIN or JZL184 increased both NAcc DA concentration and response rate, suggesting that activation of the endocannabinoid system drives direct pathway activation and primary reward seeking. Interestingly, both enhancement of 2-AG transmission (with JZL184) and disruption of CB1 activation (with AM251) attenuated adjunctive behaviors, supporting a role for the endocannabinoid system, not only in the direction of primary-reward driven behaviors governed by environmental cues but also the directions of adjunctive behaviors when environmental cues dictate that reward is not available. However, in opposition to this view, a recent report by Cui et al. () suggests a departure from the classical interpretation of basal ganglia function and supports a role for MSNs of both the direct and indirect pathway in action initiation. In this investigation, Cui et al. () utilized Cre-dependent viral expression of genetically encoded calcium indicators in transgenic mice along with time-correlated single photon counting to individually quantify D1-expressing and D2-expressing striatal MSN activation during an operant lever pressing task for food. They found that MSNs of both pathways were transiently activated just prior to the initiation of contralateral movements and quiescent during periods when the animal was not moving, suggesting that activation of both the direct and the indirect pathway promote behavioral output. Therefore, it may be that over a fixed time interval, fluctuation in extracellular DA preferentially excites individual cells within both pathways, which work together to coordinate either primary reward seeking or adjunctive behaviors during FI schedules.
The Striatal Beat Frequency Model and Endocannabinoid Modulation of Timing
The question remains, however, how does the DAergic system signal the occurrence of a distinct temporal window in order to represent an interoceptive time cue? One convincing model on the neurobiology of interval timing is the striatal beat frequency (SBF) model (, ). SBF postulates that cortico-striatal circuits encode interval durations of seconds to minutes, and these circuits are coordinated by midbrain DAergic input. Within the frontal cortex, neurons oscillating in the alpha range (8–13 Hz) act as an internal clock (). At interval onset, the presentation of a distinct conditioned stimulus results in phasic firing of midbrain DA neurons and these transient surges of extracellular DA synchronize oscillating neurons in the frontal cortex, likely through inhibition of desynchronized cells (). However, briefly after synchronization, cortical neurons begin to fall out of phase with one another, returning to their inherent individual periodicities. Thus, distinct interval durations are marked by unique patterns of neuronal ensembles firing in-phase. These cortical oscillators synapse onto MSNs of the striatum that function as “coincidence detectors” – connecting distinct patterns of oscillator activity with the occurrence of external stimuli (e.g., reward delivery). Striatal MSNs are uniquely situated to detect coincident neuronal activity with each MSN receiving input from 10,000 to 30,000 different thalamic and cortical neurons (). Further, striatal MSNs exhibit both highly polarized “down” states (−90 mV) and less polarized “up” states (approximately −60 mV) () with transitions from down to up states requiring either VTA DA input (, ) or excitatory glutamatergic input from other cortical or subcortical structures (, ). High levels of DAergic input to the striatum at interval onset are hypothesized to “clear out” irrelevant information within the coincidence detector by hyperpolarizing striatal cells into their down state (). Conversely, phasic surges of extracellular DA within the striatum at reward delivery bring striatal cells into their up state and promote LTP at active cortico-striatal synapses (, , ). Therefore, the pattern of cortical inputs spiking at the time of reinforcement, which represents a unique population code for the time elapsed since interval initiation, will undergo Hebbian strengthening. LTP at these striatal synapses allows the organism to learn specific interval durations and initiate reward seeking when a matching pattern of cortical efferent activity is encountered.
While the SBF model represents a neurobiologically plausible framework within which to examine interval timing, there are inconsistencies in this model. For example: how does phasic DA at cue onset hyperpolarize striatal cells given that D1 stimulation is excitatory (i.e., Gs-coupled)? One possibility is through collateral inhibition wherein D1-mediated excitation in specific MSNs leads to a net inhibition of striatal cells through a lateral inhibitory feedback network (–); however, this has yet to be explored within interval timing tasks. Further, there has been no direct voltammetric assessment of striatal DA levels and consequent induction of striatal LTP mechanisms.
The voltammetric data presented by Oleson et al. () lend support to the SBF model. In their investigation, extracellular DA is high at the start of the interval, providing a mechanism through which NAcc cells may be hyperpolarized (perhaps through collateral-driven lateral inhibition) and the coincidence detector reset. As the interval progresses DA levels gradually decrease, likely releasing striatal cells from collateral feedback inhibition and allowing for DA transient-induced cortico-striatal LTP. It remains unclear, however, how DA levels gradually decrease as the interval continues. This may occur through striatal cell ramping activity. Indeed, a subset of NAcc neurons display a ramping activity pattern during interval estimation wherein firing rates linearly increase from CS presentation and peak at the time of reward expectation (, ). The accumbens sends direct inhibitory input to the VTA (), thus ramping activity may result in progressive DA decline from CS presentation (). Data from Oleson et al. (), however, do not determine if NAcc DA activity is integral for interval estimation, but, rather, provide evidence for a correlation between accumbal phasic DA activity and interval estimation. Future investigations are required to determine if phasic NAcc DA release is required for interval estimation.
The SBF model suggests a specific role for the dorsal striatum in temporal processing, citing the ability of dorsal, but not ventral, striatal lesions to impair temporal control (, ). However, lesions of the NAcc core disrupt timing of Pavlovian responses, as evidenced by decreased approach to a food receptacle at CS+ presentation (). Further, while Galtress and Kirkpatrick () found that accumbal lesions do not disrupt the tracking of temporal windows in a peak-interval (PI) timing procedure, animals do exhibit a decreased ability to modify behavior when an expected reward is not delivered at interval terminus. PI is an extension of an FI schedule with the addition of non-reinforced probe trials which result in Gaussian response curves characterized by increased operant responding up to the point of expected reward followed by a gradual decrease in responding. Thus, the NAcc core likely functions to integrate temporal cues specifically with reward value and availability. Given that responding during an FI combines both temporal estimation and expectations regarding reinforcer value, the role of the NAcc core in operant responding during FI schedules of reinforcement merits more examination. Finally, it should be noted that while recordings of phasic NAcc DA activity support the SBF model, no voltammetric recordings during FI responding have been taken in the frontal cortex due to the high levels of cortical noradrenergic innervation. However, recent optogenetic investigations show that disruption of D1 receptor transmission within the prefrontal cortex impairs performance on an FI task (), supporting an integral role for phasic DA within the frontal cortex in interval timing.
The ability of cannabinoids, as well as other drugs that augment DAergic signaling, to enhance internal clock speed has been well documented (–), however, the neurobiological mechanisms underlying this effect remains unclear. Within the framework of the SBF model, enhancement of phasic DA following cannabinoid administration may affect time perception through agonizing DA transmission within the striatum. Indeed, selective manipulation of DA levels within the ventral striatum disrupts performance in timing-dependent operant tasks (–). Further, direct administration of DA into the NAcc enhances internal clock speed (). Increased phasic DAergic activity in the NAcc core, as seen following WIN administration (), may result in induction of LTP at cortico-striatal synapses that are active much earlier in the interval than those active at reinforcer delivery. This abnormal “stamping in” of premature interval estimations would thus promote reward seeking prior to interval terminus, likely through activation of the basal ganglia’s direct pathway [but see Ref. ()] (Figure 2). However, future investigations are necessary to determine if cortico-striatal LTP adheres to specific patterns during interval estimation tasks, and examine how these patterns are changed following DAergic agonist administration.
Figure 2
A greater understanding of the role of phasic DA in interval timing is integral to the study of drug addiction. Individuals that are more sensitive to the time-altering effects of drug administration are also more sensitive to the experience of stimulant-induced euphoria, suggesting that similar brain pathways maintain internal clock speed and drug reward (). Indeed, drugs of abuse increase extracellular DA within the ventral striatum and have the ability to hasten internal clock speed. Therefore, augmentation of internal clock representation may underlie a path through which drugs alter stimulus-reward associations and promote inappropriate reward seeking, such as that seen in delay discounting paradigms. Delay discounting is a maladaptive decision-making strategy characteristic to addiction wherein individuals show a preference for smaller/immediate over larger/delayed rewards. This temporal shift in reward seeking is generally considered an indication of impulsivity, but one could also imagine delay discounting to result from augmentation of internal clock representations. Certainly, a number of human studies indicate a positive correlation between substance abuse, including marijuana abuse, and measures of delay discounting (–). Investigations into the neurobiology of this phenomenon implicate alterations in striatal DA activity (, ), suggesting a link between drug-induced enhancement of phasic DA signaling and temporally biased reward seeking. Ostlund et al. () showed that repeated cocaine exposure enhances phasic DA transmission and increases cue-evoked food seeking. Thus, enhanced accumbal DA in response to reward-predictive cues following drug use, may, through interaction with the proposed SBF timing neurocircuitry, accelerate the internal clock and promote the choice of immediate over delayed rewards. Importantly, Hernandez et al. () showed that systemic pretreatment with rimonabant attenuates cocaine-induced delay discounting. These findings support a role for endocannabinoid-modulated enhancement of phasic DA transmission following drug use and subsequent temporal shifts in reward seeking resulting from an enhancement of internal clock speed. However, it remains unclear if decision making during delay discounting paradigms occurs within the same timescale as that of interval estimation, or relies on strategies adopted prior to task onset.
Conclusion
A wide body of evidence supports a role for endocannabinoid modulation of phasic midbrain DAergic activity. Phasic burst activation of DA neurons can be measured as transient fluctuations of extracellular DA in terminal regions of the mesolimbic system (e.g., the NAcc) using FSCV. In congruence with reward prediction error, following repeated stimulus-reward pairings, reward-predictive cues result in burst firing of mesolimbic DA neurons and transient increases in NAcc DA levels. This transient burst of striatal DA likely promotes maintenance of reward-seeking behaviors through activation of the basal ganglia pathways. In addition to tracking of external reward-related cues, phasic changes in striatal DA encode interoceptive cues, such as interval time that allow for the coordination of goal-directed responding. In support of this view, drugs that enhance striatal DA levels also increase individuals’ internal clock thereby resulting in the perception that time is passing more slowly. Further, animal studies show that administration of the CB1/CB2 agonist WIN or the 2-AG degradation inhibitor JZL184 enhances NAcc core DA levels and promotes premature reward seeking in a FI task. The precise neurobiological mechanism(s) through which these effects occur, however, remains unknown. The SBF model of interval timing provides a unique framework with which to examine the role of phasic DA in interval timing. SBF posits that striatal DA fluctuations mediate interval timing through selectively promoting LTP at cortico-striatal synapses active at specific interval durations. Thus, DAergic disruption of interval timing may occur through aberrant induction of LTP at cortico-striatal synapses representative of premature interval lengths. Given the ability of drugs of abuse to potently augment NAcc DA levels, it is not surprising that drug administration also disrupts interval estimation. Alterations in interval timing may also underlie addiction-related behaviors such as delay discounting, which is enhanced by endocannabinoid-mediated increases in striatal DA. A conserved mechanism in interval timing and impulsive choice suggests that following drug use, enhanced delayed discounting is consequential to augmentation of one’s internal clock, which results in temporal-biasing of reward-seeking at the presentation of reward-related cues.
Statements
Acknowledgments
The authors wish to thank Dr. Erik Oleson for the preparation of Figure 1.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
References
1
BindraD. Neuropsychological interpretation of the effects of drive and incentive motivation on general activity and instrumental behavior. Psychol Rev (1968) 75:1–22.10.1037/h0025306
2
ToatesF. Motivational Systems. Cambridge: Cambridge University Press (1986).
3
ToatesF. The interaction of cognitive and stimulus-response processes in the control of behaviour. Neurosci Biobehav Rev (1998) 22(1):59–83.10.1016/S0149-7634(97)00022-5
4
RodinJ. Current status of the internal-external hypothesis for obesity: what went wrong?Am Psychol (1981) 36(4):361–72.10.1037/0003-066X.36.4.361
5
FersterCBSkinnerBF. Schedules of Reinforcement. New York: Appleton-Century-Crofts (1957).
6
ShahamYShalevULuLDe WitHStewartJ. The reinstatement model of drug relapse: history, methodology and major findings. Psychopharmacology (2003) 168(1–2):3–20.10.1007/s00213-002-1224-x
7
BerridgeKCRobinsonTE. What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience?Brain Res Rev (1998) 28(3):309–69.10.1016/S0165-0173(98)00019-8
8
SwansonLW. The projections of the ventral tegmental area and adjacent regions: a combined fluorescent retrograde tracer and immunofluorescence study in the rat. Brain Res Bull (1982) 9(1–6):321–53.10.1016/0361-9230(82)90145-9
9
BerridgeKC. Liking’ and ‘wanting’ food rewards: brain substrates and roles in eating disorders. Physiol Behav (2009) 97(5):537–50.10.1016/j.physbeh.2009.02.044
10
IkemotoS. Dopamine reward circuitry: two projection systems from the ventral midbrain to the nucleus accumbens-olfactory tubercle complex. Brain Res Rev (2007) 56(1):27–78.10.1016/j.brainresrev.2007.05.004
11
TaberKHBlackDNPorrinoLJHurleyRA. Neuroanatomy of dopamine: reward and addiction. J Neuropsychiatry Clin Neurosci (2012) 24(1):1–4.10.1176/appi.neuropsych.24.1.1
12
WiseRARomprePP. Brain dopamine and reward. Annu Rev Psychol. (1989) 40:191–225.10.1146/annurev.ps.40.020189.001203
13
Di ChiaraGBassareoVFenuSDe LucaMASpinaLCadoniCet alDopamine and drug addiction: the nucleus accumbens shell connection. Neuropharmacology (2004) 47(Suppl 1):227–41.10.1016/j.neuropharm.2004.06.032
14
HernandezLHoebelBG. Food reward and cocaine increase extracellular dopamine in the nucleus accumbens as measured by microdialysis. Life Sci (1988) 42(18):1705–12.10.1016/0024-3205(88)90036-7
15
HernandezLHoebelBG. Feeding and hypothalamic stimulation increase dopamine turnover in the accumbens. Physiol Behav (1988) 44(4–5):599–606.10.1016/0031-9384(88)90324-1
16
HoebelBGHernandezLSchwartzDHMarkGPHunterGA. Microdialysis studies of brain norepinephrine, serotonin, and dopamine release during ingestive behavior. Theoretical and clinical implications. Ann N Y Acad Sci. (1989) 575:171–91.10.1111/j.1749-6632.1989.tb53242.x
17
YoshidaMYokooHMizoguchiKKawaharaHTsudaANishikawaTet alEating and drinking cause increased dopamine release in the nucleus accumbens and ventral tegmental area in the rat: measurement by in vivo microdialysis. Neurosci Lett (1992) 139(1):73–6.10.1016/0304-3940(92)90861-Z
18
EttenbergACampCH. A partial reinforcement extinction effect in water-reinforced rats intermittently treated with haloperidol. Pharmacol Biochem Behav (1986) 25(6):1231–5.10.1016/0091-3057(86)90117-6
19
EttenbergACampCH. Haloperidol induces a partial reinforcement extinction effect in rats: implications for a dopamine involvement in food reward. Pharmacol Biochem Behav (1986) 25(4):813–21.10.1016/0091-3057(86)90117-6
20
SalamoneJDCorreaMMingoteSWeberSM. Nucleus accumbens dopamine and the regulation of effort in food-seeking behavior: implications for studies of natural motivation, psychiatry, and drug abuse. J Pharmacol Exp Ther (2003) 305(1):1–8.10.1124/jpet.102.035063
21
ZisAPFibigerHC. Neuroleptic-induced deficits in food and water regulation: similarities to the lateral hypothalamic syndrome. Psychopharmacology (1975) 43(1):63–8.10.1007/BF00437616
22
GraceAABunneyBS. The control of firing pattern in nigral dopamine neurons: burst firing. J Neurosci (1984) 4(11):2877–90.
23
CooperDC. The significance of action potential bursting in the brain reward circuit. Neurochem Int (2002) 41(5):333–40.10.1016/S0197-0186(02)00068-2
24
DreyerJKHerrikKFBergRWHounsgaardJD. Influence of phasic and tonic dopamine release on receptor activation. J Neurosci (2010) 30(42):14273–83.10.1523/JNEUROSCI.1894-10.2010
25
GraceAA. Regulation of spontaneous activity and oscillatory spike firing in rat midbrain dopamine neurons recorded in vitro. Synapse (1991) 7(3):221–34.10.1002/syn.890070307
26
GotoYGraceA. Dopaminergic modulation of limbic and cortical drive of nucleus accumbens in goal-directed behavior. Nat Neurosci (2005) 8(6):805–12.10.1038/nn1471
27
ShenWFlajoletMGreengardPSurmeierDJ. Dichotomous dopaminergic control of striatal synaptic plasticity. Science (2008) 321(5890):848–51.10.1126/science.1160575
28
GraceAFlorescoSBGotoYLodgeDJ. Regulation of firing of dopaminergic neurons and control of goal-directed behaviors. Trends Neurosci. (2007) 30(5):220–7.10.1016/j.tins.2007.03.003
29
RomoRSchultzW. Dopamine neurons of the monkey midbrain: contingencies of responses to active touch during self-initiated arm movements. J Neurophysiol (1990) 63(3):592–606.
30
SchultzW. Predictive reward signal of dopamine neurons. J Neurophysiol (1998) 80(1):1–27.
31
LjungbergTApicellaPSchultzW. Responses of monkey dopamine neurons during learning of behavioral reactions. J Neurophysiol (1992) 67(1): 145–63.
32
FreemanASMeltzerLTBunneyBS. Firing properties of substantia nigra dopaminergic neurons in freely moving rats. Life Sci (1985) 36(20):1983–94.10.1016/0024-3205(85)90448-5
33
FreemanASBunneyBS. Activity of A9 and A10 dopaminergic neurons in unrestrained rats: further characterization and effects of apomorphine and cholecystokinin. Brain Res (1987) 405(1):46–55.
34
HorvitzJC. Mesolimbocortical and nigrostriatal dopamine responses to salient non-reward events. Neuroscience (2000) 96(4):651–6.10.1016/S0306-4522(00)00019-1
35
RebecGVChristensenJRGuerraCBardoMT. Regional and temporal differences in real-time dopamine efflux in the nucleus accumbens during free-choice novelty. Brain Res (1997) 776(1–2):61–7.
36
WightmanRMRobinsonDL. Transient changes in mesolimbic dopamine and their association with ‘reward’. J Neurochem (2002) 82(4):721–35.10.1046/j.1471-4159.2002.01005.x
37
TsaiHZhangFAdamantidisAStuberGDBonciAde LeceaLet alPhasic firing in dopaminergic neurons is sufficient for behavioral conditioning. Science (2009) 324(5930):1080–4.10.1126/science.1168878
38
NicolaSM. The flexible approach hypothesis: unification of effort and cue-responding hypotheses for the role of nucleus accumbens dopamine in the activation of reward-seeking behavior. J Neurosci (2010) 30(49):16585–600.10.1523/JNEUROSCI.3958-10.2010
39
ZweifelLSParkerJGLobbCJRainwaterAWallVZFadokJPet alDisruption of NMDAR-dependent burst firing by dopamine neurons provides selective assessment of phasic dopamine-dependent behavior. Proc Natl Acad Sci USA. (2009) 106(18):7281–8.10.1073/pnas.0813415106
40
GarrisPAKilpatrickMBuninMAMichaelDWalkerQDWightmanRM. Dissociation of dopamine release in the nucleus accumbens from intracranial self-stimulation. Nature (1999) 398(6722):67–9.10.1038/18019
41
BitoLDavsonHLevinEMurrayMSniderN. The concentrations of free amino acids and other electrolytes in cerebrospinal fluid, in vivo dialysate of brain, and blood plasma of the dog. J Neurochem (1966) 13(11):1057–67.10.1111/j.1471-4159.1966.tb04265.x
42
WesterinkBH. Brain microdialysis and its application for the study of animal behaviour. Behav Brain Res (1995) 70(2):103–24.10.1016/0166-4328(95)80001-8
43
RadhakishunFSvan ReeJMWesterinkBH. Scheduled eating increases dopamine release in the nucleus accumbens of food-deprived rats as assessed with on-line brain dialysis. Neurosci Lett (1988) 85(3):351–6.10.1016/0304-3940(88)90591-5
44
ChurchWHJusticeJBByrdLD. Extracellular dopamine in rat striatum following uptake inhibition by cocaine, nomifensine and benztropine. Eur J Pharmacol (1987) 139(3):345–8.10.1016/0014-2999(87)90592-9
45
HurdYLWeissFKoobGFUngerstedtU. Cocaine reinforcement and extracellular dopamine overflow in rat nucleus accumbens: an in vivo microdialysis study. Brain Res (1989) 498(1):199–203.
46
HurdYLWeissFKoobGUngerstedtU. The influence of cocaine self-administration on in vivo dopamine and acetylcholine neurotransmission in rat caudate-putamen. Neurosci Lett (1990) 109(1–2):227–33.10.1016/0304-3940(90)90568-T
47
PettitHOJusticeJB. Dopamine in the nucleus accumbens during cocaine self-administration as studied by in vivo microdialysis. Pharmacol Biochem Behav (1989) 34(4):899–904.10.1016/0091-3057(89)90291-8
48
PettitHOJusticeJB. Effect of dose on cocaine self-administration behavior and DA levels in the nucleus accumbens. Brain Res (1991) 539(1): 94–102.
49
WeissFPaulusMPLorangMTKoobGF. Increases in extracellular dopamine in the nucleus accumbens by cocaine are inversely related to basal levels: effects of acute and repeated administration. J Neurosci (1992) 12(11):4372–80.
50
WiseRALeonePRivestRLeebK. Elevations of nucleus accumbens dopamine and DOPAC levels during intravenous heroin self-administration. Synapse (1995) 21(2):140–8.10.1002/syn.890210207
51
RobinsonDLVentonBJHeienMLWightmanRM. Detecting subsecond dopamine release with fast-scan cyclic voltammetry in vivo. Clin Chem (2003) 49(10):1763–73.10.1373/49.10.1763
52
MillarJStamfordJAKrukZLWightmanRM. Electrochemical, pharmacological and electrophysiological evidence of rapid dopamine release and removal in the rat caudate nucleus following electrical stimulation of the median forebrain bundle. Eur J Neurosci (1985) 109(3):341–8.
53
BudyginEAPhillipsPERobinsonDLKennedyAPGainetdinovRRWightmanRM. Effect of acute ethanol on striatal dopamine neurotransmission in ambulatory rats. J Pharmacol Exp Ther (2001) 297(1):27–34.
54
GarrisPAChristensenJRRebecGVWightmanRM. Real-time measurement of electrically evoked extracellular dopamine in the striatum of freely moving rats. J Neurochem. (1997) 68(1):152–61.10.1046/j.1471-4159.1997.68010152.x
55
BrownHDMcCutcheonJEConeJRagozzinoMERoitmanMF. Primary food reward and reward-predictive stimuli evoke different patterns of phasic dopamine signaling throughout the striatum. Eur J Neurosci (2011) 34(12):1997–2006.10.1111/j.1460-9568.2011.07914.x
56
FlagelSBClarkJRobinsonTEMayoLCzujAWilluhnI. A selective role for dopamine in stimulus-reward learning. Nature (2011) 469(7328):53–7.10.1038/nature09588
57
RoitmanMFStuberGDPhillipsPEWightmanRMCarelliRM. Dopamine operates as a subsecond modulator of food seeking. J Neurosci (2004) 24(6):1265–71.10.1523/JNEUROSCI.3823-03.2004
58
RoitmanMFWheelerRAWightmanRMCarelliRM. Real-time chemical responses in the nucleus accumbens differentiate rewarding and aversive stimuli. Nat Neurosci (2008) 11(12):1376–7.10.1038/nn.2219
59
SunsayCRebecGV. Real-time dopamine efflux in the nucleus accumbens core during Pavlovian conditioning. Behav Neurosci (2008) 122(2):358–67.10.1037/0735-7044.122.2.358
60
HylandBIReynoldsJNHayJPerkCGMillerR. Firing modes of midbrain dopamine cells in the freely moving rat. Neuroscience (2002) 114(2):475–92.10.1016/S0306-4522(02)00267-1
61
NishinoHOnoTMuramotoKFukudaMSasakiK. Neuronal activity in the ventral tegmental area (VTA) during motivated bar press feeding in the monkey. Brain Res (1987) 413(2):302–13.
62
NakazatoT. Striatal dopamine release in the rat during a cued lever-press task for food reward and the development of changes over time measured using high-speed voltammetry. Exp Brain Res (2005) 166(1):137–46.10.1007/s00221-005-2345-3
63
PhillipsPEStuberGDHeienMLWightmanRMCarelliRM. Subsecond dopamine release promotes cocaine seeking. Nature (2003) 422(6932):614–8.10.1038/nature01476
64
CheerJFWassumKMSombersLAHeienMLAriansenJLAragonaBJet alPhasic dopamine release evoked by abused substances requires cannabinoid receptor activation. J Neurosci (2007) 27(4):791–5.10.1523/JNEUROSCI.4152-06.2007
65
OlesonEBGentryRNChiomaVCCheerJF. Subsecond dopamine release in the nucleus accumbens predicts conditioned punishment and its successful avoidance. J Neurosci (2012) 32(42):14804–8.10.1523/JNEUROSCI.3087-12.2012
66
McCutcheonJEEbnerSRLoriauxALRoitmanMF. Encoding of aversion by dopamine and the nucleus accumbens. Front Neurosci. (2012) 6:137.10.3389/fnins.2012.00137
67
SchultzW. Behavioral dopamine signals. Trends Neurosci. (2007) 30(5):203–10.10.1016/j.tins.2007.03.007
68
ForsterGLBlahaCD. Pedunculopontine tegmental stimulation evokes striatal dopamine efflux by activation of acetylcholine and glutamate receptors in the midbrain and pons of the rat. Eur J Neurosci (2003) 17(4):751–62.10.1046/j.1460-9568.2003.02511.x
69
OmelchenkoNSesackSR. Laterodorsal tegmental projections to identified cell populations in the rat ventral tegmental area. J Comp Neurol (2005) 483(2):217–35.10.1002/cne.20417
70
PhillipsonOT. Afferent projections to the ventral tegmental area of Tsai and interfascicular nucleus: a horseradish peroxidase study in the rat. J Comp Neurol (1979) 187(1):117–43.10.1002/cne.901870106
71
GraceAAOnnSP. Morphology and electrophysiological properties of immunocytochemically identified rat dopamine neurons recorded in vitro. J Neurosci (1989) 9(10):3463–81.
72
SangheraMKTrulsonMEGermanDC. Electrophysiological properties of mouse dopamine neurons: in vivo and in vitro studies. Neuroscience (1984) 12(3):793–801.10.1016/0306-4522(84)90171-4
73
CharletyPJGrenhoffJCherguiKDe la ChapelleBBudaMSvenssonTHet alBurst firing of mesencephalic dopamine neurons is inhibited by somatodendritic application of kynurenate. Acta Physiol Scand (1991) 142(1):105–12.10.1111/j.1748-1716.1991.tb09134.x
74
OvertonPGClarkD. Burst firing in midbrain dopaminergic neurons. Brain Res Rev (1997) 25(3):312–34.10.1016/S0165-0173(97)00039-8
75
EngbergGKling-PetersenTNissbrandtH. GABAB-receptor activation alters the firing pattern of dopamine neurons in the rat substantia nigra. Synapse (1993) 15(3):229–38.10.1002/syn.890150308
76
AmeriA. The effects of cannabinoids on the brain. Prog Neurobiol. (1999) 58(4):315–48.10.1016/S0301-0082(98)00087-2
77
FattoreLMelisMFaddaPPistisMFrattaW. The endocannabinoid system and nondrug rewarding behaviours. Exp Neurol (2010) 224(1):23–36.10.1016/j.expneurol.2010.03.020
78
MaldonadoRValverdeOBerrenderoF. Involvement of the endocannabinoid system in drug addiction. Trends Neurosci. (2006) 29(4):225–32.10.1016/j.tins.2006.01.008
79
SolinasMGoldbergSRPiomelliD. The endocannabinoid system in brain reward processes. Br J Pharmacol. (2008) 154(2):369–83.10.1038/bjp.2008.130
80
DevaneWADysarzFAJohnsonMRMelvinLSHowlettAC. Determination and characterization of a cannabinoid receptor in rat brain. Mol Pharmacol (1988) 34(5):605–13.
81
MatsudaLABonnerTILolaitSJ. Cannabinoid receptors: which cells, where, how, and why?NIDA Res Monogr (1992) 126:48–56.
82
MunroSThomasKLAbu ShaarM. Molecular characterization of a peripheral receptor for cannabinoids. Nature (1993) 365(6441):61–5.10.1038/365061a0
83
HerkenhamMLynnABJohnsonMRMelvinLSde CostaBRRiceKC. Characterization and localization of cannabinoid receptors in rat brain: a quantitative in vitro autoradiographic study. J Neurosci (1991) 11(2):563–83.
84
HowlettACBarthFBonnerTICabralGCasellasPDevaneWAet alInternational union of pharmacology. XXVII. Classification of cannabinoid receptors. Pharmacol Rev (2002) 54(2):161–202.10.1124/pr.54.2.161
85
JansenEMHaycockDAWardSJSeyboldVS. Distribution of cannabinoid receptors in rat brain determined with aminoalkylindoles. Brain Res (1992) 575(1):93–102.
86
NuñezEBenitoCPazosMRBarbachanoAFajardoOGonzálezSet alCannabinoid CB2 receptors are expressed by perivascular microglial cells in the human brain: an immunohistochemical study. Synapse (2004) 53(4):208–13.10.1002/syn.20050
87
CabralGARabornESGriffinLDennisJMarciano-CabralF. CB2 receptors in the brain: role in central immune function. Br J Pharmacol (2008) 153(2):240–51.10.1038/sj.bjp.0707584
88
AdamczykPMiszkielJMcCrearyACFilipMPappMPrzegalinskiE. The effects of cannabinoid CB1, CB2 and vanilloid TRPV1 receptor antagonists on cocaine addictive behavior in rats. Brain Res (2012) 1444:45–54.10.1016/j.brainres.2012.01.030
89
FlakeNMZweifelLS. Behavioral effects of pulp exposure in mice lacking cannabinoid receptor 2. J Endod (2012) 38(1):86–90.10.1016/j.joen.2011.09.015
90
OnaiviES. Neuropsychobiological evidence for the functional presence and expression of cannabinoid CB2 receptors in the brain. Neuropsychobiology (2006) 54(4):231–46.10.1159/000100778
91
XiZXPengXLiXSongRZhangHYLiuQRet alBrain cannabinoid CBâ‚‚ receptors modulate cocaine’s actions in mice. Nat Neurosci (2011) 14(9):1160–6.10.1038/nn.2874
92
RybergELarssonNSjögrenSHjorthSHermanssonNOLeonovaJet alThe orphan receptor GPR55 is a novel cannabinoid receptor. Br J Pharmacol (2007) 152(7):1092–101.10.1038/sj.bjp.0707460
93
SzallasiADi MarzoV. New perspectives on enigmatic vanilloid receptors. Trends Neurosci. (2000) 23(10):491–7.10.1016/S0166-2236(00)01630-1
94
DevaneWAHanusLBreuerAPertweeRGStevensonLAGriffinGet alIsolation and structure of a brain constituent that binds to the cannabinoid receptor. Science (1992) 258(5090):1946–9.10.1126/science.1470919
95
MechoulamRBen ShabatSHanusLLigumskyMKaminskiNESchatzARet alIdentification of an endogenous 2-monoglyceride, present in canine gut, that binds to cannabinoid receptors. Biochem Pharmacol (1995) 50(1):83–90.10.1016/0006-2952(95)00109-D
96
SugiuraTKondoSSukagawaANakaneSShinodaAItohKet al2-Arachidonoylglycerol: a possible endogenous cannabinoid receptor ligand in brain. Biochem Biophys Res Commun. (1995) 215(1):89–97.10.1006/bbrc.1995.2437
97
CadasHGailletSBeltramoMVenanceLPiomelliD. Biosynthesis of an endogenous cannabinoid precursor in neurons and its control by calcium and cAMP. J Neurosci (1996) 16(12):3934–42.
98
PiomelliD. The molecular logic of endocannabinoid signalling. Nat Rev Neurosci (2003) 4(11):873–84.10.1038/nrn1247
99
GoparajuSKUedaNYamaguchiHYamamotoS. Anandamide amidohydrolase reacting with 2-arachidonoylglycerol, another cannabinoid receptor ligand. FEBS Lett (1998) 422(1):69–73.10.1016/S0014-5793(97)01603-7
100
StellaNSchweitzerPPiomelliD. A second endogenous cannabinoid that modulates long-term potentiation. Nature (1997) 388(6644):773–8.10.1038/42015
101
Haj-DahmaneSShenR. The wake-promoting peptide orexin-B inhibits glutamatergic transmission to dorsal raphe nucleus serotonin neurons through retrograde endocannabinoid signaling. J Neurosci (2005) 25(4):896–905.10.1523/JNEUROSCI.3258-04.2005
102
KortlevenCBruneauLCTrudeauL. Neurotensin inhibits glutamate-mediated synaptic inputs onto ventral tegmental area dopamine neurons through the release of the endocannabinoid 2-AG. Neuropharmacology (2012) 63(6):983–91.10.1016/j.neuropharm.2012.07.037
103
MaejimaTOhno-ShosakuTKanoM. Endogenous cannabinoid as a retrograde messenger from depolarized postsynaptic neurons to presynaptic terminals. Neurosci Res (2001) 40(3):205–10.10.1016/S0168-0102(01)00241-3
104
HashimotodaniYOhno-ShosakuTTsubokawaHOgataHEmotoKMaejimaTet alPhospholipase Cbeta serves as a coincidence detector through its Ca2+ dependency for triggering retrograde endocannabinoid signal. Neuron (2005) 45(2):257–68.10.1016/j.neuron.2005.01.004
105
KanoMOhno-ShosakuTHashimotodaniYUchigashimaMWatanabeM. Endocannabinoid-mediated control of synaptic transmission. Physiol Rev (2009) 89(1):309–80.10.1152/physrev.00019.2008
106
FreundTFKatonaIPiomelliD. Role of endogenous cannabinoids in synaptic signaling. Physiol Rev (2003) 83(3):1017–66.
107
Ohno-ShosakuTKanoM. Endocannabinoid-mediated retrograde modulation of synaptic transmission. Curr Opin Neurobiol. (2014) 29C:1–8.10.1016/j.conb.2014.03.017
108
AlgerBE. Retrograde signaling in the regulation of synaptic transmission: focus on endocannabinoids. Prog Neurobiol. (2002) 68(4):247–86.10.1016/S0301-0082(02)00080-1
109
MelisMPistisMPerraSMuntoniALPillollaGGessaGL. Endocannabinoids mediate presynaptic inhibition of glutamatergic transmission in rat ventral tegmental area dopamine neurons through activation of CB1 receptors. J Neurosci (2004) 24(1):53–62.10.1523/JNEUROSCI.4503-03.2004
110
RiegelACLupicaCR. Independent presynaptic and postsynaptic mechanisms regulate endocannabinoid signaling at multiple synapses in the ventral tegmental area. J Neurosci (2004) 24(49):11070–8.10.1523/JNEUROSCI.3695-04.2004
111
Ohno-ShosakuTMaejimaTKanoM. Endogenous cannabinoids mediate retrograde signals from depolarized postsynaptic neurons to presynaptic terminals. Neuron (2001) 29(3):729–38.10.1016/S0896-6273(01)00247-1
112
Di ChiaraGImperatoA. Drugs abused by humans preferentially increase synaptic dopamine concentrations in the mesolimbic system of freely moving rats. Proc Natl Acad Sci USA (1988) 85(14):5274–8.10.1073/pnas.85.14.5274
113
WiseRA. Brain reward circuitry: insights from unsensed incentives. Neuron (2002) 36(2):229–40.10.1016/S0896-6273(02)00965-0
114
CastañedaEMossDEOddieSDWhishawIQ. THC does not affect striatal dopamine release: microdialysis in freely moving rats. Pharmacol Biochem Behav (1991) 40(3):587–91.10.1016/0091-3057(91)90367-B
115
GardnerELLowinsonJH. Marijuana’s interaction with brain reward systems: update 1991. Pharmacol Biochem Behav (1991) 40(3):571–80.10.1016/0091-3057(91)90365-9
116
CheerJFWassumKMHeienMLPhillipsPEWightmanRM. Cannabinoids enhance subsecond dopamine release in the nucleus accumbens of awake rats. J Neurosci (2004) 24(18):4393–400.10.1523/JNEUROSCI.0529-04.2004
117
ChenJPParedesWLowinsonJHGardnerEL. Strain-specific facilitation of dopamine efflux by delta 9-tetrahydrocannabinol in the nucleus accumbens of rat: an in vivo microdialysis study. Neurosci Lett (1991) 129(1):136–80.10.1016/0304-3940(91)90739-G
118
MaloneDTTaylorDA. Modulation by fluoxetine of striatal dopamine release following Delta9-tetrahydrocannabinol: a microdialysis study in conscious rats. Br J Pharmacol. (1999) 128(1):21–6.
119
TandaGPontieriFEDi ChiaraG. Cannabinoid and heroin activation of mesolimbic dopamine transmission by a common mu1 opioid receptor mechanism. Science (1997) 276(5321):2048–50.10.1126/science.276.5321.2048
120
FrenchEDDillonKWuX. Cannabinoids excite dopamine neurons in the ventral tegmentum and substantia nigra. Neuroreport (1997) 8(3):649–52.10.1097/00001756-199702100-00014
121
GessaGLMelisMMuntoniALDianaM. Cannabinoids activate mesolimbic dopamine neurons by an action on cannabinoid CB1 receptors. Eur J Pharmacol (1998) 341(1):39–44.10.1016/S0014-2999(97)01442-8
122
JulianMDMartinABCuellarBRodriguez De FonsecaFNavarroMMoratallaRet alNeuroanatomical relationship between type 1 cannabinoid receptors and dopaminergic systems in the rat basal ganglia. Neuroscience (2003) 119(1):309–18.10.1016/S0306-4522(03)00070-8
123
LupicaCRRiegelAC. Endocannabinoid release from midbrain dopamine neurons: a potential substrate for cannabinoid receptor antagonist treatment of addiction. Neuropharmacology (2005) 48(8):1105–16.10.1016/j.neuropharm.2005.03.016
124
CheerJFMarsdenCAKendallDAMasonR. Lack of response suppression follows repeated ventral tegmental cannabinoid administration: an in vitro electrophysiological study. Neuroscience (2000) 99(4):661–7.10.1016/S0306-4522(00)00241-4
125
SzaboBSiemesSWallmichrathI. Inhibition of GABAergic neurotransmission in the ventral tegmental area by cannabinoids. Eur J Neurosci (2002) 15(12):2057–61.10.1046/j.1460-9568.2002.02041.x
126
De VriesTJShahamYHombergJRCrombagHSchuurmanKDiebenJet alA cannabinoid mechanism in relapse to cocaine seeking. Nat Med (2001) 7(10):1151–4.10.1038/nm1001-1151
127
De VriesTJde VriesWJanssenMCSchoffelmeerAN. Suppression of conditioned nicotine and sucrose seeking by the cannabinoid-1 receptor antagonist SR141716A. Behav Brain Res (2005) 161(1):164–8.10.1016/j.bbr.2005.02.021
128
HernandezGCheerJF. Extinction learning of rewards in the rat: is there a role for CB1 receptors?Psychopharmacology (2011) 217(2):189–97.10.1007/s00213-011-2275-7
129
WardSJWalkerEADykstraLA. Effect of cannabinoid CB1 receptor antagonist SR141716A and CB1 receptor knockout on cue-induced reinstatement of Ensure and corn-oil seeking in mice. Neuropsychopharmacology (2007) 32(12):2592–600.10.1038/sj.npp.1301384
130
ChaperonFThiébotMH. Behavioral effects of cannabinoid agents in animals. Crit Rev Neurobiol (1999) 13(3):243–81.
131
WingVCShoaibM. A second-order schedule of food reinforcement in rats to examine the role of CB1 receptors in the reinforcement-enhancing effects of nicotine. Addict Biol. (2010) 15(4):380–92.10.1111/j.1369-1600.2009.00203.x
132
De VriesTJHombergJRBinnekadeRRaasøHSchoffelmeerAN. Cannabinoid modulation of the reinforcing and motivational properties of heroin and heroin-associated cues in rats. Psychopharmacology (2003) 168(1–2):164–9.10.1007/s00213-003-1422-1
133
AnggadiredjaKNakamichiMHiranitaTTanakaHShoyamaYWatanabeSet alEndocannabinoid system modulates relapse to methamphetamine seeking: possible mediation by the arachidonic acid cascade. Neuropsychopharmacology (2004) 29(8):1470–8.10.1038/sj.npp.1300454
134
EconomidouDMattioliLCifaniCPerfumiMMassiMCuomoVet alEffect of the cannabinoid CB1 receptor antagonist SR-141716A on ethanol self-administration and ethanol-seeking behaviour in rats. Psychopharmacology (2006) 183(4):394–403.10.1007/s00213-005-0199-9
135
JustinovaZMunzarPPanlilioLVYasarSRedhiGHTandaGet alBlockade of THC-seeking behavior and relapse in monkeys by the cannabinoid CB(1)-receptor antagonist rimonabant. Neuropsychopharmacology (2008) 33(12):2870–7.10.1038/npp.2008.21
136
BallKTCombsTABeyerDN. Opposing roles for dopamine D1- and D2-like receptors in discrete cue-induced reinstatement of food seeking. Behav Brain Res (2011) 222(2):390–3.10.1016/j.bbr.2011.03.064
137
OstlundSBMaidmentNT. Dopamine receptor blockade attenuates the general incentive motivational effects of noncontingently delivered rewards and reward-paired cues without affecting their ability to bias action selection. Neuropsychopharmacology (2012) 37(2):508–19.10.1038/npp.2011.217
138
OlesonEBBeckertMVMorraJTLansinkCSCachopeRAbdullahRAet alEndocannabinoids shape accumbal encoding of cue-motivated behavior via CB1 receptor activation in the ventral tegmentum. Neuron (2012) 73(2):360–73.10.1016/j.neuron.2011.11.018
139
DayJRoitmanMFWightmanRMCarelliRM. Associative learning mediates dynamic shifts in dopamine signaling in the nucleus accumbens. Nat Neurosci (2007) 10(8):1020–8.10.1038/nn1923
140
BuhusiCVMeckWH. What makes us tick? Functional and neural mechanisms of interval timing. Nat Rev Neurosci (2005) 6(10):755–65.10.1038/nrn1764
141
HarringtonDLHaalandKY. Sequencing in Parkinson’s disease. Abnormalities in programming and controlling movement. Brain (1991) 114(1A):99–115.
142
MalapaniCRakitinBLevyRMeckWHDeweerBDuboisBet alCoupled temporal memories in Parkinson’s disease: a dopamine-related dysfunction. J Cogn Neurosci. (1998) 10(3):316–31.10.1162/089892998562762
143
MacDonaldCJMeckWH. Differential effects of clozapine and haloperidol on interval timing in the supraseconds range. Psychopharmacology (2005) 182(2):232–44.10.1007/s00213-005-0074-8
144
MeckWHChurchRM. A mode control model of counting and timing processes. J Exp Psychol Anim Behav Process (1983) 9(3):320–34.10.1037/0097-7403.9.3.320
145
CoullJTChengRMeckWH. Neuroanatomical and neurochemical substrates of timing. Neuropsychopharmacology (2011) 36(1):3–25.10.1038/npp.2010.113
146
AndreasenNC. Understanding the causes of schizophrenia. N Engl J Med (1999) 340(8):645–7.10.1056/NEJM199902253400811
147
MatellMSKingGRMeckWH. Differential modulation of clock speed by the administration of intermittent versus continuous cocaine. Behav Neurosci (2004) 118(1):150–6.10.1037/0735-7044.118.1.150
148
MatellMSMeckWH. Neuropsychological mechanisms of interval timing behavior. Bioessays (2000) 22(1):94–103.10.1002/(SICI)1521-1878(200001)22:1<94::AID-BIES14>3.0.CO;2-E
149
MeckWH. Selective adjustment of the speed of internal clock and memory processes. J Exp Psychol Anim Behav Process. (1983) 9(2):171–201.
150
HicksREGualtieriCTMayoJPPerez-ReyesM. Cannabis, atropine, and temporal information processing. Neuropsychobiology (1984) 12(4):229–37.10.1159/000118144
151
TinklenbergJRKopellBSMelgesFTHollisterLE. Marihuana and alcohol, Time production and memory functions. Arch Gen Psychiatry (1972) 27(6):812–5.10.1001/archpsyc.1972.01750300074013
152
CrystalJDMaxwellKWHohmannAG. Cannabinoid modulation of sensitivity to time. Behav Brain Res (2003) 144(1–2):57–66.10.1016/S0166-4328(03)00062-7
153
HanCJRobinsonJK. Cannabinoid modulation of time estimation in the rat. Behav Neurosci (2001) 115(1):243–6.10.1037/0735-7044.115.1.243
154
OlesonEBCachopeRFitoussiATsutsuiKWuSGallegosJAet alCannabinoid receptor activation shifts temporally engendered patterns of dopamine release. Neuropsychopharmacology (2014) 39(6):1441–52.10.1038/npp.2013.340
155
DewsPB. The theory of fixed-interval responding. In: SchoenfeldWN, editor. The Theory of Reinforcement Schedules. New York, NY: Appleton Century Crofts (1970). p. 43–61.
156
PattijTWiskerkeJSchoffelmeerAN. Cannabinoid modulation of executive functions. Eur J Pharmacol (2008) 585(2–3):458–63.10.1016/j.ejphar.2008.02.099
157
NarayananNSLandBSolderJEDeisserothKDiLeoneRJ. Prefrontal D1 dopamine signaling is required for temporal control. Proc Natl Acad Sci USA (2012) 109(50):20726–31.10.1073/pnas.1211258109
158
AlbinRLYoungABPenneyJB. The functional anatomy of basal ganglia disorders. Trends Neurosci. (1989) 12(10):366–75.10.1016/0166-2236(89)90074-X
159
KravitzAVTyeLDKreitzerAC. Distinct roles for direct and indirect pathway striatal neurons in reinforcement. Nat Neurosci (2012) 15(6):816–8.10.1038/nn.3100
160
BradyAMO’DonnellP. Dopaminergic modulation of prefrontal cortical input to nucleus accumbens neurons in vivo. J Neurosci (2004) 24(5):1040–9.10.1523/JNEUROSCI.4178-03.2004
161
FlorescoSBBlahaCDYangCRPhillipsAG. Modulation of hippocampal and amygdalar-evoked activity of nucleus accumbens neurons by dopamine: cellular mechanisms of input selection. J Neurosci (2001) 21(8):2851–60.
162
CuiGJunSBJinXPhamMDVogelSSLovingerDMet alConcurrent activation of striatal direct and indirect pathways during action initiation. Nature (2013) 494(7436):238–42.10.1038/nature11846
163
MatellMSMeckWH. Cortico-striatal circuits and interval timing: coincidence detection of oscillatory processes. Brain Res Cogn Brain Res. (2004) 21(2):139–70.10.1016/j.cogbrainres.2004.06.012
164
MatellMSMeckWHNicolelisMA. Interval timing and the encoding of signal duration by ensembles of cortical and striatal neurons. Behav Neurosci (2003) 117(4):760–73.10.1037/0735-7044.117.4.760
165
GrovesPMGarcia-MunozMLinderJCManleyMSMartoneMEYoungSJ. Elements of the intrinsic organization and information processing in the neostriatum. In: HoukJCDavisJLBeiserDG, editors. Models of Information Processing in the Basal Ganglia. Cambridge: MIT Press (1995). p. 51–96.
166
O’DonnellPGraceAA. Synaptic interactions among excitatory afferents to nucleus accumbens neurons: hippocampal gating of prefrontal cortical input. J Neurosci (1995) 15(5):3622–39.
167
GruberAJSollaSASurmeierDJHoukJC. Modulation of striatal single units by expected reward: a spiny neuron model displaying dopamine-induced bistability. J Neurophysiol (2003) 90(2):1095–114.10.1152/jn.00618.2002
168
McGintyVBGraceA. Timing-dependent regulation of evoked spiking in nucleus accumbens neurons by integration of limbic and prefrontal cortical inputs. J Neurophysiol (2009) 101(4):1823–35.10.1152/jn.91162.2008
169
CalabresiPPicconiBTozziADi FilippoM. Dopamine-mediated regulation of corticostriatal synaptic plasticity. Trends Neurosci (2007) 30(5):211–9.10.1016/j.tins.2007.03.001
170
GrovesPM. A theory of the functional organization of the neostriatum and the neostriatal control of voluntary movement. Brain Res (1983) 286(2):109–32.10.1016/0165-0173(83)90011-5
171
WickensJRAlexanderMEMillerR. Two dynamic modes of striatal function under dopaminergic-cholinergic control: simulation and analysis of a model. Synapse (1991) 8(1):1–12.10.1002/syn.890080102
172
WickensJRKotterRAlexanderME. Effects of local connectivity on striatal function: stimulation and analysis of a model. Synapse (1995) 20(4):281–98.10.1002/syn.890200402
173
CarelliRMDeadwylerSA. Cellular mechanisms underlying reinforcement-related processing in the nucleus accumbens: electrophysiological studies in behaving animals. Pharmacol Biochem Behav (1997) 57(3):495–504.10.1016/S0091-3057(96)00442-X
174
PeoplesLLWestMO. Phasic firing of single neurons in the rat nucleus accumbens correlated with the timing of intravenous cocaine self-administration. J Neurosci (1996) 16(10):3459–73.
175
UsudaITanakaKChibaT. Efferent projections of the nucleus accumbens in the rat with special reference to subdivision of the nucleus: biotinylated dextran amine study. Brain Res (1998) 797(1):73–93.
176
VitayJHamkerFH. Timing and expectation of reward: a neuro-computational model of the afferents to the ventral tegmental area. Front Neurorobot. (2014) 8:4.10.3389/fnbot.2014.00004
177
KurtiANMatellMS. Nucleus accumbens dopamine modulates response rate but not response timing in an interval timing task. Behav Neurosci (2011) 125(2):215–25.10.1037/a0022892
178
MeckWH. Neuroanatomical localization of an internal clock: a functional link between mesolimbic, nigrostriatal, and mesocortical dopaminergic systems. Brain Res (2006) 1109(1):93–107.10.1016/j.brainres.2006.06.031
179
SinghTMcDannaldMATakahashiYKHaneyRZCoochNKLucantonioFet alThe role of the nucleus accumbens in knowing when to respond. Learn Mem (2011) 18(2):85–7.10.1101/lm.2008111
180
GaltressTKirkpatrickK. The role of the nucleus accumbens core in impulsive choice, timing, and reward processing. Behav Neurosci (2010) 124(1):26–43.10.1037/a0018464
181
BuhusiCVMeckWH. Differential effects of methamphetamine and haloperidol on the control of an internal clock. Behav Neurosci (2002) 116(2):291–7.10.1037/0735-7044.116.2.291
182
LichtmanAHMartinBR. Cannabinoid tolerance and dependence. Handb Exp Pharmacol (2005) 168:691–717.10.1007/3-540-26573-2_24
183
NalwaVRaoPS. Comparison of the effects of d-amphetamine on FI and DRL schedule performance of self-stimulating rats. Clin Exp Pharmacol Physiol (1984) 11(3):261–7.10.1111/j.1440-1681.1984.tb00263.x
184
SewellRASchnakenbergAElanderJRadhakrishnanRWilliamsASkosnikPDet alAcute effects of THC on time perception in frequent and infrequent cannabis users. Psychopharmacology (2013) 226(2):401–13.10.1007/s00213-012-2915-6
185
Cory-SlechtaDAPazminoRBareC. The critical role of nucleus accumbens dopamine systems in the mediation of fixed interval schedule-controlled operant behavior. Brain Res (1997) 764(1–2):253–6.
186
Cory-SlechtaDAO’MaraDJBrockelBJ. Nucleus accumbens dopaminergic medication of fixed interval schedule-controlled behavior and its modulation by low-level lead exposure. J Pharmacol Exp Ther (1998) 286(2):794–805.
187
RobbinsTWRobertsDCKoobGF. Effects of d-amphetamine and apomorphine upon operant behavior and schedule-induced licking in rats with 6-hydroxydopamine-induced lesions of the nucleus accumbens. J Pharmacol Exp Ther (1983) 224(3):662–73.
188
NeillDBHerndonJG. Anatomical specificity within rat striatum for the dopaminergic modulation of DRL responding and activity. Brain Res (1978) 153(3):529–38.
189
LakeJIMeckWH. Differential effects of amphetamine and haloperidol on temporal reproduction: dopaminergic regulation of attention and clock speed. Neuropsychologia (2013) 51(2):284–92.10.1016/j.neuropsychologia.2012.09.014
190
BickelWKOdumALMaddenGJ. Impulsivity and cigarette smoking: delay discounting in current, never, and ex-smokers. Psychopharmacology (1999) 146(4):447–54.10.1007/PL00005490
191
CoffeySFGudleskiGDSaladinMEBradyKT. Impulsivity and rapid discounting of delayed hypothetical rewards in cocaine-dependent individuals. Exp Clin Psychopharmacol. (2003) 11(1):18–25.10.1037/1064-1297.11.1.18
192
MaddenGJPetryNMBadgerGJBickelWK. Impulsive and self-control choices in opioid-dependent patients and non-drug-using control participants: drug and monetary rewards. Exp Clin Psychopharmacol. (1997) 5(3):256–62.10.1037/1064-1297.5.3.256
193
MitchellJMFieldsHLD’EspositoMBoettigerCA. Impulsive responding in alcoholics. Alcohol Clin Exp Res (2005) 29(12):2158–69.10.1097/01.alc.0000191755.63639.4a
194
PetersENPetryNMLapagliaDMReynoldsBCarrollKM. Delay discounting in adults receiving treatment for marijuana dependence. Exp Clin Psychopharmacol (2013) 21(1):46–54.10.1037/a0030943
195
PetryNMKirbyKNKranzlerHR. Effects of gender and family history of alcohol dependence on a behavioral task of impulsivity in healthy subjects. J Stud Alcohol (2002) 63(1):83–90.
196
VuchinichRESimpsonCA. Hyperbolic temporal discounting in social drinkers and problem drinkers. Exp Clin Psychopharmacol (1998) 6(3):292–305.10.1037/1064-1297.6.3.292
197
DayJJonesJLCarelliRM. Nucleus accumbens neurons encode predicted and ongoing reward costs in rats. Eur J Neurosci (2011) 33(2):308–21.10.1111/j.1460-9568.2010.07531.x
198
HernandezGOlesonEBGentryRNAbbasZBernsteinDLArvanitogiannisAet alEndocannabinoids promote cocaine-induced impulsivity and its rapid dopaminergic correlates. Biol Psychiatry (2014) 75(6):487–98.10.1016/j.biopsych.2013.09.005
199
OstlundSBLeBlancKHKosheleffARWassumKMMaidmentNT. Phasic mesolimbic dopamine signaling encodes the facilitation of incentive motivation produced by repeated cocaine exposure. Neuropsychopharm (2014) 39(10):2441–9.10.1038/npp.2014.96
Summary
Keywords
dopamine, cannabinoids, reward-seeking behavior, cues, endocannabinoids, fixed interval
Citation
Wenzel JM and Cheer JF (2014) Endocannabinoid-Dependent Modulation of Phasic Dopamine Signaling Encodes External and Internal Reward-Predictive Cues. Front. Psychiatry 5:118. doi: 10.3389/fpsyt.2014.00118
Received
02 July 2014
Accepted
13 August 2014
Published
01 September 2014
Volume
5 - 2014
Edited by
Steven R. Laviolette, University of Western Ontario, Canada
Reviewed by
Sulev Kõks, University of Tartu, Estonia; Steven R. Laviolette, University of Western Ontario, Canada
Copyright
© 2014 Wenzel and Cheer.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Joseph F. Cheer, Department of Anatomy and Neurobiology, University of Maryland School of Medicine, 20 Penn Street, Baltimore, MD 21201, USA e-mail: jchee001@umaryland.edu
This article was submitted to Neuropharmacology, a section of the journal Frontiers in Psychiatry.
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.