PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
J Neurosci. Author manuscript; available in PMC 2011 August 2.
Published in final edited form as:
PMCID: PMC3081716
NIHMSID: NIHMS270158

Mu opioid receptor activation in the basolateral amygdala mediates the learning of increases but not decreases in the incentive value of a food reward

Abstract

The decision to perform, or not perform, actions known to lead to a rewarding outcome is strongly influenced by the current incentive value of the reward. Incentive value is largely determined by the affective experience derived during previous consumption of the reward; the process of incentive learning. We trained rats on a two-lever seeking-taking chain paradigm for sucrose reward, in which responding on the initial seeking lever of the chain was demonstrably controlled by the incentive value of the reward. We found that infusion of the mu opioid receptor antagonist, CTOP, into the basolateral amygdala (BLA) during post-training, non-contingent consumption of sucrose in a novel elevated hunger state (a positive incentive learning opportunity) blocked the encoding of incentive value information normally used to increase subsequent sucrose-seeking responses. Similar treatment with delta (ICI 174,864), or kappa (GNTI) antagonists was without effect. Interestingly, none of these drugs affected the ability of the rats to encode a decrease in incentive value resulting from experiencing the sucrose in a novel reduced hunger state. However, the mu agonist, DAMGO, appeared to attenuate this negative incentive learning. These data suggest that up- and down-shifts in endogenous opioid transmission in the BLA mediate the encoding of positive and negative shifts in incentive value, respectively, through actions at mu opioid receptors, and provide insight into a mechanism through which opiates may elicit inappropriate ‘desire’ resulting in their continued intake in the face of diminishing affective experience.

Keywords: Opioid Receptors, CTOP, ICI 174, 864, GNTI, Goal-Directed, Reward Seeking, Incentive Value

Goal-directed actions are the means through which we exert control over our environment in service of our desires. The decision to engage in such actions is largely controlled by the incentive value of the goal; the degree to which it is ‘desired’ (Balleine and Dickinson, 1998). Incentive learning is the process through which this value is established so that it may be used to guide future reward seeking. This occurs when an individual has a novel affective experience with the reward (Balleine, 1992, 2001). Interestingly however, recent evidence suggests that the neural processes underlying the pleasure elicited during reward contact, ‘liking’, and the attribution of incentive value to that reward are dissociable (Wassum et al., 2009).

Endogenous opioid peptides are thought to convey the affective properties of food rewards, based on the palatability-enhancing effects of opiates (Doyle et al., 1993; Kelley et al., 2002), and mu opioid receptor-mediated ‘hedonic hotspots’ have been localized to the nucleus accumbens shell and ventral pallidum (Pecina and Berridge, 2005; Smith and Berridge, 2005, 2007). Popular constructs of motivated behavior highlight the dissociation of this reward ‘liking’ and ‘wanting’ (Robinson and Berridge, 2001, 2003). Such theories focus on ‘wanting’ as the general motivational influence that reward-associated cues exert on instrumental actions, mediated primarily through dopamine systems (Berridge, 2007), but also involving amygdala central nucleus opioids (Mahler and Berridge, 2009). However, as previously mentioned, goal-directed actions are heavily influenced by the incentive value of the reward (Balleine and Dickinson, 1998), which is dependent on prior reward experience, and is therefore distinct from the general motivational effects of cues (Dickinson and Balleine, 1994; Corbit and Balleine, 2005).

As alluded to above, this incentive learning process may also be dissociable from ‘liking’. Opioid receptor activation in hedonic hotspots was found to be necessary for deprivation-induced palatability increases, but not for incentive value elevations induced by such deprivation (Wassum et al., 2009). Conversely, activation of opioid receptors in the basolateral amygdala (BLA) was necessary for encoding an incentive value increase, but not for expression of increased palatability (Wassum et al., 2009).

Such a tripartite role of endogenous opioid systems in mediating the consummatory effects of rewards (‘liking’), the process by which such ‘liking’ effects are encoded as incentive value to guide reward-seeking actions (incentive learning), and the invigorating effects of reward-paired stimuli (‘wanting’), may explain the intensely addictive nature of opiates. With respect to incentive learning, this account would be strengthened by evidence that endogenous activation of BLA opioid receptors promotes positive, but not negative shifts in incentive value, since this might explain why drugs continue to be sought despite negative consequences of their use. Moreover, one might predict exogenous activation of opioid receptors in the BLA to impede the encoding of negative incentive value shifts. These hypotheses were tested here together with an examination of the opioid receptor subtype in the BLA mediating incentive learning given the presence of mu, delta and kappa opioid receptors in this region (Mansour et al., 1994; Ding et al., 1996).

Materials and Methods

General approach

An incentive learning paradigm was employed wherein rats were trained on a seeking-taking chain of actions to press one lever in order to gain access to a second lever that delivered a sucrose pellet reward (Balleine et al., 1995; Corbit and Balleine, 2003; Wassum et al., 2009). The importance of this seeking-taking chain for assessment of incentive value, over more common single lever instrumental paradigms, is highlighted by data showing that responding on the lever distal to reward delivery is sensitive to the incentive value of the reward while being relatively immune to the general activational effects of motivational state (in this case, hunger state) and to reward-related cues (Balleine et al., 1995; Corbit and Balleine, 2003). That is, whilst changes in food deprivation state have immediate general effects on activity on the lever proximal to reward delivery when tested under non-rewarded conditions, changes in responding on the distal seeking lever require that the rat learn about the value change of the specific outcome earned by the action through prior experience of the reward in the altered motivational state i.e. incentive learning (Balleine et al., 1995; Corbit and Balleine, 2003; Balleine et al., 2005). For example, an increase in reward seeking vigor occurs only after the animal has consumed reward in the new hungry state and in so doing has learned that, in this state, the reward is more palatable and now retains a higher incentive value.

Experiment 1 (see Table 1 for experimental details) was designed to replicate these previous findings and allow us to focus on the distal reward seeking response as a measure of the incentive value of the sucrose outcome the rat is working to receive. In Experiment 2 (see Table 2 for experimental details) rats were trained under low deprivation conditions and then given the opportunity for positive incentive learning by allowing them to consume non-contingent sucrose pellets when highly food-deprived and in so doing learn that in this state the sucrose is more palatable and retains a higher incentive value. Opioid antagonists or vehicle were administered into the BLA immediately prior to this learning phase. The next day their responding on the seeking-taking chain was measured, off drug, under non-rewarded conditions while in the heightened food-deprived state in order to test the effects of the previous day’s opportunity for incentive learning on reward seeking actions. In Experiment 3 (see Table 3 for experimental details) the food deprivation state was reversed, that is, animals were trained in a high food-deprived state and then given an opportunity for negative incentive learning in a low deprivation state (i.e. to learn that in the low deprivation state sucrose is less palatable and therefore less valuable). Again, opioid antagonists or vehicle were administered into the BLA immediately prior to this learning phase. This incentive learning opportunity was then followed by a non-rewarded test, off drug, in this low deprivation condition. Experiment 4 followed from Experiment 3 to assess the effects of the mu opioid receptor agonist DAMGO on negative incentive learning.

Table 1
Experiment 1 Design: Effects of incentive learning on reward seeking actions
Table 2
Experiment 2 Design: Positive Incentive Learning Experiments
Table 3
Experiment 3 Design: Negative Incentive Learning Experiments

Subjects

Male Long Evans rats (Experiment 1: N=29, Experiment 2: N=35, Experiment 3: N=32; Experiment 4: N=23; Charles River Laboratories, Wilmington, MA) were group housed and handled for 3 days prior to training. Rats had free access to tap water in the home cage and were fed approximately 3h after each day’s training session according to the deprivation schedules described below. All procedures were conducted in accordance with the NIH Guide for the Care and use of Laboratory Animals and approved by the UCLA Institutional Animal Care and Use Committee.

Apparatus and training

Training and testing took place during the light phase of the 12:12h light:dark cycle in 8 Med Associates (East Fairfield, VT) operant chambers described previously (Corbit and Balleine, 2003).

Heterogeneous seeking-delivery chain training

Briefly, rats were trained to earn 45 mg sucrose pellets (Bioserv, Frenchtown, NJ) on a heterogeneous seeking-taking chain. The training procedures were similar to those we have previously employed (Corbit and Balleine, 2003; Wassum et al., 2009). Each session started with the illumination of the house light and insertion of the levers where appropriate and ended with the retraction of the levers and turning off of the house light. Rats received only one training session per day.

Magazine training

Rats received 3 days of magazine training in which they were exposed to non-contingent sucrose deliveries (20 outcomes over 30 min) in the operant chamber with the levers retracted, in order to learn where to receive the sucrose pellet reward.

Single action instrumental training

Rats were then given 3–4 days of single action continuous reinforcement training on the lever to the right of the magazine with the sucrose delivered on a continuous reinforcement schedule. Each session lasted until 20 outcomes had been earned, or 30 min elapsed.

Training on the reward-delivery chain

Following single action instrumental training the seeking lever (i.e. the lever to the left of the magazine) was introduced into the chamber, initially in the absence of the delivery lever. Rats (N=2) that failed to acquire the chain in Experiment 2 (20 earned outcomes within 30 min) were dropped from the experiment.

Surgery

Standard stereotaxic procedures were used for implantation of bilateral guide cannulae (see (Wang et al., 2005; Wassum et al., 2009)). Rats were anesthetized with isoflurane (4–5% induction, 1–2% maintenance) and implanted bilaterally with 22 gauge stainless steel guide cannulae (Plastics One, Roanoke, VA) 1 mm above the intended injection site in the BLA (coordinates from Bregma and the skull surface: AP:−3.0; ML: ±5.1; V: 8.0).

Experiment 1

In Experiment 1 (Table 1) rats, 3h food deprived, were trained as above to press a seeking lever to gain access to a second taking lever, a single press on which delivered sucrose. After training all rats were placed in the operant chamber with the levers retracted. Half the rats (N=14) were given 30 non-contingent sucrose pellet presentations over 40 min, while the unexposed group (N=15) did not receive the any pellets. The next day, still 3h food deprived all rats were tested for their responding on the chain under non-rewarded conditions for 5 min. This non-rewarded test was conducted just as in training with rats responding on the seeking lever on RR-4 to receive the second taking lever, which once pressed, was retracted, but no reward was delivered. Rats were then retrained for 2 days on the 3h food deprived schedule. For the second phase all rats were switched to a 23h food deprived state and placed in the operant chamber with the levers retracted and either given 30 non-contingent sucrose pellet presentations over 40 min (an opportunity for incentive learning), or no pellets as before. All rats were then tested the following day, still 23h food deprived, for their responding in the chain under non-rewarded conditions. The order of the deprivation manipulation was not counterbalanced based on our preliminary data indicating that experience with the outcome in the increased deprivation state in the first test significantly impacted performance in the second testing series.

Experiment 2

For Experiment 2 (Table 2), rats, 3h food deprived, were trained as above to press a lever to gain access to a second lever, a single press on which delivered a sucrose pellet. Rats were trained prior to surgery for cannula implantation, then after surgery rats were retrained on the final schedule for 2 days. After the last post-surgery training session all rats were maintained 3h food deprived and received an infusion of either intra-BLA vehicle (N=14), ICI 174,864 (N=6), GNTI (N=8), or CTOP (N=7) immediately prior to being placed in the operant chamber with the levers retracted and given 30 non-contingent sucrose pellet presentations over 40 min (the revaluation). The next day, still 3h food deprived but devoid of drug, all rats were tested for their responding on the chain under non-rewarded conditions for 4 min. This non-rewarded test was conducted just as in training with rats responding on the seeking lever on RR-4 to receive the second taking lever, which once pressed, was retracted, but no reward was delivered. Rats were then retrained for 2 days on the 3h food deprived schedule. For the second phase all rats were switched to a 23h food deprived state and received an infusion of the same drug they received during the first phase of the experiment immediately prior to being placed in the operant chamber with the levers retracted and given 30 non-contingent sucrose pellet presentations over 40 min (the opportunity for positive incentive learning). All rats, still 23h food deprived were then tested for their responding in the chain, off drug, under non-rewarded conditions the following day.

Experiment 2 was run in 2 sets of 2 replications with the effects of ICI 174,864 and CTOP being compared against vehicle in the first set and the effects of GNTI compared against vehicle in the second. The vehicle groups were collapsed as a deprivation by replication analysis reveal no main effect of replication (F3,10=1.033, p=0.419).

Experiment 3

In Experiment 3 (Table 3) rats, 23h food deprived, were trained to press a lever to gain access to a second, lever, a single press on which delivered a sucrose pellet. Rats were trained prior to surgery for cannula implantation, then after surgery rats were retrained on the final schedule for 2 days. At test rats were then maintained 23h deprived and allowed to consume the sucrose after an infusion of CTOP (N=7), ICI 174,864 (N=5), GNTI (N=7) or vehicle (N=13) into the BLA. The following day the effect of this revaluation on seeking was tested in a non-rewarded test, conducted off drug in the same 23h deprived state. After retraining for 2 days the testing sequence was repeated but with rats being re-exposed to the outcome 3h food deprived following the same drug treatment (the opportunity for negative incentive learning). The effect of this negative incentive learning manipulation on reward seeking actions was then evaluated in a non-rewarded test, conducted in the same 3h deprived state off drug.

Similar to Experiment 2, Experiment 3 was run in 2 replications with the effects of ICI 174,864 and CTOP being compared against vehicle in the first and the effects of GNTI and vehicle compared in the second. The vehicle groups were collapsed as a deprivation by replication analysis revealed no main effect of replication (F3,11=0.232, P=0.640).

Experiment 4

In Experiment 4 rats, 23h food deprived, were trained to press a lever to gain access to a second, lever, a single press on which delivered sucrose. Rats were trained prior to surgery, then after surgery they received 2 days of training on the final chain schedule. At test rats were maintained 23h deprived and allowed to consume the sucrose after an infusion of either DAMGO (N=12), or vehicle (N=11) into the BLA. The following day the effect of the revaluation on seeking was tested in a non-rewarded test in the 23h food-deprived state. After retraining for 2 days the testing sequence was repeated but with rats being re-exposed to the outcome 3h food deprived following the same drug treatment and then tested 3h food deprived, off drug, in the non-rewarded test.

Drug administration

All drugs were obtained from Tocris Bioscience (Ellisville, MI) and were dissolved in sterile water vehicle and infused bilaterally into the BLA in a volume of 0.5 µl over 1 min via an injector inserted into the guide cannula fabricated to protrude 1 mm ventral to the tip using a microinfusion pump. Injectors were left in place for at least 1 additional min to ensure full infusion. Immediately thereafter rats were placed in operant boxes for the non-contingent delivery of sucrose pellets. The doses of the CTOP (1µg), a mu-selective agonist, ICI 174,864 (10µg), a delta-selective opioid receptor inverse agonist (Cotton et al., 1984) and GNTI (0.5µg), a kappa-specific opioid receptor antagonist (Jones and Portoghese, 2000) were selected on the basis of their affinities for their respective receptors (CTOP: 9.7pKi, ICI 174,864: 7.4pKi, GNTI: 9.9 pKi), and our previous work with the non-selective opioid receptor antagonist naloxone (pKi of 9.0, 7.2 and 8.0 at the mu, delta and kappa receptor, respectively), which when infused into the BLA at a dose of 1µg was shown to block positive incentive learning (Wassum et al., 2009). The dose of DAMGO (0.1µg) a mu-selective agonist (8.7pKi) was selected based on previous evidence of this dose being affective in reward-related behaviors (Mahler and Berridge, 2009).

Data analysis

Lever pressing data are presented as a percentage of baseline response rates, with the baseline being the average of the rate of performance during the last 2 training sessions prior to the test. For the results of Experiment 1 (Figure 2) the seeking response rate data, normalized to baseline levels, were analyzed with a 2-way repeated measure ANOVA with within subjects variable deprivation (control 3h deprived v. 23h deprived) and between subjects variable exposure. Bonferroni post hoc analyses, correcting for multiple comparisions, were used to evaluate the effects of deprivation within each exposure group. Within the exposed group we then looked at the effects of deprivation over the time course of the unrewarded test with a 2-way repeated measures ANOVA with within subjects variables deprivation and time bin (separating 5, 1 min bins).

Figure 2
An opportunity for incentive learning is required for food deprivation to affect reward seeking actions

For the results of Experiment 2 (Figure 3), Experiment 3 (Figure 4) and Experiment 4 (Figure 5) data were analyzed, separately for each experiment, with a 2-way repeated measures ANOVA with within-subjects variable deprivation state (3h v 23h deprived), and between-subjects variable drug treatment (Experiment 2 & 3: vehicle, ICI 174,864, GNTI and CTOP; Experiment 4: vehicle and DAMGO). Bonferroni post hoc analyses, controlling for multiple comparisons, were then run on these data to compare the effect of deprivation within each drug group, and then separately to compare the effect of drug within the 3h and 23h food deprived conditions. We then conducted 3 additional 2-way ANOVAs combining data from Experiments 2 and 3 and separating out drug treatment. For each of the 3 drug treatments, a 2-way ANOVA was run with within-subjects variable deprivation state and between-subjects variable direction of state change (either an upshift or downshift in hunger state). For all hypothesis tests the alpha level for significance was set to p<0.05.

Figure 3
Intra-BLA CTOP, but not ICI 174,864 or GNTI blocks positive incentive learning
Figure 4
Neither intra-BLA CTOP, ICI 174,864 nor GNTI affects negative incentive learning
Figure 5
Intra-BLA DAMGO affects negative incentive learning

In several cases a manipulation, such as drug treatment, was critically found to have no effect on lever press actions. In these select cases, we computed Bayes Factors for use in supporting the null hypothesis (Gallistel, 2009; Rouder et al., 2009) using a freely-available Bayes Factor calculator (http://pcl.missouri.edu/bayesfactor) (Rouder et al., 2009). This analysis has been argued to provide an appropriate method for expressing a preference for the null hypothesis (Gallistel, 2009; Rouder et al., 2009).

Histology

Histology was conducted as described previously (Corbit et al., 2007). Rats with miss-directed cannulae (N=4) were removed from the data analysis. See Figure 1 for cannula placements.

Figure 1
Schematic representation of the placement of injector tips for basolateral amygdala infusions

Results

Experiment 1: Changes in reward seeking actions require an opportunity for incentive learning

As illustrated in Table 1, Experiment 1 was conducted in three phases involving initial training (3h food deprived), opportunity for incentive learning, or unexposed control, and test. All rats acquired and maintained lever-pressing performance and, in the final session of training, performed the seeking lever response at a rate of 5.73 (sem 1.31), and 5.64 (0.84) presses per min in the unexposed and exposed groups, respectively.

The effects of exposure to the reward in an increased deprivation state on subsequent seeking actions are represented in Figure 2. As has been previously shown (Balleine et al., 1995; Corbit and Balleine, 2003), changes in response rate on the seeking lever only occurred in rats given an opportunity for incentive learning (re-exposure). Incentive learning occurs when an animal experiences a reward in an altered state (Dickinson and Balleine, 1994; Balleine, 2001; Dickinson and Balleine, 2002; Balleine and Killcross, 2006). Therefore, exposure to the sucrose pellet reward in an increased hunger state (23h food deprived) provides an opportunity for incentive learning, while exposing the rat to the operant context, but not to the sucrose reward, should not allow for any incentive learning. An increase in seeking actions after exposure to the sucrose when in the heightened (23h) food deprived state would suggest that the incentive value of the sucrose was increased as a consequence of that experience, and that this information was used to direct subsequent reward seeking actions (Balleine, 1992; Balleine et al., 1995).

Analysis of the data from Figure 2A shows a main effect of deprivation state (F1,27=4.97, p=0.03), no effect of exposure (F1,27=0.04, p=0.82) and a marginal exposure × deprivation interaction (F1,27=3.15, p=0.08). Most importantly, Bonferroni post hoc analysis reveals a significant increase in response rate in the 23h deprived condition over the 3h control condition for the exposed (p<0.05), but not the unexposed group (p>0.05). Moreover, Bayes factor analysis (Gallistel, 2009; Rouder et al., 2009) of the seeking data from the unexposed group indicates that the null hypothesis, that there is no difference in seeking response rate between the 3h and 23h tests, is 4.89 times more likely than the alternate hypothesis.

The incentive learning account is further supported by analysis of the seeking data over the time-course of the non-rewarded test which demonstrates that the exposure effect persists throughout the non-rewarded test. In the unexposed (Figure 2B), group there is no main effect of deprivation (F1,14=0.14, p=0.71), or time (F4,11=1.12, p=0.39), or an interaction between these factors (F4,11=0.80, p=0.55). In the exposed group (Figure 2C), however, there is a significant main effect of deprivation (F1,13=6.15, p=0.03), with no main effect of time (F4,10=2.50, p=0.11), and no interaction between these factors (F4,10=0.47, p=0.76).

Taken together these data indicate that a motivational state change alone will not significantly impact reward seeking responses. A change in reward seeking response rate resulting from a change in motivational state requires exposure to the reward in the changed state, i.e. incentive learning. This effect is sustained across the duration of the test. Reward seeking responses are therefore reflective of incentive learning.

Experiment 2: Mu, but not delta or kappa opioid receptor blockade blocks positive incentive learning

As illustrated in Table 2, this experiment was conducted in three phases involving initial training (3h food deprived), incentive learning and test. All of the rats acquired and maintained lever pressing performance, and, in the final session of training, performed the seeking lever response at a rate of 5.09 (sem 0.95), 4.94 (0.51), 5.94 (0.96) and 7.17 (2.45) presses per min in the vehicle, ICI 174,864, GNTI and CTOP groups, respectively.

The effects of specific opioid receptor blockade on positive incentive learning are represented in Figure 3. An increase in seeking actions 1 day after exposure to the sucrose when in the heightened (23h) food deprived state would suggest that the incentive value of the sucrose was increased as a consequence of that experience, and that this information was used to direct subsequent reward seeking actions (Balleine, 1992; Balleine et al., 1995). A clear incentive learning effect on reward seeking actions was indeed observed in rats given vehicle infusion into the BLA. This incentive learning effect was also seen in rats given infusion of ICI 174,864 or GNTI to block delta and kappa opioid receptors, respectively, during the incentive learning revaluation phase. Importantly however, the incentive learning effect was not apparent in the rats given intra-BLA CTOP to block mu opioid receptors.

Statistical analysis of these data (Figure 3) reveals no main effect of drug (F3,31=0.73, p=0.54), but does show a significant effect of deprivation (F1,31=18.86, p=0.0001) and, importantly, a significant drug × deprivation interaction (F3,31=3.36, p=0.03). Post hoc analyses indicate that the positive incentive learning effect on reward seeking actions is significant in the vehicle (p<0.01), ICI 174,864 (p<0.05) and GNTI (p<0.05), but not CTOP (p>0.05) treated groups. Moreover, additional post hoc analysis reveals that seeking response rate in the 23h condition is significantly lower than vehicle for the CTOP (p<0.01), but not ICI 174,864 or GNTI groups (p>0.05). Bayesian analysis (Gallistel, 2009; Rouder et al., 2009) lends additional credence to the finding that intra-BLA CTOP blocked the positive incentive learning effect; the null hypothesis that there was no difference in seeking responses in the 3h and 23h conditions when re-exposed under CTOP was found to be 3.07 times more probable than the alternative hypothesis. Interestingly, the effect of CTOP was limited to learning about the value increase as intra-BLA CTOP had no affect in the 3h food deprived condition (p>0.05, compared to vehicle), indicating that exposure to the sucrose outcome in the control 3h deprived state under intra-BLA CTOP did not affect sucrose incentive value per se, but rather acted to block the increase in value brought about by a positive shift in motivational state.

This effect of CTOP to block positive incentive learning as measured in reward seeking actions was mirrored in the magazine entries during the re-exposure incentive learning experience (Table 4). Statistical analysis of the magazine entry rate data collected during the re-exposure show a significant effect of deprivation on magazine entry rate (F1,29=27.65, p<0.0001), with no significant effect of drug (F3,29=0.88, p=0.46). There was, however, a marginal drug × deprivation interaction (F3,29=2.65, p=0.07). Separate analysis of each drug group compared to vehicle reveals a significant effect of deprivation (ICI: F1,16=28.22, p<0.0001; GNTI: F1,17=28.58, p<0.0001), with no main effect of drug (ICI: F1,16=0.04, p=0.83; GNTI: F1,17=2.11, p=0.16) and no interaction between these factors (ICI: F1,16=0.02, p=0.88; GNTI: F1,17=2.32, p=0.15) for the ICI 174,864 and GNTI groups. When comparing magazine entry rate between the vehicle and CTOP-treated rats there is a significant effect of deprivation (F1,16=9.75, p=0.006), with no effect of drug (F1,16=0.002, p=0.96), but a significant interaction between these factors (F1,16=5.77, p=0.03). Post hoc analysis confirms that there is a significant increase in magazine entry rate when 23h deprived in the vehicle (p<0.001), but not CTOP (p>0.05) treated groups. Importantly, despite the lack of increase in the magazine entry rate for the CTOP group all pellets were consumed during the re-exposure, ensuring that these rats did still have the opportunity for incentive learning. These data suggest that increasing food deprivation resulted in rats checking the magazine more often and that this was not affected by the delta or kappa opioid receptor antagonist, but was blocked by the mu opioid receptor antagonist.

Table 4
Magazine entry rate during the re-exposure incentive learning opportunity.

Experiment 3: Neither mu, delta nor kappa opioid receptor blockade affects negative incentive learning

As illustrated in Table 3, Experiment 3 was conducted in three phases involving initial training (23h food deprived), incentive learning and test. All of the rats acquired and maintained lever pressing performance, and, in the final session of training, performed the seeking lever response at a rate of 23.28 (sem 2.57), 24.59 (2.48), 23.34 (4.87) and 24.20 (3.80) presses per min in the vehicle, ICI 174,864, GNTI and CTOP groups, respectively.

The effects of specific opioid receptor blockade on negative incentive learning are represented in Figure 4. A clear negative incentive learning effect was observed in rats given vehicle, ICI 174,864 and GNTI infusion into the BLA. Contrary to the result of Experiment 2, the negative incentive learning effect was also apparent in the rats given intra-BLA CTOP to block mu opioid receptors.

Statistical analysis of these data reveals a significant effect of deprivation (F1,28=62.23, p<0.0001), but importantly no main effect of drug (F3,28=2.154, p=0.17), or significant drug × deprivation interaction (F3,28=0.33, p=0.80).

As with Experiment 2, the effects of ICI 174,864, GNTI and CTOP on subsequent reward seeking actions were mirrored in the magazine entry rate during the actual re-exposure (Table 4). Statistical analysis of the magazine entry rate show a significant effect of deprivation (F1,28=30.51, p<0.0001), with no main effect of drug (F3,28=0.60, p=0.61), or interaction between these factors (F3,28=0.45, p=0.71). These data suggest that decreasing food deprivation resulted in rats checking the magazine less often and that this was not affected by drug treatment.

Further statistical support for a selective effect of CTOP on positive versus negative incentive learning is derived from combined analyses of the data from both Experiments 1 and 2 with separate 2-way ANOVAs for each drug group. These analyses reveal a significant effect of deprivation (either from 3h control to 23h to increase value or from 23h control to 3h to decrease value), with no significant interaction between the effect of deprivation and the directional change (either increasing or decreasing) in the vehicle, ICI 174,864 and GNTI-treated groups (Vehicle: Deprivation F1,25=20.53, p=0.0001, Deprivation × Value Change F1,25=2.03, p=0.17; ICI 174,864: Deprivation F1,9=20.47, p=0.001, Deprivation × Value Change F1,9=1.71, p=0.22; GNTI: Deprivation F1,13=17.67, p=0.001, Deprivation × Value Change F1,13=1.74, p=0.21). However, in the intra-BLA CTOP group there is no significant effect of deprivation (F1,12=0.98, p=0.31), but rather a significant deprivation × value change interaction (F1,12=12.07, p=0.005), indicating that CTOP blocked learning that the value of the outcome had increased, but not that it had decreased.

Experiment 4: A mu opioid receptor agonist attenuates negative incentive learning

Having shown, in Experiment 2, that blockade of BLA mu opioid receptors blocked the effects of positive incentive learning on reward seeking and, in Experiment 3, that mu opioid receptor blockade did not affect negative incentive learning, we next wanted to explore the possibility that infusion of a mu opioid receptor agonist into the BLA may attenuate negative incentive learning. Experiment 4 was conducted in three phases involving initial training (23h food deprived), incentive learning and test. All of the rats acquired and maintained lever pressing performance, and, in the final session of training, performed the seeking lever response at a rate of 16.48 (sem 2.12) and 16.79 (1.36) presses per min in the vehicle and DAMGO groups, respectively.

The effects of the specific opioid receptor agonist, DAMGO, on negative incentive learning are represented in Figure 5. A clear negative incentive learning effect was observed in rats given vehicle, but this effect was attenuated in animals receiving intra-BLA infusion of DAMGO. Statistical analysis of these data reveals a significant effect of deprivation (F1,21=15.66, p=0.0007), but no main effect of drug (F1,21=1.27, p=0.27). Importantly, there was a significant drug × deprivation interaction (F1,21=4.34, p=0.049). Post hoc analyses clarify this interaction to show that there was a significant decrease in reward seeking response rate in the vehicle-(p<0.001), but not DAMGO- (p>0.05) treated rats when shifting from 23h to 3h food deprivation. DAMGO also appeared to have an effect alone to lower seeking response rates in the control 23h condition, but this was not significant by separate post hoc analysis (p>0.05).

Although intra-BLA DAMGO blocked the effect on subsequent reward seeking of experiencing the reward in a lower deprivation state, it did not as robustly attenuate the decrease in checking for the sucrose pellets during the incentive learning phase (Table 4). Statistical analysis of the magazine entry rate during the re-exposure show a significant effect of deprivation (F1,21=2.25, p=0.001), with no main effect of drug (F1,21=0.77, p=0.38), or interaction between these factors (F1,21=0.16, p=0.68). These data suggest that decreasing food deprivation resulted in rats checking the magazine less often and this was not affected by drug treatment. Although intra-BLA DAMGO was shown to block the effects of negative incentive learning on reward seeking, the lack of a significant interaction between drug and deprivation on magazine entries suggests that DAMGO did not as robustly attenuate the decrease in checking for the sucrose pellets.

Discussion

The present results extend the previous finding that endogenous opioids in the BLA mediate the assignment of incentive value (Wassum et al., 2009) in three significant ways. First, it is evident from these data that endogenous activation of opioid receptors in the BLA mediates the encoding of positive, but not negative shifts in value: opioid receptor blockade during revaluation, whilst preventing the increase in reward seeking following experience of the reward in a heightened motivational state (hunger) (Figure 3), had no influence on the reduction in reward-seeking actions induced by experience of the reward in a decreased motivational state (Figure 4). Second, this action of endogenous opioids in the BLA appears to be specifically mediated by mu opioid receptors (Figure 3). Third, decreases in endogenous opioid transmission may mediate the encoding of negative shifts in reward value as exogenous activation of the mu opioid receptor attenuated the reduction in reward seeking actions induced by experience of the reward in a decreased motivational state, i.e. blocked negative incentive learning (Figure 5).

The mediation of the incentive learning function by BLA endogenous opioid peptides specifically via the mu sub-type of opioid receptors, despite the presence of mu, delta and kappa receptors in this nucleus (Le Merrer et al., 2009) parallels the well-documented involvement of this receptor in the consummatory component of the reward experience. However, such consummatory hedonic effects are mediated outside of the BLA, primarily in the ventral pallidum and nucleus accumbens shell (Pecina and Berridge, 2005; Smith and Berridge, 2005, 2007; Wassum et al., 2009). Indeed, naloxone-induced blockade of opioid receptors in the BLA during reward revaluation was shown to prevent the increase in future reward-seeking despite having no effect on the increase in the palatability-related hedonic experience induced by the motivational state change (Wassum et al., 2009). Although the concept that reward ‘liking’ and cue-induced reward ‘wanting’ are dissociable processes has been established for some time (Robinson and Berridge, 1993; Berridge and Robinson, 2003; Pecina et al., 2003), these data established that reward ‘liking’ and the process by which the value of a reward is updated to drive un-cued instrumental actions, i.e. incentive learning, are also dissociable. Taken together with the current data, it appears that endogenous activation of mu opioid receptors mediates not only the affective qualities of reward consumption (in the nucleus accumbens shell and ventral pallidum), but also, independently (in the BLA), the process by which positive, but not negative changes in the incentive value of rewards are encoded. As BLA circuitry per se has been implicated in incentive learning, generally (Balleine et al., 2003; Corbit and Balleine, 2005; Wang et al., 2005; Ostlund and Balleine, 2008), it appears, that within BLA circuits mediating the assignment of incentive value there is a mechanism for encoding the valence of the reward shift. The current observation that intra-BLA administration of the mu agonist, DAMGO, attenuated negative incentive learning induced by a downward shift in hunger state suggests that this may simply be achieved by up- or downward shifts in endogenous opioid tone, with the latter facilitating negative incentive learning.

It is possible that, rather than encoding of incentive value per se, endogenous opioid transmission in the BLA may be necessary for mediating the association that is formed between interoceptive hunger state cues and the heightened affective experience with the reward, an account that we are pursuing in ongoing experiments. As systemic opioid antagonists have been shown to produce a taste aversion-like effect (Parker and Rennie, 1992), it is also possible that the observed effects of intra-BLA mu opioid receptor antagonism on positive incentive learning could also result from competition between conditioned aversion and incentive learning. This account is unlikely, however, as re-exposure to the sucrose outcome under intra-BLA CTOP did not alone affect subsequent reward seeking actions in the unrewarded test (Figure 3 and and4-4- open bars), i.e. intra-BLA CTOP/sucrose outcome pairings did not produce the devaluation effect that would be predicted by the conditioned taste aversion hypothesis.

An additional alternate interpretation of our data is that, as the opportunity for incentive learning was conducted in the same context as training and test, intra-BLA CTOP may have altered the Pavlovian incentive value of the context, and in so doing blocked the increase in reward seeking actions detected during the non-rewarded test of incentive learning. However, contextual control is not necessary for the effects of incentive learning to be expressed in reward seeking actions (Balleine et al., 1995) and responding on the seeking component of the heterogeneous seeking-taking chain has previously been shown to be relatively immune to Pavlovian influences (Corbit and Balleine, 2003), rendering this account similarly unlikely. Moreover, intra-BLA CTOP did not degrade the context-reward association under control conditions, as evidenced by no change in reward seeking in the intra-BLA CTOP group, relative to vehicle group in the control condition (either 3h in Experiment 2, or 23h in Experiment 3). The near complete blockade of the incentive learning effect by intra-BLA CTOP suggests that mu opioid receptors are involved in the process by which the instrumental incentive value of the outcome is increased. Nonetheless, the possibility that mu opioid receptors in the BLA are important for the effects of cues on instrumental performance will be assessed in subsequent experiments employing a more targeted Pavlovian to instrumental transfer design.

Interesting in this context is the observation of Mahler and Berridge (2009) that mu opioid receptor activation in the central nucleus of the amygdala enhances the effect of a reward-paired cue on approach to either the cue itself or the food source, i.e. it enhanced and focused cue-induced reward ‘wanting’, to use the authors’ terminology (Mahler and Berridge, 2009). Earlier studies have also shown that the central nucleus of the amygdala is necessary for the general motivational influence of reward-related cues on action performance, whereas the BLA is involved in more reward-specific incentive processes and instrumental incentive learning (Balleine et al., 2003; Corbit and Balleine, 2005; Dwyer and Killcross, 2006). These findings, taken with our current results, begin to elucidate an anatomically dissociable neuromodulatory role of mu opioid receptor activation in reward ‘liking’ (Pecina and Berridge, 2005; Smith and Berridge, 2005, 2007), cue-induced generalized reward ‘wanting’ (Mahler and Berridge, 2009), and the performance of un-cued specific incentive value-driven actions described herein, involving the ventral pallidum/nucleus accumbens shell, amygdala central nucleus and BLA, respectively. Given that not only opiates, but also palatable foods, cocaine, alcohol, cannabinoids and nicotine have been shown to acutely and chronically influence the activity of the endogenous opioid systems (Unterwald et al., 1994; Turchan et al., 1998; Turchan et al., 1999; Berrendero et al., 2002; Smith et al., 2002; Fattore et al., 2004; Oswald and Wand, 2004; Berrendero et al., 2005; Ziolkowska et al., 2006), the separable role of these peptides in these three aspects of reward processing may underlie the intensely addictive property of these substances. Moreover, as the current data indicate that opioid receptor activation in the BLA facilitates encoding of increases in incentive value, while reduced opioid transmission may underlie encoding of decreased incentive value, this could explain how use of addictive substances can result in aberrant drug seeking; the incentive value of the drug becomes enhanced with simultaneous overshadowing of the negative aspects of drug use that should otherwise lead to devaluation of the drug and a concomitant reduction in drug seeking. Targeting these anatomically dissociable mu opioid receptor-mediated processes may provide treatments for these addictive disorders that improve the integration of emotional and cognitive processes to result in more appropriate decision-making.

Acknowledgments

This research was supported by grants DA09359 and DA05010 from NIDA to Nigel Maidment, grants MH56446 from NIMH and AA18014 from NIAAA to Bernard Balleine, and a Ruth L. Kirschstein National Research Service Award DA023774 and Hatos scholarship to Kate Wassum.

References

  • Balleine B. Instrumental performance following a shift in primary motivation depends on incentive learning. J Exp Psychol Anim Behav Process. 1992;18:236–250. [PubMed]
  • Balleine B. Incentive processes in instrumental conditioning. In: Mowrer RaK S, editor. Handbook of Contemporary Learning Theories. Hillsdale, New Jersey: Erlbaum; 2001. pp. 307–366.
  • Balleine B, Paredes-Olay C, Dickinson A. Effects of Outcome Devaluation on the Performance of a Heterogeneous Instrumental Chain. International Journal of Comparative Psychology. 2005;18:257–272.
  • Balleine BW, Dickinson A. Goal-directed instrumental action: contingency and incentive learning and their cortical substrates. Neuropharmacology. 1998;37:407–419. [PubMed]
  • Balleine BW, Killcross S. Parallel incentive processing: an integrated view of amygdala function. Trends Neurosci. 2006;29:272–279. [PubMed]
  • Balleine BW, Killcross AS, Dickinson A. The effect of lesions of the basolateral amygdala on instrumental conditioning. J Neurosci. 2003;23:666–675. [PubMed]
  • Balleine BW, Garner C, Gonzalez F, Dickinson A. Motivational control of heterogeneous instrumental chains. J Exp Psychol Anim Behav Process. 1995;21:203–217.
  • Balleine BW, Garner C, Gonzalez F, Dickinson A. Motivation control of heterogenous instrumental chains. Journal of Experimental Psychology: Animal Behavior Processes. 1995;21:203–217.
  • Berrendero F, Kieffer BL, Maldonado R. Attenuation of nicotine-induced antinociception, rewarding effects, and dependence in mu-opioid receptor knock-out mice. J Neurosci. 2002;22:10935–10940. [PubMed]
  • Berrendero F, Mendizabal V, Robledo P, Galeote L, Bilkei-Gorzo A, Zimmer A, Maldonado R. Nicotine-induced antinociception, rewarding effects, and physical dependence are decreased in mice lacking the preproenkephalin gene. J Neurosci. 2005;25:1103–1112. [PubMed]
  • Berridge KC. The debate over dopamine's role in reward: the case for incentive salience. Psychopharmacology (Berl) 2007;191:391–431. [PubMed]
  • Berridge KC, Robinson TE. Parsing reward. Trends Neurosci. 2003;26:507–513. [PubMed]
  • Corbit LH, Balleine BW. Instrumental and Pavlovian incentive processes have dissociable effects on components of a heterogeneous instrumental chain. J Exp Psychol Anim Behav Process. 2003;29:99–106. [PubMed]
  • Corbit LH, Balleine BW. Double dissociation of basolateral and central amygdala lesions on the general and outcome-specific forms of pavlovian-instrumental transfer. J Neurosci. 2005;25:962–970. [PubMed]
  • Corbit LH, Janak PH, Balleine BW. General and outcome-specific forms of Pavlovian-instrumental transfer: the effect of shifts in motivational state and inactivation of the ventral tegmental area. Eur J Neurosci. 2007;26:3141–3149. [PubMed]
  • Cotton R, Giles MG, Miller L, Shaw JS, Timms D. ICI 174864: a highly selective antagonist for the opioid delta-receptor. Eur J Pharmacol. 1984;97:331–332. [PubMed]
  • Dickinson A, Balleine BW. Motivational control over goal-directed action. Animal Learning and Behavior. 1994;22:1–18.
  • Dickinson A, Balleine BW. The role of learning in motivation. In: Gallistel CR, editor. Learning, Motivation and Emotion, Volume 3 of Steven's Handbook of Experimental Psychology. New York: John Wiley & Sons; 2002.
  • Ding YQ, Kaneko T, Nomura S, Mizuno N. Immunohistochemical localization of mu-opioid receptors in the central nervous system of the rat. J Comp Neurol. 1996;367:375–402. [PubMed]
  • Doyle TG, Berridge KC, Gosnell BA. Morphine enhances hedonic taste palatability in rats. Pharmacol Biochem Behav. 1993;46:745–749. [PubMed]
  • Dwyer DM, Killcross S. Lesions of the basolateral amygdala disrupt conditioning based on the retrieved representations of motivationally significant events. J Neurosci. 2006;26:8305–8309. [PubMed]
  • Fattore L, Cossu G, Spano MS, Deiana S, Fadda P, Scherma M, Fratta W. Cannabinoids and reward: interactions with the opioid system. Crit Rev Neurobiol. 2004;16:147–158. [PubMed]
  • Gallistel CR. The importance of proving the null. Psychol Rev. 2009;116:439–453. [PMC free article] [PubMed]
  • Jones RM, Portoghese PS. 5'-Guanidinonaltrindole, a highly selective and potent kappa-opioid receptor antagonist. Eur J Pharmacol. 2000;396:49–52. [PubMed]
  • Kelley AE, Bakshi VP, Haber SN, Steininger TL, Will MJ, Zhang M. Opioid modulation of taste hedonics within the ventral striatum. Physiol Behav. 2002;76:365–377. [PubMed]
  • Le Merrer J, Becker JA, Befort K, Kieffer BL. Reward processing by the opioid system in the brain. Physiol Rev. 2009;89:1379–1412. [PubMed]
  • Mahler SV, Berridge KC. Which cue to "want?" Central amygdala opioid activation enhances and focuses incentive salience on a prepotent reward cue. J Neurosci. 2009;29:6500–6513. [PMC free article] [PubMed]
  • Mansour A, Fox CA, Burke S, Meng F, Thompson RC, Akil H, Watson SJ. Mu, delta, and kappa opioid receptor mRNA expression in the rat CNS: an in situ hybridization study. J Comp Neurol. 1994;350:412–438. [PubMed]
  • Ostlund SB, Balleine BW. Differential involvement of the basolateral amygdala and mediodorsal thalamus in instrumental action selection. J Neurosci. 2008;28:4398–4405. [PMC free article] [PubMed]
  • Oswald LM, Wand GS. Opioids and alcoholism. Physiol Behav. 2004;81:339–358. [PubMed]
  • Parker LA, Rennie M. Naltrexone-induced aversions: assessment by place conditioning, taste reactivity, and taste avoidance paradigms. Pharmacol Biochem Behav. 1992;41:559–565. [PubMed]
  • Pecina S, Berridge KC. Hedonic hot spot in nucleus accumbens shell: where do mu-opioids cause increased hedonic impact of sweetness? J Neurosci. 2005;25:11777–11786. [PubMed]
  • Pecina S, Cagniard B, Berridge KC, Aldridge JW, Zhuang X. Hyperdopaminergic mutant mice have higher "wanting" but not "liking" for sweet rewards. J Neurosci. 2003;23:9395–9402. [PubMed]
  • Robinson TE, Berridge KC. The neural basis of drug craving: an incentive-sensitization theory of addiction. Brain Res Brain Res Rev. 1993;18:247–291. [PubMed]
  • Robinson TE, Berridge KC. Incentive-sensitization and addiction. Addiction. 2001;96:103–114. [PubMed]
  • Robinson TE, Berridge KC. Addiction. Annu Rev Psychol. 2003;54:25–53. [PubMed]
  • Rouder JN, Speckman PL, Sun D, Morey RD, Iverson G. Bayesian t tests for accepting and rejecting the null hypothesis. Psychon Bull Rev. 2009;16:225–237. [PubMed]
  • Smith KS, Berridge KC. The ventral pallidum and hedonic reward: neurochemical maps of sucrose "liking" and food intake. J Neurosci. 2005;25:8637–8649. [PubMed]
  • Smith KS, Berridge KC. Opioid limbic circuit for reward: interaction between hedonic hotspots of nucleus accumbens and ventral pallidum. J Neurosci. 2007;27:1594–1605. [PubMed]
  • Smith SL, Harrold JA, Williams G. Diet-induced obesity increases mu opioid receptor binding in specific regions of the rat brain. Brain Res. 2002;953:215–222. [PubMed]
  • Turchan J, Przewlocka B, Lason W, Przewlocki R. Effects of repeated psychostimulant administration on the prodynorphin system activity and kappa opioid receptor density in the rat brain. Neuroscience. 1998;85:1051–1059. [PubMed]
  • Turchan J, Przewlocka B, Toth G, Lason W, Borsodi A, Przewlocki R. The effect of repeated administration of morphine, cocaine and ethanol on mu and delta opioid receptor density in the nucleus accumbens and striatum of the rat. Neuroscience. 1999;91:971–977. [PubMed]
  • Unterwald EM, Rubenfeld JM, Kreek MJ. Repeated cocaine administration upregulates kappa and mu, but not delta, opioid receptors. Neuroreport. 1994;5:1613–1616. [PubMed]
  • Wang SH, Ostlund SB, Nader K, Balleine BW. Consolidation and reconsolidation of incentive learning in the amygdala. J Neurosci. 2005;25:830–835. [PubMed]
  • Wassum KM, Ostlund SB, Maidment NT, Balleine BW. Distinct opioid circuits determine the palatability and the desirability of rewarding events. Proc Natl Acad Sci U S A. 2009;106:12512–12517. [PubMed]
  • Wassum KM, Ostlund SB, Maidment NT, Balleine BW. Distinct opioid circuits determine the palatability and the desirability of rewarding events. Proc Natl Acad Sci U S A. 2009 [PubMed]
  • Ziolkowska B, Stefanski R, Mierzejewski P, Zapart G, Kostowski W, Przewlocki R. Contingency does not contribute to the effects of cocaine self-administration on prodynorphin and proenkephalin gene expression in the rat forebrain. Brain Res. 2006;1069:1–9. [PubMed]