In this phase, rats were trained together. The aCS+/aCS- of the actor and pCS+/pCS- of the partner were combined in three compound combinations with the following reward outcomes: both reward (BR: aCS+/pCS+), own reward (OR: aCS+/pCS-), and no reward (NR: aCS-/pCS-). In the main experiments, we chose to omit the ‘partner reward’ condition where the target rats would not receive reward, while the partner rats would (PR: aCS-/pCS+; but see unequal outcomes control), to avoid a potential reward/value conflict due to disadvantageous inequity aversion (Fehr and Schmidt, 1999), which has been reported in rats as well (Oberliessen et al., 2016). Rats’ conditioned responses to these compound cues are shown (for an example trial see Videos 2 and 3) and a direct comparison of these responses to the original aCS+ and aCS- cues was made, both indexed by time spent in the food cup and the food cup rate (Figure 2b,d,f and Figure 2—figure supplement 1) In the subsequent analysis, only the behavior of the actor rats is reported. We applied a mixed repeated measures ANOVA design with the three compound trial types (BR [partner reward (PR) for control group 2], OR, and NR) and day 1-4 as within-subject factors, and with group (experimental vs control 1 vs control 2) as between-subject factor. The time spent in the food cup during the first 10 s after the cue onset was chosen as the dependent variable. We found a significant main effect of trial type (F_{(1.568, 76.845)}=161.520, p<0.001, η_p² = 0.767) and importantly found an interaction effect of experiment * trial type (F_{(3.137, 76.845)}=28.243, p<0.001, η_p² = 0.537), reflecting the difference in experiments that employed BR versus PR trials; and no effect of day (F_{(2.223, 108.195)}=0.017, p<0.001, η_p² = 0.997). Post-hoc comparison revealed that actors’ responding to the BR cue did not differ significantly from the OR cue in experimental group 1 (mean difference = 0.490, SE = 2.367, p=1.00) and control group 1 (mean difference = 1.603, SE = 2.646, p=1.00), while in control group two responding is smaller in PR (partner reward) than OR trials (mean difference = −38.784, SE = 2.646, p<0.001). BR responding was furthermore significantly higher than NR in experimental group 1 (mean difference = 32.9840.784, SE = 2.848, p<0.001) and control group 1 (mean difference = 32.684, SE = 3.185, p<0.001), while in control group 2, PR responding was not significantly different from NR (mean difference = −1.833, SE = 3.185, p=1.00), arguing against social facilitation of conditioned responding as a social learning mechanism. Finally, OR responding was significantly higher than NR responding in all groups (experimental group 1: mean difference = 32.495, SE = 3.704, p<0.001; control group 1: mean difference = 31.081, SE = 4.141, p<0.001; control group 2: mean difference = 36.901, SE = 4.141, p<0.001). We furthermore assessed if the average compound phase food cup responses over 4 days changed in comparison to the last 4 days of discrimination learning due to the addition of pCS+ and pCS- cues. Next, we assessed if there were any between-group and within-condition differences in the compound phase food cup responses to BR, OR, and NR cues. We first ran a mixed repeated measures ANOVA analysis, with three difference scores (aCS+/aCS-, BR/NR, and OR/NR) as within-subject factors and group (experimental vs control 1 vs control 2) and stimulus type (auditory/visual) as between-subject factors (Figure 2—figure supplement 1a,b and c). We found a significant main effect of trial type (F_{(1.435, 66.017)}=35.071, p<0.001, η_p² = 0.433), we furthermore found an interaction effect of trial type * group (F_{(2.870, 66.017)}=22.188, p<0.001, η_p² = 0.491), an interaction effect of trial type * stimulus type (F_{(1.435, 66.017)}=4.286, p=0.029, η_p² = 0.085) but no effect of experiment * trial type * stimulus type (F_{(2.870, 66.017)}=1.577, p=0.187, η_p² = 0.064). Post-hoc comparison for the trial type * stimulus type interaction found that rats, over all experiments, have a significantly smaller contrast score for visual than auditory cues in the OR/NR contrast (mean difference = −10.862, SE = 4.141, p<0.001), near significantly smaller in the BR/NR (mean difference = −6.409, SE = 3,432, p=0.068) but not smaller for the aCS+/aCS- (mean difference = +1.191, SE = 4.331, p=0.785). There are furthermore no differences within-experiments between aCS+/aCS- contrast scores and BR/NR or OR/NR contrast scores in all experimental groups, arguing against a putative effect on associative learning of the compound cues due to more vigorous responding in the compound phase. The only expected differences observed here is that the PR/NR contrast in control experiment 2 is smaller than the OR/NR (mean difference = 38.784, SE = 2.532, p<0.001) and aCS+/aCS- contrast (mean difference = 38.044, SE = 3.676, p<0.001), because of the altered reward contingencies. Finally, most importantly, we do not find any differences between contrasts between different experimental groups with the only exception again for the PR/NR contrast which is lower for the control group 2 (PR) compared experimental group 1 (BR) and control group 1 (BR). We find that the observed effect of stimulus type is mostly captured by a slight shift in conditioned responding to the NR compound in comparison to the aCS- responses during discrimination learning. When running a mixed repeated measures ANOVA design, with the aCS- and NR as within-subject factors and group (experimental vs control 1 vs control 2) and stimulus type (auditory/visual), we find a triple interaction effect (Figure 2—figure supplement 1d,e and f; F(2,46) = 5.247, p=0.009, η_p² = 0.186). It becomes clear that the rats show significantly more food cup responses to the visual cues in comparisons to the auditory cues in the NR (mean difference = 18.966, SE = 3.061, p<0.001) compared to the aCS- in experimental group 1 but not in control groups 1 and 2. Conditioned responses to visual cues are furthermore higher in NR over aCS- in experimental group 1 (mean difference = 25.247, SE = 4.412, p<0.001) and near significantly higher in control group 1 (mean difference = 9.00, SE = 4.697, p=0.062) but not in control group 2.

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These results indicate that adding an additional cue predicting a BR or OR outcome does not change the conditioned response in comparison to NR during discrimination learning in the experimental and control groups. Importantly, no differences were observed between rewarded conditions indicating that partner presence does not influence food cup responses by itself. The only difference we notice is that adding a visual cue to an auditory cue leads to increased food cup response in the NR condition experimental group 1 and control group 1 but not in control group two compared to the aCS-. This could indicate a deficit in inhibitory action control of a learned auditory CS- because of partner presence, or reflect some difference in stimulus efficacy or asymmetrical processing interacting with social partner presence that cannot be entirely interpreted.

In the probe trials, we aimed to show the effect of associative learning driven by self and vicarious reward. In an extinction setting, rats were individually exposed to the cues in isolation (i.e. one at a time), omitting reward. The learned associative value of each cue was indexed by the time spent in the food cup, the food cup rate, and the latency to entry over 10 extinction trials per cue (the presentation order of cues was intermixed). We show the percentage conditioned responding of the actor rats to the first 10 s of 10 presentations each of the aCS+ and aCS-, the pCS+ (unblocked) cue (example trial in Video 4) associated with an added reward to the partner (BR) and the pCS- (blocked) cue (example trial in Video 5) associated with no additional reward to the partner (OR) and no reward to self (NR) (Figure 3a, b, c) We binned responses in groups of two trials. Summary statistics for the Figure 3 comparisons (F-stats, p-values, effect sizes), including the time spent in the food cup for the 30 s after cue onset (Figure 3d,e and f), can be found in Figure 3—source data 1.

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Probing vicarious associative learning.

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A two-factor repeated measures ANOVA with stimulus type and bin as factors and the time spent in the food trough as the dependent variable was performed for the experimental group (combined social-appetitive and social-only subgroups). To sum up, we found a significant probe phase main effect of cue type on time spent in food trough (F_{(3, 57)}=83.180, p<0.01, η_p² = 0.814). As expected, time spent in the food trough was higher for aCS+ than aCS- trials (mean difference = 37.322, SE = 2.958, p<0.001; Cohen’s d = 1.92, Figure 3a). Critically, pairwise comparisons revealed that the actors spent more time in the food trough for pCS+ (unblocked) cues than for pCS- (blocked) cues (mean difference = 10.804, SE = 2.592, p=0.003, Cohen’s d = 0.60; Figure 3a). Furthermore, we also found a significantly higher responding to the pCS+ cue compared to the aCS- cue (mean difference = 14.544, SE = 2.257, p<0.001, Cohen’s d = 0.88) while responding to the pCS- cue was not significantly different from the aCS- cue (mean difference = 3.740, SE = 1.190, p=0.390, Cohen’s d = 0.25), suggesting that the blocked cue is treated similarly to the aCS-, in line with learning theory. Additionally, we found a main effect of bin number on time spent in food trough (F_{(4, 76)}=18.678, p<0.01, η_p² = 0.496), reflecting the extinction process, and finally, we found an interaction between cue type and bin number on the time spent in food trough (F_(12,228)=2.930, p=0.001, η_p² = 0.137). Simple effects analysis revealed that the food cup response for the pCS+ was significantly higher than pCS- for bin 1 (mean difference = 17.200, SE = 5.461, p<0.032), bin 3 (mean difference = 19.360, SE = 0.007, p=0.007) but that this difference disappeared from bin 4 (mean difference = 4.830, SE = 7.076, p=1.00).

Here a similar two-factor repeated measures ANOVA with stimulus type and bin as factors and the time spent in the food trough as the dependent variable was performed for the control group 1 (combined inserted wall and no partner present subgroups). We also found a significant main effect of cue type on time spent in food trough (F_{(1.372, 20.585)}=31.215, p<0.001, η_p² = 0.675). Here we find again that the time spent in food trough was higher for aCS+ than aCS- trials (mean difference = 32.043, SE = 2.958, p<0.001; Cohen’s d = 1.91, Figure 3b). Crucially, pairwise comparisons revealed that the time actors spent in the food trough did not differ for pCS+ cues compared to pCS- cues (mean difference = 3.687, SE = 2.146, p=0.637, Cohen’s d = 0.30; Figure 3b). We did find a significantly higher responding to the pCS+ cue compared to the aCS- cue (mean difference = 7.948, SE = 1.862, p=0.004, Cohen’s d = 0.75), potentially reflecting some non-social appetitive value related to second-order conditioning, while responding to the pCS- cue was not significantly different from the aCS- cue (mean difference = 4.260, SE = 1.634, p=0.119, Cohen’s d = 0.44; Figure 3b). Additionally, we again found a main effect of bin number on time spent in food trough (F_{(1.789, 26.834)}=13.270, p<0.001, η_p² = 0.469) but no interaction between condition type and bin number on the time spent in food trough (F_{(6.029, 20.585)}=0.835, p=0.547, η_p² = 0.137).

Here a similar two-factor repeated measures ANOVA with stimulus type and bin as factors and the time spent in the food trough as the dependent variable was performed for the unequal outcomes control group. The two-factor repeated measures ANOVA revealed a significant main effect of probe trial type on time spent in food trough (F_{(1.732, 25.980)}=46.215, p<0.001, η_p² = 0.755). Again, responding was higher for aCS+ than aCS- trials (mean difference = 30.162, SE = 3.754, p<0.001; Cohen’s d = 1.76, Figure 3c). Crucially, responding to pCS+ cues did not differ from pCS- cues across the five bins of extinction (mean difference = 0.513, SE = 2.294, p=1.00, Cohen’s d = 0.04; Figure 3c). No differences were found for pCS+ cue compared to the aCS- cue (mean difference = 0.318, SE = 1.622, p=1.00, Cohen’s d = 0.02) or the pCS- cue versus the aCS- cue (mean difference = −0.195, SE = 2.100, p=1.00, Cohen’s d = −0.01; Figure 3c). As expected, we found a main extinction effect of bin number on time spent in food trough (F_{(4, 60)}=8.291, p<0.001, η_p² = 0.356) but found no interaction between condition type and bin number on the time spent in food trough (F_{(4.528, 67.915)}=1.671, p=0.160, η_p² = 0.100).

Latency scores during the probe trials for the experimental group (combined social-appetitive and social-only subgroups), control group 1 (combined inserted wall and no partner present subgroups) and the control group 2 (unequal outcomes) are shown in Figure 3—figure supplement 1 (a, b, and c). We ran a bootstrapped analysis of latency differences with N = 5000 iterations per experiment, drawing with replacement from the pCS+ and pCS- trials (according to their N) per iteration and storing the difference in mean latency between these trial type. From these distributions (Figure 3—figure supplement 1d) of mean latencies, we assessed whether these distributions differed from zero and whether they differed between experimental groups with Z-tests. We found that the latency difference scores differed from zero in the experiment group (Z = −2.79, p=0.003) but not control group 1 (Z = −0.90, p=0.18) and control group 2 (Z = 2.08, p=0.98). We furthermore found that the latency difference is bigger in the experiment group compared to the control group 1 (Z = −1.712, p=0.043, one-sided) and control group 2 (Z = −4.72, p<0.001). Finally, control group 1 has larger latency differences than control group 2 (Z = −3.16, p<0.001). We conclude from these results that the rats in the experimental groups showed shorter latencies on pCS+ than on pCS- trials but this was not the case for rats in control group 1 and control group 2. Importantly, this difference is significantly larger in the experimental group than in both control groups, further supporting the interpretation that pCS+ cues acquire associative value in the experimental group, supporting social unblocking.

Taken together, these results show that the actor rats exhibited more food cup directed behavior for the pCS+ cue than both the aCS- and pCS- cue over 10 trials of extinction in the experimental condition only. This means that when actor rats have fully learned a stimulus-reward association producing reward for themselves, adding a cue that predicted an additional reward delivery to a partner rat unblocked associative social learning (pCS+>pCS-) about this cue, putatively due to a vicarious reward experience. By contrast, rats did not spend more time in the food cup for the pCS- cue compared to the aCS-, suggesting that additional cues that did not predict vicarious reward remained blocked from acquiring associative value. Contrary to the findings for the experimental group, the rats in control groups 1 and 2 did not show such conditioned responding, indicative of acquired value for the unblocked pCS+ cue, over 10 trials of extinction. This suggests that acquiring associative social value in this unblocking experiment requires social information exchange (control group: inserted wall) and/or the presence of a partner (control group: no partner present). Interestingly, disadvantageous unequal reward distributions putatively modulated the vicarious reward experience, impeding the unblocking effect. Our results reflect that cues related to mere reward delivery have to be controlled for, as witnessed by the pCS+ over aCS- difference even in the control experiments, highlighting the need for an active blocking control cue (pCS-) as implemented here.

We conclude from the simple effects analyses on the interaction effects in the experimental group that the associative value of unblocked novel cues can be measured for approximately six trials in extinction and will use this analysis window going forward. First, we extended the previous analyses with a mixed repeated measures ANOVA design with trial type (aCS+, pCS+ [unblocked], pCS- [blocked], aCS-) and trial 1–6 (bin 1–3) as within-subject factors and group (experimental group 1 vs control group 1 [a and b] vs control group 2) as between-subject factor. Performing this analysis for both 10 s and 30 s period, we found that rats exhibited more food cup directed behavior for the pCS+ cue than both the pCS- cue over six trials of extinction in the experimental group 1 and not control groups 1 and 2 (see Figure 3—source data 1).

To directly contrast the unblocking effect between the experimental and control conditions, we calculated difference scores (Figure 4) for the direct comparison of the aCS+/aCS-, pCS+/pCS-, pCS+/aCS-, and pCS-/aCS- trial types, and tested for difference in these contrasts between experimental groups. Summary statistics for the Figure 4 comparisons (F-stats, p-values, effect sizes) can be found in Figure 4—source data 1. We would expect no difference in the initial discrimination learning contrast, aCS+/aCS- tested in extinction, between groups. Indeed, in a two-way repeated measures ANOVA, we found no significant main (within-subject) effect of trial number on this contrast (F_{(4.016, 8.032)}=5.96, p=0.666) and no interaction effect (F_(10,130) = 0.460, p=0.914). Importantly, we did not find evidence for a between-subjects effect of group (F_{(2, 49)}=1.859, p=0.167, η_p² = 0.071; Figure 4a). The aCS+/aCS- contrast score of the experimental group was not higher than control group 1 (mean difference = 11.242, SE = 6.363, p=0.251) and control group 2 (mean difference = 9.400, SE = 6.363, p=0.438). When directly comparing the unblocked/blocked (pCS+/pCS-) contrast between groups, we did expect to find a between-subject group effect. Indeed, when we examined the difference scores of the pCS+/pCS- contrast with a two-way repeated measures ANOVA with group (experimental, control) and trial 1-6 as factors, we found a significant main (between-subject) effect of group (F_{(2, 49)}=6.397, p=0.003, η_p² = 0.207; Figure 4b). This analysis revealed that the percent difference in responding between pCS+ and pCS- cues was higher for the experimental group than the control group 1 (mean difference = 12.903, SE = 4.531, p=0.019) and control group 2 (mean difference = 14.520, SE = 4.531, p=0.007). We found no within-subject effect of trial number (F_{(4.111, 8.222)}=0.627, p=0.680, η_p² = 0.013), suggesting that the difference is relatively stable across trials, and no interaction (F_(5, 130) = 1.090, p=0.370, η_p² = 0.043). In the contrast analysis for the 30 s period, we also found a significant main (between-subject) effect of group for the pCS+/pCS- contrast (F_{(2, 49)}=5.976, p=0.005, η_p² = 0.196; Figure 4f), revealing that the percent difference in responding between pCS+ and pCS- cues was significantly higher (one-sided) for the experimental group than control group 1 (mean difference = 8.278, SE = 3.478, p=0.064) and significantly higher than control group 2 (mean difference = 11.493, SE = 3.478, p=0.005). As expected, also for the 30 s period, the aCS+/aCS- revealed no main (between-subject) effect of group (F_{(2, 49)}=1.251, p=0.295, η_p² = 0.049; Figure 4e). Results from the full contrast analyses for the pCS+/aCS- and pCS-/aCS- can be found in Table S1. We conclude from these results that the pCS+, predicting partner reward in a BR compound, became unblocked and acquired associative value in the experimental group but not in control groups 1 and 2, as witnessed by a significantly larger unblocked versus blocked contrast in the experimental versus control groups for both the first 10 s after cue onset and the whole 30 s period. We attribute this differential social unblocking effect to a putative difference in experienced vicarious reward. The control conditions, impeding social information exchange (control group; inserted wall) and/or the absence of the partner rat (control group; no partner present) presumably attenuated vicarious reward experience. In addition, disadvantageous unequal reward distributions did not lead to unblocking, suggesting that such distributions do not reflect vicarious reward experiences for our rats, in line with previous behavioral evidence of inequity aversion.

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Figure 4—source data 1

Strength of the social unblocking effect over trials.

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Burke et al., 2008 found that changing the sensory identity (flavor) of an outcome associated with an added cue in a compound also unblocked this cue and that this identity unblocking was captured by scoring the food cup rate, for example, the frequency or number of entries into the food cup irrespective of the total duration of visits. In our paradigm, social unblocking could also be interpreted as a reward identity switch in that the additional partner outcome changes the sensory aspects of the reward by virtue of the partner receiving and eating the rewards. Food cup rate in the probe trials, next to food cup occupancy, could therefore potentially reflect model-based reward identity unblocking and therefore could provide insight in the influence of sensory features of social unblocking. Alternatively, if the additional partner reward is interpreted solely as a change in value but not identity, we would hypothesize that food cup rate would not be affected.

To further explore the food cup rate as a measure of the potential identity unblocking effect in the experimental versus control condition, we applied the same a mixed repeated measures ANOVA design with trial type (aCS+, pCS+ [unblocked], pCS- [blocked], aCS-) and bin 1–3 as within-subject factors and group (experimental [N = 20] vs control 1 [N = 16] vs control 2 [N = 16]) as between-subject factor with food cup rate per minute for the first 10 s after the cue onset as dependent variable. We found a significant main effect of trial type (F_{(1.761, 86.275)}=78.460, p<0.001, η_p² = 0.616) and an effect of bin (F_{(1.953, 5.713)}=21.9968, p<0.001, η_p² = 0.310). We also find an interaction effect of experiment * trial type (F_{(3.52, 86.275)}=5.033, p=0.002, η_p² = 0.170). Post-hoc comparison revealed here as well that the food cup rate was significantly higher for pCS+ cue in comparison to the pCS- cue in the experimental group (mean difference = 3.883, SE = 1.207, p=0.014; Figure 3g) but not in control group 1 (mean difference = 1.500, SE = 1.350, p=1.00; Figure 3h) and not in control group 2 (mean difference = −0.062, SE = 1.350, p=1.00; Figure 3i). Interestingly, we furthermore find that the food cup rate for the pCS+ cue is significantly higher than the aCS- in both the experimental group (mean difference = 5.683, SE = 1.074, p<0.001; Figure 3g) and control group 1 (mean difference = 5.125, SE = 1.200, p=0.001; Figure 3h) but not in control group 2 (mean difference = 0.438, SE = 1.200, p=1.00; Figure 3i). These results could potentially indicate that the actor rats had a clear idea that the identity of the US food rewards in BR trials had changed, even though in the inserted wall control group where information exchange is impeded and/or in the no partner present control group where the partner is absent. We can conclude that identity unblocking as measured by the number of entries into the food cup is also present in this task and that the sensory aspects of the additional partner presence are necessary to associate the novel cue with positive social associative value (BR >OR).

During the compound phase in the experimental group and the control group inserted wall, the partner rat learns to associate another set of outcomes to the compound cues (Figure 5b,e): Both reward (BR: pCS+, aCS+), actor reward (OR: pCS-, aCS+) and no reward (NR: pCS-, aCS-) after going through discrimination learning (Figure 5a,d). For the partner, learning about the aCS+ cue is thus confounded by being paired with two qualitatively different outcomes: from the perspective of the partner, it represented both a mutual reward outcome and an unequal disadvantageous reward outcome. It is thus likely that the aCS+ cue value would be increased due to the BR associated value but at the same time decreased due to the disadvantageous unequal outcome on OR trials. We tested whether the aCS+, associated with these multiple types of partner-own-reward outcomes, still showed evidence of unblocking by performing a two-factor repeated measures ANOVA with stimulus type and trial 1-6 as factors and the time spent in the food trough as the dependent variable. For the experimental group 1, we found a significant main effect of probe trial condition on time spent in food trough (F_{(1.551, 29.472)}=79.840, p<0.001, η_p² = 0.808). As expected, time spent in food trough was higher for pCS+ than pCS- trials (mean difference = 39.00, SE = 3.774, p<0.001, Figure 5c), reflecting the partner’s initial discrimination learning. However, critically, pairwise comparisons revealed that the partners time spent in food trough was not higher for aCS+ cues compared to aCS- cues across six trials (mean difference = 3.530, SE = 1.691, p=0.303; Figure 5c). Furthermore, to see whether the absence of social information exchange (inserted wall control group) would influence partner learning we also performed a two-factor repeated measures ANOVA on the data of inserted wall control group. We found a significant main effect of probe trial condition on time spent in food trough (F_{(3, 21)}=23.490, p<0.001, η_p² = 0.770). As expected, time spent in food trough was again higher for pCS+ than pCS- trials (mean difference = 43.525, SE = 6.56, p=0.002; Figure 5f) here though there was a trend toward higher responding for aCS+ cues than for aCS- cues (mean difference = 9.958, SE = 2.855, p=0.061; Figure 5f). We conclude from these results that the compounded cue aCS+ has not become unblocked for the partner rat in the experimental group, however for the control group 1 we observe a clear trend indicative of unblocking. This potential unblocking could be influenced by two factors. First, secondary reinforcement of actor reward delivery (in aCS+ containing compounds) without observation of the actual reward delivery to the actor could have inhibited the attenuating effect of disadvantageous inequity aversion on unblocking and lead to this trend toward unblocking. Next, attentional-based unblocking (Haselgrove et al., 2013) could play a role for the partner rat when it learns that one added cue predicts both reward and the omission of reward. This attentional unblocking effect would also be stronger if evidence of actor presence/reward would be blocked. A direct test of unblocking where both rats experienced disadvantageous unequal rewards was implemented as unequal outcomes. We did not include a version of the unequal outcomes control experiment where we also impeded social information transfer but would speculate that, in that case, unblocking would remain supressed as well.

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The social unblocking effect persists when controlling for secondary reinforcement but not when the partner is not present. Besides the vicarious experience of reward, other confounding factors could have contributed to learning/unblocking in our paradigm. Most notably, sources of secondary reinforcement should be excluded as potential drivers of learning. During discrimination learning, the actor rat is conditioned to receive pellets contingent on its aCS+. Afterward, in the compound phase, the rat is presented with an auditory–visual compound. Instead of one pellet drop (self-reward), now, on some trials, two pellets drop simultaneously (both reward trials). It is possible that the additional pellet delivery sound acted as a third CS+ in the compound, in addition to the aCS+ and pCS+. Because the sound of the pellet dispenser is already associated with the aCS+ of the actor rat, it is possible that the appetitive value increased with the intensity of this cue (two pellets dropping instead of one), thus enhancing the total value of cue configuration, leading to unblocking of the pCS+. To control for this possible source of secondary reinforcement, in a subgroup of rats (experimental group; social-only), we added a pellet dispenser aimed outside the box (placed at the same location as in the compound phase) already during the discrimination phase, providing the same acoustic features of pellet delivery to the target rat, without presenting additional reward (pellets were collected outside of the box). Next, our control group 1 consisted of a subgroup 1A where a wall impeded social contact and a subgroup 1B where there was no partner present. It is clear that these two groups are similar in that the actor rat does not observe food delivery to the partner. However, in the impeded wall condition, US conditioning could still occur due to pellet dispenser sounds (not controlled for; see Figure 1—figure supplement 2) and partner rat related sounds while in the no partner present condition conditioning might still be caused by the observation of food delivery in the other compartment but not pellet dispenser related sounds (controlled for; see Figure 1—figure supplement 2). We therefore compare results between these conditions by again looking at responding during the first 10 s of the probe phase, which would equate to time period in which one extra pellet would be delivered. We performed a mixed repeated measures ANOVA design with trial type (pCS+, pCS-) and trial 1-6 as within-subject factors and four group (experimental group; social-appetitive: N = 8; one pellet added vs experimental group; social-only: N = 12; no new pellets added vs inserted wall control: N = 8; one pellet added, vs no partner present control: N = 8; one pellet added) as a between-subjects factor (see also Figure 1—figure supplement 2). We found a significant main effect (F_{(1, 32)}=17.964, p<0.001, η_p² = 0.360) of trial type, an interaction of group * trial type (F_(3, 32) = 4.559, p=0.009, η_p² = 0.299; Figure 6a) and an effect of trial number (F_(5, 160) = 7.286, p<0.001, η_p² = 0.186). Post hoc comparison reveals that responding to the pCS+ cue in extinction differs significantly from the pCS- cue in the social-appetitive group (one pellet added; mean difference = 24.808, SE = 4.578, p<0.001), social-only group (no new pellets added; mean difference = 9.717, SE = 4.047, p=0.022) but not the inserted wall group (mean difference = −0.175, SE = 4.956, p=0.972) or the no partner present group (mean difference = 5.525, SE = 4.578, p=0.273). We then also compared responding during the full 30 s, which would equate to the addition of three extra pellets. We performed a similar mixed repeated measures ANOVA design with trial type (pCS+, pCS-) and trial 1-6 as within-subject factors and four group (experimental group; social-appetitive: N = 8; one pellet added vs experimental group; social-only: N = 12; no new pellets added vs inserted wall control: N = 8; one pellet added vs no partner present control N = 8; one pellet added) factors as between-subject factor. We also found a significant main effect (F_{(1, 32)}=16.682, p<0.001, η_p² = 0.343), an interaction effect of group * trial type (F_(3, 32) = 4.211, p=0.013, η_p² = 0.283; Figure 6b) and an effect of trial (F_{(3.406, 108.98)} = 6.084, p<0.001, η_p² = 0.160). Post hoc comparison reveals that the pCS+ cue differs significantly from the pCS- cue in social-appetitive group (one pellet added; mean difference = 16.844, SE = 3.623, p<0.001), in the social-only group (no new pellets added; mean difference = 6.622, SE = 2.58, p=0.032) but not the inserted wall control (mean difference = −1.239, SE = 3.623, p=0.971) and no partner present control (mean difference = 6.106, SE = 3.623, p=0.102). Finally, to zoom in on the temporal dynamics of pCS+ vs pCS- responding in these four experiments, we created time-resolved cumulative occupancy plots. We split the 10 s before and after cue onset in five bins of 2 s each and averaged responding during these bins over the six trials which we found have shown the effect. For an additional statistical analysis, we then looked at the cumulative responding over these five post-cue onset bins. We performed a mixed repeated measures ANOVA design with trial type (pCS+, pCS-) and time bins as within-subject factors and the four groups as between-subject factor. We find a significant main effect (F_(1, 32) = 12.601, p=0.001, η_p² = 0.283), an interaction effect of group * trial type (F_(3, 32) = 3.780, p=0.020, η_p² = 0.262) and an effect of group * trial type * bin number (F_{(3.674, 39.674)} = 6.084, p=0.025, η_p² = 0.233; Figure 6c,d,e,f). Post hoc comparison revealed that cumulative response during the pCS+ cue differs significantly from the pCS- cue in social-appetitive subgroup from bin 2 (mean difference = 0.493, SE = 0.185, p=0.012) and onward on bin 3 (mean difference = 1.091, SE = 0.278, p<0.001), 4 (mean difference = 1.601, SE = 0.385, p<0.001), and 5 (mean difference = 2.427, SE = 0.495, p<0.001) after cue onset. In the social-only subgroup we find significant differences in bin 4 (mean difference = 0.804, SE = 0.314, p=0.015) and 5 (mean difference = 0.972, SE = 0.404, p=0.022). However, no significant temporal bins were found in the inserted wall and no partner present control groups.

Figure 6

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While descriptively, the magnitude of the social unblocking effect is larger when not controlling for additional pellet drops (social-appetitive subgroup) than when such a control is implemented (social-only subgroup), we conclude that the social unblocking effect still exist when explicitly controlling for additional pellets falling in the compound phase for the first 10 s and 30 s period after cue onset but not when social information exchange is impeded and finally also not when no partner is present during the compound phase.

Our results extend previous work by Holland, 1984 and Geoffrey Schoenbaum (Lopatina et al., 2015; McDannald et al., 2011) on unblocking in appetitive Pavlovian conditioning. These authors found that rats, after learning that distinct cues have specific food outcomes, can show unblocking of learning for cues added in compound, when self-rewards were altered by increasing reward value (e.g. an upward shift from one to three pellets) or a change in reward identity (same reward type but a shift in reward features such as flavor). By contrast, learning was blocked when no such reward change occurred (e.g. same reward amount or same identity). According to reinforcement learning theory, the upshift or change in identity led to a discrepancy between the expected reward (one pellet) and the received reward (three pellets), thus producing a reward prediction error. The theory states that if the added cue reliably predicts the increase in reward/identity outcome, it will acquire the value inherent in the reward itself (Sutton and Barto, 1981). The main indicator of learning about the value of a (novel) cue in the unblocking paradigm is an increase in the time spent in the food cup in the probe (extinction) phase (Lopatina et al., 2015; McDannald et al., 2011). Indeed, we observed a higher time spent in the food cup for the cue predicting mutual rewards to the actor rat and its conspecific than to the cue that predicts own-rewards. Taking into account the results of the control experiments, we conclude that the observed enhanced food cup response, that is, the social unblocking effect could be driven by an upshift-related vicarious reward prediction error. The observed social unblocking effect adds to the emerging literature showing that animals attach value to rewards delivered to conspecifics (Hernandez-Lallement et al., 2016; Kashtelyan et al., 2014) and learn about cues that predict rewards delivered to others. The social reinforcement learning hypothesis (Hernandez-Lallement et al., 2016) proposes that integration of social signals expressed by partners can aid in making appropriate decisions in a social context. Evidence for this hypothesis comes from the prosocial choice task (PCT) in which it was found that, rewards delivered to oneself and to a partner are preferred over a reward delivery only to the actor himself in both monkeys (Horner et al., 2011) and rats (Hernandez-Lallement et al., 2015; Márquez et al., 2015). In rats, it was found that this effect was modulated by the behavior displayed by the other rat (Márquez et al., 2015) and that this effect was impaired when the partner was replaced by a toy (Hernandez-Lallement et al., 2015) or when the display of the partner’s preference was impeded. In monkeys it was furthermore found that cues that are associated with reward delivery to another monkey were preferred over cues that were associated with juice delivery to a chair with no monkey in it and this preference was absent, in the non-social condition, when there was only a juice bottle present (Chang et al., 2011). We found that social learning occurs when additional reward was delivered to a visible partner but not when preventing the exchange of social information by an opaque wall or when the partner was absent during social learning, providing further evidence that social signals are indeed necessary for learning in social, other regarding, paradigms. A recent study furthermore, shows that macaques increase licking frequency in line with a higher probability of self-reward but decrease their anticipatory licking with increased probability of reward delivery to another monkey (Noritake et al., 2018). The authors interpret this decrease of anticipatory licking as an indicator of the negative affect associated with unequal disadvantageous reward pay-outs. Both monkeys and rats have been found to have a distaste for these unequal pay-outs (Brosnan and De Waal, 2003; Oberliessen et al., 2016). Here we provide similar evidence that in rats tested in our social unblocking paradigm, disadvantageous unequal reward outcomes do not support unblocking of cues that predict reward to the other rat but not oneself. Our finding extend the results of Rescorla, 1999 who found that changing the outcome of an aCS- cue by adding a cue in compound that predicts self-reward leads to unblocking of that added cue. This contrasts with the lack of unblocking found here, indicating that the observation of reward delivery to the social partner does not have similar reinforcement properties as adding self-reward, possibly due to the negative affect associated with disadvantageous unequal reward outcomes.

Further research is necessary to see whether cues associated with vicarious reward or social reinforcement can also act as a conditioned reinforcer for instrumental responses of rats, as has been found humans (Lehner et al., 2017), in a similar way as has been found for appetitive cues (Burke et al., 2008; Kruse et al., 1983; Rescorla, 1994). Finally, it is important to investigate if cues predicting vicarious rewards can guide rats’ choices in a social setting. It has been found that rats choose a reward arm in a T-maze that leads to play behavior more than an arm leading to a social encounter where play was absent (Humphreys and Einon, 1981). Furthermore, social play can induce a social place preference (Calcagnetti and Schechter, 1992) and rats are willing to lever press for social play reinforcement (Achterberg et al., 2016). Our task indicates that the unblocked cue has attained the rewarding properties of social reward and it is therefore likely that a presented unblocked cue would be preferred over a blocked cue when tested in a two-alternative forced choice task. We finally expect that our social unblocking effect depends on the successful transmission of social signals between the actor and partner rat (Nicol, 1995; Hernandez-Lallement et al., 2016) and that different signal modalities (auditory, visual, olfactory) might contribute and combine in additive or interactive fashion.

Overall, these data provide evidence that vicarious reward experience can drive associative learning in rats and that the transmission of social cues between rats is necessary for this learning. Further experiments should be conducted to reveal which mode(s) of social information processing are necessary and sufficient to drive unblocking through social value. Overall, our novel behavioral paradigm could be used to further explore how rats learn about value in social contexts and is well suited to probe the neural circuits involved in social reinforcement learning.

About 88 male Long Evans rats where housed in pairs of two and kept under an inverted 12:12 hr light-dark cycle, in a temperature (20 ± 2°C), and humidity-controlled (approx. 60%) colony room. All rats had ad libitum access to food, except during the testing period. During behavioral testing, the rats where food restricted (20 g on weekdays and 22 g in the weekend) and maintained on a body weight of about 90% of their free-feeding weight. All testing was performed in accordance with the German Welfare Act and was approved by the local authority LANUV (Landesamt für Natur-, Umwelt und Verbraucherschutz North Rhine-Westphalia, Germany).

Testing was conducted in four customised PhenoTyper (Noldus Information Technology) behavioral testing boxes (Figure 1A) of 45 × 45 × 55 cm³, supplemented with operant devices (Med Associates) and placed inside a custom-made sound- and lightproof ventilated box. The boxes where modified by adding a custom-made Plexiglas separation wall (Figure 1A, left panel), which divided the box into two compartments, to allow the training of a pair of rats at the same time. The separation wall was equipped with a sliding door (dimensions: 20 by 20 cm, located at 7 cm from the left side of the Skinner box) and four rectangular interaction windows (Figure 1A, left panel; size: 10 × 1.5 cm²) that were positioned exactly in between the door and the wall holding the stimulation devices used for conditioning. Both compartments of the box contained a food trough (Med Associates, ENV-254-CB) positioned in the middle on the right side. The food troughs were adapted in such a way that the detection photobeams were positioned at the entry point of the food trough. The food trough was connected to an automated pellet dispenser (PTPD-0010, Noldus Information Technology) that delivered sucrose pellets (20 mg dustless precision pellets, Bio-Serv, Germany). Operant devices were positioned on the right side of the box at the level of the separation wall: an LED Stimulus Light (Med Associates, ENV-211m) with green cover was positioned 10 cm above the ground and a house light (Med Associates, ENV-215m) 28 cm above the ground. A speaker (Med Associates, ENV-224am) was positioned at 20 cm above the ground for the playback of auditory stimuli (Figure 1A, right panel). Auditory stimuli were played back at a loudness of 75 dB measured with a hand-held analyser (type 2250s from Brüel and Kjaer) right in front of the speaker. In the top cover of the Skinner boxes, a camera (Basler, acA1300-60gc, GigE) was positioned to obtain videos of the behavioral experiment at 25 fps. Analyses of the recorded videos was performed with EthoVision XT 11.5 (Noldus Information Technology). Finally, a USV-microphone was positioned next to the camera for recording ultrasonic vocalizations using Ultra Vox XT (Noldus Information Technology).

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Animal experimentation: All testing was performed in accordance with the German Welfare Act and was approved by the local authority LANUV (Landesamt für Natur-, Umwelt und Verbraucherschutz North Rhine-Westphalia, Germany).

1. Received: July 6, 2020
2. Accepted: September 14, 2020
3. Version of Record published: October 1, 2020 (version 1)
4. Version of Record updated: October 28, 2020 (version 2)

© 2020, van Gurp et al.

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