What do animals remember about items out of context? For example, suppose we learn that different options (e.g. coffee shops) result in different reward outcomes (e.g. waiting time and quality), and later we are presented with a choice between two previously encountered options which we have never experienced side-by-side. What types of values do we remember for those options now presented in a novel context? Do our memories of the subjective values for each option contain absolute information (e.g. delay to reward), remembered ranking (how they compared to previous alternatives), or a weighted combination of both?

In typical studies exploring the economic choices of animals including humans, subjects do not have to use distant memories of the options; they are presented with choices where the objective values (e.g. amount, cost, and status) are concurrently visible and can be directly compared. Under such conditions, a wealth of research shows that animals’ choices can be influenced by the presence of additional options (Hunter and Daw, 2021; Spektor et al., 2021). An example of this phenomenon is frequently used in marketing: when given a choice between popcorn options in different sizes, e.g. $3 for small and $7 for large, most people choose the smaller cheaper option, but when a $6 medium option is added, more people choose the large because it now seems like a good deal. Evidence of contextual effects like this on direct assessments has been found across the animal kingdom, e.g. humans and other primates (Berkowitsch et al., 2014; Parrish et al., 2015; Trueblood et al., 2013), bats (Hemingway et al., 2021), birds (Bateson, 2002; Morgan et al., 2012), frogs (Lea and Ryan, 2015), fish (Reding and Cummings, 2017), bees (Shafir et al., 2002), and worms (Iwanir et al., 2019). However, little is known about the type and degree of information (absolute and/or relative) that is encoded in the remembered subjective values of options.

Only more recently have investigations of absolute and relative information traversed into the realm of reinforcement learning, where value must be inferred from memories. Studies on starlings (Pompilio and Kacelnik, 2010) and humans (Bavard et al., 2018; Bavard et al., 2021; Klein et al., 2017) demonstrated that both absolute memories and remembered ranking are combined in particular ways to give rise to these animals’ preferences. So far, however, no other species have been investigated for the roles played by absolute memories and remembered ranking in learned preferences. Here, we examine this in bumblebees (Bombus terrestris), an invertebrate and a key model for examining the economy of decision-making outside of humans (Real, 1996).

Specifically, we adopt an instrumental learning paradigm that combines a contextual training phase and a transfer-test phase (Palminteri and Lebreton, 2021). This paradigm essentially involves two distinct learning contexts (e.g. AB context and CD context; Figure 1), with each context offering two options of contrasting properties (e.g. A>B and C>D in reward sizes). After training, animals’ learned preferences are tested with a novel combination of options (e.g. B vs C). Note that behavioural tests for transitive inference (Guez et al., 2013; Vasconcelos, 2008) involve a similar task design, which includes several training phases and a test phase of new combinations. However, this method provides overlapped relational premises during training (e.g. A>B, B>C, C>D, and D>E) in order to examine if animals can infer the relationship between a pair of options within the chained sequence which had previously not been experienced together (e.g. B vs D). In contrast, our paradigm provides no direct overlapped training between contexts (e.g. A>B and C>D), and therefore, animals cannot infer the relationship between unchained options (e.g. B vs C). Rather, by providing both absolute and relative information during training, our paradigm is used to assess whether, and in what combination, bumblebees retain and utilise absolute and ranking memories.

Figure 1 with 4 supplements see all

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If bumblebees encode and retrieve memories for absolute values, their preference for a particular option should not depend on the context in which that option was learned (Padoa-Schioppa and Assad, 2008). To test this idea, we conducted experiment 1 with a multi-contextual design where certain flowers had the same quality of reward but different ranking. Bees were first trained (individually in all experiments) on two different pairs of coloured flowers (A and B; C and D; Figure 1A, Figure 1—figure supplement 1, and Figure 1—figure supplement 2). The sucrose concentrations of the different pairs of flowers were chosen according to Weber’s Law (Akre and Johnsen, 2014) to represent the same perceived difference, i.e. A:B=45%:30% had the same contrast of incentives as C:D=30%:20% (Figure 1A). Note that for all experiments, the order of training sessions was counterbalanced to ensure that test preferences were not a result of a recency effect. Meanwhile, the focal colours used in the unrewarded test were counterbalanced during training to account for any colour effects (Materials and methods; Figure 1; Figure 1—figure supplement 3). Following sequential training in both contexts (Figure 1—figure supplement 3 and Figure 1—figure supplement 4), we tested each bee’s preference between flower types B and C, which had the same reward quality (30%) during training. Therefore, if bumblebees’ preferences were driven exclusively by their memory for absolute values for options, they should show no preference between B and C in the test. Any significant preference would suggest a contextual effect due to B and C having different rankings during training (B<A while C>D). In an unrewarding test with B and C flowers, bees significantly preferred C over B (generalised linear model [GLM]: 95% CI = [0.08, 0.38], N=40, and p=4.00e-3; Figure 1B and Figure 1—figure supplement 3). Although these results suggest that bees store memories for the relative ranking of flowers, they still may encode absolute information (Table 1), and therefore, we carried out additional experiments.

Bees may still store and use memories for both absolute and relative information in some combined fashion. To test this, in experiment 2, we set the reward quality of flowers B and C to be different (Figure 1C and Figure 1—figure supplement 3). The sucrose concentration of flowers was A>B >> C>D (45%, 30%, 15%, and 10%). After training in both contexts, bees’ preference between B and C flowers was tested. If bumblebees retain and use memories for both ranking and absolute information (and the value weights for these two different types of information are not extremely unbalanced), bees should either prefer B over C because it is much higher in quality, or this value difference would cancel out the ranking difference (B<A while C>D), and their preference for B and C should be equal. On the other hand, a preference for the much lower reward quality flower C would indicate they have access to only ranking memories. Similar to experiment 1, the result of the unrewarding test showed that bees preferred C (GLM: 95% CI = [0.07, 0.28], N=40, and p=3.30e-3; Figure 1D).

Note that a preference for C over B in experiments 1 and 2 may have resulted from remembered ranking or a distorted absolute memory for flower type B due to the presence of and comparison with A during training. Evidence for the latter would manifest as a difference in the preference for C over B in experiment 2 compared to in experiment 1, whereas remembered ranking would predict a similar preference. There was no significant difference in preference for C across experiments 1 and 2 (GLM: 95% CI = [–0.24, 0.13], N=80, and p=0.55; Figure 1B and D). There is thus no evidence that bumblebees’ choices in novel contexts are based on remembered absolute metrics.

If bumblebees rely purely on remembered ranking, then their memories for options should only be ordinal (Vlaev et al., 2011). That is, they can tell one option is better than another but cannot tell how much better. If so, there should be no indication that bumblebees can compare options in quantitative terms. To test this, in experiment 3, we made the reward contrast ratios within the two contexts very different ([A:B] = [1.5:1]=45%:30% and [C:D] = [6:1]=30%:5%; A>B = C>>D; Figure 1E). Here, testing bees’ preference between A and C flowers can answer our question. If bees encode memories for relative differences in quantitative terms, C should be preferred over A, as C had a higher relative value than A. Alternatively, if bees only remember the ordinal rank of options, preference for A and C should be the same because they have the same rank within their training contexts. In the unrewarding test, bees chose A and C equally (GLM: 95% CI = [–0.16, 0.12], N=40, and p=0.79; Figure 1F), suggesting bumblebees store and recall only memories for the qualitative difference between options. Furthermore, bumblebees’ lack of preference for the equally ranked A and C flowers, despite their difference in sugar concentration, demonstrates absolute memories were not remembered (Table 1) and, in combination with experiments 1 and 2, suggests that bumblebees only encode and recall remembered ranking for use in novel contexts.

It may be that bumblebees can store and recall absolute information, but any ranking information available overshadows absolute memory. To test this, in experiment 4, we trained bees so that ranking information was absent. Bees experienced a temporally separated training procedure (Materials and methods; Figure 2A) whereby they first foraged on one flower with either 45% or 30% sugar solution, and 1 hr later they were trained on a different flower with either 30% or 45%, respectively. In the subsequent (1 hr later) unrewarded test, bees’ preferences were assessed. Because the two flower types were separated physically and temporally, bees had no ranking information available to putatively overshadow absolute information. Therefore, any preferences formed would be a result of remembered absolute information. However, bees had no significant preferences for either option (GLM: 95% CI = [–0.15, 0.22], N=20, and p=0.69; Figure 2B), suggesting that bees’ lack of absolute memory in the tests of experiments 1–3 was unlikely to be a result of absolute memories being less salient and overshadowed by ranking memories.

Figure 2

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In order to discriminate any two sequentially visited flowers and indeed to rank them, bumblebees must utilise absolute information for at least a brief amount of time. During training in experiments 1–3, bumblebees could see flowers of both types simultaneously. Given the results of experiment 4, we therefore asked whether bumblebees could utilise absolute information long enough to rank flowers that were temporally close together but visually separated. To do this, in experiment 5, we trained bees on one flower for each bout, i.e. each visit to the arena (Materials and methods; Figure 2C). This way, both flower types were never in a bee’s visual field at the same time. During the unrewarded test, bees preferred the option that had offered the higher sugar concentration in training (GLM: 95% CI = [0.23, 0.87], N=10, and p=8.29e-3; Figure 2D), suggesting that absolute information about a flower learned in visual isolation can be retained for at least a couple of minutes but, as experiment 4 highlights, is eventually lost or not able to be recalled later. Experiment 4 and 5 thus collectively indicate that bumblebees can use absolute information to compare options only in their short-term memories (range of minutes) but not in their mid-term memories (range of hours; Menzel, 2001).

Our results highlight the potential disadvantage of using only remembered ranking, i.e. preferring to search for a less rewarding flower. How might our results speak to bumblebees’ behaviour in more ‘natural’ settings? In the wild, bumblebees often forage in situations whereby when drinking from one flower type they cannot see other flower types in their field of view, i.e. on the other side of a bush or many meters away. Yet, the distance between any two flowers within a bumblebee’s foraging range can be traversed within minutes (Osborne et al., 1999), i.e. within the range of bumblebees’ short-term memories (Menzel, 2001). Therefore, we would expect that bumblebees in the wild would not be susceptible to learning preferences for a less rewarding flower despite being unable to retain absolute information for very long. In an attempt to formally test this idea, in experiment 6, we trained bees in a multi-contextual semi-realistic foraging situation. Here, in a divided arena, bumblebees learned to forage from flowers of four different colours (Figure 2E and Figure 1—figure supplement 3) but could only see flowers of two colours at any one time, i.e. could only see A and B (45% and 30%) flowers from one side of the arena and could only see C and D (30% and 20%) flowers from the other side (Figure 2E). In the unrewarding test with all four options available, bees preferred option A (GLM: 95% CI = [0.94, 1.68], N=20, and p=1.21e-6; Figure 2F), indicating that the short retention/utilisation of absolute memories that bumblebees showed in our lab-created situations are likely not to be disadvantageous to bumblebees in the wild, given their natural behaviour and ecological niche.

Our results suggest that bumblebees are only able to make use of ordinal ranking memories to guide foraging choices outside their original learning contexts. Although absolute information is essential for any animal to compare any two options initially, our findings show that only ordinal ranking can be recalled by bumblebees later in new contexts. Our results suggest that temporal adjacency is necessary for absolute information of different options to be compared by bees. That is, once bees experience one option, in order to utilise the absolute information, they must experience a second option within several minutes. Both our proof-of-concept experiment (experiment 6) and other previous multi-choice semi-realistic foraging tasks (e.g. Greggers and Menzel, 1993) show that with short inter-flower visits, bees can utilise absolute information in order to compare and rank flowers.

Another potential mechanism worth discussing which could potentially explain bumblebees’ preferences is state-dependent valuation learning (SDVL; for a review see McNamara et al., 2012; Table 1). If bees’ choices were a result of SDVL instead of remembered ordinal ranking, then their preferences should be quantitative, i.e. larger values should be assigned with larger differences between internal state and flower experience. However, the results of experiment 3 speak against this interpretation because bees were indifferent between equally ranked A and C even though they were experienced in a richer and poorer environment, respectively.

Why would bumblebees have evolved to use only memories for ordinal comparisons while humans and starlings evolved to retain and recall both absolute and ranking memories? Breadth of diet has been suggested to play a role in the evolution of cognition (Hemingway et al., 2017; MacLean et al., 2014; Simons and Tibbetts, 2019). Humans and starlings forage on a range of different foods, whereas adult bumblebees feed almost exclusively on nectar and pollen from flowers. Perhaps a varied diet, whereby one might need a common currency across vastly different food types (Chib et al., 2009; Levy and Glimcher, 2012) may have forced some animals to retain and use absolute memories, whereas a limited diet and limited dimensionality of reward might have favoured memories for ordinal relationships alone.

There is no reason yet to suggest a bee’s brain lacks the neural substrates to retain and recall absolute memories for options for later use in novel contexts. In fact, recent electrophysiological recordings on the gustatory neurons of bumblebees demonstrated that the spiking rates of these peripheral sensory neurons increased as a function of sucrose concentration (Miriyala et al., 2018). These gustatory neuronal signals could theoretically be used by higher centres of an animal’s brain to encode an option’s utility as a cardinal (absolute) value (Schultz, 2015). However, our results suggest that bumblebees do not access or utilise any potentially stored absolute memories when it would be of benefit in novel contexts. Given our results, it would be intriguing to determine the differences in the underlying neural mechanisms responsible for the utilisation of absolute properties and ordinal ranking memories. Whatever the ultimate and proximate causes of bumblebees’ ordinal-only memories for options’ values, our findings demonstrate a fundamental difference in the mechanisms underlying learned preferences between those of bumblebees and those of starlings and humans.

All data generated or analysed during this study are available on the Dryad Digital Repository: https://doi.org/10.5061/dryad.rr4xgxdb9.

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Author details

1. Cwyn Solvi

   1. Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
   2. Ecology and Genetics Research Unit, University of Oulu, Oulu, Finland

   Contribution

   Conceptualization, Software, Formal analysis, Supervision, Validation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   Contributed equally with

   Yonghe Zhou

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2517-6179

2. Yonghe Zhou

   1. Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
   2. Biological and Experimental Psychology, School of Biological and Behavioural Sciences, Queen Mary University of London, London, United Kingdom

   Contribution

   Data curation, Software, Investigation, Visualization, Writing – original draft, Writing – review and editing

   Contributed equally with

   Cwyn Solvi

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-3324-9972

3. Yunxiao Feng

   Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China

   Contribution

   Investigation

   Competing interests

   No competing interests declared

4. Yuyi Lu

   Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China

   Contribution

   Data curation, Formal analysis

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-1635-7907

5. Mark Roper

   Biological and Experimental Psychology, School of Biological and Behavioural Sciences, Queen Mary University of London, London, United Kingdom

   Contribution

   Conceptualization, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1135-6187

6. Li Sun

   Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China

   Contribution

   Investigation

   Competing interests

   No competing interests declared

7. Rebecca J Reid

   Biological and Experimental Psychology, School of Biological and Behavioural Sciences, Queen Mary University of London, London, United Kingdom

   Contribution

   Investigation

   Competing interests

   No competing interests declared

8. Lars Chittka

   Biological and Experimental Psychology, School of Biological and Behavioural Sciences, Queen Mary University of London, London, United Kingdom

   Contribution

   Conceptualization, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8153-1732

9. Andrew B Barron

   Department of Biological Sciences, Macquarie University, Sydney, Australia

   Contribution

   Funding acquisition, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-8135-6628

10. Fei Peng

    1. Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
    2. Department of Psychiatry, Zhujiang Hospital, Southern Medical University, Guangzhou, China
    3. Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China

    Contribution

    Conceptualization, Resources, Data curation, Software, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

    For correspondence

    fpeng@smu.edu.cn

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-1637-5611

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