Learning and memory are fundamental for animal survival in dynamic and noisy environments and for the cognitive abilities of humans. A significant amount of what we know on the biological basis of learning and memory has come from studying classical conditioning, also known as Pavlovian conditioning (Heisenberg et al., 1985; Romanski et al., 1993; Uwano et al., 1995; LeDoux, 2000; Davis and Whalen, 2001; Dubnau et al., 2001; McGuire et al., 2001; Maren and Quirk, 2004; Fanselow and Poulos, 2005; Ehrlich et al., 2009; Johansen et al., 2010; Duvarci and Pare, 2014; Herry and Johansen, 2014). During classical conditioning, learning depends on the contiguity of conditioned and unconditioned stimuli. Studying classical conditioning has provided essential insights into the molecular, cellular, and circuit basis of how the brain transforms sensory information into memories and how it uses these memories to drive behavior. Nevertheless, in humans and other animals, the instructive value of naturally occurring reinforcing experiences is acquired rather than innately instructive and does not necessarily dependent on mere contiguity. For example, the value of money and its capacity to function as a reinforcer is learned rather than innate. Learning theory has postulated the idea that learned behavioral control uses two types of information. The first results from habits, policies, or cached values (e.g., Pavlovian conditioning – model-free learning) (Jones et al., 2012). This kind of information produces a rapid, efficient behavioral response but does not consider changes in the value of the expected outcome. The second type of information relies on the knowledge of the associative structure of the environment to infer value (model-based learning). In other words, acquiring new knowledge depends on creating an associative structure of external events, which is then used to create additional new meaningful associations (Daw et al., 2005; Jones et al., 2012; McDannald et al., 2012; Lucantonio et al., 2014; Sadacca et al., 2016). Several different types of higher-order conditioning are examples of this type of information. In higher-order conditioning procedures, neutral stimuli acquire the property to elicit conditional responses even though they have never been in contiguity with a reinforcer. Sensory preconditioning is one example of higher-order conditioning (Giurfa, 2013; Giurfa, 2015; Todd et al., 2016). In sensory preconditioning, two initially neutral stimuli (S1 and S2) are repeatedly presented in contiguity or in sequence (preconditioning phase); later, one of the stimuli (S1) is paired with a reinforcer (conditioning phase). After this, S2 will elicit a conditioned response even though it was never paired with the reinforcer, indicating that the preconditioning phase created an association between S1 and S2. The response to the preconditioned stimulus (S2) is different from the response to the reinforcer-paired S1 in that it is not based on a mere association; instead, it must infer value by virtue of knowledge of the associative structure of the task (Jones et al., 2012). Sensory preconditioning has been shown previously in bees and flies (Müller et al., 2000; Brembs and Heisenberg, 2001; Guo and Guo, 2005). Using a flight simulator (Guo and Guo, 2005), trained flies, using visual or olfactory cues to avoid certain flight directions. They reported sensory preconditioning using S1–S2 cues of different modalities (olfactory and visual). Here, we provide evidence of olfactory unimodal sensory preconditioning in fruit flies. We show that the presentation of a pair of odors (S1 and S2) before one of them (S1) is associated with electric shocks elicits a conditioned response not only to the trained odor (S1) but also to the odor it was previously paired with (S2). This occurs even if the S2 odor was never presented in contiguity with the negative reinforcer. These data provide evidence for unimodal sensory preconditioning in Drosophila. These findings open the door to better understand how a simple brain achieves sensory preconditioning with limited neurons and synapses, providing meaningful insights into how a more complex mammalian brain may solve similar problems.

The Drosophila mushroom bodies (MB) are brain structures made up by the axons of the Kenyon cells (KC), and are known to play a central role in the encoding of olfactory memories (Heisenberg et al., 1985; Dubnau and Tully, 2001; McGuire et al., 2001). During associative memory acquisition, positive or negative values are assigned to odors by associated reward and punishment, respectively. This reinforcement is achieved by the coincident activation of a sparse number of KC by an odorant and the activation of dopaminergic neurons (DAN), which innervate the MB, by the unconditioned stimulus. Different DAN synapse onto discrete zones of the MB, resulting in 15 tile-like compartments of the MB. Each of these 15 tiled areas in turn synapse onto the dendrites of distinct corresponding mushroom bodies output neurons (MBONs). Activation of different MBONs are then known to alter behavioral approach or avoidance (Aso et al., 2014; Owald and Waddell, 2015; Roselli et al., 2021). The memory of an odor associated with an electric shock (classical conditioning) is known to be partially encoded as a decreased response specifically to the trained odor (CS+) in a particular MBON known as MBON-γ1pedc>α/β (Hige et al., 2015; Perisse et al., 2016; Cervantes-Sandoval et al., 2020). Conversely, odors that have not been associated with an electric shock do not normally demonstrate decreased responses in the MBON-γ1pedc>α/β neuron (Hige et al., 2015; Perisse et al., 2016; Cervantes-Sandoval et al., 2020). Thus, we were extremely surprised to report in a previous publication that flies expressing the dominant-negative form of Rac1^N17 (Rac1DN) in adult KC using the temperature-dependent tool gal80^ts (TARGET) (McGuire et al., 2003), displayed a depression to a non-shock associated odor in MBON-γ1pedc>α/β neurons (Cervantes-Sandoval et al., 2020). We decided to investigate the nature of this intriguing non-shock associated neural depression.

It has been reported that animals can link together neutral sensory cues presented in succession or simultaneously; if then one of these cues is associated with reinforcement, animals can display a response to the non-associated pre-linked cue; this is known as sensory preconditioning (Brogden, 1939; Jones et al., 2012). As mentioned above, this type of behavior is categorized as model-based learning where a value is inferred from the associative structure of the environment (Jones et al., 2012). It was also reported that expressing Rac1^N17 in KC significantly enhances trace conditioning, in which an odor is associated with an electric shock presented many seconds after odor offset – suggesting that inhibition of Rac1 lengthens an olfactory ‘sensory buffer’ that later converges with the punishment signal (Shuai et al., 2011). Therefore, we reasoned that sensory preconditioning and Rac1 inhibition could explain the observed depression to the non-trained odor we previously reported (Cervantes-Sandoval et al., 2020) and replicated this finding in pilot experiments (Figure 1—figure supplement 1).

To test for the possibility that we were observing sensory preconditioning in MBON-γ1pedc>α/β neurons, we exposed animals to a single pairing of 5 s of 4-methylcyclohexanol (MCH) (S1) and 5 s of 3-octanol (OCT) (S2) odors, separated by an interstimulus interval (ISI) of 1 s, 30 s, or 5 min, before classical aversive olfactory conditioning occurred only to S1 by pairing MCH (S1) with an electric shock (20 s of odor with four 90 V, 1.25 s electric shocks). This is also known as forward conditioning. Post-training calcium responses to both MCH and OCT were then recorded 5 min after conditioning in MBON-γ1pedc>α/β neurons using the R12G04-lexA driver to express GCaMP6f (Figure 1A, B). These calcium responses in MBON-γ1pedc>α/β were compared with the odor responses in backwards conditioned animals which serve as our procedural control. Backwards conditioned animals receive all the same stimuli as forward conditioned animals, except that the electric shock occurs before the odor during what would be the ‘conditioning phase’, thus classical conditioning does not occur. Two naive odors, penthyl acetate (PA) and ethyl lactate (EL), were also given to the animals post-conditioning to ensure that the experimental methods did not result in generalized MBON-γ1pedc>α/β changes to all odors (Figure 1A, B).

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One-second interstimulus interval (ISI) during preconditioning induces depression to non-trained, pre-paired odor S2 in control flies.

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Using the typical imaging protocol with a 25- to 30-s ISI between the preconditioned odors, we and others (Hige et al., 2015; Cervantes-Sandoval et al., 2020) have shown there is no evidence of sensory preconditioning in the MBON-γ1pedc>α/β of control animals. That is, the MBON-γ1pedc>α/β does not display a decreased response to the S2 odor (Figure 1C), but does demonstrate the expected near-complete depression in response to the conditioned S1 odor. Lengthening the ISI to 5 min has the same effect on control flies (Figure 1C). Interestingly however, when we shorten the sensory preconditioning interval to 1 s, the MBON-γ1pedc>α/β neurons in control flies exhibit a decreased calcium response to the S2 odor, and to the S1 odor that is expected (Figure 1C). Throughout these experiments, MBON-γ1pedc>α/β responses to naive odors remained unchanged, indicating the decrease in calcium response to the S2 odor is specific to the preconditioning phase, and not the result of a generalized depression to all odors (Figure 1C). This suggests that shortening the ISI window during sensory preconditioning allows control flies to form some association between the S1 and S2 odors, thus resulting in an inferred predictive value of the S2 odor after animals were aversively conditioned to the S1 odor. These results demonstrate that flies show, at least at the physiological level, sensory preconditioning.

In contrast to control animals, flies expressing dominant-negative Rac1^N17 in the KC had previously been found to exhibit a decreased calcium response to the S2 odor when using an ISI of 30 s (Figure 1D, Figure 1—figure supplement 1B). This was also true when the sensory preconditioning ISI was decreased to 1 s (Figure 1D). The data from our control flies led us to speculate that the timing of the S1/S2 ISI dictates whether an association between odors S1 and S2 (MCH and OCT) occurs during the sensory preconditioning stage. Secondly, from prior data on Rac1’s role in trace conditioning and our sensory preconditioning data, we suspected that Rac1 inhibition in the KC extends the time period that allows for the S1/S2 association to occur. If this was true, we predicted that extending the ISI should eliminate sensory preconditioning in Rac1DN flies. When the ISI was increased to 5 min, no sensory preconditioning was observed in the Rac1DN animals (Figure 1D). Again, naive odor responses in these flies were unchanged. This widening of the ISI window to allow for an S1/S2 association is dependent on the inhibition of Rac1, since flies with the same genotype but raised at 18°C to prevent the expression of Rac1^N17 (using the TARGET system) showed the normal conditioning-induced odor depression to the S1 but no change to S2 with a preconditioning ISI window of 30 s (Cervantes-Sandoval et al., 2020).

We tested whether this suspected sensory preconditioning-induced calcium depression might be the result of increased habituation of the non-associated S2 odor. We recorded olfactory responses in flies exposed to the same odor protocol except that the unconditioned stimulus was excluded. Results showed no depression to either S1 or S2 odor presented (Figure 2—figure supplement 1A). Going even further, we confirmed this observation by recording and evaluating changes in calcium responses after 10 repeated presentations of both MCH and OCT. Data were analyzed as previously described (Hattori et al., 2017). The ratio between the mean of three initial responses and mean of three last responses in MBON-γ1pedc>α/β was not significantly different between control and experimental genotypes (Figure 2—figure supplement 1B). Thus, the reduced calcium response we see in MBON-γ1pedc>α/β to the classically conditioned S1 odor and the sensory preconditioned S2 odor cannot be explained by a general habituation to the odors due to the experimental protocol.

Rac1 has been implicated in memory forgetting, and it has been theorized that forgetting is fundamental for memory generalization (Richards and Frankland, 2017). In addition, (Hige et al., 2015) showed that a similar depression to the non-trained odor could result from a partial overlap in the neural representation of odors such as MCH and OCT. For these reasons, we tested whether the expression of Rac1^N17 in KC may somehow increase that generalization between MCH and OCT, and that this may lead to the sensory preconditioned neural response that we are observing. For this, we trained animals using orthogonal odors, PA and EL, that are known to have little overlap in their KC representations. Surprisingly, similar results to MCH/OCT were obtained; we observed a depression to the non-trained S2 odor (EL) when Rac1 function is inhibited in KC (Figure 2). Thus, this physiological response to sensory preconditioning can be observed for different odors and odor pairs.

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Rac1 inhibition induces depression to sensory preconditioned odor S2 in MBON-γ1pedc>α/β using a different odor pair with orthogonal representation.

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To further challenge the assertion that the reduced calcium response in MBON-γ1pedc>α/β neurons to the S2 odor is a result of sensory preconditioning, we trained animals with forward or backwards conditioning but excluded the pre-training odor presentation of S1 and S2. When we eliminated the preconditioning association between the S1 and S2 odors, the results showed significant depression to the classically conditioned S1 odor that was associated with the shock, but no depression to any other odors (Figure 3). These results demonstrate that the depression to the non-trained S2 odor was not due to a general depression to odors or generalization of learned aversion. Instead, depression of the non-trained S2 odor is dependent on the animal learning the association between S1 and S2 during the preconditioning stage. These results further support the hypothesis that we are observing physiological sensory preconditioning.

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Excluding preconditioning eliminates depression to the S2 odor.

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We then tested if sensory preconditioning could be observed at the behavioral level. For this, we trained the flies using an Arduino microcontroller for precise odor delivery by controlling solenoids automatically. Using this Arduino system, we trained animals as follows (Figure 4—figure supplement 1A). Control flies were presented with a single pairing of the odors (5 s pulse each) with a 1-s ISI. Using the standard aversive olfactory conditioning paradigm, flies were then conditioned by the presentation of 1 min of S1 odor along with 12, 90 V shocks. Memory was tested right after training in a T-maze by presenting animals with either the S1 (shock-paired odor) and a novel odor (NO), or the S2 (non-shocked, pre-paired odor) and an NO. As in canonical aversive olfactory conditioning experiments, each behavioral experiment was conducted using the reciprocal odor as S1. The final performance index (PI) was calculated by averaging the PI for each odor used as S1. Results were compared to flies trained with backwards conditioning. Despite observing evidence of sensory preconditioning by functional imaging using a similar protocol, we could not observe a behavioral memory to the non-shocked pre-paired odor (S2) (Figure 4—figure supplement 1B). At a behavioral level, sensory preconditioning has previously been observed in animals after repeated presentation of a pair of sensory cues. Thus, we preconditioned flies with 10 repeated presentations of odor pairings (S1/S2) before training (Figure 4A). Using an ISI of 1 s, this resulted in a significant behavioral aversive memory expression to the S2 odor in control flies (Figure 4B), consistent with our predictions based on the sensory preconditioning physiological data. Furthermore, control flies did not demonstrate an aversive memory to the S2 odor when an ISI of 30 s was used (Figure 4B), as would be predicted from our physiological imaging data. These results also suggest that while a single odor pairing is sufficient to induce sensory preconditioned-related plasticity in the MBON-γ1pedc>α/β compartment, it is not enough for the S2 odor to drive the learned behavior. We suggest that the presentation of additional odor pairings recruits and induces sensory preconditioning-related plasticity in additional MB compartments, and it is the additive effect of multiple compartments that is necessary to drive the behavioral response. Similar phenomena have been observed before for classical conditioning where a short pairing of odor and shock – 1-s odor paired with 4 DAN photostimulation pulses – is enough to induce plasticity in MBON-γ1pedc>α/β compartment but not in MBON-α2sc. Longer training protocols – 1-min odor presentation paired with 120 DAN photostimulation pulses – induce plasticity in MBON-α2sc (Hige et al., 2015). Physiologically, preconditioning flies with MCH/OCT pairs repeated 10 times before training resulted in a robust depression in MBON-γ1pedc>α/β to the non-shocked pre-paired odor (CS2) in control flies (Figure 4—figure supplement 2A). These results were similar when PA/EL were used as the preconditioned odors (Figure 4—figure supplement 2B).

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Repeated presentations of paired odors (S1/S2) induce behavioral sensory preconditioning.

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We next tested flies expressing Rac1^N17 in KC for evidence of behavioral sensory preconditioning when using 30-s and 5-min ISI between S1 and S2. As would be predicted from our physiological data, while a 30-s ISI resulted in no aversive memory to S2 in control flies, a significant aversive memory was observed in flies expressing Rac1^N17 (Figure 4B). This is consistent with our calcium imaging results in Figure 1B, in which a 30-s ISI results in a depression to S2 in Rac1^N17 flies but not in control flies. Further lengthening the ISI to 5 min eliminated behavioral sensory preconditioning both in controls and in flies expressing Rac1^N17 (Figure 4B), again mirroring the physiological results in the MBON-γ1pedc>α/β neuron (Figure 1B). Flies kept at 18°C to prevent expression of Rac1^N17 behaved as control flies and did not demonstrate behavioral evidence of sensory preconditioning when using an ISI of 30 min (Figure 4—figure supplement 3). Finally, we tested if Rac1^N17 expression in KC altered olfactory responses in the MB lobes. Interestingly, we could not find any change in the calcium response dynamics in KC γ lobes, even when recordings were performed at a higher speed (28 Hz) (Figure 4—figure supplement 4).

Taken together, these results indicate that flies can undergo unimodal sensory preconditioning and that the small G protein Rac1, previously implicated in memory forgetting, gates the windows for this S1–S2 association.

All data generated or analyzed during this study are included in the manuscript and supporting files.

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Author details

1. Juan Martinez-Cervantes

   Department of Biology, Georgetown University, Washington, DC, United States

   Contribution

   Data curation, Investigation

   Contributed equally with

   Prachi Shah

   Competing interests

   No competing interests declared

2. Prachi Shah

   Department of Biology, Georgetown University, Washington, DC, United States

   Contribution

   Data curation, Formal analysis, Investigation

   Contributed equally with

   Juan Martinez-Cervantes

   Competing interests

   No competing interests declared

3. Anna Phan

   Department of Biological Sciences and Neuroscience & Mental Health Institute, University of Alberta, Edmonton, Canada

   Contribution

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

   Competing interests

   No competing interests declared

4. Isaac Cervantes-Sandoval

   1. Department of Biology, Georgetown University, Washington, DC, United States
   2. Interdisciplinary Program in Neuroscience, Georgetown University, Washington, DC, United States

   Contribution

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

   For correspondence

   ic400@georgetown.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6372-7288

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