Distinct memories of odor intensity and quality in Drosophila

The influence of stimulus duration on olfactory perception

The duration of a stimulus plays an important role in the coding of sensory information. The role of stimulus duration is extensively studied in the tactile, visual, and auditory system. In the olfactory system, temporal properties of the stimulus are key for obtaining information when an odor is released in the environment. However, how the stimulus duration influences the odor perception is not well understood. To test this, we activated the olfactory bulbs with blue light in mice expressing channelrhodopsin in the olfactory sensory neurons (OSNs) and assessed the relevance of stimulus duration on olfactory perception using foot shock associated active avoidance behavioral task on a "two-arms maze". Our behavior data demonstrate that the stimulus duration plays an important role in olfactory perception and the associated behavioral responses.

Spaced Training Forms Complementary Long-Term Memories of Opposite Valence in Drosophila

Forming long-term memory (LTM) often requires repetitive experience spread over time. Studies in Drosophila suggest aversive olfactory LTM is optimal after spaced training, multiple trials of differential odor conditioning with rest intervals. Memory after spaced training is frequently compared to that after the same number of trials without intervals. Here we show that, after spaced training, flies acquire additional information and form an aversive memory for the shock-paired odor and a slowly emerging and more persistent "safety-memory" for the explicitly unpaired odor. Safety-memory acquisition requires repetition, order, and spacing of the training trials and relies on triggering specific rewarding dopaminergic neurons. Co-existence of aversive and safety memories is evident as depression of odor-specific responses at different combinations of junctions in the mushroom body output network; combining two outputs appears to signal relative safety. Having complementary aversive and safety memories augments LTM performance after spaced training by making the odor preference more certain.

A molecular odorant transduction model and the complexity of spatio-temporal encoding in the Drosophila antenna

Over the past two decades, substantial amount of work has been conducted to characterize different odorant receptors, neuroanatomy and odorant response properties of the early olfactory system of Drosophila melanogaster. Yet many odorant receptors remain only partially characterized, and the odorant transduction process and the axon hillock spiking mechanism of the olfactory sensory neurons (OSNs) have yet to be fully determined. Identity and concentration, two key characteristics of the space of odorants, are encoded by the odorant transduction process. Detailed molecular models of the odorant transduction process are, however, scarce for fruit flies. To address these challenges we advance a comprehensive model of fruit fly OSNs as a cascade consisting of an odorant transduction process (OTP) and a biophysical spike generator (BSG). We model odorant identity and concentration using an odorant-receptor binding rate tensor, modulated by the odorant concentration profile, and an odorant-receptor dissociation rate tensor, and quantitatively describe the mechanics of the molecular ligand binding/dissociation of the OTP. We model the BSG as a Connor-Stevens point neuron. The resulting spatio-temporal encoding model of the Drosophila antenna provides a theoretical foundation for understanding the neural code of both odorant identity and odorant concentration and advances the state-of-the-art in a number of ways. First, it quantifies on the molecular level the spatio-temporal level of complexity of the transformation taking place in the antennae. The concentration-dependent spatio-temporal code at the output of the antenna circuits determines the level of complexity of olfactory processing in the downstream neuropils, such as odorant recognition and olfactory associative learning. Second, the model is biologically validated using multiple electrophysiological recordings. Third, the model demonstrates that the currently available data for odorant-receptor responses only enable the estimation of the affinity of the odorant-receptor pairs. The odorant-dissociation rate is only available for a few odorant-receptor pairs. Finally, our model calls for new experiments for massively identifying the odorant-receptor dissociation rates of relevance to flies.

Identity and concentration, intrinsically embedded in the odorant space, are two key characteristics of olfactory coding that define the level of complexity of neural processing throughout the olfactory system in the fruit fly. In this paper we advance a theoretical foundation for understanding these two characteristics by quantifying mathematically the odorant space and devising a biophysical model of the olfactory sensory neurons (OSNs). To validate our modeling approach, we propose and apply an algorithm to estimate the affinity value and the dissociation rate, the two characteristics that define odorant identity, of multiple odorant-receptor pairs. We then evaluate our model with a multitude of odorant waveforms and demonstrate that the model output reproduces the temporal responses of OSNs obtained from in vivo electrophysiology recordings. Furthermore, we evaluate the model at the OSN population level and quantify on the molecular level the spatio-temporal level of complexity of the transformation taking place between the odorant space and the OSNs. The resulting concentration-dependent spatio-temporal code determines the level of complexity of the input space driving olfactory processing in the downstream neuropils. Lastly, our model demonstrates that the currently available data for OSN responses only enables estimation of affinity value. This calls for new experiments for massively identifying the odorant-receptor dissociation rates of relevance to flies.

Odors: from chemical structures to gaseous plumes

We are immersed within an odorous sea of chemical currents that we parse into individual odors with complex structures. Odors have been posited as determined by the structural relation between the molecules that compose the chemical compounds and their interactions with the receptor site. But, naturally occurring smells are parsed from gaseous odor plumes. To give a comprehensive account of the nature of odors the chemosciences must account for these large distributed entities as well. We offer a focused review of what is known about the perception of odor plumes for olfactory navigation and tracking, which we then connect to what is known about the role odorants play as properties of the plume in determining odor identity with respect to odor quality. We end by motivating our central claim that more research needs to be conducted on the role that odorants play within the odor plume in determining odor identity.

Mechanisms of Sensory Discrimination: Insights from Drosophila Olfaction

All an animal can do to infer the state of its environment is to observe the sensory-evoked activity of its own neurons. These inferences about the presence, quality, or similarity of objects are probabilistic and inform behavioral decisions that are often made in close to real time. Neural systems employ several strategies to facilitate sensory discrimination: Biophysical mechanisms separate the neuronal response distributions in coding space, compress their variances, and combine information from sequential observations. We review how these strategies are implemented in the olfactory system of the fruit fly. The emerging principles of odor discrimination likely apply to other neural circuits of similar architecture.

A fully automated Drosophila olfactory classical conditioning and testing system for behavioral learning and memory assessment

BACKGROUND

Aversive olfactory classical conditioning has been the standard method to assess Drosophila learning and memory behavior for decades, yet training and testing are conducted manually under exceedingly labor-intensive conditions. To overcome this severe limitation, a fully automated, inexpensive system has been developed, which allows accurate and efficient Pavlovian associative learning/memory analyses for high-throughput pharmacological and genetic studies.

NEW METHOD

The automated system employs a linear actuator coupled to an odorant T-maze with airflow-mediated transfer of animals between training and testing stages. Odorant, airflow and electrical shock delivery are automatically administered and monitored during training trials. Control software allows operator-input variables to define parameters of Drosophila learning, short-term memory and long-term memory assays.

RESULTS

The approach allows accurate learning/memory determinations with operational fail-safes. Automated learning indices (immediately post-training) and memory indices (after 24h) are comparable to traditional manual experiments, while minimizing experimenter involvement.

COMPARISON WITH EXISTING METHODS

The automated system provides vast improvements over labor-intensive manual approaches with no experimenter involvement required during either training or testing phases. It provides quality control tracking of airflow rates, odorant delivery and electrical shock treatments, and an expanded platform for high-throughput studies of combinational drug tests and genetic screens. The design uses inexpensive hardware and software for a total cost of ∼$500US, making it affordable to a wide range of investigators.

CONCLUSIONS

This study demonstrates the design, construction and testing of a fully automated Drosophila olfactory classical association apparatus to provide low-labor, high-fidelity, quality-monitored, high-throughput and inexpensive learning and memory behavioral assays.

Outcome learning, outcome expectations, and intentionality in Drosophila

An animal generates behavioral actions because of the effects of these actions in the future. Occasionally, the animal may generate an action in response to a certain event or situation. If the outcome of the action is adaptive, the animal may keep this stimulus–response link in its behavioral repertoire, in case the event or situation occurs again. If a responsive action is innate but the outcome happens to be less adaptive than it had been before, the link may be loosened. This adjustment of outcome expectations involves a particular kind of learning, which will be called “outcome learning.” The present article discusses several examples of outcome learning in Drosophila. Learning and memory are intensely studied in flies, but the focus is on classical conditioning. Outcome learning, a particular form of operant learning, is of special significance, because it modulates outcome expectations that are operational components of action selection and intentionality.

A model for non-monotonic intensity coding

Peripheral neurons of most sensory systems increase their response with increasing stimulus intensity. Behavioural responses, however, can be specific to some intermediate intensity level whose particular value might be innate or associatively learned. Learning such a preference requires an adjustable trans- formation from a monotonic stimulus representation at the sensory periphery to a non-monotonic representation for the motor command. How do neural systems accomplish this task? We tackle this general question focusing on odour-intensity learning in the fruit fly, whose first- and second-order olfactory neurons show monotonic stimulus-response curves. Nevertheless, flies form associative memories specific to particular trained odour intensities. Thus, downstream of the first two olfactory processing layers, odour intensity must be re-coded to enable intensity-specific associative learning. We present a minimal, feed-forward, three-layer circuit, which implements the required transformation by combining excitation, inhibition, and, as a decisive third element, homeostatic plasticity. Key features of this circuit motif are consistent with the known architecture and physiology of the fly olfactory system, whereas alternative mechanisms are either not composed of simple, scalable building blocks or not compatible with physiological observations. The simplicity of the circuit and the robustness of its function under parameter changes make this computational motif an attractive candidate for tuneable non-monotonic intensity coding.

Genetics and behavior: a guide for practitioners

Phenotyping behavior is difficult, partly because behavior is almost always influenced by environment. Using objective terms/criteria to evaluate behaviors is best; the more objective the assessment, the more likely underlying genetic patterns will be identified. Behavioral pathologies, and highly desirable behavioral characteristics/traits, are likely complex, meaning that multiple genes are probably involved, and therefore simple genetic tests are less possible. Breeds can be improved using traditional quantitative genetic methods; unfortunately, this also creates the possibility of inadvertently selecting for covarying undesirable behaviors. Patterns of behaviors within families and breed lines are still the best guidelines for genetic counseling in dogs.

Differential associative training enhances olfactory acuity in Drosophila melanogaster

Training can improve the ability to discriminate between similar, confusable stimuli, including odors. One possibility of enhancing behaviorally expressed discrimination (i.e., sensory acuity) relies on differential associative learning, during which animals are forced to detect the differences between similar stimuli. Drosophila represents a key model organism for analyzing neuronal mechanisms underlying both odor processing and olfactory learning. However, the ability of flies to enhance fine discrimination between similar odors through differential associative learning has not been analyzed in detail. We performed associative conditioning experiments using chemically similar odorants that we show to evoke overlapping neuronal activity in the fly's antennal lobes and highly correlated activity in mushroom body lobes. We compared the animals' performance in discriminating between these odors after subjecting them to one of two types of training: either absolute conditioning, in which only one odor is reinforced, or differential conditioning, in which one odor is reinforced and a second odor is explicitly not reinforced. First, we show that differential conditioning decreases behavioral generalization of similar odorants in a choice situation. Second, we demonstrate that this learned enhancement in olfactory acuity relies on both conditioned excitation and conditioned inhibition. Third, inhibitory local interneurons in the antennal lobes are shown to be required for behavioral fine discrimination between the two similar odors. Fourth, differential, but not absolute, training causes decorrelation of odor representations in the mushroom body. In conclusion, differential training with similar odors ultimately induces a behaviorally expressed contrast enhancement between the two similar stimuli that facilitates fine discrimination.

An information theoretic model of information processing in the Drosophila olfactory system: the role of inhibitory neurons for system efficiency

Fruit flies (Drosophila melanogaster) rely on their olfactory system to process environmental information. This information has to be transmitted without system-relevant loss by the olfactory system to deeper brain areas for learning. Here we study the role of several parameters of the fly's olfactory system and the environment and how they influence olfactory information transmission. We have designed an abstract model of the antennal lobe, the mushroom body and the inhibitory circuitry. Mutual information between the olfactory environment, simulated in terms of different odor concentrations, and a sub-population of intrinsic mushroom body neurons (Kenyon cells) was calculated to quantify the efficiency of information transmission. With this method we study, on the one hand, the effect of different connectivity rates between olfactory projection neurons and firing thresholds of Kenyon cells. On the other hand, we analyze the influence of inhibition on mutual information between environment and mushroom body. Our simulations show an expected linear relation between the connectivity rate between the antennal lobe and the mushroom body and firing threshold of the Kenyon cells to obtain maximum mutual information for both low and high odor concentrations. However, contradicting all-day experiences, high odor concentrations cause a drastic, and unrealistic, decrease in mutual information for all connectivity rates compared to low concentration. But when inhibition on the mushroom body is included, mutual information remains at high levels independent of other system parameters. This finding points to a pivotal role of inhibition in fly information processing without which the system efficiency will be substantially reduced.

Olfactory memories are intensity specific in larval Drosophila

Learning can rely on stimulus quality, stimulus intensity, or a combination of these. Regarding olfaction, the coding of odour quality is often proposed to be combinatorial along the olfactory pathway, and working hypotheses are available concerning short-term associative memory trace formation of odour quality. However, it is less clear how odour intensity is coded, and whether olfactory memory traces include information about the intensity of the learnt odour. Using odour-sugar associative conditioning in larval Drosophila, we first describe the dose-effect curves of learnability across odour intensities for four different odours (n-amyl acetate, 3-octanol, 1-octen-3-ol and benzaldehyde). We then chose odour intensities such that larvae were trained at an intermediate odour intensity, but were tested for retention with either that trained intermediate odour intensity, or with respectively higher or lower intensities. We observed a specificity of retention for the trained intensity for all four odours used. This adds to the appreciation of the richness in 'content' of olfactory short-term memory traces, even in a system as simple as larval Drosophila, and to define the demands on computational models of associative olfactory memory trace formation. We suggest two kinds of circuit architecture that have the potential to accommodate intensity learning, and discuss how they may be implemented in the insect brain.

Early olfactory processing in Drosophila: mechanisms and principles

In the olfactory system of Drosophila melanogaster, it is relatively straightforward to target in vivo measurements of neural activity to specific processing channels. This, together with the numerical simplicity of the Drosophila olfactory system, has produced rapid gains in our understanding of Drosophila olfaction. This review summarizes the neurophysiology of the first two layers of this system: the peripheral olfactory receptor neurons and their postsynaptic targets in the antennal lobe. We now understand in some detail the cellular and synaptic mechanisms that shape odor representations in these neurons. Together, these mechanisms imply that interesting neural adaptations to environmental statistics have occurred. These mechanisms also place some fundamental constraints on early sensory processing that pose challenges for higher brain regions. These findings suggest some general principles with broad relevance to early sensory processing in other modalities.

Imaging a population code for odor identity in the Drosophila mushroom body

The brain represents sensory information in the coordinated activity of neuronal ensembles. Although the microcircuits underlying olfactory processing are well characterized in Drosophila, no studies to date have examined the encoding of odor identity by populations of neurons and related it to the odor specificity of olfactory behavior. Here we used two-photon Ca(2+) imaging to record odor-evoked responses from >100 neurons simultaneously in the Drosophila mushroom body (MB). For the first time, we demonstrate quantitatively that MB population responses contain substantial information on odor identity. Using a series of increasingly similar odor blends, we identified conditions in which odor discrimination is difficult behaviorally. We found that MB ensemble responses accounted well for olfactory acuity in this task. Kenyon cell ensembles with as few as 25 cells were sufficient to match behavioral discrimination accuracy. Using a generalization task, we demonstrated that the MB population code could predict the flies' responses to novel odors. The degree to which flies generalized a learned aversive association to unfamiliar test odors depended upon the relative similarity between the odors' evoked MB activity patterns. Discrimination and generalization place different demands on the animal, yet the flies' choices in these tasks were reliably predicted based on the amount of overlap between MB activity patterns. Therefore, these different behaviors can be understood in the context of a single physiological framework.

Cognition in insects

A traditional view of cognition is that it involves an internal process that represents, tracks or predicts an external process. This is not a general characteristic of all complex neural processing or feedback control, but rather implies specific forms of processing giving rise to specific behavioural capabilities. In this paper, I will review the evidence for such capabilities in insect navigation and learning. Do insects know where they are, or do they only know what to do? Do they learn what stimuli mean, or do they only learn how to behave?

Cellular-resolution population imaging reveals robust sparse coding in the Drosophila mushroom body

Sensory stimuli are represented in the brain by the activity of populations of neurons. In most biological systems, studying population coding is challenging since only a tiny proportion of cells can be recorded simultaneously. Here we used two-photon imaging to record neural activity in the relatively simple Drosophila mushroom body (MB), an area involved in olfactory learning and memory. Using the highly sensitive calcium indicator GCaMP3, we simultaneously monitored the activity of >100 MB neurons in vivo (∼5% of the total population). The MB is thought to encode odors in sparse patterns of activity, but the code has yet to be explored either on a population level or with a wide variety of stimuli. We therefore imaged responses to odors chosen to evaluate the robustness of sparse representations. Different odors activated distinct patterns of MB neurons; however, we found no evidence for spatial organization of neurons by either response probability or odor tuning within the cell body layer. The degree of sparseness was consistent across a wide range of stimuli, from monomolecular odors to artificial blends and even complex natural smells. Sparseness was mainly invariant across concentrations, largely because of the influence of recent odor experience. Finally, in contrast to sensory processing in other systems, no response features distinguished natural stimuli from monomolecular odors. Our results indicate that the fundamental feature of odor processing in the MB is to create sparse stimulus representations in a format that facilitates arbitrary associations between odor and punishment or reward.

Olfactory trace conditioning in Drosophila

The neural representation of a sensory stimulus evolves with time, and animals keep that representation even after stimulus cessation (i.e., a stimulus "trace"). To contrast the memories of an odor and an odor trace, we here establish a rigorous trace conditioning paradigm in the fruit fly, Drosophila melanogaster. We modify the olfactory associative learning paradigm, in which the odor and electric shock are presented with a temporal overlap (delay conditioning). Given a few-second temporal gap between the presentations of the odor and the shock in trace conditioning, the odor trace must be kept until the arrival of electric shock to form associative memory. We found that memories after trace and delay conditioning have striking similarities: both reached the same asymptotic learning level, although at different rates, and both kinds of memory have similar decay kinetics and highly correlated generalization profiles across odors. In search of the physiological correlate of the odor trace, we used in vivo calcium imaging to characterize the odor-evoked activity of the olfactory receptor neurons in the antennal lobe. After the offset of odor presentation, the receptor neurons showed persistent, odor-specific response patterns that lasted for a few seconds and were fundamentally different from the response patterns during the stimulation. Weak correlation between the behavioral odor generalization profile in trace conditioning and the physiological odor similarity profiles in the antennal lobe suggest that the odor trace used for associative learning may be encoded downstream of the olfactory receptor neurons.

Second-order conditioning in Drosophila

Associative conditioning in Drosophila melanogaster has been well documented for several decades. However, most studies report only simple associations of conditioned stimuli (CS, e.g., odor) with unconditioned stimuli (US, e.g., electric shock) to measure learning or establish memory. Here we describe a straightforward second-order conditioning (SOC) protocol that further demonstrates the flexibility of fly behavior. In SOC, a previously conditioned stimulus (CS1) is used as reinforcement for a second conditioned stimulus (CS2) in associative learning. This higher-order context presents an opportunity for reassessing the roles of known learning and memory genes and neuronal networks in a new behavioral paradigm.

Molecular vibration-sensing component in Drosophila melanogaster olfaction

A common explanation of molecular recognition by the olfactory system posits that receptors recognize the structure or shape of the odorant molecule. We performed a rigorous test of shape recognition by replacing hydrogen with deuterium in odorants and asking whether Drosophila melanogaster can distinguish these identically shaped isotopes. We report that flies not only differentiate between isotopic odorants, but can be conditioned to selectively avoid the common or the deuterated isotope. Furthermore, flies trained to discriminate against the normal or deuterated isotopes of a compound, selectively avoid the corresponding isotope of a different odorant. Finally, flies trained to avoid a deuterated compound exhibit selective aversion to an unrelated molecule with a vibrational mode in the energy range of the carbon-deuterium stretch. These findings are inconsistent with a shape-only model for smell, and instead support the existence of a molecular vibration-sensing component to olfactory reception.

The influence of Adh function on ethanol preference and tolerance in adult Drosophila melanogaster

Preference determines behavioral choices such as choosing among food sources and mates. One preference-affecting chemical is ethanol, which guides insects to fermenting fruits or leaves. Here, we show that adult Drosophila melanogaster prefer food containing up to 5% ethanol over food without ethanol and avoid food with high levels (23%) of ethanol. Although female and male flies behaved differently at ethanol-containing food sources, there was no sexual dimorphism in the preference for food containing modest ethanol levels. We also investigated whether Drosophila preference, sensitivity and tolerance to ethanol was related to the activity of alcohol dehydrogenase (Adh), the primary ethanol-metabolizing enzyme in D. melanogaster. Impaired Adh function reduced ethanol preference in both D. melanogaster and a related species, D. sechellia. Adh-impaired flies also displayed reduced aversion to high ethanol concentrations, increased sensitivity to the effects of ethanol on postural control, and negative tolerance/sensitization (i.e., a reduction of the increased resistance to ethanol's effects that normally occurs upon repeated exposure). These data strongly indicate a linkage between ethanol-induced behavior and ethanol metabolism in adult fruit flies: Adh deficiency resulted in reduced preference to low ethanol concentrations and reduced aversion to high ones, despite recovery from ethanol being strongly impaired.

Limited taste discrimination in Drosophila

In the gustatory systems of mammals and flies, different populations of sensory cells recognize different taste modalities, such that there are cells that respond selectively to sugars and others to bitter compounds. This organization readily allows animals to distinguish compounds of different modalities but may limit the ability to distinguish compounds within one taste modality. Here, we developed a behavioral paradigm in Drosophila melanogaster to evaluate directly the tastes that a fly distinguishes. These studies reveal that flies do not discriminate among different sugars, or among different bitter compounds, based on chemical identity. Instead, flies show a limited ability to distinguish compounds within a modality based on intensity or palatability. Taste associative learning, similar to olfactory learning, requires the mushroom bodies, suggesting fundamental similarities in brain mechanisms underlying behavioral plasticity. Overall, these studies provide insight into the discriminative capacity of the Drosophila gustatory system and the modulation of taste behavior.

Synapsin is selectively required for anesthesia-sensitive memory

Odor-shock memory in Drosophila melanogaster consists of heterogeneous components each with different dynamics. We report that a null mutant for the evolutionarily conserved synaptic protein Synapsin entails a memory deficit selectively in early memory, leaving later memory as well as sensory motor function unaffected. Notably, a consolidated memory component remaining after cold-anesthesia is not impaired, suggesting that only anesthesia-sensitive memory [ASM] depends on Synapsin. The lack of Synapsin does not further impair the memory deficit of mutants for the rutabaga gene encoding the type I adenylyl cyclase. This suggests that cAMP signaling, through a Synapsin-dependent mechanism, may underlie the formation of a labile memory component.

Optimizing Drosophila olfactory learning with a semi-automated training device

Drosophila olfactory aversive conditioning has served as a powerful model system with which to elucidate the molecular and neuronal mechanisms underlying memory formation. In the typical protocol, flies are exposed to a constant odor stream while receiving a pulsed electric shock in the conditioning tube of a manual apparatus. We have devised a simple, low-cost semi-automated conditioning apparatus that computationally controls the delivery of odor and shock. A semiconductor-based odor sensor is employed to monitor the change of odor concentration in the training tube. The system thus allows electric shocks to be precisely matched with odor concentration in the training tube. We found that short-term memory performance was improved with a pulsed odor flow protocol, in which odor is presented in short pulses, each paired with electric shock, rather than as a constant flow. The effect of pulsed odor flow might be ascribed to the phenomenon of 'conditioned approach', where approach toward an odor is induced when the electric shock is presented before odor pulse ends. Our data shows that the system is applicable to the study of olfactory memory formation and to the examination of conditioning parameters at a level of detail not practical with a manual apparatus.

Choice strategies in Drosophila are based on competition between olfactory memories

The brain mechanisms by which animals deal with multiple experiences to predict outcomes are not yet fully understood. We explored the choice strategies that flies use to assess degrees of disadvantage, as well as how flies weigh past and recent experiences to guide decisions. Drosophila were exposed to two conditioning events in a T-maze: an odor paired with an electric shock followed by a second odor paired with an electric shock of a different intensity. Subsequently, flies were forced to choose between the two odors. We found that flies chose to avoid the more 'dangerous' odor by a linear subtraction mechanism that was based on two coexisting memories. We also found that flies weighed experiences of the same danger level (60 V electric shocks) according to the times when the experiences had occurred. More recent experiences had a greater impact and past experiences gradually became 'overlooked' during decisions as the time delay between the two events lengthened. However, the past memory was not so much disrupted as it was overshadowed by recent memories during decisions. Finally, when a past experience was more disadvantageous, wild-type flies were able to coordinate both the temporal factor and the degree of disadvantage into their decisions. By contrast, amnesiac mutant flies made choices completely according to the temporal factor, ignoring the degree of disadvantage. Taken together, wild-type flies are able to store multiple olfactory memories and can coherently evaluate learned experiences to guide their decisions according to the degree of disadvantage and/or the temporal factor.

Odour intensity learning in fruit flies

Animals' behaviour towards odours depends on both odour quality and odour intensity. While neuronal coding of odour quality is fairly well studied, how odour intensity is treated by olfactory systems is less clear. Here we study odour intensity processing at the behavioural level, using the fruit fly Drosophila melanogaster. We trained flies by pairing a MEDIUM intensity of an odour with electric shock, and then, at a following test phase, measured flies' conditioned avoidance of either this previously trained MEDIUM intensity or a LOWer or a HIGHer intensity. With respect to 3-octanol, n-amylacetate and 4-methylcyclohexanol, we found that conditioned avoidance is strongest when training and test intensities match, speaking for intensity-specific memories. With respect to a fourth odour, benzaldehyde, on the other hand, we found no such intensity specificity. These results form the basis for further studies of odour intensity processing at the behavioural, neuronal and molecular level.