Associative learning between odorants and mechanosensory punishment in larval Drosophila

High-throughput automated methods for classical and operant conditioning of Drosophila larvae

Learning which stimuli (classical conditioning) or which actions (operant conditioning) predict rewards or punishments can improve chances of survival. However, the circuit mechanisms that underlie distinct types of associative learning are still not fully understood. Automated, high-throughput paradigms for studying different types of associative learning, combined with manipulation of specific neurons in freely behaving animals, can help advance this field. The Drosophila melanogaster larva is a tractable model system for studying the circuit basis of behaviour, but many forms of associative learning have not yet been demonstrated in this animal. Here, we developed a high-throughput (i.e. multi-larva) training system that combines real-time behaviour detection of freely moving larvae with targeted opto- and thermogenetic stimulation of tracked animals. Both stimuli are controlled in either open- or closed-loop, and delivered with high temporal and spatial precision. Using this tracker, we show for the first time that Drosophila larvae can perform classical conditioning with no overlap between sensory stimuli (i.e. trace conditioning). We also demonstrate that larvae are capable of operant conditioning by inducing a bend direction preference through optogenetic activation of reward-encoding serotonergic neurons. Our results extend the known associative learning capacities of Drosophila larvae. Our automated training rig will facilitate the study of many different forms of associative learning and the identification of the neural circuits that underpin them.

A neuronal arms race: the role of learning in parasitoid-host interactions

Parasitic wasps and their larval hosts are intimately connected by an array of behavioral adaptations and counter-adaptations. This co-evolution has led to highly specific, natural variation in learning rates and memory consolidation in parasitoid wasps. Similarly, the hosts of the parasitoids show specific sensory adaptations as well as non-associative learning strategies for parasitoid avoidance. However, these neuronal and behavioral adaptations of both hosts and wasps have so far been studied largely apart from each other. Here we argue that a parallel investigation of the nervous system in wasps and their hosts might lead to novel insights into the evolution of insect behavior and the neurobiology of learning and memory.

A dual-stimulation strategy in a micro-chip for the investigation of mechanical associative learning behavior of C. elegans

During the past decades, few micro-devices for analysis of associative learning behavior have been reported. In this work, an agarose-PDMS hybridized micro-chip was developed to establish a new associative learning model between mechanosensation and food reward in C. elegans. The micro-chip consisted of column arrays which mimicked mechanical stimulation to C. elegans. After trained by pairing bacterial food and mechanical stimuli in the chip, the worms exhibited associative learning behavior and gathered in the regions where there was food during training. The key research findings include: (1) Associative learning behavior of C. elegans could be generated and quantitatively analyzed by this developed micro-chip. (2) Associative learning behavior could be enhanced by extending the training time and developmental stage. (3) Mechanosensation-related genes and neurotransmitters signals had effects on the learning behavior. (4) The associative learning ability could be strengthened by exogenous dopamine in both wild type and mutants. We validated that the design of the micro-chip was useful and convenient for the study of learning behavior based on mechanosensation.

Recurrent architecture for adaptive regulation of learning in the insect brain

Dopaminergic neurons (DANs) drive learning across the animal kingdom, but the upstream circuits that regulate their activity and thereby learning remain poorly understood. We provide a synaptic-resolution connectome of the circuitry upstream of all DANs in a learning center, the mushroom body of Drosophila larva. We discover afferent sensory pathways and a large population of neurons that provide feedback from mushroom body output neurons and link distinct memory systems (aversive and appetitive). We combine this with functional studies of DANs and their presynaptic partners and with comprehensive circuit modeling. We find that DANs compare convergent feedback from aversive and appetitive systems, which enables the computation of integrated predictions that may improve future learning. Computational modeling reveals that the discovered feedback motifs increase model flexibility and performance on learning tasks. Our study provides the most detailed view to date of biological circuit motifs that support associative learning.

Softness sensing and learning in Drosophila larvae

Mechanosensation provides animals with important sensory information in addition to olfaction and gustation during feeding behavior. Here, we used Drosophila melanogaster larvae to investigate the role of softness sensing in behavior and learning. In the natural environment, larvae need to dig into soft foods for feeding. Finding foods that are soft enough to dig into is likely to be essential for their survival. We report that larvae can discriminate between different agar concentrations and prefer softer agar. Interestingly, we show that larvae on a harder surface search for a softer surface using memory associated with an odor, and that they evaluate foods by balancing softness and sweetness. These findings suggest that larvae integrate mechanosensory information with chemosensory input while foraging. Moreover, we found that the larval preference for softness is affected by genetic background.

One-trial learning in larval Drosophila

Animals of many species are capable of “small data” learning, that is, of learning without repetition. Here we introduce larval Drosophila melanogaster as a relatively simple study case for such one-trial learning. Using odor-food associative conditioning, we first show that a sugar that is both sweet and nutritious (fructose) and sugars that are only sweet (arabinose) or only nutritious (sorbitol) all support appetitive one-trial learning. The same is the case for the optogenetic activation of a subset of dopaminergic neurons innervating the mushroom body, the memory center of the insects. In contrast, no one-trial learning is observed for an amino acid reward (aspartic acid). As regards the aversive domain, one-trial learning is demonstrated for high-concentration sodium chloride, but is not observed for a bitter tastant (quinine). Second, we provide follow-up, parametric analyses of odor-fructose learning. Specifically, we ascertain its dependency on the number and duration of training trials, the requirements for the behavioral expression of one-trial odor-fructose memory, its temporal stability, and the feasibility of one-trial differential conditioning. Our results set the stage for a neurogenetic analysis of one-trial learning and define the requirements for modeling mnemonic processes in the larva.

Characterization of Drosophila Nidogen/entactin reveals roles in basement membrane stability, barrier function and nervous system patterning

Basement membranes (BMs) are specialized layers of extracellular matrix (ECM) mainly composed of Laminin, type IV Collagen, Perlecan and Nidogen/entactin (NDG). Recent in vivo studies challenged the initially proposed role of NDG as a major ECM linker molecule by revealing dispensability for viability and BM formation. Here, we report the characterization of the single Ndg gene in Drosophila. Embryonic Ndg expression was primarily observed in mesodermal tissues and the chordotonal organs, whereas NDG protein localized to all BMs. Although loss of Laminin strongly affected BM localization of NDG, Ndg-null mutants exhibited no overt changes in the distribution of BM components. Although Drosophila Ndg mutants were viable, loss of NDG led to ultrastructural BM defects that compromised barrier function and stability in vivo Moreover, loss of NDG impaired larval crawling behavior and reduced responses to vibrational stimuli. Further morphological analysis revealed accompanying defects in the larval peripheral nervous system, especially in the chordotonal organs and the neuromuscular junction (NMJ). Taken together, our analysis suggests that NDG is not essential for BM assembly but mediates BM stability and ECM-dependent neural plasticity during Drosophila development.

Maggot Instructor: Semi-Automated Analysis of Learning and Memory in Drosophila Larvae

For several decades, Drosophila has been widely used as a suitable model organism to study the fundamental processes of associative olfactory learning and memory. More recently, this condition also became true for the Drosophila larva, which has become a focus for learning and memory studies based on a number of technical advances in the field of anatomical, molecular, and neuronal analyses. The ongoing efforts should be mentioned to reconstruct the complete connectome of the larval brain featuring a total of about 10,000 neurons and the development of neurogenic tools that allow individual manipulation of each neuron. By contrast, standardized behavioral assays that are commonly used to analyze learning and memory in Drosophila larvae exhibit no such technical development. Most commonly, a simple assay with Petri dishes and odor containers is used; in this method, the animals must be manually transferred in several steps. The behavioral approach is therefore labor-intensive and limits the capacity to conduct large-scale genetic screenings in small laboratories. To circumvent these limitations, we introduce a training device called the Maggot Instructor. This device allows automatic training up to 10 groups of larvae in parallel. To achieve such goal, we used fully automated, computer-controlled optogenetic activation of single olfactory neurons in combination with the application of electric shocks. We showed that Drosophila larvae trained with the Maggot Instructor establish an odor-specific memory, which is independent of handling and non-associative effects. The Maggot Instructor will allow to investigate the large collections of genetically modified larvae in a short period and with minimal human resources. Therefore, the Maggot Instructor should be able to help extensive behavioral experiments in Drosophila larvae to keep up with the current technical advancements. In the longer term, this condition will lead to a better understanding of how learning and memory are organized at the cellular, synaptic, and molecular levels in Drosophila larvae.

Odor-taste learning in Drosophila larvae

The Drosophila larva is an attractive model system to study fundamental questions in the field of neuroscience. Like the adult fly, the larva offers a seemingly unlimited genetic toolbox, which allows one to visualize, silence or activate neurons down to the single cell level. This, combined with its simplicity in terms of cell numbers, offers a useful system to study the neuronal correlates of complex processes including associative odor-taste learning and memory formation. Here, we summarize the current knowledge about odor-taste learning and memory at the behavioral level and integrate the recent progress on the larval connectome to shed light on the sub-circuits that allow Drosophila larvae to integrate present sensory input in the context of past experience and to elicit an appropriate behavioral response.

The Ol1mpiad: concordance of behavioural faculties of stage 1 and stage 3 Drosophila larvae

Mapping brain function to brain structure is a fundamental task for neuroscience. For such an endeavour, the Drosophila larva is simple enough to be tractable, yet complex enough to be interesting. It features about 10,000 neurons and is capable of various taxes, kineses and Pavlovian conditioning. All its neurons are currently being mapped into a light-microscopical atlas, and Gal4 strains are being generated to experimentally access neurons one at a time. In addition, an electron microscopic reconstruction of its nervous system seems within reach. Notably, this electron microscope-based connectome is being drafted for a stage 1 larva – because stage 1 larvae are much smaller than stage 3 larvae. However, most behaviour analyses have been performed for stage 3 larvae because their larger size makes them easier to handle and observe. It is therefore warranted to either redo the electron microscopic reconstruction for a stage 3 larva or to survey the behavioural faculties of stage 1 larvae. We provide the latter. In a community-based approach we called the Ol1mpiad, we probed stage 1 Drosophila larvae for free locomotion, feeding, responsiveness to substrate vibration, gentle and nociceptive touch, burrowing, olfactory preference and thermotaxis, light avoidance, gustatory choice of various tastants plus odour–taste associative learning, as well as light/dark–electric shock associative learning. Quantitatively, stage 1 larvae show lower scores in most tasks, arguably because of their smaller size and lower speed. Qualitatively, however, stage 1 larvae perform strikingly similar to stage 3 larvae in almost all cases. These results bolster confidence in mapping brain structure and behaviour across developmental stages.

Genetic Dissection of Aversive Associative Olfactory Learning and Memory in Drosophila Larvae

Memory formation is a highly complex and dynamic process. It consists of different phases, which depend on various neuronal and molecular mechanisms. In adult Drosophila it was shown that memory formation after aversive Pavlovian conditioning includes—besides other forms—a labile short-term component that consolidates within hours to a longer-lasting memory. Accordingly, memory formation requires the timely controlled action of different neuronal circuits, neurotransmitters, neuromodulators and molecules that were initially identified by classical forward genetic approaches. Compared to adult Drosophila, memory formation was only sporadically analyzed at its larval stage. Here we deconstruct the larval mnemonic organization after aversive olfactory conditioning. We show that after odor-high salt conditioning larvae form two parallel memory phases; a short lasting component that depends on cyclic adenosine 3’5’-monophosphate (cAMP) signaling and synapsin gene function. In addition, we show for the first time for Drosophila larvae an anesthesia resistant component, which relies on radish and bruchpilot gene function, protein kinase C activity, requires presynaptic output of mushroom body Kenyon cells and dopamine function. Given the numerical simplicity of the larval nervous system this work offers a unique prospect for studying memory formation of defined specifications, at full-brain scope with single-cell, and single-synapse resolution.

Learning and memory helps organisms to predict and adapt to events in their environment. Gained experience leaves traces of memory in the nervous system. Yet, memory formation in vertebrates and invertebrates is a highly complex and dynamic process that consists of different phases, which depend on various neuronal and molecular mechanisms. To understand which changes occur in a brain when it learns, we applied a reductionist approach. Instead of studying complex cases, we analyzed learning and memory in Drosophila larvae that have a simple brain that is genetically and behaviorally accessible and consists of only about 10,000 neurons. Drosophila larvae are able to learn to associate an odor with punishing high salt concentrations. It is therefore possible to correlate changes in larval behavior with molecular events in identifiable neurons after classical olfactory conditioning. We show that under these circumstances larvae form two parallel memory phases; a short lasting component (lSTM) that is molecularly conserved throughout the animal kingdom as it depends on the classical cAMP pathway. In parallel they establish a larval anesthesia resistant memory (lARM) that relies on a different molecular signal. lARM has not been described in larvae before.

Learning the specific quality of taste reinforcement in larval Drosophila

The only property of reinforcement insects are commonly thought to learn about is its value. We show that larval Drosophila not only remember the value of reinforcement (How much?), but also its quality (What?). This is demonstrated both within the appetitive domain by using sugar vs amino acid as different reward qualities, and within the aversive domain by using bitter vs high-concentration salt as different qualities of punishment. From the available literature, such nuanced memories for the quality of reinforcement are unexpected and pose a challenge to present models of how insect memory is organized. Given that animals as simple as larval Drosophila, endowed with but 10,000 neurons, operate with both reinforcement value and quality, we suggest that both are fundamental aspects of mnemonic processing-in any brain.

Immediate and punitive impact of mechanosensory disturbance on olfactory behaviour of larval Drosophila

The ability to respond to and to learn about mechanosensory disturbance is widespread among animals. Using Drosophila larvae, we describe how the frequency of mechanosensory disturbance ('buzz') affects three aspects of behaviour: free locomotion, innate olfactory preference, and potency as a punishment. We report that (i) during 2-3 seconds after buzz onset the larvae slowed down and then turned, arguably to escape this situation; this was seen for buzz frequencies of 10, 100, and 1000 Hz, (ii) innate olfactory preference was reduced when tested in the presence of the buzz; this effect was strongest for the 100 Hz frequency, (iii) after odour-buzz associative training, we observed escape from the buzz-associated odour; this effect was apparent for 10 and 100, but not for 1000 Hz. We discuss the multiple behavioural effects of mechanosensation and stress that the immediate effects on locomotion and the impact as punishment differ in their frequency-dependence. Similar dissociations between immediate, reflexive behavioural effects and reinforcement potency were previously reported for sweet, salty and bitter tastants. It should be interesting to see how these features map onto the organization of sensory, ascending pathways.

Pain-relief learning in flies, rats, and man: basic research and applied perspectives

Memories relating to a painful, negative event are adaptive and can be stored for a lifetime to support preemptive avoidance, escape, or attack behavior. However, under unfavorable circumstances such memories can become overwhelmingly powerful. They may trigger excessively negative psychological states and uncontrollable avoidance of locations, objects, or social interactions. It is therefore obvious that any process to counteract such effects will be of value. In this context, we stress from a basic-research perspective that painful, negative events are "Janus-faced" in the sense that there are actually two aspects about them that are worth remembering: What made them happen and what made them cease. We review published findings from fruit flies, rats, and man showing that both aspects, respectively related to the onset and the offset of the negative event, induce distinct and oppositely valenced memories: Stimuli experienced before an electric shock acquire negative valence as they signal upcoming punishment, whereas stimuli experienced after an electric shock acquire positive valence because of their association with the relieving cessation of pain. We discuss how memories for such punishment- and relief-learning are organized, how this organization fits into the threat-imminence model of defensive behavior, and what perspectives these considerations offer for applied psychology in the context of trauma, panic, and nonsuicidal self-injury.

Maggot learning and Synapsin function

Drosophila larvae are focused on feeding and have few neurons. Within these bounds, however, there still are behavioural degrees of freedom. This review is devoted to what these elements of flexibility are, and how they come about. Regarding odour-food associative learning, the emerging working hypothesis is that when a mushroom body neuron is activated as a part of an odour-specific set of mushroom body neurons, and coincidently receives a reinforcement signal carried by aminergic neurons, the AC-cAMP-PKA cascade is triggered. One substrate of this cascade is Synapsin, and therefore this review features a general and comparative discussion of Synapsin function. Phosphorylation of Synapsin ensures an alteration of synaptic strength between this mushroom body neuron and its target neuron(s). If the trained odour is encountered again, the pattern of mushroom body neurons coding this odour is activated, such that their modified output now allows conditioned behaviour. However, such an activated memory trace does not automatically cause conditioned behaviour. Rather, in a process that remains off-line from behaviour, the larvae compare the value of the testing situation (based on gustatory input) with the value of the odour-activated memory trace (based on mushroom body output). The circuit towards appetitive conditioned behaviour is closed only if the memory trace suggests that tracking down the learned odour will lead to a place better than the current one. It is this expectation of a positive outcome that is the immediate cause of appetitive conditioned behaviour. Such conditioned search for reward corresponds to a view of aversive conditioned behaviour as conditioned escape from punishment, which is enabled only if there is something to escape from - much in the same way as we only search for things that are not there, and run for the emergency exit only when there is an emergency. One may now ask whether beyond 'value' additional information about reinforcement is contained in the memory trace, such as information about the kind and intensity of the reinforcer used. The Drosophila larva may allow us to develop satisfyingly detailed accounts of such mnemonic richness - if it exists.

Appetitive associative olfactory learning in Drosophila larvae

In the following we describe the methodological details of appetitive associative olfactory learning in Drosophila larvae. The setup, in combination with genetic interference, provides a handle to analyze the neuronal and molecular fundamentals of specifically associative learning in a simple larval brain. Organisms can use past experience to adjust present behavior. Such acquisition of behavioral potential can be defined as learning, and the physical bases of these potentials as memory traces. Neuroscientists try to understand how these processes are organized in terms of molecular and neuronal changes in the brain by using a variety of methods in model organisms ranging from insects to vertebrates. For such endeavors it is helpful to use model systems that are simple and experimentally accessible. The Drosophila larva has turned out to satisfy these demands based on the availability of robust behavioral assays, the existence of a variety of transgenic techniques and the elementary organization of the nervous system comprising only about 10,000 neurons (albeit with some concessions: cognitive limitations, few behavioral options, and richness of experience questionable). Drosophila larvae can form associations between odors and appetitive gustatory reinforcement like sugar. In a standard assay, established in the lab of B. Gerber, animals receive a two-odor reciprocal training: A first group of larvae is exposed to an odor A together with a gustatory reinforcer (sugar reward) and is subsequently exposed to an odor B without reinforcement. Meanwhile a second group of larvae receives reciprocal training while experiencing odor A without reinforcement and subsequently being exposed to odor B with reinforcement (sugar reward). In the following both groups are tested for their preference between the two odors. Relatively higher preferences for the rewarded odor reflect associative learning--presented as a performance index (PI). The conclusion regarding the associative nature of the performance index is compelling, because apart from the contingency between odors and tastants, other parameters, such as odor and reward exposure, passage of time and handling do not differ between the two groups.

A behavior-based circuit model of how outcome expectations organize learned behavior in larval Drosophila

Drosophila larvae combine a numerically simple brain, a correspondingly moderate behavioral complexity, and the availability of a rich toolbox for transgenic manipulation. This makes them attractive as a study case when trying to achieve a circuit-level understanding of behavior organization. From a series of behavioral experiments, we suggest a circuitry of chemosensory processing, odor-tastant memory trace formation, and the "decision" process to behaviorally express these memory traces--or not. The model incorporates statements about the neuronal organization of innate vs. conditioned chemosensory behavior, and the types of interaction between olfactory and gustatory pathways during the establishment as well as the behavioral expression of odor-tastant memory traces. It in particular suggests that innate olfactory behavior is responsive in nature, whereas conditioned olfactory behavior is captured better when seen as an action in pursuit of its outcome. It incorporates the available neuroanatomical and behavioral data and thus should be useful as scaffold for the ongoing investigations of the chemo-behavioral system in larval Drosophila.