Olfactory learning skews mushroom body output pathways to steer behavioral choice in Drosophila

Compensatory enhancement of input maintains aversive dopaminergic reinforcement in hungry Drosophila

Hungry animals need compensatory mechanisms to maintain flexible brain function, while modulation reconfigures circuits to prioritize resource seeking. In Drosophila, hunger inhibits aversively reinforcing dopaminergic neurons (DANs) to permit the expression of food-seeking memories. Multitasking the reinforcement system for motivation potentially undermines aversive learning. We find that chronic hunger mildly enhances aversive learning and that satiated-baseline and hunger-enhanced learning require endocrine adipokinetic hormone (AKH) signaling. Circulating AKH influences aversive learning via its receptor in four neurons in the ventral brain, two of which are octopaminergic. Connectomics revealed AKH receptor-expressing neurons to be upstream of several classes of ascending neurons, many of which are presynaptic to aversively reinforcing DANs. Octopaminergic modulation of and output from at least one of these ascending pathways is required for shock- and bitter-taste-reinforced aversive learning. We propose that coordinated enhancement of input compensates for hunger-directed inhibition of aversive DANs to preserve reinforcement when required.

Single dopaminergic neuron DAN-c1 in Drosophila larval brain mediates aversive olfactory learning through D2-like receptors

The intricate relationship between the dopaminergic system and olfactory associative learning in Drosophila has been an intense scientific inquiry. Leveraging the formidable genetic tools, we conducted a screening of 57 dopaminergic drivers, leading to the discovery of DAN-c1 driver, uniquely targeting the single dopaminergic neuron (DAN) in each brain hemisphere. While the involvement of excitatory D1-like receptors is well-established, the role of D2-like receptors (D2Rs) remains underexplored. Our investigation reveals the expression of D2Rs in both DANs and the mushroom body (MB) of third instar larval brains. Silencing D2Rs in DAN-c1 via microRNA disrupts aversive learning, further supported by optogenetic activation of DAN-c1 during training, affirming the inhibitory role of D2R autoreceptor. Intriguingly, D2R knockdown in the MB impairs both appetitive and aversive learning. These findings elucidate the distinct contributions of D2Rs in diverse brain structures, providing novel insights into the molecular mechanisms governing associative learning in Drosophila larvae.

Diverse memory paradigms in Drosophila reveal diverse neural mechanisms

In this review, we aggregated the different types of learning and memory paradigms developed in adult Drosophila and attempted to assess the similarities and differences in the neural mechanisms supporting diverse types of memory. The simplest association memory assays are conditioning paradigms (olfactory, visual, and gustatory). A great deal of work has been done on these memories, revealing hundreds of genes and neural circuits supporting this memory. Variations of conditioning assays (reversal learning, trace conditioning, latent inhibition, and extinction) also reveal interesting memory mechanisms, whereas mechanisms supporting spatial memory (thermal maze, orientation memory, and heat box) and the conditioned suppression of innate behaviors (phototaxis, negative geotaxis, anemotaxis, and locomotion) remain largely unexplored. In recent years, there has been an increased interest in multisensory and multicomponent memories (context-dependent and cross-modal memory) and higher-order memory (sensory preconditioning and second-order conditioning). Some of this work has revealed how the intricate mushroom body (MB) neural circuitry can support more complex memories. Finally, the most complex memories are arguably those involving social memory: courtship conditioning and social learning (mate-copying and egg-laying behaviors). Currently, very little is known about the mechanisms supporting social memories. Overall, the MBs are important for association memories of multiple sensory modalities and multisensory integration, whereas the central complex is important for place, orientation, and navigation memories. Interestingly, several different types of memory appear to use similar or variants of the olfactory conditioning neural circuitry, which are repurposed in different ways.

Skewing information flow through pre- and postsynaptic plasticity in the mushroom bodies of Drosophila

Animal brains need to store information to construct a representation of their environment. Knowledge of what happened in the past allows both vertebrates and invertebrates to predict future outcomes by recalling previous experience. Although invertebrate and vertebrate brains share common principles at the molecular, cellular, and circuit-architectural levels, there are also obvious differences as exemplified by the use of acetylcholine versus glutamate as the considered main excitatory neurotransmitters in the respective central nervous systems. Nonetheless, across central nervous systems, synaptic plasticity is thought to be a main substrate for memory storage. Therefore, how brain circuits and synaptic contacts change following learning is of fundamental interest for understanding brain computations tied to behavior in any animal. Recent progress has been made in understanding such plastic changes following olfactory associative learning in the mushroom bodies (MBs) of Drosophila A current framework of memory-guided behavioral selection is based on the MB skew model, in which antagonistic synaptic pathways are selectively changed in strength. Here, we review insights into plasticity at dedicated Drosophila MB output pathways and update what is known about the plasticity of both pre- and postsynaptic compartments of Drosophila MB neurons.

An integrative sensor of body states: how the mushroom body modulates behavior depending on physiological context

The brain constantly compares past and present experiences to predict the future, thereby enabling instantaneous and future behavioral adjustments. Integration of external information with the animal's current internal needs and behavioral state represents a key challenge of the nervous system. Recent advancements in dissecting the function of the Drosophila mushroom body (MB) at the single-cell level have uncovered its three-layered logic and parallel systems conveying positive and negative values during associative learning. This review explores a lesser-known role of the MB in detecting and integrating body states such as hunger, thirst, and sleep, ultimately modulating motivation and sensory-driven decisions based on the physiological state of the fly. State-dependent signals predominantly affect the activity of modulatory MB input neurons (dopaminergic, serotoninergic, and octopaminergic), but also induce plastic changes directly at the level of the MB intrinsic and output neurons. Thus, the MB emerges as a tightly regulated relay station in the insect brain, orchestrating neuroadaptations due to current internal and behavioral states leading to short- but also long-lasting changes in behavior. While these adaptations are crucial to ensure fitness and survival, recent findings also underscore how circuit motifs in the MB may reflect fundamental design principles that contribute to maladaptive behaviors such as addiction or depression-like symptoms.

Roles of feedback and feed-forward networks of dopamine subsystems: insights from Drosophila studies

Across animal species, dopamine-operated memory systems comprise anatomically segregated, functionally diverse subsystems. Although individual subsystems could operate independently to support distinct types of memory, the logical interplay between subsystems is expected to enable more complex memory processing by allowing existing memory to influence future learning. Recent comprehensive ultrastructural analysis of the Drosophila mushroom body revealed intricate networks interconnecting the dopamine subsystems-the mushroom body compartments. Here, we review the functions of some of these connections that are beginning to be understood. Memory consolidation is mediated by two different forms of network: A recurrent feedback loop within a compartment maintains sustained dopamine activity required for consolidation, whereas feed-forward connections across compartments allow short-term memory formation in one compartment to open the gate for long-term memory formation in another compartment. Extinction and reversal of aversive memory rely on a similar feed-forward circuit motif that signals omission of punishment as a reward, which triggers plasticity that counteracts the original aversive memory trace. Finally, indirect feed-forward connections from a long-term memory compartment to short-term memory compartments mediate higher-order conditioning. Collectively, these emerging studies indicate that feedback control and hierarchical connectivity allow the dopamine subsystems to work cooperatively to support diverse and complex forms of learning.

Active forgetting and neuropsychiatric diseases

Recent and pioneering animal research has revealed the brain utilizes a variety of molecular, cellular, and network-level mechanisms used to forget memories in a process referred to as "active forgetting". Active forgetting increases behavioral flexibility and removes irrelevant information. Individuals with impaired active forgetting mechanisms can experience intrusive memories, distressing thoughts, and unwanted impulses that occur in neuropsychiatric diseases. The current evidence indicates that active forgetting mechanisms degrade, or mask, molecular and cellular memory traces created in synaptic connections of "engram cells" that are specific for a given memory. Combined molecular genetic/behavioral studies using Drosophila have uncovered a complex system of cellular active-forgetting pathways within engram cells that is regulated by dopamine neurons and involves dopamine-nitric oxide co-transmission and reception, endoplasmic reticulum Ca2+ signaling, and cytoskeletal remodeling machinery regulated by small GTPases. Some of these molecular cellular mechanisms have already been found to be conserved in mammals. Interestingly, some pathways independently regulate forgetting of distinct memory types and temporal phases, suggesting a multi-layering organization of forgetting systems. In mammals, active forgetting also involves modulation of memory trace synaptic strength by altering AMPA receptor trafficking. Furthermore, active-forgetting employs network level mechanisms wherein non-engram neurons, newly born-engram neurons, and glial cells regulate engram synapses in a state and experience dependent manner. Remarkably, there is evidence for potential coordination between the network and cellular level forgetting mechanisms. Finally, subjects with several neuropsychiatric diseases have been tested and shown to be impaired in active forgetting. Insights obtained from research on active forgetting in animal models will continue to enrich our understanding of the brain dysfunctions that occur in neuropsychiatric diseases.

Dual roles of dopaminergic pathways in olfactory learning and memory in the oriental fruit fly, Bactrocera dorsalis

Dopamine (DA) is a key regulator of associative learning and memory in both vertebrates and invertebrates, and it is widely believed that DA plays a key role in aversive conditioning in invertebrates. However, the idea that DA is involved only in aversive conditioning has been challenged in recent studies on the fruit fly (Drosophila melanogaster), ants and crabs, suggesting diverse functions of DA modulation on associative plasticity. Here, we present the results of DA modulation in aversive olfactory conditioning with DEET punishment and appetitive olfactory conditioning with sucrose reward in the oriental fruit fly, Bactrocera dorsalis. Injection of DA receptor antagonist fluphenazine or chlorpromazine into these flies led to impaired aversive learning, but had no effect on the appetitive learning. DA receptor antagonists impaired both aversive and appetitive long-term memory retention. Interestingly, the impairment on appetitive memory was rescued not only by DA but also by octopamine (OA). Blocking the OA receptors also impaired the appetitive memory retention, but this impairment could only be rescued by OA, not by DA. Thus, we conclude that in B. dorsalis, OA and DA pathways mediate independently the appetitive and aversive learning, respectively. These two pathways, however, are organized in series in mediating appetitive memory retrieval with DA pathway being at upstream. Thus, OA and DA play dual roles in associative learning and memory retrieval, but their pathways are organized differently in these two cognitive processes - parallel organization for learning acquisition and serial organization for memory retrieval.

Prediction error drives associative learning and conditioned behavior in a spiking model of Drosophila larva

Predicting reinforcement from sensory cues is beneficial for goal-directed behavior. In insect brains, underlying associations between cues and reinforcement, encoded by dopaminergic neurons, are formed in the mushroom body. We propose a spiking model of the Drosophila larva mushroom body. It includes a feedback motif conveying learned reinforcement expectation to dopaminergic neurons, which can compute prediction error as the difference between expected and present reinforcement. We demonstrate that this can serve as a driving force in learning. When combined with synaptic homeostasis, our model accounts for theoretically derived features of acquisition and loss of associations that depend on the intensity of the reinforcement and its temporal proximity to the cue. From modeling olfactory learning over the time course of behavioral experiments and simulating the locomotion of individual larvae toward or away from odor sources in a virtual environment, we conclude that learning driven by prediction errors can explain larval behavior.

Minimal circuit motifs for second-order conditioning in the insect mushroom body

In well-established first-order conditioning experiments, the concurrence of a sensory cue with reinforcement forms an association, allowing the cue to predict future reinforcement. In the insect mushroom body, a brain region central to learning and memory, such associations are encoded in the synapses between its intrinsic and output neurons. This process is mediated by the activity of dopaminergic neurons that encode reinforcement signals. In second-order conditioning, a new sensory cue is paired with an already established one that presumably activates dopaminergic neurons due to its predictive power of the reinforcement. We explored minimal circuit motifs in the mushroom body for their ability to support second-order conditioning using mechanistic models. We found that dopaminergic neurons can either be activated directly by the mushroom body's intrinsic neurons or via feedback from the output neurons via several pathways. We demonstrated that the circuit motifs differ in their computational efficiency and robustness. Beyond previous research, we suggest an additional motif that relies on feedforward input of the mushroom body intrinsic neurons to dopaminergic neurons as a promising candidate for experimental evaluation. It differentiates well between trained and novel stimuli, demonstrating robust performance across a range of model parameters.

The mushroom body output encodes behavioral decision during sensory-motor transformation

Animals form a behavioral decision by evaluating sensory evidence on the background of past experiences and the momentary motivational state. In insects, we still lack understanding of how and at which stage of the recurrent sensory-motor pathway behavioral decisions are formed. The mushroom body (MB), a central brain structure in insects1 and crustaceans,2,3 integrates sensory input of different modalities4,5,6 with the internal state, the behavioral state, and external sensory context7,8,9,10 through a large number of recurrent, mostly neuromodulatory inputs,11,12 implicating a functional role for MBs in state-dependent sensory-motor transformation.13,14 A number of classical conditioning studies in honeybees15,16 and fruit flies17,18,19 have provided accumulated evidence that at its output, the MB encodes the valence of a sensory stimulus with respect to its behavioral relevance. Recent work has extended this notion of valence encoding to the context of innate behaviors.8,20,21,22 Here, we co-analyzed a defined feeding behavior and simultaneous extracellular single-unit recordings from MB output neurons (MBONs) in the cockroach in response to timed sensory stimulation with odors. We show that clear neuronal responses occurred almost exclusively during behaviorally responded trials. Early MBON responses to the sensory stimulus preceded the feeding behavior and predicted its occurrence or non-occurrence from the single-trial population activity. Our results therefore suggest that at its output, the MB does not merely encode sensory stimulus valence. We hypothesize instead that the MB output represents an integrated signal of internal state, momentary environmental conditions, and experience-dependent memory to encode a behavioral decision.

Internal-state-dependent modulation of olfactory responses: a tale of dopamine neurons in the adult Drosophila mushroom body

Olfaction is a vital sense that insects use to forage and interact with each other. When an insect smells an odor, its nervous system processes the odor information and transforms it into an appropriate behavioral decision. Olfactory processing and transformation are not label-lined, but instead are modulated by internal states. The vinegar fly, Drosophila melanogaster, has become a primary model organism for studying this modulation. It has been observed that internal state modulates olfactory behaviors in multiple sites of the fly brain. In this review article, I focus on the mushroom body, a computational center in the fly brain, and discuss how the dopamine system in this brain region mediates internal-state signals and shapes olfactory responses in adult flies.

Independent insulin signaling modulators govern hot avoidance under different feeding states

Thermosensation is critical for the survival of animals. However, mechanisms through which nutritional status modulates thermosensation remain unclear. Herein, we showed that hungry Drosophila exhibit a strong hot avoidance behavior (HAB) compared to food-sated flies. We identified that hot stimulus increases the activity of α'β' mushroom body neurons (MBns), with weak activity in the sated state and strong activity in the hungry state. Furthermore, we showed that α'β' MBn receives the same level of hot input from the mALT projection neurons via cholinergic transmission in sated and hungry states. Differences in α'β' MBn activity between food-sated and hungry flies following heat stimuli are regulated by distinct Drosophila insulin-like peptides (Dilps). Dilp2 is secreted by insulin-producing cells (IPCs) and regulates HAB during satiety, whereas Dilp6 is secreted by the fat body and regulates HAB during the hungry state. We observed that Dilp2 induces PI3K/AKT signaling, whereas Dilp6 induces Ras/ERK signaling in α'β' MBn to regulate HAB in different feeding conditions. Finally, we showed that the 2 α'β'-related MB output neurons (MBONs), MBON-α'3 and MBON-β'1, are necessary for the output of integrated hot avoidance information from α'β' MBn. Our results demonstrate the presence of dual insulin modulation pathways in α'β' MBn, which are important for suitable behavioral responses in Drosophila during thermoregulation under different feeding states.

An antagonism between Spinophilin and Syd-1 operates upstream of memory-promoting presynaptic long-term plasticity

We still face fundamental gaps in understanding how molecular plastic changes of synapses intersect with circuit operation to define behavioral states. Here, we show that an antagonism between two conserved regulatory proteins, Spinophilin (Spn) and Syd-1, controls presynaptic long-term plasticity and the maintenance of olfactory memories in Drosophila. While Spn mutants could not trigger nanoscopic active zone remodeling under homeostatic challenge and failed to stably potentiate neurotransmitter release, concomitant reduction of Syd-1 rescued all these deficits. The Spn/Syd-1 antagonism converged on active zone close F-actin, and genetic or acute pharmacological depolymerization of F-actin rescued the Spn deficits by allowing access to synaptic vesicle release sites. Within the intrinsic mushroom body neurons, the Spn/Syd-1 antagonism specifically controlled olfactory memory stabilization but not initial learning. Thus, this evolutionarily conserved protein complex controls behaviorally relevant presynaptic long-term plasticity, also observed in the mammalian brain but still enigmatic concerning its molecular mechanisms and behavioral relevance.

Neural circuit mechanisms for transforming learned olfactory valences into wind-oriented movement

How memories are used by the brain to guide future action is poorly understood. In olfactory associative learning in Drosophila, multiple compartments of the mushroom body act in parallel to assign a valence to a stimulus. Here, we show that appetitive memories stored in different compartments induce different levels of upwind locomotion. Using a photoactivation screen of a new collection of split-GAL4 drivers and EM connectomics, we identified a cluster of neurons postsynaptic to the mushroom body output neurons (MBONs) that can trigger robust upwind steering. These UpWind Neurons (UpWiNs) integrate inhibitory and excitatory synaptic inputs from MBONs of appetitive and aversive memory compartments, respectively. After formation of appetitive memory, UpWiNs acquire enhanced response to reward-predicting odors as the response of the inhibitory presynaptic MBON undergoes depression. Blocking UpWiNs impaired appetitive memory and reduced upwind locomotion during retrieval. Photoactivation of UpWiNs also increased the chance of returning to a location where activation was terminated, suggesting an additional role in olfactory navigation. Thus, our results provide insight into how learned abstract valences are gradually transformed into concrete memory-driven actions through divergent and convergent networks, a neuronal architecture that is commonly found in the vertebrate and invertebrate brains.

Learning and memory using Drosophila melanogaster: a focus on advances made in the fifth decade of research

In the last decade, researchers using Drosophila melanogaster have made extraordinary progress in uncovering the mysteries underlying learning and memory. This progress has been propelled by the amazing toolkit available that affords combined behavioral, molecular, electrophysiological, and systems neuroscience approaches. The arduous reconstruction of electron microscopic images resulted in a first-generation connectome of the adult and larval brain, revealing complex structural interconnections between memory-related neurons. This serves as substrate for future investigations on these connections and for building complete circuits from sensory cue detection to changes in motor behavior. Mushroom body output neurons (MBOn) were discovered, which individually forward information from discrete and non-overlapping compartments of the axons of mushroom body neurons (MBn). These neurons mirror the previously discovered tiling of mushroom body axons by inputs from dopamine neurons and have led to a model that ascribes the valence of the learning event, either appetitive or aversive, to the activity of different populations of dopamine neurons and the balance of MBOn activity in promoting avoidance or approach behavior. Studies of the calyx, which houses the MBn dendrites, have revealed a beautiful microglomeruluar organization and structural changes of synapses that occur with long-term memory (LTM) formation. Larval learning has advanced, positioning it to possibly lead in producing new conceptual insights due to its markedly simpler structure over the adult brain. Advances were made in how cAMP response element-binding protein interacts with protein kinases and other transcription factors to promote the formation of LTM. New insights were made on Orb2, a prion-like protein that forms oligomers to enhance synaptic protein synthesis required for LTM formation. Finally, Drosophila research has pioneered our understanding of the mechanisms that mediate permanent and transient active forgetting, an important function of the brain along with acquisition, consolidation, and retrieval. This was catalyzed partly by the identification of memory suppressor genes-genes whose normal function is to limit memory formation.

Input density tunes Kenyon cell sensory responses in the Drosophila mushroom body

The ability to discriminate sensory stimuli with overlapping features is thought to arise in brain structures called expansion layers, where neurons carrying information about sensory features make combinatorial connections onto a much larger set of cells. For 50 years, expansion coding has been a prime topic of theoretical neuroscience, which seeks to explain how quantitative parameters of the expansion circuit influence sensory sensitivity, discrimination, and generalization. Here, we investigate the developmental events that produce the quantitative parameters of the arthropod expansion layer, called the mushroom body. Using Drosophila melanogaster as a model, we employ genetic and chemical tools to engineer changes to circuit development. These allow us to produce living animals with hypothesis-driven variations on natural expansion layer wiring parameters. We then test the functional and behavioral consequences. By altering the number of expansion layer neurons (Kenyon cells) and their dendritic complexity, we find that input density, but not cell number, tunes neuronal odor selectivity. Simple odor discrimination behavior is maintained when the Kenyon cell number is reduced and augmented by Kenyon cell number expansion. Animals with increased input density to each Kenyon cell show increased overlap in Kenyon cell odor responses and become worse at odor discrimination tasks.

The Stage-Based Model of Addiction-Using Drosophila to Investigate Alcohol and Psychostimulant Responses

Addiction is a progressive and complex disease that encompasses a wide range of disorders and symptoms, including substance use disorder (SUD), for which there are few therapeutic treatments. SUD is the uncontrolled and chronic use of substances despite the negative consequences resulting from this use. The progressive nature of addiction is organized into a testable framework, the neurobiological stage-based model, that includes three behavioral stages: (1) binge/intoxication, (2) withdrawal/negative affect, and (3) preoccupation/anticipation. Human studies offer limited opportunities for mechanistic insights into these; therefore, model organisms, like Drosophila melanogaster, are necessary for understanding SUD. Drosophila is a powerful model organism that displays a variety of SUD-like behaviors consistent with human and mammalian substance use, making flies a great candidate to study mechanisms of behavior. Additionally, there are an abundance of genetic tools like the GAL4/UAS and CRISPR/Cas9 systems that can be used to gain insight into the molecular mechanisms underlying the endophenotypes of the three-stage model. This review uses the three-stage framework and discusses how easily testable endophenotypes have been examined with experiments using Drosophila, and it outlines their potential for investigating other endophenotypes.

When neurons split the load

Various aspects of olfactory memory are represented as modulated responses across different classes of neurons in C. elegans.

Modulation of aversive value coding in the vertebrate and invertebrate brain

Avoiding potentially dangerous situations is key for the survival of any organism. Throughout life, animals learn to avoid environments, stimuli or actions that can lead to bodily harm. While the neural bases for appetitive learning, evaluation and value-based decision-making have received much attention, recent studies have revealed more complex computations for aversive signals during learning and decision-making than previously thought. Furthermore, previous experience, internal state and systems level appetitive-aversive interactions seem crucial for learning specific aversive value signals and making appropriate choices. The emergence of novel methodologies (computation analysis coupled with large-scale neuronal recordings, neuronal manipulations at unprecedented resolution offered by genetics, viral strategies and connectomics) has helped to provide novel circuit-based models for aversive (and appetitive) valuation. In this review, we focus on recent vertebrate and invertebrate studies yielding strong evidence that aversive value information can be computed by a multitude of interacting brain regions, and that past experience can modulate future aversive learning and therefore influence value-based decisions.

The cellular architecture of memory modules in Drosophila supports stochastic input integration

The ability to associate neutral stimuli with valence information and to store these associations as memories forms the basis for decision making. To determine the underlying computational principles, we build a realistic computational model of a central decision module within the Drosophila mushroom body (MB), the fly's center for learning and memory. Our model combines the electron microscopy-based architecture of one MB output neuron (MBON-α3), the synaptic connectivity of its 948 presynaptic Kenyon cells (KCs), and its membrane properties obtained from patch-clamp recordings. We show that this neuron is electrotonically compact and that synaptic input corresponding to simulated odor input robustly drives its spiking behavior. Therefore, sparse innervation by KCs can efficiently control and modulate MBON activity in response to learning with minimal requirements on the specificity of synaptic localization. This architecture allows efficient storage of large numbers of memories using the flexible stochastic connectivity of the circuit.

Innate and learned odor-guided behaviors utilize distinct molecular signaling pathways in a shared dopaminergic circuit

Odor-based learning and innate odor-driven behavior have been hypothesized to require separate neuronal circuitry. Contrary to this notion, innate behavior and olfactory learning were recently shown to share circuitry that includes the Drosophila mushroom body (MB). But how a single circuit drives two discrete behaviors remains unknown. Here, we define an MB circuit responsible for both olfactory learning and innate odor avoidance and the distinct dDA1 dopamine receptor-dependent signaling pathways that mediate these behaviors. Associative learning and learning-induced MB plasticity require rutabaga-encoded adenylyl cyclase activity in the MB. In contrast, innate odor preferences driven by naive MB neurotransmission are rutabaga independent, requiring the adenylyl cyclase ACXD. Both learning and innate odor preferences converge on PKA and the downstream MBON-γ2α'1. Importantly, the utilization of this shared circuitry for innate behavior only becomes apparent with hunger, indicating that hardwired innate behavior becomes more flexible during states of stress.

Restructuring of olfactory representations in the fly brain around odor relationships in natural sources

A core challenge of olfactory neuroscience is to understand how neural representations of odor are generated and progressively transformed across different layers of the olfactory circuit into formats that support perception and behavior. The encoding of odor by odorant receptors in the input layer of the olfactory system reflects, at least in part, the chemical relationships between odor compounds. Neural representations of odor in higher order associative olfactory areas, generated by random feedforward networks, are expected to largely preserve these input odor relationships1-3. We evaluated these ideas by examining how odors are represented at different stages of processing in the olfactory circuit of the vinegar fly D. melanogaster. We found that representations of odor in the mushroom body (MB), a third-order associative olfactory area in the fly brain, are indeed structured and invariant across flies. However, the structure of MB representational space diverged significantly from what is expected in a randomly connected network. In addition, odor relationships encoded in the MB were better correlated with a metric of the similarity of their distribution across natural sources compared to their similarity with respect to chemical features, and the converse was true for odor relationships encoded in primary olfactory receptor neurons (ORNs). Comparison of odor coding at primary, secondary, and tertiary layers of the circuit revealed that odors were significantly regrouped with respect to their representational similarity across successive stages of olfactory processing, with the largest changes occurring in the MB. The non-linear reorganization of odor relationships in the MB indicates that unappreciated structure exists in the fly olfactory circuit, and this structure may facilitate the generalization of odors with respect to their co-occurence in natural sources.

A linear discriminant analysis model of imbalanced associative learning in the mushroom body compartment

To adapt to their environments, animals learn associations between sensory stimuli and unconditioned stimuli. In invertebrates, olfactory associative learning primarily occurs in the mushroom body, which is segregated into separate compartments. Within each compartment, Kenyon cells (KCs) encoding sparse odor representations project onto mushroom body output neurons (MBONs) whose outputs guide behavior. Associated with each compartment is a dopamine neuron (DAN) that modulates plasticity of the KC-MBON synapses within the compartment. Interestingly, DAN-induced plasticity of the KC-MBON synapse is imbalanced in the sense that it only weakens the synapse and is temporally sparse. We propose a normative mechanistic model of the MBON as a linear discriminant analysis (LDA) classifier that predicts the presence of an unconditioned stimulus (class identity) given a KC odor representation (feature vector). Starting from a principled LDA objective function and under the assumption of temporally sparse DAN activity, we derive an online algorithm which maps onto the mushroom body compartment. Our model accounts for the imbalanced learning at the KC-MBON synapse and makes testable predictions that provide clear contrasts with existing models.

Hacking brain development to test models of sensory coding

Animals can discriminate myriad sensory stimuli but can also generalize from learned experience. You can probably distinguish the favorite teas of your colleagues while still recognizing that all tea pales in comparison to coffee. Tradeoffs between detection, discrimination, and generalization are inherent at every layer of sensory processing. During development, specific quantitative parameters are wired into perceptual circuits and set the playing field on which plasticity mechanisms play out. A primary goal of systems neuroscience is to understand how material properties of a circuit define the logical operations-computations--that it makes, and what good these computations are for survival. A cardinal method in biology-and the mechanism of evolution--is to change a unit or variable within a system and ask how this affects organismal function. Here, we make use of our knowledge of developmental wiring mechanisms to modify hard-wired circuit parameters in the Drosophila melanogaster mushroom body and assess the functional and behavioral consequences. By altering the number of expansion layer neurons (Kenyon cells) and their dendritic complexity, we find that input number, but not cell number, tunes odor selectivity. Simple odor discrimination performance is maintained when Kenyon cell number is reduced and augmented by Kenyon cell expansion.

Hierarchical architecture of dopaminergic circuits enables second-order conditioning in Drosophila

Dopaminergic neurons with distinct projection patterns and physiological properties compose memory subsystems in a brain. However, it is poorly understood whether or how they interact during complex learning. Here, we identify a feedforward circuit formed between dopamine subsystems and show that it is essential for second-order conditioning, an ethologically important form of higher-order associative learning. The Drosophila mushroom body comprises a series of dopaminergic compartments, each of which exhibits distinct memory dynamics. We find that a slow and stable memory compartment can serve as an effective 'teacher' by instructing other faster and transient memory compartments via a single key interneuron, which we identify by connectome analysis and neurotransmitter prediction. This excitatory interneuron acquires enhanced response to reward-predicting odor after first-order conditioning and, upon activation, evokes dopamine release in the 'student' compartments. These hierarchical connections between dopamine subsystems explain distinct properties of first- and second-order memory long known by behavioral psychologists.

The making of the Drosophila mushroom body

The mushroom body (MB) is a computational center in the Drosophila brain. The intricate neural circuits of the mushroom body enable it to store associative memories and process sensory and internal state information. The mushroom body is composed of diverse types of neurons that are precisely assembled during development. Tremendous efforts have been made to unravel the molecular and cellular mechanisms that build the mushroom body. However, we are still at the beginning of this challenging quest, with many key aspects of mushroom body assembly remaining unexplored. In this review, I provide an in-depth overview of our current understanding of mushroom body development and pertinent knowledge gaps.

The role of learning-walk related multisensory experience in rewiring visual circuits in the desert ant brain

Efficient spatial orientation in the natural environment is crucial for the survival of most animal species. Cataglyphis desert ants possess excellent navigational skills. After far-ranging foraging excursions, the ants return to their inconspicuous nest entrance using celestial and panoramic cues. This review focuses on the question about how naïve ants acquire the necessary spatial information and adjust their visual compass systems. Naïve ants perform structured learning walks during their transition from the dark nest interior to foraging under bright sunlight. During initial learning walks, the ants perform rotational movements with nest-directed views using the earth’s magnetic field as an earthbound compass reference. Experimental manipulations demonstrate that specific sky compass cues trigger structural neuronal plasticity in visual circuits to integration centers in the central complex and mushroom bodies. During learning walks, rotation of the sky-polarization pattern is required for an increase in volume and synaptic complexes in both integration centers. In contrast, passive light exposure triggers light-spectrum (especially UV light) dependent changes in synaptic complexes upstream of the central complex. We discuss a multisensory circuit model in the ant brain for pathways mediating structural neuroplasticity at different levels following passive light exposure and multisensory experience during the performance of learning walks.

Transient active zone remodeling in the Drosophila mushroom body supports memory

Elucidating how the distinct components of synaptic plasticity dynamically orchestrate the distinct stages of memory acquisition and maintenance within neuronal networks remains a major challenge. Specifically, plasticity processes tuning the functional and also structural state of presynaptic active zone (AZ) release sites are widely observed in vertebrates and invertebrates, but their behavioral relevance remains mostly unclear. We here provide evidence that a transient upregulation of presynaptic AZ release site proteins supports aversive olfactory mid-term memory in the Drosophila mushroom body (MB). Upon paired aversive olfactory conditioning, AZ protein levels (ELKS-family BRP/(m)unc13-family release factor Unc13A) increased for a few hours with MB-lobe-specific dynamics. Kenyon cell (KC, intrinsic MB neurons)-specific knockdown (KD) of BRP did not affect aversive olfactory short-term memory (STM) but strongly suppressed aversive mid-term memory (MTM). Different proteins crucial for the transport of AZ biosynthetic precursors (transport adaptor Aplip1/Jip-1; kinesin motor IMAC/Unc104; small GTPase Arl8) were also specifically required for the formation of aversive olfactory MTM. Consistent with the merely transitory increase of AZ proteins, BRP KD did not interfere with the formation of aversive olfactory long-term memory (LTM; i.e., 1 day). Our data suggest that the remodeling of presynaptic AZ refines the MB circuitry after paired aversive conditioning, over a time window of a few hours, to display aversive olfactory memories.

Lipophorin receptors regulate mushroom body development and complex behaviors in Drosophila

BACKGROUND

Drosophila melanogaster lipophorin receptors (LpRs), LpR1 and LpR2, are members of the LDLR family known to mediate lipid uptake in a range of organisms from Drosophila to humans. The vertebrate orthologs of LpRs, ApoER2 and VLDL-R, function as receptors of a glycoprotein involved in development of the central nervous system, Reelin, which is not present in flies. ApoER2 and VLDL-R are associated with the development and function of the hippocampus and cerebral cortex, important association areas in the mammalian brain, as well as with neurodevelopmental and neurodegenerative disorders linked to those regions. It is currently unknown whether LpRs play similar roles in the Drosophila brain.

RESULTS

We report that LpR-deficient flies exhibit impaired olfactory memory and sleep patterns, which seem to reflect anatomical defects found in a critical brain association area, the mushroom bodies (MB). Moreover, cultured MB neurons respond to mammalian Reelin by increasing the complexity of their neurite arborization. This effect depends on LpRs and Dab, the Drosophila ortholog of the Reelin signaling adaptor protein Dab1. In vitro, two of the long isoforms of LpRs allow the internalization of Reelin, suggesting that Drosophila LpRs interact with human Reelin to induce downstream cellular events.

CONCLUSIONS

These findings demonstrate that LpRs contribute to MB development and function, supporting the existence of a LpR-dependent signaling in Drosophila, and advance our understanding of the molecular factors functioning in neural systems to generate complex behaviors in this model. Our results further emphasize the importance of Drosophila as a model to investigate the alterations in specific genes contributing to neural disorders.

Drug effect and addiction research with insects - From Drosophila to collective reward in honeybees

Animals and humans share similar reactions to the effects of addictive substances, including those of their brain networks to drugs. Our review focuses on simple invertebrate models, particularly the honeybee (Apis mellifera), and on the effects of drugs on bee behaviour and brain functions. The drug effects in bees are very similar to those described in humans. Furthermore, the honeybee community is a superorganism in which many collective functions outperform the simple sum of individual functions. The distribution of reward functions in this superorganism is unique - although sublimated at the individual level, community reward functions are of higher quality. This phenomenon of collective reward may be extrapolated to other animal species living in close and strictly organised societies, i.e. humans. The relationship between sociality and reward, based on use of similar parts of the neural network (social decision-making network in mammals, mushroom body in bees), suggests a functional continuum of reward and sociality in animals.

3D-atlas of the brain of the cockroach Rhyparobia maderae

The Madeira cockroach Rhyparobia maderae is a nocturnal insect and a prominent model organism for the study of circadian rhythms. Its master circadian clock, controlling circadian locomotor activity and sleep-wake cycles, is located in the accessory medulla of the optic lobe. For a better understanding of brain regions controlled by the circadian clock and brain organization of this insect in general, we created a three-dimensional (3D) reconstruction of all neuropils of the cerebral ganglia based on anti-synapsin and anti-γ-aminobutyric acid immunolabeling of whole mount brains. Forty-nine major neuropils were identified and three-dimensionally reconstructed. Single-cell dye fills complement the data and provide evidence for distinct subdivisions of certain brain areas. Most neuropils defined in the fruit fly Drosophila melanogaster could be distinguished in the cockroach as well. However, some neuropils identified in the fruit fly do not exist as distinct entities in the cockroach while others are lacking in the fruit fly. In addition to neuropils, major fiber systems, tracts, and commissures were reconstructed and served as important landmarks separating brain areas. Being a nocturnal insect, R. maderae is an important new species to the growing collection of 3D insect brain atlases and only the second hemimetabolous insect, for which a detailed 3D brain atlas is available. This atlas will be highly valuable for an evolutionary comparison of insect brain organization and will greatly facilitate addressing brain areas that are supervised by the circadian clock.

Structured sampling of olfactory input by the fly mushroom body

Associative memory formation and recall in the fruit fly Drosophila melanogaster is subserved by the mushroom body (MB). Upon arrival in the MB, sensory information undergoes a profound transformation from broadly tuned and stereotyped odorant responses in the olfactory projection neuron (PN) layer to narrowly tuned and nonstereotyped responses in the Kenyon cells (KCs). Theory and experiment suggest that this transformation is implemented by random connectivity between KCs and PNs. However, this hypothesis has been challenging to test, given the difficulty of mapping synaptic connections between large numbers of brain-spanning neurons. Here, we used a recent whole-brain electron microscopy volume of the adult fruit fly to map PN-to-KC connectivity at synaptic resolution. The PN-KC connectome revealed unexpected structure, with preponderantly food-responsive PN types converging at above-chance levels on downstream KCs. Axons of the overconvergent PN types tended to arborize near one another in the MB main calyx, making local KC dendrites more likely to receive input from those types. Overconvergent PN types preferentially co-arborize and connect with dendrites of αβ and α'β' KC subtypes. Computational simulation of the observed network showed degraded discrimination performance compared with a random network, except when all signal flowed through the overconvergent, primarily food-responsive PN types. Additional theory and experiment will be needed to fully characterize the impact of the observed non-random network structure on associative memory formation and recall.

Not so spontaneous: Multi-dimensional representations of behaviors and context in sensory areas

Sensory areas are spontaneously active in the absence of sensory stimuli. This spontaneous activity has long been studied; however, its functional role remains largely unknown. Recent advances in technology, allowing large-scale neural recordings in the awake and behaving animal, have transformed our understanding of spontaneous activity. Studies using these recordings have discovered high-dimensional spontaneous activity patterns, correlation between spontaneous activity and behavior, and dissimilarity between spontaneous and sensory-driven activity patterns. These findings are supported by evidence from developing animals, where a transition toward these characteristics is observed as the circuit matures, as well as by evidence from mature animals across species. These newly revealed characteristics call for the formulation of a new role for spontaneous activity in neural sensory computation.

Pairing-Dependent Plasticity in a Dissected Fly Brain Is Input-Specific and Requires Synaptic CaMKII Enrichment and Nighttime Sleep

In Drosophila, in vivo functional imaging studies revealed that associative memory formation is coupled to a cascade of neural plasticity events in distinct compartments of the mushroom body (MB). In-depth investigation of the circuit dynamics, however, will require an ex vivo model that faithfully mirrors these events to allow direct manipulations of circuit elements that are inaccessible in the intact fly. The current ex vivo models have been able to reproduce the fundamental plasticity of aversive short-term memory, a potentiation of the MB intrinsic neuron (Kenyon cells [KCs]) responses after artificial learning ex vivo However, this potentiation showed different localization and encoding properties from those reported in vivo and failed to generate the previously reported suppression plasticity in the MB output neurons (MBONs). Here, we develop an ex vivo model using the female Drosophila brain that recapitulates behaviorally evoked plasticity in the KCs and MBONs. We demonstrate that this plasticity accurately localizes to the MB α'3 compartment and is encoded by a coincidence between KC activation and dopaminergic input. The formed plasticity is input-specific, requiring pairing of the conditioned stimulus and unconditioned stimulus pathways; hence, we name it pairing-dependent plasticity. Pairing-dependent plasticity formation requires an intact CaMKII gene and is blocked by previous-night sleep deprivation but is rescued by rebound sleep. In conclusion, we show that our ex vivo preparation recapitulates behavioral and imaging results from intact animals and can provide new insights into mechanisms of memory formation at the level of molecules, circuits, and brain state.SIGNIFICANCE STATEMENT The mammalian ex vivo LTP model enabled in-depth investigation of the hippocampal memory circuit. We develop a parallel model to study the Drosophila mushroom body (MB) memory circuit. Pairing activation of the conditioned stimulus and unconditioned stimulus pathways in dissected brains induces a potentiation pairing-dependent plasticity (PDP) in the axons of α'β' Kenyon cells and a suppression PDP in the dendrites of their postsynaptic MB output neurons, localized in the MB α'3 compartment. This PDP is input-specific and requires the 3' untranslated region of CaMKII Interestingly, ex vivo PDP carries information about the animal's experience before dissection; brains from sleep-deprived animals fail to form PDP, whereas those from animals who recovered 2 h of their lost sleep form PDP.

Semaphorin 1a-mediated dendritic wiring of the Drosophila mushroom body extrinsic neurons

The adult Drosophila mushroom body (MB) is one of the most extensively studied neural circuits. However, how its circuit organization is established during development is unclear. In this study, we provide an initial characterization of the assembly process of the extrinsic neurons (dopaminergic neurons and MB output neurons) that target the vertical MB lobes. We probe the cellular mechanisms guiding the neurite targeting of these extrinsic neurons and demonstrate that Semaphorin 1a is required in several MB output neurons for their dendritic innervations to three specific MB lobe zones. Our study reveals several intriguing molecular and cellular principles governing assembly of the MB circuit.

The Drosophila mushroom body (MB) is composed of parallel axonal fibers from intrinsic Kenyon cells (KCs). The parallel fibers are bundled into five MB lobes innervated by extrinsic neurons, including dopaminergic neurons (DANs) and MB output neurons (MBONs) that project axons or dendrites to the MB lobes, respectively. Each DAN and MBON innervates specific regions in the lobes and collectively subdivides them into 15 zones. How such modular circuit architecture is established remains unknown. Here, we followed the development of the DANs and MBONs targeting the vertical lobes of the adult MB. We found that these extrinsic neurons innervate the lobes sequentially and their neurite arborizations in the MB lobe zones are independent of each other. Ablation of DAN axons or MBON dendrites in a zone had a minimal effect on other extrinsic neurites in the same or neighboring zones, suggesting that these neurons do not use tiling mechanisms to establish zonal borders. In contrast, KC axons are necessary for the development of extrinsic neurites. Dendrites of some vertical lobe-innervating MBONs were redirected to specific zones in the horizontal lobes when their normal target lobes were missing, indicating a hierarchical organization of guidance signals for the MBON dendrites. We show that Semaphorin 1a is required in MBONs to innervate three specific MB zones, and overexpression of semaphorin 1a is sufficient to redirect DAN dendrites to these zones. Our study provides an initial characterization of the cellular and molecular mechanisms underlying the assembly process of MB extrinsic neurons.

CMTr cap-adjacent 2'-O-ribose mRNA methyltransferases are required for reward learning and mRNA localization to synapses

Cap-adjacent nucleotides of animal, protist and viral mRNAs can be O-methylated at the 2‘ position of the ribose (cOMe). The functions of cOMe in animals, however, remain largely unknown. Here we show that the two cap methyltransferases (CMTr1 and CMTr2) of Drosophila can methylate the ribose of the first nucleotide in mRNA. Double-mutant flies lack cOMe but are viable. Consistent with prominent neuronal expression, they have a reward learning defect that can be rescued by conditional expression in mushroom body neurons before training. Among CMTr targets are cell adhesion and signaling molecules. Many are relevant for learning, and are also targets of Fragile X Mental Retardation Protein (FMRP). Like FMRP, cOMe is required for localization of untranslated mRNAs to synapses and enhances binding of the cap binding complex in the nucleus. Hence, our study reveals a mechanism to co-transcriptionally prime mRNAs by cOMe for localized protein synthesis at synapses.

The two cap methyltransferases (CMTrs) redundantly methylate riboses of first cap adjacent nucleotides in messenger RNAs in Drosophila. Here, CMTrs are required for reward learning and localization of untranslated messenger RNAs to synapses.

Differential mechanisms underlie trace and delay conditioning in Drosophila

Two forms of associative learning-delay conditioning and trace conditioning-have been widely investigated in humans and higher-order mammals¹. In delay conditioning, an unconditioned stimulus (for example, an electric shock) is introduced in the final moments of a conditioned stimulus (for example, a tone), with both ending at the same time. In trace conditioning, a 'trace' interval separates the conditioned stimulus and the unconditioned stimulus. Trace conditioning therefore relies on maintaining a neural representation of the conditioned stimulus after its termination (hence making distraction possible²), to learn the conditioned stimulus-unconditioned stimulus contingency³; this makes it more cognitively demanding than delay conditioning⁴. Here, by combining virtual-reality behaviour with neurogenetic manipulations and in vivo two-photon brain imaging, we show that visual trace conditioning and delay conditioning in Drosophila mobilize R2 and R4m ring neurons in the ellipsoid body. In trace conditioning, calcium transients during the trace interval show increased oscillations and slower declines over repeated training, and both of these effects are sensitive to distractions. Dopaminergic activity accompanies signal persistence in ring neurons, and this is decreased by distractions solely during trace conditioning. Finally, dopamine D1-like and D2-like receptor signalling in ring neurons have different roles in delay and trace conditioning; dopamine D1-like receptor 1 mediates both forms of conditioning, whereas the dopamine D2-like receptor is involved exclusively in sustaining ring neuron activity during the trace interval of trace conditioning. These observations are similar to those previously reported in mammals during arousal⁵, prefrontal activation⁶ and high-level cognitive learning^7,8.

The velvet worm brain unveils homologies and evolutionary novelties across panarthropods

Background

The evolution of the brain and its major neuropils in Panarthropoda (comprising Arthropoda, Tardigrada and Onychophora) remains enigmatic. As one of the closest relatives of arthropods, onychophorans are regarded as indispensable for a broad understanding of the evolution of panarthropod organ systems, including the brain, whose anatomical and functional organisation is often used to gain insights into evolutionary relations. However, while numerous recent studies have clarified the organisation of many arthropod nervous systems, a detailed investigation of the onychophoran brain with current state-of-the-art approaches is lacking, and further inconsistencies in nomenclature and interpretation hamper its understanding. To clarify the origins and homology of cerebral structures across panarthropods, we analysed the brain architecture in the onychophoran Euperipatoides rowelli by combining X-ray micro-computed tomography, histology, immunohistochemistry, confocal microscopy, and three-dimensional reconstruction.

Results

Here, we use this detailed information to generate a consistent glossary for neuroanatomical studies of Onychophora. In addition, we report novel cerebral structures, provide novel details on previously known brain areas, and characterise further structures and neuropils in order to improve the reproducibility of neuroanatomical observations. Our findings support homology of mushroom bodies and central bodies in onychophorans and arthropods. Their antennal nerve cords and olfactory lobes most likely evolved independently. In contrast to previous reports, we found no evidence for second-order visual neuropils, or a frontal ganglion in the velvet worm brain.

Conclusion

We imaged the velvet worm nervous system at an unprecedented level of detail and compiled a comprehensive glossary of known and previously uncharacterised neuroanatomical structures to provide an in-depth characterisation of the onychophoran brain architecture. We expect that our data will improve the reproducibility and comparability of future neuroanatomical studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-01196-w.

Multiphoton imaging of neural structure and activity in Drosophila through the intact cuticle

We developed a multiphoton imaging method to capture neural structure and activity in behaving flies through the intact cuticle. Our measurements showed that the fly head cuticle has surprisingly high transmission at wavelengths >900nm, and the difficulty of through-cuticle imaging is due to the air sacs and/or fat tissue underneath the head cuticle. By compressing or removing the air sacs, we performed multiphoton imaging of the fly brain through the intact cuticle. Our anatomical and functional imaging results show that 2- and 3-photon imaging are comparable in superficial regions such as the mushroom body, but 3-photon imaging is superior in deeper regions such as the central complex and beyond. We further demonstrated 2-photon through-cuticle functional imaging of odor-evoked calcium responses from the mushroom body γ-lobes in behaving flies short term and long term. The through-cuticle imaging method developed here extends the time limits of in vivo imaging in flies and opens new ways to capture neural structure and activity from the fly brain.

Neural Circuits Underlying Behavioral Flexibility: Insights From Drosophila

Behavioral flexibility is critical to survival. Animals must adapt their behavioral responses based on changes in the environmental context, internal state, or experience. Studies in Drosophila melanogaster have provided insight into the neural circuit mechanisms underlying behavioral flexibility. Here we discuss how Drosophila behavior is modulated by internal and behavioral state, environmental context, and learning. We describe general principles of neural circuit organization and modulation that underlie behavioral flexibility, principles that are likely to extend to other species.

Postsynaptic plasticity of cholinergic synapses underlies the induction and expression of appetitive and familiarity memories in Drosophila

In vertebrates, several forms of memory-relevant synaptic plasticity involve postsynaptic rearrangements of glutamate receptors. In contrast, previous work indicates that Drosophila and other invertebrates store memories using presynaptic plasticity of cholinergic synapses. Here, we provide evidence for postsynaptic plasticity at cholinergic output synapses from the Drosophila mushroom bodies (MBs). We find that the nicotinic acetylcholine receptor (nAChR) subunit α5 is required within specific MB output neurons for appetitive memory induction but is dispensable for aversive memories. In addition, nAChR α2 subunits mediate memory expression and likely function downstream of α5 and the postsynaptic scaffold protein discs large (Dlg). We show that postsynaptic plasticity traces can be induced independently of the presynapse, and that in vivo dynamics of α2 nAChR subunits are changed both in the context of associative and non-associative (familiarity) memory formation, underlying different plasticity rules. Therefore, regardless of neurotransmitter identity, key principles of postsynaptic plasticity support memory storage across phyla.

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.

Circuits for integrating learned and innate valences in the insect brain

Animal behavior is shaped both by evolution and by individual experience. Parallel brain pathways encode innate and learned valences of cues, but the way in which they are integrated during action-selection is not well understood. We used electron microscopy to comprehensively map with synaptic resolution all neurons downstream of all mushroom body (MB) output neurons (encoding learned valences) and characterized their patterns of interaction with lateral horn (LH) neurons (encoding innate valences) in Drosophila larva. The connectome revealed multiple convergence neuron types that receive convergent MB and LH inputs. A subset of these receives excitatory input from positive-valence MB and LH pathways and inhibitory input from negative-valence MB pathways. We confirmed functional connectivity from LH and MB pathways and behavioral roles of two of these neurons. These neurons encode integrated odor value and bidirectionally regulate turning. Based on this, we speculate that learning could potentially skew the balance of excitation and inhibition onto these neurons and thereby modulate turning. Together, our study provides insights into the circuits that integrate learned and innate valences to modify behavior.

Individual bitter-sensing neurons in Drosophila exhibit both ON and OFF responses that influence synaptic plasticity

The brain generates internal representations that translate sensory stimuli into appropriate behavior. In the taste system, different tastes activate distinct populations of sensory neurons. We investigated the temporal properties of taste responses in Drosophila and discovered that different types of taste sensory neurons show striking differences in their response dynamics. Strong responses to stimulus onset (ON responses) and offset (OFF responses) were observed in bitter-sensing neurons in the labellum, whereas bitter neurons in the leg and other classes of labellar taste neurons showed only an ON response. Individual labellar bitter neurons generate both ON and OFF responses through a cell-intrinsic mechanism that requires canonical bitter receptors. A single receptor complex likely generates both ON and OFF responses to a given bitter ligand. These ON and OFF responses in the periphery are propagated to dopaminergic neurons that mediate aversive learning, and the presence of the OFF response impacts synaptic plasticity when bitter is used as a reinforcement cue. These studies reveal previously unknown features of taste responses that impact neural circuit function and may be important for behavior. Moreover, these studies show that OFF responses can dramatically influence timing-based synaptic plasticity, which is thought to underlie associative learning.

Switch-like and persistent memory formation in individual Drosophila larvae

Associative learning allows animals to use past experience to predict future events. The circuits underlying memory formation support immediate and sustained changes in function, often in response to a single example. Larval Drosophila is a genetic model for memory formation that can be accessed at molecular, synaptic, cellular, and circuit levels, often simultaneously, but existing behavioral assays for larval learning and memory do not address individual animals, and it has been difficult to form long-lasting memories, especially those requiring synaptic reorganization. We demonstrate a new assay for learning and memory capable of tracking the changing preferences of individual larvae. We use this assay to explore how activation of a pair of reward neurons changes the response to the innately aversive gas carbon dioxide (CO2). We confirm that when coupled to CO2 presentation in appropriate temporal sequence, optogenetic reward reduces avoidance of CO2. We find that learning is switch-like: all-or-none and quantized in two states. Memories can be extinguished by repeated unrewarded exposure to CO2 but are stabilized against extinction by repeated training or overnight consolidation. Finally, we demonstrate long-lasting protein synthesis dependent and independent memory formation.

Prior experience conditionally inhibits the expression of new learning in Drosophila

Prior experience of a stimulus can inhibit subsequent acquisition or expression of a learned association of that stimulus. However, the neuronal manifestations of this learning effect, named latent inhibition (LI), are poorly understood. Here, we show that prior odor exposure can produce context-dependent LI of later appetitive olfactory memory performance in Drosophila. Odor pre-exposure forms a short-lived aversive memory whose lone expression lacks context-dependence. Acquisition of odor pre-exposure memory requires aversively reinforcing dopaminergic neurons that innervate two mushroom body compartments—one group of which exhibits increasing activity with successive odor experience. Odor-specific responses of the corresponding mushroom body output neurons are suppressed, and their output is necessary for expression of both pre-exposure memory and LI of appetitive memory. Therefore, odor pre-exposure attaches negative valence to the odor itself, and LI of appetitive memory results from a temporary and context-dependent retrieval deficit imposed by competition with the parallel short-lived aversive memory.

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Odor pre-exposure alters the expression of a learned association of that odor

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Pre-exposure memory only affects subsequent retrieval if context is consistent

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Pre-exposure memory can complement or compete with a learned association

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Odor pre-exposure forms a labile mushroom body-dependent aversive memory