Mushroom body output neurons encode valence and guide memory-based action selection in Drosophila

PKA restricts ERK signaling in learning and memory Kenyon cell neurons

Protein Kinase A (PKA) and Extracellular Signal-Regulated Kinase (ERK) have core roles in learning and memory. Here, we investigate kinase-kinase signaling interactions in the Drosophila brain Kenyon cell learning/memory circuit using separation of phases-based activity reporter of kinase (SPARK) biosensors to image circuit-localized functions in vivo. We find that constitutively active Rapidly Accelerated Fibrosarcoma (RAFgof) enhances ERK signaling only in Kenyon cell domains with low baseline PKA signaling, and that transgenic inhibition of PKA function elevates ERK signaling. Conversely, loss of ERK has no impact on PKA signaling, whereas RAFgof expands PKA signaling. Importantly, transgenic PKA inhibition together with RAFgof synergistically elevates ERK signaling. These findings indicate a negative PKA-ERK pathway interaction within learning/memory Kenyon cells. We find that potentiating circuit activity using an exogenous NaChBac ion channel elevates PKA signaling in circuit domains with low baseline PKA function, and uniformly strongly increases ERK signaling. Similarly, thermogenetic stimulation of circuit activity with a temperature-sensitive TRPA1 channel increases PKA signaling in circuit domains of low baseline PKA, and elevates ERK signaling. Importantly, potentiating circuit activity (NaChBac) while also inhibiting PKA function synergistically elevates ERK signaling. Likewise, conditional induction of circuit activity (TRPA1) together with PKA inhibition increases activity-dependent ERK signaling. Finally, a mechanically-induced seizure model (bang-sensitive sesB mutant) elevates PKA signaling, while simultaneous transgenic PKA inhibition in this model acts to synergistically increase ERK signaling. Taken together, we conclude PKA limits ERK signaling in Kenyon cells within the learning and memory circuit, with PKA function acting to restrict activity-dependent ERK signaling.

Rapid memory shift between different synaptic ensembles promotes forgetting in Drosophila

Forgetting is increasingly recognized as an active adaptive process, yet its mechanism remains elusive at the cellular and synaptic levels. Here, we show that the natural decay of hours-scale memory in Drosophila is promoted through shifting memory traces between distinct synaptic ensembles. Aversive conditioning produces an initial memory trace of presynaptic depression primarily confined to the γ1 compartment, one of five axonal compartments of γ Kenyon cells, that drives avoidance behavior. The memory trace later is shifted to the γ4 compartment, but is encoded as presynaptic potentiation. This shift is initiated by Rac1/Dia activation, which rapidly adds active zones (AZs), followed by Ephrin-dependent AZ elimination in the γ4 compartment, promoting decay. Preventing this shift preserves γ1 memory trace for over 1 day without forgetting. Thus, forgetting is achieved by shifting memory trace from early, more persistent presynaptic depression to new synaptic ensemble-encoded presynaptic potentiation prone to accelerated memory decay.

Hybrid neural networks in the mushroom body drive olfactory preference in Drosophila

In Drosophila melanogaster, olfactory encoding in the mushroom body (MB) involves thousands of Kenyon cells (KCs) processing inputs from hundreds of projection neurons (PNs). Recent data challenge the notion of random PN-to-KC connectivity, revealing preferential connections between food-related PNs and specific KCs. Our study further uncovers a broader picture-an L-shaped hybrid network, supported by spatial patterning: Food-related PNs diverge across KC classes, whereas pheromone-sensitive PNs converge on γ KCs. α/β KCs specialize in food odors, whereas γ KCs integrate diverse inputs. Such spatial arrangement extends further to the antennal lobe (AL) and lateral horn (LH), shaping a systematic olfactory landscape. Moreover, our functional validations align with computational predictions of KC odor encoding based on the hybrid connectivity, correlating PN-KC activity with behavioral preferences. In addition, our simulations showcase the network's augmented sensitivity and precise discrimination abilities, underscoring the computational benefits of this hybrid architecture in olfactory processing.

Rest, Repair, Repeat: The Complex Relationship of Autophagy and Sleep

Autophagy and sleep are two evolutionary conserved mechanisms across the animal kingdom. Autophagy is a pathway for the degradation of cytoplasmic material in the lysosome, playing important roles in the homeostasis and health of the organism. On the other hand, sleep is a homeostatically regulated state with numerous presumed essential roles, including the restoration of tissue and physiological functions, such as brain waste clearance via the activation of the glymphatic systems. Given that sleep and autophagy are crucial processes tightly linked to homeostasis and maintenance of good health, understanding how they interact is of great interest, especially as sleep quality decreases in our modern 24-hour societies. Autophagy represents a promising target for therapeutic interventions in this context. Here, we review the contrasted and complementary roles of autophagy and sleep in maintaining homeostasis. Specifically, we focus on recent evidence suggesting that sleep impairment may increase autophagy, while autophagosome levels may modulate the amount of sleep. We discuss outstanding questions at the intersection of these two fields, highlighting methodological shortcomings in the current literature. Overcoming these limitations will be instrumental to design new experiments with the aim of answering one of the greatest mysteries of our time - why do we sleep?

Dynamics of two distinct memory interactions during water seeking in Drosophila

Forming and forgetting memories shape our self-awareness and help us face future challenges. Therefore, understanding how memories are formed and how different memories interact in the brain is important. Previous studies have shown that thirsty flies sense humidity through ionotropic receptors, which help them locate water sources. Here, we showed that thirsty flies can be trained to associate specific odors with humidity to form a humidity memory that lasts for 30 min after association. Humidity memory formation requires the Ir93a and Ir40a ionotropic receptors, which are essential for environmental humidity sensing. Water memory takes precedence, leading to the forgetting of humidity memory by activating a small subset of dopaminergic neurons called protocerebral anterior medial (PAM)-γ4, that project to the restricted region of the mushroom body (MB) γ lobes. Adult-stage-specific silencing of Dop2R dopaminergic receptors in MB γ neurons prolongs humidity memory for 3 h. Live-brain calcium imaging and dopamine sensor studies revealed significantly increased PAM-γ4 neural activity after odor/humidity association, suggesting its role in forgetting the humidity memory. Our results suggest that overlapping neural circuits are responsible for the acquisition of water memory and forgetting humidity memory in thirsty flies.

Functional dissection of a neuronal brain circuit mediating higher-order associative learning

A central feature characterizing the neural architecture of many species' brains is their capacity to form associative chains through learning. In elementary forms of associative learning, stimuli coinciding with reward or punishment become attractive or repulsive. Notably, stimuli previously learned as attractive or repulsive can themselves serve as reinforcers, establishing a cascading effect whereby they become associated with additional stimuli. When this iterative process is perpetuated, it results in higher-order associations. Here, we use odor conditioning in Drosophila and computational modeling to dissect the architecture of neuronal networks underlying higher-order associative learning. We show that the responsible circuit, situated in the mushroom bodies of the brain, is characterized by parallel processing of odor information and by recurrent excitatory and inhibitory feedback loops that empower odors to gain control over the dopaminergic valence-signaling system. Our findings establish a paradigmatic framework of a neuronal circuit diagram enabling the acquisition of associative chains.

Profiling translation in the nervous system

Regulation at the level of translation is critical in the nervous system, such as for the formation of cell-type-specific proteomes or plastic changes in neural circuits. Whilst current knowledge of the translatome is relatively limited compared to transcriptome, a growing array of tools to analyse translation is becoming available. In this review, we discuss techniques for profiling translation on a genome-wide scale with a special emphasis on cell-type-specific analyses in the nervous system. This includes polysome-profiling-seq, Translating Ribosome Affinity Purification (TRAP)-seq and ribosome profiling (Ribo-seq). We review recent advances to achieve spatial resolution of translatome analysis, such as genetic labelling of the targeted cells and cell sorting, and discuss the biological implications of translational regulation in the brain and potential future extensions.

Enhanced memory despite severe sleep loss in Drosophila insomniac mutants

Sleep is crucial for cognitive functions and life span across species. While sleep homeostasis and cognitive processes are linked through cellular and synaptic plasticity, the signaling pathways connecting them remain unclear. Here, we show that Drosophila insomniac (inc) short sleep mutants, which lack an adaptor protein for the autism-associated Cullin-3 ubiquitin ligase, exhibited enhanced Pavlovian aversive olfactory learning and memory, unlike other sleep mutants with normal or reduced memory. Through a genetic modifier screen, we found that a mild reduction of Protein Kinase A (PKA) signaling specifically rescued the sleep and longevity phenotypes of inc mutants. However, this reduction further increased their excessive memory and mushroom body overgrowth. Since inc mutants displayed higher PKA signaling, we propose that inc loss-of-function suppresses sleep via increased PKA activity, which also constrains the excessive memory of inc mutants. Our data identify a signaling cascade for balancing sleep and memory functions, and provide a plausible explanation for the sleep phenotypes of inc mutants, suggesting that memory hyperfunction can provoke sleep deficits.

Multiple methods for assessing learning and memory in Drosophila melanogaster demonstrates the highly complex, context-dependent genetic underpinnings of cognitive traits

Learning and memory are fundamental for an individual to be able to respond to changing stimuli in their environment. Between individuals we see variation in their ability to perform learning and memory tasks, however, it is still largely unknown what genetic factors may impact this variability. To gain better insight to the genetic components impacting variation in learning and memory, we use recombinant inbred lines (RILs) from the Drosophila synthetic population resource (DSPR), a multiparent mapping population exhibiting natural variation in many traits. Using a reward based associative learning and memory assay, we trained flies to associate an odor with a sucrose reward under starvation condition and measured olfactory learning and memory ability in y-mazes for 50 DSPR RILs. While we do not find significant QTLs for olfactory learning or memory, we found suggestive regions that may be contributing to variability in performance when trained to different odors. We provide evidence that performance with specific odors should be considered different phenotypes and introduce new methods for analysis for olfactory y-maze assays with multiple decision points. Additionally, we compare our data to previously collected place learning and memory data to show there is limited correlation in performance outcomes.

Social context and dopamine signaling converge in the mushroom body to drive impulsivity

Organisms adapt their behaviors flexibly in response to various internal and environmental factors. However, how and where these factors converge in the brain to alter behavior is not well understood. In this study, we examine how social context interacts with dopamine activity to influence inhibitory control in Drosophila . We found that, regardless of social context-whether isolated or in groups-wild-type flies consistently showed strong movement suppression in a go/no-go task that measures action restraint. In contrast, flies with enhanced dopamine activity suppressed their movements when tested alone or with potential mates but exhibited impulsive behaviors when exposed to same-sex peers. This social-context-dependent impulsivity was shown to rely on dopamine-D1 receptor-cAMP signaling in mushroom body (MB) neurons. Remarkably, activating the MB was sufficient to induce impulsivity, even without dopamine input or a social context. Our findings highlight MB as a critical hub where social context and dopamine signaling converge to regulate impulsive behavior in Drosophila .

Signficance statement

This study demonstrates that impulsivity results from the interplay between elevated dopamine levels and social context, rather than dopamine alone, with the mushroom body (MB) serving as a key neural hub for integrating these signals in Drosophila . Social stimuli, such as the presence of same-sex peers, disrupt inhibitory control in a context-dependent manner, highlighting the importance of multimodal sensory inputs and MB activity. These findings challenge the isolation-focused approach in traditional impulsivity research and underscore the need to account for social influences when investigating cognitive processes and disorders like ADHD, autism, and substance use, where social settings often amplify symptoms.

Classification

Genetics / Neuroscience.

A biological model of nonlinear dimensionality reduction

Obtaining appropriate low-dimensional representations from high-dimensional sensory inputs in an unsupervised manner is essential for straightforward downstream processing. Although nonlinear dimensionality reduction methods such as t-distributed stochastic neighbor embedding (t-SNE) have been developed, their implementation in simple biological circuits remains unclear. Here, we develop a biologically plausible dimensionality reduction algorithm compatible with t-SNE, which uses a simple three-layer feedforward network mimicking the Drosophila olfactory circuit. The proposed learning rule, described as three-factor Hebbian plasticity, is effective for datasets such as entangled rings and MNIST, comparable to t-SNE. We further show that the algorithm could be working in olfactory circuits in Drosophila by analyzing the multiple experimental data in previous studies. We lastly suggest that the algorithm is also beneficial for association learning between inputs and rewards, allowing the generalization of these associations to other inputs not yet associated with rewards.

How bumblebees manage conflicting information seen on arrival and departure from flowers

Bees are flexible and adaptive learners, capable of learning stimuli seen on arrival and at departure from flowers where they have fed. This gives bees the potential to learn all information associated with a feeding event, but it also presents the challenge of managing information that is irrelevant, inconsistent, or conflicting. Here, we examined how presenting bumblebees with conflicting visual information before and after feeding influenced their learning rate and what they learned. Bees were trained to feeder stations mounted in front of a computer monitor. Visual stimuli were displayed behind each feeder station on the monitor. Positively reinforced stimuli (CS +) marked feeders offering sucrose solution. Negatively reinforced stimuli (CS-) marked feeders offering quinine solution. While alighted at the feeder station the stimuli were likely not visible to the bee. The "constant stimulus" training group saw the same stimulus throughout. For the "switched stimulus" training group, the CS + changed to the CS- during feeding. Learning was slower in the "switched stimulus" training group compared to the constant stimulus" group, but the training groups did not differ in their learning performance or the extent to which they generalised their learning. The information conflict in the "switched stimulus" group did not interfere with what had been learned. Differences between the "switched" and "constant stimulus" groups were greater for bees trained on a horizontal CS + than a vertical CS + suggesting bees differ in their processing of vertically and horizontally oriented stimuli. We discuss how bumblebees might resolve this type of information conflict so effectively, drawing on the known neurobiology of their visual learning system.

Memory-like states created by the first ethanol experience are encoded into the Drosophila mushroom body learning and memory circuitry in an ethanol-specific manner

A first ethanol exposure creates three memory-like states in Drosophila. Ethanol memory-like states appear genetically and behaviorally paralleled to the canonical learning and memory traces anesthesia-sensitive, anesthesia-resistant, and long-term memory ASM, ARM, and LTM. It is unknown if these ethanol memory-like states are also encoded by the canonical learning and memory circuitry that is centered on the mushroom bodies. We show that the three ethanol memory-like states, anesthesia-sensitive tolerance (AST) and anesthesia resistant tolerance (ART) created by ethanol sedation to a moderately high ethanol exposure, and chronic tolerance created by a longer low concentration ethanol exposure, each engage the mushroom body circuitry differently. Moreover, critical encoding steps for ethanol memory-like states reside outside the mushroom body circuitry, and within the mushroom body circuitry they are markedly distinct from classical memory traces. Thus, the first ethanol exposure creates distinct memory-like states in ethanol-specific circuits and impacts the function of learning and memory circuitry in ways that might influence the formation and retention of other memories.

Synaptic enrichment and dynamic regulation of the two opposing dopamine receptors within the same neurons

Dopamine can play opposing physiological roles depending on the receptor subtype. In the fruit fly Drosophila melanogaster, Dop1R1 and Dop2R encode the D1- and D2-like receptors, respectively, and are reported to oppositely regulate intracellular cAMP levels. Here, we profiled the expression and subcellular localization of endogenous Dop1R1 and Dop2R in specific cell types in the mushroom body circuit. For cell-type-specific visualization of endogenous proteins, we employed reconstitution of split-GFP tagged to the receptor proteins. We detected dopamine receptors at both presynaptic and postsynaptic sites in multiple cell types. Quantitative analysis revealed enrichment of both receptors at the presynaptic sites, with Dop2R showing a greater degree of localization than Dop1R1. The presynaptic localization of Dop1R1 and Dop2R in dopamine neurons suggests dual feedback regulation as autoreceptors. Furthermore, we discovered a starvation-dependent, bidirectional modulation of the presynaptic receptor expression in the protocerebral anterior medial (PAM) and posterior lateral 1 (PPL1) clusters, two distinct subsets of dopamine neurons, suggesting their roles in regulating appetitive behaviors. Our results highlight the significance of the co-expression of the two opposing dopamine receptors in the spatial and conditional regulation of dopamine responses in neurons.

Driver lines for studying associative learning in Drosophila

The mushroom body (MB) is the center for associative learning in insects. In Drosophila, intersectional split-GAL4 drivers and electron microscopy (EM) connectomes have laid the foundation for precise interrogation of the MB neural circuits. However, investigation of many cell types upstream and downstream of the MB has been hindered due to lack of specific driver lines. Here we describe a new collection of over 800 split-GAL4 and split-LexA drivers that cover approximately 300 cell types, including sugar sensory neurons, putative nociceptive ascending neurons, olfactory and thermo-/hygro-sensory projection neurons, interneurons connected with the MB-extrinsic neurons, and various other cell types. We characterized activation phenotypes for a subset of these lines and identified a sugar sensory neuron line most suitable for reward substitution. Leveraging the thousands of confocal microscopy images associated with the collection, we analyzed neuronal morphological stereotypy and discovered that one set of mushroom body output neurons, MBON08/MBON09, exhibits striking individuality and asymmetry across animals. In conjunction with the EM connectome maps, the driver lines reported here offer a powerful resource for functional dissection of neural circuits for associative learning in adult Drosophila.

Periodic ER-plasma membrane junctions support long-range Ca2+ signal integration in dendrites

Neuronal dendrites must relay synaptic inputs over long distances, but the mechanisms by which activity-evoked intracellular signals propagate over macroscopic distances remain unclear. Here, we discovered a system of periodically arranged endoplasmic reticulum-plasma membrane (ER-PM) junctions tiling the plasma membrane of dendrites at ∼1 μm intervals, interlinked by a meshwork of ER tubules patterned in a ladder-like array. Populated with Junctophilin-linked plasma membrane voltage-gated Ca2+ channels and ER Ca2+-release channels (ryanodine receptors), ER-PM junctions are hubs for ER-PM crosstalk, fine-tuning of Ca2+ homeostasis, and local activation of the Ca2+/calmodulin-dependent protein kinase II. Local spine stimulation activates the Ca2+ modulatory machinery, facilitating signal transmission and ryanodine-receptor-dependent Ca2+ release at ER-PM junctions over 20 μm away. Thus, interconnected ER-PM junctions support signal propagation and Ca2+ release from the spine-adjacent ER. The capacity of this subcellular architecture to modify both local and distant membrane-proximal biochemistry potentially contributes to dendritic computations.

The unbearable slowness of being: Why do we live at 10 bits/s?

This article is about the neural conundrum behind the slowness of human behavior. The information throughput of a human being is about 10 bits/s. In comparison, our sensory systems gather data at ∼109 bits/s. The stark contrast between these numbers remains unexplained and touches on fundamental aspects of brain function: what neural substrate sets this speed limit on the pace of our existence? Why does the brain need billions of neurons to process 10 bits/s? Why can we only think about one thing at a time? The brain seems to operate in two distinct modes: the "outer" brain handles fast high-dimensional sensory and motor signals, whereas the "inner" brain processes the reduced few bits needed to control behavior. Plausible explanations exist for the large neuron numbers in the outer brain, but not for the inner brain, and we propose new research directions to remedy this.

Social state alters vision using three circuit mechanisms in Drosophila

Animals are often bombarded with visual information and must prioritize specific visual features based on their current needs. The neuronal circuits that detect and relay visual features have been well studied1-8. Much less is known about how an animal adjusts its visual attention as its goals or environmental conditions change. During social behaviours, flies need to focus on nearby flies9-11. Here we study how the flow of visual information is altered when female Drosophila enter an aggressive state. From the connectome, we identify three state-dependent circuit motifs poised to modify the response of an aggressive female to fly-sized visual objects: convergence of excitatory inputs from neurons conveying select visual features and internal state; dendritic disinhibition of select visual feature detectors; and a switch that toggles between two visual feature detectors. Using cell-type-specific genetic tools, together with behavioural and neurophysiological analyses, we show that each of these circuit motifs is used during female aggression. We reveal that features of this same switch operate in male Drosophila during courtship pursuit, suggesting that disparate social behaviours may share circuit mechanisms. Our study provides a compelling example of using the connectome to infer circuit mechanisms that underlie dynamic processing of sensory signals.

A neurotrophin functioning with a Toll regulates structural plasticity in a dopaminergic circuit

Experience shapes the brain as neural circuits can be modified by neural stimulation or the lack of it. The molecular mechanisms underlying structural circuit plasticity and how plasticity modifies behaviour are poorly understood. Subjective experience requires dopamine, a neuromodulator that assigns a value to stimuli, and it also controls behaviour, including locomotion, learning, and memory. In Drosophila, Toll receptors are ideally placed to translate experience into structural brain change. Toll-6 is expressed in dopaminergic neurons (DANs), raising the intriguing possibility that Toll-6 could regulate structural plasticity in dopaminergic circuits. Drosophila neurotrophin-2 (DNT-2) is the ligand for Toll-6 and Kek-6, but whether it is required for circuit structural plasticity was unknown. Here, we show that DNT-2-expressing neurons connect with DANs, and they modulate each other. Loss of function for DNT-2 or its receptors Toll-6 and kinase-less Trk-like kek-6 caused DAN and synapse loss, impaired dendrite growth and connectivity, decreased synaptic sites, and caused locomotion deficits. In contrast, over-expressed DNT-2 increased DAN cell number, dendrite complexity, and promoted synaptogenesis. Neuronal activity modified DNT-2, increased synaptogenesis in DNT-2-positive neurons and DANs, and over-expression of DNT-2 did too. Altering the levels of DNT-2 or Toll-6 also modified dopamine-dependent behaviours, including locomotion and long-term memory. To conclude, a feedback loop involving dopamine and DNT-2 highlighted the circuits engaged, and DNT-2 with Toll-6 and Kek-6 induced structural plasticity in this circuit modifying brain function and behaviour.

Neuronal circuit mechanisms of competitive interaction between action-based and coincidence learning

How information is integrated across different forms of learning is crucial to understanding higher cognitive functions. Animals form classic or operant associations between cues and their outcomes. It is believed that a prerequisite for operant conditioning is the formation of a classical association. Thus, both memories coexist and are additive. However, the two memories can result in opposing behavioral responses, which can be disadvantageous. We show that Drosophila classical and operant olfactory conditioning rely on distinct neuronal pathways leading to different behavioral responses. Plasticity in both pathways cannot be formed simultaneously. If plasticity occurs at both pathways, interference between them occurs and learning is disrupted. Activity of the navigation center is required to prevent plasticity in the classical pathway and enable it in the operant pathway. These findings fundamentally challenge hierarchical views of operant and classical learning and show that active processes prevent coexistence of the two memories.

Modulation of RNA processing genes during sleep-dependent memory

Memory consolidation in Drosophila can be sleep-dependent or sleep-independent, depending on the availability of food. The anterior posterior (ap) alpha'/beta' (α'/β') neurons of the mushroom body (MB) are required for sleep-dependent memory consolidation in flies fed after training. These neurons are also involved in the increase of sleep after training, suggesting a coupling of sleep and memory. To better understand the mechanisms underlying sleep and memory consolidation initiation, we analyzed the transcriptome of ap α'/β' neurons 1 hr after appetitive memory conditioning. A small number of genes, enriched in RNA processing functions, were differentially expressed in flies fed after training relative to trained and starved flies or untrained flies. Knockdown of each of these differentially expressed genes in the ap α'/β' neurons revealed notable sleep phenotypes for Polr1F and Regnase-1, both of which decrease in expression after conditioning. Knockdown of Polr1F, a regulator of ribosome RNA transcription, in adult flies promotes sleep and increases pre-ribosome RNA expression as well as overall translation, supporting a function for Polr1F downregulation in sleep-dependent memory. Conversely, while constitutive knockdown of Regnase-1, an mRNA decay protein localized to the ribosome, reduces sleep, adult specific knockdown suggests that effects of Regnase-1 on sleep are developmental in nature. We further tested the role of each gene in memory consolidation. Knockdown of Polr1F does not affect memory, which may be expected from its downregulation during memory consolidation. Regnase-1 knockdown in ap α'/β' neurons impairs all memory, including short-term, implicating Regnase-1 in memory, but leaving open the question of why it is downregulated during sleep-dependent memory. Overall, our findings demonstrate that the expression of RNA processing genes is modulated during sleep-dependent memory and, in the case of Polr1F, this modulation likely contributes to increased sleep.

Dopamine neurons that inform Drosophila olfactory memory have distinct, acute functions driving attraction and aversion

The brain must guide immediate responses to beneficial and harmful stimuli while simultaneously writing memories for future reference. While both immediate actions and reinforcement learning are instructed by dopamine, how dopaminergic systems maintain coherence between these 2 reward functions is unknown. Through optogenetic activation experiments, we showed that the dopamine neurons that inform olfactory memory in Drosophila have a distinct, parallel function driving attraction and aversion (valence). Sensory neurons required for olfactory memory were dispensable to dopaminergic valence. A broadly projecting set of dopaminergic cells had valence that was dependent on dopamine, glutamate, and octopamine. Similarly, a more restricted dopaminergic cluster with attractive valence was reliant on dopamine and glutamate; flies avoided opto-inhibition of this narrow subset, indicating the role of this cluster in controlling ongoing behavior. Dopamine valence was distinct from output-neuron opto-valence in locomotor pattern, strength, and polarity. Overall, our data suggest that dopamine's acute effect on valence provides a mechanism by which a dopaminergic system can coherently write memories to influence future responses while guiding immediate attraction and aversion.

Activity Monitoring for Analysis of Sleep in Drosophila melanogaster

Sleep is important for survival, and the need for sleep is conserved across species. In the past two decades, the fruit fly Drosophila melanogaster has emerged as a promising system in which to study the genetic, neural, and physiological bases of sleep. Through significant advances in our understanding of the regulation of sleep in flies, the field is poised to address several open questions about sleep, such as how the need for sleep is encoded, how molecular regulators of sleep are situated within brain networks, and what the functions of sleep are. Here, we describe key findings, open questions, and commonly used methods that have been used to inform existing theories and develop new ways of thinking about the function, regulation, and adaptability of sleep behavior.

Ephrin-mediated dendrite-dendrite repulsion regulates compartment-specific targeting of dendrites in the central nervous system

Neurons often forms synaptic contacts at specific subcellular domains to differentially regulate the activity of target neurons. However, how dendrites are targeted to specific subcellular domains of axons is rarely studied. Here we use Drosophila mushroom body out neurons (MBONs) and local dopaminergic neurons (DANs) as a model system to study how dendrites and axons are targeted to specific subcellular domains (compartments) of mushroom body axonal lobes to form synaptic contacts. We found that Ephrin-mediated dendrite-dendrite repulsion between neighboring compartments restricts the projection of MBON dendrites to their specific compartments and prevents the formation of ectopic synaptic connections with DAN axons in neighboring compartments. Meanwhile, DAN neurons in a subset of compartments may also depend on their partner MBONs for projecting their axons to a specific compartment and cover the same territory as their partner MBON dendrites. Our work reveals that compartment-specific targeting of MBON dendrites and DAN axons is regulated in part by a combination of dendrite-dendrite repulsion between neighboring compartments and dendrite-axon interactions within the same compartment.

Slit regulates compartment-specific targeting of dendrites and axons in the Drosophila brain

Proper functioning of the nervous system requires precise neuronal connections at subcellular domains, which can be achieved by projection of axons or dendrites to subcellular domains of target neurons. Here we studied subcellular-specific targeting of dendrites and axons in the Drosophila mushroom body (MB), where mushroom body output neurons (MBONs) and local dopaminergic neurons (DAN) project their dendrites and axons, respectively, to specific compartments of MB axons. Through genetic ablation, we demonstrate that compartment-specific targeting of MBON dendrites and DAN axons involves mutual repulsion of MBON dendrites and/or DAN axons between neighboring compartments. We further show that Slit expressed in subset of DANs mediates such repulsion by acting through different Robo receptors in different neurons. Loss of Slit-mediated repulsion leads to projection of MBON dendrites and DAN axons into neighboring compartments, resulting formation of ectopic synaptic contacts between MBONs and DANs and changes in olfactory-associative learning. Together, our findings suggest that Slit-mediated repulsion controls compartment-specific targeting of MBON dendrites and DAN axons, which ensures precise connections between MBON dendrites and DAN axons and proper learning and memory formation.

Brief disruption of activity in a subset of dopaminergic neurons during consolidation impairs long-term memory by fragmenting sleep

Sleep disturbances are associated with poor long-term memory (LTM) formation, yet the underlying cell types and neural circuits involved have not been fully decoded. Dopamine neurons (DANs) are involved in memory processing at multiple stages. Here, using both male and female flies, Drosophila melanogaster , we show that, during the first few hours of memory consolidation, disruption of basal activity of a small subset of protocerebral anterior medial DANs (PAM-DANs), by either brief activation or inhibition of the two dorsal posterior medial (DPM) neurons, impairs 24 h LTM. Interestingly, these brief changes in activity using female flies result in sleep loss and fragmentation, especially at night. Pharmacological rescue of sleep after manipulation restores LTM. A specific subset of PAM-DANs (PAM-α1) that synapse onto DPM neurons specify the microcircuit that links sleep and memory. PAM-DANs, including PAM-α1, form functional synapses onto DPM mainly via multiple dopamine receptor subtypes. This PAM-α1 to DPM microcircuit exhibits a synchronized, transient, post-training increase in activity during the critical memory consolidation window, suggesting an effect of this microcircuit on maintaining the sleep necessary for LTM consolidation. Our results provide a new cellular and circuit basis for the complex relationship between sleep and memory.

The Neural Correlations of Olfactory Associative Reward Memories in Drosophila

Advancing treatment to resolve human cognitive disorders requires a comprehensive understanding of the molecular signaling pathways underlying learning and memory. While most organ systems evolved to maintain homeostasis, the brain developed the capacity to perceive and adapt to environmental stimuli through the continuous modification of interactions within a gene network functioning within a broader neural network. This distinctive characteristic enables significant neural plasticity, but complicates experimental investigations. A thorough examination of the mechanisms underlying behavioral plasticity must integrate multiple levels of biological organization, encompassing genetic pathways within individual neurons, interactions among neural networks providing feedback on gene expression, and observable phenotypic behaviors. Model organisms, such as Drosophila melanogaster, which possess more simple and manipulable nervous systems and genomes than mammals, facilitate such investigations. The evolutionary conservation of behavioral phenotypes and the associated genetics and neural systems indicates that insights gained from flies are pertinent to understanding human cognition. Rather than providing a comprehensive review of the entire field of Drosophila memory research, we focus on olfactory associative reward memories and their related neural circuitry in fly brains, with the objective of elucidating the underlying neural mechanisms, thereby advancing our understanding of brain mechanisms linked to cognitive systems.

Reinforcement learning when your life depends on it: A neuro-economic theory of learning

Synaptic plasticity enables animals to adapt to their environment, but memory formation can require a substantial amount of metabolic energy, potentially impairing survival. Hence, a neuro-economic dilemma arises whether learning is a profitable investment or not, and the brain must therefore judiciously regulate learning. Indeed, in experiments it was observed that during starvation, Drosophila suppress formation of energy-intensive aversive memories. Here we include energy considerations in a reinforcement learning framework. Simulated flies learned to avoid noxious stimuli through synaptic plasticity in either the energy expensive long-term memory (LTM) pathway, or the decaying anesthesia-resistant memory (ARM) pathway. The objective of the flies is to maximize their lifespan, which is calculated with a hazard function. We find that strategies that switch between the LTM and ARM pathways, based on energy reserve and reward prediction error, prolong lifespan. Our study highlights the significance of energy-regulation of memory pathways and dopaminergic control for adaptive learning and survival. It might also benefit engineering applications of reinforcement learning under resources constraints.

Whole-brain annotation and multi-connectome cell typing of Drosophila

The fruit fly Drosophila melanogaster has emerged as a key model organism in neuroscience, in large part due to the concentration of collaboratively generated molecular, genetic and digital resources available for it. Here we complement the approximately 140,000 neuron FlyWire whole-brain connectome1 with a systematic and hierarchical annotation of neuronal classes, cell types and developmental units (hemilineages). Of 8,453 annotated cell types, 3,643 were previously proposed in the partial hemibrain connectome2, and 4,581 are new types, mostly from brain regions outside the hemibrain subvolume. Although nearly all hemibrain neurons could be matched morphologically in FlyWire, about one-third of cell types proposed for the hemibrain could not be reliably reidentified. We therefore propose a new definition of cell type as groups of cells that are each quantitatively more similar to cells in a different brain than to any other cell in the same brain, and we validate this definition through joint analysis of FlyWire and hemibrain connectomes. Further analysis defined simple heuristics for the reliability of connections between brains, revealed broad stereotypy and occasional variability in neuron count and connectivity, and provided evidence for functional homeostasis in the mushroom body through adjustments of the absolute amount of excitatory input while maintaining the excitation/inhibition ratio. Our work defines a consensus cell type atlas for the fly brain and provides both an intellectual framework and open-source toolchain for brain-scale comparative connectomics.

Reinforcement learning as a robotics-inspired framework for insect navigation: from spatial representations to neural implementation

Bees are among the master navigators of the insect world. Despite impressive advances in robot navigation research, the performance of these insects is still unrivaled by any artificial system in terms of training efficiency and generalization capabilities, particularly considering the limited computational capacity. On the other hand, computational principles underlying these extraordinary feats are still only partially understood. The theoretical framework of reinforcement learning (RL) provides an ideal focal point to bring the two fields together for mutual benefit. In particular, we analyze and compare representations of space in robot and insect navigation models through the lens of RL, as the efficiency of insect navigation is likely rooted in an efficient and robust internal representation, linking retinotopic (egocentric) visual input with the geometry of the environment. While RL has long been at the core of robot navigation research, current computational theories of insect navigation are not commonly formulated within this framework, but largely as an associative learning process implemented in the insect brain, especially in the mushroom body (MB). Here we propose specific hypothetical components of the MB circuit that would enable the implementation of a certain class of relatively simple RL algorithms, capable of integrating distinct components of a navigation task, reminiscent of hierarchical RL models used in robot navigation. We discuss how current models of insect and robot navigation are exploring representations beyond classical, complete map-like representations, with spatial information being embedded in the respective latent representations to varying degrees.

Analysis of fast calcium dynamics of honey bee olfactory coding

Odour processing exhibits multiple parallels between vertebrate and invertebrate olfactory systems. Insects, in particular, have emerged as relevant models for olfactory studies because of the tractability of their olfactory circuits. Here, we used fast calcium imaging to track the activity of projection neurons in the honey bee antennal lobe (AL) during olfactory stimulation at high temporal resolution. We observed a heterogeneity of response profiles and an abundance of inhibitory activities, resulting in various response latencies and stimulus-specific post-odour neural signatures. Recorded calcium signals were fed to a mushroom body (MB) model constructed implementing the fundamental features of connectivity between olfactory projection neurons, Kenyon cells (KC), and MB output neurons (MBON). The model accounts for the increase of odorant discrimination in the MB compared to the AL and reveals the recruitment of two distinct KC populations that represent odorants and their aftersmell as two separate but temporally coherent neural objects. Finally, we showed that the learning-induced modulation of KC-to-MBON synapses can explain both the variations in associative learning scores across different conditioning protocols used in bees and the bees' response latency. Thus, it provides a simple explanation of how the time contingency between the stimulus and the reward can be encoded without the need for time tracking. This study broadens our understanding of olfactory coding and learning in honey bees. It demonstrates that a model based on simple MB connectivity rules and fed with real physiological data can explain fundamental aspects of odour processing and associative learning.

Olfactory sensory neuron population expansions influence projection neuron adaptation and enhance odour tracking

The evolutionary expansion of sensory neuron populations detecting important environmental cues is widespread, but functionally enigmatic. We investigated this phenomenon through comparison of homologous olfactory pathways of Drosophila melanogaster and its close relative Drosophila sechellia, an extreme specialist for Morinda citrifolia noni fruit. D. sechellia has evolved species-specific expansions in select, noni-detecting olfactory sensory neuron (OSN) populations, through multigenic changes. Activation and inhibition of defined proportions of neurons demonstrate that OSN number increases contribute to stronger, more persistent, noni-odour tracking behaviour. These expansions result in increased synaptic connections of sensory neurons with their projection neuron (PN) partners, which are conserved in number between species. Surprisingly, having more OSNs does not lead to greater odour-evoked PN sensitivity or reliability. Rather, pathways with increased sensory pooling exhibit reduced PN adaptation, likely through weakened lateral inhibition. Our work reveals an unexpected functional impact of sensory neuron population expansions to explain ecologically-relevant, species-specific behaviour.

Fly into tranquility: GABA's role in Drosophila sleep

Sleep is conserved across the animal kingdom, and Drosophila melanogaster is a prime model to understand its intricate circadian and homeostatic control. GABA (gamma-aminobutyric acid), the brain's main inhibitory neurotransmitter, plays a central role in sleep. This review delves into GABA's complex mechanisms of actions within Drosophila's sleep-regulating neural networks. We discuss how GABA promotes sleep, both by inhibiting circadian arousal neurons and by being a key neurotransmitter in sleep homeostatic circuits. GABA's impact on sleep is modulated by glia through astrocytic GABA recapture and metabolism. Interestingly, GABA can be coexpressed with other neurotransmitters in sleep-regulating neurons, which likely contributes to context-based sleep plasticity.

Serotonergic amplification of odor-evoked neural responses maps onto flexible behavioral outcomes

Behavioral responses to many odorants are not fixed but are flexible, varying based on organismal needs. How such variations arise and the role of various neuromodulators in achieving flexible neural-to-behavioral mapping is not fully understood. In this study, we examined how serotonin modulates the neural and behavioral responses to odorants in locusts (Schistocerca americana). Our results indicated that serotonin can increase or decrease appetitive behavior in an odor-specific manner. On the other hand, in the antennal lobe, serotonergic modulation enhanced odor-evoked response strength but left the temporal features or the combinatorial response profiles unperturbed. This result suggests that serotonin allows for sensitive and robust recognition of odorants. Nevertheless, the uniform neural response amplification appeared to be at odds with the observed stimulus-specific behavioral modulation. We show that a simple linear model with neural ensembles segregated based on behavioral relevance is sufficient to explain the serotonin-mediated flexible mapping between neural and behavioral responses.

Diversity of visual inputs to Kenyon cells of the Drosophila mushroom body

The arthropod mushroom body is well-studied as an expansion layer representing olfactory stimuli and linking them to contingent events. However, 8% of mushroom body Kenyon cells in Drosophila melanogaster receive predominantly visual input, and their function remains unclear. Here, we identify inputs to visual Kenyon cells using the FlyWire adult whole-brain connectome. Input repertoires are similar across hemispheres and connectomes with certain inputs highly overrepresented. Many visual neurons presynaptic to Kenyon cells have large receptive fields, while interneuron inputs receive spatially restricted signals that may be tuned to specific visual features. Individual visual Kenyon cells randomly sample sparse inputs from combinations of visual channels, including multiple optic lobe neuropils. These connectivity patterns suggest that visual coding in the mushroom body, like olfactory coding, is sparse, distributed, and combinatorial. However, the specific input repertoire to the smaller population of visual Kenyon cells suggests a constrained encoding of visual stimuli.

Common principles for odour coding across vertebrates and invertebrates

The olfactory system is an ideal and tractable system for exploring how the brain transforms sensory inputs into behaviour. The basic tasks of any olfactory system include odour detection, discrimination and categorization. The challenge for the olfactory system is to transform the high-dimensional space of olfactory stimuli into the much smaller space of perceived objects and valence that endows odours with meaning. Our current understanding of how neural circuits address this challenge has come primarily from observations of the mechanisms of the brain for processing other sensory modalities, such as vision and hearing, in which optimized deep hierarchical circuits are used to extract sensory features that vary along continuous physical dimensions. The olfactory system, by contrast, contends with an ill-defined, high-dimensional stimulus space and discrete stimuli using a circuit architecture that is shallow and parallelized. Here, we present recent observations in vertebrate and invertebrate systems that relate the statistical structure and state-dependent modulation of olfactory codes to mechanisms of perception and odour-guided behaviour.

A lightweight data-driven spiking neuronal network model of Drosophila olfactory nervous system with dedicated hardware support

Data-driven spiking neuronal network (SNN) models enable in-silico analysis of the nervous system at the cellular and synaptic level. Therefore, they are a key tool for elucidating the information processing principles of the brain. While extensive research has focused on developing data-driven SNN models for mammalian brains, their complexity poses challenges in achieving precision. Network topology often relies on statistical inference, and the functions of specific brain regions and supporting neuronal activities remain unclear. Additionally, these models demand huge computing facilities and their simulation speed is considerably slower than real-time. Here, we propose a lightweight data-driven SNN model that strikes a balance between simplicity and reproducibility. The model is built using a qualitative modeling approach that can reproduce key dynamics of neuronal activity. We target the Drosophila olfactory nervous system, extracting its network topology from connectome data. The model was successfully implemented on a small entry-level field-programmable gate array and simulated the activity of a network in real-time. In addition, the model reproduced olfactory associative learning, the primary function of the olfactory system, and characteristic spiking activities of different neuron types. In sum, this paper propose a method for building data-driven SNN models from biological data. Our approach reproduces the function and neuronal activities of the nervous system and is lightweight, acceleratable with dedicated hardware, making it scalable to large-scale networks. Therefore, our approach is expected to play an important role in elucidating the brain's information processing at the cellular and synaptic level through an analysis-by-construction approach. In addition, it may be applicable to edge artificial intelligence systems in the future.

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.

Functional Imaging of Learning-Induced Plasticity in the Central Nervous System with Genetically Encoded Reporters in Drosophila

Learning and memory allow animals to adjust their behavior based on the predictive value of their past experiences. Memories often exist in complex representations, spread across numerous cells and synapses in the brain. Studying relatively simple forms of memory provides insights into the fundamental processes that underlie multiple forms of memory. Associative learning occurs when an animal learns the relationship between two previously unrelated sensory stimuli, such as when a hungry animal learns that a particular odor is followed by a tasty reward. Drosophila is a particularly powerful model to study how this type of memory works. The fundamental principles are widely shared among animals, and there is a wide range of genetic tools available to study circuit function in flies. In addition, the olfactory structures that mediate associative learning in flies, such as the mushroom body and its associated neurons, are anatomically organized, relatively well-characterized, and readily accessible to imaging. Here, we review the olfactory anatomy and physiology of the olfactory system, describe how plasticity in the olfactory pathway mediates learning and memory, and explain the general principles underlying calcium imaging approaches.

Building and integrating brain-wide maps of nervous system function in invertebrates

The selection and execution of context-appropriate behaviors is controlled by the integrated action of neural circuits throughout the brain. However, how activity is coordinated across brain regions, and how nervous system structure enables these functional interactions, remain open questions. Recent technical advances have made it feasible to build brain-wide maps of nervous system structure and function, such as brain activity maps, connectomes, and cell atlases. Here, we review recent progress in this area, focusing on C. elegans and D. melanogaster, as recent work has produced global maps of these nervous systems. We also describe neural circuit motifs elucidated in studies of specific networks, which highlight the complexities that must be captured to build accurate models of whole-brain function.

Tet controls axon guidance in early brain development through glutamatergic signaling

Mutations in ten-eleven translocation (TET) proteins are associated with human neurodevelopmental disorders. We find a function of Tet in regulating Drosophila early brain development. The Tet DNA-binding domain (TetAXXC) is required for axon guidance in the mushroom body (MB). Glutamine synthetase 2 (Gs2), a key enzyme in glutamatergic signaling, is significantly down-regulated in the TetAXXC brains. Loss of Gs2 recapitulates the TetAXXC phenotype. Surprisingly, Tet and Gs2 act in the insulin-producing cells (IPCs) to control MB axon guidance, and overexpression of Gs2 in IPCs rescues the defects of TetAXXC. Feeding TetAXXC with metabotropic glutamate receptor antagonist MPEP rescues the phenotype while glutamate enhances it. Mutants in Tet and Drosophila Fmr1, the homolog of human FMR1, have similar defects, and overexpression of Gs2 in IPCs also rescues the Fmr1 phenotype. We provide the first evidence that Tet controls the guidance of developing brain axons by modulating glutamatergic signaling.

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.

The caloric value of food intake structurally adjusts a neuronal mushroom body circuit mediating olfactory learning in Drosophila

Associative learning enables the adaptive adjustment of behavioral decisions based on acquired, predicted outcomes. The valence of what is learned is influenced not only by the learned stimuli and their temporal relations, but also by prior experiences and internal states. In this study, we used the fruit fly Drosophila melanogaster to demonstrate that neuronal circuits involved in associative olfactory learning undergo restructuring during extended periods of low-caloric food intake. Specifically, we observed a decrease in the connections between specific dopaminergic neurons (DANs) and Kenyon cells at distinct compartments of the mushroom body. This structural synaptic plasticity was contingent upon the presence of allatostatin A receptors in specific DANs and could be mimicked optogenetically by expressing a light-activated adenylate cyclase in exactly these DANs. Importantly, we found that this rearrangement in synaptic connections influenced aversive, punishment-induced olfactory learning but did not impact appetitive, reward-based learning. Whether induced by prolonged low-caloric conditions or optogenetic manipulation of cAMP levels, this synaptic rearrangement resulted in a reduction of aversive associative learning. Consequently, the balance between positive and negative reinforcing signals shifted, diminishing the ability to learn to avoid odor cues signaling negative outcomes. These results exemplify how a neuronal circuit required for learning and memory undergoes structural plasticity dependent on prior experiences of the nutritional value of food.

Modeling neurodegenerative and neurodevelopmental disorders in the Drosophila mushroom body

The common fruit fly Drosophila melanogaster provides a powerful platform to investigate the genetic, molecular, cellular, and neural circuit mechanisms of behavior. Research in this model system has shed light on multiple aspects of brain physiology and behavior, from fundamental neuronal function to complex behaviors. A major anatomical region that modulates complex behaviors is the mushroom body (MB). The MB integrates multimodal sensory information and is involved in behaviors ranging from sensory processing/responses to learning and memory. Many genes that underlie brain disorders are conserved, from flies to humans, and studies in Drosophila have contributed significantly to our understanding of the mechanisms of brain disorders. Genetic mutations that mimic human diseases-such as Fragile X syndrome, neurofibromatosis type 1, Parkinson's disease, and Alzheimer's disease-affect MB structure and function, altering behavior. Studies dissecting the effects of disease-causing mutations in the MB have identified key pathological mechanisms, and the development of a complete connectome promises to add a comprehensive anatomical framework for disease modeling. Here, we review Drosophila models of human neurodevelopmental and neurodegenerative disorders via the effects of their underlying mutations on MB structure, function, and the resulting behavioral alterations.

An octopamine-specific GRAB sensor reveals a monoamine relay circuitry that boosts aversive learning

Octopamine (OA), analogous to norepinephrine in vertebrates, is an essential monoamine neurotransmitter in invertebrates that plays a significant role in various biological functions, including olfactory associative learning. However, the spatial and temporal dynamics of OA in vivo remain poorly understood due to limitations associated with the currently available methods used to detect it. To overcome these limitations, we developed a genetically encoded GPCR  activation-based (GRAB) OA sensor called GRABOA1.0. This sensor is highly selective for OA and exhibits a robust and rapid increase in fluorescence in response to extracellular OA. Using GRABOA1.0, we monitored OA release in the Drosophila mushroom body (MB), the fly's learning center, and found that OA is released in response to both odor and shock stimuli in an aversive learning model. This OA release requires acetylcholine (ACh) released from Kenyon cells, signaling via nicotinic ACh receptors. Finally, we discovered that OA amplifies aversive learning behavior by augmenting dopamine-mediated punishment signals via Octβ1R in dopaminergic neurons, leading to alterations in synaptic plasticity within the MB. Thus, our new GRABOA1.0 sensor can be used to monitor OA release in real time under physiological conditions, providing valuable insights into the cellular and circuit mechanisms that underlie OA signaling.

Sensory encoding and memory in the mushroom body: signals, noise, and variability

To survive in changing environments, animals need to learn to associate specific sensory stimuli with positive or negative valence. How do they form stimulus-specific memories to distinguish between positively/negatively associated stimuli and other irrelevant stimuli? Solving this task is one of the functions of the mushroom body, the associative memory center in insect brains. Here we summarize recent work on sensory encoding and memory in the Drosophila mushroom body, highlighting general principles such as pattern separation, sparse coding, noise and variability, coincidence detection, and spatially localized neuromodulation, and placing the mushroom body in comparative perspective with mammalian memory systems.

What do the mushroom bodies do for the insect brain? Twenty-five years of progress

In 1998, a special edition of Learning & Memory was published with a discrete focus of synthesizing the state of the field to provide an overview of the function of the insect mushroom body. While molecular neuroscience and optical imaging of larger brain areas were advancing, understanding the basic functioning of neuronal circuits, particularly in the context of the mushroom body, was rudimentary. In the past 25 years, technological innovations have allowed researchers to map and understand the in vivo function of the neuronal circuits of the mushroom body system, making it an ideal model for investigating the circuit basis of sensory encoding, memory formation, and behavioral decisions. Collaborative efforts within the community have played a crucial role, leading to an interactive connectome of the mushroom body and accessible genetic tools for studying mushroom body circuit function. Looking ahead, continued technological innovation and collaborative efforts are likely to further advance our understanding of the mushroom body and its role in behavior and cognition, providing insights that generalize to other brain structures and species.

Cyclic nucleotide-induced bidirectional long-term synaptic plasticity in Drosophila mushroom body

Activation of the cAMP pathway is one of the common mechanisms underlying long-term potentiation (LTP). In the Drosophila mushroom body, simultaneous activation of odour-coding Kenyon cells (KCs) and reinforcement-coding dopaminergic neurons activates adenylyl cyclase in KC presynaptic terminals, which is believed to trigger synaptic plasticity underlying olfactory associative learning. However, learning induces long-term depression (LTD) at these synapses, contradicting the universal role of cAMP as a facilitator of transmission. Here, we developed a system to electrophysiologically monitor both short-term and long-term synaptic plasticity at KC output synapses and demonstrated that they are indeed an exception in which activation of the cAMP-protein kinase A pathway induces LTD. Contrary to the prevailing model, our cAMP imaging found no evidence for synergistic action of dopamine and KC activity on cAMP synthesis. Furthermore, we found that forskolin-induced cAMP increase alone was insufficient for plasticity induction; it additionally required simultaneous KC activation to replicate the presynaptic LTD induced by pairing with dopamine. On the other hand, activation of the cGMP pathway paired with KC activation induced slowly developing LTP, proving antagonistic actions of the two second-messenger pathways predicted by behavioural study. Finally, KC subtype-specific interrogation of synapses revealed that different KC subtypes exhibit distinct plasticity duration even among synapses on the same postsynaptic neuron. Thus, our work not only revises the role of cAMP in synaptic plasticity by uncovering the unexpected convergence point of the cAMP pathway and neuronal activity, but also establishes the methods to address physiological mechanisms of synaptic plasticity in this important model. KEY POINTS: Although presynaptic cAMP increase generally facilitates synapses, olfactory associative learning in Drosophila, which depends on dopamine and cAMP signalling genes, induces long-term depression (LTD) at the mushroom body output synapses. By combining electrophysiology, pharmacology and optogenetics, we directly demonstrate that these synapses are an exception where activation of the cAMP-protein kinase A pathway leads to presynaptic LTD. Dopamine- or forskolin-induced cAMP increase alone is not sufficient for LTD induction; neuronal activity, which has been believed to trigger cAMP synthesis in synergy with dopamine input, is required in the downstream pathway of cAMP. In contrast to cAMP, activation of the cGMP pathway paired with neuronal activity induces presynaptic long-term potentiation, which explains behaviourally observed opposing actions of transmitters co-released by dopaminergic neurons. Our work not only revises the role of cAMP in synaptic plasticity, but also provides essential methods to address physiological mechanisms of synaptic plasticity in this important model system.

Drosophila learning and memory centers and the actions of drugs of abuse

Drug addiction and the circuitry for learning and memory are intimately intertwined. Drugs of abuse create strong, inappropriate, and lasting memories that contribute to many of their destructive properties, such as continued use despite negative consequences and exceptionally high rates of relapse. Studies in Drosophila melanogaster are helping us understand how drugs of abuse, especially alcohol, create memories at the level of individual neurons and in the circuits where they function. Drosophila is a premier organism for identifying the mechanisms of learning and memory. Drosophila also respond to drugs of abuse in ways that remarkably parallel humans and rodent models. An emerging consensus is that, for alcohol, the mushroom bodies participate in the circuits that control acute drug sensitivity, not explicitly associative forms of plasticity such as tolerance, and classical associative memories of their rewarding and aversive properties. Moreover, it is becoming clear that drugs of abuse use the mushroom body circuitry differently from other behaviors, potentially providing a basis for their addictive properties.