Dopaminergic neurons write and update memories with cell-type-specific rules

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.

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.

Genetics and Molecular Biology of Memory Suppression

The brain is designed not only with molecules and cellular processes that help to form memories but also with molecules and cellular processes that suppress the formation and retention of memory. The latter processes are critical for an efficient memory management system, given the vast amount of information that each person experiences in their daily activities and that most of this information becomes irrelevant with time. Thus, efficiency dictates that the brain should have processes for selecting the most critical information for storage and suppressing the irrelevant or forgetting it later should it escape the initial filters. Such memory suppressor molecules and processes are revealed by genetic or pharmacologic insults that lead to enhanced memory expression. We review here the predominant memory suppressor molecules and processes that have recently been discovered. They are diverse, as expected, because the brain is complex and employs many different strategies and mechanisms to form memories. They include the gene-repressive actions of small noncoding RNAs, repressors of protein synthesis, cAMP-mediated gene expression pathways, inter- and intracellular signaling pathways for normal forgetting, and others. A deep understanding of memory suppressor molecules and processes is necessary to fully comprehend how the brain forms, stabilizes, and retrieves memories and to reveal how brain disorders disrupt memory.

A neural circuit architecture for rapid learning in goal-directed navigation

Anchoring goals to spatial representations enables flexible navigation but is challenging in novel environments when both representations must be acquired simultaneously. We propose a framework for how Drosophila uses internal representations of head direction (HD) to build goal representations upon selective thermal reinforcement. We show that flies use stochastically generated fixations and directed saccades to express heading preferences in an operant visual learning paradigm and that HD neurons are required to modify these preferences based on reinforcement. We used a symmetric visual setting to expose how flies' HD and goal representations co-evolve and how the reliability of these interacting representations impacts behavior. Finally, we describe how rapid learning of new goal headings may rest on a behavioral policy whose parameters are flexible but whose form is genetically encoded in circuit architecture. Such evolutionarily structured architectures, which enable rapidly adaptive behavior driven by internal representations, may be relevant across species.

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 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.

Beyond prediction error: 25 years of modeling the associations formed in the insect mushroom body

The insect mushroom body has gained increasing attention as a system in which the computational basis of neural learning circuits can be unraveled. We now understand in detail the key locations in this circuit where synaptic associations are formed between sensory patterns and values leading to actions. However, the actual learning rule (or rules) implemented by neural activity and leading to synaptic change is still an open question. Here, I survey the diversity of answers that have been offered in computational models of this system over the past decades, including the recurring assumption-in line with top-down theories of associative learning-that the core function is to reduce prediction error. However, I will argue, a more bottom-up approach may ultimately reveal a richer algorithmic capacity in this still enigmatic brain neuropil.

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.

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.

Future avenues in Drosophila mushroom body research

How does the brain translate sensory information into complex behaviors? With relatively small neuronal numbers, readable behavioral outputs, and an unparalleled genetic toolkit, the Drosophila mushroom body (MB) offers an excellent model to address this question in the context of associative learning and memory. Recent technological breakthroughs, such as the freshly completed full-brain connectome, multiomics approaches, CRISPR-mediated gene editing, and machine learning techniques, led to major advancements in our understanding of the MB circuit at the molecular, structural, physiological, and functional levels. Despite significant progress in individual MB areas, the field still faces the fundamental challenge of resolving how these different levels combine and interact to ultimately control the behavior of an individual fly. In this review, we discuss various aspects of MB research, with a focus on the current knowledge gaps, and an outlook on the future methodological developments required to reach an overall view of the neurobiological basis of learning and memory.

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.

NeuronBridge: an intuitive web application for neuronal morphology search across large data sets

BACKGROUND

Neuroscience research in Drosophila is benefiting from large-scale connectomics efforts using electron microscopy (EM) to reveal all the neurons in a brain and their connections. To exploit this knowledge base, researchers relate a connectome's structure to neuronal function, often by studying individual neuron cell types. Vast libraries of fly driver lines expressing fluorescent reporter genes in sets of neurons have been created and imaged using confocal light microscopy (LM), enabling the targeting of neurons for experimentation. However, creating a fly line for driving gene expression within a single neuron found in an EM connectome remains a challenge, as it typically requires identifying a pair of driver lines where only the neuron of interest is expressed in both. This task and other emerging scientific workflows require finding similar neurons across large data sets imaged using different modalities.

RESULTS

Here, we present NeuronBridge, a web application for easily and rapidly finding putative morphological matches between large data sets of neurons imaged using different modalities. We describe the functionality and construction of the NeuronBridge service, including its user-friendly graphical user interface (GUI), extensible data model, serverless cloud architecture, and massively parallel image search engine.

CONCLUSIONS

NeuronBridge fills a critical gap in the Drosophila research workflow and is used by hundreds of neuroscience researchers around the world. We offer our software code, open APIs, and processed data sets for integration and reuse, and provide the application as a service at http://neuronbridge.janelia.org .

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.

Asymmetric neurons are necessary for olfactory learning in the Drosophila brain

Animals have complementary parallel memory systems that process signals from various sensory modalities. In the brain of the fruit fly Drosophila melanogaster, mushroom body (MB) circuitry is the primary associative neuropil, critical for all stages of olfactory memory. Here, our findings suggest that active signaling from specific asymmetric body (AB) neurons is also crucial for this process. These AB neurons respond to odors and electric shock separately and exhibit timing-sensitive neuronal activity in response to paired stimulation while leaving a decreased memory trace during retrieval. Our experiments also show that rutabaga-encoded adenylate cyclase, which mediates coincidence detection, is required for learning and short-term memory in both AB and MB. We observed additive effects when manipulating rutabaga co-expression in both structures. Together, these results implicate the AB in playing a critical role in associative olfactory learning and short-term memory.

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.

Orai-mediated calcium entry determines activity of central dopaminergic neurons by regulation of gene expression

Maturation and fine-tuning of neural circuits frequently require neuromodulatory signals that set the excitability threshold, neuronal connectivity, and synaptic strength. Here, we present a mechanistic study of how neuromodulator-stimulated intracellular Ca2+ signals, through the store-operated Ca2+ channel Orai, regulate intrinsic neuronal properties by control of developmental gene expression in flight-promoting central dopaminergic neurons (fpDANs). The fpDANs receive cholinergic inputs for release of dopamine at a central brain tripartite synapse that sustains flight (Sharma and Hasan, 2020). Cholinergic inputs act on the muscarinic acetylcholine receptor to stimulate intracellular Ca2+ release through the endoplasmic reticulum (ER) localised inositol 1,4,5-trisphosphate receptor followed by ER-store depletion and Orai-mediated store-operated Ca2+ entry (SOCE). Analysis of gene expression in fpDANs followed by genetic, cellular, and molecular studies identified Orai-mediated Ca2+ entry as a key regulator of excitability in fpDANs during circuit maturation. SOCE activates the transcription factor trithorax-like (Trl), which in turn drives expression of a set of genes, including Set2, that encodes a histone 3 lysine 36 methyltransferase (H3K36me3). Set2 function establishes a positive feedback loop, essential for receiving neuromodulatory cholinergic inputs and sustaining SOCE. Chromatin-modifying activity of Set2 changes the epigenetic status of fpDANs and drives expression of key ion channel and signalling genes that determine fpDAN activity. Loss of activity reduces the axonal arborisation of fpDANs within the MB lobe and prevents dopamine release required for the maintenance of long flight.

New genetic tools for mushroom body output neurons in Drosophila

How memories of past events influence behavior is a key question in neuroscience. The major associative learning center in Drosophila, the mushroom body (MB), communicates to the rest of the brain through mushroom body output neurons (MBONs). While 21 MBON cell types have their dendrites confined to small compartments of the MB lobes, analysis of EM connectomes revealed the presence of an additional 14 MBON cell types that are atypical in having dendritic input both within the MB lobes and in adjacent brain regions. Genetic reagents for manipulating atypical MBONs and experimental data on their functions have been lacking. In this report we describe new cell-type-specific GAL4 drivers for many MBONs, including the majority of atypical MBONs that extend the collection of MBON driver lines we have previously generated (Aso et al., 2014a; Aso et al., 2016; Aso et al., 2019). Using these genetic reagents, we conducted optogenetic activation screening to examine their ability to drive behaviors and learning. These reagents provide important new tools for the study of complex behaviors in Drosophila.

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.

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 odor-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 develop a system to electrophysiologically monitor both short-term and long-term synaptic plasticity at KC output synapses and demonstrate that they are indeed an exception where activation of the cAMP/protein kinase A pathway induces LTD. Contrary to the prevailing model, our cAMP imaging finds no evidence for synergistic action of dopamine and KC activity on cAMP synthesis. Furthermore, we find that forskolin-induced cAMP increase alone is insufficient for plasticity induction; it additionally requires 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 induces slowly developing LTP, proving antagonistic actions of the two second-messenger pathways predicted by behavioral study. Finally, KC subtype-specific interrogation of synapses reveals 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.

Neural mechanisms of dopamine function in learning and memory in Caenorhabditis elegans

Research into learning and memory over the past decades has revealed key neurotransmitters that regulate these processes, many of which are evolutionarily conserved across diverse species. The monoamine neurotransmitter dopamine is one example of this, with countless studies demonstrating its importance in regulating behavioural plasticity. However, dopaminergic neural networks in the mammalian brain consist of hundreds or thousands of neurons, and thus cannot be studied at the level of single neurons acting within defined neural circuits. The nematode Caenorhabditis elegans (C. elegans) has an experimentally tractable nervous system with a completely characterized synaptic connectome. This makes it an advantageous system to undertake mechanistic studies into how dopamine encodes lasting yet flexible behavioural plasticity in the nervous system. In this review, we synthesize the research to date exploring the importance of dopaminergic signalling in learning, memory formation, and forgetting, focusing on research in C. elegans. We also explore the potential for dopamine-specific fluorescent biosensors in C. elegans to visualize dopaminergic neural circuits during learning and memory formation in real-time. We propose that the use of these sensors in C. elegans, in combination with optogenetic and other light-based approaches, will further illuminate the detailed spatiotemporal requirements for encoding behavioural plasticity in an accessible experimental system. Understanding the key molecules and circuit mechanisms that regulate learning and forgetting in more compact invertebrate nervous systems may reveal new druggable targets for enhancing memory storage and delaying memory loss in bigger brains.

Glia transmit negative valence information during aversive learning in Drosophila

During Drosophila aversive olfactory conditioning, aversive shock information needs to be transmitted to the mushroom bodies (MBs) to associate with odor information. We report that aversive information is transmitted by ensheathing glia (EG) that surround the MBs. Shock induces vesicular exocytosis of glutamate from EG. Blocking exocytosis impairs aversive learning, whereas activation of EG can replace aversive stimuli during conditioning. Glutamate released from EG binds to N-methyl-d-aspartate receptors in the MBs, but because of Mg2+ block, Ca2+ influx occurs only when flies are simultaneously exposed to an odor. Vesicular exocytosis from EG also induces shock-associated dopamine release, which plays a role in preventing formation of inappropriate associations. These results demonstrate that vesicular glutamate released from EG transmits negative valence information required for associative learning.

Combinatory Actions of Co-transmitters in Dopaminergic Systems Modulate Drosophila Olfactory Memories

Dopamine neurons (DANs) are extensively studied in the context of associative learning, in both vertebrates and invertebrates. In the acquisition of male and female Drosophila olfactory memory, the PAM cluster of DANs provides the reward signal, and the PPL1 cluster of DANs sends the punishment signal to the Kenyon cells (KCs) of mushroom bodies, the center for memory formation. However, thermo-genetical activation of the PPL1 DANs after memory acquisition impaired aversive memory, and that of the PAM DANs impaired appetitive memory. We demonstrate that the knockdown of glutamate decarboxylase, which catalyzes glutamate conversion to GABA in PAM DANs, potentiated the appetitive memory. In addition, the knockdown of glutamate transporter in PPL1 DANs potentiated aversive memory, suggesting that GABA and glutamate co-transmitters act in an inhibitory manner in olfactory memory formation. We also found that, in γKCs, the Rdl receptor for GABA and the mGluR DmGluRA mediate the inhibition. Although multiple-spaced training is required to form long-term aversive memory, a single cycle of training was sufficient to develop long-term memory when the glutamate transporter was knocked down, in even a single subset of PPL1 DANs. Our results suggest that the mGluR signaling pathway may set a threshold for memory acquisition to allow the organisms' behaviors to adapt to changing physiological conditions and environments.SIGNIFICANCE STATEMENT In the acquisition of olfactory memory in Drosophila, the PAM cluster of dopamine neurons (DANs) mediates the reward signal, while the PPL1 cluster of DANs conveys the punishment signal to the Kenyon cells of the mushroom bodies, which serve as the center for memory formation. We found that GABA co-transmitters in the PAM DANs and glutamate co-transmitters in the PPL1 DANs inhibit olfactory memory formation. Our findings demonstrate that long-term memory acquisition, which typically necessitates multiple-spaced training sessions to establish aversive memory, can be triggered with a single training cycle in cases where the glutamate co-transmission is inhibited, even within a single subset of PPL1 DANs, suggesting that the glutamate co-transmission may modulate the threshold for memory acquisition.

Evolution of the neuronal substrate for kin recognition in social Hymenoptera

In evolutionary terms, life is about reproduction. Yet, in some species, individuals forgo their own reproduction to support the reproductive efforts of others. Social insect colonies for example, can contain up to a million workers that actively cooperate in tasks such as foraging, brood care and nest defence, but do not produce offspring. In such societies the division of labour is pronounced, and reproduction is restricted to just one or a few individuals, most notably the queen(s). This extreme eusocial organisation exists in only a few mammals, crustaceans and insects, but strikingly, it evolved independently up to nine times in the order Hymenoptera (including ants, bees and wasps). Transitions from a solitary lifestyle to an organised society can occur through natural selection when helpers obtain a fitness benefit from cooperating with kin, owing to the indirect transmission of genes through siblings. However, this process, called kin selection, is vulnerable to parasitism and opportunistic behaviours from unrelated individuals. An ability to distinguish kin from non-kin, and to respond accordingly, could therefore critically facilitate the evolution of eusociality and the maintenance of non-reproductive workers. The question of how the hymenopteran brain has adapted to support this function is therefore a fundamental issue in evolutionary neuroethology. Early neuroanatomical investigations proposed that social Hymenoptera have expanded integrative brain areas due to selection for increased cognitive capabilities in the context of processing social information. Later studies challenged this assumption and instead pointed to an intimate link between higher social organisation and the existence of developed sensory structures involved in recognition and communication. In particular, chemical signalling of social identity, known to be mediated through cuticular hydrocarbons (CHCs), may have evolved hand in hand with a specialised chemosensory system in Hymenoptera. Here, we compile the current knowledge on this recognition system, from emitted identity signals, to the molecular and neuronal basis of chemical detection, with particular emphasis on its evolutionary history. Finally, we ask whether the evolution of social behaviour in Hymenoptera could have driven the expansion of their complex olfactory system, or whether the early origin and conservation of an olfactory subsystem dedicated to social recognition could explain the abundance of eusocial species in this insect order. Answering this question will require further comparative studies to provide a comprehensive view on lineage-specific adaptations in the olfactory pathway of Hymenoptera.

Rewarding Capacity of Optogenetically Activating a Giant GABAergic Central-Brain Interneuron in Larval Drosophila

Larvae of the fruit fly Drosophila melanogaster are a powerful study case for understanding the neural circuits underlying behavior. Indeed, the numerical simplicity of the larval brain has permitted the reconstruction of its synaptic connectome, and genetic tools for manipulating single, identified neurons allow neural circuit function to be investigated with relative ease and precision. We focus on one of the most complex neurons in the brain of the larva (of either sex), the GABAergic anterior paired lateral neuron (APL). Using behavioral and connectomic analyses, optogenetics, Ca2+ imaging, and pharmacology, we study how APL affects associative olfactory memory. We first provide a detailed account of the structure, regional polarity, connectivity, and metamorphic development of APL, and further confirm that optogenetic activation of APL has an inhibiting effect on its main targets, the mushroom body Kenyon cells. All these findings are consistent with the previously identified function of APL in the sparsening of sensory representations. To our surprise, however, we found that optogenetically activating APL can also have a strong rewarding effect. Specifically, APL activation together with odor presentation establishes an odor-specific, appetitive, associative short-term memory, whereas naive olfactory behavior remains unaffected. An acute, systemic inhibition of dopamine synthesis as well as an ablation of the dopaminergic pPAM neurons impair reward learning through APL activation. Our findings provide a study case of complex circuit function in a numerically simple brain, and suggest a previously unrecognized capacity of central-brain GABAergic neurons to engage in dopaminergic reinforcement.SIGNIFICANCE STATEMENT The single, identified giant anterior paired lateral (APL) neuron is one of the most complex neurons in the insect brain. It is GABAergic and contributes to the sparsening of neuronal activity in the mushroom body, the memory center of insects. We provide the most detailed account yet of the structure of APL in larval Drosophila as a neurogenetically accessible study case. We further reveal that, contrary to expectations, the experimental activation of APL can exert a rewarding effect, likely via dopaminergic reward pathways. The present study both provides an example of unexpected circuit complexity in a numerically simple brain, and reports an unexpected effect of activity in central-brain GABAergic circuits.

Dopaminergic neurons dynamically update sensory values during olfactory maneuver

Dopaminergic neurons (DANs) drive associative learning to update the value of sensory cues, but their contribution to the assessment of sensory values outside the context of association remains largely unexplored. Here, we show in Drosophila that DANs in the mushroom body encode the innate value of odors and constantly update the current value by inducing plasticity during olfactory maneuver. Our connectome-based network model linking all the way from the olfactory neurons to DANs reproduces the characteristics of DAN responses, proposing a concrete circuit mechanism for computation. Downstream of DANs, odors alone induce value- and dopamine-dependent changes in the activity of mushroom body output neurons, which store the current value of odors. Consistent with this neural plasticity, specific sets of DANs bidirectionally modulate flies' steering in a virtual olfactory environment. Thus, the DAN circuit known for discrete, associative learning also continuously updates odor values in a nonassociative manner.

Brief Change in Dopamine Activity during Consolidation Impairs Long-Term Memory via Sleep Disruption

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, we show that brief activation of protocerebral anterior medial DANs (PAM-DANs) or inhibition of a pair of dorsal posterior medial (DPM) neurons during the first few hours of memory consolidation impairs 24 h LTM. Interestingly, sleep deprivation elevates the neural activity of PAM-DANs and DPM neurons, and brief thermos-activation of PAM-DANs or inactivation of DPM neurons results in sleep loss and fragmentation. Pharmacological rescue of sleep after this 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 with DPM neurons mainly via Dop1R1 receptor to inhibit DPM. Our data suggest that the post-training activity of PAM(-α1)-DPM microcircuit, especially during memory consolidation, plays an essential role in maintaining the sleep necessary for LTM consolidation, providing a new cellular and circuit basis for the complex relationship between sleep and memory.

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

The arthropod mushroom body is well-studied as an expansion layer that represents olfactory stimuli and links them to contingent events. However, 8% of mushroom body Kenyon cells in Drosophila melanogaster receive predominantly visual input, and their tuning and function are poorly understood. Here, we use the FlyWire adult whole-brain connectome to identify inputs to visual Kenyon cells. The types of visual neurons we identify are similar across hemispheres and connectomes with certain inputs highly overrepresented. Many visual projection neurons presynaptic to Kenyon cells receive input from large swathes of visual space, while local visual interneurons, providing smaller fractions of input, receive more spatially restricted signals that may be tuned to specific features of the visual scene. Like olfactory Kenyon cells, visual Kenyon cells receive sparse inputs from different combinations of visual channels, including inputs from multiple optic lobe neuropils. The sets of inputs to individual visual Kenyon cells are consistent with random sampling of available inputs. These connectivity patterns suggest that visual coding in the mushroom body, like olfactory coding, is sparse, distributed, and combinatorial. However, the expansion coding properties appear different, with a specific repertoire of visual inputs projecting onto a relatively small number of visual Kenyon cells.

Exploring the proteins and metabolites associated with male antennae responses to female exposure of Antheraea pernyi (Lepidoptera: Saturniidae) moths

Detection of sex pheromones of insects relies on the antennae. The female pheromone signal transmission in the male antennae ultimately initiates the courtship and mating behaviors of males. To investigate the proteins and metabolites involved in this neural transduction, integrative proteomics and metabolomics analysis including tandem mass tag (TMT) proteomic quantification and liquid chromatography tandem mass spectrometry (LC/MS)-based metabolomics was adopted for comparing proteomic and metabolic changes between the antennae of male moths following stimulation by females and the non-stimulated males of Antheraea pernyi (Guérin-Méneville, Lepidoptera: Saturniidae) in this study. A total of 92 differentially expressed proteins (DEPs) containing 52 upregulated and 40 downregulated proteins and 545 differentially expressed metabolites (DEMs) including 218 upregulated and 327 downregulated metabolites were identified from the antennae of female-stimulated male moths based on the proteome and metabolome data, respectively. Bioinformatics analysis was performed for the 45 DEPs and 160 DEMs, including Gene Ontology (GO), Clusters of Orthologous Groups (COG), and Kyoto Encylopaedia of Genes and Genomes (KEGG) enrichment analysis and Human Metabolome Database (HMDB) annotation. A number of DEPs and DEMs related to neural transmission of female pheromone signals in the male antennae of A. pernyi were screened, including tyrosine hydroxylase, cryptochrome-1, tachykinin, arylalkylamine N-acetyltransferase, cadherin-23, glutathione S-transferase delta 3, tyramine, tryptamine, n-oleoyl dopamine, n-stearoyl dopamine, and n-stearoyl tyrosine. The altered expression levels of those proteins or metabolites were speculated involved in regulating the neuron activity for enhanced transmission of neural impulses and continuous perception, reception, and transduction of female pheromone signals. Our findings yielded novel insights into the potential mechanisms in the antennae of male A. pernyi responding to female attraction.

Reducing Catastrophic Forgetting With Associative Learning: A Lesson From Fruit Flies

Catastrophic forgetting remains an outstanding challenge in continual learning. Recently, methods inspired by the brain, such as continual representation learning and memory replay, have been used to combat catastrophic forgetting. Associative learning (retaining associations between inputs and outputs, even after good representations are learned) plays an important function in the brain; however, its role in continual learning has not been carefully studied. Here, we identified a two-layer neural circuit in the fruit fly olfactory system that performs continual associative learning between odors and their associated valences. In the first layer, inputs (odors) are encoded using sparse, high-dimensional representations, which reduces memory interference by activating nonoverlapping populations of neurons for different odors. In the second layer, only the synapses between odor-activated neurons and the odor's associated output neuron are modified during learning; the rest of the weights are frozen to prevent unrelated memories from being overwritten. We prove theoretically that these two perceptron-like layers help reduce catastrophic forgetting compared to the original perceptron algorithm, under continual learning. We then show empirically on benchmark data sets that this simple and lightweight architecture outperforms other popular neural-inspired algorithms when also using a two-layer feedforward architecture. Overall, fruit flies evolved an efficient continual associative learning algorithm, and circuit mechanisms from neuroscience can be translated to improve machine computation.

Effects of stochastic coding on olfactory discrimination in flies and mice

Sparse coding can improve discrimination of sensory stimuli by reducing overlap between their representations. Two factors, however, can offset sparse coding's benefits: similar sensory stimuli have significant overlap and responses vary across trials. To elucidate the effects of these 2 factors, we analyzed odor responses in the fly and mouse olfactory regions implicated in learning and discrimination-the mushroom body (MB) and the piriform cortex (PCx). We found that neuronal responses fall along a continuum from extremely reliable across trials to extremely variable or stochastic. Computationally, we show that the observed variability arises from noise within central circuits rather than sensory noise. We propose this coding scheme to be advantageous for coarse- and fine-odor discrimination. More reliable cells enable quick discrimination between dissimilar odors. For similar odors, however, these cells overlap and do not provide distinguishing information. By contrast, more unreliable cells are decorrelated for similar odors, providing distinguishing information, though these benefits only accrue with extended training with more trials. Overall, we have uncovered a conserved, stochastic coding scheme in vertebrates and invertebrates, and we identify a candidate mechanism, based on variability in a winner-take-all (WTA) inhibitory circuit, that improves discrimination with training.

Dopamine-Dependent Plasticity Is Heterogeneously Expressed by Presynaptic Calcium Activity across Individual Boutons of the Drosophila Mushroom Body

The Drosophila mushroom body (MB) is an important model system for studying the synaptic mechanisms of associative learning. In this system, coincidence of odor-evoked calcium influx and dopaminergic input in the presynaptic terminals of Kenyon cells (KCs), the principal neurons of the MB, triggers long-term depression (LTD), which plays a critical role in olfactory learning. However, it is controversial whether such synaptic plasticity is accompanied by a corresponding decrease in odor-evoked calcium activity in the KC presynaptic terminals. Here, we address this question by inducing LTD by pairing odor presentation with optogenetic activation of dopaminergic neurons (DANs). This allows us to rigorously compare the changes at the presynaptic and postsynaptic sites in the same conditions. By imaging presynaptic acetylcholine release in the condition where LTD is reliably observed in the postsynaptic calcium signals, we show that neurotransmitter release from KCs is depressed selectively in the MB compartments innervated by activated DANs, demonstrating the presynaptic nature of LTD. However, total odor-evoked calcium activity of the KC axon bundles does not show concurrent depression. We further conduct calcium imaging in individual presynaptic boutons and uncover the highly heterogeneous nature of calcium plasticity. Namely, only a subset of boutons, which are strongly activated by associated odors, undergo calcium activity depression, while weakly responding boutons show potentiation. Thus, our results suggest an unexpected nonlinear relationship between presynaptic calcium influx and the results of plasticity, challenging the simple view of cooperative actions of presynaptic calcium and dopaminergic input.

Optogenetic induction of appetitive and aversive taste memories in Drosophila

Tastes typically evoke innate behavioral responses that can be broadly categorized as acceptance or rejection. However, research in Drosophila melanogaster indicates that taste responses also exhibit plasticity through experience-dependent changes in mushroom body circuits. In this study, we develop a novel taste learning paradigm using closed-loop optogenetics. We find that appetitive and aversive taste memories can be formed by pairing gustatory stimuli with optogenetic activation of sensory neurons or dopaminergic neurons encoding reward or punishment. As with olfactory memories, distinct dopaminergic subpopulations drive the parallel formation of short- and long-term appetitive memories. Long-term memories are protein synthesis-dependent and have energetic requirements that are satisfied by a variety of caloric food sources or by direct stimulation of MB-MP1 dopaminergic neurons. Our paradigm affords new opportunities to probe plasticity mechanisms within the taste system and understand the extent to which taste responses depend on experience.

Reward expectations direct learning and drive operant matching in Drosophila

Foraging animals must use decision-making strategies that dynamically adapt to the changing availability of rewards in the environment. A wide diversity of animals do this by distributing their choices in proportion to the rewards received from each option, Herrnstein's operant matching law. Theoretical work suggests an elegant mechanistic explanation for this ubiquitous behavior, as operant matching follows automatically from simple synaptic plasticity rules acting within behaviorally relevant neural circuits. However, no past work has mapped operant matching onto plasticity mechanisms in the brain, leaving the biological relevance of the theory unclear. Here, we discovered operant matching in Drosophila and showed that it requires synaptic plasticity that acts in the mushroom body and incorporates the expectation of reward. We began by developing a dynamic foraging paradigm to measure choices from individual flies as they learn to associate odor cues with probabilistic rewards. We then built a model of the fly mushroom body to explain each fly's sequential choice behavior using a family of biologically realistic synaptic plasticity rules. As predicted by past theoretical work, we found that synaptic plasticity rules could explain fly matching behavior by incorporating stimulus expectations, reward expectations, or both. However, by optogenetically bypassing the representation of reward expectation, we abolished matching behavior and showed that the plasticity rule must specifically incorporate reward expectations. Altogether, these results reveal the first synapse-level mechanisms of operant matching and provide compelling evidence for the role of reward expectation signals in the fly brain.

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.

Olfactory navigation in arthropods

Using odors to find food and mates is one of the most ancient and highly conserved behaviors. Arthropods from flies to moths to crabs use broadly similar strategies to navigate toward odor sources-such as integrating flow information with odor information, comparing odor concentration across sensors, and integrating odor information over time. Because arthropods share many homologous brain structures-antennal lobes for processing olfactory information, mechanosensors for processing flow, mushroom bodies (or hemi-ellipsoid bodies) for associative learning, and central complexes for navigation, it is likely that these closely related behaviors are mediated by conserved neural circuits. However, differences in the types of odors they seek, the physics of odor dispersal, and the physics of locomotion in water, air, and on substrates mean that these circuits must have adapted to generate a wide diversity of odor-seeking behaviors. In this review, we discuss common strategies and specializations observed in olfactory navigation behavior across arthropods, and review our current knowledge about the neural circuits subserving this behavior. We propose that a comparative study of arthropod nervous systems may provide insight into how a set of basic circuit structures has diversified to generate behavior adapted to different environments.

Local 5-HT signaling bi-directionally regulates the coincidence time window for associative learning

The coincidence between conditioned stimulus (CS) and unconditioned stimulus (US) is essential for associative learning; however, the mechanism regulating the duration of this temporal window remains unclear. Here, we found that serotonin (5-HT) bi-directionally regulates the coincidence time window of olfactory learning in Drosophila and affects synaptic plasticity of Kenyon cells (KCs) in the mushroom body (MB). Utilizing GPCR-activation-based (GRAB) neurotransmitter sensors, we found that KC-released acetylcholine (ACh) activates a serotonergic dorsal paired medial (DPM) neuron, which in turn provides inhibitory feedback to KCs. Physiological stimuli induce spatially heterogeneous 5-HT signals, which proportionally gate the intrinsic coincidence time windows of different MB compartments. Artificially reducing or increasing the DPM neuron-released 5-HT shortens or prolongs the coincidence window, respectively. In a sequential trace conditioning paradigm, this serotonergic neuromodulation helps to bridge the CS-US temporal gap. Altogether, we report a model circuitry for perceiving the temporal coincidence and determining the causal relationship between environmental events.

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.

Spontaneous recovery of reward memory through active forgetting of extinction memory

Learned behavior can be suppressed by the extinction procedure. Such extinguished memory often returns spontaneously over time, making it difficult to treat diseases such as addiction. However, the biological mechanisms underlying such spontaneous recovery remain unclear. Here, we report that the extinguished reward memory in Drosophila recovers spontaneously because extinction training forms an aversive memory that can be actively forgotten via the Rac1/Dia pathway. Manipulating Rac1 activity does not affect sugar-reward memory and its immediate extinction effect but bidirectionally regulates spontaneous recovery-the decay process of extinction. Experiments using thermogenetic inhibition and functional imaging support that such extinction appears to be coded as an aversive experience. Genetic and pharmacological inhibition of formin Dia, a downstream effector of Rac1, specifically prevents spontaneous recovery after extinction in both behavioral performance and corresponding physiological traces. Together, our data suggest that spontaneous recovery is caused by active forgetting of the opposing extinction memory.

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.

Selective integration of diverse taste inputs within a single taste modality

A fundamental question in sensory processing is how different channels of sensory input are processed to regulate behavior. Different input channels may converge onto common downstream pathways to drive the same behaviors, or they may activate separate pathways to regulate distinct behaviors. We investigated this question in the Drosophila bitter taste system, which contains diverse bitter-sensing cells residing in different taste organs. First, we optogenetically activated subsets of bitter neurons within each organ. These subsets elicited broad and highly overlapping behavioral effects, suggesting that they converge onto common downstream pathways, but we also observed behavioral differences that argue for biased convergence. Consistent with these results, transsynaptic tracing revealed that bitter neurons in different organs connect to overlapping downstream pathways with biased connectivity. We investigated taste processing in one type of downstream bitter neuron that projects to the higher brain. These neurons integrate input from multiple organs and regulate specific taste-related behaviors. We then traced downstream circuits, providing the first glimpse into taste processing in the higher brain. Together, these results reveal that different bitter inputs are selectively integrated early in the circuit, enabling the pooling of information, while the circuit then diverges into multiple pathways that may have different roles.

Food memory circuits regulate eating and energy balance

In mammals, learning circuits play an essential role in energy balance by creating associations between sensory cues and the rewarding qualities of food. This process is altered by diet-induced obesity, but the causes and mechanisms are poorly understood. Here, we exploited the relative simplicity and wealth of knowledge about the D. melanogaster reinforcement learning network, the mushroom body, in order to study the relationship between the dietary environment, dopamine-induced plasticity, and food associations. We show flies that are fed a high-sugar diet cannot make associations between sensory cues and the rewarding properties of sugar. This deficit was caused by diet exposure, not fat accumulation, and specifically by lower dopamine-induced plasticity onto mushroom body output neurons (MBONs) during learning. Importantly, food memories dynamically tune the output of MBONs during eating, which instead remains fixed in sugar-diet animals. Interestingly, manipulating the activity of MBONs influenced eating and fat mass, depending on the diet. Altogether, this work advances our fundamental understanding of the mechanisms, causes, and consequences of the dietary environment on reinforcement learning and ingestive behavior.

Sleep benefits different stages of memory in Drosophila

Understanding the physiological mechanisms that modulate memory acquisition and consolidation remains among the most ambitious questions in neuroscience. Massive efforts have been dedicated to deciphering how experience affects behavior, and how different physiological and sensory phenomena modulate memory. Our ability to encode, consolidate and retrieve memories depends on internal drives, and sleep stands out among the physiological processes that affect memory: one of the most relatable benefits of sleep is the aiding of memory that occurs in order to both prepare the brain to learn new information, and after a learning task, to consolidate those new memories. Drosophila lends itself to the study of the interactions between memory and sleep. The fruit fly provides incomparable genetic resources, a mapped connectome, and an existing framework of knowledge on the molecular, cellular, and circuit mechanisms of memory and sleep, making the fruit fly a remarkable model to decipher the sophisticated regulation of learning and memory by the quantity and quality of sleep. Research in Drosophila has stablished not only that sleep facilitates learning in wild-type and memory-impaired animals, but that sleep deprivation interferes with the acquisition of new memories. In addition, it is well-accepted that sleep is paramount in memory consolidation processes. Finally, studies in Drosophila have shown that that learning itself can promote sleep drive. Nevertheless, the molecular and network mechanisms underlying this intertwined relationship are still evasive. Recent remarkable work has shed light on the neural substrates that mediate sleep-dependent memory consolidation. In a similar way, the mechanistic insights of the neural switch control between sleep-dependent and sleep-independent consolidation strategies were recently described. This review will discuss the regulation of memory by sleep in Drosophila, focusing on the most recent advances in the field and pointing out questions awaiting to be investigated.