A Map of Olfactory Representation in the Drosophila Mushroom Body

LYNSU: automated 3D neuropil segmentation of fluorescent images for Drosophila brains

The brain atlas, which provides information about the distribution of genes, proteins, neurons, or anatomical regions, plays a crucial role in contemporary neuroscience research. To analyze the spatial distribution of those substances based on images from different brain samples, we often need to warp and register individual brain images to a standard brain template. However, the process of warping and registration may lead to spatial errors, thereby severely reducing the accuracy of the analysis. To address this issue, we develop an automated method for segmenting neuropils in the Drosophila brain for fluorescence images from the FlyCircuit database. This technique allows future brain atlas studies to be conducted accurately at the individual level without warping and aligning to a standard brain template. Our method, LYNSU (Locating by YOLO and Segmenting by U-Net), consists of two stages. In the first stage, we use the YOLOv7 model to quickly locate neuropils and rapidly extract small-scale 3D images as input for the second stage model. This stage achieves a 99.4% accuracy rate in neuropil localization. In the second stage, we employ the 3D U-Net model to segment neuropils. LYNSU can achieve high accuracy in segmentation using a small training set consisting of images from merely 16 brains. We demonstrate LYNSU on six distinct neuropils or structures, achieving a high segmentation accuracy comparable to professional manual annotations with a 3D Intersection-over-Union (IoU) reaching up to 0.869. Our method takes only about 7 s to segment a neuropil while achieving a similar level of performance as the human annotators. To demonstrate a use case of LYNSU, we applied it to all female Drosophila brains from the FlyCircuit database to investigate the asymmetry of the mushroom bodies (MBs), the learning center of fruit flies. We used LYNSU to segment bilateral MBs and compare the volumes between left and right for each individual. Notably, of 8,703 valid brain samples, 10.14% showed bilateral volume differences that exceeded 10%. The study demonstrated the potential of the proposed method in high-throughput anatomical analysis and connectomics construction of the Drosophila brain.

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.

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.

Mate copying requires the coincidence detector Rutabaga in the mushroom bodies of Drosophila melanogaster

Mate choice constitutes a major fitness-affecting decision often involving social learning leading to copying the preference of other individuals (i.e., mate copying). While mate copying exists in many taxa, its underlying neurobiological mechanisms remain virtually unknown. Here, we show in Drosophila melanogaster that the rutabaga gene is necessary to support mate copying. Rutabaga encodes an adenylyl cyclase (AC-Rut+) acting as a coincidence detector in associative learning. Since the brain localization requirements for AC-Rut+ expression differ in classical and operant learning, we determine the functional localization of AC-Rut+ for mate copying by artificially rescuing the expression of AC-Rut+ in neural subsets of a rutabaga mutant. We found that AC-Rut+ has to be expressed in the mushroom bodies' Kenyon cells (KCs), specifically in the γ-KCs subset. Thus, this form of discriminative social learning requires the same KCs as non-social Pavlovian learning, suggesting that pathways of social and asocial learning overlap significantly.

A subset of cholinergic mushroom body neurons blocks long-term memory formation in Drosophila

Long-term memory (LTM) requires learning-induced synthesis of new proteins allocated to specific neurons and synapses in a neural circuit. Not all learned information, however, becomes permanent memory. How the brain gates relevant information into LTM remains unclear. In Drosophila adults, weak learning after a single training session in an olfactory aversive task typically does not induce protein-synthesis-dependent LTM. Instead, strong learning after multiple spaced training sessions is required. Here, we report that pre-synaptic active-zone protein synthesis and cholinergic signaling from the early α/β subset of mushroom body (MB) neurons produce a downstream inhibitory effect on LTM formation. When we eliminated inhibitory signaling from these neurons, weak learning was then sufficient to form LTM. This bidirectional circuit mechanism modulates the transition between distinct memory phase functions in different subpopulations of MB neurons in the olfactory memory circuit.

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.

Experience-dependent plasticity in the olfactory system of Drosophila melanogaster and other insects

It is long known that the nervous system of vertebrates can be shaped by internal and external factors. On the other hand, the nervous system of insects was long assumed to be stereotypic, although evidence for plasticity effects accumulated for several decades. To cover the topic comprehensively, this review recapitulates the establishment of the term "plasticity" in neuroscience and introduces its original meaning. We describe the basic composition of the insect olfactory system using Drosophila melanogaster as a representative example and outline experience-dependent plasticity effects observed in this part of the brain in a variety of insects, including hymenopterans, lepidopterans, locusts, and flies. In particular, we highlight recent advances in the study of experience-dependent plasticity effects in the olfactory system of D. melanogaster, as it is the most accessible olfactory system of all insect species due to the genetic tools available. The partly contradictory results demonstrate that morphological, physiological and behavioral changes in response to long-term olfactory stimulation are more complex than previously thought. Different molecular mechanisms leading to these changes were unveiled in the past and are likely responsible for this complexity. We discuss common problems in the study of experience-dependent plasticity, ways to overcome them, and future directions in this area of research. In addition, we critically examine the transferability of laboratory data to natural systems to address the topic as holistically as possible. As a mechanism that allows organisms to adapt to new environmental conditions, experience-dependent plasticity contributes to an animal's resilience and is therefore a crucial topic for future research, especially in an era of rapid environmental changes.

Drosophila olfaction: past, present and future

Among the many wonders of nature, the sense of smell of the fly Drosophila melanogaster might seem, at first glance, of esoteric interest. Nevertheless, for over a century, the 'nose' of this insect has been an extraordinary system to explore questions in animal behaviour, ecology and evolution, neuroscience, physiology and molecular genetics. The insights gained are relevant for our understanding of the sensory biology of vertebrates, including humans, and other insect species, encompassing those detrimental to human health. Here, I present an overview of our current knowledge of D. melanogaster olfaction, from molecules to behaviours, with an emphasis on the historical motivations of studies and illustration of how technical innovations have enabled advances. I also highlight some of the pressing and long-term questions.

Structured sampling of olfactory input by the fly mushroom body

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

Shedding Light on Inter-Individual Variability of Olfactory Circuits in Drosophila

Inter-individual differences in behavioral responses, anatomy or functional properties of neuronal populations of animals having the same genotype were for a long time disregarded. The majority of behavioral studies were conducted at a group level, and usually the mean behavior of all individuals was considered. Similarly, in neurophysiological studies, data were pooled and normalized from several individuals. This approach is mostly suited to map and characterize stereotyped neuronal properties between individuals, but lacks the ability to depict inter-individual variability regarding neuronal wiring or physiological characteristics. Recent studies have shown that behavioral biases and preferences to olfactory stimuli can vary significantly among individuals of the same genotype. The origin and the benefit of these diverse "personalities" is still unclear and needs to be further investigated. A perspective taken into account the inter-individual differences is needed to explore the cellular mechanisms underlying this phenomenon. This review focuses on olfaction in the vinegar fly Drosophila melanogaster and summarizes previous and recent studies on odor-guided behavior and the underlying olfactory circuits in the light of inter-individual variability. We address the morphological and physiological variabilities present at each layer of the olfactory circuitry and attempt to link them to individual olfactory behavior. Additionally, we discuss the factors that might influence individuality with regard to olfactory perception.

The anterior paired lateral neuron normalizes odour-evoked activity in the Drosophila mushroom body calyx

To identify and memorize discrete but similar environmental inputs, the brain needs to distinguish between subtle differences of activity patterns in defined neuronal populations. The Kenyon cells (KCs) of the Drosophila adult mushroom body (MB) respond sparsely to complex olfactory input, a property that is thought to support stimuli discrimination in the MB. To understand how this property emerges, we investigated the role of the inhibitory anterior paired lateral (APL) neuron in the input circuit of the MB, the calyx. Within the calyx, presynaptic boutons of projection neurons (PNs) form large synaptic microglomeruli (MGs) with dendrites of postsynaptic KCs. Combining electron microscopy (EM) data analysis and in vivo calcium imaging, we show that APL, via inhibitory and reciprocal synapses targeting both PN boutons and KC dendrites, normalizes odour-evoked representations in MGs of the calyx. APL response scales with the PN input strength and is regionalized around PN input distribution. Our data indicate that the formation of a sparse code by the KCs requires APL-driven normalization of their MG postsynaptic responses. This work provides experimental insights on how inhibition shapes sensory information representation in a higher brain centre, thereby supporting stimuli discrimination and allowing for efficient associative memory formation.

Serotonin Signals Modulate Mushroom Body Output Neurons for Sustaining Water-Reward Long-Term Memory in Drosophila

Memory consolidation is a time-dependent process through which an unstable learned experience is transformed into a stable long-term memory; however, the circuit and molecular mechanisms underlying this process are poorly understood. The Drosophila mushroom body (MB) is a huge brain neuropil that plays a crucial role in olfactory memory. The MB neurons can be generally classified into three subsets: γ, αβ, and α′β′. Here, we report that water-reward long-term memory (wLTM) consolidation requires activity from α′β′-related mushroom body output neurons (MBONs) in a specific time window. wLTM consolidation requires neurotransmission in MBON-γ3β′1 during the 0–2 h period after training, and neurotransmission in MBON-α′2 is required during the 2–4 h period after training. Moreover, neurotransmission in MBON-α′1α′3 is required during the 0–4 h period after training. Intriguingly, blocking neurotransmission during consolidation or inhibiting serotonin biosynthesis in serotoninergic dorsal paired medial (DPM) neurons also disrupted the wLTM, suggesting that wLTM consolidation requires serotonin signals from DPM neurons. The GFP Reconstitution Across Synaptic Partners (GRASP) data showed the connectivity between DPM neurons and MBON-γ3β′1, MBON-α′2, and MBON-α′1α′3, and RNAi-mediated silencing of serotonin receptors in MBON-γ3β′1, MBON-α′2, or MBON-α′1α′3 disrupted wLTM. Taken together, our results suggest that serotonin released from DPM neurons modulates neuronal activity in MBON-γ3β′1, MBON-α′2, and MBON-α′1α′3 at specific time windows, which is critical for the consolidation of wLTM in Drosophila.

Non-synaptic interactions between olfactory receptor neurons, a possible key feature of odor processing in flies

When flies explore their environment, they encounter odors in complex, highly intermittent plumes. To navigate a plume and, for example, find food, they must solve several challenges, including reliably identifying mixtures of odorants and their intensities, and discriminating odorant mixtures emanating from a single source from odorants emitted from separate sources and just mixing in the air. Lateral inhibition in the antennal lobe is commonly understood to help solving these challenges. With a computational model of the Drosophila olfactory system, we analyze the utility of an alternative mechanism for solving them: Non-synaptic ("ephaptic") interactions (NSIs) between olfactory receptor neurons that are stereotypically co-housed in the same sensilla. We find that NSIs improve mixture ratio detection and plume structure sensing and do so more efficiently than the traditionally considered mechanism of lateral inhibition in the antennal lobe. The best performance is achieved when both mechanisms work in synergy. However, we also found that NSIs decrease the dynamic range of co-housed ORNs, especially when they have similar sensitivity to an odorant. These results shed light, from a functional perspective, on the role of NSIs, which are normally avoided between neurons, for instance by myelination.

Tissue Optical Clearing for Biomedical Imaging: From In Vitro to In Vivo

Tissue optical clearing technique provides a prospective solution for the application of advanced optical methods in life sciences. This chapter firstly gives a brief introduction to mechanisms of tissue optical clearing techniques, from the physical mechanism to chemical mechanism, which is the most important foundation to develop tissue optical clearing methods. During the past years, in vitro and in vivo tissue optical clearing methods were developed. In vitro tissue optical clearing techniques, including the solvent-based clearing methods and the hydrophilic reagents-based clearing methods, combined with labeling technique and advanced microscopy, can be applied to image 3D microstructure of tissue blocks or whole organs such as brain and spinal cord with high resolution. In vivo skin or skull optical clearing, promise various optical imaging techniques to detect cutaneous or cortical cell and vascular structure and function without surgical window.

Olfactory encoding within the insect antennal lobe: The emergence and role of higher order temporal correlations in the dynamics of antennal lobe spiking activity

In this review, we focus on the antennal lobe (AL) of three insect species - the fruit fly, sphinx moth, and locust. We first review the experimentally elucidated anatomy and physiology of the early olfactory system of each species; empirical studies of AL activity, however, often focus on assessing firing rates (averaged over time scales of about 100 ms), and hence the AL odor code is often analyzed in terms of a temporally evolving vector of firing rates. However, such a perspective necessarily misses the possibility of higher order temporal correlations in spiking activity within a single cell and across multiple cells over shorter time scales (of about 10 ms). Hence, we then review our prior theoretical work, where we constructed biophysically detailed, species-specific AL models within the fly, moth, and locust, finding that in each case higher order temporal correlations in spiking naturally emerge from model dynamics (i.e., without a prioriincorporation of elements designed to produce correlated activity). We therefore use our theoretical work to argue the perspective that temporal correlations in spiking over short time scales, which have received little experimental attention to-date, may provide valuable coding dimensions (complementing the coding dimensions provided by the vector of firing rates) that nature has exploited in the encoding of odors within the AL. We further argue that, if the AL does indeed utilize temporally correlated activity to represent odor information, such an odor code could be naturally and easily deciphered within the Mushroom Body.

Physical and chemical mechanisms of tissue optical clearing

Advanced optical methods combined with various probes pave the way toward molecular imaging within living cells. However, major challenges are associated with the need to enhance the imaging resolution even further to the subcellular level for the imaging of larger tissues, as well as for in vivo studies. High scattering and absorption of opaque tissues limit the penetration of light into deep tissues and thus the optical imaging depth. Tissue optical clearing technique provides an innovative way to perform deep-tissue imaging. Recently, various optical clearing methods have been developed, which provide tissue clearing based on similar physical principles via different chemical approaches. Here, we introduce the mechanisms of the current clearing methods from fundamental physical and chemical perspectives, including the main physical principle, refractive index matching via various chemical approaches, such as dissociation of collagen, delipidation, decalcification, dehydration, and hyperhydration, to reduce scattering, as well as decolorization to reduce absorption.

Circuit reorganization in the Drosophila mushroom body calyx accompanies memory consolidation

The formation and consolidation of memories are complex phenomena involving synaptic plasticity, microcircuit reorganization, and the formation of multiple representations within distinct circuits. To gain insight into the structural aspects of memory consolidation, we focus on the calyx of the Drosophila mushroom body. In this essential center, essential for olfactory learning, second- and third-order neurons connect through large synaptic microglomeruli, which we dissect at the electron microscopy level. Focusing on microglomeruli that respond to a specific odor, we reveal that appetitive long-term memory results in increased numbers of precisely those functional microglomeruli responding to the conditioned odor. Hindering memory consolidation by non-coincident presentation of odor and reward, by blocking protein synthesis, or by including memory mutants suppress these structural changes, revealing their tight correlation with the process of memory consolidation. Thus, olfactory long-term memory is associated with input-specific structural modifications in a high-order center of the fly brain.

Dopaminergic mechanism underlying reward-encoding of punishment omission during reversal learning in Drosophila

Animals form and update learned associations between otherwise neutral sensory cues and aversive outcomes (i.e., punishment) to predict and avoid danger in changing environments. When a cue later occurs without punishment, this unexpected omission of aversive outcome is encoded as reward via activation of reward-encoding dopaminergic neurons. How such activation occurs remains unknown. Using real-time in vivo functional imaging, optogenetics, behavioral analysis and synaptic reconstruction from electron microscopy data, we identify the neural circuit mechanism through which Drosophila reward-encoding dopaminergic neurons are activated when an olfactory cue is unexpectedly no longer paired with electric shock punishment. Reduced activation of punishment-encoding dopaminergic neurons relieves depression of olfactory synaptic inputs to cholinergic neurons. Synaptic excitation by these cholinergic neurons of reward-encoding dopaminergic neurons increases their odor response, thus decreasing aversiveness of the odor. These studies reveal how an excitatory cholinergic relay from punishment- to reward-encoding dopaminergic neurons encodes the absence of punishment as reward, revealing a general circuit motif for updating aversive memories that could be present in mammals.

Adaptive temporal processing of odor stimuli

The olfactory system translates chemical signals into neuronal signals that inform behavioral decisions of the animal. Odors are cues for source identity, but if monitored long enough, they can also be used to localize the source. Odor representations should therefore be robust to changing conditions and flexible in order to drive an appropriate behavior. In this review, we aim at discussing the main computations that allow robust and flexible encoding of odor information in the olfactory neural pathway.

The connectome of the adult Drosophila mushroom body provides insights into function

Making inferences about the computations performed by neuronal circuits from synapse-level connectivity maps is an emerging opportunity in neuroscience. The mushroom body (MB) is well positioned for developing and testing such an approach due to its conserved neuronal architecture, recently completed dense connectome, and extensive prior experimental studies of its roles in learning, memory, and activity regulation. Here, we identify new components of the MB circuit in Drosophila, including extensive visual input and MB output neurons (MBONs) with direct connections to descending neurons. We find unexpected structure in sensory inputs, in the transfer of information about different sensory modalities to MBONs, and in the modulation of that transfer by dopaminergic neurons (DANs). We provide insights into the circuitry used to integrate MB outputs, connectivity between the MB and the central complex and inputs to DANs, including feedback from MBONs. Our results provide a foundation for further theoretical and experimental work.

Availability of food determines the need for sleep in memory consolidation

Sleep remains a major mystery of biology, with little understood about its basic function. One of the most commonly proposed functions for sleep is the consolidation of memory^1–3. However, as conditions like starvation require the organism to be awake and active⁴, the ability to switch to a memory consolidation mechanism that is not contingent on sleep may confer an evolutionary advantage. Here, we identify a novel adaptive circuit-based mechanism that enables Drosophila to form sleep-dependent and sleep-independent memory. Flies fed after appetitive conditioning needed increased sleep for memory consolidation, but flies starved after training did not require sleep to form memories. Memory in fed flies is mediated by the anterior-posterior α’/β’ neurons of the mushroom body (MB), while memory under starvation is mediated by medial α’/β’ neurons. Sleep-dependent and sleep-independent memory rely upon distinct dopaminergic neurons and corresponding MB output neurons. However, sleep and memory are coupled such that mushroom body neurons required for sleep-dependent memory also promote sleep. Flies lacking Neuropeptide F display sleep-dependent memory even when starved, suggesting that circuit selection is determined by hunger. This plasticity in memory circuits enables flies to retain essential information in changing environments.

Idiosyncratic neural coding and neuromodulation of olfactory individuality in Drosophila

Innate behavioral biases and preferences can vary significantly among individuals of the same genotype. Though individuality is a fundamental property of behavior, it is not currently understood how individual differences in brain structure and physiology produce idiosyncratic behaviors. Here we present evidence for idiosyncrasy in olfactory behavior and neural responses in Drosophila We show that individual female Drosophila from a highly inbred laboratory strain exhibit idiosyncratic odor preferences that persist for days. We used in vivo calcium imaging of neural responses to compare projection neuron (second-order neurons that convey odor information from the sensory periphery to the central brain) responses to the same odors across animals. We found that, while odor responses appear grossly stereotyped, upon closer inspection, many individual differences are apparent across antennal lobe (AL) glomeruli (compact microcircuits corresponding to different odor channels). Moreover, we show that neuromodulation, environmental stress in the form of altered nutrition, and activity of certain AL local interneurons affect the magnitude of interfly behavioral variability. Taken together, this work demonstrates that individual Drosophila exhibit idiosyncratic olfactory preferences and idiosyncratic neural responses to odors, and that behavioral idiosyncrasies are subject to neuromodulation and regulation by neurons in the AL.

Flexible neural connectivity under constraints on total connection strength

Neural computation is determined by neurons’ dynamics and circuit connectivity. Uncertain and dynamic environments may require neural hardware to adapt to different computational tasks, each requiring different connectivity configurations. At the same time, connectivity is subject to a variety of constraints, placing limits on the possible computations a given neural circuit can perform. Here we examine the hypothesis that the organization of neural circuitry favors computational flexibility: that it makes many computational solutions available, given physiological constraints. From this hypothesis, we develop models of connectivity degree distributions based on constraints on a neuron’s total synaptic weight. To test these models, we examine reconstructions of the mushroom bodies from the first instar larva and adult Drosophila melanogaster. We perform a Bayesian model comparison for two constraint models and a random wiring null model. Overall, we find that flexibility under a homeostatically fixed total synaptic weight describes Kenyon cell connectivity better than other models, suggesting a principle shaping the apparently random structure of Kenyon cell wiring. Furthermore, we find evidence that larval Kenyon cells are more flexible earlier in development, suggesting a mechanism whereby neural circuits begin as flexible systems that develop into specialized computational circuits.

High-throughput electron microscopic anatomical experiments have begun to yield detailed maps of neural circuit connectivity. Uncovering the principles that govern these circuit structures is a major challenge for systems neuroscience. Healthy neural circuits must be able to perform computational tasks while satisfying physiological constraints. Those constraints can restrict a neuron’s possible connectivity, and thus potentially restrict its computation. Here we examine simple models of constraints on total synaptic weights, and calculate the number of circuit configurations they allow: a simple measure of their computational flexibility. We propose probabilistic models of connectivity that weight the number of synaptic partners according to computational flexibility under a constraint and test them using recent wiring diagrams from a learning center, the mushroom body, in the fly brain. We compare constraints that fix or bound a neuron’s total connection strength to a simple random wiring null model. Of these models, the fixed total connection strength matched the overall connectivity best in mushroom bodies from both larval and adult flies. We also provide evidence suggesting that neural circuits are more flexible in early stages of development and lose this flexibility as they grow towards specialized function.

Non-synaptic interactions between olfactory receptor neurons, a possible key feature of odor processing in flies.. [DOI: 10.1101/2020.07.23.217216]

When flies explore their environment, they encounter odors in complex, highly intermittent plumes. To navigate a plume and, for example, find food, they must solve several challenges, including reliably identifying mixtures of odorants and their intensities, and discriminating odorant mixtures emanating from a single source from odorants emitted from separate sources and just mixing in the air. Lateral inhibition in the antennal lobe is commonly understood to help solving these challenges. With a computational model of the Drosophila olfactory system, we analyze the utility of an alternative mechanism for solving them: Non-synaptic (“ephaptic”) interactions (NSIs) between olfactory receptor neurons that are stereotypically co-housed in the same sensilla.

We found that NSIs improve mixture ratio detection and plume structure sensing and they do so more efficiently than the traditionally considered mechanism of lateral inhibition in the antennal lobe. However, we also found that NSIs decrease the dynamic range of co-housed ORNs, especially when they have similar sensitivity to an odorant. These results shed light, from a functional perspective, on the role of NSIs, which are normally avoided between neurons, for instance by myelination.

Author summary

Myelin is important to isolate neurons and avoid disruptive electrical interference between them; it can be found in almost any neural assembly. However, there are a few exceptions to this rule and it remains unclear why. One particularly interesting case is the electrical interaction between olfactory sensory neurons co-housed in the sensilla of insects. Here, we created a computational model of the early stages of the Drosophila olfactory system and observed that the electrical interference between olfactory receptor neurons can be a useful trait that can help flies, and other insects, to navigate the complex plumes of odorants in their natural environment.

With the model we were able to shed new light on the trade-off of adopting this mechanism: We found that the non-synaptic interactions (NSIs) improve both the identification of the concentration ratio in mixtures of odorants and the discrimination of odorant mixtures emanating from a single source from odorants emitted from separate sources – both highly advantageous. However, they also decrease the dynamic range of the olfactory sensory neurons – a clear disadvantage.

In vivo large-scale analysis of Drosophila neuronal calcium traces by automated tracking of single somata

How does the concerted activity of neuronal populations shape behavior? Impediments to address this question are primarily due to critical experimental barriers. An integrated perspective on large scale neural information processing requires an in vivo approach that can combine the advantages of exhaustively observing all neurons dedicated to a given type of stimulus, and simultaneously achieve a resolution that is precise enough to capture individual neuron activity. Current experimental data from in vivo observations are either restricted to a small fraction of the total number of neurons, or are based on larger brain volumes but at a low spatial and temporal resolution. Consequently, fundamental questions as to how sensory information is represented on a population scale remain unanswered. In Drosophila melanogaster, the mushroom body (MB) represents an excellent model to analyze sensory coding and memory plasticity. In this work, we present an experimental setup coupled with a dedicated computational method that provides in vivo measurements of the activity of hundreds of densely packed somata uniformly spread in the MB. We exploit spinning-disk confocal 3D imaging over time of the whole MB cell body layer in vivo while it is exposed to olfactory stimulation. Importantly, to derive individual signal from densely packed somata, we have developed a fully automated image analysis procedure that takes advantage of the specificities of our data. After anisotropy correction, our approach operates a dedicated spot detection and registration over the entire time sequence to transform trajectories to identifiable clusters. This enabled us to discard spurious detections and reconstruct missing ones in a robust way. We demonstrate that this approach outperformed existing methods in this specific context and made possible high-throughput analysis of approximately 500 single somata uniformly spread over the MB in various conditions. Applying this approach, we find that learned experiences change the population code of odor representations in the MB. After long-term memory (LTM) formation, we quantified an increase in responsive somata count and a stable single neuron signal. We predict that this method, which should further enable studying the population pattern of neuronal activity, has the potential to uncover fine details of sensory processing and memory plasticity.

Multiple network properties overcome random connectivity to enable stereotypic sensory responses

Connections between neuronal populations may be genetically hardwired or random. In the insect olfactory system, projection neurons of the antennal lobe connect randomly to Kenyon cells of the mushroom body. Consequently, while the odor responses of the projection neurons are stereotyped across individuals, the responses of the Kenyon cells are variable. Surprisingly, downstream of Kenyon cells, mushroom body output neurons show stereotypy in their responses. We found that the stereotypy is enabled by the convergence of inputs from many Kenyon cells onto an output neuron, and does not require learning. The stereotypy emerges in the total response of the Kenyon cell population using multiple odor-specific features of the projection neuron responses, benefits from the nonlinearity in the transfer function, depends on the convergence:randomness ratio, and is constrained by sparseness. Together, our results reveal the fundamental mechanisms and constraints with which convergence enables stereotypy in sensory responses despite random connectivity.

Stochastic and Arbitrarily Generated Input Patterns to the Mushroom Bodies Can Serve as Conditioned Stimuli in Drosophila

Single neurons in the brains of insects often have individual genetic identities and can be unambiguously identified between animals. The overall neuronal connectivity is also genetically determined and hard-wired to a large degree. Experience-dependent structural and functional plasticity is believed to be superimposed onto this more-or-less fixed connectome. However, in Drosophila melanogaster, it has been shown that the connectivity between the olfactory projection neurons (OPNs) and Kenyon cells, the intrinsic neurons of the mushroom body, is highly stochastic and idiosyncratic between individuals. Ensembles of distinctly and sparsely activated Kenyon cells represent information about the identity of the olfactory input, and behavioral relevance can be assigned to this representation in the course of associative olfactory learning. Previously, we showed that in the absence of any direct sensory input, artificially and stochastically activated groups of Kenyon cells could be trained to encode aversive cues when their activation coincided with aversive stimuli. Here, we have tested the hypothesis that the mushroom body can learn any stochastic neuronal input pattern as behaviorally relevant, independent of its exact origin. We show that fruit flies can learn thermogenetically generated, stochastic activity patterns of OPNs as conditioned stimuli, irrespective of glomerular identity, the innate valence that the projection neurons carry, or inter-hemispheric symmetry.

Functional and anatomical specificity in a higher olfactory centre

Most sensory systems are organized into parallel neuronal pathways that process distinct aspects of incoming stimuli. In the insect olfactory system, second order projection neurons target both the mushroom body, required for learning, and the lateral horn (LH), proposed to mediate innate olfactory behavior. Mushroom body neurons form a sparse olfactory population code, which is not stereotyped across animals. In contrast, odor coding in the LH remains poorly understood. We combine genetic driver lines, anatomical and functional criteria to show that the Drosophila LH has ~1400 neurons and >165 cell types. Genetically labeled LHNs have stereotyped odor responses across animals and on average respond to three times more odors than single projection neurons. LHNs are better odor categorizers than projection neurons, likely due to stereotyped pooling of related inputs. Our results reveal some of the principles by which a higher processing area can extract innate behavioral significance from sensory stimuli.

A Complete Electron Microscopy Volume of the Brain of Adult Drosophila melanogaster

Drosophila melanogaster has a rich repertoire of innate and learned behaviors. Its 100,000-neuron brain is a large but tractable target for comprehensive neural circuit mapping. Only electron microscopy (EM) enables complete, unbiased mapping of synaptic connectivity; however, the fly brain is too large for conventional EM. We developed a custom high-throughput EM platform and imaged the entire brain of an adult female fly at synaptic resolution. To validate the dataset, we traced brain-spanning circuitry involving the mushroom body (MB), which has been extensively studied for its role in learning. All inputs to Kenyon cells (KCs), the intrinsic neurons of the MB, were mapped, revealing a previously unknown cell type, postsynaptic partners of KC dendrites, and unexpected clustering of olfactory projection neurons. These reconstructions show that this freely available EM volume supports mapping of brain-spanning circuits, which will significantly accelerate Drosophila neuroscience. VIDEO ABSTRACT.

Structural aspects of plasticity in the nervous system of Drosophila

Neurons extend and retract dynamically their neurites during development to form complex morphologies and to reach out to their appropriate synaptic partners. Their capacity to undergo structural rearrangements is in part maintained during adult life when it supports the animal's ability to adapt to a changing environment or to form lasting memories. Nonetheless, the signals triggering structural plasticity and the mechanisms that support it are not yet fully understood at the molecular level. Here, we focus on the nervous system of the fruit fly to ask to which extent activity modulates neuronal morphology and connectivity during development. Further, we summarize the evidence indicating that the adult nervous system of flies retains some capacity for structural plasticity at the synaptic or circuit level. For simplicity, we selected examples mostly derived from studies on the visual system and on the mushroom body, two regions of the fly brain with extensively studied neuroanatomy.

The interruptive effect of electric shock on odor response requires mushroom bodies in Drosophila melanogaster

Nociceptive stimulus involuntarily interrupts concurrent activities. This interruptive effect is related to the protective function of nociception that is believed to be under stringent evolutionary pressure. To determine whether such interruptive effect is conserved in invertebrate and potentially uncover underlying neural circuits, we examined Drosophila melanogaster. Electric shock (ES) is a commonly used nociceptive stimulus for nociception related research in Drosophila. Here, we showed that background noxious ES dramatically interrupted odor response behaviors in a T-maze, which is termed blocking odor response by electric shock (BOBE). The interruptive effect is not odor specific. ES could interrupt both odor avoidance and odor approach. To identify involved brain areas, we focused on the odor avoidance to 3-OCT. By spatially abolishing neurotransmission with temperature sensitive Shibire^TS1 , we found that mushroom bodies (MBs) are necessary for BOBE. Among the 3 major MB Kenyon cell (KCs) subtypes, α/β neurons and γ neurons but not α'/β' neurons are required for normal BOBE. Specifically, abolishing the neurotransmission of either α/β surface (α/β_s ), α/β core (α/β_c ) or γ dorsal (γ_d ) neurons alone is sufficient to abrogate BOBE. This pattern of MB subset requirement is distinct from that of aversive olfactory learning, indicating a specialized BOBE pathway. Consistent with this idea, BOBE was not diminished in several associative memory mutants and noxious ES interrupted both innate and learned odor avoidance. Overall, our results suggest that MB α/β and γ neurons are parts of a previously unappreciated central neural circuit that processes the interruptive effect of nociception.

Cellular diversity in the Drosophila midbrain revealed by single-cell transcriptomics

To understand the brain, molecular details need to be overlaid onto neural wiring diagrams so that synaptic mode, neuromodulation and critical signaling operations can be considered. Single-cell transcriptomics provide a unique opportunity to collect this information. Here we present an initial analysis of thousands of individual cells from Drosophila midbrain, that were acquired using Drop-Seq. A number of approaches permitted the assignment of transcriptional profiles to several major brain regions and cell-types. Expression of biosynthetic enzymes and reuptake mechanisms allows all the neurons to be typed according to the neurotransmitter or neuromodulator that they produce and presumably release. Some neuropeptides are preferentially co-expressed in neurons using a particular fast-acting transmitter, or monoamine. Neuromodulatory and neurotransmitter receptor subunit expression illustrates the potential of these molecules in generating complexity in neural circuit function. This cell atlas dataset provides an important resource to link molecular operations to brain regions and complex neural processes.

Neural Control of Startle-Induced Locomotion by the Mushroom Bodies and Associated Neurons in Drosophila

Startle-induced locomotion is commonly used in Drosophila research to monitor locomotor reactivity and its progressive decline with age or under various neuropathological conditions. A widely used paradigm is startle-induced negative geotaxis (SING), in which flies entrapped in a narrow column react to a gentle mechanical shock by climbing rapidly upwards. Here we combined in vivo manipulation of neuronal activity and splitGFP reconstitution across cells to search for brain neurons and putative circuits that regulate this behavior. We show that the activity of specific clusters of dopaminergic neurons (DANs) afferent to the mushroom bodies (MBs) modulates SING, and that DAN-mediated SING regulation requires expression of the DA receptor Dop1R1/Dumb, but not Dop1R2/Damb, in intrinsic MB Kenyon cells (KCs). We confirmed our previous observation that activating the MB α'β', but not αβ, KCs decreased the SING response, and we identified further MB neurons implicated in SING control, including KCs of the γ lobe and two subtypes of MB output neurons (MBONs). We also observed that co-activating the αβ KCs antagonizes α'β' and γ KC-mediated SING modulation, suggesting the existence of subtle regulation mechanisms between the different MB lobes in locomotion control. Overall, this study contributes to an emerging picture of the brain circuits modulating locomotor reactivity in Drosophila that appear both to overlap and differ from those underlying associative learning and memory, sleep/wake state and stress-induced hyperactivity.

Drosophila mushroom bodies integrate hunger and satiety signals to control innate food-seeking behavior

The fruit fly can evaluate its energy state and decide whether to pursue food-related cues. Here, we reveal that the mushroom body (MB) integrates hunger and satiety signals to control food-seeking behavior. We have discovered five pathways in the MB essential for hungry flies to locate and approach food. Blocking the MB-intrinsic Kenyon cells (KCs) and the MB output neurons (MBONs) in these pathways impairs food-seeking behavior. Starvation bi-directionally modulates MBON responses to a food odor, suggesting that hunger and satiety controls occur at the KC-to-MBON synapses. These controls are mediated by six types of dopaminergic neurons (DANs). By manipulating these DANs, we could inhibit food-seeking behavior in hungry flies or promote food seeking in fed flies. Finally, we show that the DANs potentially receive multiple inputs of hunger and satiety signals. This work demonstrates an information-rich central circuit in the fly brain that controls hunger-driven food-seeking behavior.

Optical clearing for multiscale biological tissues

Three-dimensional reconstruction of tissue structures is essential for biomedical research. The development of light microscopes and various fluorescent labeling techniques provides powerful tools for this motivation. However, optical imaging depth suffers from strong light scattering due to inherent heterogeneity of biological tissues. Tissue optical clearing technology provides a distinct solution and permits us to image large volumes with high resolution. Until now, various clearing methods have been developed. In this study, from the perspective of the end users, we review in vitro tissue optical clearing techniques based on the sample features in terms of size and age, enumerate the methods suitable for immunostaining and lipophilic dyes and summarize the combinations with various imaging techniques. We hope this review will be helpful for researchers to choose the most suitable clearing method from a variety of protocols to meet their specific needs.

RTF: a rapid and versatile tissue optical clearing method

Tissue optical clearing enables imaging deeper in large volumes with high-resolution. Clear T2 is a relatively rapid clearing method with no use of solvents or detergents, hence poses great advantage on preservation of diverse fluorescent labels. However, this method suffers from insufficient tissue transparency, especially for adult mouse brain blocks. In this work, we develop a rapid and versatile clearing method based on Clear T2 , termed RTF (Rapid clearing method based on Triethanolamine and Formamide), aiming for better clearing capability. The results show that RTF can not only efficiently clear embryos, neonatal brains and adult brain blocks, but also preserve fluorescent signal of both endogenous fluorescent proteins and lipophilic dyes, and be compatible with virus labeling and immunostaining. With the good transparency and versatile compatibility, RTF allows visualization and tracing of fluorescent labeling cells and neuronal axons combined with different imaging techniques, showing potentials in facilitating observation of morphological architecture and visualization of neuronal networks.

Persistent activity in a recurrent circuit underlies courtship memory in Drosophila

Recurrent connections are thought to be a common feature of the neural circuits that encode memories, but how memories are laid down in such circuits is not fully understood. Here we present evidence that courtship memory in Drosophila relies on the recurrent circuit between mushroom body gamma (MBγ), M6 output, and aSP13 dopaminergic neurons. We demonstrate persistent neuronal activity of aSP13 neurons and show that it transiently potentiates synaptic transmission from MBγ>M6 neurons. M6 neurons in turn provide input to aSP13 neurons, prolonging potentiation of MBγ>M6 synapses over time periods that match short-term memory. These data support a model in which persistent aSP13 activity within a recurrent circuit lays the foundation for a short-term memory.

Memories help to shape behavior, and can last from a few seconds to an entire lifetime. Working memory, in which information is temporarily held available for use in an ongoing task, is the most fleeting form of memory. It relies on persistent activation of a network of nerve cells or neurons that represent the information in question. Strengthening the connections between those neurons may result in a longer-lasting memory. But the mechanisms that support the formation of memories of different durations are not fully understood.

Zhao et al. have now explored these mechanisms in the fruit fly by studying memory for courtship behavior. Inexperienced male fruit flies will attempt to court both virgin females and females who have recently mated. But the latter reject courtship attempts, and male fruit flies therefore learn to avoid them. This is known as courtship memory, and it relies on a network of neurons within a region of the fruit fly brain called the mushroom body.

Within the mushroom body, dopamine neuron sends signals to a neuron called the Kenyon cell, which in turn sends signals to a mushroom body output neuron. The latter activates circuits responsible for decision-making and movement. But it also activates the dopamine neuron, thereby forming a recurrent circuit or loop. When the courtship is rejected, the dopamine neuron becomes persistently active, which generates a working memory of the experience. If the circuit is activated again during this period of persistent firing, the working memory may be converted into a longer-lasting memory.

The results of Zhao et al. provide insights into the mechanisms by which memories form and undergo strengthening. They suggest that distinct processes within a single neural circuit give rise to memories of different durations. Recurrent loops are also present within the brains of mammals. Similar processes may thus support the formation and persistence of our own memories.

Origins of Cell-Type-Specific Olfactory Processing in the Drosophila Mushroom Body Circuit

How cell-type-specific physiological properties shape neuronal functions in a circuit remains poorly understood. We addressed this issue in the Drosophila mushroom body (MB), a higher olfactory circuit, where neurons belonging to distinct glomeruli in the antennal lobe feed excitation to three types of intrinsic neurons, α/β, α'/β', and γ Kenyon cells (KCs). Two-photon optogenetics and intracellular recording revealed that whereas glomerular inputs add similarly in all KCs, spikes were generated most readily in α'/β' KCs. This cell type was also the most competent in recruiting GABAergic inhibition fed back by anterior paired lateral neuron, which responded to odors either locally within a lobe or globally across all lobes depending on the strength of stimuli. Notably, as predicted from these physiological properties, α'/β' KCs had the highest odor detection speed, sensitivity, and discriminability. This enhanced discrimination required proper GABAergic inhibition. These results link cell-type-specific mechanisms and functions in the MB circuit.

Long-term memory requires sequential protein synthesis in three subsets of mushroom body output neurons in Drosophila

Creating long-term memory (LTM) requires new protein synthesis to stabilize learning-induced synaptic changes in the brain. In the fruit fly, Drosophila melanogaster, aversive olfactory learning forms several phases of labile memory to associate an odor with coincident punishment in the mushroom body (MB). It remains unclear how the brain consolidates early labile memory into LTM. Here, we survey 183 Gal4 lines containing almost all 21 distinct types of MB output neurons (MBONs) and show that sequential synthesis of learning-induced proteins occurs at three types of MBONs. Downregulation of oo18 RNA-binding proteins (ORBs) in any of these MBONs impaired LTM. And, neurotransmission outputs from these MBONs are all required during LTM retrieval. Together, these results suggest an LTM consolidation model in which transient neural activities of early labile memory in the MB are consolidated into stable LTM at a few postsynaptic MBONs through sequential ORB-regulated local protein synthesis.

A connectome of a learning and memory center in the adult Drosophila brain

Understanding memory formation, storage and retrieval requires knowledge of the underlying neuronal circuits. In Drosophila, the mushroom body (MB) is the major site of associative learning. We reconstructed the morphologies and synaptic connections of all 983 neurons within the three functional units, or compartments, that compose the adult MB’s α lobe, using a dataset of isotropic 8 nm voxels collected by focused ion-beam milling scanning electron microscopy. We found that Kenyon cells (KCs), whose sparse activity encodes sensory information, each make multiple en passant synapses to MB output neurons (MBONs) in each compartment. Some MBONs have inputs from all KCs, while others differentially sample sensory modalities. Only 6% of KC>MBON synapses receive a direct synapse from a dopaminergic neuron (DAN). We identified two unanticipated classes of synapses, KC>DAN and DAN>MBON. DAN activation produces a slow depolarization of the MBON in these DAN>MBON synapses and can weaken memory recall.

DOI:http://dx.doi.org/10.7554/eLife.26975.001

Olfactory coding from the periphery to higher brain centers in the Drosophila brain

BACKGROUND

Odor information is processed through multiple receptor-glomerular channels in the first order olfactory center, the antennal lobe (AL), then reformatted into higher brain centers and eventually perceived by the fly. To reveal the logic of olfaction, it is fundamental to map odor representations from the glomerular channels into higher brain centers.

RESULTS

We characterize odor response profiles of AL projection neurons (PNs) originating from 31 glomeruli using whole cell patch-clamp recordings in Drosophila melanogaster. We reveal that odor representation from olfactory sensory neurons to PNs is generally conserved, while transformation of odor tuning curves is glomerulus-dependent. Reconstructions of PNs reveal that attractive and aversive odors are represented in different clusters of glomeruli in the AL. These separate representations are preserved into higher brain centers, where attractive and aversive odors are segregated into two regions in the lateral horn and partly separated in the mushroom body calyx.

CONCLUSIONS

Our study reveals spatial representation of odor valence coding from the AL to higher brain centers. These results provide a global picture of the olfactory circuit design underlying innate odor-guided behavior.

What can tiny mushrooms in fruit flies tell us about learning and memory?

Nervous systems have evolved to translate external stimuli into appropriate behavioral responses. In an ever-changing environment, flexible adjustment of behavioral choice by experience-dependent learning is essential for the animal's survival. Associative learning is a simple form of learning that is widely observed from worms to humans. To understand the whole process of learning, we need to know how sensory information is represented and transformed in the brain, how it is changed by experience, and how the changes are reflected on motor output. To tackle these questions, studying numerically simple invertebrate nervous systems has a great advantage. In this review, I will feature the Pavlovian olfactory learning in the fruit fly, Drosophila melanogaster. The mushroom body is a key brain area for the olfactory learning in this organism. Recently, comprehensive anatomical information and the genetic tool sets were made available for the mushroom body circuit. This greatly accelerated the physiological understanding of the learning process. One of the key findings was dopamine-induced long-term synaptic plasticity that can alter the representations of stimulus valence. I will mostly focus on the new studies within these few years and discuss what we can possibly learn about the vertebrate systems from this model organism.

The glia of the adult Drosophila nervous system

Glia play crucial roles in the development and homeostasis of the nervous system. While the GLIA in the Drosophila embryo have been well characterized, their study in the adult nervous system has been limited. Here, we present a detailed description of the glia in the adult nervous system, based on the analysis of some 500 glial drivers we identified within a collection of synthetic GAL4 lines. We find that glia make up ∼10% of the cells in the nervous system and envelop all compartments of neurons (soma, dendrites, axons) as well as the nervous system as a whole. Our morphological analysis suggests a set of simple rules governing the morphogenesis of glia and their interactions with other cells. All glial subtypes minimize contact with their glial neighbors but maximize their contact with neurons and adapt their macromorphology and micromorphology to the neuronal entities they envelop. Finally, glial cells show no obvious spatial organization or registration with neuronal entities. Our detailed description of all glial subtypes and their regional specializations, together with the powerful genetic toolkit we provide, will facilitate the functional analysis of glia in the mature nervous system. GLIA 2017 GLIA 2017;65:606–638

Visual Attention in Flies-Dopamine in the Mushroom Bodies Mediates the After-Effect of Cueing

Visual environments may simultaneously comprise stimuli of different significance. Often such stimuli require incompatible responses. Selective visual attention allows an animal to respond exclusively to the stimuli at a certain location in the visual field. In the process of establishing its focus of attention the animal can be influenced by external cues. Here we characterize the behavioral properties and neural mechanism of cueing in the fly Drosophila melanogaster. A cue can be attractive, repulsive or ineffective depending upon (e.g.) its visual properties and location in the visual field. Dopamine signaling in the brain is required to maintain the effect of cueing once the cue has disappeared. Raising or lowering dopamine at the synapse abolishes this after-effect. Specifically, dopamine is necessary and sufficient in the αβ-lobes of the mushroom bodies. Evidence is provided for an involvement of the αβ_posterior Kenyon cells.

NBLAST: Rapid, Sensitive Comparison of Neuronal Structure and Construction of Neuron Family Databases

Neural circuit mapping is generating datasets of tens of thousands of labeled neurons. New computational tools are needed to search and organize these data. We present NBLAST, a sensitive and rapid algorithm, for measuring pairwise neuronal similarity. NBLAST considers both position and local geometry, decomposing neurons into short segments; matched segments are scored using a probabilistic scoring matrix defined by statistics of matches and non-matches. We validated NBLAST on a published dataset of 16,129 single Drosophila neurons. NBLAST can distinguish neuronal types down to the finest level (single identified neurons) without a priori information. Cluster analysis of extensively studied neuronal classes identified new types and unreported topographical features. Fully automated clustering organized the validation dataset into 1,052 clusters, many of which map onto previously described neuronal types. NBLAST supports additional query types, including searching neurons against transgene expression patterns. Finally, we show that NBLAST is effective with data from other invertebrates and zebrafish.

Video Abstract

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NBLAST is a fast and sensitive algorithm to measure pairwise neuronal similarity

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NBLAST can distinguish neuronal types at the finest level without training

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Automated clustering of 16,129 Drosophila neurons identifies 1,052 classes

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Online search tool for databases of single neurons or genetic driver lines

Cell-Type-Specific Transcriptome Analysis in the Drosophila Mushroom Body Reveals Memory-Related Changes in Gene Expression

Learning and memory formation in Drosophila rely on a network of neurons in the mushroom bodies (MBs). Whereas numerous studies have delineated roles for individual cell types within this network in aspects of learning or memory, whether or not these cells can also be distinguished by the genes they express remains unresolved. In addition, the changes in gene expression that accompany long-term memory formation within the MBs have not yet been studied by neuron type. Here, we address both issues by performing RNA sequencing on single cell types (harvested via patch pipets) within the MB. We discover that the expression of genes that encode cell surface receptors is sufficient to identify cell types and that a subset of these genes, required for sensory transduction in peripheral sensory neurons, is not only expressed within individual neurons of the MB in the central brain, but is also critical for memory formation.

Brain/MINDS: brain-mapping project in Japan

There is an emerging interest in brain-mapping projects in countries across the world, including the USA, Europe, Australia and China. In 2014, Japan started a brain-mapping project called Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS). Brain/MINDS aims to map the structure and function of neuronal circuits to ultimately understand the vast complexity of the human brain, and takes advantage of a unique non-human primate animal model, the common marmoset (Callithrix jacchus). In Brain/MINDS, the RIKEN Brain Science Institute acts as a central institute. The objectives of Brain/MINDS can be categorized into the following three major subject areas: (i) structure and functional mapping of a non-human primate brain (the marmoset brain); (ii) development of innovative neurotechnologies for brain mapping; and (iii) human brain mapping; and clinical research. Brain/MINDS researchers are highly motivated to identify the neuronal circuits responsible for the phenotype of neurological and psychiatric disorders, and to understand the development of these devastating disorders through the integration of these three subject areas.