A multilayer circuit architecture for the generation of distinct locomotor behaviors in Drosophila

CRASH2p: Closed-loop Two Photon Imaging in Freely Moving Animals

Direct measurement of neural activity in freely moving animals is essential for understanding how the brain controls and represents behaviors. Genetically encoded calcium indicators report neural activity as changes in fluorescence intensity, but brain motion confounds quantitative measurement of fluorescence. Translation, rotation, and deformation of the brain and the movements of intervening scattering or auto-fluorescent tissue all alter the amount of fluorescent light captured by a microscope. Compared to single-photon approaches, two photon microscopy is less sensitive to scattering and off-target fluorescence, but more sensitive to motion, and two photon imaging has always required anchoring the microscope to the brain. We developed a closed-loop resonant axial-scanning high-speed two photon (CRASH2p) microscope for real-time 3D motion correction in unrestrained animals, without implantation of reference markers. We complemented CRASH2p with a novel scanning strategy and a multistage registration pipeline. We performed volumetric ratiometrically corrected functional imaging in the CNS of freely moving Drosophila larvae and discovered previously unknown neural correlates of behavior.

40 years of homeodomain transcription factors in the Drosophila nervous system

Drosophila nervous system development progresses through a series of well-characterized steps in which homeodomain transcription factors (HDTFs) play key roles during most, if not all, phases. Strikingly, although some HDTFs have only one role, many others are involved in multiple steps of the developmental process. Most Drosophila HDTFs engaged in nervous system development are conserved in vertebrates and often play similar roles during vertebrate development. In this Spotlight, we focus on the role of HDTFs during embryogenesis, where they were first characterized.

The tail segments are required by the performance but not the accomplishment of various modes of Drosophila larval locomotion

The tail plays important roles in locomotion control in many animals. But in animals with multiple body segments, the roles of the hind body segments and corresponding innervating neurons in locomotion control are not clear. Here, using the Drosophila larva as the model animal, we investigated the roles of the posterior terminal segments in various modes of locomotion and found that they participate in all of them. In forward crawling, paralysis of the larval tail by blocking the Abdb-Gal4 labeled neurons in the posterior segments of VNC led to a slower locomotion speed but did not prevent the initiation of forward peristalsis. In backward crawling, larvae with the Abdb-Gal4 neurons inhibited were unable to generate effective displacement although waves of backward peristalsis could be initiated and persist. In head swing where the movement of the tail is not obvious, disabling the larval tail by blocking Abdb-Gal4 neurons led to increased bending amplitude upon touching the head. In the case of larval lateral rolling, larval tail paralysis by inhibition of Abdb-Gal4 neurons did not prevent the accomplishment of rolling, but resulted in slower rolling speed. Our work reveals that the contribution of Drosophila larval posterior VNC segments and corresponding body segments in the tail to locomotion is comprehensive but could be compensated at least partially by other body segments. We suggest that the decentralization in locomotion control with respect to animal body parts helps to maintain the robustness of locomotion in multi-segment animals.

Prediction of neural activity in connectome-constrained recurrent networks

We develop a theory of connectome-constrained neural networks in which a "student" network is trained to reproduce the activity of a ground-truth "teacher," representing a neural system for which a connectome is available. Unlike standard paradigms with unconstrained connectivity, here the two networks have the same connectivity but different biophysical parameters, reflecting uncertainty in neuronal and synaptic properties. We find that a connectome is often insufficient to constrain the dynamics of networks that perform a specific task, illustrating the difficulty of inferring function from connectivity alone. However, recordings from a small subset of neurons can remove this degeneracy, producing dynamics in the student that agree with the teacher. Our theory can also prioritize which neurons to record from to most efficiently predict unmeasured network activity. Our analysis shows that the solution spaces of connectome-constrained and unconstrained models are qualitatively different and provides a framework to determine when such models yield consistent dynamics.

Synaptic architecture of leg and wing premotor control networks in Drosophila

Animal movement is controlled by motor neurons (MNs), which project out of the central nervous system to activate muscles. MN activity is coordinated by complex premotor networks that allow individual muscles to contribute to many different behaviors. Here, we use connectomics to analyze the wiring logic of premotor circuits controlling the Drosophila leg and wing. We find that both premotor networks cluster into modules that link MNs innervating muscles with related functions. Within most leg motor modules, the synaptic weights of each premotor neuron are proportional to the size of their target MNs, establishing a circuit basis for hierarchical MN recruitment. In contrast, wing premotor networks lack proportional synaptic connectivity, which may allow wing steering muscles to be recruited with different relative timing. By comparing the architecture of distinct limb motor control systems within the same animal, we identify common principles of premotor network organization and specializations that reflect the unique biomechanical constraints and evolutionary origins of leg and wing motor control.

Neuronal mechanisms regulating locomotion in adult Drosophila

The coordinated action of multiple leg joints and muscles is required even for the simplest movements. Understanding the neuronal circuits and mechanisms that generate precise movements is essential for comprehending the neuronal basis of the locomotion and to infer the neuronal mechanisms underlying several locomotor-related diseases. Drosophila melanogaster provides an excellent model system for investigating the neuronal circuits underlying motor behaviors due to its simple nervous system and genetic accessibility. This review discusses current genetic methods for studying locomotor circuits and their function in adult Drosophila. We highlight recently identified neuronal pathways that modulate distinct forward and backward locomotion and describe the underlying neuronal control of leg swing and stance phases in freely moving flies. We also report various automated leg tracking methods to measure leg motion parameters and define inter-leg coordination, gait and locomotor speed of freely moving adult flies. Finally, we emphasize the role of leg proprioceptive signals to central motor circuits in leg coordination. Together, this review highlights the utility of adult Drosophila as a model to uncover underlying motor circuitry and the functional organization of the leg motor system that governs correct movement.

Balance of activity during a critical period tunes a developing network

Developing neural circuits are influenced by activity and are especially sensitive to changes in activity during critical periods (CPs) of development. Changes occurring during a CP often become 'locked in' so that they affect the mature network. Indeed, several neurodevelopmental disorders have been linked to excessive activity during such periods. It is, therefore, important to identify those aspects of neural circuit development that are influenced by neural activity during a CP. In this study, we take advantage of the genetic tractability of Drosophila to show that activity perturbation during an embryonic CP permanently alters properties of the locomotor circuit. Specific changes we identify include increased synchronicity of motoneuron activity and greater strengthening of excitatory over inhibitory synaptic drive to motoneurons. These changes are sufficient to reduce network robustness, evidenced by increased sensitivity to induced seizure. We also show that we can rescue these changes when increased activity is mitigated by inhibition provided by mechanosensory neurons. Similarly, we demonstrate a dose-dependent relationship between inhibition experienced during the CP and the extent to which it is possible to rescue the hyperexcitable phenotype characteristic of the parabss mutation. This suggests that developing circuits must be exposed to a properly balanced sum of excitation and inhibition during the CP to achieve normal mature network function. Our results, therefore, provide novel insight into how activity during a CP shapes specific elements of a circuit, and how activity during this period is integrated to tune neural circuits to the environment in which they will likely function.

Neuromuscular basis of Drosophila larval rolling escape behavior

When threatened by dangerous or harmful stimuli, animals engage in diverse forms of rapid escape behaviors. In Drosophila larvae, one type of escape response involves C-shaped bending and lateral rolling followed by rapid forward crawling. The sensory circuitry that promotes larval escape has been extensively characterized; however, the motor programs underlying rolling are unknown. Here, we characterize the neuromuscular basis of rolling escape behavior. We used high-speed, volumetric, Swept Confocally Aligned Planar Excitation (SCAPE) microscopy to image muscle activity during larval rolling. Unlike sequential peristaltic muscle contractions that progress from segment to segment during forward and backward crawling, muscle activity progresses circumferentially during bending and rolling escape behavior. We propose that progression of muscular contraction around the larva's circumference results in a transient misalignment between weight and the ground support forces, which generates a torque that induces stabilizing body rotation. Therefore, successive cycles of slight misalignment followed by reactive aligning rotation lead to continuous rolling motion. Supporting our biomechanical model, we found that disrupting the activity of muscle groups undergoing circumferential contraction progression leads to rolling defects. We use EM connectome data to identify premotor to motor connectivity patterns that could drive rolling behavior and perform neural silencing approaches to demonstrate the crucial role of a group of glutamatergic premotor neurons in rolling. Our data reveal body-wide muscle activity patterns and putative premotor circuit organization for execution of the rolling escape response.

Molecular logic of synaptic diversity between Drosophila tonic and phasic motoneurons

Although neuronal subtypes display unique synaptic organization and function, the underlying transcriptional differences that establish these features are poorly understood. To identify molecular pathways that contribute to synaptic diversity, single-neuron Patch-seq RNA profiling was performed on Drosophila tonic and phasic glutamatergic motoneurons. Tonic motoneurons form weaker facilitating synapses onto single muscles, while phasic motoneurons form stronger depressing synapses onto multiple muscles. Super-resolution microscopy and in vivo imaging demonstrated that synaptic active zones in phasic motoneurons are more compact and display enhanced Ca2+ influx compared with their tonic counterparts. Genetic analysis identified unique synaptic properties that mapped onto gene expression differences for several cellular pathways, including distinct signaling ligands, post-translational modifications, and intracellular Ca2+ buffers. These findings provide insights into how unique transcriptomes drive functional and morphological differences between neuronal subtypes.

The Intrinsic Similarity of Topological Structure in Biological Neural Networks

Most previous studies mainly have focused on the analysis of structural properties of individual neuronal networks from C. elegans. In recent years, an increasing number of synapse-level neural maps, also known as biological neural networks, have been reconstructed. However, it is not clear whether there are intrinsic similarities of structural properties of biological neural networks from different brain compartments or species. To explore this issue, we collected nine connectomes at synaptic resolution including C. elegans, and analyzed their structural properties. We found that these biological neural networks possess small-world properties and modules. Excluding the Drosophila larval visual system, these networks have rich clubs. The distributions of synaptic connection strength for these networks can be fitted by the truncated pow-law distributions. Additionally, compared with the power-law model, a log-normal distribution is a better model to fit the complementary cumulative distribution function (CCDF) of degree for these neuronal networks. Moreover, we also observed that these neural networks belong to the same superfamily based on the significance profile (SP) of small subgraphs in the network. Taken together, these findings suggest that biological neural networks share intrinsic similarities in their topological structure, revealing some principles underlying the formation of biological neural networks within and across species.

Mechanosensory Control of Locomotion in Animals and Robots: Moving Forward

While animals swim, crawl, walk, and fly with apparent ease, building robots capable of robust locomotion remains a significant challenge. In this review, we draw attention to mechanosensation-the sensing of mechanical forces generated within and outside the body-as a key sense that enables robust locomotion in animals. We discuss differences between mechanosensation in animals and current robots with respect to (1) the encoding properties and distribution of mechanosensors and (2) the integration and regulation of mechanosensory feedback. We argue that robotics would benefit greatly from a detailed understanding of these aspects in animals. To that end, we highlight promising experimental and engineering approaches to study mechanosensation, emphasizing the mutual benefits for biologists and engineers that emerge from moving forward together.

Linking neural circuits to the mechanics of animal behavior in Drosophila larval locomotion

The motions that make up animal behavior arise from the interplay between neural circuits and the mechanical parts of the body. Therefore, in order to comprehend the operational mechanisms governing behavior, it is essential to examine not only the underlying neural network but also the mechanical characteristics of the animal's body. The locomotor system of fly larvae serves as an ideal model for pursuing this integrative approach. By virtue of diverse investigation methods encompassing connectomics analysis and quantification of locomotion kinematics, research on larval locomotion has shed light on the underlying mechanisms of animal behavior. These studies have elucidated the roles of interneurons in coordinating muscle activities within and between segments, as well as the neural circuits responsible for exploration. This review aims to provide an overview of recent research on the neuromechanics of animal locomotion in fly larvae. We also briefly review interspecific diversity in fly larval locomotion and explore the latest advancements in soft robots inspired by larval locomotion. The integrative analysis of animal behavior using fly larvae could establish a practical framework for scrutinizing the behavior of other animal species.

Synchronous multi-segmental activity between metachronal waves controls locomotion speed in Drosophila larvae

The ability to adjust the speed of locomotion is essential for survival. In limbed animals, the frequency of locomotion is modulated primarily by changing the duration of the stance phase. The underlying neural mechanisms of this selective modulation remain an open question. Here, we report a neural circuit controlling a similarly selective adjustment of locomotion frequency in Drosophila larvae. Drosophila larvae crawl using peristaltic waves of muscle contractions. We find that larvae adjust the frequency of locomotion mostly by varying the time between consecutive contraction waves, reminiscent of limbed locomotion. A specific set of muscles, the lateral transverse (LT) muscles, co-contract in all segments during this phase, the duration of which sets the duration of the interwave phase. We identify two types of GABAergic interneurons in the LT neural network, premotor neuron A26f and its presynaptic partner A31c, which exhibit segmentally synchronized activity and control locomotor frequency by setting the amplitude and duration of LT muscle contractions. Altogether, our results reveal an inhibitory central circuit that sets the frequency of locomotion by controlling the duration of the period in between peristaltic waves. Further analysis of the descending inputs onto this circuit will help understand the higher control of this selective modulation.

Neural substrates of cold nociception in Drosophila larva

Metazoans detect and differentiate between innocuous (non-painful) and/or noxious (harmful) environmental cues using primary sensory neurons, which serve as the first node in a neural network that computes stimulus specific behaviors to either navigate away from injury-causing conditions or to perform protective behaviors that mitigate extensive injury. The ability of an animal to detect and respond to various sensory stimuli depends upon molecular diversity in the primary sensors and the underlying neural circuitry responsible for the relevant behavioral action selection. Recent studies in Drosophila larvae have revealed that somatosensory class III multidendritic (CIII md) neurons function as multimodal sensors regulating distinct behavioral responses to innocuous mechanical and nociceptive thermal stimuli. Recent advances in circuit bases of behavior have identified and functionally validated Drosophila larval somatosensory circuitry involved in innocuous (mechanical) and noxious (heat and mechanical) cues. However, central processing of cold nociceptive cues remained unexplored. We implicate multisensory integrators (Basins), premotor (Down-and-Back) and projection (A09e and TePns) neurons as neural substrates required for cold-evoked behavioral and calcium responses. Neural silencing of cell types downstream of CIII md neurons led to significant reductions in cold-evoked behaviors and neural co-activation of CIII md neurons plus additional cell types facilitated larval contraction (CT) responses. We further demonstrate that optogenetic activation of CIII md neurons evokes calcium increases in these neurons. Collectively, we demonstrate how Drosophila larvae process cold stimuli through functionally diverse somatosensory circuitry responsible for generating stimulus specific behaviors.

Distinctive features of the central synaptic organization of Drosophila larval proprioceptors

Proprioceptive feedback is critically needed for locomotor control, but how this information is incorporated into central proprioceptive processing circuits remains poorly understood. Circuit organization emerges from the spatial distribution of synaptic connections between neurons. This distribution is difficult to discern in model systems where only a few cells can be probed simultaneously. Therefore, we turned to a relatively simple and accessible nervous system to ask: how are proprioceptors' input and output synapses organized in space, and what principles underlie this organization? Using the Drosophila larval connectome, we generated a map of the input and output synapses of 34 proprioceptors in several adjacent body segments (5-6 left-right pairs per segment). We characterized the spatial organization of these synapses, and compared this organization to that of other somatosensory neurons' synapses. We found three distinguishing features of larval proprioceptor synapses: (1) Generally, individual proprioceptor types display segmental somatotopy. (2) Proprioceptor output synapses both converge and diverge in space; they are organized into six spatial domains, each containing a unique set of one or more proprioceptors. Proprioceptors form output synapses along the proximal axonal entry pathway into the neuropil. (3) Proprioceptors receive few inhibitory input synapses. Further, we find that these three features do not apply to other larval somatosensory neurons. Thus, we have generated the most comprehensive map to date of how proprioceptor synapses are centrally organized. This map documents previously undescribed features of proprioceptors, raises questions about underlying developmental mechanisms, and has implications for downstream proprioceptive processing circuits.

High-resolution analysis of individual Drosophila melanogaster larvae uncovers individual variability in locomotion and its neurogenetic modulation

Neuronally orchestrated muscular movement and locomotion are defining faculties of multicellular animals. Due to its simple brain and genetic accessibility, the larva of the fruit fly Drosophila melanogaster allows one to study these processes at tractable levels of complexity. However, although the faculty of locomotion clearly pertains to the individual, most studies of locomotion in larvae use measurements aggregated across animals, or animals tested one by one, an extravagance for larger-scale analyses. This prevents grasping the inter- and intra-individual variability in locomotion and its neurogenetic determinants. Here, we present the IMBA (individual maggot behaviour analyser) for analysing the behaviour of individual larvae within groups, reliably resolving individual identity across collisions. We use the IMBA to systematically describe the inter- and intra-individual variability in locomotion of wild-type animals, and how the variability is reduced by associative learning. We then report a novel locomotion phenotype of an adhesion GPCR mutant. We further investigated the modulation of locomotion across repeated activations of dopamine neurons in individual animals, and the transient backward locomotion induced by brief optogenetic activation of the brain-descending 'mooncrawler' neurons. In summary, the IMBA is an easy-to-use toolbox allowing an unprecedentedly rich view of the behaviour and its variability of individual larvae, with utility in multiple biomedical research contexts.

A complete biomechanical model of Hydra contractile behaviors, from neural drive to muscle to movement

How does neural activity drive muscles to produce behavior? The recent development of genetic lines in Hydra that allow complete calcium imaging of both neuronal and muscle activity, as well as systematic machine learning quantification of behaviors, makes this small cnidarian an ideal model system to understand and model the complete transformation from neural firing to body movements. To achieve this, we have built a neuromechanical model of Hydra's fluid-filled hydrostatic skeleton, showing how drive by neuronal activity activates distinct patterns of muscle activity and body column biomechanics. Our model is based on experimental measurements of neuronal and muscle activity and assumes gap junctional coupling among muscle cells and calcium-dependent force generation by muscles. With these assumptions, we can robustly reproduce a basic set of Hydra's behaviors. We can further explain puzzling experimental observations, including the dual timescale kinetics observed in muscle activation and the engagement of ectodermal and endodermal muscles in different behaviors. This work delineates the spatiotemporal control space of Hydra movement and can serve as a template for future efforts to systematically decipher the transformations in the neural basis of behavior.

The connectome of an insect brain

Brains contain networks of interconnected neurons and so knowing the network architecture is essential for understanding brain function. We therefore mapped the synaptic-resolution connectome of an entire insect brain (Drosophila larva) with rich behavior, including learning, value computation, and action selection, comprising 3016 neurons and 548,000 synapses. We characterized neuron types, hubs, feedforward and feedback pathways, as well as cross-hemisphere and brain-nerve cord interactions. We found pervasive multisensory and interhemispheric integration, highly recurrent architecture, abundant feedback from descending neurons, and multiple novel circuit motifs. The brain's most recurrent circuits comprised the input and output neurons of the learning center. Some structural features, including multilayer shortcuts and nested recurrent loops, resembled state-of-the-art deep learning architectures. The identified brain architecture provides a basis for future experimental and theoretical studies of neural circuits.

Molecular Logic of Synaptic Diversity Between Drosophila Tonic and Phasic Motoneurons

Although neuronal subtypes display unique synaptic organization and function, the underlying transcriptional differences that establish these features is poorly understood. To identify molecular pathways that contribute to synaptic diversity, single neuron PatchSeq RNA profiling was performed on Drosophila tonic and phasic glutamatergic motoneurons. Tonic motoneurons form weaker facilitating synapses onto single muscles, while phasic motoneurons form stronger depressing synapses onto multiple muscles. Super-resolution microscopy and in vivo imaging demonstrated synaptic active zones in phasic motoneurons are more compact and display enhanced Ca 2+ influx compared to their tonic counterparts. Genetic analysis identified unique synaptic properties that mapped onto gene expression differences for several cellular pathways, including distinct signaling ligands, post-translational modifications and intracellular Ca 2+ buffers. These findings provide insights into how unique transcriptomes drive functional and morphological differences between neuronal subtypes.

Sphingolipids in neurodegenerative diseases

Neurodegenerative Diseases (NDDs) are a group of disorders that cause progressive deficits of neuronal function. Recent evidence argues that sphingolipid metabolism is affected in a surprisingly broad set of NDDs. These include some lysosomal storage diseases (LSDs), hereditary sensory and autonomous neuropathy (HSAN), hereditary spastic paraplegia (HSP), infantile neuroaxonal dystrophy (INAD), Friedreich's ataxia (FRDA), as well as some forms of amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD). Many of these diseases have been modeled in Drosophila melanogaster and are associated with elevated levels of ceramides. Similar changes have also been reported in vertebrate cells and mouse models. Here, we summarize studies using fly models and/or patient samples which demonstrate the nature of the defects in sphingolipid metabolism, the organelles that are implicated, the cell types that are initially affected, and potential therapeutics for these diseases.

Critical periods in Drosophila neural network development: Importance to network tuning and therapeutic potential

Critical periods are phases of heightened plasticity that occur during the development of neural networks. Beginning with pioneering work of Hubel and Wiesel, which identified a critical period for the formation of ocular dominance in mammalian visual network connectivity, critical periods have been identified for many circuits, both sensory and motor, and across phyla, suggesting a universal phenomenon. However, a key unanswered question remains why these forms of plasticity are restricted to specific developmental periods rather than being continuously present. The consequence of this temporal restriction is that activity perturbations during critical periods can have lasting and significant functional consequences for mature neural networks. From a developmental perspective, critical period plasticity might enable reproducibly robust network function to emerge from ensembles of cells, whose properties are necessarily variable and fluctuating. Critical periods also offer significant clinical opportunity. Imposed activity perturbation during these periods has shown remarkable beneficial outcomes in a range of animal models of neurological disease including epilepsy. In this review, we spotlight the recent identification of a locomotor critical period in Drosophila larva and describe how studying this model organism, because of its simplified nervous system and an almost complete wired connectome, offers an attractive prospect of understanding how activity during a critical period impacts a neuronal network.

Protocols for measuring cold-evoked neural activity and cold tolerance in Drosophila larvae following fictive cold acclimation

Here, we outline protocols to study cold acclimation in Drosophila from a neurobiological perspective, starting with fictive cold acclimation using a custom-built optogenetics-housing apparatus we call the OptoBox. We also provide detailed steps for single-unit electrophysiological recordings from larval cold nociceptors and a high-throughput cold-tolerance assay. These protocols expand the toolkit for the study of insect cold acclimation and nociception. For complete details on the use and execution of this protocol, please refer to Himmel et al. (2021).

Electrophysiological Validation of Monosynaptic Connectivity between Premotor Interneurons and the aCC Motoneuron in the Drosophila Larval CNS

The Drosophila connectome project aims to map the synaptic connectivity of entire larval and adult fly neural networks, which is essential for understanding nervous system development and function. So far, the project has produced an impressive amount of electron microscopy data that has facilitated reconstructions of specific synapses, including many in the larval locomotor circuit. While this breakthrough represents a technical tour de force, the data remain underutilized, partly because of a lack of functional validation of reconstructions. Attempts to validate connectivity posited by the connectome project, have mostly relied on behavioral assays and/or GFP reconstitution across synaptic partners (GRASP) or GCaMP imaging. While these techniques are useful, they have limited spatial or temporal resolution. Electrophysiological assays of synaptic connectivity overcome these limitations. Here, we combine patch-clamp recordings with optogenetic stimulation in male and female larvae, to test synaptic connectivity proposed by connectome reconstructions. Specifically, we use multiple driver lines to confirm that several connections between premotor interneurons and the anterior corner cell motoneuron are, as the connectome project suggests, monosynaptic. In contrast, our results also show that conclusions based on GRASP imaging may provide false-positive results regarding connectivity between cells. We also present a novel imaging tool, based on the same technology as our electrophysiology, as a favorable alternative to GRASP imaging. Finally, of eight Gal4 lines tested, five are reliably expressed in the premotor interneurons they are targeted to. Thus, our work highlights the need to confirm functional synaptic connectivity, driver line specificity, and use of appropriate genetic tools to support connectome projects.SIGNIFICANCE STATEMENT The Drosophila connectome project aims to provide a complete description of connectivity between neurons in an organism that presents experimental advantages over other models. It has reconstructed hundreds of thousands of synaptic connections of the fly larva by manual identification of anatomic landmarks present in serial section transmission electron microscopy (ssTEM) volumes of the larval CNS. We use a highly reliable electrophysiological approach to verify these connections, providing useful insight into the accuracy of work based on ssTEM. We also present a novel imaging tool for validating excitatory monosynaptic connections between cells and show that several genetic driver lines designed to target neurons of the larval connectome exhibit nonspecific and/or unreliable expression.

Extended disordered regions of ribosome-associated NAC proteins paralogs belong only to the germline in Drosophila melanogaster

The nascent polypeptide-associated complex (NAC) consisting of α- and β-subunits is an essential ribosome-associated protein conserved in eukaryotes. NAC is a ubiquitously expressed co-translational regulator of nascent protein folding and sorting providing for homeostasis of cellular proteins. Here we report on discovering the germline-specific NACαβ paralogs (gNACs), whose β-subunits, non-distinguishable by ordinary immunodetection, are encoded by five highly homologous gene copies, while the α-subunit is encoded by a single αNAC gene. The gNAC expression is detected in the primordial embryonic and adult gonads via immunostaining. The germline-specific α and β subunits differ from the ubiquitously expressed paralogs by the extended intrinsically disordered regions (IDRs) acquired at the N- and C-termini of the coding regions, predicted to be phosphorylated. The presence of distinct phosphorylated isoforms of gNAC-β subunits is confirmed by comparing of their profiles by 2D-isoeletrofocusing resolution before and after phosphatase treatment of testis ribosomes. We revealed that the predicted S/T sites of phosphorylation in the individual orthologous IDRs of gNAC-β sequences of Drosophila species are positionally conserved despite these disordered regions are drastically different. We propose the IDR-dependent molecular crowding and specific coordination of NAC and other proteostasis regulatory factors at the ribosomes of germinal cells. Our findings imply that there may be a functional crosstalk between the germinal and ubiquitous α- and β-subunits based on assessing their depletion effects on the fly viability and gonad development.

Geometric framework to predict structure from function in neural networks

Neural computation in biological and artificial networks relies on the nonlinear summation of many inputs. The structural connectivity matrix of synaptic weights between neurons is a critical determinant of overall network function, but quantitative links between neural network structure and function are complex and subtle. For example, many networks can give rise to similar functional responses, and the same network can function differently depending on context. Whether certain patterns of synaptic connectivity are required to generate specific network-level computations is largely unknown. Here we introduce a geometric framework for identifying synaptic connections required by steady-state responses in recurrent networks of threshold-linear neurons. Assuming that the number of specified response patterns does not exceed the number of input synapses, we analytically calculate the solution space of all feedforward and recurrent connectivity matrices that can generate the specified responses from the network inputs. A generalization accounting for noise further reveals that the solution space geometry can undergo topological transitions as the allowed error increases, which could provide insight into both neuroscience and machine learning. We ultimately use this geometric characterization to derive certainty conditions guaranteeing a nonzero synapse between neurons. Our theoretical framework could thus be applied to neural activity data to make rigorous anatomical predictions that follow generally from the model architecture.

Systematic expression profiling of Dpr and DIP genes reveals cell surface codes in Drosophila larval motor and sensory neurons

In complex nervous systems, neurons must identify their correct partners to form synaptic connections. The prevailing model to ensure correct recognition posits that cell-surface proteins (CSPs) in individual neurons act as identification tags. Thus, knowing what cells express which CSPs would provide insights into neural development, synaptic connectivity, and nervous system evolution. Here, we investigated expression of Dpr and DIP genes, two CSP subfamilies belonging to the immunoglobulin superfamily, in Drosophila larval motor neurons (MNs), muscles, glia and sensory neurons (SNs) using a collection of GAL4 driver lines. We found that Dpr genes are more broadly expressed than DIP genes in MNs and SNs, and each examined neuron expresses a unique combination of Dpr and DIP genes. Interestingly, many Dpr and DIP genes are not robustly expressed, but are found instead in gradient and temporal expression patterns. In addition, the unique expression patterns of Dpr and DIP genes revealed three uncharacterized MNs. This study sets the stage for exploring the functions of Dpr and DIP genes in Drosophila MNs and SNs and provides genetic access to subsets of neurons.

The two-body problem: Proprioception and motor control across the metamorphic divide

Like a rocket being propelled into space, evolution has engineered flies to launch into adulthood via multiple stages. Flies develop and deploy two distinct bodies, linked by the transformative process of metamorphosis. The fly larva is a soft hydraulic tube that can crawl to find food and avoid predators. The adult fly has a stiff exoskeleton with articulated limbs that enable long-distance navigation and rich social interactions. Because the larval and adult forms are so distinct in structure, they require distinct strategies for sensing and moving the body. The metamorphic divide thus presents an opportunity for comparative analysis of neural circuits. Here, we review recent progress toward understanding the neural mechanisms of proprioception and motor control in larval and adult Drosophila. We highlight commonalities that point toward general principles of sensorimotor control and differences that may reflect unique constraints imposed by biomechanics. Finally, we discuss emerging opportunities for comparative analysis of neural circuit architecture in the fly and other animal species.

Localization of muscarinic acetylcholine receptor-dependent rhythm-generating modules in the Drosophila larval locomotor network

Mechanisms of rhythm generation have been extensively studied in motor systems that control locomotion over terrain in limbed animals; however, much less is known about rhythm generation in soft-bodied terrestrial animals. Here we explored how muscarinic acetylcholine receptor (mAChR)-modulated rhythm-generating networks are distributed in the central nervous system (CNS) of soft-bodied Drosophila larvae. We measured fictive motor patterns in isolated CNS preparations, using a combination of Ca2+ imaging and electrophysiology while manipulating mAChR signaling pharmacologically. Bath application of the mAChR agonist oxotremorine potentiated bilaterally asymmetric activity in anterior thoracic regions and promoted bursting in posterior abdominal regions. Application of the mAChR antagonist scopolamine suppressed rhythm generation in these regions and blocked the effects of oxotremorine. Oxotremorine triggered fictive forward crawling in preparations without brain lobes. Oxotremorine also potentiated rhythmic activity in isolated posterior abdominal CNS segments as well as isolated anterior brain and thoracic regions, but it did not induce rhythmic activity in isolated anterior abdominal segments. Bath application of scopolamine to reduced preparations lowered baseline Ca2+ levels and abolished rhythmic activity. Overall, these results suggest that mAChR signaling plays a role in enabling rhythm generation at multiple sites in the larval CNS. This work furthers our understanding of motor control in soft-bodied locomotion and provides a foundation for study of rhythm-generating networks in an emerging genetically tractable locomotor system.NEW & NOTEWORTHY Using a combination of pharmacology, electrophysiology, and Ca2+ imaging, we find that signaling through mACh receptors plays a critical role in rhythmogenesis in different regions of the Drosophila larval CNS. mAChR-dependent rhythm generators reside in distal regions of the larval CNS and provide functional substrates for central pattern-generating networks (CPGs) underlying headsweep behavior and forward locomotion. This provides new insights into locomotor CPG operation in soft-bodied animals that navigate over terrain.

Single‐cell RNA sequencing of motoneurons identifies regulators of synaptic wiring in Drosophila embryos

The correct wiring of neuronal circuits is one of the most complex processes in development, since axons form highly specific connections out of a vast number of possibilities. Circuit structure is genetically determined in vertebrates and invertebrates, but the mechanisms guiding each axon to precisely innervate a unique pre‐specified target cell are poorly understood. We investigated Drosophila embryonic motoneurons using single‐cell genomics, imaging, and genetics. We show that a cell‐specific combination of homeodomain transcription factors and downstream immunoglobulin domain proteins is expressed in individual cells and plays an important role in determining cell‐specific connections between differentiated motoneurons and target muscles. We provide genetic evidence for a functional role of five homeodomain transcription factors and four immunoglobulins in the neuromuscular wiring. Knockdown and ectopic expression of these homeodomain transcription factors induces cell‐specific synaptic wiring defects that are partly phenocopied by genetic modulations of their immunoglobulin targets. Taken together, our data suggest that homeodomain transcription factor and immunoglobulin molecule expression could be directly linked and function as a crucial determinant of neuronal circuit structure.

Connectomic features underlying diverse synaptic connection strengths and subcellular computation

Connectomes generated from electron microscopy images of neural tissue unveil the complex morphology of every neuron and the locations of every synapse interconnecting them. These wiring diagrams may also enable inference of synaptic and neuronal biophysics, such as the functional weights of synaptic connections, but this requires integration with physiological data to properly parameterize. Working with a stereotyped olfactory network in the Drosophila brain, we make direct comparisons of the anatomy and physiology of diverse neurons and synapses with subcellular and subthreshold resolution. We find that synapse density and location jointly predict the amplitude of the somatic postsynaptic potential evoked by a single presynaptic spike. Biophysical models fit to data predict that electrical compartmentalization allows axon and dendrite arbors to balance independent and interacting computations. These findings begin to fill the gap between connectivity maps and activity maps, which should enable new hypotheses about how network structure constrains network function.

Connectomics: Relating synaptic connectivity to physiology

Synaptic wiring diagrams, or connectomes, promise constraints for highly detailed neural circuit models, but relating the connectivity information they provide to physiological properties is challenging. A new study describes this relationship for a fruit fly neural pathway, suggesting a path forward for future models.

An electrically coupled pioneer circuit enables motor development via proprioceptive feedback in Drosophila embryos

Precocious movements are widely seen in embryos of various animal species. Whether such movements via proprioceptive feedback play instructive roles in motor development or are a mere reflection of activities in immature motor circuits is a long-standing question. Here we image the emerging motor activities in Drosophila embryos that lack proprioceptive feedback and show that proprioceptive experience is essential for the development of locomotor central pattern generators (CPGs). Downstream of proprioceptive inputs, we identify a pioneer premotor circuit composed of two pairs of segmental interneurons, whose gap-junctional transmission requires proprioceptive experience and plays a crucial role in CPG formation. The circuit autonomously generates rhythmic plateau potentials via IP₃-mediated Ca²⁺ release from internal stores, which contribute to muscle contractions and hence produce proprioceptive feedback. Our findings demonstrate the importance of self-generated movements in instructing motor development and identify the cells, circuit, and physiology at the core of this proprioceptive feedback.

Neural development: The role of spontaneous activity

Developing nervous systems exhibit spontaneous activity. Two new studies identify the instructive influence such activity has on the formation of functionally appropriate circuits.

Mechanosensory input during circuit formation shapes Drosophila motor behavior through patterned spontaneous network activity

Neural activity sculpts circuit wiring in many animals. In vertebrates, patterned spontaneous network activity (PaSNA) generates sensory maps and establishes local circuits.1-3 However, it remains unclear how PaSNA might shape neuronal circuits and behavior in invertebrates. Previous work in the developing Drosophila embryo discovered intrinsic muscle activity that did not require synaptic transmission, and hence was myogenic, preceding PaSNA.4-6 These studies, however, monitored muscle movement, not neural activity, and were therefore unable to observe how myogenic activity might relate to subsequent neural network engagement. Here we use calcium imaging to directly record neural activity and characterize the emergence of PaSNA. We demonstrate that the spatiotemporal properties of PaSNA are highly stereotyped across embryos, arguing for genetic programming. Neural activity begins well before it becomes patterned, emerging during the myogenic stage. Remarkably, inhibition of mechanosensory input, as well as inhibition of muscle contractions, results in premature and excessive PaSNA, demonstrating that muscle movement serves as a brake on this process. Finally, transient mechanosensory inhibition during PaSNA, followed by quantitative modeling of larval behavior, shows that mechanosensory modulation during development is required for proper larval foraging. This work provides a foundation for using the Drosophila embryo to study the role of PaSNA in circuit formation, provides mechanistic insight into how PaSNA is entrained by motor activity, and demonstrates that spontaneous network activity is essential for locomotor behavior. These studies argue that sensory feedback during the earliest stages of circuit formation can sculpt locomotor behaviors through innate motor learning.

Regulation of excitation-contraction coupling at the Drosophila neuromuscular junction

The Drosophila neuromuscular system is widely used to characterize synaptic development and function. However, little is known about how specific synaptic alterations effect neuromuscular transduction and muscle contractility, which ultimately dictate behavioural output. Here we develop and use a force transducer system to characterize excitation-contraction coupling at Drosophila larval neuromuscular junctions (NMJs), examining how specific neuronal and muscle manipulations disrupt muscle contractility. Muscle contraction force increased with motoneuron stimulation frequency and duration, showing considerable plasticity between 5 and 40 Hz and saturating above 50 Hz. Endogenous recordings of fictive contractions revealed average motoneuron burst frequencies of 20-30 Hz, consistent with the system operating within this plastic range of contractility. Temperature was also a key factor in muscle contractility, as force was enhanced at lower temperatures and dramatically reduced with increasing temperatures. Pharmacological and genetic manipulations of critical components of Ca²⁺ regulation in both pre- and postsynaptic compartments affected the strength and time course of muscle contractions. A screen for modulators of muscle contractility led to identification and characterization of the molecular and cellular pathway by which the FMRFa peptide, TPAEDFMRFa, increases muscle performance. These findings indicate Drosophila NMJs provide a robust system to correlate synaptic dysfunction, regulation and modulation to alterations in excitation-contraction coupling. KEY POINTS: Larval muscle contraction force increases with stimulation frequency and duration, revealing substantial plasticity between 5 and 40 Hz. Fictive contraction recordings demonstrate endogenous motoneuron burst frequencies consistent with the neuromuscular system operating within the range of greatest plasticity. Genetic and pharmacological manipulations of critical components of pre- and postsynaptic Ca²⁺ regulation significantly affect the strength and time course of muscle contractions. A screen for modulators of the excitation-contraction machinery identified a FMRFa peptide, TPAEDFMRFa and its associated signalling pathway, that dramatically increases muscle performance. Drosophila serves as an excellent model for dissecting components of the excitation-contraction coupling machinery.

Pupal behavior emerges from unstructured muscle activity in response to neuromodulation in Drosophila

Identifying neural substrates of behavior requires defining actions in terms that map onto brain activity. Brain and muscle activity naturally correlate via the output of motor neurons, but apart from simple movements it has been difficult to define behavior in terms of muscle contractions. By mapping the musculature of the pupal fruit fly and comprehensively imaging muscle activation at single-cell resolution, we here describe a multiphasic behavioral sequence in Drosophila. Our characterization identifies a previously undescribed behavioral phase and permits extraction of major movements by a convolutional neural network. We deconstruct movements into a syllabary of co-active muscles and identify specific syllables that are sensitive to neuromodulatory manipulations. We find that muscle activity shows considerable variability, with sequential increases in stereotypy dependent upon neuromodulation. Our work provides a platform for studying whole-animal behavior, quantifying its variability across multiple spatiotemporal scales, and analyzing its neuromodulatory regulation at cellular resolution.

How do we find out how the brain works? One way is to use imaging techniques to visualise an animal’s brain in action as it performs simple behaviours: as the animal moves, parts of its brain light up under the microscope. For laboratory animals like fruit flies, which have relatively small brains, this lets us observe their brain activity right down to the level of individual brain cells.

The brain directs movements via collective activity of the body’s muscles. Our ability to track the activity of individual muscles is, however, more limited than our ability to observe single brain cells: even modern imaging technology still cannot monitor the activity of all the muscle cells in an animal’s body as it moves about. Yet this is precisely the information that scientists need to fully understand how the brain generates behaviour.

Fruit flies perform specific behaviours at certain stages of their life cycle. When the fly pupa begins to metamorphose into an adult insect, it performs a fixed sequence of movements involving a set number of muscles, which is called the pupal ecdysis sequence. This initial movement sequence and the rest of metamorphosis both occur within the confines of the pupal case, which is a small, hardened shell surrounding the whole animal. Elliott et al. set out to determine if the fruit fly pupa’s ecdysis sequence could be used as a kind of model, to describe a simple behaviour at the level of individual muscles.

Imaging experiments used fly pupae that were genetically engineered to produce an activity-dependent fluorescent protein in their muscle cells. Pupal cases were treated with a chemical to make them transparent, allowing easy observation of their visually ‘labelled’ muscles. This yielded a near-complete record of muscle activity during metamorphosis.

Initially, individual muscles became active in small groups. The groups then synchronised with each other over the different regions of the pupa’s body to form distinct movements, much as syllables join to form words. This synchronisation was key to progression through metamorphosis and was co-ordinated at each step by specialised nerve cells that produce or respond to specific hormones.

These results reveal how the brain might direct muscle activity to produce movement patterns. In the future, Elliott et al. hope to compare data on muscle activity with comprehensive records of brain cell activity, to shed new light on how the brain, muscles, and other factors work together to control behaviour.

The Drosophila Larval Locomotor Circuit Provides a Model to Understand Neural Circuit Development and Function

It is difficult to answer important questions in neuroscience, such as: "how do neural circuits generate behaviour?," because research is limited by the complexity and inaccessibility of the mammalian nervous system. Invertebrate model organisms offer simpler networks that are easier to manipulate. As a result, much of what we know about the development of neural circuits is derived from work in crustaceans, nematode worms and arguably most of all, the fruit fly, Drosophila melanogaster. This review aims to demonstrate the utility of the Drosophila larval locomotor network as a model circuit, to those who do not usually use the fly in their work. This utility is explored first by discussion of the relatively complete connectome associated with one identified interneuron of the locomotor circuit, A27h, and relating it to similar circuits in mammals. Next, it is developed by examining its application to study two important areas of neuroscience research: critical periods of development and interindividual variability in neural circuits. In summary, this article highlights the potential to use the larval locomotor network as a "generic" model circuit, to provide insight into mammalian circuit development and function.

Regulation of coordinated muscular relaxation in Drosophila larvae by a pattern-regulating intersegmental circuit

Typical patterned movements in animals are achieved through combinations of contraction and delayed relaxation of groups of muscles. However, how intersegmentally coordinated patterns of muscular relaxation are regulated by the neural circuits remains poorly understood. Here, we identify Canon, a class of higher-order premotor interneurons, that regulates muscular relaxation during backward locomotion of Drosophila larvae. Canon neurons are cholinergic interneurons present in each abdominal neuromere and show wave-like activity during fictive backward locomotion. Optogenetic activation of Canon neurons induces relaxation of body wall muscles, whereas inhibition of these neurons disrupts timely muscle relaxation. Canon neurons provide excitatory outputs to inhibitory premotor interneurons. Canon neurons also connect with each other to form an intersegmental circuit and regulate their own wave-like activities. Thus, our results demonstrate how coordinated muscle relaxation can be realized by an intersegmental circuit that regulates its own patterned activity and sequentially terminates motor activities along the anterior-posterior axis.

A developmental framework linking neurogenesis and circuit formation in the Drosophila CNS

The mechanisms specifying neuronal diversity are well characterized, yet it remains unclear how or if these mechanisms regulate neural circuit assembly. To address this, we mapped the developmental origin of 160 interneurons from seven bilateral neural progenitors (neuroblasts) and identify them in a synapse-scale TEM reconstruction of the Drosophila larval central nervous system. We find that lineages concurrently build the sensory and motor neuropils by generating sensory and motor hemilineages in a Notch-dependent manner. Neurons in a hemilineage share common synaptic targeting within the neuropil, which is further refined based on neuronal temporal identity. Connectome analysis shows that hemilineage-temporal cohorts share common connectivity. Finally, we show that proximity alone cannot explain the observed connectivity structure, suggesting hemilineage/temporal identity confers an added layer of specificity. Thus, we demonstrate that the mechanisms specifying neuronal diversity also govern circuit formation and function, and that these principles are broadly applicable throughout the nervous system.

Training Spiking Neural Networks in the Strong Coupling Regime

Recurrent neural networks trained to perform complex tasks can provide insight into the dynamic mechanism that underlies computations performed by cortical circuits. However, due to a large number of unconstrained synaptic connections, the recurrent connectivity that emerges from network training may not be biologically plausible. Therefore, it remains unknown if and how biological neural circuits implement dynamic mechanisms proposed by the models. To narrow this gap, we developed a training scheme that, in addition to achieving learning goals, respects the structural and dynamic properties of a standard cortical circuit model: strongly coupled excitatory-inhibitory spiking neural networks. By preserving the strong mean excitatory and inhibitory coupling of initial networks, we found that most of trained synapses obeyed Dale's law without additional constraints, exhibited large trial-to-trial spiking variability, and operated in inhibition-stabilized regime. We derived analytical estimates on how training and network parameters constrained the changes in mean synaptic strength during training. Our results demonstrate that training recurrent neural networks subject to strong coupling constraints can result in connectivity structure and dynamic regime relevant to cortical circuits.

Astrocytes close a motor circuit critical period

Critical periods-brief intervals during which neural circuits can be modified by activity-are necessary for proper neural circuit assembly. Extended critical periods are associated with neurodevelopmental disorders; however, the mechanisms that ensure timely critical period closure remain poorly understood^1,2. Here we define a critical period in a developing Drosophila motor circuit and identify astrocytes as essential for proper critical period termination. During the critical period, changes in activity regulate dendrite length, complexity and connectivity of motor neurons. Astrocytes invaded the neuropil just before critical period closure³, and astrocyte ablation prolonged the critical period. Finally, we used a genetic screen to identify astrocyte-motor neuron signalling pathways that close the critical period, including Neuroligin-Neurexin signalling. Reduced signalling destabilized dendritic microtubules, increased dendrite dynamicity and impaired locomotor behaviour, underscoring the importance of critical period closure. Previous work defined astroglia as regulators of plasticity at individual synapses⁴; we show here that astrocytes also regulate motor circuit critical period closure to ensure proper locomotor behaviour.

Anatomy and activity patterns in a multifunctional motor neuron and its surrounding circuits

Dorsal Excitor motor neuron DE-3 in the medicinal leech plays three very different dynamical roles in three different behaviors. Without rewiring its anatomical connectivity, how can a motor neuron dynamically switch roles to play appropriate roles in various behaviors? We previously used voltage-sensitive dye imaging to record from DE-3 and most other neurons in the leech segmental ganglion during (fictive) swimming, crawling, and local-bend escape (Tomina and Wagenaar, 2017). Here, we repeated that experiment, then re-imaged the same ganglion using serial blockface electron microscopy and traced DE-3's processes. Further, we traced back the processes of DE-3's presynaptic partners to their respective somata. This allowed us to analyze the relationship between circuit anatomy and the activity patterns it sustains. We found that input synapses important for all the behaviors were widely distributed over DE-3's branches, yet that functional clusters were different during (fictive) swimming vs. crawling.

Reconstruction of motor control circuits in adult Drosophila using automated transmission electron microscopy

To investigate circuit mechanisms underlying locomotor behavior, we used serial-section electron microscopy (EM) to acquire a synapse-resolution dataset containing the ventral nerve cord (VNC) of an adult female Drosophila melanogaster. To generate this dataset, we developed GridTape, a technology that combines automated serial-section collection with automated high-throughput transmission EM. Using this dataset, we studied neuronal networks that control leg and wing movements by reconstructing all 507 motor neurons that control the limbs. We show that a specific class of leg sensory neurons synapses directly onto motor neurons with the largest-caliber axons on both sides of the body, representing a unique pathway for fast limb control. We provide open access to the dataset and reconstructions registered to a standard atlas to permit matching of cells between EM and light microscopy data. We also provide GridTape instrumentation designs and software to make large-scale EM more accessible and affordable to the scientific community.

Anatomy and Neural Pathways Modulating Distinct Locomotor Behaviors in Drosophila Larva

The control of movements is a fundamental feature shared by all animals. At the most basic level, simple movements are generated by coordinated neural activity and muscle contraction patterns that are controlled by the central nervous system. How behavioral responses to various sensory inputs are processed and integrated by the downstream neural network to produce flexible and adaptive behaviors remains an intense area of investigation in many laboratories. Due to recent advances in experimental techniques, many fundamental neural pathways underlying animal movements have now been elucidated. For example, while the role of motor neurons in locomotion has been studied in great detail, the roles of interneurons in animal movements in both basic and noxious environments have only recently been realized. However, the genetic and transmitter identities of many of these interneurons remains unclear. In this review, we provide an overview of the underlying circuitry and neural pathways required by Drosophila larvae to produce successful movements. By improving our understanding of locomotor circuitry in model systems such as Drosophila, we will have a better understanding of how neural circuits in organisms with different bodies and brains lead to distinct locomotion types at the organism level. The understanding of genetic and physiological components of these movements types also provides directions to understand movements in higher organisms.

Structural and Functional Synaptic Plasticity Induced by Convergent Synapse Loss in the Drosophila Neuromuscular Circuit

Throughout the nervous system, the convergence of two or more presynaptic inputs on a target cell is commonly observed. The question we ask here is to what extent converging inputs influence each other's structural and functional synaptic plasticity. In complex circuits, isolating individual inputs is difficult because postsynaptic cells can receive thousands of inputs. An ideal model to address this question is the Drosophila larval neuromuscular junction (NMJ) where each postsynaptic muscle cell receives inputs from two glutamatergic types of motor neurons (MNs), known as 1b and 1s MNs. Notably, each muscle is unique and receives input from a different combination of 1b and 1s MNs; we surveyed multiple muscles for this reason. Here, we identified a cell-specific promoter that allows ablation of 1s MNs postinnervation and measured structural and functional responses of convergent 1b NMJs using microscopy and electrophysiology. For all muscles examined in both sexes, ablation of 1s MNs resulted in NMJ expansion and increased spontaneous neurotransmitter release at corresponding 1b NMJs. This demonstrates that 1b NMJs can compensate for the loss of convergent 1s MNs. However, only a subset of 1b NMJs showed compensatory evoked neurotransmission, suggesting target-specific plasticity. Silencing 1s MNs led to similar plasticity at 1b NMJs, suggesting that evoked neurotransmission from 1s MNs contributes to 1b synaptic plasticity. Finally, we genetically blocked 1s innervation in male larvae and robust 1b synaptic plasticity was eliminated, raising the possibility that 1s NMJ formation is required to set up a reference for subsequent synaptic perturbations.SIGNIFICANCE STATEMENT In complex neural circuits, multiple convergent inputs contribute to the activity of the target cell, but whether synaptic plasticity exists among these inputs has not been thoroughly explored. In this study, we examined synaptic plasticity in the structurally and functionally tractable Drosophila larval neuromuscular system. In this convergent circuit, each muscle is innervated by a unique pair of motor neurons. Removal of one neuron after innervation causes the adjacent neuron to increase neuromuscular junction outgrowth and functional output. However, this is not a general feature as each motor neuron differentially compensates. Further, robust compensation requires initial coinnervation by both neurons. Understanding how neurons respond to perturbations in adjacent neurons will provide insight into nervous system plasticity in both healthy and disease states.

Development of motor circuits: From neuronal stem cells and neuronal diversity to motor circuit assembly

In this review, we discuss motor circuit assembly starting from neuronal stem cells. Until recently, studies of neuronal stem cells focused on how a relatively small pool of stem cells could give rise to a large diversity of different neuronal identities. Historically, neuronal identity has been assayed in embryos by gene expression, gross anatomical features, neurotransmitter expression, and physiological properties. However, these definitions of identity are largely unlinked to mature functional neuronal features relevant to motor circuits. Such mature neuronal features include presynaptic and postsynaptic partnerships, dendrite morphologies, as well as neuronal firing patterns and roles in behavior. This review focuses on recent work that links the specification of neuronal molecular identity in neuronal stem cells to mature, circuit-relevant identity specification. Specifically, these studies begin to address the question: to what extent are the decisions that occur during motor circuit assembly controlled by the same genetic information that generates diverse embryonic neuronal diversity? Much of the research addressing this question has been conducted using the Drosophila larval motor system. Here, we focus largely on Drosophila motor circuits and we point out parallels to other systems. And we highlight outstanding questions in the field. The main concepts addressed in this review are: (1) the description of temporal cohorts-novel units of developmental organization that link neuronal stem cell lineages to motor circuit configuration and (2) the discovery that temporal transcription factors expressed in neuronal stem cells control aspects of circuit assembly by controlling the size of temporal cohorts and influencing synaptic partner choice.

Synaptic Properties and Plasticity Mechanisms of Invertebrate Tonic and Phasic Neurons

Defining neuronal cell types and their associated biophysical and synaptic diversity has become an important goal in neuroscience as a mechanism to create comprehensive brain cell atlases in the post-genomic age. Beyond broad classification such as neurotransmitter expression, interneuron vs. pyramidal, sensory or motor, the field is still in the early stages of understanding closely related cell types. In both vertebrate and invertebrate nervous systems, one well-described distinction related to firing characteristics and synaptic release properties are tonic and phasic neuronal subtypes. In vertebrates, these classes were defined based on sustained firing responses during stimulation (tonic) vs. transient responses that rapidly adapt (phasic). In crustaceans, the distinction expanded to include synaptic release properties, with tonic motoneurons displaying sustained firing and weaker synapses that undergo short-term facilitation to maintain muscle contraction and posture. In contrast, phasic motoneurons with stronger synapses showed rapid depression and were recruited for short bursts during fast locomotion. Tonic and phasic motoneurons with similarities to those in crustaceans have been characterized in Drosophila, allowing the genetic toolkit associated with this model to be used for dissecting the unique properties and plasticity mechanisms for these neuronal subtypes. This review outlines general properties of invertebrate tonic and phasic motoneurons and highlights recent advances that characterize distinct synaptic and plasticity pathways associated with two closely related glutamatergic neuronal cell types that drive invertebrate locomotion.

Useful road maps: studying Drosophila larva's central nervous system with the help of connectomics

The larva of Drosophila melanogaster is emerging as a powerful model system for comprehensive brain-wide understanding of the circuit implementation of neural computations. With an unprecedented amount of tools in hand, including synaptic-resolution connectomics, whole-brain imaging, and genetic tools for selective targeting of single neuron types, it is possible to dissect which circuits and computations are at work behind behaviors that have an interesting level of complexity. Here we present some of the recent advances regarding multisensory integration, learning, and action selection in Drosophila larva.

A neural algorithm for Drosophila linear and nonlinear decision-making

It has been evidenced that vision-based decision-making in Drosophila consists of both simple perceptual (linear) decision and value-based (non-linear) decision. This paper proposes a general computational spiking neural network (SNN) model to explore how different brain areas are connected contributing to Drosophila linear and nonlinear decision-making behavior. First, our SNN model could successfully describe all the experimental findings in fly visual reinforcement learning and action selection among multiple conflicting choices as well. Second, our computational modeling shows that dopaminergic neuron-GABAergic neuron-mushroom body (DA-GABA-MB) works in a recurrent loop providing a key circuit for gain and gating mechanism of nonlinear decision making. Compared with existing models, our model shows more biologically plausible on the network design and working mechanism, and could amplify the small differences between two conflicting cues more clearly. Finally, based on the proposed model, the UAV could quickly learn to make clear-cut decisions among multiple visual choices and flexible reversal learning resembling to real fly. Compared with linear and uniform decision-making methods, the DA-GABA-MB mechanism helps UAV complete the decision-making task with fewer steps.

Comparative Connectomics Reveals How Partner Identity, Location, and Activity Specify Synaptic Connectivity in Drosophila

The mechanisms by which synaptic partners recognize each other and establish appropriate numbers of connections during embryonic development to form functional neural circuits are poorly understood. We combined electron microscopy reconstruction, functional imaging of neural activity, and behavioral experiments to elucidate the roles of (1) partner identity, (2) location, and (3) activity in circuit assembly in the embryonic nerve cord of Drosophila. We found that postsynaptic partners are able to find and connect to their presynaptic partners even when these have been shifted to ectopic locations or silenced. However, orderly positioning of axon terminals by positional cues and synaptic activity is required for appropriate numbers of connections between specific partners, for appropriate balance between excitatory and inhibitory connections, and for appropriate functional connectivity and behavior. Our study reveals with unprecedented resolution the fine connectivity effects of multiple factors that work together to control the assembly of neural circuits.