Organization of the Drosophila larval visual circuit

A machine learning based method for tracking of simultaneously imaged neural activity and body posture of freely moving maggot

To understand neural basis of animal behavior, it is necessary to monitor neural activity and behavior in freely moving animal before building relationship between them. Here we use light sheet fluorescence microscope (LSFM) combined with microfluidic chip to simultaneously capture neural activity and body movement in small freely behaving Drosophila larva. We develop a transfer learning based method to simultaneously track the continuously changing body posture and activity of neurons that move together using a sub-region tracking network with a precise landmark estimation network for the inference of target landmark trajectory. Based on the tracking of each labelled neuron, the activity of the neuron indicated by fluorescent intensity is calculated. For each video, annotation of only 20 frames in a video is sufficient to yield human-level accuracy for all other frames. The validity of this method is further confirmed by reproducing the activity pattern of PMSIs (period-positive median segmental interneurons) and larval movement as previously reported. Using this method, we disclosed the correlation between larval movement and left-right asymmetry in activity of a group of unidentified neurons labelled by R52H01-Gal4 and further confirmed the roles of these neurons in bilateral balance of body contraction during larval crawling by genetic inhibition of these neurons. Our method provides a new tool for accurate extraction of neural activities and movement of freely behaving small-size transparent animals.

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.

Continuous, long-term crawling behavior characterized by a robotic transport system

Detailed descriptions of behavior provide critical insight into the structure and function of nervous systems. In Drosophila larvae and many other systems, short behavioral experiments have been successful in characterizing rapid responses to a range of stimuli at the population level. However, the lack of long-term continuous observation makes it difficult to dissect comprehensive behavioral dynamics of individual animals and how behavior (and therefore the nervous system) develops over time. To allow for long-term continuous observations in individual fly larvae, we have engineered a robotic instrument that automatically tracks and transports larvae throughout an arena. The flexibility and reliability of its design enables controlled stimulus delivery and continuous measurement over developmental time scales, yielding an unprecedented level of detailed locomotion data. We utilize the new system's capabilities to perform continuous observation of exploratory search behavior over a duration of 6 hr with and without a thermal gradient present, and in a single larva for over 30 hr. Long-term free-roaming behavior and analogous short-term experiments show similar dynamics that take place at the beginning of each experiment. Finally, characterization of larval thermotaxis in individuals reveals a bimodal distribution in navigation efficiency, identifying distinct phenotypes that are obfuscated when only analyzing population averages.

Bisected graph matching improves automated pairing of bilaterally homologous neurons from connectomes

Graph matching algorithms attempt to find the best correspondence between the nodes of two networks. These techniques have been used to match individual neurons in nanoscale connectomes-in particular, to find pairings of neurons across hemispheres. However, since graph matching techniques deal with two isolated networks, they have only utilized the ipsilateral (same hemisphere) subgraphs when performing the matching. Here, we present a modification to a state-of-the-art graph matching algorithm that allows it to solve what we call the bisected graph matching problem. This modification allows us to leverage the connections between the brain hemispheres when predicting neuron pairs. Via simulations and experiments on real connectome datasets, we show that this approach improves matching accuracy when sufficient edge correlation is present between the contralateral (between hemisphere) subgraphs. We also show how matching accuracy can be further improved by combining our approach with previously proposed extensions to graph matching, which utilize edge types and previously known neuron pairings. We expect that our proposed method will improve future endeavors to accurately match neurons across hemispheres in connectomes, and be useful in other applications where the bisected graph matching problem arises.

Multi-neuronal recording in unrestrained animals with all acousto-optic random-access line-scanning two-photon microscopy

To understand how neural activity encodes and coordinates behavior, it is desirable to record multi-neuronal activity in freely behaving animals. Imaging in unrestrained animals is challenging, especially for those, like larval Drosophila melanogaster, whose brains are deformed by body motion. A previously demonstrated two-photon tracking microscope recorded from individual neurons in freely crawling Drosophila larvae but faced limits in multi-neuronal recording. Here we demonstrate a new tracking microscope using acousto-optic deflectors (AODs) and an acoustic GRIN lens (TAG lens) to achieve axially resonant 2D random access scanning, sampling along arbitrarily located axial lines at a line rate of 70 kHz. With a tracking latency of 0.1 ms, this microscope recorded activities of various neurons in moving larval Drosophila CNS and VNC including premotor neurons, bilateral visual interneurons, and descending command neurons. This technique can be applied to the existing two-photon microscope to allow for fast 3D tracking and scanning.

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.

Continuous, long-term crawling behavior characterized by a robotic transport system

Detailed descriptions of behavior provide critical insight into the structure and function of nervous systems. In Drosophila larvae and many other systems, short behavioral experiments have been successful in characterizing rapid responses to a range of stimuli at the population level. However, the lack of long-term continuous observation makes it difficult to dissect comprehensive behavioral dynamics of individual animals and how behavior (and therefore the nervous system) develops over time. To allow for long-term continuous observations in individual fly larvae, we have engineered a robotic instrument that automatically tracks and transports larvae throughout an arena. The flexibility and reliability of its design enables controlled stimulus delivery and continuous measurement over developmental time scales, yielding an unprecedented level of detailed locomotion data. We utilize the new system’s capabilities to perform continuous observation of exploratory behavior over a duration of six hours with and without a thermal gradient present, and in a single larva for over 30 hours. Long-term free-roaming behavior and analogous short-term experiments show similar dynamics that take place at the beginning of each experiment. Finally, characterization of larval thermotaxis in individuals reveals a bimodal distribution in navigation efficiency, identifying distinct phenotypes that are obfuscated when only analyzing population averages.

Modeling the Evolution of Biological Neural Networks Based on Caenorhabditis elegans Connectomes across Development

Knowledge of the structural properties of biological neural networks can help in understanding how particular responses and actions are generated. Recently, Witvliet et al. published the connectomes of eight isogenic Caenorhabditis elegans hermaphrodites at different postembryonic ages, from birth to adulthood. We analyzed the basic structural properties of these biological neural networks. From birth to adulthood, the asymmetry between in-degrees and out-degrees over the C. elegans neuronal network increased with age, in addition to an increase in the number of nodes and edges. The degree distributions were neither Poisson distributions nor pure power-law distributions. We have proposed a model of network evolution with different initial attractiveness for in-degrees and out-degrees of nodes and preferential attachment, which reproduces the asymmetry between in-degrees and out-degrees and similar degree distributions via the tuning of the initial attractiveness values. In this study, we present the well-preserved structural properties of C. elegans neuronal networks across development, and provide some insight into understanding the evolutionary processes of biological neural networks through a simple network model.

Circuit analysis reveals a neural pathway for light avoidance in Drosophila larvae

Understanding how neural circuits underlie behaviour is challenging even in the connectome era because it requires a combination of anatomical and functional analyses. This is exemplified in the circuit underlying the light avoidance behaviour displayed by Drosophila melanogaster larvae. While this behaviour is robust and the nervous system relatively simple, the circuit is only partially delineated with some contradictions among studies. Here, we devise trans-Tango MkII, an offshoot of the transsynaptic circuit tracing tool trans-Tango, and implement it in anatomical tracing together with functional analysis. We use neuronal inhibition to test necessity of particular neuronal types in light avoidance and selective neuronal activation to examine sufficiency in rescuing light avoidance deficiencies exhibited by photoreceptor mutants. Our studies reveal a four-order circuit for light avoidance connecting the light-detecting photoreceptors with a pair of neuroendocrine cells via two types of clock neurons. This approach can be readily expanded to studying other circuits.

Studying neural circuits requires a multipronged approach. Here, the authors present a transsynaptic tracing tool in fruit fly larvae and combine it with neuronal inhibition and activation to study the circuit underlying light avoidance behaviour.

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.

Sensory neuroecology and multimodal evolution across the genus Drosophila

The neural basis and genetic mechanisms for sensory evolution are increasingly being explored in depth across many closely related members of the Drosophila genus. This has, in part, been achieved due to the immense efforts toward adapting gene-editing technologies for additional, non-model species. Studies targeting both peripheral sensory variations, as well as interspecies divergence in coding or neural connectivity, have generated numerous, tangible examples of how and where the evolution of sensory-driven animal behavior has occurred. Here, we review and discuss studies that each aim to identify the neurobiological and genetic components of sensory system evolution to provide a comparative overview of the types of functional variations observed across both perceptual input and behavioral output. In addition, we examined the roles neuroecology and neuroevolution play in speciation events, such as courtship and intraspecies communication, as well as those aspects related to behavioral divergence in host navigation or egg-laying preferences. Through the investigation of comparative, large-scale trends and correlations across diverse, yet closely related species within this highly ecologically variable genus of flies, we can begin to describe the underlying pressures, mechanisms, and constraints that have guided sensory and nervous system evolution within the natural environments of these organisms.

---Connectomic analysis of the Drosophila lateral neuron clock cells reveals the synaptic basis of functional pacemaker classes

The circadian clock orchestrates daily changes in physiology and behavior to ensure internal temporal order and optimal timing across the day. In animals, a central brain clock coordinates circadian rhythms throughout the body and is characterized by a remarkable robustness that depends on synaptic connections between constituent neurons. The clock neuron network of Drosophila, which shares network motifs with clock networks in the mammalian brain yet is built of many fewer neurons, offers a powerful model for understanding the network properties of circadian timekeeping. Here, we report an assessment of synaptic connectivity within a clock network, focusing on the critical lateral neuron (LN) clock neuron classes within the Janelia hemibrain dataset. Our results reveal that previously identified anatomical and functional subclasses of LNs represent distinct connectomic types. Moreover, we identify a small number of non-clock cell subtypes representing highly synaptically coupled nodes within the clock neuron network. This suggests that neurons lacking molecular timekeeping likely play integral roles within the circadian timekeeping network. To our knowledge, this represents the first comprehensive connectomic analysis of a circadian neuronal network.

Most organisms on Earth possess an internal timekeeping system which ensures that bodily processes such as sleep, wakefulness or digestion take place at the right time. These precise daily rhythms are kept in check by a master clock in the brain. There, thousands of neurons – some of which carrying an internal ‘molecular clock’ – connect to each other through structures known as synapses. Exactly how the resulting network is organised to support circadian timekeeping remains unclear.

To explore this question, Shafer, Gutierrez et al. focused on fruit flies, as recent efforts have systematically mapped every neuron and synaptic connection in the brain of this model organism. Analysing available data from the hemibrain connectome project at Janelia revealed that that the neurons with the most important timekeeping roles were in fact forming the fewest synapses within the network. In addition, neurons without internal molecular clocks mediated strong synaptic connections between those that did, suggesting that ‘clockless’ cells still play an integral role in circadian timekeeping.

With this research, Shafer, Gutierrez et al. provide unexpected insights into the organisation of the master body clock. Better understanding the networks that underpin circadian rhythms will help to grasp how and why these are disrupted in obesity, depression and Alzheimer’s disease.

High-throughput automated methods for classical and operant conditioning of Drosophila larvae

Learning which stimuli (classical conditioning) or which actions (operant conditioning) predict rewards or punishments can improve chances of survival. However, the circuit mechanisms that underlie distinct types of associative learning are still not fully understood. Automated, high-throughput paradigms for studying different types of associative learning, combined with manipulation of specific neurons in freely behaving animals, can help advance this field. The Drosophila melanogaster larva is a tractable model system for studying the circuit basis of behaviour, but many forms of associative learning have not yet been demonstrated in this animal. Here, we developed a high-throughput (i.e. multi-larva) training system that combines real-time behaviour detection of freely moving larvae with targeted opto- and thermogenetic stimulation of tracked animals. Both stimuli are controlled in either open- or closed-loop, and delivered with high temporal and spatial precision. Using this tracker, we show for the first time that Drosophila larvae can perform classical conditioning with no overlap between sensory stimuli (i.e. trace conditioning). We also demonstrate that larvae are capable of operant conditioning by inducing a bend direction preference through optogenetic activation of reward-encoding serotonergic neurons. Our results extend the known associative learning capacities of Drosophila larvae. Our automated training rig will facilitate the study of many different forms of associative learning and the identification of the neural circuits that underpin them.

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.

Critical periods shaping the social brain: A perspective from Drosophila

Many sensory processing regions of the central brain undergo critical periods of experience-dependent plasticity. During this time ethologically relevant information shapes circuit structure and function. The mechanisms that control critical period timing and duration are poorly understood, and this is of special importance for those later periods of development, which often give rise to complex cognitive functions such as social behavior. Here, we review recent findings in Drosophila, an organism that has some unique experimental advantages, and introduce novel views for manipulating plasticity in the post-embryonic brain. Critical periods in larval and young adult flies resemble classic vertebrate models with distinct onset and termination, display clear connections with complex behaviors, and provide opportunities to control the time course of plasticity. These findings may extend our knowledge about mechanisms underlying extension and reopening of critical periods, a concept that has great relevance to many human neurodevelopmental disorders.

Neuron-glia interaction in the Drosophila nervous system

Animals are able to move and react in manifold ways to external stimuli. Thus, environmental stimuli need to be detected, information must be processed, and, finally, an output decision must be transmitted to the musculature to get the animal moving. All these processes depend on the nervous system which comprises an intricate neuronal network and many glial cells. Glial cells have an equally important contribution in nervous system function as their neuronal counterpart. Manifold roles are attributed to glia ranging from controlling neuronal cell number and axonal pathfinding to regulation of synapse formation, function, and plasticity. Glial cells metabolically support neurons and contribute to the blood-brain barrier. All of the aforementioned aspects require extensive cell-cell interactions between neurons and glial cells. Not surprisingly, many of these processes are found in all phyla executed by evolutionarily conserved molecules. Here, we review the recent advance in understanding neuron-glia interaction in Drosophila melanogaster to suggest that work in simple model organisms will shed light on the function of mammalian glial cells, too.

Circadian and Genetic Modulation of Visually-Guided Navigation in Drosophila Larvae

Organisms possess an endogenous molecular clock which enables them to adapt to environmental rhythms and to synchronize their metabolism and behavior accordingly. Circadian rhythms govern daily oscillations in numerous physiological processes, and the underlying molecular components have been extensively described from fruit flies to mammals. Drosophila larvae have relatively simple nervous system compared to their adult counterparts, yet they both share a homologous molecular clock with mammals, governed by interlocking transcriptional feedback loops with highly conserved constituents. Larvae exhibit a robust light avoidance behavior, presumably enabling them to avoid predators and desiccation, and DNA-damage by exposure to ultraviolet light, hence are crucial for survival. Circadian rhythm has been shown to alter light-dark preference, however it remains unclear how distinct behavioral strategies are modulated by circadian time. To address this question, we investigate the larval visual navigation at different time-points of the day employing a computer-based tracking system, which allows detailed evaluation of distinct navigation strategies. Our results show that due to circadian modulation specific to light information processing, larvae avoid light most efficiently at dawn, and a functioning clock mechanism at both molecular and neuro-signaling level is necessary to conduct this modulation.

Visualisation of ribosomes in Drosophila axons using Ribo-BiFC

The distribution of assembled, and potentially translating, ribosomes within cells can be visualised in Drosophila by using Bimolecular Fluorescence Complementation (BiFC) to monitor the interaction between tagged pairs of 40S and 60S ribosomal proteins (RPs) that are close neighbours across inter-subunit junctions in the assembled 80S ribosome. Here we describe transgenes expressing two novel RP pairs tagged with Venus-based BiFC fragments that considerably increase the sensitivity of this technique we termed Ribo-BiFC. This improved method should provide a convenient way of monitoring the local distribution of ribosomes in most Drosophila cells and we suggest that it could be implemented in other organisms. We visualised 80S ribosomes in different neurons, particularly photoreceptors in the larva, pupa and adult brain. Assembled ribosomes are most abundant in the various neuronal cell bodies, but they are also present along the full length of axons. They are concentrated in growth cones of developing photoreceptors and are apparent at the terminals of mature larval photoreceptors targeting the larval optical neuropil. Surprisingly, there is relatively less puromycin incorporation in the distal portion of axons in the larval optic stalk, suggesting that some of the ribosomes that have initiated translation may not be engaged in elongation in growing axons.This article has an associated First Person interview with the first author of the paper.

Linking physiological processes and feeding behaviors by octopamine

The biogenic amine octopamine and to some extent its precursor tyramine function as an alerting signal in insects. Octopaminergic/tyraminergic neurons arborize in most parts of the central nervous system and additionally reach almost all peripheral organs, tissues, and muscles. Indeed, octopamine is involved in motivation, arousal, and the initiation of different behaviors reflecting its function as an alerting signal. A well-studied example of octopamine function is feeding behavior in Drosophila. Here, the amine is involved in food search, sugar/bitter sensitivity, food intake, and starvation-induced hyperactivity. Thereby octopamine modulates feeding initiation in response to internal needs and external stimuli. Additionally, it seems that octopamine/tyramine orchestrate behaviors such as locomotion and feeding or flight and song production to adapt the behavioral outcome of an animal to physiological and environmental conditions. There is a possibility that octopamine and tyramine are required in the selection of behaviors in insects.

Muscarinic acetylcholine receptor signaling generates OFF selectivity in a simple visual circuit

ON and OFF selectivity in visual processing is encoded by parallel pathways that respond to either light increments or decrements. Despite lacking the anatomical features to support split channels, Drosophila larvae effectively perform visually-guided behaviors. To understand principles guiding visual computation in this simple circuit, we focus on investigating the physiological properties and behavioral relevance of larval visual interneurons. We find that the ON vs. OFF discrimination in the larval visual circuit emerges through light-elicited cholinergic signaling that depolarizes a cholinergic interneuron (cha-lOLP) and hyperpolarizes a glutamatergic interneuron (glu-lOLP). Genetic studies further indicate that muscarinic acetylcholine receptor (mAchR)/Gαo signaling produces the sign-inversion required for OFF detection in glu-lOLP, the disruption of which strongly impacts both physiological responses of downstream projection neurons and dark-induced pausing behavior. Together, our studies identify the molecular and circuit mechanisms underlying ON vs. OFF discrimination in the Drosophila larval visual system.

Drosophila larvae are able to perform visually-guided behaviours yet the molecular and circuit mechanisms for discriminating changes in light intensity are not known. Here, the authors report that ON versus OFF discrimination results from opposing cholinergic and glutamatergic mechanisms.

Constraining computational models using electron microscopy wiring diagrams

Numerous efforts to generate "connectomes," or synaptic wiring diagrams, of large neural circuits or entire nervous systems are currently underway. These efforts promise an abundance of data to guide theoretical models of neural computation and test their predictions. However, there is not yet a standard set of tools for incorporating the connectivity constraints that these datasets provide into the models typically studied in theoretical neuroscience. This article surveys recent approaches to building models with constrained wiring diagrams and the insights they have provided. It also describes challenges and the need for new techniques to scale these approaches to ever more complex datasets.

Whole-animal connectomes of both Caenorhabditis elegans sexes

Knowledge of connectivity in the nervous system is essential to understanding its function. Here we describe connectomes for both adult sexes of the nematode Caenorhabditis elegans, an important model organism for neuroscience research. We present quantitative connectivity matrices that encompass all connections from sensory input to end-organ output across the entire animal, information that is necessary to model behaviour. Serial electron microscopy reconstructions that are based on the analysis of both new and previously published electron micrographs update previous results and include data on the male head. The nervous system differs between sexes at multiple levels. Several sex-shared neurons that function in circuits for sexual behaviour are sexually dimorphic in structure and connectivity. Inputs from sex-specific circuitry to central circuitry reveal points at which sexual and non-sexual pathways converge. In sex-shared central pathways, a substantial number of connections differ in strength between the sexes. Quantitative connectomes that include all connections serve as the basis for understanding how complex, adaptive behavior is generated.

A Plastic Visual Pathway Regulates Cooperative Behavior in Drosophila Larvae

Cooperative behavior emerges in biological systems through coordinated actions among individuals [1, 2]. Although widely observed across animal species, the cellular and molecular mechanisms underlying the establishment and maintenance of cooperative behaviors remain largely unknown [3]. To characterize the circuit mechanisms serving the needs of independent individuals and social groups, we investigated cooperative digging behavior in Drosophila larvae [4-6]. Although chemical and mechanical sensations are important for larval aggregation at specific sites [7-9], an individual larva's ability to participate in a cooperative burrowing cluster relies on direct visual input as well as visual and social experience during development. In addition, vision modulates cluster dynamics by promoting coordinated movements between pairs of larvae [5]. To determine the specific pathways within the larval visual circuit underlying cooperative social clustering, we examined larval photoreceptors (PRs) and the downstream local interneurons (lOLPs) using anatomical and functional studies [10, 11]. Our results indicate that rhodopsin-6-expressing-PRs (Rh6-PRs) and lOLPs are required for both cooperative clustering and movement detection. Remarkably, visual deprivation and social isolation strongly impact the structural and functional connectivity between Rh6-PRs and lOLPs, while at the same time having no effect on the adjacent rhodopsin-5-expressing PRs (Rh5-PRs). Together, our findings demonstrate that a specific larval visual pathway involved in social interactions undergoes experience-dependent modifications during development, suggesting that plasticity in sensory circuits could act as the cellular substrate for social learning, a possible mechanism allowing an animal to integrate into a malleable social environment and engage in complex social behaviors.

Parallel visual circuitry in a basal chordate

A common CNS architecture is observed in all chordates, from vertebrates to basal chordates like the ascidian Ciona. Ciona stands apart among chordates in having a complete larval connectome. Starting with visuomotor circuits predicted by the Ciona connectome, we used expression maps of neurotransmitter use with behavioral assays to identify two parallel visuomotor circuits that are responsive to different components of visual stimuli. The first circuit is characterized by glutamatergic photoreceptors and responds to the direction of light. These photoreceptors project to cholinergic motor neurons, via two tiers of cholinergic interneurons. The second circuit responds to changes in ambient light and mediates an escape response. This circuit uses GABAergic photoreceptors which project to GABAergic interneurons, and then to cholinergic interneurons. Our observations on the behavior of larvae either treated with a GABA receptor antagonist or carrying a mutation that eliminates photoreceptors indicate the second circuit is disinhibitory.

Neural Substrates of Drosophila Larval Anemotaxis

Animals use sensory information to move toward more favorable conditions. Drosophila larvae can move up or down gradients of odors (chemotax), light (phototax), and temperature (thermotax) by modulating the probability, direction, and size of turns based on sensory input. Whether larvae can anemotax in gradients of mechanosensory cues is unknown. Further, although many of the sensory neurons that mediate taxis have been described, the central circuits are not well understood. Here, we used high-throughput, quantitative behavioral assays to demonstrate Drosophila larvae anemotax in gradients of wind speeds and to characterize the behavioral strategies involved. We found that larvae modulate the probability, direction, and size of turns to move away from higher wind speeds. This suggests that similar central decision-making mechanisms underlie taxis in somatosensory and other sensory modalities. By silencing the activity of single or very few neuron types in a behavioral screen, we found two sensory (chordotonal and multidendritic class III) and six nerve cord neuron types involved in anemotaxis. We reconstructed the identified neurons in an electron microscopy volume that spans the entire larval nervous system and found they received direct input from the mechanosensory neurons or from each other. In this way, we identified local interneurons and first- and second-order subesophageal zone (SEZ) and brain projection neurons. Finally, silencing a dopaminergic brain neuron type impairs anemotaxis. These findings suggest that anemotaxis involves both nerve cord and brain circuits. The candidate neurons and circuitry identified in our study provide a basis for future detailed mechanistic understanding of the circuit principles of anemotaxis.

A disinhibitory mechanism biases Drosophila innate light preference

Innate preference toward environmental conditions is crucial for animal survival. Although much is known about the neural processing of sensory information, how the aversive or attractive sensory stimulus is transformed through central brain neurons into avoidance or approaching behavior is largely unclear. Here we show that Drosophila larval light preference behavior is regulated by a disinhibitory mechanism. In the disinhibitory circuit, a pair of GABAergic neurons exerts tonic inhibition on one pair of contralateral projecting neurons that control larval reorientation behavior. When a larva enters the light area, the reorientation-controlling neurons are disinhibited to allow reorientation to occur as the upstream inhibitory neurons are repressed by light. When the larva exits the light area, the inhibition on the downstream neurons is restored to repress further reorientation and thus prevents the larva from re-entering the light area. We suggest that disinhibition may serve as a common neural mechanism for animal innate preference behavior.

The Drosophila NCAM homolog Fas2 signals independent of adhesion

The development of tissues and organs requires close interaction of cells. To do so, cells express adhesion proteins such as the neural cell adhesion molecule (NCAM) or its Drosophila orthologue Fasciclin 2 (Fas2). Both are members of the Ig-domain superfamily of proteins that mediate homophilic adhesion. These proteins are expressed as different isoforms differing in their membrane anchorage and their cytoplasmic domains. To study the function of single isoforms we have conducted a comprehensive genetic analysis of fas2. We reveal the expression pattern of all major Fas2 isoforms, two of which are GPI-anchored. The remaining five isoforms carry transmembrane domains with variable cytoplasmic tails. We generated fas2 mutants expressing only single isoforms. In contrast to the null mutation which causes embryonic lethality, these mutants are viable, indicating redundancy among the different isoforms. Cell type specific rescue experiments showed that glial secreted Fas2 can rescue the fas2 mutant phenotype to viability. This demonstrates cytoplasmic Fas2 domains have no apparent essential functions and indicate that Fas2 has function(s) other than homophilic adhesion. In conclusion, our data propose novel mechanistic aspects of a long studied adhesion protein.

Two Pairs of Drosophila Central Brain Neurons Mediate Larval Navigational Strategies Based on Temporal Light Information Processing

Some animals are attracted by sun light, others are highly repulsed by it. Especially for slowly moving animals, such as Drosophila larvae, direct sunlight may be perceived as noxious stimulus as it increases the risk of desiccation, DNA-damaging by UV-light and exposure to predators. For several reasons, model organisms like Drosophila larvae are well-suited for investigating how light cues are translated into an appropriate behavioral output. First, many of the genetic tools, which were created for use in adult fruit flies, work also in larvae. Second, the lower number of cells in Drosophila larvae compared to adults makes this system adequate for reconstructing neural circuits. Third, the relatively simple behavioral repertoire of larvae facilitates the study of basic functions like navigation with regards to light. Larvae navigate robustly away from a light source by the use of several sophisticated behavioral strategies which are based on temporal or spatial information processing. Two central brain neurons, the NP394-neurons, are highly important for larval light avoidance. It was even reported that these cells seem to play a functional role in a putative larval light preference switch right before pupation. However, the exact function of the NP394-neurons in light navigation remains unknown. We here show that the functional role of NP394-neurons in larval light navigation is restricted to behaviors based on temporal information processing, but not for spatial navigation.

WB. Verifying, Challenging, and Discovering New Synapses Among Fully EM-Reconstructed Neurons in the Leech Ganglion

Neural circuits underpin the production of animal behavior, largely based upon the precise pattern of synaptic connectivity among the neurons involved. For large numbers of neurons, determining such "connectomes" by direct physiological means is difficult, as physiological accessibility is ultimately required to verify and characterize the function of synapses. We collected a volume of images spanning an entire ganglion of the juvenile leech nervous system via serial blockface electron microscopy (SBEM). We validated this approach by reconstructing a well-characterized circuit of motor neurons involved in the swimming behavior of the leech by locating the synapses among them. We confirm that there are multiple synaptic contacts between connected pairs of neurons in the leech, and that these synapses are widely distributed across the region of neuropil in which the neurons' arbors overlap. We verified the anatomical existence of connections that had been described physiologically among longitudinal muscle motor neurons. We also found that some physiological connections were not present anatomically. We then drew upon the SBEM dataset to design additional physiological experiments. We reconstructed an uncharacterized neuron and one of its presynaptic partners identified from the SBEM dataset. We subsequently interrogated this cell pair via intracellular electrophysiology in an adult ganglion and found that the anatomically-discovered synapse was also functional physiologically. Our findings demonstrate the value of combining a connectomics approach with electrophysiology in the leech nervous system.

Recording Neural Activity in Unrestrained Animals with Three-Dimensional Tracking Two-Photon Microscopy

Optical recordings of neural activity in behaving animals can reveal the neural correlates of decision making, but brain motion, which often accompanies behavior, compromises these measurements. Two-photon point-scanning microscopy is especially sensitive to motion artifacts, and two-photon recording of activity has required rigid coupling between the brain and microscope. We developed a two-photon tracking microscope with extremely low-latency (360 μs) feedback implemented in hardware. This microscope can maintain continuous focus on neurons moving with velocities of 3 mm/s and accelerations of 1 m/s2 both in-plane and axially. We recorded calcium dynamics of motor neurons and inter-neurons in unrestrained freely behaving fruit fly larvae, correlating neural activity with stimulus presentations and behavioral outputs, and we measured light-induced depolarization of a visual interneuron in a moving animal using a genetically encoded voltage indicator. Our technique can be extended to stabilize recordings in a variety of moving substrates.

Statistical modelling of navigational decisions based on intensity versus directionality in Drosophila larval phototaxis

Organisms use environmental cues for directed navigation. Understanding the basic logic behind navigational decisions critically depends on the complexity of the nervous system. Due to the comparably simple organization of the nervous system of the fruit fly larva, it stands as a powerful model to study decision-making processes that underlie directed navigation. We have quantitatively measured phototaxis in response to well-defined sensory inputs. Subsequently, we have formulated a statistical stochastic model based on biased Markov chains to characterize the behavioural basis of negative phototaxis. Our experiments show that larvae make navigational decisions depending on two independent physical variables: light intensity and its spatial gradient. Furthermore, our statistical model quantifies how larvae balance two potentially-contradictory factors: minimizing exposure to light intensity and at the same time maximizing their distance to the light source. We find that the response to the light field is manifestly non-linear, and saturates above an intensity threshold. The model has been validated against our experimental biological data yielding insight into the strategy that larvae use to achieve their goal with respect to the navigational cue of light, an important piece of information for future work to study the role of the different neuronal components in larval phototaxis.

Neural circuits driving larval locomotion in Drosophila

More than 30 years of studies into Drosophila melanogaster neurogenesis have revealed fundamental insights into our understanding of axon guidance mechanisms, neural differentiation, and early cell fate decisions. What is less understood is how a group of neurons from disparate anterior-posterior axial positions, lineages and developmental periods of neurogenesis coalesce to form a functional circuit. Using neurogenetic techniques developed in Drosophila it is now possible to study the neural substrates of behavior at single cell resolution. New mapping tools described in this review, allow researchers to chart neural connectivity to better understand how an anatomically simple organism performs complex behaviors.

Photoreceptor specialization and the visuomotor repertoire of the primitive chordate Ciona

The swimming tadpole larva of Ciona has one of the simplest central nervous systems (CNSs) known, with only 177 neurons. Despite its simplicity, the Ciona CNS has a common structure with the CNS of its close chordate relatives, the vertebrates. The recent completion of a larval Ciona CNS connectome creates enormous potential for detailed understanding of chordate CNS function, yet our understanding of Ciona larval behavior is incomplete. We show here that Ciona larvae have a surprisingly rich and dynamic set of visual responses, including a looming-object escape behavior characterized by erratic circular swims, as well as negative phototaxis characterized by sustained directional swims. Making use of mutant lines, we show that these two behaviors are mediated by distinct groups of photoreceptors. The Ciona connectome predicts that these two behavioral responses should act through distinct, but overlapping, visuomotor pathways, and that the escape behavior is likely to be integrated into a broader startle behavior.

Dedicated photoreceptor pathways in Drosophila larvae mediate navigation by processing either spatial or temporal cues

To integrate changing environmental cues with high spatial and temporal resolution is critical for animals to orient themselves. Drosophila larvae show an effective motor program to navigate away from light sources. How the larval visual circuit processes light stimuli to control navigational decision remains unknown. The larval visual system is composed of two sensory input channels, Rhodopsin5 (Rh5) and Rhodopsin6 (Rh6) expressing photoreceptors (PRs). We here characterize how spatial and temporal information are used to control navigation. Rh6-PRs are required to perceive temporal changes of light intensity during head casts, while Rh5-PRs are required to control behaviors that allow navigation in response to spatial cues. We characterize how distinct behaviors are modulated and identify parallel acting and converging features of the visual circuit. Functional features of the larval visual circuit highlight the principle of how early in a sensory circuit distinct behaviors may be computed by partly overlapping sensory pathways.

Learning from connectomics on the fly

Parallels between invertebrates and vertebrates in nervous system development, organisation and circuits are powerful reasons to use insects to study the mechanistic basis of behaviour. The last few years have seen the generation in Drosophila melanogaster of very large light microscopy data sets, genetic driver lines and tools to report or manipulate neural activity. These resources in conjunction with computational tools are enabling large scale characterisation of neuronal types and their functional properties. These are complemented by 3D electron microscopy, providing synaptic resolution data. A whole brain connectome of the fly larva is approaching completion based on manual reconstruction of electron-microscopy data. An adult whole brain dataset is already publicly available and focussed reconstruction is under way, but its 40× greater volume would require ∼500-5000 person-years of manual labour. Nevertheless rapid technical improvements in imaging and especially automated segmentation will likely deliver a complete adult connectome in the next 5 years. To enhance our understanding of the circuit basis of behaviour, light and electron microscopy outputs must be integrated with functional and physiological information into comprehensive databases. We review presently available data, tools and opportunities in Drosophila. We then consider the limits and potential of future progress and how this may impact neuroscience in rich model systems provided by larger insects and vertebrates.

Conserved neural circuit structure across Drosophila larval development revealed by comparative connectomics

During postembryonic development, the nervous system must adapt to a growing body. How changes in neuronal structure and connectivity contribute to the maintenance of appropriate circuit function remains unclear. Previously , we measured the cellular neuroanatomy underlying synaptic connectivity in Drosophila (Schneider-Mizell et al., 2016). Here, we examined how neuronal morphology and connectivity change between first instar and third instar larval stages using serial section electron microscopy. We reconstructed nociceptive circuits in a larva of each stage and found consistent topographically arranged connectivity between identified neurons. Five-fold increases in each size, number of terminal dendritic branches, and total number of synaptic inputs were accompanied by cell type-specific connectivity changes that preserved the fraction of total synaptic input associated with each pre-synaptic partner. We propose that precise patterns of structural growth act to conserve the computational function of a circuit, for example determining the location of a dangerous stimulus.