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Water induced soil erosion has always been a matter of concern in watersheds as they increase the soil vulnerability towards erosion. If unchecked, the eroded material reduces the capability of the river to carry the adequate amount of water and increase the amount of sediments in the watershed area. Determining vulnerability of soil to erosion plays a key role in identifying the extent of fragility and helps in making appropriate plans for conservation. Among various methods present to assess soil erosion vulnerability, there is a need to understand the frequently used methods so far and its advancement with time. Various models have been used in past two decades (1991-2019) and the Revised Universal Soil Loss Equation (RUSLE) is the most used model because of its quantitative ability to estimate the average annual soil loss due to erosion in a watershed and its compatibility with the GIS interface. Different approaches like MCDM, SWAT etc. are being utilised to study soil erosion vulnerability of watersheds. This review showed that the frequently used MCDM method is a Compound Factor (CF) method and that RUSLE is a most used quantitative approach. The review identifies 14 different methods which includes 4 methods which provide quantitative estimation while the other 10 methods are used for qualitative assessment of soil erosion vulnerability. Being the most adopted approach, various modifications of different factors of RUSLE introduced by researchers have made it more efficient with time. This review identifies the trend in advancement of various approaches and methods to study soil erosion vulnerability of watersheds around the world and also how various studies are distributed in the Himalayan and non-Himalayan region. The review also provides an understanding of the status of various current approaches to study soil erosion in a watershed and lists the improvements adopted in the frequently used approaches during 1991 and 2019.

This paper presents the results of an erosion processes research on the territory of the morphological unit of Šutilovacki stream, the prevention measures of same processes, as well as the justification of socio-economic investments and a sensitivity analysis of the economic efficiency parameters. The research includes a period from 2017-2032 year, whereby the evaluation methods of professor Gavrilović are applied in erosion process intensity assessment, on the whole research area, and universal soil loss equation - USLE, on the agricultural land area. Different rates of soil erosion vulnerability are established on the whole research area by applying these methods. Present erosion processes are prevented by the predicted model of future production from the aspect of soil resource protection in the area of the city of Belgrade, by professor Zlatić (1994). Erosion soil losses are significantly diminished and reduced under a tolerable limit, along with the accomplishment of socio-economic justification of investment, examined by the dynamic methods of internal rate of yield, term for the repayment of invested funds, cost-benefit ratio, and net present value. In addition, an analysis of internal rate of yield sensitivity and term for repayment of invested funds are executed. The obtained data indicate justification of the investment.

The process of establishing protected areas in Serbia has been influenced by specific social-economic changes in period after World War II, which have resulted in constant growth of protected area surface and changes in protected area type of manager. Because of that, this research analysis changes in the area of established protected area, through average annual absolute change and average annual exponential growth rate. These elements are important because of estimation of the future growth of protected areas in public and private sectors, as well as for defining the necessary measures for the implementation of defined goals.

The subject of this paper is the influence of anthropogenic factors on the state of erosion in the rural part of the municipality of Voždovac. The aim of the research is the analysis of the influence of the local population on land resources, based on the past and present state of erosion and sediment production, the usage of land resources, as well as natural and mechanical population movements. The municipality of Voždovac is one of the 17 municipalities in Belgrade area, which covers an area of 15,000 ha. The municipal territory includes both urban and rural parts (9216 ha). When it comes to how land resources are used, it is a characteristic example of erosion processes in the mountainous Belgrade area. This paper presents an analysis of the degree of erosion threat to agricultural land in the municipality of Voždovac, including three periods (1971; 1988; 2012), where the method used is the erosion potential method by professor Gavrilović. However, the calculation of sediment yield was made by the method of S. Gavrilović. The analysis of demographic factors pointed to the influence of anthropogenic factors on the state of erosion. Mathematical methods were used - geometric and exponential progression for population projections in 2020 and 2030. The results of this study showed that the intensity of erosion in that area significantly decreased and that it has a tendency of further decline.

In terms of the visible effects of climate change, in Serbia as well as in other countries is present an increase of average annual temperature, reduced amount of precipitation, the occurrence of floods, droughts, forest fires and ice breakage. The aim of the research is to determine the pattern of the trends in the extent of damages from natural hazards in the forests in Serbia, their share in the total forest damage and the impact of temperature and precipitation on the extent of damage from natural hazards in the forests during the researched period. A modelling method was used as a basic scientific method, with an application of trend, regression and correlation analysis, methods of reasoning (abstraction and concretization, analysis and synthesis, induction and deduction, etc.), along with other methods and techniques necessary for obtaining all needed elements (processes, absolute growth, growth rate, etc.). Regardless of the lack of significance in all models, the research results indicate that the damages from natural hazards in the forests in Serbia are expanding, with increased share in total forest damages, which might be related to significantly lower temperatures and higher rainfall (snow-breaks, snow uprooting, ice-breaks, ice uprooting, floods, etc.). [Projekat Ministarstva nauke Republike Srbije, br. 43007: Studies of climate changes and their impact on the environment -monitoring impacts, adaptation and mitigation, sub-project br. 43007/16-III: Socio-economic development, mitigation and adaptation to climate change]

Torrential floods have caused great material and economic damage in Serbia, in the past and even more frequently nowadays. Definitely, the reduction of negative consequences can be achieved by taking preventive measures which include integral basin arrangement. The economic justification of investment in the protection against torrential floods includes a specific approach, especially when it comes to technical facilities in this area. On the basis of the example of flood control on a part of the river Ljuboviđa, variants of protection were selected on the basis of economic criteria. On the basis of the techniques of avoided damage, evaluation of the economic effects of provided embankments for flood control was done using dynamic methods: the cost-benefit relationship and net present value. It was concluded that the second option is more economical, even though it does not protect the whole area from floods, because a part of that role would be taken over by the intended dam in the upper flow of this river.

This paper investigates the issue of the culture of written expression in primary school students. Starting from the fact that teaching practices increasingly points to the fact that knowledge of rules of writing in primary school students presents the weakest link in teaching Serbian language, we sought to describe the problem, point to the possible causes, propose measures and illustrate all this on concrete examples of students' essays. Our microinvestigation showed that primary school students display considerably poorer mastery of rules of writing than previously thought, to the extent that it presents a serious obstacle in language teaching as well as in other areas of educational process.

Motivation: As more behavioural assays are carried out in large-scale experiments on Drosophila larvae, the definitions of the archetypal actions of a larva are regularly refined. In addition, video recording and tracking technologies constantly evolve. Consequently, automatic tagging tools for Drosophila larval behaviour must be retrained to learn new representations from new data. However, existing tools cannot transfer knowledge from large amounts of previously accumulated data. We introduce LarvaTagger, a piece of software that combines a pre-trained deep neural network, providing a continuous latent representation of larva actions for stereotypical behaviour identification, with a graphical user interface to manually tag the behaviour and train new automatic taggers with the updated ground truth., Results: We reproduced results from an automatic tagger with high accuracy, and we demonstrated that pre-training on large databases accelerates the training of a new tagger, achieving similar prediction accuracy using less data., Availability and Implementation: All the code is free and open source. Docker images are also available. See gitlab.pasteur.fr/nyx/LarvaTagger.jl., (© The Author(s) 2024. Published by Oxford University Press.)

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.

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., Competing Interests: EC, MC, LV, SH, BJ, LN, MW, JM, MZ, KK No competing interests declared, (© 2022, Croteau-Chonka, Clayton et al.)

Molecular profiles of neurons influence neural development and function but bridging the gap between genes, circuits, and behavior has been very difficult. Here we used single cell RNAseq to generate a complete gene expression atlas of the Drosophila larval central nervous system composed of 131,077 single cells across three developmental stages (1 h, 24 h and 48 h after hatching). We identify 67 distinct cell clusters based on the patterns of gene expression. These include 31 functional mature larval neuron clusters, 1 ring gland cluster, 8 glial clusters, 6 neural precursor clusters, and 13 developing immature adult neuron clusters. Some clusters are present across all stages of larval development, while others are stage specific (such as developing adult neurons). We identify genes that are differentially expressed in each cluster, as well as genes that are differentially expressed at distinct stages of larval life. These differentially expressed genes provide promising candidates for regulating the function of specific neuronal and glial types in the larval nervous system, or the specification and differentiation of adult neurons. The cell transcriptome Atlas of the Drosophila larval nervous system is a valuable resource for developmental biology and systems neuroscience and provides a basis for elucidating how genes regulate neural development and function., (© 2022. The Author(s).)

The mechanisms that generate neural diversity during development remains largely unknown. Here, we use scRNA-seq methodology to discover new features of the Drosophila larval CNS across several key developmental timepoints. We identify multiple progenitor subtypes - both stem cell-like neuroblasts and intermediate progenitors - that change gene expression across larval development, and report on new candidate markers for each class of progenitors. We identify a pool of quiescent neuroblasts in newly hatched larvae and show that they are transcriptionally primed to respond to the insulin signaling pathway to exit from quiescence, including relevant pathway components in the adjacent glial signaling cell type. We identify candidate "temporal transcription factors" (TTFs) that are expressed at different times in progenitor lineages. Our work identifies many cell type specific genes that are candidates for functional roles, and generates new insight into the differentiation trajectory of larval neurons., (© 2022. The Author(s).)

Animal behavior is shaped both by evolution and by individual experience. Parallel brain pathways encode innate and learned valences of cues, but the way in which they are integrated during action-selection is not well understood. We used electron microscopy to comprehensively map with synaptic resolution all neurons downstream of all mushroom body (MB) output neurons (encoding learned valences) and characterized their patterns of interaction with lateral horn (LH) neurons (encoding innate valences) in Drosophila larva. The connectome revealed multiple convergence neuron types that receive convergent MB and LH inputs. A subset of these receives excitatory input from positive-valence MB and LH pathways and inhibitory input from negative-valence MB pathways. We confirmed functional connectivity from LH and MB pathways and behavioral roles of two of these neurons. These neurons encode integrated odor value and bidirectionally regulate turning. Based on this, we speculate that learning could potentially skew the balance of excitation and inhibition onto these neurons and thereby modulate turning. Together, our study provides insights into the circuits that integrate learned and innate valences to modify behavior., Competing Interests: CE, AF, MW, BA, IA, BC, KE, RG, GS, JV, RF, MG, GJ, AS, JT, AC, MZ No competing interests declared, (© 2021, Eschbach et al.)

Techniques for calcium imaging were first achieved in the mid-1970s, whilst tools to analyse these markers of cellular activity are still being developed and improved. For image analysis, custom tools were developed within labs and until relatively recently, software packages were not widely available between researchers. We will discuss some of the most popular, alongside our preferred, methods for calcium imaging analysis that are now widely available and describe why these protocols are so effective. We will also describe some of the newest innovations in the field that are likely to benefit researchers, particularly as calcium imaging is often an inherently low signal-to-noise method. Although calcium imaging analysis has seen recent advances, particularly following the rise of machine learning, we will end by highlighting the outstanding requirements and questions that hinder further progress, and pose the question of how far we have come in the past sixty years and what can be expected for future development in the field., Competing Interests: No competing interests were disclosed., (Copyright: © 2021 Robbins M et al.)

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., Competing Interests: Declaration of Interests The authors declare no competing interests., (Crown Copyright © 2020. Published by Elsevier Inc. All rights reserved.)

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., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

An adaptive transition from exploring the environment in search of vital resources to exploiting these resources once the search was successful is important to all animals. Here we study the neuronal circuitry that allows larval Drosophila melanogaster of either sex to negotiate this exploration-exploitation transition. We do so by combining Pavlovian conditioning with high-resolution behavioral tracking, optogenetic manipulation of individually identified neurons, and EM data-based analyses of synaptic organization. We find that optogenetic activation of the dopaminergic neuron DAN-i1 can both establish memory during training and acutely terminate learned search behavior in a subsequent recall test. Its activation leaves innate behavior unaffected, however. Specifically, DAN-i1 activation can establish associative memories of opposite valence after paired and unpaired training with odor, and its activation during the recall test can terminate the search behavior resulting from either of these memories. Our results further suggest that in its behavioral significance DAN-i1 activation resembles, but does not equal, sugar reward. Dendrogram analyses of all the synaptic connections between DAN-i1 and its two main targets, the Kenyon cells and the mushroom body output neuron MBON-i1, further suggest that the DAN-i1 signals during training and during the recall test could be delivered to the Kenyon cells and to MBON-i1, respectively, within previously unrecognized, locally confined branching structures. This would provide an elegant circuit motif to terminate search on its successful completion. SIGNIFICANCE STATEMENT In the struggle for survival, animals have to explore their environment in search of food. Once food is found, however, it is adaptive to prioritize exploiting it over continuing a search that would now be as pointless as searching for the glasses you are wearing. This exploration-exploitation trade-off is important for animals and humans, as well as for technical search devices. We investigate which of the only 10,000 neurons of a fruit fly larva can tip the balance in this trade-off, and identify a single dopamine neuron called DAN-i1 that can do so. Given the similarities in dopamine neuron function across the animal kingdom, this may reflect a general principle of how search is terminated once it is successful., (Copyright © 2020 the authors.)

Dopaminergic neurons (DANs) drive learning across the animal kingdom, but the upstream circuits that regulate their activity and thereby learning remain poorly understood. We provide a synaptic-resolution connectome of the circuitry upstream of all DANs in a learning center, the mushroom body of Drosophila larva. We discover afferent sensory pathways and a large population of neurons that provide feedback from mushroom body output neurons and link distinct memory systems (aversive and appetitive). We combine this with functional studies of DANs and their presynaptic partners and with comprehensive circuit modeling. We find that DANs compare convergent feedback from aversive and appetitive systems, which enables the computation of integrated predictions that may improve future learning. Computational modeling reveals that the discovered feedback motifs increase model flexibility and performance on learning tasks. Our study provides the most detailed view to date of biological circuit motifs that support associative learning.

Nervous systems have the ability to select appropriate actions and action sequences in response to sensory cues. The circuit mechanisms by which nervous systems achieve choice, stability and transitions between behaviors are still incompletely understood. To identify neurons and brain areas involved in controlling these processes, we combined a large-scale neuronal inactivation screen with automated action detection in response to a mechanosensory cue in Drosophila larva. We analyzed behaviors from 2.9x105 larvae and identified 66 candidate lines for mechanosensory responses out of which 25 for competitive interactions between actions. We further characterize in detail the neurons in these lines and analyzed their connectivity using electron microscopy. We found the neurons in the mechanosensory network are located in different regions of the nervous system consistent with a distributed model of sensorimotor decision-making. These findings provide the basis for understanding how selection and transition between behaviors are controlled by the nervous system., Competing Interests: The authors have declared that no competing interests exist.

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., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Sensory navigation results from coordinated transitions between distinct behavioral programs. During chemotaxis in the Drosophila melanogaster larva, the detection of positive odor gradients extends runs while negative gradients promote stops and turns. This algorithm represents a foundation for the control of sensory navigation across phyla. In the present work, we identified an olfactory descending neuron, PDM-DN, which plays a pivotal role in the organization of stops and turns in response to the detection of graded changes in odor concentrations. Artificial activation of this descending neuron induces deterministic stops followed by the initiation of turning maneuvers through head casts. Using electron microscopy, we reconstructed the main pathway that connects the PDM-DN neuron to the peripheral olfactory system and to the pre-motor circuit responsible for the actuation of forward peristalsis. Our results set the stage for a detailed mechanistic analysis of the sensorimotor conversion of graded olfactory inputs into action selection to perform goal-oriented navigation., Competing Interests: IT, AK, DT, NF, JT, MZ, AC, ML No competing interests declared, (© 2018, Tastekin et al.)

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.

The brain adaptively integrates present sensory input, past experience, and options for future action. The insect mushroom body exemplifies how a central brain structure brings about such integration. Here we use a combination of systematic single-cell labeling, connectomics, transgenic silencing, and activation experiments to study the mushroom body at single-cell resolution, focusing on the behavioral architecture of its input and output neurons (MBINs and MBONs), and of the mushroom body intrinsic APL neuron. Our results reveal the identity and morphology of almost all of these 44 neurons in stage 3 Drosophila larvae. Upon an initial screen, functional analyses focusing on the mushroom body medial lobe uncover sparse and specific functions of its dopaminergic MBINs, its MBONs, and of the GABAergic APL neuron across three behavioral tasks, namely odor preference, taste preference, and associative learning between odor and taste. Our results thus provide a cellular-resolution study case of how brains organize behavior.

Rapid and efficient escape behaviors in response to noxious sensory stimuli are essential for protection and survival. Yet, how noxious stimuli are transformed to coordinated escape behaviors remains poorly understood. In Drosophila larvae, noxious stimuli trigger sequential body bending and corkscrew-like rolling behavior. We identified a population of interneurons in the nerve cord of Drosophila , termed Down-and-Back (DnB) neurons, that are activated by noxious heat, promote nociceptive behavior, and are required for robust escape responses to noxious stimuli. Electron microscopic circuit reconstruction shows that DnBs are targets of nociceptive and mechanosensory neurons, are directly presynaptic to pre-motor circuits, and link indirectly to Goro rolling command-like neurons. DnB activation promotes activity in Goro neurons, and coincident inactivation of Goro neurons prevents the rolling sequence but leaves intact body bending motor responses. Thus, activity from nociceptors to DnB interneurons coordinates modular elements of nociceptive escape behavior., Competing Interests: AB, KH, TO, CQ, GS, DG, MS, WT, MZ, AC, WG No competing interests declared, (© 2018, Burgos et al.)

Animals adaptively respond to a tactile stimulus by choosing an ethologically relevant behavior depending on the location of the stimuli. Here, we investigate how somatosensory inputs on different body segments are linked to distinct motor outputs in Drosophila larvae. Larvae escape by backward locomotion when touched on the head, while they crawl forward when touched on the tail. We identify a class of segmentally repeated second-order somatosensory interneurons, that we named Wave, whose activation in anterior and posterior segments elicit backward and forward locomotion, respectively. Anterior and posterior Wave neurons extend their dendrites in opposite directions to receive somatosensory inputs from the head and tail, respectively. Downstream of anterior Wave neurons, we identify premotor circuits including the neuron A03a5, which together with Wave, is necessary for the backward locomotion touch response. Thus, Wave neurons match their receptive field to appropriate motor programs by participating in different circuits in different segments., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Associating stimuli with positive or negative reinforcement is essential for survival, but a complete wiring diagram of a higher-order circuit supporting associative memory has not been previously available. Here we reconstruct one such circuit at synaptic resolution, the Drosophila larval mushroom body. We find that most Kenyon cells integrate random combinations of inputs but that a subset receives stereotyped inputs from single projection neurons. This organization maximizes performance of a model output neuron on a stimulus discrimination task. We also report a novel canonical circuit in each mushroom body compartment with previously unidentified connections: reciprocal Kenyon cell to modulatory neuron connections, modulatory neuron to output neuron connections, and a surprisingly high number of recurrent connections between Kenyon cells. Stereotyped connections found between output neurons could enhance the selection of learned behaviours. The complete circuit map of the mushroom body should guide future functional studies of this learning and memory centre.

Visual systems transduce, process and transmit light-dependent environmental cues. Computation of visual features depends on photoreceptor neuron types (PR) present, organization of the eye and wiring of the underlying neural circuit. Here, we describe the circuit architecture of the visual system of Drosophila larvae by mapping the synaptic wiring diagram and neurotransmitters. By contacting different targets, the two larval PR-subtypes create two converging pathways potentially underlying the computation of ambient light intensity and temporal light changes already within this first visual processing center. Locally processed visual information then signals via dedicated projection interneurons to higher brain areas including the lateral horn and mushroom body. The stratified structure of the larval optic neuropil (LON) suggests common organizational principles with the adult fly and vertebrate visual systems. The complete synaptic wiring diagram of the LON paves the way to understanding how circuits with reduced numerical complexity control wide ranges of behaviors., Competing Interests: IL, PF, NG, GN, RF, CS, JT, MZ, AC, SS No competing interests declared, (© 2017, Larderet et al.)

Mapping brain function to brain structure is a fundamental task for neuroscience. For such an endeavour, the Drosophila larva is simple enough to be tractable, yet complex enough to be interesting. It features about 10,000 neurons and is capable of various taxes, kineses and Pavlovian conditioning. All its neurons are currently being mapped into a light-microscopical atlas, and Gal4 strains are being generated to experimentally access neurons one at a time. In addition, an electron microscopic reconstruction of its nervous system seems within reach. Notably, this electron microscope-based connectome is being drafted for a stage 1 larva - because stage 1 larvae are much smaller than stage 3 larvae. However, most behaviour analyses have been performed for stage 3 larvae because their larger size makes them easier to handle and observe. It is therefore warranted to either redo the electron microscopic reconstruction for a stage 3 larva or to survey the behavioural faculties of stage 1 larvae. We provide the latter. In a community-based approach we called the Ol 1 mpiad, we probed stage 1 Drosophila larvae for free locomotion, feeding, responsiveness to substrate vibration, gentle and nociceptive touch, burrowing, olfactory preference and thermotaxis, light avoidance, gustatory choice of various tastants plus odour-taste associative learning, as well as light/dark-electric shock associative learning. Quantitatively, stage 1 larvae show lower scores in most tasks, arguably because of their smaller size and lower speed. Qualitatively, however, stage 1 larvae perform strikingly similar to stage 3 larvae in almost all cases. These results bolster confidence in mapping brain structure and behaviour across developmental stages., Competing Interests: Competing interestsThe authors declare no competing or financial interests., (© 2017. Published by The Company of Biologists Ltd.)

Efforts to map neural circuits have been galvanized by the development of genetic technologies that permit the manipulation of targeted sets of neurons in the brains of freely behaving animals. The success of these efforts relies on the experimenter's ability to target arbitrarily small subsets of neurons for manipulation, but such specificity of targeting cannot routinely be achieved using existing methods. In Drosophila melanogaster , a widely-used technique for refined cell type-specific manipulation is the Split GAL4 system, which augments the targeting specificity of the binary GAL4-UAS (Upstream Activating Sequence) system by making GAL4 transcriptional activity contingent upon two enhancers, rather than one. To permit more refined targeting, we introduce here the "Killer Zipper" (KZip + ), a suppressor that makes Split GAL4 targeting contingent upon a third enhancer. KZip + acts by disrupting both the formation and activity of Split GAL4 heterodimers, and we show how this added layer of control can be used to selectively remove unwanted cells from a Split GAL4 expression pattern or to subtract neurons of interest from a pattern to determine their requirement in generating a given phenotype. To facilitate application of the KZip + technology, we have developed a versatile set of LexA op -KZip + fly lines that can be used directly with the large number of LexA driver lines with known expression patterns. KZip + significantly sharpens the precision of neuronal genetic control available in Drosophila and may be extended to other organisms where Split GAL4-like systems are used., (Copyright © 2017 Dolan et al.)

Even a simple sensory stimulus can elicit distinct innate behaviors and sequences. During sensorimotor decisions, competitive interactions among neurons that promote distinct behaviors must ensure the selection and maintenance of one behavior, while suppressing others. The circuit implementation of these competitive interactions is still an open question. By combining comprehensive electron microscopy reconstruction of inhibitory interneuron networks, modeling, electrophysiology, and behavioral studies, we determined the circuit mechanisms that contribute to the Drosophila larval sensorimotor decision to startle, explore, or perform a sequence of the two in response to a mechanosensory stimulus. Together, these studies reveal that, early in sensory processing, (1) reciprocally connected feedforward inhibitory interneurons implement behavioral choice, (2) local feedback disinhibition provides positive feedback that consolidates and maintains the chosen behavior, and (3) lateral disinhibition promotes sequence transitions. The combination of these interconnected circuit motifs can implement both behavior selection and the serial organization of behaviors into a sequence., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Dopaminergic neurons serve multiple functions, including reinforcement processing during associative learning [1-12]. It is thus warranted to understand which dopaminergic neurons mediate which function. We study larval Drosophila, in which only approximately 120 of a total of 10,000 neurons are dopaminergic, as judged by the expression of tyrosine hydroxylase (TH), the rate-limiting enzyme of dopamine biosynthesis [5, 13]. Dopaminergic neurons mediating reinforcement in insect olfactory learning target the mushroom bodies, a higher-order "cortical" brain region [1-5, 11, 12, 14, 15]. We discover four previously undescribed paired neurons, the primary protocerebral anterior medial (pPAM) neurons. These neurons are TH positive and subdivide the medial lobe of the mushroom body into four distinct subunits. These pPAM neurons are acutely necessary for odor-sugar reward learning and require intact TH function in this process. However, they are dispensable for aversive learning and innate behavior toward the odors and sugars employed. Optogenetical activation of pPAM neurons is sufficient as a reward. Thus, the pPAM neurons convey a likely dopaminergic reward signal. In contrast, DL1 cluster neurons convey a corresponding punishment signal [5], suggesting a cellular division of labor to convey dopaminergic reward and punishment signals. On the level of individually identified neurons, this uncovers an organizational principle shared with adult Drosophila and mammals [1-4, 7, 9, 10] (but see [6]). The numerical simplicity and connectomic tractability of the larval nervous system [16-19] now offers a prospect for studying circuit principles of dopamine function at unprecedented resolution., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Rhythmic motor patterns underlying many types of locomotion are thought to be produced by central pattern generators (CPGs). Our knowledge of how CPG networks generate motor patterns in complex nervous systems remains incomplete, despite decades of work in a variety of model organisms. Substrate borne locomotion in Drosophila larvae is driven by waves of muscular contraction that propagate through multiple body segments. We use the motor circuitry underlying crawling in larval Drosophila as a model to try to understand how segmentally coordinated rhythmic motor patterns are generated. Whereas muscles, motoneurons and sensory neurons have been well investigated in this system, far less is known about the identities and function of interneurons. Our recent study identified a class of glutamatergic premotor interneurons, PMSIs (period-positive median segmental interneurons), that regulate the speed of locomotion. Here, we report on the identification of a distinct class of glutamatergic premotor interneurons called Glutamatergic Ventro-Lateral Interneurons (GVLIs). We used calcium imaging to search for interneurons that show rhythmic activity and identified GVLIs as interneurons showing wave-like activity during peristalsis. Paired GVLIs were present in each abdominal segment A1-A7 and locally extended an axon towards a dorsal neuropile region, where they formed GRASP-positive putative synaptic contacts with motoneurons. The interneurons expressed vesicular glutamate transporter (vGluT) and thus likely secrete glutamate, a neurotransmitter known to inhibit motoneurons. These anatomical results suggest that GVLIs are premotor interneurons that locally inhibit motoneurons in the same segment. Consistent with this, optogenetic activation of GVLIs with the red-shifted channelrhodopsin, CsChrimson ceased ongoing peristalsis in crawling larvae. Simultaneous calcium imaging of the activity of GVLIs and motoneurons showed that GVLIs' wave-like activity lagged behind that of motoneurons by several segments. Thus, GVLIs are activated when the front of a forward motor wave reaches the second or third anterior segment. We propose that GVLIs are part of the feedback inhibition system that terminates motor activity once the front of the motor wave proceeds to anterior segments.

Natural events present multiple types of sensory cues, each detected by a specialized sensory modality. Combining information from several modalities is essential for the selection of appropriate actions. Key to understanding multimodal computations is determining the structural patterns of multimodal convergence and how these patterns contribute to behaviour. Modalities could converge early, late or at multiple levels in the sensory processing hierarchy. Here we show that combining mechanosensory and nociceptive cues synergistically enhances the selection of the fastest mode of escape locomotion in Drosophila larvae. In an electron microscopy volume that spans the entire insect nervous system, we reconstructed the multisensory circuit supporting the synergy, spanning multiple levels of the sensory processing hierarchy. The wiring diagram revealed a complex multilevel multimodal convergence architecture. Using behavioural and physiological studies, we identified functionally connected circuit nodes that trigger the fastest locomotor mode, and others that facilitate it, and we provide evidence that multiple levels of multimodal integration contribute to escape mode selection. We propose that the multilevel multimodal convergence architecture may be a general feature of multisensory circuits enabling complex input-output functions and selective tuning to ecologically relevant combinations of cues.

The identification of active neurons and circuits in vivo is a fundamental challenge in understanding the neural basis of behavior. Genetically encoded calcium (Ca(2+)) indicators (GECIs) enable quantitative monitoring of cellular-resolution activity during behavior. However, such indicators require online monitoring within a limited field of view. Alternatively, post hoc staining of immediate early genes (IEGs) indicates highly active cells within the entire brain, albeit with poor temporal resolution. We designed a fluorescent sensor, CaMPARI, that combines the genetic targetability and quantitative link to neural activity of GECIs with the permanent, large-scale labeling of IEGs, allowing a temporally precise "activity snapshot" of a large tissue volume. CaMPARI undergoes efficient and irreversible green-to-red conversion only when elevated intracellular Ca(2+) and experimenter-controlled illumination coincide. We demonstrate the utility of CaMPARI in freely moving larvae of zebrafish and flies, and in head-fixed mice and adult flies., (Copyright © 2015, American Association for the Advancement of Science.)

Complex animal behaviors are built from dynamical relationships between sensory inputs, neuronal activity, and motor outputs in patterns with strategic value. Connecting these patterns illuminates how nervous systems compute behavior. Here, we study Drosophila larva navigation up temperature gradients toward preferred temperatures (positive thermotaxis). By tracking the movements of animals responding to fixed spatial temperature gradients or random temperature fluctuations, we calculate the sensitivity and dynamics of the conversion of thermosensory inputs into motor responses. We discover three thermosensory neurons in each dorsal organ ganglion (DOG) that are required for positive thermotaxis. Random optogenetic stimulation of the DOG thermosensory neurons evokes behavioral patterns that mimic the response to temperature variations. In vivo calcium and voltage imaging reveals that the DOG thermosensory neurons exhibit activity patterns with sensitivity and dynamics matched to the behavioral response. Temporal processing of temperature variations carried out by the DOG thermosensory neurons emerges in distinct motor responses during thermotaxis.

A single nervous system can generate many distinct motor patterns. Identifying which neurons and circuits control which behaviors has been a laborious piecemeal process, usually for one observer-defined behavior at a time. We present a fundamentally different approach to neuron-behavior mapping. We optogenetically activated 1054 identified neuron lines in Drosophila larvae and tracked the behavioral responses from 37,780 animals. Application of multiscale unsupervised structure learning methods to the behavioral data enabled us to identify 29 discrete, statistically distinguishable, observer-unbiased behavioral phenotypes. Mapping the neural lines to the behavior(s) they evoke provides a behavioral reference atlas for neuron subsets covering a large fraction of larval neurons. This atlas is a starting point for connectivity- and activity-mapping studies to further investigate the mechanisms by which neurons mediate diverse behaviors.

All organisms react to noxious and mechanical stimuli but we still lack a complete understanding of cellular and molecular mechanisms by which somatosensory information is transformed into appropriate motor outputs. The small number of neurons and excellent genetic tools make Drosophila larva an especially tractable model system in which to address this problem. We developed high throughput assays with which we can simultaneously expose more than 1,000 larvae per man-hour to precisely timed noxious heat, vibration, air current, or optogenetic stimuli. Using this hardware in combination with custom software we characterized larval reactions to somatosensory stimuli in far greater detail than possible previously. Each stimulus evoked a distinctive escape strategy that consisted of multiple actions. The escape strategy was context-dependent. Using our system we confirmed that the nociceptive class IV multidendritic neurons were involved in the reactions to noxious heat. Chordotonal (ch) neurons were necessary for normal modulation of head casting, crawling and hunching, in response to mechanical stimuli. Consistent with this we observed increases in calcium transients in response to vibration in ch neurons. Optogenetic activation of ch neurons was sufficient to evoke head casting and crawling. These studies significantly increase our understanding of the functional roles of larval ch neurons. More generally, our system and the detailed description of wild type reactions to somatosensory stimuli provide a basis for systematic identification of neurons and genes underlying these behaviors.

Cbl-associated protein (CAP) localizes to focal adhesions and associates with numerous cytoskeletal proteins; however, its physiological roles remain unknown. Here, we demonstrate that Drosophila CAP regulates the organization of two actin-rich structures in Drosophila: muscle attachment sites (MASs), which connect somatic muscles to the body wall; and scolopale cells, which form an integral component of the fly chordotonal organs and mediate mechanosensation. Drosophila CAP mutants exhibit aberrant junctional invaginations and perturbation of the cytoskeletal organization at the MAS. CAP depletion also results in collapse of scolopale cells within chordotonal organs, leading to deficits in larval vibration sensation and adult hearing. We investigate the roles of different CAP protein domains in its recruitment to, and function at, various muscle subcellular compartments. Depletion of the CAP-interacting protein Vinculin results in a marked reduction in CAP levels at MASs, and vinculin mutants partially phenocopy Drosophila CAP mutants. These results show that CAP regulates junctional membrane and cytoskeletal organization at the membrane-cytoskeletal interface of stretch-sensitive structures, and they implicate integrin signaling through a CAP/Vinculin protein complex in stretch-sensitive organ assembly and function.

Longitudinal axon fascicles within the Drosophila embryonic CNS provide connections between body segments and are required for coordinated neural signaling along the anterior-posterior axis. We show here that establishment of select CNS longitudinal tracts and formation of precise mechanosensory afferent innervation to the same CNS region are coordinately regulated by the secreted semaphorins Sema-2a and Sema-2b. Both Sema-2a and Sema-2b utilize the same neuronal receptor, plexin B (PlexB), but serve distinct guidance functions. Localized Sema-2b attraction promotes the initial assembly of a subset of CNS longitudinal projections and subsequent targeting of chordotonal sensory afferent axons to these same longitudinal connectives, whereas broader Sema-2a repulsion serves to prevent aberrant innervation. In the absence of Sema-2b or PlexB, chordotonal afferent connectivity within the CNS is severely disrupted, resulting in specific larval behavioral deficits. These results reveal that distinct semaphorin-mediated guidance functions converge at PlexB and are critical for functional neural circuit assembly., (Copyright © 2011 Elsevier Inc. All rights reserved.)

During the development of neural circuitry, neurons of different kinds establish specific synaptic connections by selecting appropriate targets from large numbers of alternatives. The range of alternative targets is reduced by well organised patterns of growth, termination, and branching that deliver the terminals of appropriate pre- and postsynaptic partners to restricted volumes of the developing nervous system. We use the axons of embryonic Drosophila sensory neurons as a model system in which to study the way in which growing neurons are guided to terminate in specific volumes of the developing nervous system. The mediolateral positions of sensory arbors are controlled by the response of Robo receptors to a Slit gradient. Here we make a genetic analysis of factors regulating position in the dorso-ventral axis. We find that dorso-ventral layers of neuropile contain different levels and combinations of Semaphorins. We demonstrate the existence of a central to dorsal and central to ventral gradient of Sema 2a, perpendicular to the Slit gradient. We show that a combination of Plexin A (Plex A) and Plexin B (Plex B) receptors specifies the ventral projection of sensory neurons by responding to high concentrations of Semaphorin 1a (Sema 1a) and Semaphorin 2a (Sema 2a). Together our findings support the idea that axons are delivered to particular regions of the neuropile by their responses to systems of positional cues in each dimension., Competing Interests: The authors have declared that no competing interests exist.

Drosophila sensory neurons form distinctive terminal branch patterns in the developing neuropile of the embryonic central nervous system. In this paper we make a genetic analysis of factors regulating arbor position. We show that mediolateral position is determined in a binary fashion by expression (chordotonal neurons) or nonexpression (multidendritic neurons) of the Robo3 receptor for the midline repellent Slit. Robo3 expression is one of a suite of chordotonal neuron properties that depend on expression of the proneural gene atonal. Different features of terminal branches are separately regulated: an arbor can be shifted mediolaterally without affecting its dorsoventral location, and the distinctive remodeling of one arbor continues as normal despite this arbor shifting to an abnormal position in the neuropile.