Most land animals normally walk forward but switch to backward walking upon sensing an obstacle or danger in the path ahead. A change in walking direction is likely to be triggered by descending "command" neurons from the brain that act upon local motor circuits to alter the timing of leg muscle activation. Here we identify descending neurons for backward walking in Drosophila--the MDN neurons. MDN activity is required for flies to walk backward when they encounter an impassable barrier and is sufficient to trigger backward walking under conditions in which flies would otherwise walk forward. We also identify ascending neurons, MAN, that promote persistent backward walking, possibly by inhibiting forward walking. These findings provide an initial glimpse into the circuits and logic that control walking direction in Drosophila.

By using a combination of dye injections, clonal labeling, and molecular markers, we have reconstructed the axonal connections between brain and ventral nerve cord of the first-instar Drosophila larva. Out of the approximately 1,400 neurons that form the early larval brain hemisphere, less than 50 cells have axons descending into the ventral nerve cord. Descending neurons fall into four topologically defined clusters located in the anteromedial, anterolateral, dorsal, and basoposterior brain, respectively. The anterolateral cluster represents a lineage derived from a single neuroblast. Terminations of descending neurons are almost exclusively found in the anterior part of the ventral nerve cord, represented by the gnathal and thoracic neuromeres. This region also contains small numbers of neurons with axons ascending into the brain. Terminals of the ascending axons are found in the same basal brain regions that also contain descending neurons. We have mapped ascending and descending axons to the previously described scaffold of longitudinal fiber tracts that interconnect different neuromeres of the ventral nerve cord and the brain. This work provides a structural framework for functional and genetic studies addressing the control of Drosophila larval behavior by brain circuits.

It is often assumed that highly-branched neuronal structures perform compartmentalized computations. However, previously we showed that the Gastric Mill (GM) neuron in the crustacean stomatogastric ganglion (STG) operates like a single electrotonic compartment, despite having thousands of branch points and total cable length >10 mm (Otopalik et al., 2017a; 2017b). Here we show that compact electrotonic architecture is generalizable to other STG neuron types, and that these neurons present direction-insensitive, linear voltage integration, suggesting they pool synaptic inputs across their neuronal structures. We also show, using simulations of 720 cable models spanning a broad range of geometries and passive properties, that compact electrotonus, linear integration, and directional insensitivity in STG neurons arise from their neurite geometries (diameters tapering from 10-20 µm to \uline< 2 µm at their terminal tips). A broad parameter search reveals multiple morphological and biophysical solutions for achieving different degrees of passive electrotonic decrement and computational strategies in the absence of active properties.

Animals consolidate some, but not all, learning experiences into long-term memory. Across the animal kingdom, sleep has been found to have a beneficial effect on the consolidation of recently formed memories into long-term storage. However, the underlying mechanisms of sleep dependent memory consolidation are poorly understood. Here, we show that consolidation of courtship long-term memory in is mediated by reactivation during sleep of dopaminergic neurons that were earlier involved in memory acquisition. We identify specific fan-shaped body neurons that induce sleep after the learning experience and activate dopaminergic neurons for memory consolidation. Thus, we provide a direct link between sleep, neuronal reactivation of dopaminergic neurons, and memory consolidation.

The mouse has become an important model for understanding the neural basis of visual perception. Although it has long been known that mouse lens transmits ultraviolet (UV) light and mouse opsins have absorption in the UV band, little is known about how UV visual information is processed in the mouse brain. Using a custom UV stimulation system and in vivo calcium imaging, we characterized the feature selectivity of layer 2/3 neurons in mouse primary visual cortex (V1). In adult mice, a comparable percentage of the neuronal population responds to UV and visible stimuli, with similar pattern selectivity and receptive field properties. In young mice, the orientation selectivity for UV stimuli increased steadily during development, but not direction selectivity. Our results suggest that, by expanding the spectral window through which the mouse can acquire visual information, UV sensitivity provides an important component for mouse vision.

We explore the hypothesis that the neuronal spike generation mechanism is an analog-to-digital converter, which rectifies low-pass filtered summed synaptic currents and encodes them into spike trains linearly decodable in post-synaptic neurons. To digitally encode an analog current waveform, the sampling rate of the spike generation mechanism must exceed its Nyquist rate. Such oversampling is consistent with the experimental observation that the precision of the spike-generation mechanism is an order of magnitude greater than the cut-off frequency of dendritic low-pass filtering. To achieve additional reduction in the error of analog-to-digital conversion, electrical engineers rely on noise-shaping. If noise-shaping were used in neurons, it would introduce correlations in spike timing to reduce low-frequency (up to Nyquist) transmission error at the cost of high-frequency one (from Nyquist to sampling rate). Using experimental data from three different classes of neurons, we demonstrate that biological neurons utilize noise-shaping. We also argue that rectification by the spike-generation mechanism may improve energy efficiency and carry out de-noising. Finally, the zoo of ion channels in neurons may be viewed as a set of predictors, various subsets of which are activated depending on the statistics of the input current.

Human mesenchymal stem cells (MSCs) are good candidates for brain cell replacement strategies and have already been used as adjuvant treatments in neurological disorders. MSCs can be obtained from many different sources, and the present study compares the potential of neuronal transdifferentiation in MSCs from adult and neonatal sources (Wharton's jelly (WhJ), dental pulp (DP), periodontal ligament (PDL), gingival tissue (GT), dermis (SK), placenta (PLAC), and umbilical cord blood (UCB)) with a protocol previously tested in bone marrow- (BM-) MSCs consisting of a cocktail of six small molecules: I-BET151, CHIR99021, forskolin, RepSox, Y-27632, and dbcAMP (ICFRYA). Neuronal morphology and the presence of cells positive for neuronal markers (TUJ1 and MAP2) were considered attributes of neuronal induction. The ICFRYA cocktail did not induce neuronal features in WhJ-MSCs, and these features were only partial in the MSCs from dental tissues, SK-MSCs, and PLAC-MSCs. The best response was found in UCB-MSCs, which was comparable to the response of BM-MSCs. The addition of neurotrophic factors to the ICFRYA cocktail significantly increased the number of cells with complex neuron-like morphology and increased the number of cells positive for mature neuronal markers in BM- and UCB-MSCs. The neuronal cells generated from UCB-MSCs and BM-MSCs showed increased reactivity of the neuronal genes TUJ1, MAP2, NF-H, NCAM, ND1, TAU, ENO2, GABA, and NeuN as well as down- and upregulation of MSC and neuronal genes, respectively. The present study showed marked differences between the MSCs from different sources in response to the transdifferentiation protocol used here. These results may contribute to identifying the best source of MSCs for potential cell replacement therapies.

During and vertebrate brain development, the conserved transcription factor Prospero/Prox1 is an important regulator of the transition between proliferation and differentiation. Prospero level is low in neural stem cells and their immediate progeny, but is upregulated in larval neurons and it is unknown how this process is controlled. Here, we use single molecule fluorescent hybridisation to show that larval neurons selectively transcribe a long mRNA isoform containing a 15 kb 3' untranslated region, which is bound in the brain by the conserved RNA-binding protein Syncrip/hnRNPQ. Syncrip binding increases the mRNA stability of the long isoform, which allows an upregulation of Prospero protein production. Adult flies selectively lacking the long isoform show abnormal behaviour that could result from impaired locomotor or neurological activity. Our findings highlight a regulatory strategy involving alternative polyadenylation followed by differential post-transcriptional regulation.

Connections between neurons can be mapped by acquiring and analyzing electron microscopic (EM) brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative, yet inadequate for understanding brain function more globally. Here, we present the first neuronal wiring diagram of a whole adult brain, containing 5×10 chemical synapses between ∼130,000 neurons reconstructed from a female . The resource also incorporates annotations of cell classes and types, nerves, hemilineages, and predictions of neurotransmitter identities. Data products are available by download, programmatic access, and interactive browsing and made interoperable with other fly data resources. We show how to derive a projectome, a map of projections between regions, from the connectome. We demonstrate the tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine, and descending neurons), across both hemispheres, and between the central brain and the optic lobes. Tracing from a subset of photoreceptors all the way to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviors. The technologies and open ecosystem of the FlyWire Consortium set the stage for future large-scale connectome projects in other species.

Background

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

Results

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

Conclusions

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