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.

Homeostasis is a biological principle for regulation of essential physiological parameters within a set range. Behavioural responses due to deviation from homeostasis are critical for survival, but motivational processes engaged by physiological need states are incompletely understood. We examined motivational characteristics of two separate neuron populations that regulate energy and fluid homeostasis by using cell-type-specific activity manipulations in mice. We found that starvation-sensitive AGRP neurons exhibit properties consistent with a negative-valence teaching signal. Mice avoided activation of AGRP neurons, indicating that AGRP neuron activity has negative valence. AGRP neuron inhibition conditioned preference for flavours and places. Correspondingly, deep-brain calcium imaging revealed that AGRP neuron activity rapidly reduced in response to food-related cues. Complementary experiments activating thirst-promoting neurons also conditioned avoidance. Therefore, these need-sensing neurons condition preference for environmental cues associated with nutrient or water ingestion, which is learned through reduction of negative-valence signals during restoration of homeostasis.

In insects, the shedding of the old cuticle at the end of a molt involves a stereotyped sequence of distinct behaviors. Our studies on the isolated nervous system of Manduca sexta show that the peptides ecdysis-triggering hormone (ETH) and crustacean cardioactive peptide (CCAP) elicit the first two motor behaviors, the pre-ecdysis and ecdysis behaviors, respectively. Exposing isolated abdominal ganglia to ETH resulted in the generation of sustained pre-ecdysis bursts. By contrast, exposing the entire isolated CNS to ETH resulted in the sequential appearance of pre-ecdysis and ecdysis motor outputs. Previous research has shown that ETH activates neurons within the brain that then release eclosion hormone within the CNS. The latter elevates cGMP levels within and increases the excitability of a group of neurons containing CCAP. In our experiments, the ETH-induced onset of ecdysis bursts was always associated with a rise in intracellular cGMP within these CCAP neurons. We also found that CCAP immunoreactivity decreases centrally during normal ecdysis. Isolated, desheathed abdominal ganglia responded to CCAP by generating rhythmical ecdysis bursts. These ecdysis motor bursts persisted as long as CCAP was present and could be reinduced by successive application of the peptide. CCAP exposure also actively terminated pre-ecdysis bursts from the abdominal CNS, even in the continued presence of ETH. Thus, the sequential performance of the two behaviors arises from one modulator activating the first behavior and also initiating the release of the second modulator. The second modulator then turns off the first behavior while activating the second.

In insects, the neuropeptide eclosion hormone (EH) acts on the CNS to evoke the stereotyped behaviors that cause ecdysis, the shedding of the cuticle at the end of each molt. Concomitantly, EH induces an increase in cyclic GMP (cGMP). Using antibodies against this second messenger, we show that this increase is confined to a network of 50 peptidergic neurons distributed throughout the CNS. Increases appeared 30 min after EH treatment, spread rapidly throughout these neurons, and were extremely long lived. We show that this response is synaptically driven, and does not involve the soluble, nitric oxide (NO)-activated, guanylate cyclase. Stereotyped variations in the duration of the cGMP response among neurons suggest a role in coordinating responses having different latencies and durations.

Measuring the dynamics of neural processing across time scales requires following the spiking of thousands of individual neurons over milliseconds and months. To address this need, we introduce the Neuropixels 2.0 probe together with newly designed analysis algorithms. The probe has more than 5000 sites and is miniaturized to facilitate chronic implants in small mammals and recording during unrestrained behavior. High-quality recordings over long time scales were reliably obtained in mice and rats in six laboratories. Improved site density and arrangement combined with newly created data processing methods enable automatic post hoc correction for brain movements, allowing recording from the same neurons for more than 2 months. These probes and algorithms enable stable recordings from thousands of sites during free behavior, even in small animals such as mice.

Although CMOS fabrication has enabled a quick evolution in the design of high-density neural probes and neural-recording chips, the scaling and miniaturization of the complete data-acquisition systems has happened at a slower pace. This is mainly due to the complexity and the many requirements that change depending on the specific experimental settings. In essence, the fundamental challenge of a neural-recording system is getting the signals describing the largest possible set of neurons out of the brain and down to data storage for analysis. This requires a complete system optimization that considers the physical, electrical, thermal and signal-processing requirements, while accounting for available technology, manufacturing constraints and budget. Here we present a scalable and open-standards-based open-source data-acquisition system capable of recording from over 10,000 channels of raw neural data simultaneously. The components and their interfaces have been optimized to ensure robustness and minimum invasiveness in small-rodent electrophysiology.